Identification of new molecular mechanisms potentially - TI Pharma

Identification of new molecular mechanisms potentially involved in the

development of Parkinson’s disease

The research described in this thesis was conducted in the Laboratory for Neu-roregeneration at the Netherlands Institute for Neuroscience, an Institute of the Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands. The research was supported by the Top Institute Pharma, Leiden, The Nether-lands, project T5-207, the International Parkinson Fonds and the Netherlands In-stitute for Neuroscience.

Thesis Committee:Dr. A. Van Dam Prof. Dr. E.M. HolProf. Dr. P. HeutingProf. Dr. J.J. van HiltenProf. Dr. M. P. SmidtProf. Dr. A.B. Smit

About the cover:Parkinson’s disease is a neurodegenerative disease where, according to the dy-ing back hypothesis, the dopaminergic neurons of the Substantia Nigra (SN) first lose their axonal connectivity with the striatum and consequently degen-erate. The sprouts symbolize these dopaminergic neurons ‘growing out’ of the mouse SN (the red area). Normally, these neurons contain brown melanin pig-ment (brown seeds) and project their long axons (stems) to the striatum where they connect through their synapses (leaves) with the striatal targets. In PD, these axons lose their synaptic connectivity, retract their axons and lose their brown pigmentation as is illustrated by the ‘degenerated’ sprouts. It is expected that through identification of molecular signals that induce axon retraction and degeneration we would be able to alter this process and stop the progression of the disease. There may even be a possibility to induce re-growth of the retracted axons so they can ‘sprout’ back into the striatum and reconnect with their des-tined targets.

Publication of this thesis was financially supported by:Netherlands Institute for Neuroscience, the Vrije Universiteit and Lundbeck B.V.

Cover design: Joanna A. KoreckaLayout: Joanna A. Korecka & Koen BossersPrinted by: Proefschriftmaken.nl || Uitgeverij BOXPress Published by: Uitgeverij BOXPress, Oisterwijk

ISBN: 9789088915451Copyright © 2012 by Joanna A. Korecka. All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without prior permission of the author.

VRIJE UNIVERSITEIT

Identification of new molecular mechanisms potentially involved in the development of

Parkinson’s disease

ACADEMISCH PROEFSCHRIFT

ter verkrijging van de graad Doctor aande Vrije Universiteit Amsterdam,

op gezag van de rector magnificusprof.dr. L.M. Bouter,

in het openbaar te verdedigenten overstaan van de promotiecommissie

van de Faculteit der Aard- en Levenswetenschappenop maandag 21 januari 2013 om 13.45 uur

in de aula van de universiteit,De Boelelaan 1105

door

Joanna Aleksandra Korecka

geboren te Gdańsk, Polen

promotoren: prof.dr. J. Verhaagen prof.dr. D.F. Swaabcopromotoren: dr. R.E. van Kesteren dr. K. Bossers

Dla mojej wspaniałej rodzinki

Contents Scope & Outline 9

Chapter 1 Cell replacement and gene-therapy strategies for 19 Parkinson’s and Alzheimer’s disease J.A. Korecka, J. Verhaagen and E. Hol Regen Med. 2007 Jul; 2(4):425-46.

Chapter 2 Gene expression profiling and Parkinson’s disease: 57 target selection and mRNA and protein localization in human Substantia Nigra J.A. Korecka, U.A. Unmehopa, R. Balesar, J. Anink, C. Vlaskamp, G. Meerhoff, D.F. Swaab, K. Bossers, J. Verhaagen

Chapter 3 Phenotypic characterization of retinoic acid differentiated 91 SH-SY5Y cells by transcriptional profiling J.A. Korecka, R.E. van Kesteren, E. Blaas, S.O.Spitzer, A.B. Smit, D.F. Swaab, J. Verhaagen, K. Bossers Submitted

Chapter 4 High-content cellular screening of genes dysregulated 145 in Parkinson’s disease identifies regulators of cell viability, mitochondrial activity and axon growth J.A. Korecka, E. Blaas, R.E. van Kesteren, U.A. Unmehopa, R. Balesar, D.F. Swaab, A.B. Smit, K. Bossers, J. Verhaagen Manuscript in preparation

Chapter 5 Modeling early Parkinson’s disease pathology with 181 chronic low dose MPTP treatment J.A. Korecka, R. Eggers, D.F. Swaab, K. Bossers, J. Verhaagen Manuscript accepted to be published in RNN

Chapter 6 Comparison of AAV serotypes for gene delivery to 199 dopaminergic neurons in the substantia nigra J.A. Korecka, M. Schouten, R. Eggers, A. Ulusoy, D.F. Swaab, K. Bossers, J. Verhaagen Viral Gene Therapy 2011, July; Ch: 10: 205-24, Intech

Chapter 7 Repulsive guidance molecule a (RGMa) induces 221 degeneration of dopaminergic neurons in the mouse Substantia Nigra: implications for Parkinson’s disease J.A. Korecka, R. Eggers, N. Ras-Verloop, R.J. Pasterkamp, D.F. Swaab, A.B. Smit, R.E. Van Kesteren, K. Bossers, J. Verhaagen

Chapter 8 Summary and general discussion 243 J.A. Korecka, K. Bossers, R.E van Kesteren, D.F. Swaab, J. Verhaagen

Reference list 259

Nederlandse samenvatting 278

Acknowledgements 282

Publications 286

Curriculum Vitae 287

Scope & Outline

Joanna A. Korecka

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Scope

Parkinson’s disease (PD) is a progressive neurodegenerative disorder. Ac-cording to the Parkinson ’s Disease Foundation, 7 to 10 million people suffer from PD worldwide. Approximately 60,000 new cases are diagnosed each year in the US alone (www.pdf.org). In the Netherlands, more than 50,000 patients have been diagnosed with the disease (www. parkinsonfonds.nl). The combined direct and indirect costs of PD in the US, including treatment, social security payments and loss of income are about $25 billion dollars per year. Only 5% of the PD cases are familial, while the rest of the patients suffer from a sporadic form of the disease (Dauer and Przedborski, 2003). The principal risk factor for PD is age, with incidence rising significantly after age 50 (Driver et al., 2009). Despite extensive research efforts worldwide, the causes of sporadic PD remain unknown until this day. The current treatments, both pharmacological and sur-gical, diminish the symptoms of both familial and sporadic forms of the disease, and therefore temporarily improve the quality of life of the patients(reviewed in Olanow et al., 2009). As yet, no genuine regenerative treatments that stop the progression or cure the disease are available.

Neuropathological changes in sporadic PD are of a progressive nature and involve multiple neuronal systems. Lewy body formation and neurodegeneration start in the brain stem and olfactory bulb, ascending to the Substantia Nigra pars compacta (SN) nucleus and further progressing towards the neocortex, reaching sensory and prefrontal areas of the brain (Braak et al., 2003). Selective loss of do-paminergic (DAergic) neurons in the SN as well as extensive gliosis in that area are the best known neuropathological characteristics of PD, directly accounting for the motor symptoms. The familial forms of the disease are caused by muta-tions in genes such as SNCA, PARK2, DJ-1, PINK1, LRRK2 and PARK9 (reviewed in Hardy et al., 2006; Bonifati, 2007; Hardy, 2010). These genetic mutations helped investigators to identify a number of biological processes that potentially con-tribute to the development of familial PD. However, for sporadic PD the specific molecular alterations leading to the typical neuropathological changes in the SN still need to be elucidated. The etiology of the disease appears to be multifactori-al, involving both biological and environmental components (reviewed in Dauer and Przedborski, 2003; Maguire-Zeiss et al., 2008; Olanow et al., 2009). Devel-oping regenerative treatment requires more research into the basic cellular and molecular changes that occur in the brain of PD patients.

In the last years, in particular since the completion of the human genome project (Lander et al., 2001; Venter et al., 2001), a number of new “high-through-put” approaches have been used to further dissect the molecular changes in PD at a scale that was previously unthinkable. These approaches include large scale analysis of single nucleotide polymorphisms (SNP), genome-wide gene expres-sion analysis using micro arrays, and more recently “deep” sequencing, and pro-teomics approaches (reviewed in Tsuji, 2010; Hardy, 2010; Lewis and Cookson,

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2011; Greene, 2012). These techniques revealed molecular changes in multiple brain regions and in blood samples from PD patients.

The transition from studies of single ‘candidate’ genes to a broader unbi-ased analysis of multiple molecular changes in human postmortem tissue has re-sulted in the identification of new “molecular signatures” of PD. Genome-wide SNP analysis has identified several potential susceptibility genes [UCHL1 (Le-roy et al., 1998), SEMA5A (Maraganore et al., 2005), SNCA (Mizuta et al., 2006), MAPT (Simon-Sanchez et al., 2009)] for PD. Genome-wide gene expression profil-ing revealed the dysregulation of numerous new genes involved in processes that had previously been implicated in the disease, including genes involved in the ubiquitin/proteasome system, heat shock regulation, iron transport, chaperone activity, oxidative stress regulation, vesicular transport and neurotransmission, and most recently miRNA modulation of mitochondrial function. Importantly, microarray studies also revealed changes in the expression of genes implicated in pathways not previously linked to the disease, including extracellular matrix signaling, cell adhesion, the polyamine signaling pathway and axon guidance (re-viewed in Lewis and Cookson, 2011; Greene, 2012).

We have studied genome-wide alterations in gene expression in the SN of PD patients using Agilent microarrays (Bossers et al., 2009). As we were particu-larly interested in transcriptional alterations during the early stages of DAergic degeneration, we analyzed those parts of the PD SN that were relatively spared. This approach allows the identification of transcriptional changes in neurons that are potentially compromised by the disease but have not yet degenerated. We found 287 genes significantly differentially expressed in the PD SN. These expression changes may either be causal to the development and/or progression of sporadic PD, or may be the consequence of the disease process.

The primary challenge of genome-wide gene and protein expression stud-ies is to translate the alternations in gene and protein expression into concrete biological mechanisms that underlie the degeneration of DAergic neurons in the SN of PD patients. Extracting this information from lists of target genes and pro-teins is essential to advance our understanding of the mechanisms underlying the disease.

The overall objective of the work described in this thesis was to face this challenge and to investigate the potential role of a relatively large set of genes in the degenerative process of DAergic neurons that occurs in PD. These genes were selected from the total group of 287 genes identified by microarray based on bio-informatics and literature study. Next, we used high-content cellular screens to examine the role of these target genes in DAergic neuron viability, neurite out-growth and mitochondrial activity. This integrative approach allowed us to se-lect a small number of targets for functional study in vivo. Overexpression of one of these targets, repulsive guidance molecule A (RGMA), in the SN of mice ap-peared to be sufficient to induce degeneration of DAergic neurons. Figure 1 pro-

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vides an outline of the steps that together comprise the experimental strategy that was employed in this thesis.

Outline

Chapter 1 reviews recent cell replacement and gene therapy studies for PD and AD. Unlike the temporary symptomatic relief of current pharmacologi-cal (dopamine replacement) and neurosurgical treatments (deep brain stimula-tion) for PD, cell replacement and gene therapy are novel approaches that aim to either replace the damaged cells or prevent neuronal degeneration by stimulat-ing regenerative and neuro-protective mechanisms in the affected tissue. Gene therapy for neurturin, a protective trophic factor for DAergic neurons, recently entered a phase II clinical trial. This demonstrates that this cutting edge thera-peutic approach, based on adeno-associated viral vectors (AAV) to deliver the therapeutic gene, is well-tolerated and safe in human subjects (Marks, Jr. et al., 2010).

Chapter 2 describes the selection of 79 primary target genes from the total set of 287 dysregulated genes in the PD SN. These genes were selected, because based on bioinformatics and literature, they play a role in: 1) cell death- degen-eration of neurons is a cardinal pathological feature in the SN of PD patients, 2) axon guidance, neurotrophic support and synaptic transmission - biological pro-cesses recently implicated in the development of PD, and 3) mitochondrial gene expression and cellular metabolism - interrelated processes clearly disturbed in PD. Cellular localization studies of 34 target genes using in situ hybridization and immunohistochemistry revealed that these genes are almost exclusively ex-pressed in neurons in the SN, and not in reactive astrocytes or activated microg-lia.

The aim of chapter 3 was to establish an appropriate in vitro cell model to study target gene function. A good cell model to elucidate gene function in the context of PD should: 1) contain the main cellular and molecular properties that are characteristic of DA neurons, 2) be sensitive to environmental factors that are known to contribute to PD, and 3) be suitable for cellular screening, which allows examination of the function of many genes, proteins and specific com-pounds in a high-content manner. Using genome-wide transcriptional profiling combined with gene ontology and pathway analysis we characterized the mo-lecular phenotype of SH-SY5Y cells after retinoic acid (RA) differentiation. First-ly, we found that RA induces the differentiation of SH-SY5Y cells and enhances their DAergic characteristics, while suppressing other transmitter phenotypes. Secondly, RA differentiated SH-SY5Y do indeed express 73% of our PD genes of interest. Finally, treatment of these differentiated cells with 0.01mM 1-methyl-4-phenylpyridinium (MPP(+)) reduces mitochondrial activity similar to DAergic neurons in vivo. Thus, RA differentiated SH-SY5Y cells can be used to model the effect of both environmental and genetic factors in the PD-associated neurode-

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Figure 1. Schematic representation of the thesis outline. The project started with the identifica-tion of 287 genes differentially regulated in the human SN PD tissue compared to the matched controls (step 1). Based on gene ontology and Ingenuity Pathway Analysis, 4 biological func-tions have been identified to be altered in the PD SN tissue (step 2). From these functions, we have selected 79 primary genes of interest- the target genes (step 3), from which we have suc-cessfully localized 33 in human SN neurons (step 4). This allowed us to further develop appropri-ate PD-related in vitro and in vivo models (step 5), where the functional role of these genes could be tested. We performed high throughput siRNA knockdown screen of 62 genes and high content overexpression screen of 14 genes to explore the biological relevance of the investigated genes in PD related cellular function (step 6). Finally one gene was selected for in vivo validation, where its role in inducing cellular death of DAergic neurons in the mouse SN became clear (step 7). The chapter numbers describing the given steps are indicated in the bottom right corner of each box. Abbreviations: PD- Parkinson’s disease, SN- Substantia nigra pars compacta, DAergic- dopami-nergic, RA- retinoic acid, MPP(+)-1-methyl-4-phenylpyridinium, AAV- adeno-associated virus, MPTP- 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine, LV- lenti virus, RGMA- repulsive guidance molecule A.

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generative process. We therefore used these cells in functional gene screening assays.

Chapter 4 describes the results of high content screening to determine the functional effects of 62 target genes in SH-SY5Y cells in the absence or presence of MPP(+). siRNA-mediated knockdown of 62 genes and LV-overexpression of 14 genes demonstrated that 12 genes significantly affected various parameters including cellular viability, mitochondrial activity, and neurite outgrowth. Four genes were selected for further validation based on 1) being upregulated in PD SN as illustrated by the microarray study, and 2) induced dramatic changes in two or more of the measured cellular functional readouts. Overexpression of RGMA decreased neurite count, while its knockdown induced apoptosis. Over-expression of the transcription regulator of cellular survival prothymosin alpha (PTMA), neuron specific gene silencing transcription regulator carboxyl-termi-nal domain small phosphatase 1 (CTDSP1) and a cytoplasmic phosphoprotein involved in synaptic plasticity (WWC1), all decreased both cellular viability and neurite outgrowth.

In chapter 5 we describe the development of a mouse model that mimics the early stage of PD based on a chronic low dose MPTP treatment (15mg/kg) twice a week for 5 weeks. This treatment induces dopamine dependent behav-ioral deficit accompanied by a loss of tyrosine hydroxylase (TH) positive nigros-triatal axon terminals in the striatum, and gliosis, but no cellular death in the SN. This model bears a striking resemblance to the cellular changes that have led to the so-called ‘dying back’ hypothesis of PD, and provides an interesting window of opportunity to study the mechanisms that underlie early neurodegenerative events that may initiate the cellular death of DAergic neurons.

In chapter 6 targeted viral vector-mediated gene transfer is tested as means to study the function of target genes in murine DAergic neurons in vivo. The ability of different AAV vector serotypes to drive reporter gene GFP expres-sion in DAergic neurons in the mouse SN was tested, and the performance of two different promoters (the classical, ubiquitously active CMV promoter and the neuron specific synapsin promoter) were evaluated. Transgene expression by AAV serotype 7 harboring the synapsin promoter resulted in the most efficient transduction of TH positive neurons in the mouse SN and induced the highest GFP expression in nigro-striatal axonal projections. This vector was therefore used in chapter 7 to study the role of RGMA in vivo in the mouse SN.

The cellular screens in chapter 4 resulted in the identification of a small set of genes that affected mitochondrial activity, neurite growth or viability of DAe-rgic cells. In chapter 7 we show that AAV7-mediated overexpression of RGMA in the mouse SN results in behavioral abnormalities that are typical for loss of striatal DA input, a gradual degeneration of DAergic neurons, and micro- and as-troglial activation in the SN. These data suggest that the upregulation of RGMA in human SN neurons in PD may be causally involved in PD-associated motor symp-toms and the degeneration of SN DAergic neurons.

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Chapter 8 provides a general discussion of the most striking results pre-sented in this thesis. We speculate on the mechanism of RGMA signaling and its role in the degeneration of DAergic neuron, but also propose other possible genes identified in the in vitro screen to be equally important in the context of PD, such as PTMA, CTDSP1 and WWC1. We conclude this thesis with future prospects of our research and its contribution to the development of new therapeutic strate-gies for PD.

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CHAPTER 1

Cell replacement and gene-therapy strategies for

Parkinson’s and Alzheimer’s disease

J.A. Korecka1, J. Verhaagen1 & E. Hol2

Regen Med. 2007 Jul; 2(4):425-46

1 Department of Neuroregeneration, Netherlands Institute for Neuroscience, An Institute of the Royal Netherlands Academy of Arts and Sciences, Meibergdreef 47, 1105BA,

Amsterdam, The Netherlands2 Department of Astrocyte Biology and Neurodegeneration, Netherlands Institute for Neuroscience,

An Institute of the Royal Netherlands Academy of Arts and Sciences, Meibergdreef 47, 1105BA, Amsterdam, The Netherlands

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Abstract

Parkinson’s disease and Alzheimer’s disease are the most common neuro-degenerative diseases in the elderly population. Given that age is the most impor-tant risk factor in these diseases, the number of patients is expected to rise dra-matically in the coming years. Therefore, an effective therapy for these diseases is highly sought. Current treatment brings only temporary symptomatic relief and does not result in halting the progression of these diseases. The increasing knowledge on the molecular mechanisms that underlie these diseases enables the design of novel therapies, targeted at degenerating neurons by creating an optimal regenerative cellular environment. Here, we review the progress made in the field of cell-replacement and gene-therapy strategies. New developments in the application of embryonic stem cells and adult neuronal progenitors are discussed. We also discuss the use of genetically engineered cells in neuronal rescuing strategies that have recently advanced into the clinic. The first trials for the treatment of Alzheimer’s disease and Parkinson’s disease with this approach are ongoing.

GENER A L IN TRODUCTION

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Introduction

Parkinson’s disease (PD) and Alzheimer’s disease (AD) are the two most common neurodegenerative diseases associated with age. PD is primarily a movement disorder and at least 1% of people suffer from it by age 70 years [1]. AD is characterized by progressive memory loss and is the most common cause of dementia in the elderly. Approximately 7% of those aged over 65 years and approximately 40% of those aged over 80 years are affected by this disease [2]. Owing to aging of the population worldwide and lack of a cure, the number of PD and AD cases will grow substantially the next two to three decades [3–5]. Therapies used today are only relief based and are unable to halt the progression of PD and AD. Therefore, there is a great need to find new effective regenerative therapeutic strategies that can stop the development and progression of these neurodegenerative diseases and that will improve a patient’s quality of life.

Over the past 20 years, a substantial progression in our understanding of the molecular mechanisms underlying PD and AD has been achieved, enabling the development of novel therapeutic strategies to cure these diseases. The main hallmarks of both disorders is neuronal degeneration and neuronal death; there-fore, cell replacement strategies are currently regarded as a potential therapy by either transplanting embryonic stem cells or neural progenitors [6]. In addition, due to the progress in gene-manipulation strategies, gene therapy also becomes an attractive approach, where cells engineered to express neurotrophic factors have been transplanted with the aim to promote neuronal survival and rescue neuronal function [7,8].

In this review, we will critically discuss emerging cell replacement and gene therapies for PD and AD and the current status of applying these experimental therapies in clinical trials.


Pathogenesis

PD is a progressive disease and clinical symptoms, such as rest tremor, ri-gidity, balance impairment and slowness of movement, only manifest in the late stages. Braak and colleagues described in detail six stages of the disease based on the pathological hallmarks, that is, α-synuclein build up in the Lewy bodies (LB) and Lewy neurites (LN) and degeneration of the dopaminergic (DAergic) neurons in the substantia nigra (SN) [9]. The loss of DA neurons in the SN and the loss of DAergic innervations in the striatum are the cause of movement disabili-ties described in PD (Figure 1). Apart from these well-known motor disabilities, additional symptoms present themselves, such as sleep disruption, depression, fatigue, constipation and anxiety.

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The cause of PD in the majority of the patients suffering from the nonher-iditary form of the disease is as yet unknown. A role of environmental factors in the development of the disorder has been suggested. In the early twentieth century, it has been observed that a viral infection can cause nigral degeneration [10].

Additionally, it has been shown that toxic substances, such as 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), rotenone, paraquat, maneb and ep-oxomicin, can induce Parkinsonism [1]. Some of these substances (e.g., MPTP and epoxomicin) are used today in research to induce PD-like symptoms in animals, thus generating a model for the disease.

In the past 10 years, genetic mutations were identified that cause or are involved in PD. Single point mutations in the α-synuclein, parkin, DJ-1, PTEN-in-duced putative kinase 1 (PINK-1), dardarin (LRRK2) [1] and ubiquitin carboxyl-terminal esterase L1 (UCH-L1) [11] genes have been shown to be involved in the pathogenesis of PD [12]. The discovery of these genetic factors revealed that an impaired energy metabolism, a deficient ubiquitin– proteasome pathway and an inhibition of neurotransmitter release are likely to be involved in the pathogen-esis of the disease.

Figure 1. Dopaminergic projections and pathology of Parkinson’s disease. (A) Dopaminergic neurons project from the substantia nigra to the caudate nucleus and putamen. (B) Haema-toxilin staining of the substantia nigra of a neurological control and a Parkinson’s patient. A clear decrease in the number of naturally melanin-pigmented dopaminergic neurons (brown) is observed in the Parkinson’s patient (Netherlands Brain Bank [NBB] 02–003) compared with the control tissue (NBB 01–140). Scale bars represent 0.5mm (C) Lewy body (brown) pathology in the substantia nigra of a Parkinson’s patient (NBB 01–140) stained with an α–synuclein antibody. Scale bar represents 50µm. Reproduced from Regenerative Medicine, July 2007, Vol. 2, No. 4, Pages 425-446 with permission of Future Medicine Ltd.


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It is expected that, in the non-monogenic forms of PD, genetic factors are important as well, since many PD patients are known to have an affected family member [13]. Genes such as tau, semaphoring 5A, α-synuclein, fibroblast growth factor 20 and nuclear receptor-related 1 (Nurr1) are all implicated in the devel-opment of PD [1,14]. Interestingly, different variants of semaphorin 5A were asso-ciated with PD in a Taiwanese population. However, this could not be confirmed in a Finish population study, prompting a debate regarding this gene and its role in PD development [15]. Current genome-wide screening studies will contribute to our knowledge of the molecular mechanisms involved in PD pathogenesis.

Treatment

All current PD therapies focus on restoring the DA levels by either the oral administration of the DA precursor levodopa (L-DOPA), which supplements the low level of endogenous DA, or inhibition of the breakdown of endogenous DA by treatment with the monoamine oxidase type B (MAO-B) inhibitor, selegiline. DA agonists are also used to directly stimulate the DA receptors [1,16]. Unfortu-nately, these therapies are all symptomatic treatments and do not prevent the progression of the DAergic neuronal degeneration and, more importantly, are not capable of curing PD. In the later stages of the disease,

L-DOPA becomes ineffective or, even worse, causes severe side effects, such as the development of dyskinesias (fragmented or incomplete movements) and the prolongation of the ‘off ’ time (time of enhanced symptomatic activation) [17]. Surgical treatment by deep brain stimulation is practiced to further modify dyskinesias and decrease the ‘off ’ time [18]. Although advanced, this treatment does not stop the progression of the disease either [1], therefore there is a great need to develop new regenerative therapeutic strategies that directly target the degenerating DAergic neurons or their innervation areas.

Alzheimer’s disease

Pathogenesis

AD is characterized by a progressive cognitive decline and memory loss [7]. The classical pathological changes in the brain of AD patients include deposition of α-amyloid plaques, the presence of neurofibillary tangles, gliosis and neuronal atrophy.

The neuronal degeneration and loss of synapses progresses over time and are widespread in AD, beginning with the entorhinal cortex and hippocam-pus and progressing to the neocortex, amygdala, thalamus and SN [19]. A main feature is the degeneration of the cholinergic neurons in the nucleus basalis of Meynert, which leads to a reduction in the cholinergic innervation of thecorti-cal and subcortical regions [20]. This reduction in acetylcholine correlates with

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the clinical and pathological severity of AD and is currently the main target for therapy (Figure 2) [21].

The majority of AD cases are nonfamilial with an unknown etiology. Many risk factors have been implicated to contribute to AD [22], such as old age, head injury, smoking, diabetes and exposure to heavy metals, such as copper or alu-minium [23,24].

Genetic screenings have so far revealed the causative role of three genes in early-onset familial AD. Missense mutations in presenilin 1 (PS1), preseni-lin 2 (PS2) and the amyloid precursor protein (APP) gene all caused autosomal dominant AD [25]. Furthermore, the presence of one or two apolipoprotein E 4 (ApoE4) alleles has been shown to be the main genetic risk factor for AD [26]. Over the years, many other genes have been associated with the disease, such as sortilinrelated receptor (SORL1), LRP and α2macroglobulin [27,28]. The genetic forms of AD have taught us a lot about the molecular mechanism underlying am-yloid plaque formation. Oxidative stress and an impaired ubiquitin–proteosome system have also been implicated in AD [29]. However, the cellular pathways that cause cholinergic neuron degeneration and tangle formation in AD are still elu-sive.

Treatment

Currently, there is no cure for AD and today’s treatments bring relatively small symptomatic relief to the patients, without having an effect on the progres-sion of the disease. The most common therapy is the prescription of acetyl cho-

Figure 2. Cholinergic projections and pathology of Alzheimer’s disease. (A) Cholinergic neurons in the nucleus basalis of Meynert project to the different cortical and subcortical areas of the brain. (B) Shrinkage and degeneration of cholinergic neurons in the nucleus basalis of Meynert of an Alzheimer’s patient compared with cholinergic neurons in a neurological control. (C) Tangle (hyperphosphorylated tau) and plaque (amyloid) pathology of an AD patient (NBB 06–050) in the anterior and posterior hippocampus, respectively. Reprinted with permission from [161]. Reproduced from Regenerative Medicine, July 2007, Vol. 2, No. 4, Pages 425-446 with permission of Future Medicine Ltd.


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linesterase inhibitors, such as donepezil, tacrine or rivastigmine, which reduce the rate of acetylcholine breakdown and increase its concentration in the brain, resulting in a modest cognitive improvement [30]. Another drug, memantine, is a novel NMDA receptor antagonist that targets the glutamatergic pathway [31]. Light therapy and electrical stimulation have also been used as treatments for AD. These treatments slightly improve the patient’s cognitive function [32,33]. As with PD, there is also an urgent need for effective regenerative therapeutic approaches for AD that prevent neuronal degeneration or rescue dying neurons.

Cell-replacement therapy

Over the last decades, cell-replacement therapyhas emerged as a potential treatment for neurodegenerative diseases such as PD and AD. We will discuss different cell-replacement strategies based on human fetal mesencephalic brain tissue, embryonic stem cells, neural progenitor cells (NPCs) and genetically engi-neered cells. Figure 3 shows the different cell types and defines the terminology used in this review. Most research has been performed in the field of PD, since the clinical symptoms are connected to the degeneration of the DAergic neurons mainly restricted to the SN and therefore can be easily targeted. This contrasts with the possibilities in AD, where the widespread pathological changes are a great challenge for cell-replacement treatment [17,34]. Recent extensive assess-ment of brain pathology in PD patients reveals that, in PD, there is also a wide-spread neuropathology [9], indicating the cell replacement aimed at the SN might not be sufficient as a therapy for PD. To create a successful cell-replacement ther-apy, five main goals must be achieved:

• Establishment of sufficient amounts of viable cells (DAergic or cholin-ergic) for transplantation

• Successful axon extension• Formation of functional synapses• Stable and long-term integration of the cells into the host brain circuit-

ry• Evidence of functional recovery

First cell-transplantation trials in PD & AD

The first clinical trials concentrated on transplantation of DAergic cell types with the intention of creating a new local source of DA. Animal studies have shown that functional synaptic integration of grafted DAergic neurons is possible [35,36]. However, to date, similar methods have failed to reconstitute the lost neuronal circuitry of the DA system in patients. Adrenal medulla tissue was first transplanted [37], resulting in a slight short-term improvement in be-havior; however the graft did not survive [6]. Human fetal ventral mesencephalic tissue has also been grafted in the striatal area of PD patients. Over 300 patients

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have been transplanted worldwide with this tissue [6], showing high graft sur-vival, reinnervation of the striatum and long-lasting symptomatic relief in small initial trials. However, double-blind studies failed to prove group improvement, but rather indicated individual patient differences and dyskinesia development [38,39]. Long-term effect studies showed DA storage and release by the graft tissue contributed to some symptomatic relief. The disease, however, was still progressing [40]. The differences in these trials and the ethical and practical rea-sons make this therapeutic approach unsatisfactory [41]. These issues were re-cently extensively discussed by Winkler and colleagues, and lie beyond the scope of this review [42]. In AD, cholinergic-rich tissue [43] and peripheral choliner-gic neurons [44] were transplanted into an AD rat model with nucleus basalis of Meynert lesions. These animal trials showed a memory improvement, which indicated a partial neuronal rescue in the disease model. No clinical trials in AD patients have been initiated with this method.

Figure 3. Generation and terminology of different stem cells. Embryonic stem cells (blue) are generated from a blastocyst and divide asymmetrically. They can differentiate into any tissue, in-cluding multipotent neural progenitor cells (purple) or mesenchymal progenitor cells (red). These progenitors also undergo asymmetric divisions. Neural progenitors can give rise to neurons, astrocytes and oligodendrocytes. Astrocytes can also differentiate into neurons and possibly neurons can change into astrocytes [162,163]. Reproduced from Regenerative Medicine, July 2007, Vol. 2, No. 4, Pages 425-446 with permission of Future Medicine Ltd.


27

Embryonic stem cells as regenerative tools in degenerative diseases

Embryonic stem (ES) cells are defined as pluripotent, undifferentiated cells that can proliferate and have the capacity of self-renewal and differentiation into different types of specialized cells from all three primary germ layers. They are derived from the inner mass of the embryonic blastula. ES cells were first isolat-ed from mice in 1981 [45], later from primates in 1995 [46] and finally from hu-mans in 1998 [47]. Hope exists that ES cells may prove to provide an inexhaust-ible source of neurons and glia for therapies that are aimed at cell replacement or neuronal protection in neurodegenerative disorders [34]. A lot of research has been focused on developing the best method of using ES cells in a therapeutic approach. Cell-replacement therapy for PD can be targeted to specific brain ar-eas, the SN or the caudate putamen, as these areas are directly connected to the clinical symptoms of the disease (Figure 1) [17,34]. Unfortunately, this technique is more difficult to apply to AD patients, since the neuropathology is too wide-spread throughout the brain (Figure 2).

Animal ES cells

To date, the research on ES cells has progressed to the level of animal test-ing. In PD, these models are mostly behavioral models with a chemically induced SN injury. Table 1 summarizes some of the animal studies performed, showing the progression in this field.

A prerequisite to prevent tumor formation after transplantation is ES cell differentiation (Table 1). Many different techniques were used to produce the most efficient differentiation procedure with the highest yield of DAergic neu-rons. Mimicking developmental signaling was thought to be the best method to differentiate ES cells. Lee and colleagues were the first to obtain a high yield of over 30% tyrosine hydroxylase (TH)- positive cells marking DAergic neurons in vitro by applying mitogens and specific signaling molecules [48]. They have de-veloped a protocol for ES cell differentiation into CNS progenitors and further maturation into DAergic and serotonergic neurons expressing all the cell-specific markers, such as Nurr1 for midbrain neurons. Kim and colleagues improved the protocol by the use of a stable Nurr1-expressing ES cell line derived by transfec-tion of cells with Nurr1 cDNA [49]. Later, Barberi and colleagues demonstrated that, by coculturing ES cells with stromal cells that present developmental sig-nals, the same goal could be reached [50]. Recently, it was shown that the Lmx1 and MSX1 homeodomain proteins are important in the generation of DA neurons from ES cells [51]. Transfection of ES cells with Lmx1a cDNAs driven by a nestin promoter, resulted in a robust generation of THpositive neurons. Furthermore, the stromal cellderived- inducing activity (SDIA) technique enabled generation of DA neurons by co-culturing mouse ES cells with PA6 cells (stromal cells derived from skull bone marrow). This technique was very efficient and, in 92% of the differentiated ES cells, expression of TH was observed [52]. A similar technique was applied on primate ES cells [53], generating a high yield of TH-positive cells

CH A PTER 1

28

Stud

y an

d ye

arTy

pe o

f cel

lsTr

ansp

lant

atio

n si

teA

sses

ing

tech

niqu

eR

esul

ts

Side

effe

cts

Ref

Dea

con

et a

l.,

(199

8)U

ndiff

eran

tiate

d m

ouse

ES

ce

llsM

ouse

and

rat

stria

tum

Cel

l sur

viva

l and

dif-

fere

ntia

tion

into

TH

+ ne

uron

s

Som

e ne

uron

al d

iffer

entia

tion

note

d, b

ut n

o in

tegr

atio

n in

to

the

host

bra

in

Not

men

tione

d[1

32]

Bjo

rklu

nd e

t al.,

20

02; T

ai e

t al.

(200

4)

Und

iffer

antia

ted

mou

se E

S

cells

Rat

PD

mod

el b

rain

Cel

l diff

eren

tiato

n,

beha

viou

ral t

ests

and

M

RI

Cel

ls p

ositi

ve fo

r diff

eren

tia-

tion

and

func

tinal

reco

very

pr

esen

t in

the

anim

al.2

4% o

f gr

afts

sho

ed n

o su

rviv

al

20%

of a

nim

als

deve

lope

d te

rato

mas

an

d ha

d to

be

sacr

a-fic

ed b

efor

e th

e en

d of

the

expe

riem

ent

[91,

133]

Kim

et a

l., (2

002)

In v

itro

ES

der

ived

TH

+ ce

lls b

y hi

gh N

urr1

gen

e ex

pres

sion

Stri

atum

of 6

-OH

DA

rat m

odel

Cel

l sur

viva

l and

inte

-gr

atio

n in

to th

e br

ain

and

beha

viou

r tes

ts.

Cel

ls e

xten

ded

thie

r axo

ns

into

the

stria

tum

, for

med

fu

nctio

nal s

ynap

tic c

onne

c-tio

ns a

nd th

e an

imal

sho

wed

re

cove

ry b

ehav

iour

No

tera

tom

a fo

rma-

tion,

but

furth

er

obse

rvat

ion

is re

com

-m

ende

d

[49]

Bar

beri

et a

l.,

(200

3)D

A ne

uron

s de

rived

in v

itro

from

mou

se E

S c

ells

by

co-c

ultu

re w

ith m

urin

e bo

ne

mar

row

-der

ived

stro

mal

fe

eder

cel

ls a

nd e

xpos

ure

to F

GF8

sig

nalin

g

Ipsa

late

ral s

triat

um

of m

ouse

6-O

HD

A P

D m

odel

cell

surv

ival

and

ass

es-

men

t of T

H+

cell

type

. B

ehav

iour

al a

sses

men

t

Beh

avio

ural

reco

very

.N

o te

rato

ma

form

a-tio

n.

[50]

Taka

gi e

t al.,

(2

005)

In v

itro

ES

der

ived

DA

neur

ons

with

the

use

of

stro

mal

cel

l der

ived

indu

c-in

g ac

tivity

(SD

IA) a

nd F

GF

and

FGF2

0 si

ngal

ing

Prim

ate

MP

TP

mod

el o

f PD

Beh

avio

ur s

tudi

es a

nd

func

tiona

l im

agin

gB

ehav

iour

reco

very

and

DA

activ

ity.

No

tum

or fo

rma-

tion

3 m

onth

s af

ter

trans

plan

tatio

n, b

ut

long

er o

bser

vatio

n su

gges

ted

[134

]

Rod

rigue

z-G

o-m

ez e

t al.

(200

7)In

vitr

o m

ouse

ES

-der

ived

D

A ne

uron

sIp

sala

tera

l stri

atum

of

mou

se 6

-OH

DA

PD

mod

el

Beh

avio

ur s

tudi

es, D

A re

leas

e, re

upta

ke a

nd

syna

pse

stim

ulat

ion

with

PE

T im

agin

g

Beh

avio

ral i

mpr

ovem

ent a

nd

long

-term

DA

rele

ase

from

th

e gr

aft.

Pos

tsyn

aptic

DA

D2

rece

ptor

nor

mal

ized

in th

e st

riatu

m

No

tera

tom

a fo

rma-

tion

[135

]

Tabl

e 1.

Rod

ent a

nd p

rimat

e em

bryo

nic s

tem

cell

trans

plan

tatio

n st

udie

s in

Park

inso

n’s d

iseas

e an

imal

mod

els.

6-O

HD

A: 6

-hyd

roxy

dop

amin

e; D

A:

Dop

amin

e; E

S: E

mbr

yoni

c ste

m; F

GF:

Fib

robl

ast g

row

th f

acto

r; M

PTP:

1-m

e th

yl 4

-phe

nyl 1

,2,3

,6-t

e tr

ahyd

ropy

ridin

e; M

RI: M

agne

tic r

eson

ance

imag

ing;

PE

T: P

ositr

on e

miss

ion

tom

ogra

phy;

SD

IA: S

trom

al ce

ll-de

rived

indu

cing

act

ivity

; TH

: Tyr

osin

e hy

drox

ylas

e.


29

(35%). Such a technique provides, in principle, a stable and unlimited source of primate neuronal cells.

Since undifferentiated ES cells may cause teratoma formation after trans-plantation, a method of complete irreversible differentiation into DA neurons and reliable, reproducible purification of the newly formed DA neurons is the biggest challenge. The field is turning now towards the use of the developmental signaling present in the CNS since these molecular pathways play a critical role in the generation of DA neurons. Smidt and Burbach defined a molecular scheme for ES differentiation leading to DAergic neurons. First, an early ES cell induction of Shh, Fgf8 and Wnt1 is needed and, shortly afterwards, the induction of Lmx1a and Lmx1b as well as Oxt2 and Foxa2 will start off the differentiation procedure. Foxa1, En1 and En2 induction would move the differentiation process into the next stage when the cells express Ptx3, Nr4a2 and Ilf1 and, as a consequence, TH and Vmat2 expression would be upregulated, at which point the cells represent mature DAergic neurons of the SN or ventral tegmental area [54,55]. Choliner-gic neurons can also be differentiated from ES and neural stem cells. Embryonic skeletal muscle extract [56] and bone morphogenetic protein 2 [57] were both shown to induce stem cell differentiation into the cholinergic neuron phenotype. More studies identifying the developmental cues responsible for this neuronal subtype, such as the finding that the Islet-1 transcription factor is specific for cholinergic neurons [58], are needed to develop a similar molecular scheme for cholinergic neuron differentiation.

Human ES cells

Similarly to animal ES cells, the use of human ES (hES) cells as a tool for cell-replacement therapies is still at an early stage. Table 2 summarizes the ex-periments performed in the search for the most optimal conditions for hES cell differentiation into DA neurons. With each trial, the DAergic cell numbers increased; however, when applied in transplantation studies, these hES cell-de-rived neurons did not integrate into the host brain and did not result in func-tional recovery in the PD animal models. Table 3 summarizes animal studies per-formed with these cells.

Apart from the ethical problems concerning the use of hES cells, many practical concerns emerge. A significant problem lies in the differentiation meth-ods of hES cells, since nonhuman stromal cells or other tumor cell lines are used to induce lineage specificity. If hES cells are to be used as a therapeutic tool, they will have to be cultured under animal-free conditions (i.e., not grown on, for ex-ample, a mouse cell monolayer) to avoid any animal viral infection of human tis-sue. Recently, this was achieved by Roy and colleagues, who used human fetal midbrain astrocytes for co-culture [59]. The use of different hES cell lines also poses a problem since they may differ in their ability to generate DAergic neu-rons and may have different functional activity in the host brain. For instance, in the study by Ben-Hur and colleagues, hES cells were able to improve animal

CH A PTER 1

30

behavior after a lesion [60], which was in contrast to Shultz and colleagues, who performed the same experiment but failed to show a functional recovery [61]. Another major problem is the minimal survival rate of the hES-derived neurons in the host brain after transplantation. These cells either do not survive the graft procedure or they die in the rodent brain after transplantation. This was not observed with other mammalian ES cells, indicating significant differences be-tween species. Finally, and probably the most troubling issue, is the inability to completely differentiate all ES cells. This is a necessity since purifying the dif-ferentiated from the undifferentiated cells has not been successful [62]. Some of the ES cells may still proliferate and may cause teratoma formation after they have been transplanted into the host brain. This and other aforementioned prob-lems must be solved before an ES cell-replacement therapy will be safe enough for starting a clinical trial [63].

Alternative use of ES cells: gene modification and/or environmental ‘chap-erones’

The cell-replacement strategy with ES cells is still in a very early stage of development. Their migration ability and their ‘chaperone’ attribute are also important and may lead to alternative uses of ES stem cells in future therapies. ES cells can be used in ex vivo gene therapeutic approaches as delivery vehicles. Cultured ES cells can be genetically modified by using eitherplasmid-based or lentiviral or retroviral vectormediated cDNA transduction [17]. After transplan-tation, the genetically modified ES cell and its progeny, in case of integration of the cDNA in the DNA of the ES cells, will express the gene of interest in vivo [64]. Additionally, the ‘chaperone’ character of ES stem cells (i.e., to nurse and sup-port host neurons) is an interesting feature, which might be related to either the secretion of growth factors by the stem cells or expression of specific surface

Study Cell line Differentiation technique

Results Ref.

Park et al., (2004)

MB03 Basic FGF cell induc-tion with further TGF-α treatment

20% TH+ neurons but no confir-mation of mibrain DA neurons.

[136]

Perrier et al., (2004)

H1, H9 and HES-3

Use of stromal feeder-based differentiation system [50] and midbrain DA neuronal induction by FGF8 and SHH signaling

79% TH+ midbrain DA neurons derived.

[137]

Yan et al., (2005)

H1 and H9 FGF8, SHH and Sox1 treatment

60% of TH+ cells also expressed midbrain DA neuron markers. These cells were electrophysi-ologically active and released DA in activity-dependent manner.

[138]

Table 2. Human embryonic stem cells differentiation in vitro. DA: Dopamine; FGF: Fibroblast growth f actor; SHH: Sonic hedgehog; TGF: Transforming growth f actor; TH: Tyrosine hydroxylase.


31

Stud

yC

ell l

ine

Diff

eren

tiatio

n te

chni

que

Tran

spla

nta-

tion

site

Ass

esin

g te

chni

que

Res

ults

Ref

.

Sch

ulz

et

al.,

(200

4)B

G01

and

B

G03

Sus

pens

ion

grow

th in

Hep

G2

liver

tum

or

cell-

cond

ition

ed m

ediu

m a

nd la

ter i

n co

nven

-tio

nal s

erum

-free

med

ium

.

6-O

HD

A ra

t st

riatu

mC

ell s

urvi

val

and

beha

viou

r te

sts

Very

few

TH

+ ce

lls fo

und

at th

e si

te o

f the

gr

aft.

[61]

Ben

-Hur

et

al.,

(200

4)H

ES

-1E

xpos

ure

to b

one

mor

phog

enet

ic p

rote

in

anta

goni

st n

oggi

n6-

OH

DA

anim

al

mod

elC

ell s

urvi

val

and

beha

vior

al

test

s

0.5%

TH

+ ce

lls in

vitr

o, im

prov

emen

t in

be-

ahvi

or. 1

2 w

eeks

afte

r tra

nspl

anta

tion

0.2%

of

tran

spln

ated

cel

ls T

H+

[60,

63

]

Zeng

et a

l.,

(200

4)B

G01

PA6

stro

mal

cel

l co-

cultu

re6-

OH

DA

lesi

oned

rode

nt

stria

tum

Cel

l sur

viva

l an

d le

ania

ge

Few

sur

vivi

ng T

H+

neur

ons

5 w

eeks

pos

t-tra

nspl

anta

tion,

man

y m

esod

erm

al li

neag

e ce

lls

[139

]

Par

k et

al.,

(2

005)

HS

F-6

Use

fo s

trom

al fe

eder

-bas

ed d

iffer

entia

tion

syst

em a

nd m

idbr

ain

DA

neur

onal

indu

ctio

n by

FG

F8 a

nd S

HH

sig

nalin

g

Stri

atum

of P

D

rat m

odel

Cel

l sur

viva

l an

d be

havi

or

test

s

In v

itro

40%

of c

ells

TH

+ D

Aer

gic

linea

ge

with

cap

abili

ty o

f rel

easi

ng D

A. I

n vi

vo n

o TH

+ ce

lls fo

und

at th

e si

te o

f the

gra

ft an

d no

beh

avio

r cha

nges

[140

]

Bre

der-

lau

et a

l. (2

006)

SA

0002

.5PA

6 st

rom

al c

ell c

o-cu

lture

for 1

6, 2

0 or

23

days

6-O

HD

A le

sion

ra

t stri

atum

Cel

l sur

viva

l an

d lin

eage

, be

havi

our t

est

Low

DA

neur

on p

heno

type

s of

the

graf

t. N

o be

havi

oral

cha

nges

. Sev

ere

tera

tom

a de

vel-

opm

ent i

n 16

-day

diff

eren

tiatio

n co

nditi

on

[141

]

Roy

et a

l. (2

006)

Hi a

nd H

9S

HH

and

FG

F8 e

xpos

ure

and

co-c

ultu

re

with

telo

mer

ase-

imm

ortiz

ed fe

tal m

idbr

ain

astro

cyte

s

6-O

HD

A le

sion

ra

t stri

atum

Cel

l sur

viva

l an

d lin

eage

, be

havi

our t

est

21%

of T

H c

ells

at 1

0 w

eeks

pos

t-gra

ft an

d de

clin

ing

with

tim

e. 6

wee

ks p

ost-g

raft,

si

gnifi

cant

beh

avor

cha

nges

not

ed. G

raft

also

sho

wed

the

pres

ence

of n

ondi

ffere

nti-

ated

cel

ls

[59]

Mar

tinat

et

al.,

(200

6)H

9C

o-cu

lture

with

bon

e m

arro

w-d

eriv

ed s

trom

al

cells

(SID

A pr

otoc

ol) a

nd tr

ansd

uced

with

le

ntiv

iral v

ecto

rs e

xpre

ssin

g N

urr1

and

Pitx

3

6-O

HD

A le

sion

m

ouse

stri

atum

Cel

l sur

viva

l an

d lin

eage

, be

havi

our t

est

45%

TH

+ ce

lls a

nd b

ehav

ior i

mpr

ovem

ent

[142

]

Son

ntag

et

al.,

(200

7)H

7 an

d H

9E

xpos

ure

to b

one

mor

phog

enet

ic p

rote

in

anta

goni

st n

oggi

n an

d st

rom

al c

ell c

o-cu

lture

6-O

HD

A le

sion

ra

t stri

atum

Cel

l sur

viva

l an

d lin

eage

, be

havi

our t

est

H7-

deriv

ed g

rafts

con

tain

ed T

H+

neur

ons

and

som

e an

imal

s sh

owed

beh

avio

ral i

m-

prov

emen

t. Te

rato

ma

grow

th w

as n

oted

[143

]

Iaco

vitti

et

al.,

(200

7)H

9, H

UE

S7

and

8U

se o

f che

mic

ally

defi

ned

nhum

an-d

eriv

ed

med

ia a

dditi

ves

and

subs

trata

6-O

HD

A le

sion

ra

t stri

atum

Cel

l sur

viva

l an

d lin

eage

Rob

ust c

ell s

urvi

val w

ith n

euro

nal l

inea

ge.

Man

y ce

lls e

xpre

ss T

H[1

44]

Tabl

e 3.

Hum

an e

mbr

yoni

c ste

m ce

ll tra

nspl

anta

tion

stud

ies i

n Pa

rkin

son’

s dise

ase

anim

al m

odel

s. 6-

OH

DA:

6-h

ydro

xy d

opam

ine;

DA:

Dop

amin

e; F

GF:

Fi

brob

last

gro

wth

f ac

tor;

PD: P

arki

nson

’s di

se a

se; S

DIA

: Str

omal

cell-

deriv

ed in

duci

ng a

ctiv

ity; S

HH

: Son

ic h

edge

hog;

TH

: Tyr

osin

e hy

drox

ylas

e.

CH A PTER 1

32

molecules. More research is needed to clarify this phenomenon. In spinal cord in-jury, this effect, along with the remyelination of the injured axons by transplant-ed precursor cells, could have contributed to the restoration of locomotion [65]. There are even plans to make use of this ES cell ‘nursing’ characteristic observed in rat spinal cord injury and to inject ES cells into patients with paralyzing spinal cord injuries [66].

Neural progenitor cells

Progenitor cells are multipotent cells that divide asymmetrically giving rise to a daughter progenitor cell and a cell that will differentiate into a neuron or a glial cell (Figure 3). NPCs are a promising source of cells for transplantation.

Embryonic & adult neural progenitors

With the discovery of neurogenesis in the adult hippocampus [67] and ol-factory bulb [68], the dogma of the CNS as an unregenerative, hardwired tissue was discredited. Multipotent neural progenitors and lineage-specific NPCs were shown to be present in the brain (Figure 3) [69]. In the mammalian adult brain, two main neurogenic niches were identified: the subgranular zone of the dentate gyrus in the hippocampus [70,71] and the subventricular zone (SVZ) in the walls of the lateral ventricle of the brain [72,73]. Additionally, neural progenitors were found in other areas of the adult brain, such as the cortex [74], SN [75,76] and ependymal layer of the third ventricle [77]. The presence of neural progenitors in the SN is still in dispute [69,75,78]. Also, in the human brain, neurogenesis was observed in the SVZ [79] and hippocampus [71]. Recently, it has been shown that the rostal migratory stream is also present in the human brain. Newly born neu-rons travel from the SVZ to the olfactory bulb along the rostral migratory stream [80].

Neural progenitors became attractive candidates for cell-replacement therapy. Flax and colleagues were the first to explore the characteristics of the human NPCs in vitro and in vivo [81]. Their experiments show that human em-bryonic NPCs are capable of expansion in vitro and are also capable of producing neurons, astrocytes and oligodendrocytes. Additionally, this group also showed that these human cells can be transplanted into an animal model and that they survive and even replace cells lost due to injury [81]. NPCs apparently have the ability to respond to local environment-derived signals at the site of the injury. NPCs can migrate toward a lesion area, differentiate into neurons and establish synaptic contacts with the local neurons [69,78]. This demonstrates that these cells can be useful tools in future therapy for neurodegeneration. On the other hand, Jain and colleagues transplanted NPCs in the PD 6-OHDA animal model and showed that, although capable of migration, these cells move out of the graft site, not influenced by the DA neuronal loss in the SN [82].

As in ES cell research, the use of NPCs in transplantation procedures comes with some apprehensions. One concern relates to the method of culturing and


33

differentiating NPCs. Until recently, there was a problem with establishing a stable human NPC culture with a constant ability to sustain ex vivo mitosis in culture [83]. Walton and colleagues resolved this issue by developing an optimal protocol to culture human adult progenitor cells that were highly expandable [83]. In addition to the culture conditions, the method of differentiation is also important. New ways of stimulating NPCs into differentiation have been devel-oped, such as the use of different growth factors, retinoic acid or cAMP stimula-tion [69,84]. However, before the NPCs can be used in the clinic, these proce-dures have to be consistent and proven to be safe.

A further concern relates to the phenotype of the transplanted NPCs. Should the cells be in an undifferentiated form, or should they be stimulated in vitro to differentiate into specific neuronal cells? Both types of cells show sur-vival in the graft [85,86], although undifferentiated human precursor cells show a better migration behavior towards the lesion, whereas the differentiated pre-cursors have higher survival rate with more neurons present in the graft [87,88]. A study by Burnstein and colleagues compared two cell types as candidates for transplantation in a PD model, but they could not show recovery or additional DAergic neuronal differentiation. In this study, the cells survived in the graft, but they did not integrate into the host system [88]. This brings us to the final con-cern with this technique, regarding the functional significance of the transplan-tation method. Functional recovery can only take place when there is integra-tion of donor cells into the host neuronal network and restoration of function. Table 4 summarizes transplantation experiments with the use of NPCs in animal models for PD. The various results of these experiments, plus the possibility of tumor growth induced by these NPCs [89], make this cell-replacement method still risky and it is necessary to understand the mechanism of progenitor cell dif-ferentiation in more detail before using them as a therapeutic tool.

NPCs as environmental ‘chaperones’

While performing transplantation experiments, Ourednik and colleagues made a very interesting discovery concerning the behavior of NPCs after graft-ing into the MPTP mice model [90]. They not only noticed a conversion of NPCs into DAergic neurons, but they also found that the majority of the new TH-posi-tive neurons belonged to the host. This may be indicating a ‘rescue’ of the host neurons by the NPC graft. The NPCs may play a role as ‘chaperones’ of the host cells and promote their regrowth. These cells could have an inherent capacity to preserve and reactivate cells through their natural expression of trophic and neuroprotective substances. Therefore, the presence of NPCs at the injury site by itself may alter the microenvironment, resulting in the rescue of the impaired host neurons. This approach provides an alternative to the cell-replacement method, where the NPCs do not necessarily have to substitute the impaired neu-rons, but they may just simply promote their growth and stimulate their activity [90]. Others also share this view and suggest a new role of NPCs as chaperones

CH A PTER 1

34

Stud

yC

ell t

ype

Tran

spla

ntat

ion

site

Ass

esin

g te

chni

que

Res

ults

Ref

.S

anch

ez-

Per

naut

e et

al.,

(2

001)

Hum

an fe

tal m

idbr

ain

prec

urso

r cel

ls

Stri

atum

of 6

-OH

DA

rat P

D

mod

elB

ehav

iora

l tes

ts a

nd

graf

t exa

min

atio

nH

ihg

surv

ivin

g ce

ll ra

te o

f neu

rons

and

tre

nd in

beh

avio

r im

prov

emen

t[1

45]

Sve

ndse

n et

al.,

(1

996)

Hum

an fe

tal m

esen

-ce

phal

on n

euro

nal

stem

cel

ls

Stri

atum

of D

A-d

eple

tad

rat P

D

mod

elG

raft

exam

inat

ion

Mos

t cel

ls in

the

graf

t sho

wed

glia

l lin

eage

[146

]

Sny

der e

t al.,

(1

997)

Mul

itpot

ent N

PC

sM

ouse

neo

corte

x w

ith ta

rget

ed

apop

totic

neu

rona

l deg

enen

ra-

tion

Gra

ft ex

amin

atio

nLi

ttle

surv

ival

and

15%

diff

eren

tiatio

n of

N

PC

into

neu

rons

[147

]

Lepo

re e

t al.,

(2

004)

Rat

feta

l neu

rona

l an

d gl

ial l

inea

ge-

rest

ricte

d N

PC

s

Rat

adu

lt h

ippo

cam

pus,

stri

a-tu

m a

nd s

pina

l cor

d (in

tact

and

in

jure

d)

Gra

ft ex

amin

atio

nS

urvi

val o

f mat

ure

linea

ge-r

estri

cted

cel

ls in

th

e gr

aft a

nd in

tegr

ated

into

the

host

bra

in

[87]

Ahn

et a

l., (2

004)

DA

cells

der

ived

from

ne

uron

al s

tem

cel

lsR

at D

A-d

ener

vate

d st

riatu

m.

Gra

ft ex

amin

atio

n an

d be

havi

oral

test

sN

o m

igra

tion

to th

e ne

uron

al d

egen

enra

tive

area

s an

d no

cha

nge

in b

ehav

ior

[148

]

Lepo

er e

t al.,

(2

006)

Rat

neu

rona

l and

gl

ial l

inea

ge re

stric

ted

NP

Cs

Rat

adu

lt an

d de

velo

ping

st

riatu

mG

raft

exam

inat

ion

NP

C d

iffer

entia

ton

and

inte

grat

ion

into

the

host

bra

in[8

6]

Jain

et a

l., (2

006)

Hum

an e

xpan

ded

neur

onal

pre

curs

or

cells

Rat

stri

atum

of 6

-OH

DA

OD

m

odel

prio

r, at

the

sam

e tim

e, o

r af

ter t

he le

sion

Pre

senc

e of

don

or c

ells

in

SN

, fro

ntal

cor

tex

and

glob

us p

allid

us

Alth

ough

cap

able

of m

igra

tion,

NP

Cs

do

not s

how

spe

cific

trop

ism

for t

he s

ites

of D

A ne

uron

loss

[82]

Tabl

e 4.

Neu

ral p

roge

nito

r cel

l-tra

nspl

anta

tion

stud

ies i

n Pa

rkin

son’

s dise

ase

anim

al m

odel

s. 6-

OH

DA:

6-h

ydro

xy d

opam

ine;

DA:

Dop

amin

e; N

PC: N

eu-

ral p

roge

nito

r cel

l; PD

: Par

kins

on’s

dise

ase;

SN

: Sub

st a

ntia

nig

ra.


35

that offer neuroprotection and mediate rescue of specific populations of degen-erating neurons in the host brain [91].

NPCs used in molecule delivery to the diseased brain

As an alternative to cell replacement, NPCs can be used as delivery vehicles due to their favorable migratory capabilities. There are at least three important factors influencing the migratory behavior of progenitor cells: inflammation, reactive gliosis and angiogenesis [17]. During inflammation, neurotransmitters released by microglia [17] and the release of attractive chemicals by reactive astrocytes both promote neuronal survival and progenitor migration [92]. This also accounts for angiogenesis, where the activated endothelial cells secret neu-ronal chemoattractants, such as vascular growth factor [17]. An indication that this process takes place was shown in a study by Jin and colleagues. They pro-vided evidence that neurogenesis was induced by stroke in the human brain [93].

The migration capacity of the NPCs made them a good vehicle for the de-livery of small molecules into the brain. NPCs may be manipulated in vitro to ex-press certain molecules by a gene-transfer method by either cDNA transfection or lentivirus or retrovirus transduction techniques [17]. A wide variety of thera-peutic genes can be expressed by progenitor cells depending on their later func-tion in vivo. In the case of PD, NPCs have been used to deliver glial cell-derived neurotrophic factor (GDNF). GDNF is a potent neurotrophic factor for SN DAergic neurons, preventing the progression of neuronal loss, maintaining neuronal con-nections and function, and inducing an additional regenerative response in these neurons [94]. An experiment with the use of GDNF-expressing NPCs showed successful integration and differentiation of these cells and, most importantly, showed a stable GDNF expression for up to 4 months post-transplantation [94]. An improvement of animal behavior indicated that the GDNF NPCs prevented DA ergic neuron degeneration in the SN.

NPCs can also be used in AD as delivery vehicles of therapeutic molecules. The character of AD imposes a greater problem with specific molecule delivery, since the damage in the brain is spread over many areas. The use of the homing qualities of NPCs can allow delivery of molecules such as enzymes or antibodies to the amyloid deposition areas [17,95]. These experiments are still ongoing, but the possibility of such therapeutic approaches may have a significant impact.

A new interesting approach of in vivo genetic modification of NPCs by a len-tiviral-vector encoding the green fluorescent protein (GFP) as a marker protein was recently explored by Consiglio and colleagues [96]. The lentivirus was inject-ed into the SVZ of mice and labeled the NPCs. As time progressed, the daughter NPCs were expressing the marker protein, showing an efficient long-lived trans-fer of GFP. This experiment demonstrated the feasibility of a new gene-therapy strategy that creates a continuous source of expression of a therapeutic gene in new-born neurons, by transducing the NPCs in vivo (Figure 4).

CH A PTER 1

36

Other progenitor cells

Bone marrow adult progenitor cells became an interesting candidate for cell-replacement therapy due to their accessibility. Recently, these cells were shown to generate neurons in the brain of mice in vivo [97]. Although the num-ber of neuronal cells derived from the bone marrow progenitor cells was low, this study showed that tissue-specific stem cells were able to transdifferentiate [6]. Interestingly, this approach also seems to be possible in humans. Cogle and colleagues looked at the brains of three sex-mismatched female bone marrow transplantation patients [98]. At 6 years after the transplantation, they found hippocampal neurons containing a Y chromosome in all transplanted patients. In total, 1% of the neurons found in the female brains contained one Y chromo-some and 1–2% of glial cells was made up of male astrocytes and microglia. This study supports the theory that hemopoietic cells can indeed transdifferentiated and demonstrates that this process can take place in human patients, indicating its future impact for therapy [98]. Another approach presents a possibility to dif-ferentiate human and mouse bone marrow progenitor cells into neuronal cells in

Figure 4. Present and future possibilities of therapies for Parkinson’s and Alzheimer’s disease. Gene-therapy and cell-transplantation methods separately (or in the future possibly combined) might be able to provide the most optimal therapy for neurodegenerative diseases. The use of NPCs ex vivo manipulated to express neuronal support molecules may be able to reconstruct degenerated circuits and contribute to the regeneration of diseased brain areas, ceasing the pro-gression of the disease. CP: Caudate putamen; ESC: Embryonic stem cell; NBM: Nucleus basalis of Meynert; NPC: Neural progenitor cell; SN: Substantia nigra. Reproduced from Regenerative Medicine, July 2007, Vol. 2, No. 4, Pages 425-446 with permission of Future Medicine Ltd.


37

vitro [99,100]. Schwarz and colleagues transplanted such cells expressing human TH into a rodent model of PD and demonstrated significant functional recovery [100]. Some doubt was put on this hypothesis, where two studies argued that no new neurons were made from these stem cells, but rather they occasionally fuse with host neurons [101,102]. Interestingly, further investigations of female patients who were transplanted with male bone marrow patients showed that the Y chromosome present in neuronal cells in these patients’ brains could not be explained by cell fusion [103,104].

Gene therapy

Gene therapy for neurodegenerative diseases involves the delivery of genes encoding protective or restorative molecules into an area of interest in the brain with the aim of preventing neuronal loss or atrophy, or to promote axonal re-generation and synapse formation. Successful gene therapy will either prevent further functional decline or promote the restoration of neuronal function. In current research, the predominant molecules used in this approach are neuronal growth factors. When delivered to areas of neuronal degeneration in the brain, they promote neuronal survival and counteract or reverse atrophy. Compelling evidence from animal studies suggests that neurotrophic factors can potentially halt the progression of neurodegeneration in diseases such as PD and AD, result-ing in improved motor and cognitive performance [105–107].

Delivery of neurotrophic factors to the CNS is difficult. Injection in the bloodstream is not optimal since most proteins do not cross the blood–brain bar-rier and systemic injection of certain growth factors results in strong peripheral side effects. There are three main ways of molecular delivery of large molecules to the brain:

• Use of transplanted cells genetically engineered to secrete the molecule of interest (previously discussed)

• Delivering the protein itself• Direct transfer of genes using viral vectors [108]

Viral vector-mediated gene delivery allows specific targeting of diseased tis-sue, high local expression of the substance of interest and low spread of the mol-ecule into other regions of the brain. Viral vector-mediated gene transfer thus allows for long-term and local expression of a foreign gene after a single injection of a viral vector [107–109].

In this section, we will discuss gene delivery in PD and AD models, as well as cover the ongoing clinical trials of neurotrophic factor delivery in these dis-eases (Table 5).

CH A PTER 1

38

Stud

yA

nim

alG

ene

deliv

ery

vehi

cle

Tran

spla

ntat

ion

site

Ass

esin

g te

chni

que

Ref

.P

arki

nson

’s d

isea

se

Bac

klun

d et

al.,

(198

5);

Say

les

et a

l., (2

004)

Adr

enal

med

ulla

tis

sue

neur

onal

tra

nspl

anta

tion

Tran

spla

ntat

ion

into

stri

atum

or c

auda

te

nucl

eus

Incr

ease

d in

L-D

OPA

‘on’

pha

se,

disa

ppea

red

afte

r 18m

onth

s, n

o gr

aft

surv

ival

Hig

h le

vel o

f mor

talit

y[6

,37]

Say

les

et a

l., (2

004)

; Fr

eed

et a

l., (2

002)

; O

lano

w e

t al.,

(200

3)

Feta

l VM

tran

s-pl

anta

tion

Tran

spla

ntat

ion

into

stri

atal

are

aG

raft

surv

ival

and

rein

nerv

atio

n. N

o tre

atm

ent e

ffect

s on

PD

Dev

elop

emnt

of d

yski

-ne

sias

[6, 3

9,

62]

Men

dez

et a

l., (2

005)

Feta

l mid

brai

n tra

nspl

anta

tion

Cel

l sus

pent

ion

trans

plan

tatio

n in

to

stria

tum

Gra

ft su

rviv

al a

nd re

inne

rvat

ion,

m

inim

al in

flam

mat

ion

reac

tion

Unk

now

n[1

60]

Tita

n P

harm

aceu

tical

s,

Inc.

Sph

eram

ine

cell

ther

apy

Ste

reot

actic

inje

ctio

n of

hum

an p

ost-

mor

tem

retin

al p

igm

ente

d ep

ithel

ial c

ells

pr

oduc

ing

L-D

OPA

atta

ched

to m

icro

carr

i-er

s in

to D

A-d

efici

ent b

rain

reag

ons

Impr

ovem

ent i

n m

otor

func

tion

12

mon

ths

post

-trea

tmen

t, su

stai

ned

for

24 m

onth

s

Unk

now

n[2

05]

Kor

dow

er e

t al.,

(199

9);

Nut

t et a

l., (2

003)

; Das

s et

al.,

(200

6)

GD

NF

prot

ein

inje

ctio

nIn

trave

ntric

ular

pro

tein

inje

ctio

nN

o im

prov

emen

tsN

ause

a, v

omiti

ng, c

on-

fusi

on, h

allu

cina

tions

an

d dy

skin

esia

s

[107

, 11

1,

112]

Gill

et a

l., (2

003)

; S

levi

n et

al.,

(200

3);

Das

s et

al.,

(200

6)

GD

NF

prot

ein

inje

ctio

nC

hron

ic in

fusi

on o

f pro

tein

into

pos

tcom

-m

issu

ral p

utam

en w

ith th

e us

e of

a p

ump

Func

tiona

l im

prov

emen

t, 1-

year

in

crea

se o

f DA

stor

age

in p

utam

en,

redu

ced

dysk

ines

ias

No

side

effe

cts

[107

, 11

3,

114]

Das

s et

al.,

(200

6);

Am

gen

biot

echn

olog

yG

DN

F pr

otei

n in

ject

ion

Dou

ble-

blin

d st

udy

with

intra

puta

mea

nal

inje

ctio

nS

tudy

pre

mat

urel

y te

rmin

ated

- no

diffe

renc

e in

pla

cebo

gro

upIm

mun

olog

ical

reac

tion

note

d in

10%

of t

he

patie

nts

[107

]

Das

s et

al.,

(200

6);

Cer

egen

e, N

euro

logi

x an

d Av

igen

, Inc

.

AAV

-NTN

, A

AV-G

AD

and

A

AV-A

AD

C

gene

del

iver

y

Stri

atum

inje

ctio

n, s

ubth

alam

ic in

ject

ion

and

seco

nd s

triat

um in

ject

ion,

resp

ectiv

ely

AAV

-NTN

tria

l sho

ws

good

tole

ranc

e to

the

vect

or a

nd re

duct

ion

of d

isea

se

sym

ptom

s by

40%

No

side

effe

cts

re-

porte

d[1

07]

Alz

heim

er’s

dis

ease

Erik

sdot

ter e

t al.,

(1

998)

NG

F pr

otei

n in

ject

ion

Intra

cere

brov

entri

cula

ry p

rote

in in

ject

ion

Slig

ht im

prov

emen

t in

cogn

itive

fu

nctio

nD

ull c

onst

ant b

ack

pain

an

d w

eigh

t red

uctio

n[1

20]

Tusz

ynsk

i et a

l., (2

005)

Ex

vitro

NG

F ex

pres

sion

Inje

ctio

n of

NG

F-ex

pres

sing

fibr

obla

sts

to

the

chol

iner

gic

basa

l for

ebra

inN

GF-

indu

ced

troph

ic e

ffect

, cho

liner

-gi

c co

nnec

tions

are

reco

nnec

ted

and

cogn

itive

impa

irmen

t slo

wed

dow

n

No

side

effe

cts

re-

porte

d[7

]


39


In PD, gene therapy has the potential to deliver neurotrophic factors to the anatomical areas of the brain that are affected: the SN, putamen and striatum. GDNF was demonstrated to prevent degeneration of DAergic neurons and, out of all growth-promoting factors, it is so far the most consistent in its action [110]. Because of these attributes, GDNF is the most researched growth factor in rela-tion to PD and it was the first to be used in clinical trials. Two methods of GDNF administration have been used: either direct administration of the protein or de-livery of the GDNF gene.

GDNF protein delivery

After demonstrating the potency of GDNF in reversing degeneration of DA neurons in animal models, the first clinical trials were endorsed [111,112]. GDNF protein was intraventriculary injected into PD patients, but failed to produce im-provements in disease symptoms. This may be due to a failure to deliver GDNF to the site of pathology, such that no nigral neurons were reached by the factor. This procedure caused serious side effects, including nausea, anorexia, vomiting, con-fusion, hallucinations, parasthesias, headaches and dyskinesias, indicating that the protein reached unwanted peripheral targets. The diffusion of GDNF in the brain parenchyma was very poor, with little GDNF passing the ventricular epen-dyma and, consequently, no GDNF reached the nigral neurons [107]. These stud-ies showed that it is not only the neurotrophic activity of the growth factor that matters, but that the site and method of delivery are essential for the growth factor treatment to be successful.

Two other open-label clinical trials were initiated where GDNF was chroni-cally infused using pumps into the postcommissural putamen (an area of the brain that displays the greatest DA loss and directly connects to the motor cor-tex [107]) of PD patients [113,114]. Both of these trials showed functional im-provement with a long-term (1 year) increase of DA storage in the putamen and a corresponding improvement in the processing of motor output [113]. Addition-ally, dyskinesia scores were significantly reduced in both studies. No side effects were noted, showing that site-specific direct GDNF treatment may be safe and beneficial.

To further explore the impact of direct GDNF protein delivery, in 2004, Am-gen biotechnology [201] performed a double-blind, placebo- controlled study where GDNF was injected into the putamen of 34 PD patients [107]. The study was prematurely terminated after 6 months due to lack of clinical improvements

Table 5. (Previous page). Clinical trials in Parkinson’s disease and Alzheimer’s disease patients. A ADC: Aromatic L-amino acid decarboxylase; A AV: A deno-associa ted virus; GAD: Glut amic acid decarboxylase; GDNF: Glial cell line-derived neurotrophic f actor; L-DOPA: Levodopa; NGF: Nerve growth f actor; NTN: Neurturin; PD: Parkinson’s dise ase; VM: Ventral mesencephalic.

CH A PTER 1

40

in the group treated with GDNF compared with the placebo-controlled group. Additionally, animmunological reaction against GDNF was noted in 10% of pa-tients. Parallel results from monkey studies showed irreversible brain damage in the animals treated with high-dose GDNF. Fortunately, this was not noted in patients, presumably because the dose of GDNF was much lower [107].

A complicating factor of GDNF protein infusion is the fact that intraparen-chymal protein diffusion may be uncontrollably affecting other cell types in sur-rounding brain areas. Although there are no eminent side effects in PD patients treated for a maximum of 1 year, these issues may lead to problems following long-term treatment regiments [107].

GDNF gene delivery

Compared with protein delivery, gene delivery offers several advantages. It is technically more practical, since it does not require permanent intraparen-chymal catheter implantation and refills of the minipumps. Additionally, a num-ber of carefully spaced small stereotactic injections of a viral vector carrying a transgene in a defined brain region ensure the continuous and more targeted lo-cal production of a therapeutic transgene (Figure 4).

GDNF gene delivery to the brain was investigated in several ways in animal models for PD (Table 6). The main issues addressed in these experiments were the identification of the best viral vector and finding the most optimal site for delivery of the transgene in order to create the best conditions for neuronal pro-tection and/or neuronal restoration by GDNF.

Some experiments were designed in such a way that viral GDNF was inject-ed into the animal before the administration of the neurotoxin, to show neuron-protective characteristics of this growth factor. The site of the injection plays a crucial role in the successful rescue of the DA neurons. The striatum is suggest-ed to be the optimal site of viral GDNF injection and this will most likely be the area that will be genetically modified in future clinical trials [107]. Additionally, adeno-associated virus (AAV) vectors were found to be the most efficient and safe gene-delivery vehicles. Although prelesion viral vector-mediated expression of GDNF results in neuronal protection, these observations cannot be directly translated to a treatment for PD since the vector encoding GDNF would have to be injected after the initiation of neuronal degeneration. Therefore, other studies examined the effectiveness of GDNF to rescue injured DA neurons after induc-tion of the lesion and showed that GDNF could indeed improve motor behavior and decrease cell death (Table 6).

Table 6. (Next page). Rodent and primate GDNF gene-delivery trials in Parkinson’s disease ani-mal models. 6-OHDA: 6-hydroxy dopamine; A AV: A deno-associat ed virus; A d: A denovirus; DA: Dopamine; GDNF: Glial cell line-derived neurotrophic factor; HSV: Herpes simplex virus; MPTP: 1-methyl-4-phenyl- 1,2,3,6-t etrahydropyridine; PD: Parkinson’s dise ase; SN: Subst antia nigra; TH: Tyrosine hydroxylase.


41

Stu

dyA

nim

alG

ene

deliv

ery

vehi

cle

Tran

spla

ntat

ion

site

Ass

esin

g te

ch-

niqu

eR

esul

tsR

ef.

Bef

ore

lesi

on

Kiri

k et

al.,

(200

0)6-

OH

DA

anim

al m

odel

Ad-

GD

NF

Intra

stria

tal,

intra

ni-

gral

and

intra

ven-

tricu

lar

Cel

l dea

th, T

H+

cell

coun

t and

beh

av-

iour

al te

sts

Onl

y in

trast

riata

l inj

ectio

n co

uld

pr

eser

ve T

H+

neur

ons

[149

]

Cho

i-Lun

dber

g et

al

., (2

000)

6-O

HD

A an

imal

mod

elA

d-G

DN

FIn

trast

riata

lC

ell s

urvi

val a

nd

beha

viou

r tes

ts40

% o

f DA

neur

ons

resc

ued,

be

havi

or im

prov

emen

t and

sev

ere

infla

mm

ator

y re

spon

se

[150

]

Nat

sum

e et

al.,

(2

001)

6-O

HD

A an

imal

mod

elH

SV-

GD

NF

and

HS

V-B

lc-2

Intra

nigr

alC

ell d

eath

and

TH

+ ce

ll co

unt

50%

cel

l sur

viva

l and

stro

ng in

flam

-m

ator

y re

spon

se[1

51]

Kiri

k et

al.,

(200

0)6-

OH

DA

anim

al m

odel

AAV

-GD

NF

Intra

stria

tal

Cel

l dea

th, T

H le

vel

and

beha

vior

test

sH

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CH A PTER 1

42

Other gene-therapy approaches in PD treatment

The trophic factor neurturin (NTN), a member of the GDNF family, was identified in 1996 and is an alternative candidate to GDNF gene therapy. Re-search on AAV–NTN proved that this molecule can provide structural and func-tional protection of nigrostriatal neurons [107]. These results formed the basis of a Phase I clinical trial by Ceregene with AAV–NTN delivery into the striatum of 12 advanced PD patients. Recent initial results showed good tolerance for the viral vector and reduction of the disease symptoms by approximately 40%. The company is preparing for a Phase II clinical trial [202]. Two other clinical trials have also begun using either AAV-glutamic acid decarboxylase (GAD; an enzyme that catalyzes the synthesis of the GABA neurotransmitter) gene delivery to the subthalamic nucleus of twelve patients [203] and AAV aromatic L-amino acid decarboxylase (AADC; an enzyme that converts L-DOPA into DA) delivery to the striatum [107,204]. No results are reported yet. AAV–GAD injected into primate PD models was well tolerated by the animals and proved to have potential thera-peutic characteristics [115].

Alzheimer’s disease

Gene therapy is also used as a therapeutic experimental approach for AD. The widespread neuronal and synaptic loss throughout the brain creates a chal-lenge to target the degeneration of neurons [34]. Thus, again, as in the cell-re-placement strategies, AD is very difficult to tackle with gene therapy due to its extended brain pathology. However, it is possible to target selected areas of neu-ronal degeneration, such as the nucleus basalis of Meynert, with neurotrophic factors that promote cell type-specific neuronal restoration. The cholinergic neurons in this area are known to degenerate in AD patients (Figure 2) and this finding has been corroborated by animal studies. A good candidate for neuro-trophic gene therapy is nerve growth factor (NGF), since it has been shown to be a trophic factor preventing both lesion-induced and agerelated atrophy of basal forebrain cholinergic (BFC) neurons in rodents and nonhuman primates [21,116,117]. Furthermore, it was shown that, in the Ts65Dn mouse, a model for Down’s syndrome, BFC neurons degenerate and that these mice had a deficit in NGF retrograde transport [118]. Down’s syndrome patients suffer from AD pa-thology, and the T65Dn can therefore also be a model for certain aspects of AD. Also, aged AD11 mice expressing NGF antibodies showed a dramatic neurode-generative phenotype similar to AD with both β-amyloid depositions and tau intracellular accumulation and degeneration of BFC cholinergic neurons [119]. These observations imply that NGF is an essential factor for the maintenance of the cholinergic system.


43

NGF protein delivery

The first clinical trial using NGF as a therapeutic molecule was performed with three AD patients, where the NGF protein was administered into the ventri-cles. Due to side effects, such as strong constant back pain and loss of weight, in all three patients, the trial was suspended [120]. The intranasal administration of NGF protein has been studied as an alternative to NGF delivery in the brain ventricles [121]. De Rosa and colleagues used an AD11 mouse model and showed that the intranasal route of administration of NGF did result in an improvement of the cognitive deficit [121]. A potential problem associated with this method of delivery is the nonspecific targeting. We know from both AD and PD research that the site of growth factor application is crucial for the success of the treat-ment as well as for the avoidance of side effects. NGF is known to cause pain, and its intranasal application may lead to the diffusion of NGF to unwanted sites.

NGF gene delivery

A first Phase I clinical trial with NGF gene therapy in AD has been complet-ed [7]. In this trial, eight patients were treated using an ‘ex vivo’ gene therapy strategy. Fibroblasts of the patients were genetically modified to express NGF and were grafted into the nucleus basalis of Meynert. Studies using rodent and primate models have demonstrated the feasibility, effectiveness and safety of this approach [21,116,122,123].

In this clinical trial, three potentially beneficial effects of NGF gene therapy in AD were observed. First, PET studies showed a widespread increase in glucose uptake by cortical neurons after 6–8 months. This suggests that the cholinergic projections to the cortex are re-activated by NGF. Second, a decrease in disease progression was presented based on cognition assessment with the use of the Mini-Mental State Examination scores. As this study progresses, the reduction in the rate of cognitive decline is hoped to become even more significant. Finally, NGF-induced ‘trophic’ effects in the brain, including robust cholinergic axonal sprouting around and into the site of the NGF expression, were noted. The au-thors realized that, although this is a small group and an open-label study with no placebo control, these results are very encouraging [7]. No negative effects of NGF administration (weight loss or pain) were noted in the AD patients, even up to 2 years post surgery. Direct AAV-mediated expression of NGF is the next step to determine the safety and effectiveness of gene therapy for AD [202].

Concern and criticism towards using NGF as a therapeutic molecule was presented, after it was shown that β-amyloid precursor protein may be induced by NGF [124]. In this scenario, rather than reducing neuronal degeneration, NGF would accelerate the pathology of AD. To test this hypothesis, Tuszynski and col-leagues designed an experiment where NGF was ex vivo delivered in the paren-chym of an aged primate brain [21]. This study not only found no increase of β-amyloid plaque deposition in NGF-treated monkeys, but also showed a reduc-

CH A PTER 1

44

tion of age-related atrophy of cholinergic neurons by NGF delivery into the basal forebrain.

Questions remain on the safety of long-term constant NGF expression in the human brain. Since the genetically modified fibroblasts have been implanted into the brains of the patients, there is no feasible way to control the NGF ex-pression if side effects would occur. Also, following injection of AAV–NGF into the brain, NGF will be expressed constitutively, leading to constant release of NGF from the transduced neural cells. This issue could be resolved by the use of a reg-ulatable viral vector [109,125]. The problem is that the tetracycline (Tet) repres-sor-protein that controls the transgene expression is a foreign protein that elicits an immunological response [126]. In the future, this problem could potentially be solved by using modified Tet repressor-proteins that are less immunogenic.

Conclusion & future perspective

The field of cell replacement and gene therapy as a new therapy for PD and AD has evolved enormously over the last years. Currently, no cure is available for these diseases. The application of embryonic and neural stem cells has opened new avenues to treat PD and AD, as well as the feasibility of delivering and ex-pressing genes encoding neurotrophic factors in the human brain, which can be regarded as a breakthrough. However, none of the cell-replacement and gene-therapy strategies reported so far result in complete rescuing or restoration and functional repair of the damaged brain areas. Targeting molecular mechanisms with current genome-wide genotyping of large populations of patients [127], large-scale gene expression profiling [128] and proteomics studies [129] will pinpoint novel molecular pathways involved in the process of degeneration in PD and AD. Furthermore, new developments, such as the identification of noncoding microRNAs [130,131], may have an impact on our understanding of the matura-tion of neuronal progenitor cells, recruitment of these cells for neural repair and promotion of neuronal regeneration. Our increasing knowledge on the molecu-lar mechanisms underlying PD and AD will enable the development of novel cell- and gene-based therapies. Each of these strategies, or perhaps a combination of the two, could result in genuine repair and rescue of degenerating DAergic and cholinergic neurons in the future, thereby ideally bringing not only symptom-atic relief but also stopping the progression of these neurodegenerative diseases (Figure 4).


45

Executive summary

• The early neuron-replacement therapies did relieve some of the symp-toms of Parkinson’s disease (PD) in several of the patients, but did not cure the disease.

• Animal models for PD and Alzheimer’s disease (AD) only partially mim-ic the disease, therefore better animal models covering the full clinical spectrum of PD and AD are required.

• The first clinical trial transplantating genetically engineered cells that secrete nerve growth factor has advanced the field of genuine restor-ative treatments for neurodegenerative diseases enormously.

• Novel direct gene-therapy approaches in AD patients have the potential to again bring the field a step forward.

• The discovery of adult human neuronal stem cells revealed a new and important population of cells that can be stimulated and targeted to treat PD and AD in the future.

• Advances in molecular analyses, such as population genotyping and genome-wide expression studies, will contribute to our understanding of the pathogenesis of PD and AD.

Acknowledgements

The authors would like to thank Prof. Dr DF Swaab (NIN, Amsterdam) for providing us with a picture of the NBM in Figure 2 and we are grateful to the Netherlands Brain Bank, (NIN, Amsterdam) for providing the human post-mor-tem brain material and for the neuropathological stainings.

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Bibliography1. Savitt JM, Dawson VL, Dawson TM: Diagnosis and treatment of Parkinson disease: mol-ecules to medicine. J. Clin. Invest. 116, 1744–1754 (2006).2. Ott A, Breteler MM, van Harskamp F, Stijnen T, Hofman A: Incidence and risk of dementia. The Rotterdam Study. Am. J. Epidemiol. 147, 574–580 (1998).3. Ferri CP, Prince M, Brayne C et al.: Global prevalence of dementia: a Delphi consensus study. Lancet 366, 2112–2117 (2005).4. de Lau LM, Breteler MM: Epidemiology of Parkinson’s disease. Lancet Neurol. 5, 525–535 (2006).5. Dorsey ER, Constantinescu R, Thompson JP et al.: Projected number of people with Par-kinson disease in the most populous nations, 2005 through 2030. Neurology 68, 384–386 (2007).6. Sayles M, Jain M, Barker RA: The cellular repair of the brain in Parkinson’s disease – past, present and future. Transpl. Immunol. 12, 321–342 (2004).7. Tuszynski MH, Thal L, Pay M et al.: A phase 1 clinical trial of nerve growth factor gene therapy for Alzheimer disease. Nat. Med. 11, 551–555 (2005).8. Cunningham LA, Su C: Astrocyte delivery of glial cell line-derived neurotrophic factor in a mouse model of Parkinson’s disease. Exp. Neurol. 174, 230–242 (2002).9. Braak H, Del Tredici K, Rub U, de Vos RA, Jansen Steur EN, Braak E: Staging of brain pathol-ogy related to sporadic Parkinson’s disease. Neurobiol. Aging 24, 197–211 (2003).10. Poskanzer DC, Schwab RS: Cohort analysis of Parkinson’s syndrome: evidence for a single etiology related to subclinical infection about 1920. J. Chronic Dis. 16, 961–973(1963).11. Leroy E, Boyer R, Auburger G et al.: The ubiquitin pathway in Parkinson’s disease. Nature 395, 451–452 (1998).12. Hardy J, Cai H, Cookson MR, Gwinn-Hardy K, Singleton A: Genetics of Parkinson’s disease and parkinsonism. Ann. Neurol. 60, 389–398 (2006).13. Maraganore DM, de Andrade M, Lesnick TG et al.: High-resolution whole genome associa-tion study of Parkinson disease. Am. J. Hum. Genet. 77, 685–693 (2005).14. Mizuta I, Satake W, Nakabayashi Y et al.: Multiple candidate gene analysis identifies alpha-synuclein as a susceptibility gene for sporadic Parkinson’s disease. Hum. Mol. Genet. 15, 1151–1158 (2006).15. Clarimon J, Scholz S, Fung HC et al.: Conflicting results regarding the semaphoring gene (SEMA5A) and the risk for Parkinson disease. Am. J. Hum. Genet. 78, 1082–1084; author reply 1092–1094 (2006).16. Schapira AH, Bezard E, Brotchie J et al.: Novel pharmacological targets for the treatment of Parkinson’s disease. Nat. Rev. Drug Discov. 5, 845–854 (2006).17. Muller FJ, Snyder EY, Loring JF: Gene therapy: can neural stem cells deliver? Nat. Rev. Neurosci. 7, 75–84 (2006).18. Benabid AL, Koudsie A, Pollak P et al.: Future prospects of brain stimulation. Neurol. Res. 22, 237–246 (2000).19. Braak H, Braak E: Neuropathological stageing of Alzheimer-related changes. Acta Neuro-pathol. 82, 239–259 (1991).


47

20. Counts SE, Nadeem M, Wuu J, Ginsberg SD, Saragovi HU, Mufson EJ: Reduction of cortical TrkA but not p75(NTR) protein in early-stage Alzheimer’s disease. Ann. Neurol. 56, 520–531 (2004).21. Tuszynski MH, Smith DE, Roberts J, McKay H, Mufson E: Targeted intraparenchymal delivery of human NGF by gene transfer to the primate basal forebrain for 3 months does not accelerate beta-amyloid plaque deposition. Exp. Neurol. 154, 573–582 (1998).22. Blennow K, de Leon MJ, Zetterberg H: Alzheimer’s disease. Lancet 368, 387–403 (2006).23. White AR, Barnham KJ, Bush AI: Metal homeostasis in Alzheimer’s disease. Expert Rev. Neurother. 6, 711–722 (2006).24. Adlard PA, Bush AI: Metals and Alzheimer’s disease. J. Alzheimers Dis. 10, 145–163 (2006).25. Hardy J: A hundred years of Alzheimer’s disease research. Neuron 52, 3–13 (2006).26. Reiman EM, Caselli RJ, Yun LS et al.: Preclinical evidence of Alzheimer’s disease in per-sons homozygous for the δ4 allele for apolipoprotein E. N. Engl. J. Med. 334, 752–758 (1996).27. Rogaeva E, Meng Y, Lee JH et al.: The neuronal sortilin-related receptor SORL1 is geneti-cally associated with Alzheimer disease. Nat. Genet. 39, 168–177 (2007).28. Palotas A, Kalman J: Candidate susceptibility genes in Alzheimer’s disease are at high risk for being forgotten – they don’t give peace of mind. Curr. Drug Metab. 7, 273–293 (2006).29. de Vrij FM, Fischer DF, van Leeuwen FW, Hol EM: Protein quality control in Alzheimer’s disease by the ubiquitin proteasome system. Prog. Neurobiol. 74, 249–270 (2004).30. Kaduszkiewicz H, Zimmermann T, Beck-Bornholdt HP, van den Bussche H: Cholinesterase inhibitors for patients with Alzheimer’s disease: systematic review of randomised clinical trials. BMJ 331, 321–327 (2005).31. Areosa SA, Sherriff F, McShane R: Memantine for dementia. Cochrane Database Syst. Rev. CD003154 (2005).32. Dowling GA, Mastick J, Hubbard EM, Luxenberg JS, Burr RL: Effect of timed bright light treatment for rest-activity disruption in institutionalized patients with Alzheimer’s disease. Int. J. Geriatr. Psychiatry 20, 738–743 (2005).33. Swaab DF, Dubelaar EJ, Scherder EJ, van Someren EJ, Verwer RW: Therapeutic strategies for Alzheimer disease: focus on neuronal reactivation of metabolically impaired neurons. Alzheimer Dis. Assoc. Disord. 17(Suppl. 4), S114–S122 (2003).34. Lindvall O, Kokaia Z: Stem cells for the treatment of neurological disorders. Nature 441, 1094–1096 (2006).35. Thompson L, Barraud P, Andersson E, Kirik D, Bjorklund A: Identification of dopaminer-gic neurons of nigral and ventral tegmental area subtypes in grafts of fetal ventral mesen-cephalon based on cell morphology, protein expression, and efferent projections. J. Neurosci. 25, 6467–6477 (2005).36. Sorensen AT, Thompson L, Kirik D, Bjorklund A, Lindvall O, Kokaia M: Functional proper-ties and synaptic integration of genetically labeled dopaminergic neurons in intrastriatal grafts. Eur. J. Neurosci. 21, 2793–2799 (2005).37. Backlund EO, Granberg PO, Hamberger B et al.: Transplantation of adrenal medullary tis-sue to striatum in parkinsonism. First clinical trials. J. Neurosurg. 62, 169–173 (1985).38. Freed CR, Greene PE, Breeze RE et al.: Transplantation of embryonic dopamine neurons for severe Parkinson’s disease. N. Engl. J. Med. 344, 710–719 (2001).

CH A PTER 1

48

39. Olanow CW, Goetz CG, Kordower JH et al.: A double-blind controlled trial of bilateral fetal nigral transplantation in Parkinson’s disease. Ann. Neurol. 54, 403–414 (2003).40. Piccini P, Brooks DJ, Bjorklund A et al.: Dopamine release from nigral transplants visual-ized in vivo in a Parkinson’s patient. Nat. Neurosci. 2, 1137–1140 (1999).41. Lindvall O, Hagell P: Cell therapy and transplantation in Parkinson’s disease. Clin. Chem. Lab. Med. 39, 356–361 (2001). 42. Winkler C, Kirik D, Bjorklund A: Cell transplantation in Parkinson’s disease: how can we make it work? Trends Neurosci. 28, 86–92 (2005).43. Fine A, Dunnett SB, Bjorklund A, Iversen SD: Cholinergic ventral forebrain grafts into the neocortex improve passive avoidance memory in a rat model of Alzheimer disease. Proc. Natl Acad. Sci. USA 82, 5227–5230 (1985).44. Itakura T, Umemoto M, Kamei I et al.: Autotransplantation of peripheral cholinergic neu-rons into the brains of Alzheimer model rats. Acta Neurochir. 115, 127–132 (1992).45. Martin GR: Isolation of a pluripotent cell line from early mouse embryos cultured in medium conditioned by teratocarcinoma stem cells. Proc. Natl Acad. Sci. USA 78, 7634–7638 (1981).46. Thomson JA, Kalishman J, Golos TG et al.: Isolation of a primate embryonic stem cell line. Proc. Natl Acad. Sci. USA 92, 7844–7848 (1995).47. Thomson JA, Itskovitz-Eldor J, Shapiro SS et al.: Embryonic stem cell lines derived from human blastocysts. Science 282, 1145–1147 (1998).48. Lee SH, Lumelsky N, Studer L, Auerbach JM, McKay RD: Efficient generation of midbrain and hindbrain neurons from mouse embryonic stem cells. Nat. Biotechnol. 18, 675–679 (2000).49. Kim JH, Auerbach JM, Rodriguez-Gomez JA et al.: Dopamine neurons derived from em-bryonic stem cells function in an animal model of Parkinson’s disease. Nature 418, 50–56 (2002).50. Barberi T, Klivenyi P, Calingasan NY et al.: Neural subtype specification of fertilization and nuclear transfer embryonic stem cells and application in parkinsonian mice. Nat. Bio-technol. 21, 1200–1207 (2003).51. Andersson E, Tryggvason U, Deng Q et al.: Identification of intrinsic determinants of mid-brain dopamine neurons. Cell 124, 393–405 (2006).52. Kawasaki H, Mizuseki K, Nishikawa S et al.: Induction of midbrain dopaminergic neurons from ES cells by stromal cell-derived inducing activity. Neuron 28, 31–40 (2000).53. Kawasaki H, Suemori H, Mizuseki K et al.: Generation of dopaminergic neurons and pig-mented epithelia from primate ES cells by stromal cell-derived inducing activity. Proc. Natl Acad. Sci. USA 99, 1580–1585 (2002).54. Smidt MP, Burbach JP: How to make a mesodiencephalic dopaminergic neuron. Nat. Rev. Neurosci. 8, 21–32 (2007).55. Burbach JP, Smidt MP: Molecular programming of stem cells into mesodiencephalic dopa-minergic neurons. Trends Neurosci. 29, 601–603 (2006).56. Wang TT, Jing AH, Luo XY et al.: Neural stem cells: isolation and differentiation into cho-linergic neurons. Neuroreport 17, 1433–1436 (2006).


49

57. Gossrau G, Thiele J, Konang R, Schmandt T, Brustle O: BMP-mediated modulation of lin-eage diversification during neural differentiation of embryonic stem cells. Stem Cells 25(4), 939–949 (2007).58. Wang HF, Liu FC: Developmental restriction of the LIM homeodomain transcription fac-tor Islet-1 expression to cholinergic neurons in the rat striatum. Neuroscience 103, 999–1016 (2001).59. Roy NS, Cleren C, Singh SK, Yang L, Beal MF, Goldman SA: Functional engraftment of hu-man ES cell-derived dopaminergic neurons enriched by coculture with telomerase-immor-talized midbrain astrocytes. Nat. Med. 12, 1259–1268 (2006).60. Ben-Hur T, Idelson M, Khaner H et al.: Transplantation of human embryonic stem cell-derived neural progenitors improves behavioral deficit in Parkinsonian rats. Stem Cells 22, 1246–1255 (2004).61. Schulz TC, Noggle SA, Palmarini GM et al.: Differentiation of human embryonic stem cells to dopaminergic neurons in serum-free suspension culture. Stem Cells 22, 1218 1238 (2004).62. Freed CR: Will embryonic stem cells be a useful source of dopamine neurons for trans-plant into patients with Parkinson’s disease? Proc. Natl Acad. Sci. USA 99, 1755–1757 (2002).63. Taylor H, Minger SL: Regenerative medicine in Parkinson’s disease: generation of mesen-cephalic dopaminergic cells from embryonic stem cells. Curr. Opin. Biotechnol. 16, 487–492 (2005).64. Svendsen CN, Smith AG: New prospects for human stem-cell therapy in the nervous sys-tem. Trends Neurosci. 22, 357–364 (1999).65. Keirstead HS, Nistor G, Bernal G et al.: Human embryonic stem cell-derived oligodendro-cyte progenitor cell transplants remyelinate and restore locomotion after spinal cord injury. J. Neurosci. 25, 4694–7405 (2005).66. Zandonella C: Stem-cell therapies: the first wave. Nature 435, 877–878 (2005).67. Altman J, Das GD: Autoradiographic and histological evidence of postnatal hippocampal neurogenesis in rats. J. Comp. Neurol. 124, 319–335 (1965).68. Altman J: Autoradiographic and histological studies of postnatal neurogenesis. IV. Cell proliferation and migration in the anterior forebrain, with special reference to persisting neurogenesis in the olfactory bulb. J. Comp. Neurol. 137, 433–457 (1969).69. Emsley JG, Mitchell BD, Kempermann G, Macklis JD: Adult neurogenesis and repair of the adult CNS with neural progenitors, precursors, and stem cells. Prog. Neurobiol. 75, 321–341 (2005).70. Kaplan MS, Bell DH: Mitotic neuroblasts in the 9-day-old and 11-month-old rodent hip-pocampus. J. Neurosci. 4, 1429–1441 (1984).71. Eriksson PS, Perfilieva E, Bjork-Eriksson T et al.: Neurogenesis in the adult human hip-pocampus. Nat. Med. 4, 1313–1317 (1998).72. Doetsch F, Caille I, Lim DA, Garcia-Verdugo JM, Alvarez-Buyll A: Subventricular zone astrocytes are neural stem cells in the adult mammalian brain. Cell 97, 703–716 (1999).73. Laywell ED, Rakic P, Kukekov VG, Holland EC, Steindler DA: Identification of a multipotent astrocytic stem cell in the immature and adult mouse brain. Proc. Natl Acad. Sci. USA 97, 13883–13888 (2000).74. Gould E, Reeves AJ, Graziano MS, Gross CG: Neurogenesis in the neocortex of adult pri-mates. Science 286, 548–552 (1999).

CH A PTER 1

50

75. Lie DC, Dziewczapolski G, Willhoite AR, Kaspar BK, Shults CW, Gage FH: The adult sub-stantia nigra contains progenitor cells with neurogenic potential. J. Neurosci. 22, 6639–6649 (2002).76. Zhao M, Momma S, Delfani K et al.: Evidence for neurogenesis in the adult mammalian substantia nigra. Proc. Natl Acad. Sci. USA 100, 7925–7930 (2003). 77. Xu Y, Tamamaki N, Noda T et al.: Neurogenesis in the ependymal layer of the adult rat 3rd ventricle. Exp. Neurol. 192, 251–264 (2005).78. Lie DC, Song H, Colamarino SA, Ming GL, Gage FH: Neurogenesis in the adult brain: new strategies for central nervous system diseases. Annu. Rev. Pharmacol. Toxicol. 44, 399–421 (2004).79. Sanai N, Tramontin AD, Quinones-Hinojosa A et al.: Unique astrocyte ribbon in adult hu-man brain contains neural stem cells but lacks chain migration. Nature 427, 740–744 (2004).80. Curtis MA, Kam M, Nannmark U et al.: Human neuroblasts migrate to the olfactory bulb via a lateral ventricular extension. Science 315, 1243–1249 (2007).81. Flax JD, Aurora S, Yang C et al.: Engraftable human neural stem cells respond to devel-opmental cues, replace neurons, and express foreign genes. Nat. Biotechnol. 16, 1033–1039 (1998).82. Jain M, Armstrong RJ, Elneil S, Barker RA: Transplanted human neural precursor cells migrate widely but show no lesion-specific tropism in the 6-hydroxydopamine rat model of Parkinson’s disease. Cell Transplant. 15, 579–593 (2006).83. Walton NM, Sutter BM, Chen HX et al.: Derivation and large-scale expansion of multipo-tent astroglial neural progenitors from adult human brain. Development 133, 3671–3681 (2006).84. Roussa E, Wiehle M, Dunker N, Becker-Katins S, Oehlke O, Krieglstein K: Transforming growth factor β is required for differentiation of mouse mesencephalic progenitors into dopaminergic neurons in vitro and in vivo: ectopic induction in dorsal mesencephalon. Stem Cells 24, 2120–2129 (2006).85. Cao Q, Benton RL, Whittemore SR: Stem cell repair of central nervous system injury. J. Neurosci. Res. 68, 501–510 (2002).86. Lepore AC, Neuhuber B, Connors TM et al.: Long-term fate of neural precursor cells fol-lowing transplantation into developing and adult CNS. Neuroscience 139, 513–530 (2006).87. Lepore AC, Han SS, Tyler-Polsz CJ, Cai J, Rao MS, Fischer I: Differential fate of multipotent and lineage-restricted neural precursors following transplantation into the adult CNS. Neu-ron Glia Biol. 1, 113–126 (2004).88. Burnstein RM, Foltynie T, He X, Menon DK, Svendsen CN, Caldwell MA: Differentiation and migration of long term expanded human neural progenitors in a partial lesion model of Parkinson’s disease. Int. J. Biochem. Cell Biol. 36, 702–713 (2004).89. Vescovi AL, Galli R, Reynolds BA: Brain tumour stem cells. Nat. Rev. Cancer 6, 425–436 (2006).90. Ourednik J, Ourednik V, Lynch WP, Schachner M, Snyder EY: Neural stem cells display an inherent mechanism for rescuing dysfunctional neurons. Nat. Biotechnol. 20, 1103–1110 (2002).


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91. Tai YT, Svendsen CN: Stem cells as a potential treatment of neurological disorders. Curr. Opin. Pharmacol. 4, 98–104 (2004).92. Leavitt BR, Hernit-Grant CS, Macklis JD: Mature astrocytes transform into transitional radial glia within adult mouse neocortex that supports directed migration of transplanted immature neurons. Exp. Neurol. 157, 43–57 (1999).93. Jin K, Wang X, Xie L et al.: Evidence for stroke-induced neurogenesis in the human brain. Proc. Natl Acad. Sci. USA 103, 13198–13202 (2006).94. Akerud P, Canals JM, Snyder EY, Arenas E: Neuroprotection through delivery of glial cell line-derived neurotrophic factor by neural stem cells in a mouse model of Parkinson’s dis-ease. J. Neurosci. 21, 8108–8118 (2001).95. Park KI, Ourednik J, Ourednik V et al.: Global gene and cell replacement strategies via stem cells. Gene Ther. 9, 613–624 (2002).96. Consiglio A, Gritti A, Dolcetta D et al.: Robust in vivo gene transfer into adult mammalian neural stem cells by lentiviral vectors. Proc. Natl Acad. Sci. USA 101, 14835–14840 (2004).97. Brazelton TR, Rossi FM, Keshet GI, Blau HM: From marrow to brain: expression of neuro-nal phenotypes in adult mice. Science 290, 1775–1779 (2000).98. Cogle CR, Yachnis AT, Laywell ED et al.: Bone marrow transdifferentiation in brain after transplantation: a retrospective study. Lancet 363, 1432–1437 (2004).99. Sanchez-Ramos J, Song S, Cardozo-Pelaez F et al.: Adult bone marrow stromal cells dif-ferentiate into neural cells in vitro. Exp. Neurol. 164, 247–256 (2000).100. Schwarz EJ, Alexander GM, Prockop DJ, Azizi SA: Multipotential marrow stromal cells transduced to produce L-DOPA: engraftment in a rat model of Parkinson disease. Hum. Gene Ther. 10, 2539–2549 (1999).101. Terada N, Hamazaki T, Oka M et al.: Bone marrow cells adopt the phenotype of other cells by spontaneous cell fusion. Nature 416, 542–545 (2002).102. Ying QL, Nichols J, Evans EP, Smith AG: Changing potency by spontaneous fusion. Nature 416, 545–548 (2002).103. Mezey E, Key S, Vogelsang G, Szalayova I, Lange GD, Crain B: Transplanted bone marrow generates new neurons in human brains. Proc. Natl Acad. Sci. USA 100, 1364–1369 (2003).104. Crain BJ, Tran SD, Mezey E: Transplanted human bone marrow cells generate new brain cells. J. Neurol. Sci. 233, 121–123 (2005).105. Kordower JH: In vivo gene delivery of glialcell line-derived neurotrophic factor forParkinson’s disease. Ann. Neurol. 53(Suppl. 3), S120–S134 (2003).106. Tuszynski MH, U HS, Alksne J et al.: Growth factor gene therapy for Alzheimer disease. Neurosurg. Focus 13, e5 (2002).107. Dass B, Olanow CW, Kordower JH: Gene transfer of trophic factors and stem cell grafting as treatments for Parkinson’s disease. Neurology 66, S89–S103 (2006). 108. Hendriks WT, Ruitenberg MJ, Blits B, Boer GJ, Verhaagen J: Viral vector-mediated gene transfer of neurotrophins to promote regeneration of the injured spinal cord. Prog.Brain Res. 146, 451–476 (2004).109. Blesch A, Conner JM, Tuszynski MH: Modulation of neuronal survival and axonal growth in vivo by tetracycline-regulated neurotrophin expression. Gene Ther. 8, 954–960 (2001).

CH A PTER 1

52

110. Hoffer BJ, Hoffman A, Bowenkamp K et al.: Glial cell line-derived neurotrophic factor reverses toxin-induced injury to midbrain dopaminergic neurons in vivo. Neurosci. Lett. 182, 107–111 (1994).111. Kordower JH, Palfi S, Chen EY et al.: Clinicopathological findings following intraventric-ular glial-derived neurotrophic factor treatment in a patient with Parkinson’s disease. Ann. Neurol. 46, 419–424 (1999).112. Nutt JG, Burchiel KJ, Comella CL et al.: Randomized, double-blind trial of glial cell line-derived neurotrophic factor (GDNF) in PD. Neurology 60, 69–73 (2003).113. Gill SS, Patel NK, Hotton GR et al.: Direct brain infusion of glial cell line-derived neuro-trophic factor in Parkinson disease. Nat. Med. 9, 589–595 (2003).114. Slevin JT, Gerhardt GA, Smith CD, Gash DM, Kryscio R, Young B: Improvement of bilateral motor functions in patients with Parkinson disease through the unilateral intraputaminal infusion of glial cell line-derived neurotrophic factor. J. Neurosurg. 102, 216–222 (2005).115. Emborg ME, Carbon M, Holden JE et al.: Subthalamic glutamic acid decarboxylase gene therapy: changes in motor function and cortical metabolism. J. Cereb. Blood Flow Metab. 27, 501–509 (2006).116. Tuszynski MH, Roberts J, Senut MC, U HS, Gage FH: Gene therapy in the adult primate brain: intraparenchymal grafts of cells genetically modified to produce nerve growth factor prevent cholinergic neuronal degeneration. Gene Ther. 3, 305–314 (1996).117. Tuszynski MH, Blesch A: Nerve growth factor: from animal models of cholinergic neu-ronal degeneration to gene therapy in Alzheimer’s disease. Prog. Brain Res. 146, 441–449 (2004).118. Salehi A, Delcroix JD, Swaab DF: Alzheimer’sdisease and NGF signaling. J. Neural Transm.111, 323–345 (2004).119. Capsoni S, Giannotta S, Cattaneo A: β-amyloid plaques in a model for sporadic Alzheim-er’s disease based on transgenic antinerve growth factor antibodies. Mol. Cell. Neurosci. 21, 15–28 (2002).120. Eriksdotter Jonhagen M, Nordberg A, Amberla K et al.: Intracerebroventricular infusion of nerve growth factor in three patients with Alzheimer’s disease. Dement. Geriatr. Cogn. Disord. 9, 246–257 (1998).121. De Rosa R, Garcia AA, Braschi C et al.: Intranasal administration of nerve growth factor (NGF) rescues recognition memory deficits in AD11 anti-NGF transgenic mice. Proc. Natl Acad. Sci. USA 102, 3811–3816 (2005).122. Chen KS, Gage FH: Somatic gene transfer of NGF to the aged brain: behavioral and mor-phological amelioration. J. Neurosci. 15, 2819–2825 (1995).123. Martinez-Serrano A, Fischer W, Bjorklund A: Reversal of age-dependent cognitive impairments and cholinergic neuron atrophy by NGF-secreting neural progenitors grafted to the basal forebrain. Neuron 15, 473–484 (1995).124. Mobley WC, Neve RL, Prusiner SB, McKinley MP: Nerve growth factor increases mRNA levels for the prion protein and the β- amyloid protein precursor in developing hamster brain. Proc. Natl Acad. Sci. USA 85, 9811–9815 (1988).125. Szulc J, Wiznerowicz M, Sauvain MO, Trono D, Aebischer P: A versatile tool for condi-tional gene expression and knockdown. Nat. Methods 3, 109–116 (2006).


53

126. Latta-Mahieu M, Rolland M, Caillet C et al.: Gene transfer of a chimeric trans-activator is immunogenic and results in short-lived transgene expression. Hum. Gene Ther. 13, 1611–1620 (2002).127. Fung HC, Scholz S, Matarin M et al.: Genome-wide genotyping in Parkinson’s disease and neurologically normal controls: first stage analysis and public release of data. Lancet Neurol. 5, 911–916 (2006).128. Mandel S, Grunblatt E, Riederer P et al.: Gene expression profiling of sporadicParkinson’s disease substantia nigra pars compacta reveals impairment of ubiquitinprotea-some subunits, SKP1A, aldehyde dehydrogenase, and chaperone HSC 70. Ann. NY Acad. Sci. 1053, 356–375 (2005).129. Chen JY, Shen C, Sivachenko AY: Mining Alzheimer disease relevant proteins from inte-grated protein interactome data. Pac. Symp. Biocomput. 367–378 (2006).130. Cao X, Yeo G, Muotri AR, Kuwabara T, Gage FH: Noncoding RNAs in the mammalian central nervous system. Annu. Rev. Neurosci. 29, 77–103 (2006).131. Kuwabara T, Hsieh J, Nakashima K, Taira K, Gage FH: A small modulatory dsRNA speci-fies the fate of adult neural stem cells. Cell 116, 779–793 (2004).132. Deacon T, Dinsmore J, Costantini LC, Ratliff J, Isacson O: Blastula-stage stem cells can differentiate into dopaminergic and serotonergic neurons after transplantation. Exp. Neurol. 149, 28–41 (1998).133. Bjorklund LM, Sanchez-Pernaute R, Chung S et al.: Embryonic stem cells develop into functional dopaminergic neurons after transplantation in a Parkinson rat model. Proc. Natl Acad. Sci. USA 99, 2344–2349 (2002).134. Takagi Y, Takahashi J, Saiki H et al.: Dopaminergic neurons generated from monkey embryonic stem cells function in a Parkinson primate model. J. Clin. Invest. 115, 102–109 (2005).135. Rodriguez-Gomez JA, Lu JQ, Velasco I et al.: Persistent dopamine functions of neurons derived from embryonic stem cells in a rodent model of Parkinson disease. Stem Cells 25, 918–928 (2007).136. Park S, Lee KS, Lee YJ et al.: Generation of dopaminergic neurons in vitro from human embryonic stem cells treated with neurotrophic factors. Neurosci. Lett. 359, 99–103 (2004).137. Perrier AL, Tabar V, Barberi T et al.: Derivation of midbrain dopamine neurons from hu-man embryonic stem cells. Proc. Natl Acad. Sci. USA 101, 12543–12548 (2004).138. Yan Y, Yang D, Zarnowska ED et al.: Directed differentiation of dopaminergic neuronal subtypes from human embryonic stem cells. Stem Cells 23, 781–790 (2005).139. Zeng X, Cai J, Chen J et al.: Dopaminergic differentiation of human embryonic stem cells. Stem Cells 22, 925–940 (2004).140. Park CH, Minn YK, Lee JY et al.: In vitro and in vivo analyses of human embryonic stem cell-derived dopamine neurons. J. Neurochem. 92, 1265–1276 (2005).141. Brederlau A, Correia AS, Anisimov SV et al.: Transplantation of human embryonic stem cell-derived cells to a rat model of Parkinson’s disease: effect of in vitro differentiation on graft survival and teratoma formation. Stem Cells 24, 1433–1440 (2006).142. Martinat C, Bacci JJ, Leete T et al.: Cooperative transcription activation by Nurr1 and Pitx3 induces embryonic stem cell maturation to the midbrain dopamine neuron phenotype. Proc. Natl Acad. Sci. USA 103, 2874–2879 (2006).

CH A PTER 1

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143. Sonntag KC, Pruszak J, Yoshizaki T, van Arensbergen J, Sanchez-Pernaute R, Isacson O: Enhanced yield of neuroepithelial precursors and midbrain-like dopaminergic neurons from human embryonic stem cells using the bone morphogenic protein antagonist noggin. Stem Cells 25, 411–418 (2007).144. Iacovitti L, Donaldson AE, Marshall CE, Suon S, Yang M: A protocol for the differentiation of human embryonic stem cells into dopaminergic neurons using only chemically defined human additives: studies in vitro and in vivo. Brain Res. 1127, 19–25 (2007).145. Sanchez-Pernaute R, Studer L, Bankiewicz KS, Major EO, McKay RD: In vitro generation and transplantation of precursor-derived human dopamine neurons. J. Neurosci. Res. 65, 284–288 (2001).146. Svendsen CN, Clarke DJ, Rosser AE, Dunnett SB: Survival and differentiation of rat and human epidermal growth factor responsive precursor cells following grafting into the lesioned adult central nervous system. Exp. Neurol. 137, 376–388 (1996).147. Snyder EY, Yoon C, Flax JD, Macklis JD: Multipotent neural precursors can differentiate toward replacement of neurons undergoing targeted apoptotic degeneration in adult mouse neocortex. Proc. Natl Acad. Sci. USA 94, 11663–11668 (1997). 148. Ahn TB, Kim JM, Kwon KM, Lee SH, Jeon BS: Survival and migration of transplanted neural stem cell-derived dopamine cells in the brain of parkinsonian rat. Int. J. Neurosci. 114, 575–585 (2004).149. Kirik D, Rosenblad C, Bjorklund A: Preservation of a functional nigrostriatal dopamine pathway by GDNF in the intrastriatal 6-OHDA lesion model depends on the site of adminis-tration of the trophic factor. Eur. J. Neurosci. 12, 3871–3882 (2000).150. Choi-Lundberg DL, Lin Q, Schallert T et al.: Behavioral and cellular protection of rat dopaminergic neurons by an adenoviral vector encoding glial cell line-derived neurotrophic factor. Exp. Neurol. 154, 261–275 (1998).151. Natsume A, Mata M, Goss J et al.: Bcl-2 and GDNF delivered by HSV-mediated gene trans-fer act additively to protect dopaminergic neurons from 6-OHDA-induced degeneration. Exp. Neurol. 169, 231–238 (2001).152. Kirik D, Rosenblad C, Bjorklund A, Mandel RJ: Long-term rAAV-mediated gene transfer of GDNF in the rat Parkinson’s model: intrastriatal but not intranigral transduction promotes functional regeneration in the lesioned nigrostriatal system. J. Neurosci. 20, 4686–4700 (2000).153. Georgievska B, Kirik D, Rosenblad C, Lundberg C, Bjorklund A: Neuroprotection in the rat Parkinson model by intrastriatal GDNF gene transfer using a lentiviral vector. Neurore-port 13, 75–82 (2002).154. Kojima H, Abiru Y, Sakajiri K et al.: Adenovirus-mediated transduction with human glial cell line-derived neurotrophic factor gene prevents 1-methyl-4-phenyl- 1,2,3,6-tetrahydro-pyridine-induced dopamine depletion in striatum of mouse brain. Biochem. Biophys. Res. Commun. 238, 569–573 (1997).155. Eslamboli A, Cummings RM, Ridley RM et al.: Recombinant adeno-associated viral vector (rAAV) delivery of GDNF provides protection against 6-OHDA lesion in the common marmoset monkey (Callithrix jacchus). Exp. Neurol. 184, 536–548 (2003).


55

156. Lo Bianco C, Deglon N, Pralong W, Aebischer P: Lentiviral nigral delivery of GDNF does not prevent neurodegeneration in a genetic rat model of Parkinson’s disease. Neurobiol. Dis. 17, 283–289 (2004).157. Wang L, Muramatsu S, Lu Y et al.: Delayed delivery of AAV–GDNF prevents nigral neuro-degeneration and promotes functional recovery in a rat model of Parkinson’s disease. Gene Ther. 9, 381–389 (2002).158. Kordower JH, Emborg ME, Bloch J et al.: Neurodegeneration prevented by lentiviral vec-tor delivery of GDNF in primate models of Parkinson’s disease. Science 290, 767–773 (2000).159. Palfi S, Leventhal L, Chu Y et al.: Lentivirally delivered glial cell line-derived neuro-trophic factor increases the number of striatal dopaminergic neurons in primate models of nigrostriatal degeneration. J. Neurosci. 22, 4942–4954 (2002).160. Mendez I, Sanchez-Pernaute R, Cooper O et al.: Cell type analysis of functional fetal dopamine cell suspension transplants in the striatum and substantia nigra of patients with Parkinson’s disease. Brain 128, 1498–1510 (2005).161. Swaab DF: Nucleus basalis of Meynert (NBM) and diagonal band of Broca (DBB). In: Handbook of the Clinical Neurology, Volume 79; The human hypothalamus. Basic and Clinical aspects. Part I: Nuclei of the hypothalamus. Aminoff MJ, Boller F, Swaab DF (Eds). Elsevier, Amsterdam, The Netherlands 39–59 (2003).162. Laywell ED, Kearns SM, Zheng T et al.: Neuron-to-astrocyte transition: phenotypic fluid-ity and the formation of hybrid asterons in differentiating neurospheres. J. Comp. Neurol. 493, 321–333 (2005).163. Hol EM, Roelofs RF, Moraal E et al. : Neuronal expression of GFAP in patients with Al-zheimer pathology and identification of novel GFAP splice forms. Mol. Psychiatry 8, 786–796 (2003).

Websites

201. Amgen, Inc. www.amgen.com202. Ceregene www.ceregene.com203. Neurologix, Inc. www.neurologix.net204. Genzyme Corporation www.genzyme.com205. Titan Pharmaceuticals, Inc. www.titanpharm.com

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CHAPTER 2

Gene expression profiling and Parkinson’s disease:

target selection and mRNA and protein localization in human

Substantia Nigra

J.A. Korecka1, U.A. Unmehopa2, R. Balesar2, J. van Heerikhuize3, J.J. Anink2, C. Vlaskamp2,

G.F. Meerhoff1,a, D.F. Swaab2, K. Bossers1, J. Verhaagen1


Amsterdam, The Netherlands2 Neuropsychiatric Disorders, Netherlands Institute for Neuroscience, An Institute of the Royal

Netherlands Academy of Arts and Sciences, Meibergdreef 47, 1105BA,Amsterdam, The Netherlands

3 Technology and Software Development, Netherlands Institute for Neuroscience, An Institute of the Royal Netherlands Academy of Arts and Sciences, Meibergdreef 47, 1105BA,

Amsterdam, The NetherlandsA Present address: Center for Neuroscience, Swammerdam Institute for Life Sciences, University of

Amsterdam, Amsterdam, The Netherlands

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CH A PTER 2

Abstract

Parkinson’s disease (PD) is a multifactorial neurodegenerative disease, mainly characterized by a movement disorder caused by progressive loss of do-paminergic neurons in the substantia nigra (SN) and a decrease in striatal dopa-mine levels. The etiology of sporadic PD is still unknown. In a recent publication we demonstrated alterations in the expression of 287 genes in relatively spared PD SN tissue by using a microarray approach (Bossers et al., 2009). This chapter describes the ground-work that is necessary in order to start future functional studies on the dysregulated genes identified in the microarray study. Firstly, from the total list of 287 dysregulated genes we selected 79 target genes that are potentially involved in the degeneration of dopaminergic (DAergic) neurons in PD. These genes were selected by means of gene ontology, Ingenuity pathway analysis (IPA) and literature study and have a role in one or more of the following processes: cell death, neurotrophic support, synaptic transmission, mitochon-drial activity and axon guidance. Secondly, we studied the localization of a sub-set of these genes and demonstrated that they are almost exclusively expressed in human DAergic neurons and not in microglia cells or astrocytes. Therefore, most genes identified in our microarray study do apparently function in neurons and future studies on their role in PD should be performed in a neuronal cellular model. Introduction

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Introduction

Parkinson’s disease (PD) is the second most prevalent age related neurode-generative disease. Patients suffer from both motor and cognitive dysfunction. The motor behavior deficits consist of tremor at rest, muscle rigidity, postural instability, akinesia or bradykinesia (Dauer and Przedborski, 2003), and are of-ten accompanied by flexed posture and freezing (Jankovic, 2008). Cognitive dys-functions consist of language difficulties (Nikolaus et al., 2009), mood disorders, sleep impairment and dementia, autonomic dysfunctions, pain and sensory dis-turbances (Olanow et al., 2009). It is generally accepted that the motor symp-toms can be attributed to the best studied neuropathological hallmark of PD: the selective loss of the dopaminergic (DAergic) neurons in the substantia nigra pars compacta (SN). Another pathological hallmark of the disease is the formation of Lewy bodies (ubiquitin and α-synuclein containing cytoplasmic inclusions) throughout the brain during the development of the disease, starting in the olfac-tory bulb and lower brainstem areas and ascending to the higher cortical levels of the brain (Spillantini et al., 1997; Braak et al., 2003).

The etiology of PD appears to be multifactorial, with both genetic and envi-ronmental components playing a major role (Gorell et al., 2004). Mutations have been found in several genes (SNCA, PARK2, DJ-1, PINK1, LRRK2 and PARK9 (Har-dy et al., 2006; Bonifati, 2007)), that cause rare, familial forms of PD. Single nu-cleotide polymorphisms in UCHL1, SNCA, SEMA5A and MAPT are also associated with increased susceptibility for PD (Leroy et al., 1998; Maraganore et al., 2005; Mizuta et al., 2006; Simon-Sanchez et al., 2009). The precise cellular functions of these genes are the subject of study of many laboratories. Interestingly, however, several of these genes are associated with dysregulated protein aggregation, el-evated levels of oxidative stress and mitochondrial dysfunction.

A number of neurotoxins have been identified that induce PD-like pathol-ogy in humans. These include pesticides such as rotenone (insecticide), paraquat (herbicide) and maneb (fungicide), but also the meperidine analog synthesis by-product 1-methyl-4-phenyl1,2,3,6-tetrahydropyridine (MPTP) (Langston et al., 1999; Cicchetti et al., 2009). Most of these neurotoxins induce neuronal apoptosis in the SN by interfering with protein complexes of the electron transport chain in mitochondria, resulting in ATP depletion, loss of mitochondrial membrane po-tential and the formation of reactive oxygen species (Cicchetti et al., 2009).

The vast majority of PD cases are sporadic and not caused by a single ge-netic mutation or toxin exposure. In recent years, a number of gene expression profiling studies have been published that demonstrated broad gene expres-sion changes in the SN of sporadic PD patients (Grunblatt et al., 2004; Hauser et al., 2005; Mandel et al., 2005; Zhang et al., 2005; Moran et al., 2006; Miller et al., 2006; Papapetropoulos et al., 2006; Cantuti-Castelvetri et al., 2007; Duke et al., 2007; Simunovic et al., 2009; Bossers et al., 2009; Lanoue et al., 2010; Lewan-dowski et al., 2010). These studies confirmed the dysregulation of genes involved

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in molecular pathways already implicated in the disease, including the ubiquitin/proteasome system, heat shock regulation, iron transport, vesicular transport, neurotransmission, chaperone activity and oxidative stress regulation. Impor-tantly, these studies also revealed changes in the expression of genes implicated in pathways not previously linked to the disease, including extracellular matrix signaling, cell adhesion, the polyamine signaling pathway and, most recently, miRNA modulation of mitochondrial function (Minones-Moyano et al., 2011). An-other interesting approach, based on the biocomputational analysis of existing gene expression and single nucleotide polymorphism databases, suggested that axon guidance cues and their receptors are involved in the pathogenesis of PD (Lesnick et al., 2007). Together, these studies illustrate the complexity of the mo-lecular changes that occur in the sporadic form of PD.

A confounding factor of most gene expression profiling studies is that the observed changes may be influenced by the loss of DAergic neurons in the PD SN. In an attempt to minimize the effect of DAergic cell death on the observed chang-es in gene expression, we have performed a microarray study on the relatively spared area of the PD SN, which exhibited a neuronal density of approximately 70% of control individuals. This study identified a total of 287 genes significant-ly dysregulated in PD (Bossers et al., 2009). Interestingly, we observed chang-es in genes involved in neurotrophic support, axon guidance cues, cytoskeletal structure and microtubule-based axonal transport, transcriptional regulation and cell death. Based on these findings we hypothesized that a gradual loss of neurotrophic support and alterations in axon guidance cues could causally con-tribute to neurodegeneration of DAergic neurons in the SN of PD patients (Boss-ers et al., 2009).

The SN is a heterogeneous tissue that contains multiple cell types, includ-ing DAergic neurons, astrocytes, microglia cells, blood vessels and immune cells. Gene expression profiling, based on mRNA isolated from homogenates of human SN tissue, does not provide insight into the cell type(s) in which the expression of the dysregulated genes takes place. In order to investigate the function of the genes identified by the microarray and the above mentioned hypothesis, it is nec-essary to know in which cell type those genes are expressed in the human SN. In this chapter we describe two necessary steps that had to be executed before meaningful functional studies on interesting candidate genes could start. First, we selected 79 target genes of the 287 significantly regulated genes in the PD SN. This selection was based on their biological function and on their potential impact on the viability of DAergic neurons. Subsequently, the cellular localization of almost half of the selected genes was studied in human SN tissue at the mRNA and/or protein level. All but one of the selected genes appears to be expressed by SN neurons, mainly by the DAergic neurons. Furthermore, we quantified the pro-tein and mRNA expression levels for 10 of these genes in the SN neurons. Finally, we investigated the expression profile of different transcript variants of three genes of interest: LRDD, EHBP1 and ARHGEF2 and found that specific transcript variants of LRDD and EHBP1 are differentially expressed in PD.


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Methods

Selection of PD target genes

Ingenuity Pathway Analysis of the gene expression changes in PD SN

The Ingenuity Pathway Analysis (IPA) software (Ingenuity systems, www.ingenuity.com, Mountain View, CA, USA) was used to identify functional inter-actions between the 287 significantly regulated genes identified by Bossers et al (2009). A core analysis was performed on all 287 genes yielding an unbiased overrepresentation analysis of dysregulated ‘biological functions’. With a cut off p< 0.01, a list of most overrepresented ‘biological functions’ was identified. From that list, the ‘cell death’ biological function was selected. The 45 genes in this ‘bi-ological function’ were used to manually generate a molecular network using the IPA default pathway ‘build’ and ‘overlay’ tools.

Gene selection based on gene ontology and literature study

The two main selection criteria for target gene identification from the total list of 287 significantly regulated genes were defined as follows:

1) Genes involved in axon guidance, neurotrophic support and synaptic transmission. One of the hypotheses addressing the pathogenesis of PD is the dy-ing back hypothesis (Dauer and Przedborski, 2003; Cheng et al., 2010). In this hypothesis the primary neurodegenerative event in PD is the loss of nigrostriatal synaptic terminals, resulting in the loss of functional synaptic connections, the subsequent retraction of axons and the consequent degeneration of DAergic neu-rons in the SN. Transcriptional alternations in genes involved in axon guidance, neurotrophic support and synaptic transmission could therefore directly con-tribute to dysfunctional nigrostriatal nerve endings and axon retraction (Boss-ers et al., 2009).

2) Genes involved in mitochondrial gene expression and cellular metabo-lism. Mitochondrial dysfunction is an important element of the pathogenesis of PD (Dawson and Dawson, 2003; Bender et al., 2006; Henchcliffe and Beal, 2008). Moreover, DAergic neurons display relatively high sensitivity to oxidative stress due to their high metabolic rate and build-up of dopamine oxidation products (Berman and Hastings, 1999; Burke et al., 2003).

Tissue

Tissue used in these studies was from the same controls and PD patients as in the previously described gene expression profiling study (Bossers et al., 2009). In brief, snap frozen and formalin-fixed, paraffin-embedded postmortem human SN tissue from 7 PD patients and 9 controls were obtained from the Neth-erlands Brain Bank (NBB, Amsterdam, the Netherlands). All brain tissue was

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collected from donors from whose written informed consent for a brain autopsy and the use of the material and clinical information for research purposes had been obtained by the NBB. For further diagnosis, an extensive neuropathologi-cal investigation was performed on all PD and control tissue. Control tissue did not present a Braak pathology score for neurofibrillary tangles higher than 2 (Braak et al., 2003) and neither control nor PD subject had a known history of neurological or psychiatric disease other than PD or PD-related dementia. All PD patients received dopamine replacement therapy during the course of the dis-ease. Table 1 summarizes the clinical and pathological details of all the donors, the age and cause of death, post-mortem delay, cerebral spinal fluid pH as a mea-sure for agonal state (Ravid et al., 1992), brain weight and RNA integrity number. Brain stems containing the SN tissue were fixed in 4% paraformaldehyde (Sig-ma-Aldrich Co., St. Louis, MO, USA) for 30 days, dehydrated, paraffin-embedded and tissue blocks containing the SN were sectioned at 6µm. Sections were then mounted onto Superfrost PlusPlus slides (Fisher Scientific, The Netherlands) in a water bath set at 50oC, and dried in a stove at 37oC for 48 hours.

Subject Diagnosis Sex Age PMI pH BW RIN Cause of Death00-115 PD/DEM m 70 9:05 6.33 1258 6.2 Pneumonia, septic shock

04-045 PD/DEM m 71 6:58 6.55 1358 8.4 * Pneumonia

00-139 PD/DEM m 72 7:15 6.55 1546 6.7 Uremia

02-003 PD f 75 5:00 6.52 1218 9.6 * Euthanasia

02-011 PD f 79 5:45 6.37 1203 8.7 * Myocard infarction

00-034 PD m 86 8:30 6.52 1178 9.2 * Unknown

02-064 PD m 87 7:20 6.37 1166 7.4 Respiratory insufficiency

98-126 CTRL m 71 6:00 6.54 1385 8.8 Respiratory insufficiency

00-049 CTRL m 78 6:55 6.42 1332 9.2 * Cardiac failure

97-144 CTRL m 78 4:00 6.43 1160 9 * Pulmonary carcinoma

00-142 CTRL f 82 5:30 6.60 1280 9.2 * Myocardial infarct

00-022 CTRL f 83 7:45 6.52 1102 9.2 * Acute myocard infarction

98-062 CTRL m 85 4:35 6.95 1332 7.5 Respiratory insufficiency

99-046 CTRL f 89 5:10 6.62 1168 9.5 Cardiac arrest

01-029 CTRL f 90 5:25 6.58 1066 7.6 Myocard infarction

00-050 CTRL f 52 6:50 7.16 1258 - Leiomyosarcoma

Table 1. Clinicopathological data of human postmortem tissue samples. Column ‘Subjects’ provides the NBB numbers of each donor. Abbreviations: PD: Parkinson’s disease; CTRL: control; PD/DEM = Parkinson’s disease with dementia; PMI = post-mortem interval (hours); m: male; f: female; BW = brain weight (grams); RIN = RNA integrity number. Samples marked with an * have been used in the microarray study and almost all samples have been used for qPCR analysis as described earlier (Bossers et al., 2009). Donor NBB 00-050 was only used for in situ hybridizations.


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Immunohistochemistry

For protein localization and quantification studies, one SN section was used from each PD and control sample. The sections were deparaffinized in xylene (2 times for 10 min), rehydrated in a graded series of ethanol (2x 5 min in 100% ethanol, 2 min in each 95%, 80% and 60% ethanol) and washed twice for 2 min in distilled water. Antigen retrieval was performed by microwave heating (2x 5 min at 700W) in either 0.01M citrate buffer at pH 4.0 or 6.0, Tris buffered saline pH 7.6 (TBS,150mM NaCl, 50mM Tris-HCl) or 50mM Tris-HCl pH 9.0 (see Supple-mentary Table 2 for the exact combination of antibody and antigen retrieval method). Sections were then washed in TBS two times for 5min. Some sections were pre-blocked with milk-TBS solution (non-fat dry milk, Elk, Campina, Eind-hoven, The Netherlands) for 1h at room temperature (RT) (Supplementary Table 2). Primary antibodies were incubated in Super Mix pH 7.6 (1x TBS, 0.25% gel-atin (Merck, New Jersey, USA) and 0.5% Triton X-100 (Sigma-Aldrich, St Louis, Missouri, USA) for 1 hour at RT followed by overnight incubation at 4°C (Supple-mentary Table 2). For double staining, an anti-pan neurofilament antibody (NF, Clone SMI-311, Covance, Berkeley, CA, USA, 1:1000) was used to label neurons and an anti-tyrosine hydroxylase antibody (TH, Jacques Boy SA, Reims, France, 1:1000) was used to label DAergic neurons, an anti-GFAP antibody (DAKO A/S, Glostrup, Denmark, 1:1000) was used to label astrocytes and an anti-HLA anti-body (Dako A/S, 1:1000) was used to label microglia. After the primary antibody incubation, sections were washed three times with TBS. Secondary antibody conjugated to Alexa 596 fluorophore (Invitrogen, Carlsbad, CA, USA) was used to visualize primary antibody binding to the target protein in the sections. Cellular specific markers were detected with anti-mouse or anti-rabbit Alexa 488 conju-gated antibodies (Invitrogen). These antibodies were incubated in Super mix at a 1:800 dilution for 1 hour at RT. For some proteins of interest, signal amplifica-tion was necessary (Supplementary Table 2). In brief, biotin-labelled secondary antibodies (Vector Laboratories, Burlingame, CA, USA) were used at dilution of 1:400 and incubated for 1h at RT. These sections were subsequently incubated in ABC solution (1:800 in TBS, Vector Laboratories) for 1h at RT followed by in-cubation in streptavidin-conjugated Alexa 596 (1:800 in TBS, Invitrogen) for 1h at RT. To quench autofluorescence, all sections were treated with 0.5% filtered Sudan Black solution (BDH, Poole, England) for 7min, briefly washed in 70% ethanol, followed by TBS washes. Finally, all sections were embedded in Mowiol (0.1 M Tris pH 8.5, 25% glycerol, 10% w/v Mowiol 4-88 (Sigma-Aldrich)) contain-ing Hoechst 33258 (BioRad, Hercules, CA, USA; 1:10000). For protein localiza-tion studies images were acquired on the Confocal Laser Scanning Microscope (CLSM, Zeiss, Sliedrecht, The Netherlands).

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In situ hybridization

RNA probe generation:

DIG-labeled RNA probes were synthesized from T3 (sense probe) and T7 (antisense probe) RNA polymerase promoter sequences which flanked PCR tem-plates of genes of interest, generated from a human cDNA library. PCR primers were designed by using Dharmacon software (http://www.dharmacon.com/designcenter). Their sequences are listed in Supplementary Table 2. PCR was carried out on the cDNA library in a standard reaction containing 0.2mM dNTPs (Invitrogen), 0.5μM primers (Eurogentec, Liège, Belgium), 1μl cDNA, 1U Super-Taq DNA polymerase (SphaeroQ, Leiden, The Netherlands) and 1.5mM MgCl2 in 1x Supertaq Buffer (SphaeroQ). SuperTaq DNA polymerase was activated at 94oC for 5min, followed by 40 amplification cycles of 30 sec denaturing at 94oC, 1 min annealing at 55oC and 45 sec extension at 72oC. PCR was completed by a final extension step of 5 min at 72oC. The product was purified from 1% agarose gel using a gel extraction kit (Nucleospin Extract II, Macherey-Nagel, Düren, Germa-ny). DIG-labeled RNA probes were synthesized using 1μg PCR template in a 20μl in vitro transcription reaction containing 1xTranscription buffer (Roche, Basel, Switzerland), 1xDIG labeling mix (Roche), 40U RNase inhibitor (RNaseOUT, Invi-trogen) and 40U T3/T7 RNA polymerase for 2 hrs at 37oC. The PCR template was then degraded by incubation with 2U of DNase I (Invitrogen) for 15 min at 37oC. DIG-labeled RNA probes were purified by extraction with Nucleospin RNA Clean-up kit (Macherey-Nagel). For two genes (RGMA and Necdin) LNA-2’Omethyl-RNA modified oligonucleotide probes were used containing a 5’ end labeled with flu-orescein. Probes were designed using Dharmacon software and were obtained from RiboTask Aps (Denmark).

Tissue pretreatment:

For quantitative and semi-quantitative study of mRNA expression levels in PD and control tissue, one SN section from every subject was used. The sections were deparaffinized and rehydrated as described above. Tissue penetration was improved by microwave heating in 0.1M citrate buffer pH 6.0. Sections were then washed in PBS for 2x 5 min and de-proteinated as follows: 20 min incubation in 0.2 N HCl, 2x 5 min wash in PBS, and 15 min incubation at 37°C with proteinase K (10ug/ml, Invitrogen) in proteinase K buffer (2 mM CaCl2, 10 mM Tris-HCl, pH 7.5). Sections were then incubated for 30 sec in Glycin buffer (27mM glycine in PBS) to stop the proteinase K digestion and washed 2x 5 min in PBS. Finally, sec-tions were delipidated for 10 min in PBS- 0.1% Triton X-100 (Sigma-Aldrich) and washed 2x 5min in PBS.


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Hybridization and immunological detection:

For DIG-RNA probes, sections were prehybridized in 200μl RNA hybridiza-tion buffer (50% formamide, 750nM NaCl, 75nM Na3C6H5O7, 5x Denhardt’s and 250 μg/ml yeast tRNA (Sigma-Aldrich)) covered with Nescofilm for 2 hours at RT in a humidified chamber. Next, the probe was diluted in RNA hybridization buf-fer to final concentrations ranging from 1500-2500ng/ml (Supplementary Table 2), denatured at 85oC for 5 min and cooled on ice. Sections were hybridized over-night at the probe-specific optimal temperature (Supplementary Table 2). Next, sections were washed for 5 min in 5xSSC at 55oC, 1 min in 2x SSC at 55oC, 30 min 0.2xSSC/50% formamide at 55oC and 5 min 0.2xSSC at RT. To detect the probes, sections were washed for 5min in Buffer 1 (100mM Tris, 150mM NaCl, pH 7.5) followed by 1h incubation in 1% Blocking reagent (Roche) in Buffer 1 at RT. After a 5min wash in Buffer1, sections were incubated in sheep IgG anti-DIG-AP Fab (1:3000 in Buffer 1) for 3hrs at RT.

For LNA -2’Omethyl-RNA probes, sections were prehybridized in 200μl LNA hybridization buffer (50% formamide, 600mM NaCl, 10mM Hepes buffer (pH7.5), 5x Denhardt’s, 1mM EDTA, 200 μg/ml denatured herring sperm DNA (Roche)) overnight covered with Nescofilm at RT in a humidified chamber. Next, the probe was diluted in LNA hybridization buffer, denatured at 95oC for 5 min and cooled on ice for 5 min. Sections were hybridized in this buffer at 55oC for 90 min, followed by series of wash steps: 5 min in 5x SSC at 55oC, 5 min in 2x SSC at 55oC, 5 min in 0.2x SSC at 55oC and 5 min in PBS at RT. To detect the probes, sections were pre-incubated with 1% milk-TBS pH 7.6 for 1h at RT, followed by 3h RT incubation with sheep IgG, anti-fluorescein-AP-Fab fragments (Roche) di-luted1:3000 in 1% milk-Super Mix.

For both DIG-RNA and LNA-2’Omethyl-RNA probes the signal was devel-oped as follows: sections were washed twice in Buffer 1 and once in Buffer 2 (100mM Tris-HCl pH 9.0, 100mM NaCl, 5mM MgCl2) for 5 min and further incu-bated in 10ml Buffer 2 containing 3.4mg nitro-blue tetrazolium chloride (NBT) (Roche), 1.75mg 5-bromo-4-chloro-3’-indolyphosphate p-toluidine salt (BCIP, Roche) and 2.4mg levamisole (Sigma-Aldrich). The incubation duration varied from 20 minutes up to 24hrs, depending on the intensity of the signal. Reaction was stopped in water and slides were treated with 100% MetOH for 5 min and cover slipped with Aquamount (Merck). For each gene, the adjacent section was incubated with sense probe to test the specificity of the observed in situ hybrid-ization signal.

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Image analysis

Quantification of protein levels in single DAergic neurons:

Image acquisition and subsequent image analysis were performed with an Axioplan microscope (Carl Zeiss) and Image Pro Plus software (Media cybernet-ics, Bethesda, MD, USA). The entire SN structure was imaged at 10X magnifica-tion at a fixed exposure time for each antibody used. Within the SN, a fluorescent signal was measured in three 10µm-diameter circles, placed in the cytoplasmic area of each melanin-containing (DAergic) neuron. Areas positive for melanin pigmentation were avoided. The circle values were then averaged for each neu-ron, and the mean fluorescence level of all DAergic neurons was calculated. For RGMA protein quantification, three 20x magnification images were taken cover-ing the whole SN. The fluorescence intensity was measured in the outlined SN, multiplied by the area measured, and divided over the three images to eventu-ally give an average fluorescence in the SN. To estimate background levels, flu-orescence was sampled for each section in the area adjacent to the SN. The 2x background value was then subtracted from the average neuronal or SN area fluorescent intensity yielding the final DAergic neuron protein expression or av-erage SN fluorescence level per subject. Statistical analysis was performed using the Kruskal-Wallis test. P values < 0.05 were determined as statistically signifi-cant.

Quantification of mRNA expression in single DAergic neurons:

Images of in situ hybridization signal were acquired with an Axioplan mi-croscope. The level of mRNA expression was semi-quantified by scoring the in-tensity of the staining (-, ±, +, or +++) and, if there was an indication of difference in mRNA expression levels between PD and control sections, the signal was fur-ther quantified on the single cell level by measuring the optical density of the ISH signal in all dopaminergic neurons of the SN as described below.

For each section, the entire SN was outlined at 2.5x magnification. The out-lined area was then subdivided into a rectangular grid using an Image Pro Plus macro, each grid field representing one image at 40x magnification. Grid fields in which the outlined SN constituted less than 50% of the field area were excluded from the quantification. For each neuron, identified based on its morphology and containing a visible nucleolus in the center of the nucleus, ISH signal was quanti-fied by filling the cellular structure with circles of 5μm in diameter. Within each circle, the absorption spectrum throughout the visible spectrum (wavelengths from 400 to 800) was then measured using the spectrometer (Avaspec 3649, Avantes) and a color camera (Evolution MP, Media Cybernetics) both assembled on an Axioskop microscope. The ISH signal was identified at the absorption peak of 600nm. The brown melanin pigmentation in DAergic neurons also absorbed light, but at a much lower level at 600nm wavelength. This melanin-specific ab-sorption signal was then subtracted to obtain the ISH signal. The average opti-


67

cal density for the blue ISH signal was calculated for each neuron and corrected for the background by subtracting the values measured just outside that neuron. Finally, for each subject, the mean ISH signal in a single neuron was estimated by averaging the ISH levels in all positive neurons. Furthermore, the percentage of the pigmented neurons positive for the ISH signal was calculated. To test for differences in mRNA hybridization signal between PD patients and controls, the Kruskal-Wallis test was used. P values < 0.05 were assessed as statistically sig-nificant.

Quantitative PCR

Tissue used for qPCR was the same as used in the microarray study. RNA isolation, cDNA synthesis and qPCR procedure were performed as previous-ly described (Bossers et al., 2009). In brief, cDNA synthesis was performed on 250ng of RNA using SuperScript Reverse Transcriptase (Invitrogen. Carlsbad, CA, USA) and 1/100 or 1/20 of total cDNA yield was used for each qPCR reac-tion. In each reaction, 3pmol of forward and reverse primer was used with 10µl 2x SYBR green ready mix (Applied Biosystems, Carlsbad, CA, USA) in the final reaction volume of 20µl. The sequences for forward and reverse primers for each tested gene were designed using Primer Express (Applied Biosystems) and can be found in the Supplementary Table 3. Reactions were carried out on the ABI 7300 sequence system (Applied Biosystems). Dissociation curve analysis was performed to check for primer dimer formation, with non to be observed, and to determine the primer pair efficiency. We used the same housekeeping genes used as before: ACTB, MRPL24 and DHX16 (Bossers et al., 2009). Absolute ex-pression of gene variants was calculated by correcting the Ct values (detected with the same threshold) for the primer efficiency and normalizing to the geo-metric mean of the housekeeping genes (Dijk et al., 2004). Relative values of gene variants were calculated by correcting for the primer efficiency, calculating the Δ Ct and finally corrected with the normalization value of the housekeeping genes previously calculated using GeNorm software (Vandesompele et al., 2002). Statistical analysis between PD and control samples was performed with the use of the Mann-Whitney U test. P-values < 0.05 were determined to be significant.

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Results

Ingenuity Pathway Analysis (IPA) of gene expression changes in PD reveals alterations in genes involved in cell death

An unbiased IPA of the 287 significantly regulated genes identified previ-ously by gene expression profiling (Bossers et al., 2009) revealed 35 significantly overrepresented biological functions (Supplementary Table 4). Some of the bio-logical functions identified by IPA have already been indicated in the gene on-tology analysis by Bossers et al., such as ‘neurological disease’, ‘cell to cell sig-naling’ (including synaptic transmission) and ‘nervous system development’ (2009). Many other functions were either very general, such as ‘cellular function and maintenance’ and ‘genetic disorder’, or represented processes or diseases difficult to interpret in the context of PD, such as ‘reproductive system’, ‘cancer’ or ‘hepatic system disease’. Importantly, however, the list contained one biologi-cal function, ‘cell death’, comprised of 45 genes (16% of the total dysregulated genes) that have been previously linked to various forms of cell death, including apoptosis. Since degeneration of DAergic neurons is a cardinal feature of PD we focused on these genes and generated a molecular network using the IPA ‘grow’ and ‘overlay’ tool (Figure 1). 16 genes from the cell death biological function were selected as target genes for further localization (Chapter 2) and/or for functional studies (Chapter 4) (red squares Figure 1, Table 2). The ‘cell death’ network con-tained several very interesting candidate genes involved in transcriptional regu-lation of cell death or survival (PTMA, NR2A4 and FOXO4), caspase activation (LRDD) and nuclear ATP-signaling receptor (P2RX7). Apart from NR2A4, none of these genes have so far been linked to cell death in PD.

Selection of other primary PD gene targets

In addition to the 16 genes involved in ‘cell death’ identified by IPA, we se-lected 41 target genes (14%, Table 2) from the list of the 287 significantly reg-ulated genes in the PD SN (Bossers et al., 2009) based on their involvement in axon guidance, neurotrophic support and synaptic transmission (Table 2, selec-tion category 1), and 15 genes (5%) based on their involvement in mitochondrial function and cellular metabolism (Table 2, selection category 2). Lastly, a het-erogeneous group of 18 genes (6%) with functions in various biological process-es possibly involved in PD pathology was included. These genes play a role in: transcription factor activity and gene expression regulation, maintenance of the DAergic neuronal phenotype, cell adhesion, and cytoskeletal function. 2 genes with unknown function were also included (Table 2, selection category 3). The fi-nal list of 79 target genes served as a starting point for the localization and quan-tification studies of target gene expression in human PD and control SN sections.


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Localization of target genes in human SN tissue

To investigate the cell type in which the target genes are expressed, mRNA and protein localization studies were performed for 34 out of 79 target genes. mRNA localization was analyzed for 7 genes by in situ hybridization and pro-tein localization was analyzed for 29 genes by immunohistochemistry (Table 3). The expression of 2 genes, ALDH1A1 and RGMA, has been studied at both the mRNA and protein level. mRNA expression of all 7 genes was almost exclusively observed in neuromelanin-positive neurons in the SN of control and PD subjects (Figure 2). Protein expression for all genes, except for one protein (VIM, Figure

Figure 1. Identification of 45 genes involved in biological function of cell death by Ingenuity Pathway Analysis. The intensity of the coloring indicates the significance of regulation. Red indi-cates significantly upregulated genes, while green indicates significantly downregulated genes. Gray indicates genes with no significantly altered expression on the microarray. 16 molecules outlined in red rectangles were selected for further investigation (see also Table 2). Direct and indirect signaling between the molecules are represented by solid and dotted lines respectively.

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Selec-tion cat-

egory

Gene Name

NCBI reference number

Description

Fold change

PD/Contr

Cell death IPA identyfied genes

AGTR1 NM_031850 Angiotensin II receptor, type 1 0.07

ALDH1A1 NM_000689 Aldehyde dehydrogenase 1 family, member A1 0.18

CASP7 NM_001227 Caspase 7, apoptosis-related cysteine peptidase 1.91

DLK1 NM_003836 Delta-like 1 homolog (Drosophila) 0.22

FOXO4 NM_005938 Forkhead box O4 1.82

FST NM_006350 Follistatin 0.17

HPRT1 NM_000194 Hypoxanthine phosphoribosyltransferase 1 (Lesch-Nyhan syndrome)

0.37

LRDD NM_018494 Leucine-rich repeats and death domain containing 2.00

MAPK9 NM_002752 Mitogen-activated protein kinase 9 0.51

MDH1 NM_005917 Malate dehydrogenase 1, NAD (soluble) 0.40

NR4A2 NM_006186 Nuclear receptor subfamily 4, group A, member 2 0.20

P2RX7 NM_002562 Purinergic receptor P2X, ligand-gated ion channel, 7 1.90

PTMA NM_002823 Prothymosin, alpha (gene sequence 28) 1.80

SDC2 J04621 Syndecan 2 (heparan sulfate proteoglycan 1, cell surface-associated, fibroglycan)

0.37

SNCA NM_000345 Synuclein, alpha (non A4 component of amyloid precursor) 0.27

SLC18A2 NM_003054 Solute carrier family 18 (vesicular monoamine), member 2 0.16

SOX9 NM_000346 SRY (sex determining region Y)-box 9 (campomelic dysplasia, autosomal sex-reversal)

1.72

Axon guidance

1

HS6ST3 AF339796 Heparan sulfate 6-O-sulfotransferase 3 0.48

NETO2 NM_018092 Neuropilin (NRP) and tolloid (TLL)-like 2 0.46

OLFM3 AF397397 Olfactomedin 3 0.31

RGMA NM_020211 RGM domain family, member A 1.97

ROBO2 NM_002942

Roundabout, axon guidance receptor, homolog 2 (Drosophila) 0.32

SDC2 J04621 Syndecan 2 (heparan sulfate proteoglycan 1, cell surface-associated, fibroglycan)

0.37

SEMA5A NM_003966 Sema domain, seven thrombospondin repeats (type 1 and type 1-like), transmembrane domain (TM) and short cytoplasmic domain, (semaphorin) 5A

1.28

SLITRK5 NM_015567 SLIT and NTRK-like family, member 5 0.46

Trophic support

ARHGEF2 NM_004723 Rho/rac guanine nucleotide exchange factor (GEF) 2 1.77

CDK5 NM_004935 Cyclin dependent kinase 5 0.44

DLK1 NM_003836 Delta-like 1 homolog (Drosophila) 0.22

DNC1I1 NM_004411 Dynein, cytoplasmic, intermediate polypeptide 1 0.41

DOK6 AK057795 Docking protein 6 0.26


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1

EDG2 NM_001401 Endothelial differentiation, lysophosphatidic acid G-protein-coupled receptor, 2

2.06

GPCR5A NM_003979 G protein-coupled receptor, family C, group 5, member A 0.30

HN1 NM_016185 Hematological and neurological expressed 1 0.49

KCNJ6 NM_002240 Potassium inwardly-rectifying channel, subfamily J, member 6 0.26

KIFAP3 NM_014970 Kinesin-associated protein 3 0.45

MAGEE1 AB046807 Melanoma antigen family E, 1 0.40

NDN NM_002487 Necdin homolog (mouse) 0.38

NELL2 NM_006159 NEL-like 2 (chicken) 0.30

NTRK2 NM_006180 Neurotrophic tyrosine kinase, receptor, type 2 1.62

PFDN4 NM_002623 Prefoldin 4 0.53

PLEKHE1 NM_194449 PH domain and leucine rich repeat protein phosphatase 1.90

RIT2 NM_002930 Ras-like without CAAX 2 0.36

STS-1 NM_032873 Cbl-interacting protein Sts-1 0.38

TRIM36 NM_018700 Tripartite motif-containing 36 0.30

VAV3 NM_006113 Vav 3 oncogene 0.34

Synapse/neurotransmitter packaging and release

AAK1 AF090100 AP2 associated kinase 1 0.43

AMPH NM_001635 Amphiphysin (Stiff-Man syndrome with breast cancer 128kDa autoantigen)

0.33

CADPS NM_003716 Ca2+-dependent secretion activator 0.34

CAST1 AB002376 CAZ-associated structural protein 0.28

EHBP1A1 NM_015252 EH domain binding protein 1 0.49

HIP1R NM_000194 Huntingtin interacting protein-1-related 1.66

NECAP1 NM_015509 Adaptin ear-binding coat-associated protein 1 0.41

PCLO AB011131 Piccolo (presynaptic cytomatrix protein) 0.40

SNAP91 NM_014841 Synaptosomal-associated protein, 91kDa homolog (mouse) 0.45

SNCA NM_000345 Synuclein, alpha (non A4 component of amyloid precursor) 0.27

SYT1 NM_005639 Synaptotagmin I 0.23

UNC13C AK054981 Unc-13 homolog C (C. elegans) 0.28

WWC1 AB020676 WW, C2 and coiled-coil domain containing 1 1.69

Mitochondria/energy synthesis

2

AGTR1 NM_031850 Angiotensin II receptor, type 1 0.07

ALDH1A1 NM_000689 Aldehyde dehydrogenase 1 family, member A1 0.18

COMT NM_000754 Catechol-O-methyltransferase 1.48

GBE1 NM_000158 Glucan (1,4-alpha-), branching enzyme 1 (glycogen branching enzyme, Andersen disease, glycogen storage disease type IV)

0.18

LTF NM_002343 Lactotransferrin 4.56

MDH1 NM_005917 Malate dehydrogenase 1, NAD (soluble) 0.40

MRPS25 NM_022497 Mitochondrial ribosomal protein S25 0.51

SLC25A4 NM_001151 Solute carrier family 25 (mitochondrial carrier; adenine nucleo-tide translocator), member 4

0.52

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2

Metabolism

CA2 NM_000067 Carbonic anhydrase II 2.26

FST NM_006350 Follistatin 0.17

GBP1 NM_002053 Guanylate binding protein 1, interferon-inducible, 67kDa 2.62

HPRT1 NM_000194 Hypoxanthine phosphoribosyltransferase 1 (Lesch-Nyhan syndrome)

0.37

P2RX7 NM_002562 Purinergic receptor P2X, ligand-gated ion channel, 7 1.90

PTS NM_000317 6-pyruvoyltetrahydropterin synthase 0.56

UCHL1 NM_004181 Ubiquitin carboxyl-terminal esterase L1 (ubiquitin thiolesterase) 0.31

3

Transcription factor activity/gene expression

CTDSP1 NM_021198 CTD (carboxy-terminal domain, RNA polymerase II, polypeptide A) small phosphatase 1

1.77

DENR AB014731 Density-regulated protein 0.41

FOXA1 NM_004496 Forkhead box A1 0.18

FOXO4 NM_005938 Forkhead box O4 1.82

LASS6 AK023042 LAG1 longevity assurance homolog 6 (S. cerevisiae) 0.34

PTMA NM_002823 Prothymosin, alpha (gene sequence 28) 1.80

SOX2 NM_003106 SRY (sex determining region Y)-box 2 1.86

SOX9 NM_000346 SRY (sex determining region Y)-box 9 (campomelic dysplasia, autosomal sex-reversal)

1.72

TGIF1 NM_003244 TGFB-induced factor (TALE family homeobox) 1.96

Dopaminergic phenotype

DDC NM_000790 Dopa decarboxylase (aromatic L-amino acid decarboxylase) 0.18

EN1 NM_001426 Engrailed homolog 1 0.28

NR4A2 NM_006186 Nuclear receptor subfamily 4, group A, member 2 0.20

SLC18A2 NM_003054 Solute carrier family 18 (vesicular monoamine), member 2 0.16

TH NM_000360 Tyrosine hydroxylase 0.57

Cell adhesion

ADAM23 NM_003812 ADAM metallopeptidase domain 23 0.41

KLK6 NM_002774 kallikrein-related peptidase 6 1.60

Cytoskeleton

DNM3 NM_015569 Dynamin 3 0.55

VIM NM_003380 Vimentin 2.22

Unknown

CALN1 NM_031468 Calneuron 1 0.33

ELOVL4 NM_022726 Elongation of very long chain fatty acids (FEN1/Elo2, SUR4/Elo3, yeast)-like 4

0.46

Table 2. The 79 PD target genes selected for further study based on IPA and ‘biased’ hypothesis driven selection criteria as defined in the methods. All, except for 3 genes selected from the unbiased IPA analysis playing a role in cellular death, have a primary function in other biological functions. Therefore these genes were mentioned twice in the table and are typed in italic bold font for recognition. Selection category 1 includes genes involved in axon guidance, neurotroph-ic support and synaptic transmission, all possibly contributing to the dying back hypothesis in


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3) expressed by astrocytes, was also specific for SN neurons (Table 3). Figure 3 shows examples of protein localization for 10 genes: ALDH1A1, NETO2, ROBO2, SYT1, AMPH, PLEKHE1, RGMA, RIT2, SCD2 and VIM. The co-localization of AL-DH1A1, NETO2, ROBO2, AMPH and PLEKHE1 protein with neurofilament dem-onstrated that these proteins are expressed in the cytoplasm of SN neurons in both control and PD tissue. ALDH1A1, ROBO2, AMPH and PLEKHE1 show no ob-vious change in sub-cellular localization in PD, whereas NETO2 protein expres-sion appears to occur in a more punctate and locally concentrated pattern in the cytoplasm of neurons in PD patients compared to controls (Figure 3). As expect-ed, SYT1 was mostly expressed in a typical punctate manner, characteristic for synaptic staining. The pattern of expression of SYT1 was similar in controls and PD. RGMA, RIT2 and SCD2 were all expressed in tyrosine hydroxylase positive neurons, indicating their localization in DAergic neurons. Interestingly, RGMA and SDC2, apart from a punctate staining in the cytoplasm of the DAergic neu-rons, also showed a punctate extracellular expression.

Quantification of mRNA and protein expression in PD and control SN

In addition to the cellular localization studies, mRNA and/or protein expres-sion were quantified on the level of individual neurons for 10 target genes. First-ly, a semi-quantitative analysis of mRNA levels for 7 selected genes (ALDH1A1, DYNCI1, EHBP1, NDN, RGMA, SLITRK5 and SOX2) was performed (Figure 4A). This semi-quantitative analysis pointed to four genes (ALDH1A1, EHBP1, SOX2, and RGMA) displaying possible differential neuronal expression between PD and control. For DYNCI1, SLITRK5 and NDN no difference in signal intensity between PD and control patients was observed.

The four regulated genes (ALDH1A1, EHBP1, SOX2, and RGMA) were quan-tified by measuring the mean optical density of the ISH signal in SN neurons and compared between the PD and control samples (Figure 4B). ALDH1A1 mRNA levels were on average 60% lower in PD SN neurons compared to the control SN neurons (P =0.028). RGMA mRNA levels displayed a trend towards an increase in PD SN neurons, but this failed to reach statistical significance (P value = 0.18). EHBP1and SOX2 did not show a significant difference in mRNA expression levels in PD SN neurons.

PD. Category 2 includes genes involved in mitochondrial function and cellular metabolism - im-portant element of PD pathogenesis. Category 3 includes a heterogeneous group of genes with a function in various biological processes, such as transcription factor activity and gene expression regulation, maintenance of the DAergic neuronal phenotype, cell adhesion, cytoskeletal func-tion and 2 genes with unknown function. All genes are significantly dysregulated in PD SN tissue (Bonferroni corrected p<0.05) (Bossers et al., 2009). Gene names, their NCBI reference numbers and full names are all mentioned in the table. The column ‘Fold change’ reflects the transcrip-tional alterations between PD and control SN, as measured on the microarray.

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CH A PTER 2

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e 3.

Cel

lula

r loc

aliz

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n of

34

targ

et g

enes

from

the

tota

l list

of s

elec

ted

79 p

rimar

y ta

rget

gen

es. S

elec

tion

crite

ria a

re in

dica

ted

in th

e ‘se

lect

ion

cate

gory

’ ref

errin

g to

Tabl

e 1.

Gen

e na

me,

NCB

I num

ber a

nd fu

ll na

me

are

indi

cate

d in

the

follo

win

g co

lum

ns. T

he co

lum

n ‘F

old

chan

ge’ r

eflec

ts th

e de

gree

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rans

crip

tiona

l alte

ratio

ns b

etw

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nd co

ntro

l SN

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on th

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icro

arra

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RNA

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lar l

ocal

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lum

ns ‘m

RNA

loca

lizat

ion

in th

e SN

’ and

‘pro

tein

loca

lizat

ion

in th

e SN

’ res

pect

ivel

y. T

he co

lum

n ‘Q

uant

ifica

tion’

den

otes

the

quan

tifica

tion

of m

RNA

and/

or p

rote

in e

xpre

ssio

n on

sing

le n

euro

nal c

ell l

evel

.


77

Figure 2. In situ hybridization for 6 genes in control and PD SN sections. mRNA ISH signal (blue) is exclusively present in cellular structures morphologically identified as neurons (large cells with visible nucleolus in the center of the nucleus) predominantly containing neuromelanin (brown pigmentation) indicating their DAergic phenotype. Note the absence of staining in the sense probe (right column), supporting the specificity of the observed signal. NBB numbers of each subject are included in the left bottom of each image. Scale bar represents 0.1mm.

CH A PTER 2

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To further investigate the differential expression of ALDH1A1 and RGMA, the protein levels in PD and control SN tissue were investigated by quantification of the average immunofluorescence signal in each SN neuron. ALDH1A1 expres-sion was 50% lower in PD SN neurons (P value= 0.021, Figure 4C). Since RGMA immunofluorescence signal was expressed in neurons and in large extracellular puncta (Figure 3), the total immunofluorescence intensity in the entire SN area was determined. Total protein levels in each section were on average higher in the PD SN compared to the control SN, but this increase was not significant (P value =0.13, Figure 4D). Additionally, protein expression of four other genes of interest was quantified: NETO2, ROBO2 and SCL18A2 (VMAT2). None of these proteins showed significant differences in the levels of expression in individual neurons of PD and control tissue (Figure 4C).

QPCR detection of splice variants expression in human PD SN tissue

Three genes from the list of 78 genes have multiple transcript variants encoding for proteins with either unknown or different biological functions: EHBP1, ARHGEF2 and LRDD. For both EHBP1, gene involved in endocytic traf-ficking, and ARHGEF2, a Rho GTPase, the splice variants encode different pro-teins but it is not known whether these protein variants have a distinct or related biological role. LRDD, a protein that controls cell fate after DNA damage detec-tion, has three transcript variants that encode for proteins that all activate the NFκB signaling cascade, but only splice variant 1 can activate caspase-2, thereby sensitizing cells to genotoxic stress. The microarray probes for all three genes were designed to recognize all transcripts. We have therefore designed qPCR primers which discriminate between most of the known transcript variants for all three of these genes (see Supplementary Table 3 for NCBI reference numbers and primer sequences). In some cases the differences in mRNA sequences were too small to generate discriminating primer pairs (LRDD variant 1, EHBP1 vari-ant 2 and 4, and ARHGEF2 variant 1 and 2).

In the human SN the expression levels of LRDD variants 1 and 2 were low, whereas variant 3 was the dominant isoform (Figure 5A). Interestingly, vari-ant 2 was significantly upregulated in the PD SN (Figure 5B). Primers detecting both variants 1 and 2 also showed an increase in expression in PD tissue, but un-fortunately, since variant 2 alone was already upregulated, we cannot conclude whether variant 1 was significantly regulated as well.

EHBP1 has four known transcript variants with unknown functions. Vari-ant 1 was shown to be most abundant in human SN tissue when compared to variants 3 and 4 (Figure 5C). As primers against the combined variants 1 and 2, and primers against variant 1 only gave a very small difference in expression values, we cannot conclude anything about the expression of variant 2. Variant 1 was significantly downregulated in the PD SN, whereas variant 3 was almost two-fold upregulated (Figure 5D).


79

Figure 3. Immunofluorescence detection of 10 target genes at protein level in human control and PD SN sections: ALDH1A1, NETO2, ROBO2, SYT1 AMPH, PLEKHE1, RGMA, RIT2, SDC2 and VIM. All target genes are labeled in red while pan neurofilament (NF), tyrosine hydroxylase (TH) and glial fibrillary acidic protein (GFAP) astrocyte marker are labeled in green. Arrows point to co-localization of the genes in neurons and in case of VIM in astrocytes. NBB numbers of the donors are indicated at the bottom of each image. Bars represent 20µm. Images were collected with the CLSM at 40X magnification and represent a Z-stack of the 6µm SN section.

CH A PTER 2

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Figure 4. Quantification of mRNA and protein expression in SN neurons of PD and control. A. Semi-quantitative assessment of in situ hybridization signal for ALDH1A1, DYNCI1, EHBP1, NDN, RGMA, SLITRK5 and SOX2 in SN neurons of control and PD samples. Objective assessment of ISH intensity was made and scored in a following fashion: no signal -, low signal ±, intermediate signal +, and high signal +++. B. Quantification of mean optical density of in situ hybridization signal of ALDH1A1, SOX2, EHBP1 and RGMA in control and PD SN neurons. ALDH1A1 illustrates a significantly lower mRNA expression in PD SN neurons (P value = 0.028), whereas a trend of upregulation was observed for RGMA in PD SN neurons (P value = 0.18). C. Quantification of fluorescence intensity of ALDH1A1, NETO2, ROBO2, and SLIC18A2 in control and PD SN neurons. ALDH1A1 protein expression is significantly decreased in PD SN neurons with P value = 0.021. D. Quantification of average RGMA fluorescence level in the whole SN reveals a trend of protein upregulation in PD tissue (P value = 0.13). All donors mentioned in Table 1 were included in these measurements, except for CTRL 00-050. Abbreviations: PD- Parkinson’s disease, PD/DEM- PD with dementia, CTRL- control.


81

ARHGEF2 has three known transcript variants, with unknown differential functions. Splice variant 3 was slightly more expressed in SN tissue compared to variants 1 and 2 (Figure 5E). All three variants were almost two-fold upregu-lated in the PD SN, confirming the microarray data (Figure 5F).

Figure 5. QPCR detection of multiple splice variants of LRDD, EHBP1 and ARHGEF2 genes in control and PD SN. A, C and E. Relative absolute expression levels of LRDD, EHBP1 and ARHGEF2 splice variants in control (CTRL) and Parkinson’s disease (PD) SN tissue. B, D and F. Relative expression changes of splice variants of LRDD, EHBP1 and ARHGEF2 in CTRL and PD SN tissue (* p value < 0.05, ** p value < 0.01).

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Discussion

In a recent publication, we have described alterations in gene expression in the SN of PD patients identified by microarray-based gene expression profiling (Bossers et al., 2009). The primary challenge of genome-wide expression stud-ies is to translate the identified broad gene expression changes into concrete functional information that brings us closer to an understanding of the biological mechanisms causing the disease. In this chapter we describe two steps neces-sary to realize future in depth functional studies on the genes dysregulated in PD: 1) selection of target genes (from the total set of 287 genes) that are poten-tially involved in the neurodegenerative process in PD based on IPA, gene ontol-ogy analysis, and literature search and 2) identification of the cell type in which these dysregulated genes are expressed.

We selected genes that, in our view, were most likely to be specifically in-volved in the neurodegeneration process of PD. We applied IPA on the total gene set and found that 45 genes have a role in ‘cell death’, a cardinal feature of PD (Da-mier et al., 1999; Papapetropoulos et al., 2006; Simunovic et al., 2009). The set of 287 genes was also searched for genes involved in processes that have been im-plicated to be affected in PD, namely axon guidance signaling, neurotrophic sup-port (Lesnick et al., 2007; Bossers et al., 2009), synaptic transmission (Miller et al., 2006; Cantuti-Castelvetri et al., 2007; Simunovic et al., 2009) and mitochon-drial activity (Grunblatt et al., 2004; Hauser et al., 2005; Simunovic et al., 2009; reviewed in Lewis and Cookson, 2011; and Greene, 2012). This resulted in the identification of 79 genes that are linked to one or more of these processes and may therefore be specifically involved in the development of PD neuropathology.

If one wants to investigate how dysregulated gene expression contributes to PD-associated neurodegeneration, it is essential to know in which cell type the dysregulated genes are expressed and whether their cellular localization changes during the disease process. With the selected shortlist of target genes we initiated studies on their cellular expression profile of about half of the select-ed genes in the human SN by using both in situ hybridization and/or immuno-histochemistry. We observed that almost all of the genes were expressed by the melanin-positive neurons of the SN and not in other cell types. This was surpris-ing, since the human SN, during the progression of PD, undergoes also profound cellular changes including gliosis, inflammatory alterations and blood brain bar-rier breakdown (Langston et al., 1999; Hauser et al., 2005; McGeer and McGeer, 2008). However, the microarray study and the cellular localization studies were both performed on parts of the human PD SN that were relatively spared. This was a deliberate choice, since we wanted to study transcriptional alterations in the DAergic neurons that were still viable but potentially affected by the disease process. This tissue sampling strategy may have resulted in enrichment for dys-regulated neuronal genes, as opposed to genes expressed in non-neuronal cells. Several other gene profiling studies used whole SN tissue without pre-selection


83

of the area of the SN that did still contain relatively high numbers of surviving neurons. The gene expression changes reported in these studies may be a reflec-tion of late pathological changes in the SN, including neuronal death and glio-sis, rather than the early changes leading to the cause of the disease (reviewed in Greene, 2012). The best attempt to minimize the impact of neuronal loss on changes in gene expression was undertaken by Cantuti-Castelvetri et al., and Si-munovic et al., (2007; 2009). In these studies a homogeneous population of SN DAergic neurons was collected by laser-capture microscopy. The selected DAe-rgic neurons displayed changes in the expression of genes playing a role in cell death, synaptic transmission and mitochondrial activity. These biological func-tions were also identified as dysregulated in our microarray study. The implica-tion of the predominantly neuronal expression of our target genes is that future studies on gene function will have to be executed by experimental manipulations of these genes or their encoded proteins in neuronal cell lines and in neurons in vivo.

All genes studied by in situ hybridization and/or immunohistochemistry were selected because they were significantly dysregulated on the microarray. Quantitative analysis of the mRNA and protein expression in tissue sections in single neurons revealed that it was difficult to confirm the dysregulation as ob-served in the microarray study. Of the 10 target genes that we quantified, only one gene displayed the expected downregulation (ALDH1A1) while one gene (RGMA) showed a trend toward the expected increased expression. ALDH1A1 is involved in dopamine metabolism. It oxidizes the toxic compound 3,4-Dihydroxy-phenylacetaldehyde- a product of DA degradation by monoamine oxydases- to non toxic 3,4-dihydroxyphenylacetic acid. ALDH1A1 mRNA expression has been shown to be downregulated in PD SN DAergic neurons (Galter et al., 2003) and in blood samples from early PD patients (Grunblatt et al., 2010). To our knowledge, our study is the first showing ALDH1A1 protein significantly downregulated in the surviving DAergic neurons in PD.

The lack of consistency between the gene regulation detected by microar-ray and the regulation of protein expression in tissue sections has been noted be-fore (Chuaqui et al., 2002). There are several factors that can contribute to this. Firstly, neuronal proteins occupy multiple intracellular and extracellular com-partments. Therefore quantitative immunohistochemical analysis of the pro-tein content in the neuronal cell bodies may not necessarily result in an accurate reflection of the actual protein levels in the whole cell including its axons, den-drites and synapses. There can also be a change in axonal transport by which the amount of protein in the cell body does no longer reflect the changes in the pro-duction (Zhou et al., 2001). Moreover, some proteins are secreted and diffused in the extracellular space or bind to the extracellular matrix. RGMA is an example of a neuronal protein that upon secretion forms large, heavily stained, protein deposits that are difficult to quantify reliably. Secondly, depending on the half life of the protein, it may either accumulate in the cell or may be rapidly degrad-ed. Protein stability can have a profound effect on the actual protein levels in the

CH A PTER 2

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cell. Finally, methodological factors can influence the quantitative readouts for both mRNA and protein levels. The microarray study has been performed on a heterogeneous, relatively large piece of human PD SN tissue, containing intra-specimen cellular/molecular heterogeneity, which may not be accurately repre-sented in one section of the structure (Chuaqui et al., 2002).

The differential expression of transcript variants has been implicated in many neurodegenerative diseases (Beyer et al., 2008; Twine et al., 2011). LRDD, a gene encoding three splice variants, is responsible for cell fate determination after DNA damage detection. All three transcripts of LRDD induce pro-survival NFκB pathway activation and cell cycle arrest, whereas only variant 1 directly activates caspase-2, thereby inducing cellular apoptosis. Interestingly, variant 2 was shown to be protective against this pro-apoptotic activity of splice vari-ant 1, whereas variant 3, although unable by itself to activate caspase 2, further amplifies the pro-apoptotic effects of variant 1 (Cuenin et al., 2008). The spe-cific increase of LRDD variant 2 in PD SN tissue may indicate its role in coun-teracting the apoptotic changes in the neurons induced by LRDD splice variant 1 and amplified by highly expressed variant 3. It would be worth looking into the state of activation of caspase 2 in this tissue to further investigate this hy-pothesis. EHBP1, an endocytic trafficking gene, expresses four different splice variants with yet unknown differential biological functions. We cannot therefore conclude anything about the specific functional role of the upregulation of splice variant 3.

In conclusion, our cellular localization studies demonstrated that most genes that we identified in our microarray study function in neurons. Future studies on their role in PD should therefore be performed on a neuronal cellular model. In chapter 3 we have characterized the SH-SY5Y cell, a neuronal cell line with dopaminergic properties, and in chapter 4 we use these cells to perform a high content cellular screen to further investigate a large set of our PD targets.


85

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AP

1:25

Tyra

min

e

CD

K5

NM

_004

935

CD

K5

Citr

ic B

uffe

r pH

6.0

0.1%

milk

-TB

SSa

ntaC

ruz,

rabb

it po

lycl

onal

sc-1

731:

10A

BC

-stre

ptav

idin

DLK

1N

M_0

0383

6D

LK1

Tris

-HC

l pH

9.0

0.5%

milk

-TB

SPr

otei

ntec

h gr

oup,

rabb

it po

lycl

onal

1063

6-1-

AP

1:50

Tyra

min

e

EN1

NM

_001

426

En1

Tris

-HC

l pH

9.0

0.5%

milk

-TB

SC

hem

icon

, rab

bit p

olyc

lona

lA

B57

321:

100

AB

C-s

trept

avid

in

KC

NJ6

NM

_002

240

GIR

K2

Citr

ic B

uffe

r pH

6.0

-A

bcam

, rab

bit p

olyc

lona

lab

3073

81:

300

AB

C-s

trept

avid

in

HPR

T1N

M_0

0019

4H

PRT

Tris

-HC

l pH

9.0

0.5%

milk

-TB

SC

hem

icon

, rab

bit p

olyc

lona

lA

B98

821:

25Ty

ram

ine

LTF

NM

_002

343

LTF

Tris

-HC

l pH

9.0

-A

bcam

, rab

bit p

olyc

lona

lab

1581

11:

10A

BC

-stre

ptav

idin

NET

O2

NM

_018

092

NET

O2

Tris

-HC

l pH

9.0

0.1%

milk

-TB

SR

&D

syst

ems,

goat

pol

yclo

nal

AF3

859

1:50

AB

C-s

trept

avid

in

NR

4A2

NM

_006

186

Nur

r1C

itric

Buf

fer p

H 6

.01%

milk

-TB

SSa

nta

Cru

z, ra

bbit

poly

clop

nal

sc-9

911:

10A

BC

-stre

ptav

idin

NTR

K2

NM

_006

180

TrkB

Tris

-HC

l pH

9.0

2% m

ilk-T

BS

Sant

a C

ruz,

rabb

it po

lycl

onal

sc-8

316

1:50

AB

C-s

trept

avid

in

NTR

K2

trunc

ated

NM

_006

180

TrkB

trun

cate

dTr

is-H

Cl p

H 9

.00.

5% m

ilk-T

BS

Sant

a C

ruz,

rabb

it po

lycl

onal

sc-1

191:

100

Tyra

min

e

PLEK

HE1

NM

_194

449

SCO

PTr

is-H

Cl p

H 9

.0-

Shim

izu

et a

l. 19

99, r

abbi

t pol

yclo

nal

-1:

100

AB

C-s

trept

avid

in

PTM

AN

M_0

0282

3PT

MA

--

Abc

am, r

abbi

t pol

yclo

nal

ab76

557

1:20

0A

BC

-stre

ptav

idin

RG

MA

NM

_020

211

RG

MA

Tris

-HC

l pH

9.0

-Sa

nta

Cru

z, g

oat p

olyc

lona

lsc

-464

821:

25Ty

ram

ine

RIT

2N

M_0

0293

0R

IN1X

TB

S pH

7.6

-Si

gma,

mou

se m

onoc

lona

lR

190

21:

100

AB

C-s

trept

avid

in

RO

BO

2 N

M_0

0294

2R

OB

O2

Tris

-HC

l pH

9.0

0.5%

milk

-TB

SR

&D

syst

ems,

goat

pol

yclo

nal

AF3

147

Tyra

min

e

SDC

2J0

4621

SDC

2Tr

is-H

Cl p

H 9

.0-

van

Hor

ssen

et a

l 200

1, m

ouse

mon

oclo

nal

-1:

200

AB

C-s

trept

avid

in

Sem

a5A

NM

_003

966

Sem

a5A

Tris

-HC

l pH

9.0

-N

ovus

Bio

logi

cals

, mou

se p

olyc

lona

lH

0000

9037

-A01

1:10

0A

BC

-stre

ptav

idin

SLC

18A

2N

M_0

0305

4V

MAT

2C

itric

Buf

fer p

H 4

.0-

Che

mic

on, r

abbi

t pol

yclo

nal

AB

1767

1:30

0-

SNA

P91

NM

_014

841

AP1

80Tr

is-H

Cl p

H 9

.0-

Sigm

a, m

ouse

mon

oclo

nal

A48

251:

1000

AB

C-s

trept

avid

in

SNC

AN

M_0

0034

5α-

synu

clei

nC

itric

Buf

fer p

H 6

.0-

BD

Bio

scie

nces

, mou

se m

onoc

lona

l61

0786

1:50

0A

BC

-stre

ptav

idin

Supplementary Tables

CH A PTER 2

86

SYT1

NM

_005

639

Syna

ptot

ag-

min

1Tr

is-H

Cl p

H 9

.0-

Che

mic

on, c

hick

en p

olyc

lona

lA

B93

561:

500

AB

C-s

trept

avid

in

VIM

NM

_003

380

Vim

entin

Citr

ic B

uffe

r pH

6.0

-Si

gma,

chi

cken

pol

yclo

nal

V46

301:

1000

AB

C-s

trept

avid

in

THN

M_0

0036

0TH

All

treat

men

ts-

Jacq

ues B

oy, r

abbi

t pol

yclo

nal

2080

2023

41:

1000

-

Supp

lem

enta

ry T

able

1. T

issue

trea

tmen

t and

ant

ibod

ies u

sed

for i

mm

unoh

istoc

hem

ical

det

ectio

n of

pro

tein

s of i

nter

est.

Tabl

e in

dica

tes t

he

gene

nam

e, N

CBI d

ata

base

refe

renc

e nu

mbe

r, pr

otei

n na

me,

mic

row

ave

(MW

) ant

igen

trea

tmen

t con

ditio

ns, b

lock

ing

reag

ent u

sed,

ant

ibod

y an

d ca

talo

g nu

mbe

r, an

tibod

y di

lutio

n, a

nd d

etec

tion

met

hod.

Gen

e na

me

NC

BI

refe

renc

e nu

mbe

r

Prob

e se

quen

ce

(bas

e pa

irs)

PC

R p

rimer

forw

ard

PCR

prim

er re

vers

eM

W

pret

reat

-m

ent

Hyb

rid-

izat

ion

tem

p.

Prob

e co

ncen

t.

AL-

DH

1A1

NM

_000

689.

374

3-11

485’

- ATT

AA

CC

CTC

AC

TAA

AG

GG

AG

GC

AG

CAT

TTC

TTC

T-C

AC

A-3

’5’

- TA

ATA

CG

AC

TCA

CTA

TAG

GG

CC

TCC

TCC

A-

CAT

TCC

AG

TTT-

3’Ye

s55

°C15

00ng

/ml

DY

NC

1I1

NM

_004

411.

414

10-1

859

5’-A

TTA

AC

CC

TCA

CTA

AA

GG

GA

AG

GA

GTA

GA

GC

GC

TT-

GTT

GTG

C-3

’5’

-TA

ATA

CG

AC

TCA

CTA

TAG

GG

TGC

AG

CG

GA

-C

AC

CC

TTAT

CA

G-3

’Ye

s55

°C15

00ng

/ml

EH

BP

1N

M_0

1525

2.3

2988

-330

55’

- ATT

AA

CC

CTC

AC

TAA

AG

GG

AC

GG

GG

AAT

AA

GC

-C

AAT

AC

-3’

5’-T

AAT

AC

GA

CTC

AC

TATA

GG

GTC

GG

GA

GTA

T-C

AA

GG

TCAT

-3’

Yes

55°C

1500

ng/m

l

ND

NN

M_0

0248

7.2

1417

-143

5LN

A -2

’Om

ethy

l-RN

A pr

obe:

5’-F

AM

-Tug

Cug

Gug

Acu

TcuT

ccA

-3’

Yes

55°C

100n

M

RG

MA

NM

_020

211.

211

69-1

187

LNA

-2’O

met

hyl-R

NA

prob

e: 5

’-FA

M-T

ugA

ccA

cuTc

cTcu

Ggc

A-3

’Ye

s55

°C25

nM

SLI

TRK

5N

M_0

1556

7.1

3067

-342

95’

-ATT

AA

CC

CTC

AC

TAA

AG

GG

AG

AA

AA

AC

AG

AC

CA

C-

GTT

TAG

CC

-3’

5’-T

AAT

AC

GA

CTC

AC

TATA

GG

GA

CC

ATTC

TTA

G-

CA

CTT

CC

AA

CC

-3’

Yes

55°C

2000

ng/m

l

SO

X2

NM

_003

106.

289

0-12

125’

-ATT

AA

CC

CTC

AC

TAA

AG

GG

AC

AG

CG

CAT

GG

AC

AG

T-TA

C-3

’5’

- TA

ATA

CG

AC

TCA

CTA

TAG

GG

CTG

GA

GTG

GG

AG

-G

AA

GA

G-3

’N

o57

°C25

00ng

/ml

Supp

lem

enta

ry T

able

2. I

n sit

u hy

brid

izat

ion

prob

e se

quen

ces,

PCR

prim

er se

quen

ces a

nd h

ybrid

izat

ion

cond

ition

s for

8 g

enes

. PCR

prim

ers w

ere

desig

ned

with

T7

and

T3 p

rom

oter

sequ

ence

s (in

dica

ted

in b

old)

. Abb

revi

atio

ns: M

W- m

icro

wav

e.


87

Gen

e na

me

NC

BI r

efer

ence

num

ber

qPC

R p

rimer

forw

ard

qPC

R p

rimer

reve

rse

Varia

nt

Hou

seke

epin

g ge

nes

AC

TBN

M_0

0110

1TC

CC

TGG

AG

AA

GA

GC

TAC

GA

AG

GA

AG

GA

AG

GC

TGG

AA

GA

G

MR

PL2

4N

M_0

2454

0 G

GA

GA

CC

CG

GA

AAT

AC

AA

GA

AG

GT

TGG

CAT

CTG

AA

AA

AG

AA

GTG

CC

DH

X16

NM

_003

587

TTG

AC

TCG

GA

GTG

GC

TAC

CG

AG

CG

TGG

CTG

TTG

CTC

AA

AG

A

Gen

es o

f int

eres

t

LRD

DN

M_0

1849

4.3

GAT

CTG

GG

AC

CTC

GG

AC

GTT

GC

CC

TCC

TGG

GA

AG

varia

nt 2

LRD

DN

M_1

4588

6.3

& N

M_0

1849

4.3

GA

AG

AG

TTC

TTTG

CG

GC

GA

GTG

GTG

GTC

AC

GTA

Tva

riant

1 a

nd 2

LRD

DN

M_1

4588

7.3

GA

AG

AG

TTC

TTTG

CG

GC

GTA

GA

AG

GA

CA

CC

TCC

TTva

riant

3

AR

HG

EF2

NM

_004

723.

3A

GC

GG

AC

CTG

GG

CTT

GG

T

GA

GC

AA

CTT

TCTT

TCA

AG

CG

GC

va

riant

3

AR

HG

EF2

NM

_001

1623

83.1

& N

M_0

0116

2384

.1C

TGTC

CC

CG

AG

AC

CA

AC

G

CC

GG

CG

TCC

TGTA

TTG

TTG

varia

nt 1

and

2

EH

BP

1N

M_0

1525

2.3

GC

TCTG

AG

CA

GC

TTA

GAT

GA

AG

CTG

GC

TGAT

TTA

GC

TGA

AC

Gva

riant

1

EH

BP

1N

M_0

0114

2615

.2C

AG

AA

CTG

GG

TTG

CTT

GC

TATG

GTT

AG

GTG

GTT

GG

CTT

Gva

riant

3

EH

BP

1N

M_0

1525

2.3

& N

M_0

0114

2616

.1TG

GC

TGG

CTT

GG

CTG

TTC

GC

CC

CG

TTC

CC

TTC

TCAT

Ava

riant

1 a

nd 4

EH

BP

1N

M_0

1525

2.3

& N

M_0

0114

2614

.1A

AG

GC

TTTG

TTG

TAG

GA

GG

TTC

GG

GA

GTA

TCA

AG

GTC

ATT

varia

nt 1

and

2

Supp

lem

enta

ry T

able

3. q

PCR

prim

er se

quen

ces f

or h

ouse

keep

ing

gene

s and

3 g

enes

of i

nter

est d

etec

ting

spec

ific t

rans

crip

t va

riant

CH A PTER 2

88

Biological function p-value # of molecules

Neurological Disease 1,13E-09-3,05E-02 67

Cellular Function and Maintenance 5,19E-09-4,02E-02 58

Cell-To-Cell Signaling and Interaction 6,22E-09-3,78E-02 30

Nervous System Development and Function 6,22E-09-4,31E-02 46

Molecular Transport 1,8E-08-3,78E-02 33

Small Molecule Biochemistry 1,8E-08-3,78E-02 43

Genetic Disorder 5,03E-08-3,78E-02 91

Cellular Assembly and Organization 3,4E-06-4,31E-02 32

Psychological Disorders 9,96E-06-3,46E-02 27

Cellular Movement 1,09E-05-4,31E-02 14

Drug Metabolism 1,49E-04-3,72E-02 12

Cellular Compromise 1,62E-04-4,31E-02 21

Amino Acid Metabolism 2,31E-04-3,78E-02 6

Nucleic Acid Metabolism 2,31E-04-3,78E-02 10

Cancer 4,04E-04-4,31E-02 64

Cell Morphology 4,04E-04-4,31E-02 29

Protein Trafficking 4,76E-04-4,02E-02 9

Carbohydrate Metabolism 4,83E-04-4,31E-02 7

Lipid Metabolism 4,83E-04-3,78E-02 19

Skeletal and Muscular Disorders 8,35E-04-3,78E-02 14

Reproductive System Disease 1,89E-03-3,78E-02 24

Developmental Disorder 1,94E-03-3,78E-02 22

Cell Death 3,18E-03-3,83E-02 45

Cell Cycle 3,41E-03-3,78E-02 12

Hepatic System Disease 5,51E-03-3,78E-02 5

Cardiovascular Disease 6,23E-03-3,78E-02 9

Organ Morphology 6,23E-03-3,78E-02 9

Dermatological Diseases and Conditions 6,83E-03-2,54E-02 3

Cellular Development 7,76E-03-4,02E-02 13

Embryonic Development 8,12E-03-3,79E-02 21

Renal and Urological Disease 8,46E-03-2,54E-02 6

DNA Replication, Recombination, and Repair 9,85E-03-3,78E-02 12

Endocrine System Development and Function 9,85E-03-3,78E-02 6

RNA Post-Transcriptional Modification 9,85E-03-9,85E-03 2

Connective Tissue Development and Function 9,96E-03-4,31E-02 11

Supplementary Table 4. Significantly regulated biological functions in PD SN indicated by an unbiased Ingenuity Pathway Analysis. All 287 significantly regulated PD genes were imported for the analysis. Table indicates biological functions, their overrepresentation significance (cut off p<0.01), and the number of regulated molecules present in the function.

89

90

CHAPTER 3

Phenotypic characterization of retinoic acid differentiated

SH-SY5Y cells by transcriptional profiling

J.A. Korecka1, R.E. van Kesteren2, E.Blaas2, S.O. Spitzer1,a, A.B. Smit2, D.F. Swaab3

J. Verhaagen1,2, K. Bossers1

Submitted


Amsterdam, The Netherlands2 Center for Neurogenomics and Cognitive Research, Neuroscience Campus Amsterdam, VU Univer-

sity, Boelelaan 1085, 1081HV, Amsterdam, The Netherlands

3 Neuropsychiatric Disorders, Netherlands Institute for Neuroscience, An Institute of the Royal Neth-erlands Academy of Arts and Sciences, Meibergdreef 47, 1105BA,

Amsterdam, The Netherlandsa Present address: MRC Center for Stem Cell & Regenerative Medicine and Department of Veterinary

Medicine, University of Cambridge, UK

92

CH A PTER 3

Abstract

Multiple genetic and environmental factors play a role in the development and progression of Parkinson’s disease (PD). The main neuropathological hall-mark of PD is the degeneration of dopaminergic (DAergic) neurons in the sub-stantia nigra pars compacta (SN). To study genetic and molecular contributors to the disease process, there is a great need for readily accessible cells with prominent DAergic features that can be used for reproducible in vitro cellular screening. Here, we investigated the molecular phenotype of retinoic acid (RA) differentiated SH-SY5Y cells using genome wide transcriptional profiling com-bined with gene ontology, transcription factor and molecular pathway analysis. We demonstrated that RA induces a general neuronal differentiation program in SH-SY5Y cells and that these cells develop a predominantly mature DAergic neurotransmitter phenotype. This phenotype is characterized by increased do-pamine levels together with substantial suppression of other neurotransmitter phenotypes, such as those for noradrenaline, acetylcholine, glutamate, serotonin and histamine. In addition, we show that RA differentiated SH-SY5Y cells ex-press the typical neurotransmitter transporters that are responsible for uptake of MPP(+), a well known DAergic cell toxicant, and that MPP(+) treatment alters mitochondrial activity according to its proposed cytotoxic effect in DAergic neu-rons. Taken together, RA differentiated SH-SY5Y cells have a DAergic-like phe-notype, and provide a good cellular screening tool to find novel genes or com-pounds that affect cytotoxic processes that are associated with PD.

MICROA R R AY OF R A DIFFER EN TI ATED SH-SY5Y CELLS

93

Introduction

Parkinson’s disease (PD) is the second most prevalent age-related neuro-degenerative disease. The primary clinical symptoms consist of deficits in motor behavior such as tremor, muscle rigidity, postural instability, akinesia and bra-dykinesia (Dauer and Przedborski, 2003) as well as cognitive dysfunction (Niko-laus et al., 2009; Olanow et al., 2009). The motor symptoms are caused by the selective loss of the dopamine (DA) neurons in the substantia nigra pars compac-ta (SN) leading to depletion of striatal dopamine levels. Several mutations have been found that cause rare, familial forms of PD in genes such as SNCA, PARK2, DJ-1, PINK1, LRRK2 and PARK9 (Bonifati, 2007; Bonifati et al., 2003). These fa-milial forms account for only 5% of the patients, whereas most PD cases are spo-radic (Dauer and Przedborski, 2003). The etiology of sporadic PD appears to be multifactorial including both genetic and environmental factors (Gorell et al., 2004; Wirdefeldt et al., 2011). So far, several cellular defects, such as the forma-tion of Lewy bodies (Spillantini et al., 1997; Braak et al., 2003), mitochondrial dysfunction and increased oxidative stress, have been linked to the disease, al-though these cannot fully explain the molecular basis of the disease (Greena-myre and Hastings, 2004).

Recently, several genome-wide gene expression studies on postmortem hu-man brain tissue have identified transcriptional alterations that are associated with sporadic PD (Grunblatt et al., 2004; Mandel et al., 2005; Miller et al., 2006; Hauser et al., 2005; Lewandowski et al., 2010; Moran et al., 2006; Simunovic et al., 2009; Zhang et al., 2005; Bossers et al., 2009). These alterations may either be causally involved in the development of sporadic PD, or be the consequence of the progression of the disease. The functional interpretation of the molecular signa-tures obtained by transcriptional profiling poses a challenge and gene function analysis is dependent on a reliable cellular model enabling large-scale function-al screening of genes. An adequate cell model for research on PD gene function should: 1. display the main cellular and molecular features that are characteris-tic of DA neurons, 2. be sensitive to perturbations in cellular processes that are commonly associated with PD, and 3. be suitable for up-scaled cellular screening, in which the function of many genes, proteins and compounds can be examined in a high-throughput and high-content manner.

One potentially suitable cell model is the human neuroblastoma SH-SY5Y cell line, which was originally derived from the SK-N-SH cell line (Biedler et al., 1978). SH-SY5Y cells have been used frequently, either in an undifferentiated state (Cheung et al., 2009; Conn et al., 2003; Brill and Bennett, Jr., 2003; Ding et al., 2004), or in a neuron-like differentiated state after induction with all-trans-retinoic acid (RA) (Kaplan et al., 1993; Cuende et al., 2008; Miloso et al., 2004; Rossino et al., 1991; Pan et al., 2005; Truckenmiller et al., 2001; Lopez-Carballo et al., 2002; Kito et al., 1997). The specific neurotransmitter phenotype of SH-SY5Y cells differentiated with RA is still unclear. RA treatment has been shown to in-

CH A PTER 3

94

duce the expression of tyrosine hydroxylase (TH), suggesting a shift towards a DA neurotransmitter phenotype (Lopes et al., 2010). However, others did not observe changes in the expression of key DA-cell markers in RA treated cells (Cheung et al., 2009). RA treatment has also been reported to induce a cholin-ergic phenotype (Zimmermann et al., 2004). The lack of an unequivocal charac-terization of the transmitter phenotype of RA differentiated SH-SY5Y cells cur-rently impacts on the potential relevance of these cells for PD research.

In 1982, 1-methyl-4-phenyl1,2,3,6-tetrahydropyridine (MPTP) was discov-ered, a neurotoxin which induced rapid PD symptoms in exposed humans. Neu-ropathological examination of the brains of these subjects revealed a moderate to severe loss of DAergic neurons in the SN (Langston et al., 1999). In the brains of exposed individuals, 1-methyl-4-phenyl-pyridium (MPP(+)), an active metabo-lite of MPTP, is taken up by DA neurons via the dopamine (DAT) and noradrena-line transporter (NAT) (Pifl et al., 1996), resulting in the inhibition of complex 1 of the mitochondrial electron transport chain, rapid ATP depletion, loss of mi-tochondrial membrane potential and the formation of reactive oxygen species (ROS) (Nakamura et al., 2000; Lotharius and O’Malley, 2000), together leading to cellular dysfunction and cell death (Nicotra and Parvez, 2002).

MPP(+) treated SH-SY5Y cells have been widely used as an in vitro model to study mitochondrial impairments observed in PD. So far, two gene expres-sion profiling studies investigated the effect of MPP(+) treatment on undiffer-entiated SH-SY5Y cells (Brill and Bennett, Jr., 2003; Conn et al., 2003). In these studies, mitochondrial stress indeed preceded cellular death, but the relevance of these studies for PD research is so far unclear because the neurotransmit-ter phenotype of these undifferentiated cells was not studied. This is of impor-tance, since both PD and MPP(+) specifically induce cell death in SN DA neurons, which suggests an interaction between the DA neurotransmitter phenotype and PD-associated mitochondrial stress. For example, MPP(+) is not only selectively transported into DAergic neurons, but it also binds with high affinity to VMAT2, a protein that transports DA into vesicles. The interaction between VMAT2 and MPP(+) causes excessive release of DA into the cytoplasm, increasing ROS gen-eration, which subsequently contributes to cell death (Lotharius and O’Malley, 2000). Thus, it is of importance to know if SH-SY5Y cells display any typical DAe-rgic characteristics that enable the study of MPP(+) toxicity in a PD-like context.

Genome-wide transcriptional analysis of specific neuronal cell types is a powerful method to investigate their molecular properties, ascertain their lin-eage and study their differentiation characteristics (Cahoy et al., 2008; Kurimoto and Saitou, 2010). Here we used large-scale transcriptional profiling combined with gene ontology and pathway analysis to determine the molecular phenotype of SH-SY5Y cells. We then used high-content microscopy to assess the mitochon-drial activity of RA-differentiated SH-SY5Y cells, challenged with MPP(+). Our observations indicate that SH-SY5Y cells have a molecular phenotype character-


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istic for DAergic cells, and are an appropriate model to study the effects of PD related mitochondrial inhibition on cell viability and function.

Materials & Methods

Cell culture and MPP(+) treatment

Human SH-SY5Y neuroblastoma cells were obtained from The European Collection of Cell Culture (ECACC, 94030304, Sigma-Aldrich). Cells were cultured in Dulbecco’s Modified Eagle’s Medium (DMEM)/F-12 without L-glutamine (Invi-trogen) supplemented with 0.5% fetal calf serum (FCS), 100U/ml penicillin (Sig-ma) and 0.1mg/ml streptomycin (Sigma) for 8 days at 37°C in 5% CO2. Cells were grown in 96-well plates coated with 0.1mg/ml poly-L-lysine (PLL, Sigma) and 1mg/ml growth factor reduced Matrigel Matrix without phenol red (BD Biosci-ences). 10,000 cells per well were plated. As we were interested in the effects of retinoic acid on the growth and differentiation of SH-SY5Y cells, as well as in the toxic effects of MPP+, cultured cells were assigned to three treatment groups: culture in medium only (noRA), culture with medium and 1µM all trans-retinoic acid (RA, Sigma), and culture with medium, 1µM RA and 0.01mM MPP+ (RA/MPP(+), Sigma-Aldrich) (Figure 1).

RNA isolation and quality control

Cells were harvested for RNA isolation at the time points indicated in Fig-ure 1. Cells were lysed by adding 50µl of Trizol Reagent (Invitrogen) to each well, followed by incubation on ice for 10min. Each time point/treatment condi-tion consisted of 30 wells, divided into three replicates of 10 pooled wells. Phase separation was performed with chloroform and Phase Lock Gel (5 Prime). The

Figure 1. Culture setup of SH-SY5Y cells treated with or without RA. Cells were cultured for 8 days in medium only (the noRNA group) or in medium supplemented with 1μM retinoic acid (the RA group). Cells were harvested for RNA isolation at the indicated time points.

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final aqueous phase was diluted with an equal volume of 70% ethanol. RNA was isolated using RNeasy Micro columns (Qiagen) according to the manufacturer’s instructions. RNA quantity and purity were determined by NanoDrop ND-1000 spectrophotometer (Nanodrop Technologies) and RNA integrity was determined using the RNA Integrity Number (RIN) measured on an Agilent 2100 Bioanalyz-er (Agilent Technologies).

RNA labeling and microarray hybridization

RNA samples were amplified and labeled with either Cy5-CTP or Cy3-CTP using the two-color Low Input Quick Amp Labeling Kit (Agilent Technologies) and purified with the RNA Micro kit according to the manufacturer’s protocol. Quality control was performed where cRNA quantity and dye integration were determined by NanoDrop measurement and cRNA fragment length was investi-gated with the Bioanalyzer.

Labeled cRNA was hybridized on Agilent 4x44K Whole Human Genome arrays (Agilent Technologies, Part Number G4112F) according to the manufac-turer’s protocol. Briefly, 825ng of Cy3-CTP or Cy5-CTP labeled cRNA were frag-mented for 30min at 60°C in 1X fragmentation buffer (Agilent Technologies) and loaded onto the array in 1X GEx Hybridization Buffer (Agilent Technologies). Ar-rays were incubated at 60°C in a rotating hybridization chamber for 17h, after which they were washed in 6xSSPE 0.005% N- Lauroylsarcosine (Sigma-Aldrich) for 5min and in 0.06xSSPE 0.005% N-Lauroylsarcosine for one minute. Finally, slides were washed in acetonitril (Sigma-Aldrich) for 30 seconds and dried in a nitrogen flow. Microarrays were scanned in an Agilent DNA Microarray Scanner at 5µm resolution at 10% and 100% PMT settings. Scan images were combined and quantified using Agilent Feature Extraction Software (version 9.5.1). The hy-bridization set up can be found in the Supplementary Figure 1.

Microarray normalization and single gene analysis

Raw expression data, generated by Feature Extraction software, was im-ported into the R statistical processing environment using the LIMMA package (Smyth, 2004) in Bioconductor (http://www.bioconductor.org). All features for which one or more foreground measurements were flagged as non-uniformity outlier or as saturated outliers were excluded from further analysis. We previ-ously demonstrated that the intensity-based analysis of complex ratio-based designs is more efficient and powerful than the standard ratio-based analysis (Bossers et al., 2010). We have therefore used an intensity-based analysis for this dataset. The individual signal intensities were extracted from the ratio measure-ments and 2log transformed intensity measurements were used for further anal-ysis. Normalization between arrays was performed using the quintile algorithm in LIMMA. Due to the hybridization scheme, some samples were hybridized in duplicate - in this case the mean expression level of the duplicates was used.


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To detect genes with differential expression between treatment conditions (RA versus noRA) and during the time of culture, a two-way analysis of variance (ANOVA) was performed on the 2log transformed intensity levels for each probe to detect features with a significant interaction between treatment and time in culture. All values were corrected for multiple testing using the Benjamini-Hoch-berg (BH) algorithm. All corrected p-values < 0.05 were considered significant.

Cluster analysis, pathway analysis and transcription factor selection

To visualize the relationship between all treatment-time point combina-tions, unsupervised cluster analysis was performed on all genes with a signifi-cant change in expression (p<0.05) after BH correction using the heatmap func-tion in R. Additionally, temporal profiles were created for the RA group for each gene by: 1. normalizing expression values by subtracting the average expression of all measurements, and 2. averaging the expression for each treatment-time point condition. These temporal profiles were clustered into 20 clusters using a soft clustering approach based on fuzzy c-means using the M-Fuzz package (ver-sion 16.0) in Bioconductor to detect patterns of co-regulated genes over time for each treatment group. Clusters with up or down regulation of gene expression in time were chosen for further analysis using Ingenuity Pathways Analysis (IPA) and Gene Ontology GOstat software(Beissbarth and Speed, 2004).

In order to further examine the RA differentiation process, all transcrip-tion factors (TF’s) were selected from the significantly regulated gene list. TF genes were selected based on regular expression terms indicating a tran-scriptional function of the gene: “transcription, zinc.*f, EF.*hand, forkhead, homeo(.*domain|.*box), nucleic.*acid, nuclear(.*factor|.*receptor), DNA\Wbind-ing, Helicase, \Wets\W, Kruppel” (Stam et al., 2007). All TF hits were further con-firmed and their specific functional roles analyzed with the NCBI Entrez Gene database.

Reverse transcription and quantitative PCR

180ng of each RNA sample was reverse transcribed using the QuantiTect Reverse Transcription Kit (Qiagen). 1/250 or 1/300 of total cDNA was used for each qPCR reaction, depending on the expression level of each gene. In each reac-tion 3pmol of forward and reverse primer (see Supplementary Table 1 for primer sequences) was used with 10µl 2xSYBR green ready reaction mix (Applied Bio-systems, Foster City, CA, USA), totaling a volume of 20µl per reaction. Reactions were carried out on an ABI 7300 sequence system (Applied Biosystems). Each primer pair was checked for primer dimers by analyzing dissociation curves. As housekeeping genes we used the most stably expressed genes in the micro-array dataset. Six genes were selected, based on their biological function, such as cytoskeleton or mitochondrial related, and tested with qPCR (SELK, PPP1R8, NDUFV2, NY-SAR-48, PRKCZ, UQCRFS1). With the use of GeNorm software (Van-

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desompele et al., 2002) the final three most stable housekeeping genes were identified (NDUFV2, NY-SAR-48 and PRKCZ) and the normalization factor was calculated.

Immunocytochemical staining

Cells were cultured in 24-well plates on glass cover slips as described above and fixed with 4% paraformaldehyde (PFA) (Sigma) for 30min followed by 30min blocking at room temperature (RT) in blocking buffer (1x phosphate buff-ered saline (PBS), 0.5% Triton X-100 (Sigma), 0.25% gelatin (Merk) and 2% fetal calf serum (FCS). The following primary antibodies were applied in 1XPBS/2% FCS/0.25% gelatin (Merk)/0.5% Triton X-100 (Sigma) and incubated at 4°C over-night: anti-tyrosine hydroxylase (TH) (rabbit, Institute Jacques Boy SA, Reims, France, 208020234) at 1:200, DBH (chicken, Millipore, AB1537) at 1:200, and an-ti-dopamine at 1:100 (rabbit, (Geffard et al., 1984). Cells were washed and labeled with either Alexa 488 or Alexa 594 anti-mouse, rabbit, goat or sheep antibodies (Invitrogen, Carlsbad, CA, USA), depending on the applied primary antibodies, at 1:800 dilution for 2h at RT in 1xPBS/2% FCS followed by 20min nuclear staining with Hoechst 1:20,000 in 1xPBS. Cells were mounted in Mowiol solution (0.1 M Tris pH 8.5, 25% glycerol, 10% w/v Mowiol 4-88 (Sigma)) and analyzed with the use of a Confocal Laser Section Microscopy (CLSM, Zeiss, Sliedrecht, The Nether-lands).

High-content analysis of mitochondrial activity

SH-SY5Y cells were cultured and treated with 0.01mM MPP+ as indicated in Figure 1. Cells were fixed after 8 days and incubated with 100nM MitoTracker solution (Molecular Probes) diluted in PBS for 20min at RT. Cells were washed 2x 5min in PBS, and nuclear staining was then performed by incubating cells in 100 ml Hoechst 33258 (Molecular Probes; 10 mg/ml, diluted 1:20,000 in H2O) for 20min at RT. Cells were washed 2x 5min in H2O and left in H2O for image col-lection. Image acquisition and analysis were performed using an ArrayScan VTI HCS Reader instrument and the Compartmental Analysis Bioapplication. Twenty images per well were collected, and mitochondrial activity was measured on a per cell basis quantifying both the number and the intensity of MitoTracker-posi-tive spots in the cytoplasmic region of the cell. Readout from five wells was aver-aged and biological replicates were merged. Statistical analysis was performed using student t-Test. P values under 0.05 were considered significant.

Protein isolation and Western blot analysis

For Western blot analysis cells were cultured as described above in 24 well plates in two conditions: RA treated and noRA treated. On day 8, cells were in-cubated on ice for 10 min in 70µl RIPA buffer (25mM Tris-HCl pH 7.4 (Sigma), 150mM NaCl (Sigma), 1% NP40 (AppliChemicals), 1% sodium deoxycholate


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(Sigma), 0.1% SDS and 1x Complete Protease Inhibitor (Roche)). The cell lysate was then collected, sonicated and the protein concentration was calculated with bicinchoninic acid protein assay kit (Pierce, Thermo Scientific). For West-ern blot analysis, each sample was heated in 5xloading buffer containing 10% sodium dodecyl sulphate (SDS, MP Biomedicals) and 5% ß-mercaptoethanol (Sigma) at 95°C for 5min and loaded on 8% SDS gel. Tris-glycine sodium dodecyl sulphate polyacrylamide gel electrophoresis was performed using the BioRad Mini-PROTEAN 3 gel electrophoresis system (Bio-Rad Laboratories, Hercules, CA, USA) and proteins were semi-dry transferred to nitrocellulose membranes and blocked with 5% fat-free milk powder in 1xtris buffered saline (TBS)/0.05% Tween-20 (Sigma) for 1 h at room temperature. Blots were incubated with anti-bodies against DBH at 1:200, ß-actin (mouse, Sigma-Aldrich, A5316) at 1:1000, and DJ1 (rabbit, Novus Biologicals, NB300-270) at 1:1000 at 4°C overnight in TBS/0/05% Tween-20. The primary antibodies were further detected, first with biotyn anti-sheep antibody (Vector laboratories) at 1:400 dilution and then with SA-Cy5 (Jackson’s Lab) at 1:800 for DBH detection, anti-rabbit Cy5 at 1:800 for DJ1 detection, and anti-mouse IR-dye 800 at 1:2000 for ß-actin detection. Blots were scanned and analyzed using the Odyssey Infrared Imager and Odyssey 2.1 scanning software (LI-COR biosciences). The ß-actin signal was used to normal-ize the final protein quantifications.

Detection of functional DAT and NAT

DAT and NAT activity in RA-differentiated SH-SY5Y cells were measured using different concentrations (0,003 µM - 3.0 µM) of the selective DAT inhibi-tor 1-(2-[bis(4-fluorophenyl)methoxy] ethyl)-4-(3 phenylpropyl) piperazine (GBR 12909) or with different concentrations (0,0001 µM – 0,1 µM) of the se-lective NAT inhibitor desipramine (DMI) in culture medium for 1h as previ-ously described (Schoffelmeer et al., 2011). In short, cultures were incubated for 20min at 37°C with 1mM [3H]DA in Krebs-Ringer buffer (16mM sodium phos-phate, 119mM NaCl, 4.7mM KCl, 1.8mM CaCl2, 1.2mM MgSO4, 1.3mM EDTA, and 5.6mM glucose; pH 7.4). Nonspecific uptake was measured in the presence of 10 µM mazindol. After washing three times with ice-cold Krebs-Ringer buffer, cells were lysed in 1N NaOH and [3H] DA uptake was determined by liquid scintilla-tion counting. Specific [3H] DA uptake was calculated by subtracting the amount of uptake measured in the presence of mazindol.

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Results

Retinoic acid induces neuronal differentiation of SH-SY5Y cells

Gene expression changes induced by RA treatment

To study the effects of RA on the differentiation of SH-SY5Y cells we per-formed a microarray analysis of RA treated and untreated cells during an eight-day culture period. After hybridization, 2329 microarray probes (representing 2020 genes) showed differential gene expression in RA cells compared to noRA cells(BH-corrected p<0.05, ANOVA-derived interaction between treatment and time in culture). The 50 genes most significantly regulated following RA treat-ment are listed in Table 1 (for all significantly regulated genes, see Supplemen-tary Table 2). Real time quantitative PCR (qPCR) was used to validate the sig-nificant changes in expression of 10 selected genes as identified by microarray analysis (Supplementary Table 1, including sequences of used primers). Gene ex-pression levels as measured by microarray and qPCR were highly correlated (see Supplementary Table 1 for correlation coefficient values).

IPA confirmed that RA induces the retinoic acid receptor (RAR) signaling pathway, as the significantly regulated genes in RA cells are highly enriched for members of this pathway (p = 0.013) (Supplementary Figure 2). For example, RAR-A and -B, which control all RA induced signaling, are highly upregulated fol-lowing RA treatment (fold change D8 RA/noRA 2.79 and 23.45 respectively).

RA regulates cellular differentiation and proliferation

Unsupervised hierarchical cluster analysis of the expression levels of all significant genes showed a clear distinction based on treatment condition and time in culture (Figure 2A). Except for Day 1, the RA treatment induced a highly distinct gene expression program on which treatments can be separated. Addi-tionally, in RA treated cells, we observed distinct expression differences between the early time points (days 3 and 4) and later time points (days 5 and 8), indicat-ing that the time of culture played a role in RA induced expression changes. To a lesser extent, time of culture also determined the gene expression profile of cells not treated with RA, with days 1 and 2 clustering together and days 3, 4 and 5 forming a distinct cluster. Day 8 stands separate. In general, gene expression changes are less pronounced during time in culture in noRA cells as compared to RA treated cells.

We also performed a gene expression cluster analysis of the temporal pat-terns that emerged over time of culturing for all detectable genes in RA treated cells. Four clusters (Figure 2B; clusters 2, 13, 3 and 4) out of a total of 20 clus-ters (Supplementary Figure 3) showed a clear directional pattern of expression, with genes in clusters 2 and 13 downregulated over time, and genes in clusters


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Tabl

e 1.

List

of t

he 5

0 m

ost s

igni

fican

tly re

gula

ted

gene

s in

RA tr

eate

d SH

-SY5

Y ce

lls co

mpa

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to n

oRA

cells

as i

dent

ified

by

mic

roar

ray

anal

ysis.

Gen

e ex

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essio

n fo

ld ch

ange

s are

giv

en fo

r the

com

paris

on o

f RA

trea

ted

cells

on

day

8 (D

8) v

ersu

s RA

day

1 (D

1), n

oRA

D8

vers

us n

oRA

D1 a

nd R

A D

8 ve

rsus

noR

A D

8. T

he la

st co

lum

n in

dica

tes t

he cl

uste

r num

ber t

o w

hich

that

gen

e is

assig

ned

base

d on

its e

xpre

ssio

n pr

ofile

(see

Sup

plem

enta

ry F

igur

e 2)

. CXC

R4 a

nd

CR61

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pres

ente

d by

mor

e th

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ne p

robe

in th

e lis

t and

the

corr

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nd fo

ld ch

ange

s wer

e av

erag

ed. P

-val

ues a

re B

enja

min

i-H

ochb

erg

corr

ecte

d. T

he co

mpl

ete

list o

f all

signi

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gene

s can

be

foun

d in

Sup

plem

enta

ry Ta

ble

2.

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3 and 4 upregulated over time. Gene Ontology analysis (GOstat) and IPA were performed to determine which biological processes are overrepresented in these temporal clusters (Supplementary Table 3). These biological processes can be grouped into five functional categories: development, cellular development, neu-ronal function, proliferation and cell death.

RA induces the expression of transcription factors that regulate neuronal differentiation

To investigate the molecular mechanisms by which RA alters cellular de-velopment, we examined the effects of RA on the expression of transcription fac-tors (TFs). We identified 103 significantly regulated TFs in RA-treated cells. Us-ing gene function references derived from the NCBI Gene and IPA databases, we aimed at uncovering the biological function of each TF (Supplementary Table 4). We found 74 TFs with known functions. Out of these 74 TFs, 20 regulate cellular development and differentiation. Most of these were positive regulators of differ-entiation, and three are both positive and negative regulators of cellular differ-entiation i.e. ID1 (RA/noRA 2.79), SP1 (RA/noRA 1.45) and ZNF521 (RA/noRA 3.39). At day 8, 13 pro-differentiation TFs were upregulated in RA treated cells as compared to untreated cells. Examples of upregulated pro-differentiation TFs include ALX3 (fold change RA/noRA 1.42), KLF13 (RA/noRA 2.43) and NR4A3 (RA/noRA1.6). In contrast, only 4 pro-differentiation TFs are downregulated in RA treated cells, i.e. ELF4 (RA/noRA 0.25), SIX6 (RA/noRA 0.41), E2F5 (RA/noRA 0.42) and RUNX1 (RA/noRA 0.45).

In addition to the predominant upregulation of TFs that promote general cellular differentiation, RA alters the expression of 13 TFs that are known to specifically stimulate neuronal development/differentiation and function. RA treatment increases the expression of 6 positive regulators of neuronal devel-opment and differentiation i.e. NCOA7 (RA/noRA 3.97), TLX2 (RA/noRA 2.79), ID3 (fold change RA/noRA 2.11), NFE2L2 (RA/noRA 1.68), ZNRF1 (RA/noRA 1.27) and HOXD10 (RA/noRA 3.30). Moreover, 4 negative regulators of neuronal differentiation and function are downregulated after RA treatment i.e. TFAP2B (RA/noRA 0.37), ISL1 (RA/noRA 0.56),SIX3 (RA/noRA 0.41) and ATF5 (RA/noRA 0.55). Only one neuronal differentiation and neuronal survival promoting TF, MEF2C, is downregulated after RA treatment (RA/noRA 0.63). Two TFs that are responsible for neuronal differentiation are downregulated during the time of culture independently of RA treatment i.e. MSX2 (RA/noRA 0.92)and PHOX2B (RA/noRA 0.92).

We also observed RA-induced changes in the expression of TFs that are in-volved in regulating apoptosis and cell death; 4 pro-apoptotic TFs were upregu-lated and 3 were downregulated after RA treatment. Finally, 14 TFs involved in cellular proliferation were also changed after RA treatment: 6 pro-proliferation TFs were upregulated and 7 were downregulated. CGREF1, a negative regulator of proliferation, was also downregulated (RA/noRA 0.49). The functional impli-


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Figure 2. Regulation of gene expression in RA treated cells. A. Heat-map of all significantly regu-lated genes indicates that differences in gene expression can be used to separate both treatment condition and time in culture. Day of culture, the biological replicate, and the culture conditions are indicated on the X-axis. On the Y-axis each row represents one gene. Green indicates down-regulation, and red indicates upregulation in expression represented in the color key based on the row expression values spread through the whole color scale. B. The 4 clusters with the most distinct pattern of gene regulation in time in RA treated cells (for all clusters, see Supplementary Figure 3). Each line represents one gene. The red line represents the average pattern of expression of all genes in the cluster. Clusters sizes are indicated next to the cluster numbers.

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cations of these expression changes of TFs involved in apoptosis and prolifera-tion are not straightforward. The specific functions and differential expression patterns of all TFs mentioned above can be found in Supplementary Table 4.

Taken together, the TF expression profiles indicate that RA treated SH-SY5Y cells are in a pro-differentiation transcriptional state and, more specifi-cally, a differentiation state towards a neuronal phenotype. Additionally, during differentiation specific changes in the expression of apoptotic and proliferative TFs are observed.

Retinoic acid treated SH-SY5Y cells show a DAergic neurotransmitter phenotype

Expression of early DAergic markers in SH-SY5Y cells

We were particularly interested in characterizing the putative DA cell phenotype of RA treated SH-SY5Y cells. To address this, we investigated the ex-pression profiles of genes typically required for DAergic neuronal development in vivo. We discriminated between markers that are expressed either during early or late stages of DA cell development based on a study of Smidt and Bur-bach (2007). These authors discuss the specific cascades of molecular codes that regulate the generation of mesodiencephalic DAergic neurons in the developing mouse brain. During the early stage of DAergic neuron development two types of signals are required, i.e. external inductive signals such as growth factors pres-ent in the environment (such as FGF, TGF and WNT), and intrinsic TFs expressed by the cells themselves. At 8 days in culture, microarray detection established that SH-SY5Y cells express 5 out of the 26 markers that have a role in the ear-ly stage of DAergic neuronal development (Figure 3). Two of these early stage markers were significantly downregulated after RA treatment (fold change on day 8 between RA and noRA: ASCL1 0.27 and NEUROG2 0.02), but overall RA treatment did not significantly affect the expression of these markers. In addi-tion to the microarray data, we have confirmed the expression of these markers with qPCR (for primer sequences see Supplementary Table 1). We conclude that SH-SY5Y cells do not express early stage DAergic markers, irrespective of cul-ture conditions.

SH-SY5Y cells synthesize DA

Mature DAergic cells should express DA, as well as the molecules that are important for DA synthesis, transport and turnover. SH-SY5Y cells express all of the DA synthesizing enzymes and DA degrading enzyme MAO-A as detected by micorarray analysis (Figure 4A) and by qPCR (Supplementary Table 1). Although the vesicular monoamine transporter (VMAT2) was initially not detected by microarray analysis, qPCR confirmed its presence in RA-treated cells. However DAT is not detected in these cells, also not with qPCR. Interestingly, the DA sero-tonin and tryptamine synthesizing enzyme dopa decarboxylase (DDC) and do-


107

pamine breakdown enzyme MAO-A were both significantly downregulated by RA (RA/noRA fold change 0.30 and 0.55 respectively) (Figure 4A). We did not observe significant changes between RA and noRA cells in the expression levels of other DA synthesis and turnover markers such as COMT, GCH1, PTS, TH and SLC18A2 (VMAT2). In RA differentiated SH-SY5Y cells the expression of VMAT2 and TH, two genes with a central role in DA synthesis and transport, was con-firmed at the protein level (Figure 4B). Thus, SH-SY5Y cells express all necessary molecules to produce DA, mostly independent of RA treatment.

We then asked whether SH-SY5Y cells produce DA and whether DA levels are altered in RA-treated SH-SY5Y cells. Immunohistochemical analysis of DA content showed that both noRA and RA treated cells produce DA and that DA immunoreactivity was increased following RA treatment (Figure 4C). As shown before, both noRA and RA treated cells show similar expression levels of DA syn-thesizing enzymes, with the exception of DDC and MAO-A. The decrease in MAO-A levels may explain the higher DA levels in RA treated cells. Our data clearly show that RA differentiated SH-SY5Y cell synthesize and store DA, and thus have a DAergic neuron-like phenotype.

Figure 3. Expression of early stage dopaminergic markers, based on Smidt and Burbach (2007), in noRA (black circle) and RA (gray square) differentiated SH-SY5Y cells on culture day 8 as measured by microarray analysis. The gray line represents the cut off between detected gene ex-pression (2log expression> 7) and undetected gene expression (2log expression≤ 7). Significantly regulated genes between the two conditions are marked with an ‘*’.

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Figure 4. Expression of dopamine synthesis and turnover markers (NCBI Gene data base and IPA) in noRA and RA differentiated SH-SY5Y cells at culture day 8. A. Microarray expression values of these molecular markers are represented for the noRA (black circle) and RA (gray square) treated cells at D8. Red line characterizes the cut-off at 2log intensity of 7 demarcating expression versus no expression of the mRNA in these cells (equivalent to 2x background levels). SLC18A2 (VMAT2) not detected on the microarray, but confirmed to be expressed by qPCR analy-sis (red marking). Significantly regulated genes between the two conditions are marked with an ‘*’. B. Immunocytochemistry of two dopamine synthesis and transport proteins TH and VMAT2 expressed by the RA treated cells at D8. C. Immunocytochemical detection of dopamine in noRA and RA SH-SY5Y cells. Images, taken with the same laser intensity, consist of a z-stack projection of the cell layer.


109

Expression of mature DAergic markers and neurotransmitter receptors in SH-SY5Y cells

Mature DAergic neurons in the brain express specific mature DAergic mark-ers as well as specific neurotransmitter receptors. We compiled a list of these mature DAergic markers and identified the specific neurotransmitter receptor subunits based on literature (Figure 5, Smidt and Burbach, 2007; Tepper and Lee, 2007; Schwarzer et al., 2001; Okada et al., 2004; Bustos et al., 2004; Paquet et al., 1997; Albers et al., 1999; Mena-Segovia et al., 2008). In general, there is no dif-ference in expression of the selected markers and receptors between noRA and RA differentiated SH-SY5Y cells, with one expection. Receptor tyrosine kinase (RET), expressed in mature DAergic neurons in vivo, was highly upregulated af-ter RA treatment (RA/noRA fold change 16.13). SH-SY5Y cells further express 3 out of 5 mature DAergic markers, including DA receptor 2 (DRD2), irrespective of the culture conditions.

With respect to other neurotransmitter receptors, both noRA and RA SH-SY5Y cells express 2 out of 10 GABA receptor subunits known to be expressed by SN DAergic neurons, i.e. GABA A β-3 subunit (GABRB3) and GABA B 1 subunit (GABBR1). Interestingly GABA B receptors are expressed by DAergic neurons in vitro, whereas their expression in vivo is controversial (Tepper and Lee, 2007; Schwarzer et al., 2001; Okada et al., 2004). Additionally, SH-SY5Y cells express a SN pars compacta specific chloride channel, CLCN2, which is necessary for GABA neurotransmission, but not the SN pars reticulata potassium-chloride co-trans-porter KCC2 (SLC12A5, data not shown, (Tepper and Lee, 2007).

SH-SY5Y cells further express 2 out of the 5 glutamate receptor subunits known to be expressed by SN DAergic neurons i.e. AMPA selective glutamate receptor 2 subunit (GRIA2), and NMDA selective glutamate receptor 1 subunit (GRIN1) (Bustos et al., 2004; Paquet et al., 1997; Albers et al., 1999).

Finally, both noRA and RA differentiated SH-SY5Y cells express 5 out of the 8 acetylcholine (Ach) receptor subunits known to be present in SN DAergic neu-rons. These include 3 of 4 subunits of nicotinic AChRα and 2 subunits of nico-tinic AChRβ (Mena-Segovia et al., 2008). Muscarinic AChR5 showed either very low or no expression in SH-SY5Y cells.

In conclusion, SH-SY5Y cells express many of the mature DAergic markers and neurotransmitter receptors characteristic for SN DAergic neurons. The ex-pression pattern of these genes is independent of RA treatment.

RA alters the expression of DA receptor signaling components

Complementary to the analysis of classical DAergic markers, IPA revealed that RA treatment had a significant effect on genes playing a role in the DA re-ceptor signaling pathway (p=2.11E-02). The dopamine receptor inhibitor and desensitization protein NCS1 (also known as FREQ, fold change RA/noRA 0.62) was downregulated after RA treatment, providing a potential mechanism for en-

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hanced DA signaling via the DRD2 receptor, which is also expressed by SH-SY5Y cells (Figure 5). Indeed, RA decreases the expression levels of two adenylate-cyclases that normally convert ATP to cAMP and are inhibited by DRD2 recep-tor activation (ADCY1 RA/noRA 0.61, ADCY7 RA/noRA 0.68). cAMP dependent protein kinase regulatory unit 1 is also downregulated in the RA treated cells (PRKAR1B RA/noRA0.69).

In contrast, several protein phosphatase 2 subunits (a downstream tar-get of DRD/AC/cAMP/PKA signaling pathway), were upregulated in RA treated cells: PPP2R5A (RA/noRA 1.59), PPP2R2B (RA/noRA 2.0) and PPP2R5B (RA/noRA 1.92, Supplementary Table 2). Interestingly, the regulatory B’beta subunits (PPP2R2B and PPP2R5B) are known to be present in the DAergic neurons and dephosphorylate TH (Saraf et al., 2007).

The expression of several protein phosphatase 1 subunits, also down-stream targets of the DRD/AC/cAMP/PKA signaling pathway) were changed after RA treatment (PPP1R3C RA/noRA 2.53 and PPP1R14A RA/noRA 0.35) as well.

Effects of RA treatment on neurotransmitter phenotypes other than DA in SH-SY5Y cells

We then investigated the expression of non-DA neurotransmitter markers in RA differentiated SH-SY5Y cells. Based on reviews by Verney (2003) and Ern-sberger (2000), combined with NCBI Gene database annotations, we compiled a list of key non-DA neurotransmitter markers that are required for successful neurotransmitter production and transport, including synthesizing enzymes, degrading enzymes and neurotransmitter transporters (Figure 6). RA treatment results in downregulation of DDC and DBH (30% and 28% reduction compared to noRA cells), involved in serotonin and noradrenaline synthesis respectively. Other markers for histaminergic, cholinergic and glutaminergic neurotransmit-ter phenotypes are not altered in their expression after RA treatment. Serotonin production is probably suppressed by decreased expression of DDC, which, apart from dopamine production, is also involved in serotonin biosynthesis. Noradren-aline production may also be suppressed by decreased expression of DBH syn-thesizing enzyme also validated to be true on the protein level, where RA treated cells show a trend toward a significant 70% reduction of DBH protein levels (Fig-ure 6C, p=0.07). Most of the histamine, acetylcholine, and glutamate synthesis genes were undetectable in SH-SY5Y cells as measured by microarray, suggest-ing that these neurotransmitter phenotypes are not prominent in SH-SY5Y cells.

The effects of MPP(+) toxicity on SH-SY5Y cells

MPP(+) uptake by neurons requires expression of either the DAT or the NAT (Pifl et al., 1996). We therefore measured DAT and NAT activity inSH-SY5Y cells by selectively blocking these transporters using vanoxerine (BBR-12909, a DAT


111

inhibitor) or desipramine (DMI, a NAT inhibitor), and measuring DA uptake. Both compounds decreased DA uptake in a dose-dependent manner (Figure 7A), indi-cating that both transporters are expressed and could therefore mediate MPP(+) uptake. NAT activity was significantly higher than DAT activity, which is in line with the observed mRNA levels (Figure 4A and 6B).

We then investigated whether MPP(+) could actually induce mitochondrial stress in RA differentiated SH-SY5Y cells. We first tested what concentration of MPP(+) was required to induce mitochondrial stress using a MitoTracker probe (Figure 7B). Doses from 0.01mM of MPP(+) to 0.05mM MPP(+) resulted in a small but significant increase in mitochondrial activity in RA treated SH-SY5Y cells, whereas doses of 0.1mM and above (except for 0.2mM) decreased mitochondrial activity in a dose-dependent manner when compared to non treated cells.

Figure 5. Expression of mature SN pars compacta DAergic neuron markers and neurotransmit-ter receptors in noRA (black circle) and RA (gray square) differentiated SH-SY5Y cells on culture day 8 as measured by microarray analysis. Graph shows expression of DAergic markers known to be expressed by mature SN DAergic neurons (Smidt and Burbach, 2007), and neurotransmit-ter receptors known to be expressed by SN DAergic enurons such as GABA receptor subunits and chloride chanels (Tepper and Lee, 2007; Schwarzer et al., 2001; Okada et al., 2004), glutamate receptor subunits (Bustos et al., 2004; Paquet et al., 1997; Albers et al., 1999) and nicotinic and muscaric acetylcholine receptor subunits (Mena-Segovia et al., 2008). Gray line characterizes the cut-off at 2log intensity of 7 determining the expression and no expression of the mRNA in these cells (equivalent to 2x background levels). Significantly regulated genes between the two condi-tions are marked with an ‘*’.

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Discussion

Combining genome-wide transcriptional profiling, gene ontology and IPA, analysis of transcription factor expression and the expression of key markers as-sociated with neurotransmitter phenotypes, we show that RA treatment of SH-SY5Y cells induces a differentiation program that promotes general neuron-like state and predominant DAergic characteristics. MPP(+) treatment of RA differ-entiated SH-SY5Y cells alters mitochondrial activity in a dose-dependent man-ner: low MPP(+) concentrations increase mitochondrial activity, whereas high concentrations decrease mitochondrial activity. This study thus extensively describes the molecular changes induced by RA treatment in SH-SY5Y cells and

Figure 6. Expression of genes involved in five different neurotransmitter phenotypes in undif-ferentiated (noRA) and RA differentiated (RA) SH-SY5Y cells: serotonin (A), noradreneline (B), histamine (D), acetylcholine (E) and glutamate (F). Genes below the red line are not expressed (microarray expression levels below 2x background). Significantly regulated genes between the two culture conditions are marked with an ‘*’. C. DBH protein expression was detected in three independent undifferentiated (noRA) and differentiated (RA) SH-SY5Y cell cultures by immunob-lotting. Paired student T-test showed a trend of decrease of DBH protein when normalized to the β-actin protein levels (p=0.07).


113

demonstrates that MPP(+) can be used to model PD-associated mitochondrial dysfunction in vitro.

RA treatment of SH-SY5Y cells initiates transcriptional changes that promote a general neuron-like phenotype

RA is a key signaling molecule that has been shown to promote neuronal differentiation and to maintain a neuron phenotype through activation of reti-noic acid receptors and their downstream targets (Maden, 2007). Here, we pro-vide an extensive characterization of the transcriptional events downstream of the RA signaling pathway in SH-SY5Y cells. GO analysis revealed that GO classes related to neuronal function were both enriched in the up- and downregulated gene clusters. However, a closer inspection of these data shows that the num-ber of genes annotated with a neuronal function in the upregulated clusters (n=115, or 35% of all upregulated genes) is much larger than the amount of neu-ronal genes in the downregulated clusters (71 genes, or 4% of all downregulated genes) (see Supplementary Table 3). Examples of upregulated genes important for neuronal differentiation include NCAM2 (12-fold upregulated on day 8), a cell adhesion molecule involved in neuronal compartmentalization (Winther et al., 2012), the BDNF receptor NTRK2 (27-fold higher on day 8), and NTNG2 (10-fold upregulated at day 8), a regulator of lamina-specific subdendritic compartmen-

Figure 7. DAT and NAT activity and the effects of MPP(+) on mitochondrial activity in RA dif-ferentiated SH-SY5Y cells. A. Transport of radioactive DA in the presence of GBR12909 (selective DAT inhibitor) or DMI (selective NAT inhibitor) suggests that both of these transporter proteins are expressed and active in RA treated SH-SY5Y cells. B. Dose response curve of mitochondrial activ-ity in SH-SY5Y cells treated with MPP(+). Mitochondrial activity was calculated by averaging the normalized MitoTracker mean cytoplasmic total intensity, mean cytoplasmic average intensity and mean cytoplasmic spot total intensity. Mitochondrial intensity is significantly increased in RA treated SH-SY5Y cells treated with 0.01mM MPP(+) up to 0.05mM, and significantly decreased in cells treated with 0.1mM, 0.05mM and 1mM MPP(+) (* p value < 0.05, ** p value < 0.01, *** p value < 0.001).

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talization (Nishimura-Akiyoshi et al., 2007). Furthermore, several downregu-lated genes involved in neuronal function actually inhibit neuronal differentia-tion. Notable examples include MYCN, a positive regulator of S-phase reentry of neurons (Wartiovaara et al., 2002) and BMP7, a secreted signaling molecule that decreases neurogenesis of olfactory receptor neurons (Shou et al., 1999). We also observed a downregulationof ASCL1, a gene that directly controls successive steps of neurogenesis and promotes proliferation of neuronal progenitors (Cas-tro et al., 2011), and has been reported to be downregulated in SH-SY5Y cells after RA treatment (Lopez-Carballo et al., 2002).

The shift towards neuronal differentiation, as indicated by GO analysis, is further supported by our TF analysis, which shows that out of the 13 regulated TFs with a function in neuronal differentiation, 6 positive regulators of neuronal differentiation are upregulated, whereas 4 out of 5 negative regulators of neuro-nal differentiation are downregulated. Thus, RA alters the expression of 10 out of 13 neuronal differentiation TFs in such a way that neuronal differentiation is promoted.

Finally, our gene expression data corroborate the RA-induced upregulation of multiple genes already known to play a crucial role in neuronal differentiation of SH-SY5Y cells. These include NRF2, a transcription factor regulating the en-dogenous antioxidant response and neuronal differentiation (Zhao et al., 2009) integrin α1 and ß1, cell membrane receptors involved in cell adhesion and recog-nition (Rossino et al., 1991), and the Rho GTPase RAC1, a neurite outgrowth ini-tiator (Pan et al., 2005). Taken together, these data provide strong evidence for a pro-neuronal differentiation process in SH-SY5Y cells after treatment with RA.

RA differentiated SH-SY5Y cells express multiple markers characteris-tic for SN DAergic neurons in vivo, and produce high levels of DA

The precise neuron-like phenotype of RA differentiated SH-SY5Y cells has been controversial. Although some studies claim that RA increases the expres-sion of TH (Lopes et al., 2010), we and others report that TH is already present in non-differentiated cells and that RA-induced differentiation does not induce changes in TH protein levels (Cheung et al., 2009). To gain more insight into the exact dopaminergic characteristics of RA-differentiated SH-SY5Y cells, we inves-tigated the expression of other markers that are associated with early develop-ment of DA neurons, DA synthesis and mature SN DAergic neurons. This analy-sis revealed that only 19% of the early stage DAergic markers are expressed by RA treated SH-SY5Y cells. On the other hand, all genes required for DA synthesis are expressed by SH-SY5Y cells, including TH and VMAT2. Finally, SH-SY5Y cells express many additional markers that are normally expressed by mature mid-brain DAergic neurons including transcription factor PITX3, receptor tyrosine kinase RET and several neurotransmitter receptors (DRD2, and several subunits of GABA, NMDA, AMPA and ACh receptors). RA treatment does not change the expression of these mature SN DAergic markers, with the notable exception of


115

RET, which is strongly induced. In contrast, RA treatment reduces expression of 2 out of 9 early stage DAergic markers. These data suggest that RA may shift the DAergic phenotype of SH-SY5Y cells towards a more mature state. Additionally, we observe an increase in DA immunoreactivity, suggesting that the net change of RA treatment is towards enhanced DA levels. This increase may in part be ex-plained by the downregulation of the DA-degrading enzyme MAO-A, and the DA-converting enzyme DBH, or may reflect the overall mature DAergic neuron-like state of RA differentiated SH-SY5Y cells.

Furthermore, we observed a significant regulation of the DAergic receptor signaling pathway in the RA treated cells as indicated by IPA. The DA receptor signaling pathway involves DA binding to D1-type and D2-type DA receptors, and the activation of their respective downstream targets. Activation of the D1-type receptors promotes the activity of adenylate cyclases, and thus the conversion of ATP to cAMP. DA signaling via the D2-type receptors on the other hand inhib-its the activity of adenylate cyclases. Our data support that signaling via the D2-type DA receptors is enhanced, as we observed a significant downregulation of adenylate cyclases. Furthermore, NCS1, an inhibitor of D2-type receptors, is also downregulated. These data suggest that the downstream targets of cAMP in this particular pathway (PKA and PP2A) should be decreased. In apparent contrast, we observed an increase in the expression of the B beta subunits of protein phos-phatase 2A (PPP2R2B and PPP2R5B). It is possible that PP2A subunit expression is enhanced via a DA receptor-independent mechanism. As the B’beta subunits dephosphorylate TH and thereby reduce its activity, we hypothesize that their upregulation may be part of a negative feedback loop to the DA synthesis path-way.

Together, our data show that RA treated cells, like true DA neurons in vivo, actively synthesize dopamine and are sensitive to DRD2-mediated dopamine re-ceptor signaling and other neurotransmitter signaling pathways, including glu-tamate, acetylcholine and GABA.

RA suppresses serotonergic, noradrenergic and cholinergic charac-teristics of SH-SY5Y cells

In addition to investigating the DAergic phenotype of SH-SY5Y cells, the gene expression data also allowed us to assess the serotonergic, noradrenergic, cholinergic, glutaminergic, and histaminergic characteristics of RA-treated SH-SY5Y cells. The RA-induced downregulation of DBH and DDC, two key enzymes involved in noradrenaline and serotonin synthesis respectively, and the down-regulation of noradrenaline-specifying transcription factor ASCL1 (fold change RA/noRA 0.27) and transcription regulator BMP7 (fold change RA/noRA 0.35) (Ernsberger, 2000) all indicate that these phenotypes are at least partially sup-pressed in RA differentiated SH-SY5Y cells. Additionally, the observation that many of the monoamine producing enzymes and transporters are not expressed by the SH-SY5Y cells, irrespective of the treatment condition, suggests that these

CH A PTER 3

116

specific neurotransmitter phenotypes are not prominent in SH-SY5Y cells. How-ever it should be noted that we cannot exclude that markers whose expression levels are below the microarray detection threshold are actually expressed at low levels.

MPP(+) treatment induces mitochondrial stress in RA differentiated SH-SY5Y cells

A good cell model for PD related research should not only closely mimic the phenotype of SN DAergic neurons in vivo, but should also be sensitive to altera-tions in cellular processes that are commonly associated with PD. Mitochondrial dysfunction and increase of oxidative stress are well known characteristics of PD (Henchcliffe and Beal, 2008) and MPP(+) has been widely used to induce PD-like mitochondrial impairments in vitro and in vivo (reviewed in Nicotra and Parvez, 2002). We show here that RA differentiated SH-SY5Y cells 1) actively take up MPP(+), most likely via DAT and NAT, which mimics MPP(+) uptake by DAergic neurons in vivo and 2) are susceptible to mitochondrial dysfunction.

Conclusion

RA-treated SH-SY5Y cells provide a suitable cellular model for high-throughput functional screening of genes involved in PD

Despite their neuron-like phenotype and expression of multiple DAergic markers, SH-SY5Y cells are still neuroblastoma cells that only resemble mature midbrain SN DAergic neurons to some extent. However, SH-SY5Y cells can be cul-tured in a highly reproducible manner and allow for easy and successful genetic manipulation, including transfection-based gene knockdown or lenti-viral in-duced overexpression. Moreover, SH-SY5Y cells are readily available and can be easily expanded, and are thus suitable for use in high-throughput and high-con-tent functional screening approaches to test large sets of target genes obtained by gene expression studies. We found that 73% of the 79 selected PD target genes (Chapter 2, Table 2) are expressed by RA differentiated SH-SY5Y cells (Supple-mentary Table 5). Finally, the sensitivity of RA-treated SH-SY5Y to MPP(+) may be very useful in functional screening experiments investigating mitochondrial dysfunction in PD and the potential modifying effect of PD target genes towards the MPP(+) induced mitochodrial stress.


117

Acknowledgments:

We thank Mr. K. Jongenelen from the Neuroscience Campus Amsterdam for technical assistance and the Center of Medical Systems Biology and the Neuro-science Campus Amsterdam for support of the Cellomics facility. This research has been funded by the Top Institute Pharma, Leiden, The Netherlands, project T5-207.

Supplementary Figure 1. The hybridization set up for RA vs. noRA microarray study. Different culture days are indicated by numbers in the circle with each biological replicate (N=3) being hybridized against a different culture time point.

Supplementary Figures

CH A PTER 3

118

Supplementary Figure 2. Retinoic acid receptor signaling pathway regulation in RA treated SH-SY5Y cells. The figure represents the regulation of gene expression after RA treatment play-ing a role in retinoic acid signaling pathway illustrated by IPA. Red symbols represent genes significantly upregulated in RA treated SH-SY5Y cells and green represent genes significantly downregulated. Gray symbols with p values represent genes not significantly regulated after RA treatment.


119

Cluster 1 , size: 4507

Time

2log

Inte

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Time

2log

Inte

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−10

12

3



Time

2log

Inte

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−10

12

3



Time

2log

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12

3



Time

2log

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12

3



Time

2log

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−10

12

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2log

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12

3



Time

2log

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12

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Time

2log

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nsity

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Time

2log

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nsity

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12

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2log

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nsity

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12

3



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2log

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12

3



Time

2log

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nsity

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12

3



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nsity

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12

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12

3



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2log

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12

3



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3



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12

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2log

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Supplementary Figure 3. Expression profiles of all 20 gene clusters in time of culture in RA differentiated cells. The expression level of each gene is indicated by the 2 log intensity (y axis) in time of culture (x axis). Each graph indicates the cluster number and the amount of genes present in this cluster. Red line indicates the average expression profile of each cluster.

CH A PTER 3

120

Supplementary TablesSy

stem

atic

N

ame

Gen

e N

ame

Des

crip

tion

Frow

ard

prim

erR

ever

se p

rimer

Cor

rala

tion

noR

AC

orra

latio

n R

A

Reg

ulat

ed g

enes

dur

ing

RA

treat

men

t

NM

_003

812

AD

AM

23H

omo

sapi

ens

AD

AM

met

allo

pept

idas

e do

mai

n 23

G

CA

CTG

TTG

GAT

TCTG

GG

TAC

ATC

CTT

GTC

AC

CC

CA

AC

TT0.

733

0.58

1

NM

_004

316

AS

CL1

Hom

o sa

pien

s ac

haet

e-sc

ute

com

plex

hom

olog

1

(Dro

soph

ila)

AC

TGG

GA

CC

TGA

GTC

AAT

GC

GC

TGTG

CG

TGTT

AG

AG

GTG

A0.

967

0.98

3

NM

_000

787

DB

HH

omo

sapi

ens

dopa

min

e be

ta-h

ydro

xyla

se (d

opam

ine

beta

-mon

ooxy

gena

se)

AC

CTA

AA

GG

GA

AG

CC

CTG

AC

GC

AG

AG

AA

GC

AA

GC

TGG

TG0.

414

0.93

5

NM

_000

790

DD

CH

omo

sapi

ens

dopa

dec

arbo

xyla

se (a

rom

atic

L-a

min

o ac

id d

ecar

boxy

lase

)G

CA

ATC

AAT

GTT

CA

CG

CA

AC

AG

GC

ATTT

AG

CC

AC

ATG

AC

AA

0.95

70.

968

NM

_003

836

DLK

1H

omo

sapi

ens

delta

-like

1 h

omol

og (D

roso

phila

) (D

LK1)

, tra

nscr

ipt v

aria

nt 1

CTC

AA

CA

AG

TGC

GA

GA

CC

TGC

TTC

TCG

GG

GA

AG

ATG

ATG

T0.

829

0.95

5

NM

_015

569

DN

M3

Hom

o sa

pien

s dy

nam

in 3

TCTT

CTT

GG

CA

CTT

TCA

GG

ATC

AA

GA

AC

GAT

AC

AG

-G

CTT

TGA

0.69

60.

964

NM

_024

019

NE

U-

RO

G2

Hom

o sa

pien

s ne

urog

enin

2G

CA

AG

CG

TGG

AA

ATTT

AG

GC

GC

AAT

CC

TCC

CTC

CTG

ATTT

0.94

40.

923

NM

_006

164

NFE

2L2

Hom

o sa

pien

s nu

clea

r fac

tor (

eryt

hroi

d-de

rived

2)-

like

2G

CAT

GAT

GC

CC

AAT

GTG

AG

AA

CC

AA

GC

GG

CTT

GA

ATG

TTTG

0.65

60.

545

NM

_004

289

NFE

2L3

Hom

o sa

pien

s nu

clea

r fac

tor (

eryt

hroi

d-de

rived

2)-

like

3TC

CC

AG

CAT

GA

GG

AA

AAT

GA

TTC

TGC

CTC

CC

AG

TCA

GG

TTT

0.91

60.

914

NM

_006

113

VAV

3H

omo

sapi

ens

vav

3 on

coge

ne (V

AV3)

, tra

nscr

ipt v

aria

nt 1

CG

CTC

GG

TATG

AC

TTC

TGTG

CC

AC

CC

TGC

CAT

TTA

CTT

CT

0.90

80.

955

DA

ergi

c m

arke

rs

NM

_000

689

ALD

H1A

1H

omo

sapi

ens

alde

hyde

deh

ydro

gena

se 1

fam

ily, m

embe

r A

1G

GA

GA

GTA

CG

GTT

TCC

AT-

GA

ATTT

GA

AG

AG

CTT

CTC

TC-

CA

CTC

TT

NM

_000

754

CO

MT

Hom

o sa

pien

s ca

tech

ol-O

-met

hyltr

ansf

eras

e (C

OM

T),

trans

crip

t var

iant

MB

-CO

MT,

TC

CTA

AAT

GC

AA

AG

CA

CA

CC

CA

ATC

CA

GTG

TTG

CA

GTT

CA

G

NM

_000

795

DR

D2

Hom

o sa

pien

s do

pam

ine

rece

ptor

D2

(DR

D2)

, tra

nscr

ipt

varia

nt 1

GG

AA

ATTC

AG

CA

G-

GAT

TCA

CTG

ATG

CTG

ATG

GC

AC

AC

AA

GTT

C

NM

_001

426

EN

1H

omo

sapi

ens

engr

aile

d ho

mol

og 1

TGTC

GG

TCTG

TCTG

TTC

TGC

TCTG

TGG

GG

TCG

TATT

TCTC

A

NM

_004

496

FOX

A1

Hom

o sa

pien

s fo

rkhe

ad b

ox A

1G

GAT

TTC

AA

AA

CG

TGG

TC-

CA

AG

AC

AA

GC

AC

AC

GAT

GG

CA

ATG

NM

_021

784

FOX

A2

Hom

o sa

pien

s fo

rkhe

ad b

ox A

2 (F

OX

A2)

, tra

nscr

ipt

varia

nt 1

AC

AC

GG

TGA

AAT

CC

AG

GTC

TCC

CTT

GC

AG

CC

AG

AAT

AC

A-

CAT

T

NM

_000

161

GC

H1

Hom

o sa

pien

s G

TP c

yclo

hydr

olas

e 1

(dop

a-re

spon

sive

dy

ston

ia) (

GC

H1)

, tra

nscr

ipt v

aria

nt 1

CTT

CA

AAT

TCAT

CC

CAT

TAC

CC

GC

CC

CAT

CAT

AA

CC

CA

AAT

A


121

Syst

emat

ic

Nam

eG

ene

Nam

eD

escr

iptio

nFr

owar

d pr

imer

Rev

erse

prim

erC

orra

latio

n no

RA

Cor

rala

tion

RA

NM

_005

269

GLI

1H

omo

sapi

ens

glio

ma-

asso

ciat

ed o

ncog

ene

hom

olog

1

(zin

c fin

ger p

rote

in)

TTA

GC

CC

AA

GC

CG

TGC

TAA

AC

CC

TATG

TGA

AG

CC

CTA

TTT-

GC

NM

_005

270

GLI

2H

omo

sapi

ens

GLI

-Kru

ppel

fam

ily m

embe

r GLI

2A

CA

GTG

CTT

TCC

AG

CC

TTTG

CG

AAT

GTC

AG

CC

GTG

AA

GA

NM

_000

168

GLI

3H

omo

sapi

ens

GLI

-Kru

ppel

fam

ily m

embe

r GLI

3 (G

reig

ce

phal

opol

ysyn

dact

yly

synd

rom

e)C

CTC

CC

AA

CTC

CTC

AC

AC

ATC

AA

CA

CC

AA

CTG

GTC

CC

TCT

NM

_000

838

GR

M1

Hom

o sa

pien

s gl

utam

ate

rece

ptor

, met

abot

ropi

c 1

CC

TGAT

TATG

GG

GTC

TCC

TGG

GC

CC

TCTT

GG

TATA

GG

GTA

NM

_002

316

LMX

1BH

omo

sapi

ens

LIM

hom

eobo

x tra

nscr

iptio

n fa

ctor

1, b

eta

TTC

CTG

ATG

CG

AG

TCA

AC

-G

AG

TTG

CA

GTA

CA

GTT

TCC

GAT

CC

C

NM

_002

448

MS

X1

Hom

o sa

pien

s m

sh h

omeo

box

1A

GA

GC

TAG

AG

GC

CAT

-G

TCTC

CT

TCTG

CG

CTT

TTC

TTG

CC

TG

NM

_002

509

NK

X2-

2H

omo

sapi

ens

NK

2 tra

nscr

iptio

n fa

ctor

rela

ted,

locu

s 2

(Dro

soph

ila)

GG

AAAA

GAA

AAC

CC

TGTA

GG

CC

CG

AAT

AG

CTG

AG

CTC

CA

A

NM

_006

168

NK

X6-

1H

omo

sapi

ens

NK

6 tra

nscr

iptio

n fa

ctor

rela

ted,

locu

s 1

(Dro

soph

ila)

CTC

GTT

TGG

CC

TATT

CG

TTG

GG

AA

CC

AG

AC

CTT

GA

CC

TGA

NM

_006

186

NR

4A2

Hom

o sa

pien

s nu

clea

r rec

epto

r sub

fam

ily 4

, gro

up A

, m

embe

r 2 (N

R4A

2), t

rans

crip

t var

iant

1A

CTT

GC

ATG

CA

GC

AG

CTT

TTA

ATTC

AA

AG

TGC

TCA

GT-

TATT

TCC

A

NM

_014

562

OTX

1H

omo

sapi

ens

orth

oden

ticle

hom

olog

1 (D

roso

phila

)G

CC

CA

GG

AAT

GA

AA

GA

G-

GA

GA

AC

AG

TTTT

GG

AG

AA

GA

C-

GA

GG

C

NM

_021

728

OTX

2H

omo

sapi

ens

orth

oden

ticle

hom

olog

2 (D

roso

phila

) (O

TX2)

, tra

nscr

ipt v

aria

nt 1

AG

AG

GTC

CTA

TCC

CAT

GA

CC

AA

GTA

GG

AA

GTT

GA

GC

-C

AG

CA

NM

_005

029

PIT

X3

Hom

o sa

pien

s pa

ired-

like

hom

eodo

mai

n tra

nscr

iptio

n fa

ctor

3TG

GA

CTA

GG

CC

CTA

CA

CA

-C

AG

AC

CG

CG

CA

CG

TTTA

TTTC

A

NM

_000

317

PTS

Hom

o sa

pien

s 6-

pyru

voyl

tetra

hydr

opte

rin s

ynth

ase

ATTG

CA

CA

AA

GC

CC

AG

TTTC

TAG

GC

AC

TCC

AG

AG

CA

-C

AAT

G

NM

_000

193

SH

HH

omo

sapi

ens

soni

c he

dgeh

og h

omol

og (D

roso

phila

) (S

HH

), m

RN

A [N

M_0

0019

3]G

CTG

AC

CC

CTT

TAG

CC

TAC

AA

TCG

GA

GTT

TCTG

GA

GA-

TCTT

CC

NM

_003

054

SLC

18A

2H

omo

sapi

ens

solu

te c

arrie

r fam

ily 1

8 (v

esic

ular

mon

o-am

ine)

, mem

ber 2

CG

GA

AG

CTC

ATC

CTG

TTC

ATC

AC

GA

CA

GTG

AG

CA

GC

AT-

GTT

G

NM

_001

044

SLC

6A3

Hom

o sa

pien

s so

lute

car

rier f

amily

6 (n

euro

trans

mitt

er

trans

porte

r, do

pam

ine)

, mem

ber 3

GC

CTG

CTT

GC

TGAT

ATTG

-C

AG

TTG

GC

CA

AC

ATC

CTT

CA

CTC

A

NM

_003

236

TGFA

Hom

o sa

pien

s tra

nsfo

rmin

g gr

owth

fact

or, a

lpha

TGC

CTG

TAA

CA

CA

CAT

G-

CA

GTG

AAT

GG

TCC

AA

CC

AG

GC

TTG

CH A PTER 3

122

Syst

emat

ic

Nam

eG

ene

Nam

eD

escr

iptio

nFr

owar

d pr

imer

Rev

erse

prim

erC

orra

latio

n no

RA

Cor

rala

tion

RA

NM

_000

660

TGFB

1H

omo

sapi

ens

trans

form

ing

grow

th fa

ctor

, bet

a 1

(Cam

urat

i-Eng

elm

ann

dise

ase)

AC

ATTG

AC

TTC

CG

CA

AG

GA

CG

TCC

AG

GC

TCC

AA

ATG

TAG

G

NM

_199

292

THH

omo

sapi

ens

tyro

sine

hyd

roxy

lase

(TH

), tra

nscr

ipt

varia

nt 2

GTG

AG

GTT

GTG

CTG

CC

TGT

CTT

TTAT

TGTG

AC

GG

T-G

ATTG

G

NM

_007

005

TLE

4H

omo

sapi

ens

trans

duci

n-lik

e en

hanc

er o

f spl

it 4

(E(s

p1)

hom

olog

, Dro

soph

ila)

TCC

TCC

TGG

TAG

CA

CTT

TGC

AG

CA

AG

TGG

GA

AG

TGA

GG

TT

Oth

er q

PC

R v

alid

ated

gen

es

NM

_002

133

HM

OX

1H

omo

sapi

ens

hem

e ox

ygen

ase

(dec

yclin

g) 1

GA

CA

CC

CTA

ATG

TGG

CA

GC

T-G

TTG

GC

CG

TGTC

AA

-C

AA

GG

ATA

C

NM

_000

903

NQ

O1

Hom

o sa

pien

s N

AD

(P)H

deh

ydro

gena

se, q

uino

ne 1

(N

QO

1), t

rans

crip

t var

iant

1C

GA

GC

TGG

AA

AA

CC

TCC

TTTA

GC

CG

TCA

GC

TATT

GTG

-G

ATA

CT

NM

_001

043

SLC

6A2

Hom

o sa

pien

s so

lute

car

rier f

amily

6 (n

euro

trans

mitt

er

trans

porte

r, no

radr

enal

in),

mem

ber 2

TCC

CC

TGG

AA

GTT

GTC

CTT

TTC

CTG

TTTG

CTC

CTC

TCC

TC

Supp

lem

enta

ry T

able

1. G

ene

valid

atio

n by

qPC

R. V

alid

atio

n of

mic

roar

ray

resu

lts w

ith q

PCR

expr

essio

n st

udy

of se

lect

ed g

enes

of i

nter

est.

For

the

signi

fican

tly re

gula

ted

gene

s cor

rela

tion

coeffi

cien

ts a

re in

dica

ted

betw

een

the

patt

ern

of a

rray

exp

ress

ion

and

qPCR

exp

ress

ion.

Add

ition

-al

ly, s

eque

nces

of q

PCR

dete

ctio

n pr

imer

s for

war

d an

d re

vers

e ar

e gi

ven.

Supp

lem

enta

ry T

able

2. T

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Cluster 2 DOWN (1455 genes)

IPA analysis

Code Name P-value # of molecules

Functions and Diseases

PRO Amino Acid Metabolism 1.39E-03 - 3.31E-02 13

CF Molecular Transport 1.39E-03 - 3.31E-02 23 # of genes % of genes

Small Molecule Biochemistry 1.39E-03 - 4.84E-02 45 101 6.942 PRO

PRO Cell Cycle 3.15E-03 - 3.27E-02 9 10 0.687 CD

Infection Mechanism 3.15E-03 - 3.27E-02 3 27 1.856 NFD

CF Lipid Metabolism 3.15E-03 - 4.84E-02 10 21 1.443 CDEV

CD Cell Death 6.15E-03 - 4.84E-02 10 80 5.498 DEV

NFD Neurological Disease 6.18E-03 - 4.84E-02 15 90 6.186 CF

PRO Carbohydrate Metabolism 1.00E-02 - 4.05E-02 8

DEV Developmental Disorder 1.00E-02 - 3.31E-02 11

DEV Digestive System Development and Function 1.00E-02 - 3.27E-02 3

Gastrointestinal Disease 1.00E-02 - 4.84E-02 9

DEV Hair and Skin Development and Function 1.00E-02 - 3.27E-02 5

Hepatic System Disease 1.00E-02 - 4.05E-02 4

PRO Nucleic Acid Metabolism 1.00E-02 - 4.84E-02 13

DEV Organ Morphology 1.00E-02 - 3.27E-02 9

PRO Cancer 1.19E-02 - 4.84E-02 24

Immunological Disease 1.19E-02 - 3.27E-02 6

Reproductive System Disease 1.43E-02 - 3.27E-02 4

CF Cellular Function and Maintenance 1.47E-02 - 3.27E-02 10

Genetic Disorder 1.47E-02 - 3.31E-02 16

Organismal Functions 1.47E-02 - 3.27E-02 2

Tumor Morphology 1.47E-02 - 4.12E-02 11

Ophthalmic Disease 1.69E-02 - 3.27E-02 6

Endocrine System Disorders 1.69E-02 - 4.05E-02 5

Psychological Disorders 1.69E-02 - 1.69E-02 3

PRO Cellular Assembly and Organization 2.02E-02 - 4.84E-02 16

CDEV Cellular Development 2.02E-02 - 4.84E-02 6

PRO DNA Replication, Recombination, and Repair 2.02E-02 - 4.84E-02 6

CF Protein Trafficking 2.02E-02 - 3.27E-02 3

Dermatological Diseases and Conditions 2.63E-02 - 3.31E-02 5

Skeletal and Muscular Disorders 2.64E-02 - 3.31E-02 10

CF Energy Production 2.94E-02 - 2.94E-02 4

CF Antigen Presentation 3.27E-02 - 3.27E-02 2

Antimicrobial Response 3.27E-02 - 3.27E-02 1

Auditory Disease 3.27E-02 - 3.27E-02 1

NFD Behavior 3.27E-02 - 3.31E-02 3

DEV Cardiovascular System Development and Function

3.27E-02 - 4.62E-02 9

PRO Cell Morphology 3.27E-02 - 4.84E-02 8

CH A PTER 3

124

CF Cell-To-Cell Signaling and Interaction 3.27E-02 - 3.27E-02 7

CF Cell-mediated Immune Response 3.27E-02 - 3.27E-02 3

CF Cellular Compromise 3.27E-02 - 3.27E-02 1

PRO Cellular Growth and Proliferation 3.27E-02 - 3.27E-02 4

CF Cellular Movement 3.27E-02 - 3.27E-02 1

CF Cellular Response to Therapeutics 3.27E-02 - 3.27E-02 1

DEV Connective Tissue Development and Function 3.27E-02 - 4.84E-02 5

Connective Tissue Disorders 3.27E-02 - 3.27E-02 1

Drug Metabolism 3.27E-02 - 3.27E-02 4

DEV Embryonic Development 3.27E-02 - 4.84E-02 11

DEV Endocrine System Development and Function 3.27E-02 - 3.27E-02 1

CF Gene Expression 3.27E-02 - 4.05E-02 3

Hematological Disease 3.27E-02 - 3.27E-02 1

DEV Hematological System Development and Func-tion

3.27E-02 - 3.27E-02 1

Hematopoiesis 3.27E-02 - 3.27E-02 1

DEV Hepatic System Development and Function 3.27E-02 - 3.27E-02 1

Humoral Immune Response 3.27E-02 - 3.27E-02 1

Immune Cell Trafficking 3.27E-02 - 3.27E-02 1

Inflammatory Disease 3.27E-02 - 3.27E-02 2

CF Inflammatory Response 3.27E-02 - 3.27E-02 2

Lymphoid Tissue Structure and Development 3.27E-02 - 4.62E-02 8

Metabolic Disease 3.27E-02 - 3.27E-02 3

NFD Nervous System Development and Function 3.27E-02 - 4.84E-02 9

DEV Organ Development 3.27E-02 - 3.27E-02 5

Organismal Injury and Abnormalities 3.27E-02 - 3.27E-02 3

CF Protein Degradation 3.27E-02 - 3.27E-02 1

CF Protein Synthesis 3.27E-02 - 3.27E-02 1

Renal and Urological Disease 3.27E-02 - 3.27E-02 1

DEV Renal and Urological System Development and Function

3.27E-02 - 3.27E-02 1

DEV Reproductive System Development and Function 3.27E-02 - 4.72E-02 6

Respiratory Disease 3.27E-02 - 3.27E-02 1

DEV Respiratory System Development and Function 3.27E-02 - 3.27E-02 3

DEV Skeletal and Muscular System Development and Function

3.27E-02 - 4.84E-02 9

CDEV Tissue Development 3.27E-02 - 4.84E-02 10

CDEV Tissue Morphology 3.27E-02 - 4.84E-02 5

CF Vitamin and Mineral Metabolism 3.27E-02 - 3.27E-02 1

CF RNA Trafficking 3.31E-02 - 3.31E-02 2

CF RNA Damage and Repair 3.81E-02 - 3.81E-02 3

CF Cell Signaling 4.62E-02 - 4.62E-02 7

CF RNA Post-Transcriptional Modification 4.65E-02 - 4.65E-02 5

Canoniacal Pathways

Methionine Metabolism 6.77E-5 7/76


125

CF Aminoacyl-tRNA Biosynthesis 1.31E-4 7/83

CF Purine Metabolism 1.51E-4 29/417

CF Pyrimidine Metabolism 1.53E-4 17/228

Valine, Leucine and Isoleucine Biosynthesis 1.69E-2 3/44

Synthesis and Degradation of Ketone Bodies 1.98E-2 3/19

Pantothenate and CoA Biosynthesis 2.43E-2 4/63

Selenoamino Acid Metabolism 2.94E-2 4/69

GO analysis

CF GO:0042254: ribosome biogenesis and assembly 6.58E-5 26

CF GO:0022613: ribonucleoprotein complex biogen-esis and assembly

7.37E-3 30

CF GO:0009058: biosynthetic process 7.37E-3 106

CF GO:0044249: cellular biosynthetic process 2.42E-2 85

CF GO:0005856: cytoskeleton 5.04E-2 25

NFD GO:0007600: sensory perception 6.81E-2 6

CF GO:0016072: rRNA metabolic process 7.42E-2 16

CF GO:0015630: mycrotubule cytoskeleton 7.42E-2 4

CF GO:0006396: RNA processing 7.64E-2 45

CF GO:0005730: nucleolus 8.33E-2 25

Cluster 3 UP (98 genes)

IPA analysis



NFD Neurological Disease 2.53E-04-4.71E-02 19

PRO Cancer 1.99E-03-4.85E-02 16 # of genes % of genes

PRO Cell Cycle 1.99E-03-4.52E-02 7 34 34.694 PRO

CD Cell Death 1.99E-03-4.47E-02 18 21 21.429 CD

CF Cell Morphology 1.99E-03-4.66E-02 6 41 41.837 NFD

CF Cell-To-Cell Signaling and Interaction 1.99E-03-4.85E-02 11 8 8.163 CDEV

CF Cell-mediated Immune Response 1.99E-03-4.47E-02 5 63 64.286 DEV

CF Cellular Assembly and Organization 1.99E-03-4.09E-02 10 92 93.878 CF

CDEV Cellular Development 1.99E-03-4.61E-02 8

PRO Cellular Growth and Proliferation 1.99E-03-4.66E-02 9

CF Cellular Movement 1.99E-03-4.85E-02 9

DEV Connective Tissue Development and Function 1.99E-03-4.85E-02 4

Dermatological Diseases and Conditions 1.99E-03-4.28E-02 3

Developmental Disorder 1.99E-03-1.99E-03 1

DEV Embryonic Development 1.99E-03-4.66E-02 3

CF Gene Expression 1.99E-03-1.58E-02 2

Genetic Disorder 1.99E-03-4.66E-02 18

Hematological Disease 1.99E-03-3.71E-02 2


1.99E-03-4.85E-02 4

CF Humoral Immune Response 1.99E-03-4.38E-02 3

CF Immune Cell Trafficking 1.99E-03-4.85E-02 4

CH A PTER 3

126

Immunological Disease 1.99E-03-4.28E-02 3

NFD Nervous System Development and Function 1.99E-03-4.85E-02 11

Ophthalmic Disease 1.99E-03-3.9E-02 3

DEV Organ Development 1.99E-03-3.32E-02 4

DEV Tissue Development 1.99E-03-4.85E-02 11

DEV Tissue Morphology 1.99E-03-4.09E-02 14

Reproductive System Disease 2.35E-03-4.66E-02 8

CF Lipid Metabolism 3.97E-03-2.16E-02 2

CF Molecular Transport 3.97E-03-4.28E-02 9

DEV Reproductive System Development and Function 3.97E-03-3.97E-03 1

CF Small Molecule Biochemistry 3.97E-03-3.91E-02 8

CF Vitamin and Mineral Metabolism 3.97E-03-4.28E-02 3

Connective Tissue Disorders 5.61E-03-2.75E-02 4

Inflammatory Disease 5.61E-03-4.28E-02 5

Skeletal and Muscular Disorders 5.61E-03-3.52E-02 4

CF Amino Acid Metabolism 5.95E-03-9.89E-03 2

NFD Behavior 5.95E-03-5.95E-03 1

CD Cellular Compromise 5.95E-03-2.94E-02 3

NFD Psychological Disorders 7E-03-2.16E-02 7

Auditory Disease 7.92E-03-7.92E-03 1

CF Drug Metabolism 7.92E-03-7.92E-03 1

DEV Organ Morphology 7.92E-03-4.09E-02 4

DEV Hair and Skin Development and Function 9.89E-03-9.89E-03 1

Organismal Injury and Abnormalities 9.89E-03-4.85E-02 5


9.89E-03-2.36E-02 3

NFD Visual System Development and Function 9.89E-03-2.36E-02 3

CF Hematopoiesis 1.45E-02-4.47E-02 4

DEV Lymphoid Tissue Structure and Development 1.45E-02-3.9E-02 3

CF Protein Degradation 1.77E-02-1.77E-02 1


1.97E-02-4.85E-02 3

Infectious Disease 1.97E-02-2.67E-02 3

Renal and Urological Disease 1.97E-02-2.16E-02 2

Respiratory Disease 1.97E-02-4.28E-02 2

Tumor Morphology 1.97E-02-3.52E-02 2

Cardiovascular Disease 2.16E-02-4.66E-02 2

CF Hypersensitivity Response 2.16E-02-4.66E-02 1


2.16E-02-4.85E-02 5

CF Antigen Presentation 2.55E-02-4.85E-02 3

CF Cellular Function and Maintenance 2.55E-02-4.28E-02 3

CF Inflammatory Response 2.55E-02-4.85E-02 4

CF Protein Trafficking 2.55E-02-2.55E-02 1

CF Cell Signaling 2.73E-02-4.28E-02 6


127

CF Nucleic Acid Metabolism 3.13E-02-3.91E-02 3

DEV Respiratory System Development and Function 3.32E-02-3.32E-02 1

PRO DNA Replication, Recombination, and Repair 3.91E-02-3.91E-02 2

DEV Organismal Development 4.42E-02-4.42E-02 2

Endocrine System Disorders 4.66E-02-4.66E-02 1

Metabolic Disease 4.66E-02-4.66E-02 1

Hepatic System Disease 4.85E-02-4.85E-02 1

Cluster 4 UP (256 genes)

IPA analysis



DEV Tissue Development 1.25E-05 - 4.42E-02 28

Cell-mediated Immune Response 2.24E-05 - 3.90E-02 13 # of genes % of genes

CF Cellular Function and Maintenance 2.24E-05 - 4.65E-02 9 74 28.906 PRO

CF Gene Expression 2.24E-05 - 3.74E-02 10 32 12.5 CD

Hematological System Development and Func-tion

2.24E-05 - 4.61E-02 23 74 28.906 NFD

Hematopoiesis 2.24E-05 - 3.28E-02 18 36 14.063 CDEV

CF Cellular Movement 6.71E-05 - 4.5E-02 28 235 91.797 DEV

DEV Organismal Development 1.60E-05 - 4.62E-02 14 184 71.875 CF


1.60E-04 - 3.79E-02 19

PRO Cancer 2.40E-04 - 4.65E-02 30

Reproductive System Disease 2.40E-04 - 4.27E-02 22

Developmental Disorder 3.32E-04 - 4.19E-02 7






5.34E-04 - 4.65E-02 14

CF Cell Morphology 5.88E-04 - 4.65E-02 19


DEV Lymphoid Tissue Structure and Development 7.90E-04 - 4.50E-02 14



DEV Tissue Morphology 7.90E-04 - 2.83E-02 19

CF Molecular Transport 1.69E-03 - 4.65E-02 13


CF Lipid Metabolism 1.96E-03 - 4.65E-02 10

Small Molecule Biochemistry 1.96E-03 - 4.65E-02 22



CF Drug Metabolism 3.64E-03 - 3.28E-02 4


CH A PTER 3

128





CF Nucleic Acid Metabolism 4.71E-03 - 4.56E-02 11

CF Carbohydrate Metabolism 4.75E-03 - 4.65E-02 10

PRO Cell Cycle 4.75E-03 - 4.65E-02 7

CF Cellular Assembly and Organization 4.75E-03 - 4.27E-02 10

PRO Cellular Growth and Proliferation 4.75E-03 - 4.65E-02 34




CF Organismal Functions 4.75E-03 - 1.48E-02 4



NFD Neurological Disease 7.53E-03 - 4.65E-02 34

CF Amino Acid Metabolism 9.47E-03 - 9.47E-03 1

Auditory and Vestibular System Development and Function

9.47E-03 - 9.47E-03 1

NFD Behavior 9.47E-03 - 9.47E-03 1

Cardiovascular Disease 9.47E-03 - 3.28E-02 8

CD Cell Death 9.47E-03 - 4.65E-02 32

Cellular Compromise 9.47E-03 - 2.29E-02 5

Gastrointestinal Disease 9.47E-03 - 4.65E-02 17


Hepatic System Disease 9.47E-03 - 1.89E-02 3




9.47E-03 - 2.64E-02 7

Auditory Disease 1.42E-02 - 1.42E-02 1


Infectious Disease 1.42E-02 - 1.42E-02 1



NFD Psychological Disorders 1.46E-02 - 3.77E-02 12


CF Post-Translational Modification 1.89E-02 - 1.89E-02 1


DEV Visual System Development and Function 2.35E-02 - 3.10E-02 3







129



Canoniacal Pathways

CF Chondroitin Sulfate Biosynthesis 2.82E-2 2/61

Aryl Hydrocarbon Receptor Signaling 3.50E-2 6/155

NFD Notch Signaling 4.85E-2 2/41

GO analysis

DEV GO:0007275: multicellular organismal develop-ment

2.54E-5 40

DEV GO:0048731: system development 1.85E-3 30

DEV GO:0048856: anatomical structure development 5.20E-3 54

CF GO:0005509: calcium ion binding 5.25E-3 17

NFD GO:0007399: nervous system development 8.40E-3 16

GO:0032501: multicellular organismal process 8.54E-3 44

DEV GO:0032502: developmental process 8.54E-3 44

CF GO:0044422: organelle part 1.94E-2 8

CF GO:0044446: intracellular organelle part 1.94E-2 8

DEV GO:0048513: organ development 5.86E-2 21

Cluster 13 DOWN (454 genes)

IPA analysis



CF Amino Acid Metabolism 7.29E-05 - 3.38E-02 9

Small Molecule Biochemistry 7.29E-05 - 3.38E-02 39 # of genes % of genes

DEV Tissue Morphology 1.55E-04 - 3.26E-02 36 162 35.683 PRO

PRO Cancer 1.87E-04 - 3.21E-02 82 20 4.405 CD

Gastrointestinal Disease 1.87E-04 -2.37E-02 34 44 9.692 NFD

CF Cellular Movement 4.60E-04 - 3.38E-02 25 52 11.454 CDEV

Reproductive System Disease 4.60E-04 - 3.07E-02 29 250 55.066 DEV

PRO Cellular Growth and Proliferation 4.89E-04 - 3.05E-02 64 220 48.458 CF


DEV Organismal Development 6.46E-04 - 2.71E-02 8


Cardiovascular Disease 1.07E-03 - 3.23E-02 10

DEV Visual System Development and Function 1.07E-03 - 2.88E-02 10


1.23E-03 - 2.88E-02 25

CF Gene Expression 1.24E-03 - 3.38E-02 10



CF Lipid Metabolism 1.87E-03 - 2.54E-02 20

CF Molecular Transport 1.87E-03 - 3.38E-02 23


Dermatological Diseases and Conditions 2.71E-03 - 2.54E-02 10

CH A PTER 3

130


3.17E-03 - 3.04E-02 24

DEV Tissue Development 3.49E-03 - 3.38E-02 32

CF Cell Morphology 3.81E-03 - 3.38E-02 19



Drug Metabolism 3.81E-03 - 2.54E-02 11


Infection Mechanism 3.81E-03 - 2.54E-02 6






NFD Neurological Disease 5.34E-03 - 3.21E-02 11


CF Cellular Function and Maintenance 5.51E-03 - 3.31E-02 15




Antimicrobial Response 7.11E-03 - 7.11E-03 2

CF Cell-mediated Immune Response 7.11E-03 - 1.70E-02 4





8.08E-03 - 2.54E-02 8

DEV Auditory and Vestibular System Development and Function

8.55E-03 - 2.54E-02 2

Carbohydrate Metabolism 8.55E-03 - 3.38E-02 12

PRO Cell Cycle 8.55E-03 - 2.88E-02 13

CD Cell Death 8.55E-03 - 3.38E-02 20

CF Cellular Assembly and Organization 8.55E-03 - 3.38E-02 14


CDEV Developmental Disorder 8.55E-03 - 3.38E-02 28


CF Energy Production 8.55E-03 - 2.54E-02 3



Hematopoiesis 8.55E-03 - 1.70E-02 4



DEV Lymphoid Tissue Structure and Development 8.55E-03 - 2.54E-02 4

CF Nucleic Acid Metabolism 8.55E-03 - 2.54E-02 8

CF Protein Degradation 8.55E-03 - 8.55E-03 1


131





CF Post-Translational Modification 9.11E-03 - 2.66E-02 8

CF Protein Folding 9.11E-03 - 1.70E-02 2

CF Free Radical Scavenging 1.25E-02 - 1.25E-02 2


Organismal Survival 1.34E-02 - 1.34E-02 5


Cellular Compromise 1.70E-02 - 2.64E-02 7



CF RNA Post-Transcriptional Modification 1.70E-02 - 1.70E-02 1


1.70E-02 - 3.38E-02 2

Infectious Disease 2.22E-02 - 2.54E-02 3


NFD Behavior 2.54E-02 - 2.54E-02 1

CF RNA Trafficking 2.54E-02 - 2.54E-02 1

Canoniacal Pathways

One Carbon Pool by Folate 1.19E-3 4/38

Selenoamino Acid Metabolism 1.06E-2 3/69

PRO Glycine, Serine and Threonine Metabolism 1.16E-2 4/144

NFD LPS/IL-1 Mediated Inhibition of RXR Function 1.21E-2 8/198

Alanine and Aspartate Metabolism 1.23E-2 3/86

PRO Pyruvate Metabolism 1.49E-2 4/145

PRO Cysteine Metabolism 1.62E-2 3/85

Glycerolipid Metabolism 1.83E-2 4/145

PRO Arginine and Proline Metabolism 1.88E-2 4/178

Glyoxylate and Dicarboxylate Metabolism 1.92E-2 2/114

Xenobiotic Metabolism Signaling 3.54E-2 9/251

Biosynthesis of Steroids 3.79E-2 2/127

Glycolysis/Gluconeogenesis 4.20E-2 4/141

GO analysis

PRO GO:0019752: carboxylic acid metabolic process 2.55E-2 23

PRO GO:0006082: organic acid metabolic process 2.55E-2 23

GO:0044271: cellular nitrogen compound biosyn-thetic process

9.90E-2 11

Supplementary Table 3. Ingenuity pathway analysis (IPA) and GO stat analysis of 4 clusters showing the most

regulated expression of genes in the time of culture. The set of genes present in each indicated cluster was ana-

lyzed by two data bases and significant overrepresentations of gene functions are categorized with a color code

and related to proliferation (PRO), cell death (CD), neuronal function and development (NFD), cellular develop-

ment (CDEV) and development (DEV). Apart from the functional groups overrepresented in the specific clusters,

p-values along with the number of molecules present in each group are shown in this table.

CH A PTER 3

132

Biological process; role in cell P.value Fold changes Cluster

Systematic-Name GeneName Description Entrez gene summary, GO annotation, top findings from

Ingenuity knowledge databaseRA

D8/D1noRA D8/D1

D8 RA/noRA

NM_002166 ID2 Homo sapiens inhibitor of DNA binding 2, dominant negative helix-loop-helix protein negatively regulating cell differentiation, multicellular organismal development; positive regulation of cell cycle; positive regulation of cell proliferation;

2.24E-8 0.77 0.30 3.00 17

NM_024645 ZMAT4 Homo sapiens zinc finger, matrin type 4 2.37E-7 0.66 0.67 1.28 11

NM_001421 ELF4 Homo sapiens E74-like factor 4 (ets domain transcription factor) involved in natural killer cell development and function, innate immunity, and induction of cell cycle arrest in naive CD8+ cells

3.37E-6 0.21 0.95 0.25 13

NM_001005273 CHD3 Homo sapiens chromodomain helicase DNA binding protein 3, transcript variant 1 chromatin assembly or disassembly; chromatin modification 9.85E-6 0.30 1.25 0.17 13

NM_016307 PRRX2 Homo sapiens paired related homeobox 2 positive regulation of mesenchymal cell proliferation; 3.21E-5 0.11 0.46 0.29 13

NM_013435 RAX Homo sapiens retina and anterior neural fold homeobox retinal cell fate determination and also regulates stem cell proliferation; apoptosis

3.24E-5 4.19 1.19 3.53 4

NM_004289 NFE2L3 Homo sapiens nuclear factor (erythroid-derived 2)-like 3 oxidative stress response 3.50E-5 0.24 0.92 0.31 13

NM_002449 MSX2 Homo sapiens msh homeobox 2 negative regulation of cell proliferation; positive regulation of apoptosis; negative regulation of apoptosis; establishes a balance between survival and apoptosis of neural crest-derived cells required for proper craniofacial morphogenesis

4.43E-5 0.27 0.30 0.92 13

NM_001453 FOXC1 Homo sapiens forkhead box C1 role in the regulation of embryonic and ocular development 6.15E-5 13.24 0.84 13.72 3

NM_003326 TNFSF4 Homo sapiens tumor necrosis factor (ligand) superfamily, member 4 (tax-transcrip-tionally activated glycoprotein 1, 34kDa)

cholesterol metabolic process; positive regulation of cell proliferation; apoptosis, proliferation, differentiation, cytotoxic reaction,

8.65E-5 3.32 1.13 3.04 4

NM_002165 ID1 Homo sapiens inhibitor of DNA binding 1, dominant negative helix-loop-helix protein, transcript variant 1

cell growth, senescence, and differentiation. 9.37E-5 0.35 0.15 2.79 11

NM_003221 TFAP2B Homo sapiens transcription factor AP-2 beta (activating enhancer binding protein 2 beta)

stimulate cell proliferation and suppress terminal differentiation of spe-cific cell types during embryonic development, differentiation of neural crest cell derivatives, nervous system development; apoptosis, growth, metastatic potential, differentiation

1.05E-4 0.51 1.51 0.37 11

NM_015461 ZNF521 Homo sapiens zinc finger protein 521 possible roles in development, stem cell regulation and oncogenesis 1.23E-4 4.24 1.46 3.39 14

NM_181782 NCOA7 Homo sapiens nuclear receptor coactivator 7 regulation of ATRA-mediated neuronal differentiation, involved in RAR-mediated transcriptional regulation

1.43E-4 2.84 0.89 3.97 4

NM_007374 SIX6 Homo sapiens sine oculis homeobox homolog 6 (Drosophila) multicellular organismal development; organ morphogenesis 1.49E-4 0.45 1.22 0.41 11

NM_016170 TLX2 Homo sapiens T-cell leukemia homeobox 2 multicellular organismal development; enteric nervous system develop-ment; negative regulation of dendrite morphogenesis

1.63E-4 1.29 0.37 2.79 16

NM_003924 PHOX2B Homo sapiens paired-like homeobox 2b development of several major noradrenergic neuron populations and the determination of neurotransmitter phenotype; neuron migration; nervous system development; cell differentiation in hindbrain; negative regulation of neuron differentiation; positive regulation of neuron dif-ferentiation; cell development

2.19E-4 1.12 1.33 0.94 9

BC029439 ZMYM6 Homo sapiens zinc finger, MYM-type 6, mRNA (cDNA clone IMAGE:4609257), complete cds.

multicellular organismal development 4.04E-4 1.47 0.55 2.56 8

NM_020856 TSHZ3 Homo sapiens teashirt family zinc finger 3 multicellular organismal development 4.14E-4 5.03 1.58 3.33 4

NM_006998 SCGN Homo sapiens secretagogin, EF-hand calcium binding protein proliferation, directs a shift in the cell synthetic program away from growth and toward endocrine differentiation or cell maturation

4.94E-4 15.98 0.69 21.07 3

NM_002167 ID3 Homo sapiens inhibitor of DNA binding 3, dominant negative helix-loop-helix protein neuron differentiation; epithelial cell differentiation; positive regulation of apoptosis; negative regulation of transcription factor activity; regulation of cell cycle;

6.06E-4 0.77 0.31 2.11 12

NM_024697 ZNF659 Homo sapiens zinc finger protein 659 8.95E-4 0.73 2.88 0.19 7

ENST00000355898 ENST00000355898 Zinc finger protein 507. [Source:Uniprot/SWISSPROT;Acc:Q8TCN5] 1.81E-3 14.52 0.94 13.54 4

NM_145166 ZBTB47 Homo sapiens zinc finger and BTB domain containing 47 1.91E-3 0.78 0.97 0.94 2



NM_007146 VEZF1 Homo sapiens vascular endothelial zinc finger 1 angiogenesis; endothelial cell development; development 3.39E-3 1.31 0.84 1.52 1

NM_006492 ALX3 Homo sapiens aristaless-like homeobox 3 transcriptional regulator involved in cell-type differentiation and devel-opment

3.66E-3 1.59 1.02 1.42 16


133




D8/D1noRA D8/D1

D8 RA/noRA

NM_002166 ID2 Homo sapiens inhibitor of DNA binding 2, dominant negative helix-loop-helix protein negatively regulating cell differentiation, multicellular organismal development; positive regulation of cell cycle; positive regulation of cell proliferation;

2.24E-8 0.77 0.30 3.00 17

NM_024645 ZMAT4 Homo sapiens zinc finger, matrin type 4 2.37E-7 0.66 0.67 1.28 11

NM_001421 ELF4 Homo sapiens E74-like factor 4 (ets domain transcription factor) involved in natural killer cell development and function, innate immunity, and induction of cell cycle arrest in naive CD8+ cells

3.37E-6 0.21 0.95 0.25 13

NM_001005273 CHD3 Homo sapiens chromodomain helicase DNA binding protein 3, transcript variant 1 chromatin assembly or disassembly; chromatin modification 9.85E-6 0.30 1.25 0.17 13

NM_016307 PRRX2 Homo sapiens paired related homeobox 2 positive regulation of mesenchymal cell proliferation; 3.21E-5 0.11 0.46 0.29 13

NM_013435 RAX Homo sapiens retina and anterior neural fold homeobox retinal cell fate determination and also regulates stem cell proliferation; apoptosis

3.24E-5 4.19 1.19 3.53 4

NM_004289 NFE2L3 Homo sapiens nuclear factor (erythroid-derived 2)-like 3 oxidative stress response 3.50E-5 0.24 0.92 0.31 13

NM_002449 MSX2 Homo sapiens msh homeobox 2 negative regulation of cell proliferation; positive regulation of apoptosis; negative regulation of apoptosis; establishes a balance between survival and apoptosis of neural crest-derived cells required for proper craniofacial morphogenesis

4.43E-5 0.27 0.30 0.92 13

NM_001453 FOXC1 Homo sapiens forkhead box C1 role in the regulation of embryonic and ocular development 6.15E-5 13.24 0.84 13.72 3

NM_003326 TNFSF4 Homo sapiens tumor necrosis factor (ligand) superfamily, member 4 (tax-transcrip-tionally activated glycoprotein 1, 34kDa)

cholesterol metabolic process; positive regulation of cell proliferation; apoptosis, proliferation, differentiation, cytotoxic reaction,

8.65E-5 3.32 1.13 3.04 4

NM_002165 ID1 Homo sapiens inhibitor of DNA binding 1, dominant negative helix-loop-helix protein, transcript variant 1

cell growth, senescence, and differentiation. 9.37E-5 0.35 0.15 2.79 11

NM_003221 TFAP2B Homo sapiens transcription factor AP-2 beta (activating enhancer binding protein 2 beta)

stimulate cell proliferation and suppress terminal differentiation of spe-cific cell types during embryonic development, differentiation of neural crest cell derivatives, nervous system development; apoptosis, growth, metastatic potential, differentiation

1.05E-4 0.51 1.51 0.37 11

NM_015461 ZNF521 Homo sapiens zinc finger protein 521 possible roles in development, stem cell regulation and oncogenesis 1.23E-4 4.24 1.46 3.39 14

NM_181782 NCOA7 Homo sapiens nuclear receptor coactivator 7 regulation of ATRA-mediated neuronal differentiation, involved in RAR-mediated transcriptional regulation

1.43E-4 2.84 0.89 3.97 4

NM_007374 SIX6 Homo sapiens sine oculis homeobox homolog 6 (Drosophila) multicellular organismal development; organ morphogenesis 1.49E-4 0.45 1.22 0.41 11

NM_016170 TLX2 Homo sapiens T-cell leukemia homeobox 2 multicellular organismal development; enteric nervous system develop-ment; negative regulation of dendrite morphogenesis

1.63E-4 1.29 0.37 2.79 16

NM_003924 PHOX2B Homo sapiens paired-like homeobox 2b development of several major noradrenergic neuron populations and the determination of neurotransmitter phenotype; neuron migration; nervous system development; cell differentiation in hindbrain; negative regulation of neuron differentiation; positive regulation of neuron dif-ferentiation; cell development

2.19E-4 1.12 1.33 0.94 9

BC029439 ZMYM6 Homo sapiens zinc finger, MYM-type 6, mRNA (cDNA clone IMAGE:4609257), complete cds.

multicellular organismal development 4.04E-4 1.47 0.55 2.56 8

NM_020856 TSHZ3 Homo sapiens teashirt family zinc finger 3 multicellular organismal development 4.14E-4 5.03 1.58 3.33 4

NM_006998 SCGN Homo sapiens secretagogin, EF-hand calcium binding protein proliferation, directs a shift in the cell synthetic program away from growth and toward endocrine differentiation or cell maturation

4.94E-4 15.98 0.69 21.07 3

NM_002167 ID3 Homo sapiens inhibitor of DNA binding 3, dominant negative helix-loop-helix protein neuron differentiation; epithelial cell differentiation; positive regulation of apoptosis; negative regulation of transcription factor activity; regulation of cell cycle;

6.06E-4 0.77 0.31 2.11 12


ENST00000355898 ENST00000355898 Zinc finger protein 507. [Source:Uniprot/SWISSPROT;Acc:Q8TCN5] 1.81E-3 14.52 0.94 13.54 4

NM_145166 ZBTB47 Homo sapiens zinc finger and BTB domain containing 47 1.91E-3 0.78 0.97 0.94 2



NM_007146 VEZF1 Homo sapiens vascular endothelial zinc finger 1 angiogenesis; endothelial cell development; development 3.39E-3 1.31 0.84 1.52 1

NM_006492 ALX3 Homo sapiens aristaless-like homeobox 3 transcriptional regulator involved in cell-type differentiation and devel-opment

3.66E-3 1.59 1.02 1.42 16

CH A PTER 3

134




D8/D1noRA D8/D1

D8 RA/noRA

NM_006569 CGREF1 Homo sapiens cell growth regulator with EF-hand domain 1 response to stress; cell cycle; cell cycle arrest; cell adhesion; negative regulation of cell proliferation

4.01E-3 0.35 0.71 0.49 13

THC2634862 THC2634862 NM_063888 TAF (TBP-associated transcription factor) family member (taf-13) {Caenorhabditis elegans} (exp=-1; wgp=0; cg=0), partial (15%)

4.30E-3 0.41 1.30 0.52 2

ENST00000371189 ENST00000371189 Nuclear factor 1 A-type (Nuclear factor 1/A) (NF1-A) (NFI-A) (NF-I/A) (CCAAT-box-binding transcription factor) (CTF) (TGGCA-binding protein). [Source:Uniprot/SWISSPROT;Acc:Q12857]

DNA replication 4.79E-3 3.46 1.22 2.73 3

NR_002307 MSX2P Homo sapiens msh homeobox 2 pseudogene on chromosome 17 5.61E-3 0.34 0.33 1.17 13

NM_022366 TFB2M Homo sapiens transcription factor B2, mitochondria rRNA methylation; transcription of human mitochondrial DNA 5.94E-3 0.49 0.88 0.65 2

NM_007086 WDHD1 Homo sapiens WD repeat and HMG-box DNA binding protein 1, transcript variant 1 chromatin assembly, transcription and replication 6.20E-3 0.80 0.91 0.91 7

NM_004599 SREBF2 Homo sapiens sterol regulatory element binding transcription factor 2 lipid metabolic process; spermatogenesis; aging; steroid metabolic process; cholesterol metabolic process; damage, survival

6.73E-3 1.34 1.57 0.61 16

NM_031844 HNRPU Homo sapiens heterogeneous nuclear ribonucleoprotein U (scaffold attachment factor A), transcript variant 1,

RNA processing; mRNA processing; RNA splicing; CRD-mediated mRNA stabilization

6.86E-3 0.84 0.80 1.38 9

NM_002202 ISL1 Homo sapiens ISL1 transcription factor, LIM/homeodomain, (islet-1) neural crest cell migration; visceral motor neuron differentiation; retinal ganglion cell axon guidance; negative regulation of neuron dif-ferentiation; positive regulation of transcription from RNA polymerase II promoter; neuron fate commitment; mesenchymal cell differentiation

7.91E-3 1.06 1.88 0.56 9

NM_025049 PIF1 Homo sapiens PIF1 5’-to-3’ DNA helicase homolog (S. cerevisiae) negatively regulates telomerase, chromosome maintenance in associa-tion with DNA replication,

8.50E-3 1.06 1.48 0.64 7

NM_015995 KLF13 Homo sapiens Kruppel-like factor 13 cell death, apoptosis, outgrowth, proliferation 8.50E-3 1.55 0.79 1.54 1

ENST00000380186 SSBP2 Single-stranded DNA-binding protein 2 (Sequence-specific single- stranded-DNA-binding protein 2). [Source:Uniprot/SWISSPROT;Acc:P81877]

regulator of hematopoietic growth and differentiation, inhibits prostate cancer cell proliferation

8.98E-3 1.22 0.90 1.83 14

NM_002397 MEF2C Homo sapiens MADS box transcription enhancer factor 2, polypeptide C (myocyte enhancer factor 2C)

apoptosis; multicellular organismal development; nervous system development; cell differentiation; positive regulation of survival gene product expression

9.39E-3 0.91 1.99 0.63 7

NM_024786 ZDHHC11 Homo sapiens zinc finger, DHHC-type containing 11 9.85E-3 0.60 1.07 0.60 17


NM_174937 TCERG1L Homo sapiens transcription elongation regulator 1-like 1.10E-2 6.62 0.67 9.48 4

NM_015144 ZCCHC14 Homo sapiens zinc finger, CCHC domain containing 14 cell communication 1.19E-2 1.55 1.01 1.61 8

NM_003223 TFAP4 Homo sapiens transcription factor AP-4 (activating enhancer binding protein 4) apoptosis 1.19E-2 0.55 1.07 0.60 11

NM_006164 NFE2L2 Homo sapiens nuclear factor (erythroid-derived 2)-like 2 apoptosis, oxidative stress response, cell death, damage, killing, survival, neuronal differentiation

1.20E-2 1.01 0.77 1.68 9

NM_006813 PNRC1 Homo sapiens proline-rich nuclear receptor coactivator 1 1.31E-2 2.46 1.29 1.95 8

BC042172 BC042172 Homo sapiens zinc finger, MYM-type 6, mRNA (cDNA clone MGC:52473 IM-AGE:5455214), complete cds.

1.34E-2 1.75 0.85 2.82 8

NM_004091 E2F2 Homo sapiens E2F transcription factor 2 This protein binds specifically to retinoblastoma protein pRB in a cell-cycle dependent manner, apoptosis; regulation of cell cycle,

1.34E-2 0.41 0.83 0.56 2

BC025026 SIN3B Homo sapiens SIN3 homolog B, transcription regulator (yeast), mRNA (cDNA clone IMAGE:3923074), partial cds.

negative regulation of transcription, DNA-dependent 1.36E-2 0.91 1.28 0.61 11

NM_032268 ZNRF1 Homo sapiens zinc and ring finger 1 ubiquitin-mediated protein modification, upregulated in response to nerve damage

1.37E-2 1.14 0.95 1.27 1

NM_004799 ZFYVE9 Homo sapiens zinc finger, FYVE domain containing 9, transcript variant 3 endocytosis; transforming growth factor beta receptor signaling pathway; transforming growth factor beta receptor complex assembly; SMAD protein complex assembly; SMAD protein nuclear translocation

1.41E-2 1.36 1.33 0.84 19

ENST00000373816 GMEB1 Glucocorticoid modulatory element-binding protein 1 (GMEB-1) (Parvovirus initiation factor p96) (PIF p96) (DNA-binding protein p96PIF). [Source:Uniprot/SWISSPROT;Acc:Q9Y692]

potent inhibitor of caspase activation and apoptosis in response to oxidative stress

1.44E-2 0.82 0.89 1.02 17

NM_001951 E2F5 Homo sapiens E2F transcription factor 5, p130-binding interact with tumor suppressor proteins p130 and p107, but not with pRB, downregulated in late embriogenesis

1.48E-2 0.56 1.28 0.42 11


135




D8/D1noRA D8/D1

D8 RA/noRA

NM_006569 CGREF1 Homo sapiens cell growth regulator with EF-hand domain 1 response to stress; cell cycle; cell cycle arrest; cell adhesion; negative regulation of cell proliferation

4.01E-3 0.35 0.71 0.49 13

THC2634862 THC2634862 NM_063888 TAF (TBP-associated transcription factor) family member (taf-13) {Caenorhabditis elegans} (exp=-1; wgp=0; cg=0), partial (15%)

4.30E-3 0.41 1.30 0.52 2

ENST00000371189 ENST00000371189 Nuclear factor 1 A-type (Nuclear factor 1/A) (NF1-A) (NFI-A) (NF-I/A) (CCAAT-box-binding transcription factor) (CTF) (TGGCA-binding protein). [Source:Uniprot/SWISSPROT;Acc:Q12857]

DNA replication 4.79E-3 3.46 1.22 2.73 3

NR_002307 MSX2P Homo sapiens msh homeobox 2 pseudogene on chromosome 17 5.61E-3 0.34 0.33 1.17 13

NM_022366 TFB2M Homo sapiens transcription factor B2, mitochondria rRNA methylation; transcription of human mitochondrial DNA 5.94E-3 0.49 0.88 0.65 2

NM_007086 WDHD1 Homo sapiens WD repeat and HMG-box DNA binding protein 1, transcript variant 1 chromatin assembly, transcription and replication 6.20E-3 0.80 0.91 0.91 7

NM_004599 SREBF2 Homo sapiens sterol regulatory element binding transcription factor 2 lipid metabolic process; spermatogenesis; aging; steroid metabolic process; cholesterol metabolic process; damage, survival

6.73E-3 1.34 1.57 0.61 16

NM_031844 HNRPU Homo sapiens heterogeneous nuclear ribonucleoprotein U (scaffold attachment factor A), transcript variant 1,

RNA processing; mRNA processing; RNA splicing; CRD-mediated mRNA stabilization

6.86E-3 0.84 0.80 1.38 9

NM_002202 ISL1 Homo sapiens ISL1 transcription factor, LIM/homeodomain, (islet-1) neural crest cell migration; visceral motor neuron differentiation; retinal ganglion cell axon guidance; negative regulation of neuron dif-ferentiation; positive regulation of transcription from RNA polymerase II promoter; neuron fate commitment; mesenchymal cell differentiation

7.91E-3 1.06 1.88 0.56 9

NM_025049 PIF1 Homo sapiens PIF1 5’-to-3’ DNA helicase homolog (S. cerevisiae) negatively regulates telomerase, chromosome maintenance in associa-tion with DNA replication,

8.50E-3 1.06 1.48 0.64 7

NM_015995 KLF13 Homo sapiens Kruppel-like factor 13 cell death, apoptosis, outgrowth, proliferation 8.50E-3 1.55 0.79 1.54 1

ENST00000380186 SSBP2 Single-stranded DNA-binding protein 2 (Sequence-specific single- stranded-DNA-binding protein 2). [Source:Uniprot/SWISSPROT;Acc:P81877]

regulator of hematopoietic growth and differentiation, inhibits prostate cancer cell proliferation

8.98E-3 1.22 0.90 1.83 14

NM_002397 MEF2C Homo sapiens MADS box transcription enhancer factor 2, polypeptide C (myocyte enhancer factor 2C)

apoptosis; multicellular organismal development; nervous system development; cell differentiation; positive regulation of survival gene product expression

9.39E-3 0.91 1.99 0.63 7



NM_174937 TCERG1L Homo sapiens transcription elongation regulator 1-like 1.10E-2 6.62 0.67 9.48 4

NM_015144 ZCCHC14 Homo sapiens zinc finger, CCHC domain containing 14 cell communication 1.19E-2 1.55 1.01 1.61 8

NM_003223 TFAP4 Homo sapiens transcription factor AP-4 (activating enhancer binding protein 4) apoptosis 1.19E-2 0.55 1.07 0.60 11

NM_006164 NFE2L2 Homo sapiens nuclear factor (erythroid-derived 2)-like 2 apoptosis, oxidative stress response, cell death, damage, killing, survival, neuronal differentiation

1.20E-2 1.01 0.77 1.68 9

NM_006813 PNRC1 Homo sapiens proline-rich nuclear receptor coactivator 1 1.31E-2 2.46 1.29 1.95 8

BC042172 BC042172 Homo sapiens zinc finger, MYM-type 6, mRNA (cDNA clone MGC:52473 IM-AGE:5455214), complete cds.

1.34E-2 1.75 0.85 2.82 8

NM_004091 E2F2 Homo sapiens E2F transcription factor 2 This protein binds specifically to retinoblastoma protein pRB in a cell-cycle dependent manner, apoptosis; regulation of cell cycle,

1.34E-2 0.41 0.83 0.56 2

BC025026 SIN3B Homo sapiens SIN3 homolog B, transcription regulator (yeast), mRNA (cDNA clone IMAGE:3923074), partial cds.

negative regulation of transcription, DNA-dependent 1.36E-2 0.91 1.28 0.61 11

NM_032268 ZNRF1 Homo sapiens zinc and ring finger 1 ubiquitin-mediated protein modification, upregulated in response to nerve damage

1.37E-2 1.14 0.95 1.27 1

NM_004799 ZFYVE9 Homo sapiens zinc finger, FYVE domain containing 9, transcript variant 3 endocytosis; transforming growth factor beta receptor signaling pathway; transforming growth factor beta receptor complex assembly; SMAD protein complex assembly; SMAD protein nuclear translocation

1.41E-2 1.36 1.33 0.84 19

ENST00000373816 GMEB1 Glucocorticoid modulatory element-binding protein 1 (GMEB-1) (Parvovirus initiation factor p96) (PIF p96) (DNA-binding protein p96PIF). [Source:Uniprot/SWISSPROT;Acc:Q9Y692]

potent inhibitor of caspase activation and apoptosis in response to oxidative stress

1.44E-2 0.82 0.89 1.02 17

NM_001951 E2F5 Homo sapiens E2F transcription factor 5, p130-binding interact with tumor suppressor proteins p130 and p107, but not with pRB, downregulated in late embriogenesis

1.48E-2 0.56 1.28 0.42 11

CH A PTER 3

136




D8/D1noRA D8/D1

D8 RA/noRA

ENST00000219169 ENST00000219169 Nuclear transport factor 2 (NTF-2) (Placental protein 15) (PP15). [Source:Uniprot/SWISSPROT;Acc:P61970]

protein transporter activity 1.48E-2 0.71 1.02 0.68 2

NM_024329 EFHD2 Homo sapiens EF-hand domain family, member D2 calclium ion binding; 1.76E-2 0.52 0.97 0.64 2

NM_005225 E2F1 Homo sapiens E2F transcription factor 1 It can mediate both cell proliferation and p53-dependent/independent apoptosis

1.82E-2 0.50 0.74 0.71 12

NM_005413 SIX3 Homo sapiens sine oculis homeobox homolog 3 (Drosophila) multicellular organismal development; negative regulation of brain development; diencephalon development; telencephalon development; forebrain anterior/posterior pattern formation; negative regulation of Wnt receptor signaling pathway;

1.88E-2 0.72 1.37 0.48 5

NM_025134 CHD9 Homo sapiens chromodomain helicase DNA binding protein 9 chromatin assembly or disassembly; 2.08E-2 1.30 0.79 1.51 15

ENST00000368192 ENST00000368192 ETS translocation variant 3 (ETS-domain transcriptional repressor PE1) (PE-1) (Mi-togenic Ets transcriptional suppressor). [Source:Uniprot/SWISSPROT;Acc:P41162]

2.38E-2 0.95 0.71 1.71 17

NM_024501 HOXD1 Homo sapiens homeobox D1 multicellular organismal development; embryonic skeletal system development

2.39E-2 6.10 0.66 7.15 4

NM_003791 MBTPS1 Homo sapiens membrane-bound transcription factor peptidase, site 1, transcript variant 1

regulation of lipid metabolism in cells 2.39E-2 1.37 1.03 1.37 1

NM_018416 FOXJ2 Homo sapiens forkhead box J2 2.40E-2 1.09 0.73 1.72 1

NM_012257 HBP1 Homo sapiens HMG-box transcription factor 1 cell cycle arrest; Wnt receptor signaling pathway 2.40E-2 1.68 1.04 1.70 8


NM_138473 SP1 Homo sapiens Sp1 transcription factor trophectodermal cell differentiation; liver development; embryonic placenta development; regulation of transcription; cell death, differentia-tion, extension, apoptosis, colony formation

2.46E-2 1.59 0.90 1.45 18

NM_007249 KLF12 Homo sapiens Kruppel-like factor 12 regulator of gene expression during vertebrate development and carcinogenesis

2.54E-2 2.33 0.98 2.43 8

NM_001040619 ATF3 Homo sapiens activating transcription factor 3, transcript variant 4 gluconeogenesis; regulation of transcription, DNA-dependent; positive regulation of cell proliferation

2.60E-2 0.76 0.50 1.89 15

NM_024680 E2F8 Homo sapiens E2F transcription factor 8 orchestrating expression of genes required for cell cycle progression and proliferation

2.65E-2 0.57 0.98 0.69 7

NM_005655 KLF10 Homo sapiens Kruppel-like factor 10, transcript variant 1 induction of apoptosis; cell-cell signaling; cell proliferation; negative regulation of cell proliferation;

2.82E-2 1.52 0.81 2.75 8

NM_173198 NR4A3 Homo sapiens nuclear receptor subfamily 4, group A, member 3, transcript variant 2 mesoderm formation; organ regeneration; apoptosis, cell cycle pro-gression, growth, differentiation, survival, proliferation

2.84E-2 0.89 0.74 1.60 9

NM_001079526 IKZF2 Homo sapiens IKAROS family zinc finger 2 (Helios), transcript variant 2 proliferation, survival, 2.95E-2 2.91 1.12 2.37 19

NM_012068 ATF5 Homo sapiens activating transcription factor 5 regulation of transcription from RNA polymerase II promoter; anti-apoptosis; negative regulation of neurogenesis

2.99E-2 0.55 0.78 0.55 12


ENST00000356102 ENST00000356102 Doublesex- and mab-3-related transcription factor C1. [Source:Uniprot/SWIS-SPROT; Acc:Q5HYR2]

3.07E-2 1.71 1.00 1.79 8

NM_017580 ZRANB1 Homo sapiens zinc finger, RAN-binding domain containing 1 positive regulation of Wnt receptor signaling pathway 3.14E-2 1.29 0.90 1.48 1

NM_032680 EFCAB4B Homo sapiens EF-hand calcium binding domain 4B positive regulation of calcium ion transport; 3.35E-2 0.73 1.27 0.63 20

BC046475 MGC26356 Homo sapiens similar to zinc finger protein 595, mRNA (cDNA clone MGC:51010 IMAGE:5270267), complete cds.

3.37E-2 0.41 0.78 0.63 12

NM_013448 BAZ1A Homo sapiens bromodomain adjacent to zinc finger domain, 1A, transcript variant 1 chromatin remodeling 3.53E-2 0.43 0.92 0.69 2

NM_005250 FOXL1 Homo sapiens forkhead box L1 multicellular organismal development; organ morphogenesis; proteogly-can biosynthetic process; regulation of Wnt receptor signaling pathway;

3.66E-2 2.98 1.16 2.86 8

NM_006195 PBX3 Homo sapiens pre-B-cell leukemia transcription factor 3 anterior compartment pattern formation; posterior compartment specification

3.69E-2 2.62 1.22 1.64 14

BC010934 ZBTB20 Homo sapiens zinc finger and BTB domain containing 20, mRNA (cDNA clone IM-AGE:4291354), partial cds.

3.99E-2 1.69 0.61 2.24 8



137




D8/D1noRA D8/D1

D8 RA/noRA

ENST00000219169 ENST00000219169 Nuclear transport factor 2 (NTF-2) (Placental protein 15) (PP15). [Source:Uniprot/SWISSPROT;Acc:P61970]

protein transporter activity 1.48E-2 0.71 1.02 0.68 2

NM_024329 EFHD2 Homo sapiens EF-hand domain family, member D2 calclium ion binding; 1.76E-2 0.52 0.97 0.64 2

NM_005225 E2F1 Homo sapiens E2F transcription factor 1 It can mediate both cell proliferation and p53-dependent/independent apoptosis

1.82E-2 0.50 0.74 0.71 12

NM_005413 SIX3 Homo sapiens sine oculis homeobox homolog 3 (Drosophila) multicellular organismal development; negative regulation of brain development; diencephalon development; telencephalon development; forebrain anterior/posterior pattern formation; negative regulation of Wnt receptor signaling pathway;

1.88E-2 0.72 1.37 0.48 5

NM_025134 CHD9 Homo sapiens chromodomain helicase DNA binding protein 9 chromatin assembly or disassembly; 2.08E-2 1.30 0.79 1.51 15

ENST00000368192 ENST00000368192 ETS translocation variant 3 (ETS-domain transcriptional repressor PE1) (PE-1) (Mi-togenic Ets transcriptional suppressor). [Source:Uniprot/SWISSPROT;Acc:P41162]

2.38E-2 0.95 0.71 1.71 17

NM_024501 HOXD1 Homo sapiens homeobox D1 multicellular organismal development; embryonic skeletal system development

2.39E-2 6.10 0.66 7.15 4

NM_003791 MBTPS1 Homo sapiens membrane-bound transcription factor peptidase, site 1, transcript variant 1

regulation of lipid metabolism in cells 2.39E-2 1.37 1.03 1.37 1

NM_018416 FOXJ2 Homo sapiens forkhead box J2 2.40E-2 1.09 0.73 1.72 1

NM_012257 HBP1 Homo sapiens HMG-box transcription factor 1 cell cycle arrest; Wnt receptor signaling pathway 2.40E-2 1.68 1.04 1.70 8


NM_138473 SP1 Homo sapiens Sp1 transcription factor trophectodermal cell differentiation; liver development; embryonic placenta development; regulation of transcription; cell death, differentia-tion, extension, apoptosis, colony formation

2.46E-2 1.59 0.90 1.45 18

NM_007249 KLF12 Homo sapiens Kruppel-like factor 12 regulator of gene expression during vertebrate development and carcinogenesis

2.54E-2 2.33 0.98 2.43 8

NM_001040619 ATF3 Homo sapiens activating transcription factor 3, transcript variant 4 gluconeogenesis; regulation of transcription, DNA-dependent; positive regulation of cell proliferation

2.60E-2 0.76 0.50 1.89 15

NM_024680 E2F8 Homo sapiens E2F transcription factor 8 orchestrating expression of genes required for cell cycle progression and proliferation

2.65E-2 0.57 0.98 0.69 7

NM_005655 KLF10 Homo sapiens Kruppel-like factor 10, transcript variant 1 induction of apoptosis; cell-cell signaling; cell proliferation; negative regulation of cell proliferation;

2.82E-2 1.52 0.81 2.75 8

NM_173198 NR4A3 Homo sapiens nuclear receptor subfamily 4, group A, member 3, transcript variant 2 mesoderm formation; organ regeneration; apoptosis, cell cycle pro-gression, growth, differentiation, survival, proliferation

2.84E-2 0.89 0.74 1.60 9

NM_001079526 IKZF2 Homo sapiens IKAROS family zinc finger 2 (Helios), transcript variant 2 proliferation, survival, 2.95E-2 2.91 1.12 2.37 19

NM_012068 ATF5 Homo sapiens activating transcription factor 5 regulation of transcription from RNA polymerase II promoter; anti-apoptosis; negative regulation of neurogenesis

2.99E-2 0.55 0.78 0.55 12


ENST00000356102 ENST00000356102 Doublesex- and mab-3-related transcription factor C1. [Source:Uniprot/SWIS-SPROT; Acc:Q5HYR2]

3.07E-2 1.71 1.00 1.79 8

NM_017580 ZRANB1 Homo sapiens zinc finger, RAN-binding domain containing 1 positive regulation of Wnt receptor signaling pathway 3.14E-2 1.29 0.90 1.48 1

NM_032680 EFCAB4B Homo sapiens EF-hand calcium binding domain 4B positive regulation of calcium ion transport; 3.35E-2 0.73 1.27 0.63 20

BC046475 MGC26356 Homo sapiens similar to zinc finger protein 595, mRNA (cDNA clone MGC:51010 IMAGE:5270267), complete cds.

3.37E-2 0.41 0.78 0.63 12

NM_013448 BAZ1A Homo sapiens bromodomain adjacent to zinc finger domain, 1A, transcript variant 1 chromatin remodeling 3.53E-2 0.43 0.92 0.69 2

NM_005250 FOXL1 Homo sapiens forkhead box L1 multicellular organismal development; organ morphogenesis; proteogly-can biosynthetic process; regulation of Wnt receptor signaling pathway;

3.66E-2 2.98 1.16 2.86 8

NM_006195 PBX3 Homo sapiens pre-B-cell leukemia transcription factor 3 anterior compartment pattern formation; posterior compartment specification

3.69E-2 2.62 1.22 1.64 14

BC010934 ZBTB20 Homo sapiens zinc finger and BTB domain containing 20, mRNA (cDNA clone IM-AGE:4291354), partial cds.

3.99E-2 1.69 0.61 2.24 8


CH A PTER 3

138




D8/D1noRA D8/D1

D8 RA/noRA

NM_021211 ZBED5 Homo sapiens zinc finger, BED-type containing 5 4.10E-2 1.84 0.95 1.70 8


NM_138456 BATF2 Homo sapiens basic leucine zipper transcription factor, ATF-like 2 4.16E-2 1.60 0.60 1.83 10

NM_032328 EFCAB2 Homo sapiens EF-hand calcium binding domain 2 calclium ion binding; 4.20E-2 0.74 0.52 1.61 11

NM_181659 NCOA3 Homo sapiens nuclear receptor coactivator 3, transcript variant 1 positive regulation of estrogen receptor signaling pathway; positive regulation of transcription; proliferation, growth, apoptosis

4.22E-2 3.94 1.22 2.56 4

NM_002148 HOXD10 Homo sapiens homeobox D10 multicellular organismal development;spinal cord motor neuron cell fate specification; peripheral nervous system neuron development; neuromuscular process

4.27E-2 6.04 1.22 3.30 4

NM_021260 ZFYVE1 Homo sapiens zinc finger, FYVE domain containing 1, transcript variant 1 cell dispersal, morphology 4.40E-2 2.19 1.20 1.66 16

NM_032836 FIZ1 Homo sapiens FLT3-interacting zinc finger 1 interacts with a receptor tyrosine kinase involved in the regulation of hematopoietic and lymphoid cells, regulates the expression of rod-specific genes in retina

4.51E-2 0.95 0.95 0.91 15

NM_001001890 RUNX1 Homo sapiens runt-related transcription factor 1 (acute myeloid leukemia 1; aml1 oncogene), transcript variant 2

regulation of transcription, DNA-dependent; multicellular organismal development; positive regulation of granulocyte differentiation; positive regulation of angiogenesis; differentiation, apoptosis, proliferation, growth, quantity, cell death, development,

4.51E-2 0.86 2.51 0.45 15

NM_022351 EFCBP1 Homo sapiens EF-hand calcium binding protein 1 calclium ion binding; oxidoreductase activity 4.51E-2 0.89 0.61 1.76 17

NM_003143 SSBP1 Homo sapiens single-stranded DNA binding protein 1 mitochondrion morphogenesis 4.57E-2 0.64 1.06 0.69 2


NM_020529 NFKBIA Homo sapiens nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, alpha

apoptosis; anti-apoptosis; regulation of cell proliferation; regulation of NF-kappaB import into nucleus; proliferation, survival, growth, cell viability, cell death,

4.67E-2 0.58 0.78 0.88 2

NM_014648 DZIP3 Homo sapiens zinc finger DAZ interacting protein 3 protein polyubiquitination 4.87E-2 3.05 1.91 1.01 19


NM_015428 ZNF473 Homo sapiens zinc finger protein 473, transcript variant 1 histone mRNA 3’-end processing 4.91E-2 0.87 1.30 0.64 7



NM_014827 ZC3H11A Homo sapiens zinc finger CCCH-type containing 11A 4.98E-2 1.48 0.96 1.54 8

Supplementary Table 4. List of significantly regulated transcription factors during RA treat-ment of SH-SY5Y cells. Full list of all regulated transcription factors (TF’s) was composed with an algorithm after BH correction on the data set (see methods) (P value< 0.05). Each TF was then investigated regarding its biological function with the relevant Entrez gene summary, GO an-notation and IPA gene summary. The regulation pattern fold changes of each gene are indicated between day 1 (D1) and day 8 (D8) in RA and noRA culture conditions and between D8 of RA and noRA culture conditions. Additionally, a cluster number is shown to which each TF’s pattern of expression in time is assigned (Supplementary Figure 1).


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D8/D1noRA D8/D1

D8 RA/noRA

NM_021211 ZBED5 Homo sapiens zinc finger, BED-type containing 5 4.10E-2 1.84 0.95 1.70 8


NM_138456 BATF2 Homo sapiens basic leucine zipper transcription factor, ATF-like 2 4.16E-2 1.60 0.60 1.83 10

NM_032328 EFCAB2 Homo sapiens EF-hand calcium binding domain 2 calclium ion binding; 4.20E-2 0.74 0.52 1.61 11

NM_181659 NCOA3 Homo sapiens nuclear receptor coactivator 3, transcript variant 1 positive regulation of estrogen receptor signaling pathway; positive regulation of transcription; proliferation, growth, apoptosis

4.22E-2 3.94 1.22 2.56 4

NM_002148 HOXD10 Homo sapiens homeobox D10 multicellular organismal development;spinal cord motor neuron cell fate specification; peripheral nervous system neuron development; neuromuscular process

4.27E-2 6.04 1.22 3.30 4

NM_021260 ZFYVE1 Homo sapiens zinc finger, FYVE domain containing 1, transcript variant 1 cell dispersal, morphology 4.40E-2 2.19 1.20 1.66 16

NM_032836 FIZ1 Homo sapiens FLT3-interacting zinc finger 1 interacts with a receptor tyrosine kinase involved in the regulation of hematopoietic and lymphoid cells, regulates the expression of rod-specific genes in retina

4.51E-2 0.95 0.95 0.91 15

NM_001001890 RUNX1 Homo sapiens runt-related transcription factor 1 (acute myeloid leukemia 1; aml1 oncogene), transcript variant 2

regulation of transcription, DNA-dependent; multicellular organismal development; positive regulation of granulocyte differentiation; positive regulation of angiogenesis; differentiation, apoptosis, proliferation, growth, quantity, cell death, development,

4.51E-2 0.86 2.51 0.45 15

NM_022351 EFCBP1 Homo sapiens EF-hand calcium binding protein 1 calclium ion binding; oxidoreductase activity 4.51E-2 0.89 0.61 1.76 17

NM_003143 SSBP1 Homo sapiens single-stranded DNA binding protein 1 mitochondrion morphogenesis 4.57E-2 0.64 1.06 0.69 2


NM_020529 NFKBIA Homo sapiens nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, alpha

apoptosis; anti-apoptosis; regulation of cell proliferation; regulation of NF-kappaB import into nucleus; proliferation, survival, growth, cell viability, cell death,

4.67E-2 0.58 0.78 0.88 2

NM_014648 DZIP3 Homo sapiens zinc finger DAZ interacting protein 3 protein polyubiquitination 4.87E-2 3.05 1.91 1.01 19


NM_015428 ZNF473 Homo sapiens zinc finger protein 473, transcript variant 1 histone mRNA 3’-end processing 4.91E-2 0.87 1.30 0.64 7



NM_014827 ZC3H11A Homo sapiens zinc finger CCCH-type containing 11A 4.98E-2 1.48 0.96 1.54 8

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Gene Name

Systematic Name

Description D8 noRA

D8 RA

AAK1 NM_014911 Homo sapiens AP2 associated kinase 1 (AAK1) 6.639 6.695

ADAM23 NM_003812 Homo sapiens ADAM metallopeptidase domain 23 (ADAM23) 9.127 9.097

AGTR1 NM_031850 Homo sapiens angiotensin II receptor, type 1 (AGTR1), transcript variant 4

8.875 6.236

ALDH1A1 NM_000689 Homo sapiens aldehyde dehydrogenase 1 family, member A1 (ALDH1A1) 4.770 5.408

AMPH NM_001635 Homo sapiens amphiphysin (Stiff-Man syndrome with breast cancer 128kDa autoantigen) (AMPH), transcript variant 1

5.233 5.664

ARHGEF2 NM_004723 Homo sapiens rho/rac guanine nucleotide exchange factor (GEF) 2 (ARHGEF2)

9.350 8.944

CADPS NM_183393 Homo sapiens Ca2+-dependent secretion activator (CADPS), transcript variant 3

7.883 9.129

CALN1 NM_031468 Homo sapiens calneuron 1 (CALN1), transcript variant 1 5.436 5.032

CASP7 NM_033338 Homo sapiens caspase 7, apoptosis-related cysteine peptidase (CASP7), transcript variant delta

10.055 9.778

CDK5 NM_004935 Homo sapiens cyclin-dependent kinase 5 (CDK5) 13.039 13.383

COMT NM_000754 Homo sapiens catechol-O-methyltransferase (COMT), transcript variant MB-COMT

10.645 10.161

CTDSP1 NM_182642 Homo sapiens CTD (carboxy-terminal domain, RNA polymerase II, poly-peptide A) small phosphatase 1 (CTDSP1), transcript variant 2

10.444 10.549

DDC NM_000790 Homo sapiens dopa decarboxylase (aromatic L-amino acid decarboxyl-ase) (DDC)

14.488 12.770

DENR NM_003677 Homo sapiens density-regulated protein (DENR) 10.300 10.178

DLK1 NM_003836 Homo sapiens delta-like 1 homolog (Drosophila) (DLK1), transcript variant 1

14.234 9.944

DNM3 NM_015569 Homo sapiens dynamin 3 (DNM3) 8.519 10.843

DOK6 NM_152721 Homo sapiens docking protein 6 (DOK6) 9.773 9.365

EDG2 NM_057159 Homo sapiens endothelial differentiation, lysophosphatidic acid G-protein-coupled receptor, 2 (EDG2), transcript variant 2

5.317 7.019

EHBP1A1 NM_015252 Homo sapiens EH domain binding protein 1 (EHBP1) 7.992 8.111

ELOVL4 NM_022726 Homo sapiens elongation of very long chain fatty acids (FEN1/Elo2, SUR4/Elo3, yeast)-like 4 (ELOVL4)

7.881 8.537

EN1 NM_001426 Homo sapiens engrailed homolog 1 (EN1) 4.963 5.201

FOXA1 NM_004496 Homo sapiens forkhead box A1 (FOXA1) 4.717 4.896

FST NM_013409 Homo sapiens follistatin (FST), transcript variant FST344 4.915 4.506

GBP1 NM_002053 Homo sapiens guanylate binding protein 1, interferon-inducible, 67kDa (GBP1)

4.986 5.320

GPCR5A NM_003979 Homo sapiens G protein-coupled receptor, family C, group 5, member A (GPRC5A)

4.787 4.774

HIP1R NM_003959 Homo sapiens huntingtin interacting protein 1 related (HIP1R) 10.786 10.812

HN1 NM_001002033 Homo sapiens hematological and neurological expressed 1 (HN1), transcript variant 3

14.560 14.371

HPRT1 NM_000194 Homo sapiens hypoxanthine phosphoribosyltransferase 1 (Lesch-Nyhan syndrome) (HPRT1)

11.856 11.379

HS6ST3 NM_153456 Homo sapiens heparan sulfate 6-O-sulfotransferase 3 (HS6ST3) 5.437 5.679

KCNJ6 NM_002240 Homo sapiens potassium inwardly-rectifying channel, subfamily J, member 6 (KCNJ6)

4.053 4.088

KIFAP3 NM_014970 Homo sapiens kinesin-associated protein 3 (KIFAP3) 12.626 13.293

KLK6 NM_001012964 Homo sapiens kallikrein-related peptidase 6 (KLK6), transcript variant B 5.139 5.506


141

Gene Name

Systematic Name

Description D8 noRA

D8 RA

LASS6 NM_203463 Homo sapiens LAG1 homolog, ceramide synthase 6 (S. cerevisiae) (LASS6)

10.649 11.237

LRDD NM_018494 Homo sapiens leucine-rich repeats and death domain containing (LRDD), transcript variant 2

10.324 9.964

LTF NM_002343 Homo sapiens lactotransferrin (LTF) 5.257 5.139

MAGEE1 NM_020932 Homo sapiens melanoma antigen family E, 1 (MAGEE1) 8.198 8.356

MAPK9 NM_002752 Homo sapiens mitogen-activated protein kinase 9 (MAPK9), transcript variant JNK2-a2

7.363 7.737

MDH1 NM_005917 Homo sapiens malate dehydrogenase 1, NAD (soluble) (MDH1) 9.874 9.714

MRPS25 NM_022497 Homo sapiens mitochondrial ribosomal protein S25 (MRPS25), nuclear gene encoding mitochondrial protein

12.872 12.334

NDN NM_002487 Homo sapiens necdin homolog (mouse) (NDN) 7.576 8.023

NECAP1 NM_015509 Homo sapiens NECAP endocytosis associated 1 (NECAP1) 8.014 8.037

NELL2 NM_006159 Homo sapiens NEL-like 2 (chicken) (NELL2) 11.310 12.139

NETO2 NM_018092 Homo sapiens neuropilin (NRP) and tolloid (TLL)-like 2 (NETO2) 11.500 11.076

NR4A2 NM_006186 Homo sapiens nuclear receptor subfamily 4, group A, member 2 (NR4A2), transcript variant 1

4.691 5.247

NTRK2 NM_006180 Homo sapiens neurotrophic tyrosine kinase, receptor, type 2 (NTRK2), transcript variant a

6.232 9.554

OLFM3 NM_058170 Homo sapiens olfactomedin 3 (OLFM3) 6.757 8.034

P2RX7 NM_002562 Homo sapiens purinergic receptor P2X, ligand-gated ion channel, 7 (P2RX7)

7.539 6.839

PCLO ENST00000333891 PCLO_HUMAN Isoform 3 of Q9Y6V0 - Homo sapiens (Human) [Source:Uniprot/Varsplic;Acc:Q9Y6V0-3]

7.316 7.475

PFDN4 NM_002623 Homo sapiens prefoldin subunit 4 (PFDN4) 11.683 11.489

PTMA NM_002823 Homo sapiens prothymosin, alpha (gene sequence 28) (PTMA) 14.332 14.043

PTS NM_000317 Homo sapiens 6-pyruvoyltetrahydropterin synthase (PTS) 12.661 12.535

RGMA NM_020211 Homo sapiens RGM domain family, member A (RGMA) 8.676 7.712

ROBO2 NM_002942 Homo sapiens roundabout, axon guidance receptor, homolog 2 (Dro-sophila) (ROBO2)

7.183 6.592

SDC2 NM_002998 Homo sapiens syndecan 2 (heparan sulfate proteoglycan 1, cell surface-associated, fibroglycan) (SDC2)

10.425 9.120

SEMA5A NM_003966 Homo sapiens sema domain, seven thrombospondin repeats (type 1 and type 1-like), transmembrane domain (TM) and short cytoplasmic domain, (semaphorin) 5A (SEMA5A)

6.733 8.612

SLC18A2 NM_003054 Homo sapiens solute carrier family 18 (vesicular monoamine), member 2 (SLC18A2)

5.048 5.043

SLC25A4 NM_001151 Homo sapiens solute carrier family 25 (mitochondrial carrier; adenine nucleotide translocator), member 4 (SLC25A4), nuclear gene encoding mitochondrial protein

12.088 12.004

SLITRK5 NM_015567 Homo sapiens SLIT and NTRK-like family, member 5 (SLITRK5) 5.498 4.706

SNAP91 NM_014841 Homo sapiens synaptosomal-associated protein, 91kDa homolog (mouse) (SNAP91)

7.435 7.419

SNCA NM_007308 Homo sapiens synuclein, alpha (non A4 component of amyloid precursor) (SNCA), transcript variant NACP112

9.535 9.682

SOX2 NM_003106 Homo sapiens SRY (sex determining region Y)-box 2 (SOX2) 6.698 6.537

SOX9 NM_000346 Homo sapiens SRY (sex determining region Y)-box 9 (campomelic dysplasia, autosomal sex-reversal) (SOX9)

5.939 6.388

STS-1 NM_032873 Homo sapiens Cbl-interacting protein Sts-1 (STS-1) 4.223 4.261

SYT1 NM_005639 Homo sapiens synaptotagmin I (SYT1) 10.245 11.008

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Supplementary Table 5. Expression analysis of 79 selected PD target genes (Chapter 2, Table 2) in SH-SY5Y cells not treated (noRA) and treated with RA (RA) on the 8th day of culture. 73% of the PD target genes are detected in their expression in RA treated SH-SY5Y cells as measured by microarray. Genes in italic font are not expressed by the RA treated cells (microarray expression levels below 2x background).

Gene Name

Systematic Name

Description D8 noRA

D8 RA

TH NM_199292 Homo sapiens tyrosine hydroxylase (TH), transcript variant 1 8.209 7.992

TRIM36 NM_018700 Homo sapiens tripartite motif-containing 36 (TRIM36), transcript variant 1 9.260 8.995

UCHL1 NM_004181 Homo sapiens ubiquitin carboxyl-terminal esterase L1 (ubiquitin thioles-terase) (UCHL1)

16.689 16.608

UNC13C ENST00000260323 Unc-13 homolog C (Munc13-3) (Fragment). [Source:Uniprot/SWISSPROT;Acc:Q8NB66]

4.160 4.467

VAV3 NM_006113 Homo sapiens vav 3 oncogene (VAV3), transcript variant 1 7.379 9.379

VIM NM_003380 Homo sapiens vimentin (VIM) 13.538 10.002

WWC1 NM_015238 Homo sapiens WW and C2 domain containing 1 (WWC1) 10.071 8.650

143

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CHAPTER 4

High-content cellular screening of genes dysregulated in

Parkinson’s disease identifies regulators of cell viability,

mitochondrial activity and axon growth

J.A. Korecka1, E. Blaas2, R.E. van Kesteren2, U.A. Unmehopa3, R. Balesar3, D.F. Swaab3,

A.B. Smit2, K. Bossers1, J. Verhaagen1,2

Manuscript in preparation


Amsterdam, The Netherlands2 Center for Neurogenomics and Cognitive Research, Neuroscience Campus Amsterdam, VU Univer-

sity, Boelelaan 1085, 1081HV, Amsterdam, The Netherlands3 Department of Neuropsychiatric Disorders, Netherlands Institute for

Neuroscience, An Institute of the Royal Netherlands Academy of Arts and Sciences,Meibergdreef 47, 1105BA, Amsterdam, The Netherlands

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Abstract

In this chapter high-content cellular screening (HCS) was used to function-ally test 62 genes that are dysregulated in the SN of Parkinson’s disease (PD) pa-tients. HCS was performed in SH-SY5Y cells, a well characterized dopaminergic cell line, and was designed to test the effect of siRNA mediated knockdown or lentivirus (LV)-mediated overexpression of target genes on mitochondrial activ-ity, cell viability, and neurite growth. HCS of 62 genes revealed that RGMA and PTMA knockdown increased mitochondrial activity only in cells treated with MPP(+) (which induced mitochondrial inhibition), and FOXO4 knockdown in-creased neurite outgrowth independent of MPP(+). RGMA knockdown showed an interaction effect on mitochondrial activity and cell viability when coupled with MPP(+) treatment, indicating that its signaling is linked to mitochondrial activity. Overexpression of 12 out of 14 genes had an effect on at least one of the cellular parameters investigated. The most dramatic effects on cell viability were induced by FOXO4 and HIP1R, independent of MPP(+) treatment, and AL-DH1A1 only after MPP(+) treatment. SOX2 most dramatically decreased neurite outgrowth of SH-SY5Y differentiated cells. CTDSP1, RGMA, PTMA, SLITRK5 and WWC1 induced effects on both cell survival and neurite outgrowth, suggest-ing that these genes contribute to both of these cellular parameters. Apart from gene-only overexpression effects, ALDH1A1, HIP1R and WWC1 overexpression showed clear interaction effects on cell survival and mitochondrial activation when treated with MPP(+), strongly suggesting a functional interaction between these genes and the level of mitochondrial activity and/or cellular oxidative stress. A total of 9 genes identified by this HCS may be causally or consequen-tially involved in the complex process of DAergic neuron degeneration in PD pa-tients, and are likely candidates for testing their role in vivo in the initiation of PD-like neurodegeneration in a rodent model of PD.

HIGH CON TEN T CELLU L A R SCR EEN OF SELECTED PD GENES

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Introduction

The progressive degeneration of dopaminergic (DAergic) neurons in the substantia nigra (SN) of Parkinson’s disease (PD) patients is a complex event. Al-though the exact cause of sporadic, non-inherited forms of PD is still unknown, the degenerative process may involve genetic predispositions and multiple func-tional alterations in DAergic neurons in the SN and in their cellular environment (Dauer and Przedborski, 2003; Olanow et al., 2009). Genome wide expression profiling on human post mortem brain tissue has identified numerous dysregu-lated genes in PD. Many of these genes play a role in biological processes implicat-ed in the etiology of PD, such as mitochondrial activity, synaptic activity and axo-nal transport, the ubiquitin/proteasome system, heat shock protein regulation, iron and vesicular transport, chaperone activity, oxidative stress regulation, ex-tracellular matrix signaling, and cell adhesion (reviewed in Lewis and Cookson, 2011; and Greene, 2012). At present, it is still unclear during which stage of the disease these genes and the processes they are involved in come into play. Most importantly, it is unknown which transcriptional alterations are causative and which are secondary to the disease process. Therefore, one of the primary chal-lenges in PD research is to causally link the observed alterations in gene expres-sion to the functional cellular changes that lead to PD.

High-content cellular screening (HCS) is an efficient strategy to test the function of large numbers of genes by simultaneously using cell-based quantifi-cation of multiple cellular processes. Combined with chemical exposure or gene knockdown/overexpression, HCS can provide a detailed analysis of the cellular response to environmental or genetic factors (reviewed in Jain and Heutink, 2010; Jain et al., 2012). Genome-wide HCS has previously been used to iden-tify novel genes involved in cellular rhythm amplitude regulation (Zhang et al., 2009a) and the progression of cell proliferation in human cancer cells (Moffat et al., 2006). HCS can also be efficiently employed to rapidly obtain functional insight in preselected sets of target genes derived from microarray studies. Tar-geted HCS has been used to identify genes involved in HeLa cell division (Kit-tler et al., 2004), neurite outgrowth (Moore et al., 2009; MacGillavry et al., 2009; Blackmore et al., 2010), and the neurite growth promoting properties of olfac-tory ensheathing glia cells (Roet et al, unpublished).

In a recent study we identified gene expression differences in 287 genes within a relatively spared part of the SN of PD patients (Bossers et al., 2009). In chapter 2 of this thesis, we carefully selected 79 of these genes based upon their potential role in the development and progression of PD. These genes are mainly involved in (1) cell death - a cardinal feature of PD (Damier et al., 1999; Papa-petropoulos et al., 2006; Simunovic et al., 2009), (2) axon guidance - the early loss of axon terminals in the nigrostriatal system (also known as the dying back hypothesis) is an event that has been given particular attention as an important feature of PD (Dauer and Przedborski, 2003; Lesnick et al., 2007), or (3) mito-

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chondrial function – a process also previously implicated in PD pathology (Grun-blatt et al., 2004; Hauser et al., 2005). In this chapter we describe the results of two HCS experiments performed to investigate the role of 62 of these genes in cellular viability, mitochondrial activity and neurite outgrowth. The DAergic SH-SY5Y cell line, extensively characterized in chapter 3, was used to study the ef-fect of knockdown or overexpression of these genes in the absence or presence of 1-methyl-4-phenylpyridinium (MPP(+)). MPP(+) was used to mimic the mito-chondrial dysfunction observed in DAergic neurons in PD patients (Langston et al., 1999; Nicotra and Parvez, 2002). In the first screen we investigated the effect of 62 target genes on mitochondrial activity and neurite outgrowth fol-lowing siRNA-mediated knockdown. The second screen investigated the effect of the overexpression of 14 target genes on cell viability, mitochondrial activity and neurite outgrowth.

HCS revealed that RGMA and PTMA knockdown increased mitochondrial activity, and that KLK6 knockdown decreased neurite outgrowth only when combined with MPP(+) treatment. Knock-down of FOXO4 increased neurite out-growth, independent of MPP+. Additionally, RGMA knockdown in SH-SY5Y cells decreased cellular viability in a MPP(+) treatment interaction manner. Nine genes displayed dramatic effects on cell function after LV-induced overexpres-sion. FOXO4 and HIP1R induced cell death, whereas SOX2 dramatically inhibited neurite outgrowth, independent of MPP(+) treatment. CTDSP1, RGMA, PTMA and WWC1 appeared to regulate more than one cellular process by decreasing both cell survival and neurite outgrowth. Finally, the extent of the ALDH1A1, HIP1R and WWC1 effect on cell survival and mitochondrial activity were connected with MPP(+) treatment, strongly suggesting a functional interaction between these genes and the level of mitochondrial activity and/or cellular oxidative stress. The identification of 9 genes by HCS now provides the basis to further investigate their role in vivo in the process of DAergic neuron degeneration.

Materials & Methods

Generation of Overexpression Constructs

Lentiviral plasmid production

All brain material was collected from donors whose written informed con-sent for a brain autopsy and their use of the brain tissue and clinical information for research purposes had been obtained by the Netherlands Brain Bank (NBB, Amsterdam, The Netherlands). Coding sequences for DLK1, NETO2, P2RX7 and WWC1 were obtained from a cDNA library generated from three control human SN tissue samples from the NBB (donor numbers: 96-020, 99-105 and 01-063). RNA was isolated from human SN tissue as previously described (Bossers et al., 2009) and cDNA synthesis was performed on 250ng of RNA using SuperScript


149

Reverse Transcriptase (Invitrogen. Carlsbad, CA, USA). cDNA encoding DLK1, NETO2, P2RX7 and WWC1 was amplified by PCR (Phusion DNA polymerase; Finnzymes, Thermo Scientific) using the primers shown in Table 1. PCR products were separated by agarose gel electrophoresis followed by gel extraction (Nu-cleospin Extract II kit, Macherey-Nagel, Düren, Germany).

ALDH1A1, CTDSP1, FOXO4, KLK6, PTMA, SLITRK5 and SOX2 expression clones and pDONOR plasmids encoding HIP1R, RGMA and ROBO2 were pur-chased from ImaGenes (Source BioScience, Nottingham, UK) (Table 1). Clones were inoculated overnight at 37˚C in Difco Luria-Bertani Broth, Miller (LB; Bec-ton, Dickinson and Company, Le Point de Claix, France) in the presence of the ap-propriate antibiotics, and plasmid DNA was isolated with a Nucleospin plasmid Quickpure kit (Macherey-Nagel).

The DNA coding sequences of genes not available in pDONOR vectors were amplified by PCR with gateway primers, shown in Table 1. PCR products were isolated and recombined with the pDONR221 plasmid from the Gateway Vector Conversion System (Invitrogen) using the BP Clonase II enzyme mix overnight at 25˚C and transformed into One Shot TOP10 Chemically Competent E. coli cells (Invitrogen). Colonies were inoculated and grown overnight at 37˚C in LB with 50 μg/ml kanamycin (Life Technologies, The Netherlands). The resulting plas-mid DNA was sequenced to confirm correct gene insertion.

Self-inactivating lentiviral vectors (LV) were produced as described previ-ously (Naldini et al., 1996; Dull et al., 1998; Hendriks et al., 2007). The LV-desti-nation plasmids were constructed by replacing the GFP sequence from the trans-fer vector pRRLsin-PPthCMV-GFP-WPRE with Reading Frame Cassette B of the Gateway Vector Conversion System followed by an IRES-GFP sequence (Roet et al., unpublished). pDONOR plasmids, or entry clones, were recombined overnight at 25˚C with the LV-destination plasmids using LR Clonase II (Invitrogen) accord-ing to manufacturer’s instructions. The recombination product was introduced in DH5-alpha E. coli (Invitrogen) or One Shot TOP10 Chemically Competent E. coli cells by a standard transformation procedure and grown overnight at 37˚C in LB in the presence of 50μg/ml ampicillin (Roche Diagnostics). Plasmids were isolated and correct insertion of DNA fragments was confirmed by restriction analysis.

Lentiviral vector production

Human embryonic kidney (HEK) 293T cells were plated at a density of 11.25 x 106 in a 15 cm dish in Iscove’s modified Dulbecco’s medium (IMDM; Invi-trogen) containing 10% fetal calf serum (FCS), 1% P/S and 1x Glutamax (Invitro-gen). One day after plating, each of the LV-destination vectors (25 µg) including LV-GFP as the reference, were co-transfected with the VSV-G envelope protein vector pMD.G.2 (8.75 µg) and the viral core packaging construct pCMVdeltaR8.74 (16.25 µg) into cells using polyethylenimine (Polysciences, Eppelheim, Germany). After 16h incubation at 37˚C with the transfection mix, the medium was replaced

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150

Gene name


ImaGenes plas-mid name

PCR primer forward

PCR primer reverse Length Gateway primer forward Gateway primer reverse

cDS Sequence

lengthGenes isolated from human cDNA libarary Genes isolated from human cDNA libarary

DLK1 NM_003836.4 GAGATGACCGC-GACCGAAGC

TAGAGGGGGCT-GTGGGAACG

1161 GGGGACAAGTTTGTACAAAAAAGCAG-GCTTCACC-ATGACCGCGACCGAAGCCCT

GGGGACCACTTTGTACAAGAAAGCTGGGTTC-TA-TTAGATCTCCTCGTCGCCGG

1219

NETO2 NM_018092.3 GCTACCT-CAGCCCTTCGCGA

GGCTGCGTACG-TACACACCCTAAG

1667 GGGGACAAGTTTGTACAAAAAAGCAG-GCTTCACC-ATGGCCCTGGAGCGGCTCTG

GGGGACCACTTTGTACAAGAAAGCTGGGTTC-TA-TTAGAAGTCAATGGATATGG

1645

P2RX7 NM_002562.4 CTGTGGCCCTGT-CAGGAAGAGTAG

TGCCTG-GCTTCAGTA-AGGACTCTTG

1811 GGGGACAAGTTTGTACAAAAAAGCAG-GCTTCACC-ATGCCGGCCTGCTGCAGCTG’

GGGGACCACTTTGTACAAGAAAGCTGGGTTC-TA-TCAGTAAGGACTCTTGAAGC

1855

WWC1 NM_015238.2 GGCAGCGCTT-GGGAAGATGC

CAGCCTG-GTCAGTGGAA-CAAAGG

3397 GGGGACAAGTTTGTACAAAAAAGCAG-GCTTCACC-ATGCCCCGGCCGGAGCTGCC

GGGGACCACTTTGTACAAGAAAGCTGGGTTC-TA-TTAGACGTCATCTGCAGAGA

3409

Genes isolated from ImaGenes plasmids Genes isolated from ImaGenes plasmids

ALDH1A1 NM_000689.3 IRAUp966H0146D GGGGACAAGTTTGTACAAAAAAGCAG-GCTTCACC-ATGTCATCCTCAGGCACGCC

GGGGACCACTTTGTACAAGAAAGCTGGGTTC-TA-TTATGAGTTCTTCTGAGAGA

1573

CTDSP1 NM_021198.1 IRAUp969H0356D GGGGACAAGTTTGTACAAAAAAGCAG-GCTTCACC-ATGGACAGCTCGGCCGTCAT

GGGGACCACTTTGTACAAGAAAGCTGGGTTC-TA-CTAGCTCCCTGGCCGTGGCT

853

FOXO4 NM_005938.2 IRCMp5012F074D GGGGACAAGTTTGTACAAAAAAGCAG-GCTTCACC-ATGGATCCGGGGAATGAGAA

GGGGACCACTTTGTACAAGAAAGCTGGGTTC-TA-TCAGGGATCTGGCTCAAAGT

1585

HIP1R NM_003959.1 IOH60041 Gateway entry clone

3274

KLK6 NM_001012964.1 IRATp970E0915D GGGGACAAGTTTGTACAAAAAAGCAG-GCTTCACC-ATGAAGAAGCTGATGGTGGT

GGGGACCACTTTGTACAAGAAAGCTGGGTTC-TA-TCACTTGGCCTGAATGGTTT

802

PTMA NM_002823.4 IRATp970F0295D GGGGACAAGTTTGTACAAAAAAGCAG-GCTTCACC-ATGTCAGACGCAGCCGTAGA

GGGGACCACTTTGTACAAGAAAGCTGGGTTC-TA-CTAGTCATCCTCGTCGGTCT

400

RGMA NM_020211.1 OCAAO5051G024D Entry clone

1420

ROBO2 NM_002942.3 IOH53663 Gateway Entry clone

4204

SLITRK5 NM_015567.1 IRCMp5012C112D GGGGACAAGTTTGTACAAAAAAGCAG-GCTTCACC-ATGCACACTTGCTGCCCCCC

GGGGACCACTTTGTACAAGAAAGCT-GGGTTCTA-TTAGAACTGGCTAAACGT-GG

2944

SOX2 NM_003106.2 IRAUp969A0546D GGGGACAAGTTTGTACAAAAAAGCAG-GCTTCACC-ATGTACAACATGATGGAGAC

GGGGACCACTTTGTACAAGAAAGCT-GGGTTCTA-TCACATGTGTGAGA-GGGGCA

1021

Table 1. List of Gateway expression vectors used to generate the LV vectors. Gene name and their NCBI reference number are indicated in the first two columns. When possible, ImaGenes plasmids were purchased (column 3). For four genes the specific cDNA sequence was amplified from a human SN cDNA library using forward and reverse PCR primers (PCR primer), generating amplicons ranging in size from 1100-3400 base pairs (Sequence length). Apart from a few genes already supplied in the Gateway entry clone, most genes required the introduction of Gateway specific overhangs at the 5’ and 3’ ends of the cDNA using PCR (Gateway forward and reverse primers). Resulting products varied in sizes from 400-4200 base pairs (cDS Gateway sequence). These cDNA sequences were ultimately used for ligation into the pDONOR vectors to generate an entry clone for transformation into LV-IRES GFP destination vectors.


151

Gene name


ImaGenes plas-mid name

PCR primer forward

PCR primer reverse Length Gateway primer forward Gateway primer reverse

cDS Sequence

lengthGenes isolated from human cDNA libarary Genes isolated from human cDNA libarary

DLK1 NM_003836.4 GAGATGACCGC-GACCGAAGC

TAGAGGGGGCT-GTGGGAACG

1161 GGGGACAAGTTTGTACAAAAAAGCAG-GCTTCACC-ATGACCGCGACCGAAGCCCT

GGGGACCACTTTGTACAAGAAAGCTGGGTTC-TA-TTAGATCTCCTCGTCGCCGG

1219

NETO2 NM_018092.3 GCTACCT-CAGCCCTTCGCGA

GGCTGCGTACG-TACACACCCTAAG

1667 GGGGACAAGTTTGTACAAAAAAGCAG-GCTTCACC-ATGGCCCTGGAGCGGCTCTG

GGGGACCACTTTGTACAAGAAAGCTGGGTTC-TA-TTAGAAGTCAATGGATATGG

1645

P2RX7 NM_002562.4 CTGTGGCCCTGT-CAGGAAGAGTAG

TGCCTG-GCTTCAGTA-AGGACTCTTG

1811 GGGGACAAGTTTGTACAAAAAAGCAG-GCTTCACC-ATGCCGGCCTGCTGCAGCTG’

GGGGACCACTTTGTACAAGAAAGCTGGGTTC-TA-TCAGTAAGGACTCTTGAAGC

1855

WWC1 NM_015238.2 GGCAGCGCTT-GGGAAGATGC

CAGCCTG-GTCAGTGGAA-CAAAGG

3397 GGGGACAAGTTTGTACAAAAAAGCAG-GCTTCACC-ATGCCCCGGCCGGAGCTGCC

GGGGACCACTTTGTACAAGAAAGCTGGGTTC-TA-TTAGACGTCATCTGCAGAGA

3409

Genes isolated from ImaGenes plasmids Genes isolated from ImaGenes plasmids

ALDH1A1 NM_000689.3 IRAUp966H0146D GGGGACAAGTTTGTACAAAAAAGCAG-GCTTCACC-ATGTCATCCTCAGGCACGCC

GGGGACCACTTTGTACAAGAAAGCTGGGTTC-TA-TTATGAGTTCTTCTGAGAGA

1573

CTDSP1 NM_021198.1 IRAUp969H0356D GGGGACAAGTTTGTACAAAAAAGCAG-GCTTCACC-ATGGACAGCTCGGCCGTCAT

GGGGACCACTTTGTACAAGAAAGCTGGGTTC-TA-CTAGCTCCCTGGCCGTGGCT

853

FOXO4 NM_005938.2 IRCMp5012F074D GGGGACAAGTTTGTACAAAAAAGCAG-GCTTCACC-ATGGATCCGGGGAATGAGAA

GGGGACCACTTTGTACAAGAAAGCTGGGTTC-TA-TCAGGGATCTGGCTCAAAGT

1585

HIP1R NM_003959.1 IOH60041 Gateway entry clone

3274

KLK6 NM_001012964.1 IRATp970E0915D GGGGACAAGTTTGTACAAAAAAGCAG-GCTTCACC-ATGAAGAAGCTGATGGTGGT

GGGGACCACTTTGTACAAGAAAGCTGGGTTC-TA-TCACTTGGCCTGAATGGTTT

802

PTMA NM_002823.4 IRATp970F0295D GGGGACAAGTTTGTACAAAAAAGCAG-GCTTCACC-ATGTCAGACGCAGCCGTAGA

GGGGACCACTTTGTACAAGAAAGCTGGGTTC-TA-CTAGTCATCCTCGTCGGTCT

400

RGMA NM_020211.1 OCAAO5051G024D Entry clone

1420

ROBO2 NM_002942.3 IOH53663 Gateway Entry clone

4204

SLITRK5 NM_015567.1 IRCMp5012C112D GGGGACAAGTTTGTACAAAAAAGCAG-GCTTCACC-ATGCACACTTGCTGCCCCCC

GGGGACCACTTTGTACAAGAAAGCT-GGGTTCTA-TTAGAACTGGCTAAACGT-GG

2944

SOX2 NM_003106.2 IRAUp969A0546D GGGGACAAGTTTGTACAAAAAAGCAG-GCTTCACC-ATGTACAACATGATGGAGAC

GGGGACCACTTTGTACAAGAAAGCT-GGGTTCTA-TCACATGTGTGAGA-GGGGCA

1021

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with IMDM medium containing 2% FCS, 1% PS and 1x Glutamax. The medium was harvested 24h later, passed through a 0.20 µm filter and was ultracentri-fuged for 2.5h at 20.000rpm in a SW-28 rotor (Beckman Coulter BV, The Neth-erlands). The viral pellet was resuspended in phosphate buffered saline (PBS, Sigma) pH 7.4, aliquoted and stored at -80˚C. To determine the number of trans-ducing particles in the LV stocks, HEK 293T cells were transduced and after 48h the number of GFP-expressing cells was counted. LV stock titers were expressed as transducing units (TU) per ml.

SH-SY5Y cell culture and MPP(+) treatment

Human SH-SY5Y neuroblastoma cells were obtained from The European Collection of Cell Culture (ECACC, 94030304, Sigma-Aldrich). Cells were cultured at 37°C in 5% CO2 in Dulbecco’s Modified Eagle’s Medium (DMEM)/F-12 without L-glutamine (reduced serum medium1:1, Invitrogen) supplemented with 0.5% FCS, 100U/ml penicillin (Sigma) and 0.1mg/ml streptomycin (Sigma) in 96-well plates coated with 0.1mg/ml poly-L-lysine (PLL, Sigma) and 1mg/ml growth fac-tor reduced Matrigel Matrix without phenol red (BD Biosciences). 15,000 cells were plated per well. On day 1, 3 and 6 medium was refreshed and supplemented with 1µM all-trans-retinoic acid (Sigma, RA). For cells that were treated with a low and high dose of MPP(+), 0.01mM and 0.5mM were added to the culture me-dium on day 3 and 6. On day 8 the culture was terminated.

siRNA knockdown

For gene knockdown, cells were transfected one day after plating with siG-ENOME SMART pools for 62 human target gene sequences (Dharmacon) consist-ing of 4 siRNA duplexes (see Supplementary Table 1 for all siRNA sequences). Transfections were performed using DharmaFECT 3 according to the manufac-turer’s protocol. In short, the transfection mix was prepared by first diluting siRNA (1:1) and DharmaFECT 3(1:10) separately in serum-free medium, and then mixing them together, followed by incubation for 20 min at room tempera-ture (RT). Finally, pre-warmed (37°C) medium containing 0.5% FCS was added to reach a final siRNA concentration of 100nM. The transfection mix was then transferred to the cells. After 4h the incubation medium was refreshed as de-scribed above. siControl or siGLO were used as control conditions. The screen required a total of 24 assay plates, and MPP(+) conditions were always the same within one plate. To minimize between-plate and within-plate effects, all data were normalized against the plate average.


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LV-mediated overexpression

LV transduction of SH-SY5Y cells was performed one day after plat-ing. The viral vectors were diluted to a multiplicity of infection (MOI) of 3 in medium/0.5%FCS/1µM RA. Medium was refreshed on culture day 3. LV-GFP was used as the control condition.

High Content Cellomics screen

Immunocytochemistry

SH-SY5Y cells were transfected with siRNA or transduced with LV overex-pression vectors and cultures in the presence or absence of MPP(+) as decribed above. On culture day 8 cells were fixed in 4% paraformaldehyde pH 7.4 (PFA, Sigma) and 1% sucrose (Sigma) for 30min, followed by 2 washes with 1X PBS pH 7.4 and 30min blocking at RT in 1X PBS/0.5% Triton X-100 (Sigma) and 2% FCS. Fixed cells were incubated with anti-β-III-tubulin mouse antibody (1:600, Co-vance) in 1X PBS/2% FCS/0.25% gelatin (Merk)/0.5% Triton X-100 (Sigma) at 4°C overnight. Next, cells were incubated in anti-mouse Cy-5 antibody (1:800, Invit-rogen) in 1X PBS /2% FCS for 2h at RT. Finally, cells were incubated with 100nM MitoTracker (Invitrogen) diluted in 1X PBS for 20min at RT and with Hoechst at 1:20000 dilution in 1X PBS for 20min.

Data acquisition and statistical analysis

Mitochondrial activity and neurite outgrowth were measured on a Cello-mics Arrayscan VTI HCS Reader (Thermo Fisher Scientific, Pittsburgh, PA, USA). A maximum of 40 fields per well were imaged (20x magnification), starting from the center of the well. The Neuronal Profiling BioApplication (Cellomics software version 3.5) was used on the β-III tubulin images to trace neurites and the Cellu-lar Compartmental Analysis BioApplication (Cellomics software version 3.0) was used to measure the Mito Tracker images to measure mitochondrial activity. The neurite parameters that were used in this study were mean neurite total length and mean neurite count per cell. Mitochondrial activity was calculated by aver-aging the normalized MitoTracker mean cytoplasmic total intensity, mean cyto-plasmic average intensity and mean cytoplasmic spot total intensity.

For the siRNA knockdown screen, each assay plate contained 3 (proof-of-principle screen) or 5 (real screen) replicate wells per siRNA and the same num-ber of negative control (siControl or siGlo) wells. Normalization was performed against the plate average, and siRNA effects were considered significant when the mean normalized effect of siRNA treatment deviated more than two standard deviations from the plate average. For siRGMA validation, 10 wells per treatment condition were used. Two way ANOVA was used to detect siRGMA*MPP(+) inter-action effects, followed by student T-test analysis to find the significant differ-ences between each condition.

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The LV mediated overexpression experiments were normalized to the plate average and scaled to LV-GFP treated cells. Only the transduced (GFP positive) cells, as identified by intensity cut off at 2x background signal in non-transduced cell, were analyzied. Overexpression experiments were repeated three times with different cell batches and each experiment included 8 wells. Data was ana-lyzed using two way nested ANOVA where the 8 replicate wells were nested in the three independent cultures. The results from the ANOVA were divided into two categories: 1) conditions with significant ‘gene overexpression*MPP(+) treatment’ interaction effects and 2) significant gene overexpression effects in the absence of an interaction with MPP(+). When a significant gene overexpres-sion effect was detected, one way nested ANOVA was performed to compare all gene overexpression treatment conditions to their respective LV-GFP control conditions. All p-values <0.05 were considered significant.

CellTiter Blue Cell Viability assay

Cells were cultured in black 96 well plates with five wells per condition (Greiner Bio-one, The Netherlands). Cell Titer Blue Cell Viability Assay was per-formed according to the manufacturer’s instructions (Promega, Madison, WI, USA). Briefly, on day 8, 100µl of medium was removed from each well and 20µl of Cell Titer Blue reagent (Promega) was added. Cells were incubated for 2h at 37°C and whole-well fluorescence intensity was measured at 560/590nm using a Varioscan Flash scanner and Skan It RE Varioskan Flash software (version 2.4.3, Thermo Scientific). For overexpression screen the assay was repeated 2 times on independent cultures. As with the HC screen, experiments were normalized to the plate average and scaled to LV-GFP treated cells. Statistical analysis was performed using two way nested ANOVA with a search for 1) conditions with significant ‘gene overexpression*MPP(+) treatment’ interaction effects and 2) significant ‘gene overexpression effects’ in the absence of an interaction with MPP(+). When a significant gene overexpression effect was detected, one way nested ANOVA was performed to compare each gene’s overexpression treatment conditions to their retrospective LV-GFP control conditions. A p-value <0.05 was considered significant.

Knock down and overexpression validation

mRNA isolation and qPCR

Cell culture, siRNA-mediated gene knockdown and LV-mediated gene over-expression were performed as described above. Cells were harvested for RNA isolation either 48h after siRNA transfection or on culture day 3 and 8 for LV transduction. Cells were lysed by replacing medium with 50µl of Trizol Reagent (Invitrogen) to each well, followed by incubation on ice for 10min. RNA was puri-fied by two rounds of chloroform extraction. Phase separation was achieved us-


155

ing Phase Lock Gel (5 Prime, Hamburg, Germany). The final aqueous phase was diluted with an equal volume of 70% ethanol and the RNA was isolated using RNeasy Micro columns (Qiagen) according to the manufacturer’s instructions. RNA quantity and purity were determined on the NanoDrop ND-1000 spectro-photometer (Nanodrop Technologies). cDNA synthesis was performed on 300ng of RNA using QuantiTect Reverse Transcription Kit (Qiagen). Each qPCR reac-tion was performed with 2.3 ng of cDNA, 3pmol of forward and reverse primer (Supplementary Table 2) and 10µl 1x SYBR green ready reaction mix (Applied Biosystems, Foster City, CA, USA). Reactions were carried out on the ABI 7300 sequence system (Applied Biosystems). Each primer pair was checked for primer dimers and for amplification of a single product by analyzing dissociation curves. No primer dimers were observed, while each primer pair yielded only one prod-uct. Primer efficiencies were determined for each primer pair. For normalization, four reference genes were used: NDUFV2, NY-SAR-48, PPP1R8 and UQCRFS1. These genes were previously identified to be the least regulated genes in SH-SY5Y cells (chapter 3). Normalization was performed by geometric averaging of reference gene expression using GeNorm software (Vandesompele et al., 2002).

Immunocytochemical detection of overexpressed proteins

Cells were cultured in 24-well plates on glass cover slips. Cells were trans-duced with lentiviral vectors encoding for, ALDH1A1, CTDPS1, DLK1, FOXO4, PTMA, RGMA, SOX2 and GFP as control. Cell culture, fixation and blocking were performed as described above. The following primary antibodies were applied in PBS/2% FCS/0.25% gelatin/0.5% Triton X-100 and incubated overnight at 4°C: anti-ALDH1A1 (1:100, Abcam, ab24343, Cambridge, UK), anti-CTDSP1 (1:100, Sigma-Aldrich, SAB1300998), anti-DLK1 (1:50, Proteintech group, 10636-1-AP, Manchester, UK), anti-FOXO4 (1:500, Cell signaling tech., 9472, Boston MA, USA), anti-PTMA (1:100, Santa Cruz Biotech, N-18, sc18205, Santa Cruz, CA, USA), anti-RGMA (1:100, Santa Cruz, D-16, sc46482), and anti-SOX2 (1:100, Millipore, AB5603, MA, USA). Depending on the host in which the primary antibodies were raised, cells were incubated with either anti-mouse, anti-rabbit, or anti-goat an-tibodies conjugated to Alexa-594 (Invitrogen), at 1:800 dilution in PBS /2% FCS for 2h at RT, followed by 20min nuclear staining with Hoechst 1:20,000 in 1XPBS. Cells were mounted on glass slides in Mowiol solution (0.1 M Tris pH 8.5, 25% glycerol, 10% w/v Mowiol 4-88) and analyzed with a fluorescence Axioplan mi-croscope (Zeiss, Sliedrecht, the Netherlands).

Protein isolation and Western blot analysis

Cells were cultured in 24-well plates and transfected with DJ1 or UCHL1 siRNA or transduced with LV- ALDH1A1, CTDSP1, FOXO4, RGMA and SOX2 and GFP as a reference (PTMA antibody (Santa Cruz Biotech, N-18, sc18205) and DLK1 antibody (Proteintech group, 10636-1-AP) did not detect any bands on the blot). On day 8, cells were incubated on ice for 10 min in 70µl RIPA buffer (25mM Tris-HCl pH 7.4 (Sigma), 150mM NaCl (Sigma), 1% NP40 (AppliChemicals, Darm-

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stadt, Germany), 1% sodium deoxycholate (Sigma), 0.1% SDS and 1X Complete Protease Inhibitor (Roche)). The cell lysate was collected and sonicated and its protein concentration determined using the bicinchoninic acid protein assay kit (Pierce, Thermo Scientific). For western blot analysis, each sample was heated in 5X loading buffer containing 10% sodium dodecyl sulphate (SDS, MP Biomedi-cals) and 5% ß-mercaptoethanol (Sigma) at 95°C for 5min and loaded on an 8% polyacrylamine-SDS gel. Gel electrophoresis was performed using the BioRad Mini-PROTEAN 3 gel electrophoresis system (Bio-Rad Laboratories, Hercu-les, CA, USA). Proteins were then transferred to nitrocellulose membranes and blocked in block mix (0.25% gelatin/1XTBS/0.5% Triton X-100) for 10min at RT. Blots were incubated with antibodies against ALDH1A1 (1:100, Abcam), CTDSP1 (1:200, Sigma), FOXO4 (1:1000, Cell Signaling Tech.), phosphorylated FOXO4 (1:1000, Cell Signaling Tech., 9471), RGMA (1:500, Santa Cruz), SOX2 (1:500, Mil-lipore), DJ1 (1:1000, Novus Biologicals, NB300-270), UCHL1 (1:10,000 Novus Bi-ologicals) and ß-actin (1:1000, Sigma-Aldrich, A5316) at 4°C overnight in block mix. The primary antibodies were detected with anti-rabbit or anti-goat -Cy5 (1:800, Jackson’s Lab) and anti-mouse IR-dye 800 conjugated antibodies (1:2000, Thermo Scientific). Blots were scanned using the Odyssey Infrared Imager and Odyssey 2.1 scanning software (LI-COR biosciences).

Results

High-content assay development

SH-SH5Y cells provide a good in vitro model to study gene-toxin inter-actions in the context of PD (see Chapter 3). Here we utilized SH-SY5Y cells in an HCS approach. We first performed a proof-of-principle screen in which we knocked down the expression of four known PD genes: DJ1, Parkin, PINK1 and UCHL1 and we subsequently cultured cells in the absence or presence of 0.01mM MPP(+). Cells were stained with Hoechst, MitoTracker and anti-β-III-tubulin, and cytoplasmic MitoTracker intensity and neurite length were measured using au-tomated microscopy (Figure 1A). After normalization of all assay parameters to the siControl/no-MPP(+) condition, 20 relevant parameters were selected. Unsu-pervised cluster analysis of the normalized fold-change values revealed a good separation based on the MPP(+) treatment condition as well as a near perfect clustering of sample replicates (Figure 1B). Moreover, all assay parameters per-fectly clustered together in mitochondrial activity parameters, neurite length parameters and neurite branch point parameters. As expected, the most robust changes induced by knockdown of these known PD genes were observed for mitochondrial activity. To increase parameter robustness, we created one mi-tochondrial activity parameter by averaging the normalized MitoTracker mean cytoplasmic total intensity, mean cytoplasmic average intensity and mean cyto-plasmic spot total intensity. Using this combined mitochondrial activity param-


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Hoechst MitoTracker Beta-Tubulin Overlay

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Tubulin Neurite Total CountMitoTracker Cytoplasmic Spot Average IntensityMitoTracker Cytoplasmic Spot Total AreaMitoTracker Cytoplasmic Spot Average AreaMitoTracker Cytoplasmic Average IntensityMitoTracker Cytoplasmic Spot Total IntensityMitoTracker Cytoplasmic Total IntensityTubulin Cell Body Average IntensityTubulin Cell Body Total IntensityMitoTracker Cytoplasmic Spot CountTubulin Neurite Maximum Length With BranchesTubulin Neurite Average LengthTubulin Neurite Maximum Length Without BranchesTubulin Neurite Total AreaTubulin Neurite Total LengthTubulin Branch Point Average Distance From Cell BodyTubulin Branch Point Count Per Neurite LengthTubulin Branch Point Average CountTubulin Branch Point Total CountTubulin Valid Neuron Count

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Figure 1. Development of a high-content assay to study gene-MPP(+) interactions. A. Cellomics-obtained images (upper panels) of SH-SY5Y cells stained with Hoechst, MitoTracker and β-III-tubulin, and image overlays (bottom panels) after automated detection of nuclei, cytoplasmic MitoTracker spots and neurites. B. Heatmap showing the fold changes in 20 high-content assay

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eter and the DJ1 knockdown condition as a positive control, the screen had an F’-factor of 0.44, indicating good assay performance.

To further test if our assay was able to detect significant gene-MPP(+) in-teraction effects, we selected two genes with the largest (DJ1) and smallest (UCHL1) effect on mitochondrial activity. Two way ANOVA revealed a significant gene-MPP(+) interaction (F1,8 = 168, p< 0.0001 for DJ1; F1,68 = 58.7, p = 0.0001 for UCHL1). In both cases, gene knockdown or MPP(+) treatment by itself sig-nificantly increased mitochondrial activity, whereas combined gene knockdown and MPP(+) treatment significantly reduced mitochondrial activity (Figure 1C). Western blotting confirmed a significant knockdown of DJ1 and UCHL1 protein levels, to 42% and 46% respectively of the control levels (Figure 1D). Taken to-gether, the proof-of-principle screening results indicate that we have a robust and reliable assay to detect interaction effects between genes and MPP(+) treat-ment in cultured SH-SY5Y cells.

High-content RNA interference screen of 62 potential PD genes

We then tested the effect of siRNA-mediated knockdown of 62 target genes in the absence of MPP(+), or in the presence of 0.01mM or 0.5mM MPP(+). We fo-cused on three assay parameters: mitochondrial activity (as defined in the previ-ous section), total neurite length, and total neurite count. Changes in any of these parameters were considered significant if they deviated more than two standard deviations from the plate average (Figure 2A). Importantly, none of the negative controls that were included on each assay plate produced effects that deviated more than one standard deviation from the plate average. Knockdown of two genes (PTMA and RGMA), resulted in an increase in mitochondrial activity only in the presence of MPP(+): knockdown of RGMA increased mitochondrial activ-ity by 40% in the presence of 0.01mM MPP(+), whereas knockdown of PTMA in-creased mitochondrial activity by 38% in the presence of 0.5mM MPP(+). Knock-down of KLK6 reduced neurite total length by 19% in the presence of 0.01mM

parameters after knockdown of 4 PD genes (DJ1, Parkin, PINK1 and UCHL1) and in the absence or presence of 0.01mM MPP(+). siControl was used as a negative control. Each condition was tested in triplicate, and both samples and parameters were clustered in an unsupervised manner using covariance as the clustering metric. Note that samples are separated according to conditions, and that sample replicates and related assay parameters tend to cluster together. MitoTracker intensity parameters are indicated in red, neurite length parameters in green, neurite branch-ing parameters in blue, and other (individual) parameters in black. C. DJ1 (as an example of a large effect gene) and UCHL1 (as an example of a small effect gene) both show a significant knockdown/MPP(+) interaction: knockdown or MPP(+) treatment alone both significantly increased mitochondrial activity, whereas combined knockdown and MPP(+) treatment in both cases significantly decreased mitochondrial activity. D. Western blotting confirmed a significant knockdown of both DJ1 and UCHL1 protein levels in siRNA treated cells (* p< 0.05; ** p< 0.01).


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siAAK1 siAGTR1

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siEHBP1 siEN1

siFOXA1 siFOXO4

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siHPRT1 siKCNJ6 siKIFAP3

siKLK6 siLASS6 siLRDD

siLTF siMAGEE1

siMAPK9 siMDH1

siMRPS25 siNECAP1

siNELL2 siNETO2 siNURR1 siP2RX7 siPFDN4 siPITX3

siPLEKHE1 siPTMA siRGMA

siROBO2 siSDC2

siSEMA5A siSLC25A4 siSLITRK5 siSNAP91

siSNCA siSOX2 siSTS1

siTGIF1 siTH

siTRIM36 siVAV3

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siEHBP1 siEN1

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siLTF siMAGEE1

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siROBO2 siSDC2



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siEHBP1 siEN1

siFOXA1 siFOXO4

siFST siGBP1

siHIP1R siHN1

siHPRT1 siKCNJ6 siKIFAP3


siLTF siMAGEE1

siMAPK9 siMDH1

siMRPS25 siNECAP1



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Figure 2. High-content RNA interference screen of 62 potential PD genes. A. Combined results of all 62 genes showing effects on mitochondrial activity (upper panel), neurite total length (middle panel) and neurite count (bottom panel) under no MPP(+) conditions (black bars), 0.01mM MPP(+) conditions (light grey bares), or 0.5mM MPP(+) conditions (dark grey bars). All data points are normalized to the corresponding plate average (red dashed line). Significant effects (deviating >2xSD from the plate average) are indicated with *. B. Cellomics obtained im-ages of MitoTracker intensity in SH-SY5Y cells showing an independent validation of the effects of RGMA knockdown on the MPP(+)-induced increase in mitochondrial activity. C. Quantifica-

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MPP(+). Notably, this reduction in neurite length was paralleled by a similar, near-significant, decrease in neurite count and increase in mitochondrial activ-ity. Finally, knockdown of FOXO4 increased neurite total length by 11-16% and neurite count by 22-24%, both by itself, and in combination with both MPP(+) concentrations.

To validate our screening results, we repeated the assay for RGMA using 10 independent assay wells. qPCR confirmed a 70% reduction in RGMA mRNA lev-els 48 hours after transfection. MitoTracker staining clearly showed an increase in mitochondrial activity in RGMA knockdown cells in the presence of 0.01mM MPP(+) relative to RGMA knockdown alone (Figure 2B). Two way ANOVA re-vealed a significant interaction effect between knockdown and MPP(+) treat-ment on mitochondrial activity (F1,36 = 4.7, p = 0.037): 0.01mM MPP(+) increased mitochondrial activity in control cells by 23%, whereas the increase in RGMA knockdown cells was significantly larger (57%, p = 0.02; Figure 2C). We also measured cell viability in RGMA knockdown cells and control cells in response to different concentrations of MPP(+) using a cell titer blue assay. Two way ANOVA again revealed a significant interaction between knockdown and MPP(+) treat-ment (F3,31 = 6.6, p = 0.001): cells showed a stronger MPP(+)-dependent decrease in cell viability when RGMA was knocked down compared to control cells (Fig-ure 2D).

HCS of LV-mediated overexpression

Gene selection for LV-mediated overexpression

We selected 14 target genes for overexpression analysis to further inves-tigate their function in the PD-related cellular model. These included 7 genes identified by siRNA HCS knockdown screen, 4 of which modulated mitochondrial activity and neurite outgrowth (RGMA, PTMA, KLK6 and FOXO4) and 3 showed a trend towards such modulation (CTDSP1, WWC1 and P2RX7). Additionally, we selected 7 other genes for overexpression studies based on their role in specific cellular processes relevant to PD pathology (chapter 2). Table 2 lists all 14 genes and highlights their known function(s).

Validation of LV-mediated overexpression

LV-mediated transgene expression was investigated at the mRNA and pro-tein level following transduction of SH-SY5Y cells with individual LV vectors. An increase in gene specific mRNA expression in transduced SH-SY5Y cells ranging

tion of independent validation data showing a significant increase in mitochondrial activity in MPP(+) treated RGMA knockdown cells compared with MPP(+) treated control cells (n = 10; p = 0.02). D. SH-SH5Y cells show an MPP(+) dependent reduction in cell viability, and this reduction in cell viability as a result of MPP(+) treatment is significantly stronger in RGMA knockdown cells compared with control cells (* p< 0.05; ** p< 0.01).


161

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CH A PTER 4

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from around 4 to 5,000- fold compared to LV-GFP transduced cells was demon-strated by qPCR (Table 3). For PTMA the degree of overexpression was relatively modest, which can be explained by the already high expression levels in LV-GFP transduced SH-SY5Y cells (CT value of 17). For two genes, FOXO4 and HIP1R, LV-directed mRNA expression had decreased approximately 25-50 fold by day 8. This can be explained by the reduction in the number of cells overexpressing these genes at this time in culture (Figure 4A).

To demonstrate target gene overexpression at the protein level, we used Western blot analysis and/or immunocytochemistry (Figures 3A and B). West-ern blot analysis of whole cell lysates of SH-SY5Y cells overexpressing ALDH1A1, CTDSP1, FOXO4, RGMA and SOX2 confirmed elevated protein expression levels compared with LV-GFP transduced cells (Figure 3A). Protein levels were gener-ally higher on day 8 in culture than on day 3, except for a small decrease in SOX2 and a large decrease in FOXO4 transduced cells. On day 8 in culture, FOXO4 pro-tein bands were almost undetectable, corresponding to the decrease in mRNA expression levels (Table 3). Such a dramatic decrease of FOXO4 protein level can be explained by a significant effect of FOXO4 on cell survival: only 6% of FOXO4 positive cells survived after 8 days in culture (Figure 3A). FOXO4 phosphoryla-tion is required for translocation to the nucleus, leading to transcriptional chang-es in the cell (van der Heide et al., 2004). We detected phosphorylated FOXO4

Gene name Expression

Day 3 Day 8

ALDH1A1 4974.8 3237.9

CTDSP1 236.7 90.2

DLK1 26.2 79.8

FOXO4 329.0 21.4

HIP1R 1056.9 20.3

KLK6 2175.4 1979.8

NETO2 21.1 5.0

P2RX7 223.1 47.8

PTMA 5.6 4.1

RGMA 865.8 1201.5

ROBO2 31.0 27.2

SLITRK5 1689.0 731.5

SOX2 906.2 775.6

WWC1 440.0 288.9

Table 3. mRNA detection of LV-mediated overexpression of 14 target genes in SH-SY5Y cells as measured by qPCR. RNA was isolated from cells transduced with LV-GFP or cells transduced with a LV-vector encoding the target gene. Samples were collected on culture day 3 and 8. Relative expression values from culture day 3 were normalized to the mRNA expression levels of day 3 LV-GFP cells, and from culture day 8 to day 8 LV-GFP cells.


163

Figure 3. LV-mediated protein overexpression of 7 target genes in SH-SY5Y cells as measured by Western blotting and immunocytochemistry. A. Western blot analysis of the whole SH-SY5Y cell lysates transduced with LV-vectors for ALDH1A1, CTDSP1, FOXO4, RGMA and SOX2. Cell lysates were derived from cells cultured for 3 and 8 days. Human embryonic kidney 293T cells were trans-fected with the same LV plasmids used for LV production, lysed after 3 days in culture and used as positive control for protein detection. LV-GFP transduced SH-SY5Y cells were used as negative controls. β-actin was used as loading control. B. Immunocytochemical staining of SH-SY5Y cells transduced with LV vectors driving protein expression of: ALDH1A1, CTDSP1, DLK1, FOXO4, PTMA, RGMA and SOX2. All transduced cells (Green, as determined by GFP expression driven by the IRES promoter) exhibited a positive immunoreactivity for the encoded transgene (red). As control LV-CMV-GFP transduced cells (lower panel) were stained with specific antibodies directed against the protein of interest. Blue: Hoechst staining. Scale bar represents 0.1 mm. Abbreviations: D3, day 3; D8,day 8; D3 LV- day 3 LV transduced, D8 LV- day 8 LV transduced, LV-Gene- target gene transduced cells, LV-GFP- GFP transduced cells, t293T- transfected HEK 293T cells, 293T- non-transfected HEK 293T cells, FOXO4p- phosphorylated FOXO4.

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expression in SH-SY5Y cell lysis (Figure 3A), indicating that this transcription factor is functionally active after LV-mediated overexpression.

Immunocytochemical analysis of ALDH1A1, CTDSP1, DLK1, FOXO4, PTMA, RGMA, SOX2 protein expression revealed that the GFP-positive cells transduced with LV-gene-IRES-GFP viral vectors were indeed expressing the encoded trans-gene (Figure 3B). Furthermore, the subcellular localization of the proteins cor-responded to their known function: the transcription factors FOXO4, SOX2 and transcriptional regulators CTDSP1 and PTMA all showed nuclear localization, whereas ALHD1A1, DLK1 and RGMA were localized in the cytoplasm. RGMA also displayed punctate expression in/on the cell bodies (Figure 3B). LV-GFP trans-duced control cells did not express ALDH1A1, CTDSP1, DLK1, FOXO4 and SOX2 at detectable levels, whereas relatively low levels of endogenous expression of RGMA and PTMA were observed (Figure 3B).

Overexpression of 10 target genes affected cellular viability and/or neurite outgrowth in SH-SY5Y cells

In addition to measuring mitochondrial activity, neurite length and neurite count, independent cell titer blue assays were performed to measure the effect of gene overexpression on cell viability (Figure 4). Similar to the knockdown screen, LV-mediated overexpression was combined with MPP(+) induced mito-chondrial inhibition, using a low dose MPP(+) (0.01 mM) treatment, which by it-self increases mitochondrial activity, and a high dose of MPP(+) (0.5 mM), which by itself causes a strong reduction in mitochondrial activity (chapter 3).

We considered two categories of gene overexpression effects. Category 1 contains the “gene-only overexpression effect”, for which the observed pheno-type is not connected to the MPP(+)-induced mitochondrial dysfunction. The two way nested ANOVA for these genes resulted in a significant “gene” term, but the “gene*MPP(+)” term is not significant. It should be noted that the “gene-only” ef-fect can also be observed in MPP(+) treated cells, but not in untreated cells. This merely signifies that an additional stressor (in this case mitochondrial dysfunc-tion) is needed to sensitize cells to the gene effect; it does not imply that MPP(+)-induced mitochondrial dysfunction and the gene effect interact biologically. Category 2 contains the “gene overexpression and MPP(+) treatment interaction effects”, where the combination of gene overexpression and MPP(+) treatment resulted in a different effect size than the combined effects of the treatment-only and gene only conditions. The two way nested ANOVA for these genes resulted in a significant “gene*MPP(+)” term. Here, the downstream effects of MPP(+)-in-duced mitochondrial dysfunction and gene overexpression converge in the same biological endpoint.


165

Overexpression of 9 target genes resulted in a decline of cellular viability

Gene-only overexpression effects

Three genes (ALDH1A1, PTMA and FOXO4) have previously been shown to play a role in cell death signaling (Chapter 2; Table 2). FOXO4 and PTMA overex-pression decreased cellular viability by ~35% and ~45% respectively, indepen-dent of MPP(+) treatment (Figure 4A). FOXO4 overexpression induces cell death very early after transduction, with only around 6% of FOXO4 positive cells being present on culture day 8 (data not shown). The 63% of cells that were left by day 6 were mostly FOXO4 negative. Cells overexpressing FOXO4 treated with 0.5mM MPP(+) showed a trend towards a significant decrease (p=0.085). Similarly, even though it has not been indicated by IPA to play a role in cell death pathway, CTD-SP1 decreased the number of viable cells by 53%, independent of MPP(+) treat-ment.

Overexpression of ALDH1A1, NETO2, ROBO2 and SLITRK5 only affected cellular viability when combined with MPP(+) treatment. NETO2 and ROBO2 de-creased cellular viability only when cells were subjected to treatment with low (0.01mM) and high dose (0.5mM) MPP(+) treatment, whereas ALDH1A1 and SLITRK5 overexpressing cells displayed decreased viability only when treated with a high dose of 0.5mM MPP(+).

Gene overexpression and MPP(+) treatment interaction effects

HIP1R and WWC1, not indicated in the IPA cell death pathways, induced cell loss independent of and in combination with MPP(+) treatment (Figure 4A). Over-expression of HIP1R induced the most dramatic decrease in cell viability: 97% of the cells had died after 8 days in culture. Two way nested ANOVA identified that HIP1R-induced alterations in cell viability interacted with MPP(+)-induced cell viability changes (F2,6 = 6.49, p = 0.032, Figure 4E). WWC1 overexpression reduced cell viability by 40% and also showed an interaction effect with MPP(+) treatment (F2,6 = 8.94, p = 0.016, Figure 4F): WWC1 overexpression induced less cell death when combined with 0.01mM MPP(+) treatment.

Overexpression of 6 target genes resulted in an increased mitochondrial activity


In addition to dramatically reducing cell viability, overexpression of CTD-SP1 and PTMA increased mitochondrial activity in surviving cells (Figure 4B), both in the absence and presence of MPP(+) treatment. Although HIP1R also ap-pears to dramatically increase mitochondrial activity, the number of surviving cells (3%) was not sufficient to reliably measure mitochondrial activity. Over-

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Figure 4. Functional effects of LV-mediated overexpression of 14 target genes in SH-SY5Y cells. The functional roles of each target gene were determined by analyzing their effect on four cellular processes: cellular viability (A), mitochondrial activity (B), neurite length (C) and neurite count (D). Cells were cultured in three different conditions: overexpression only (black bars),


167

expression of SLITRK5, which also decreased cell viability, also increased mito-chondrial activity only in combination with low dose MPP(+) treatment.

SOX2 and DLK1 were the only genes which increased mitochondrial activ-ity without decreasing cellular viability. For SOX2 this effect was only observed in gene-only overexpression, whereas DLK1 only induced mitochondrial activity when cells were treated with a low dose MPP(+).

Gene overexpression and MPP(+) treatment interaction effects

ALDH1A1 overexpression increased mitochondrial activity only when combined with high dose MPP(+) treatment. Additionally, this effect was identi-fied by two way nested ANOVA to be due to the interaction between ALDH1A1 overexpression and MPP(+) treatment (F2,12 = 4.06, p = 0.045, Figure 4G). Inter-estingly, only in this treatment condition, ALDH1A1 overexpressing cells show a significant decrease of cellular viability when compared to control cells.

Neurite length and neurite count are both affected after overexpression of 9 target genes


Overexpression of DLK1, SLITRK5, SOX2 and WWC1 decreased both total neurite length and neurite count in SH-SY5Y cells when compared to GFP trans-duced cells (Figure 4C and D). Out of these 4 genes, SOX2 induced the most dra-matic reduction of neurite length and count (an approximate decrease of 60% for total neurite length and of 55% for neurite count) also when treated with MPP(+). DLK1 overexpression on its own decreased neurite length and count by about 15%, but this effect was absent when cells were treated with MPP(+). SLITRK5 overexpression decreased neurite length by 11% only in 0.01mM MPP(+) treated cells and neurite count by 15% in 0.01mM and 0.5mM MPP(+)

0.01mM MPP(+) treatment (light gray bars) and 0.5mM MPP(+) treatment (dark gray bars). All measurements were normalized to LV-GFP transduced SH-SY5Y cells under the same treatment conditions (red dotted line). In case of HIP1R and FOXO4 overexpression, the mitochondrial activ-ity, neurite length and neurite count parameters were measured in only a very small number of cells (3 and 6% respectively), most probably not reflecting a true cellular state (empty bars). Data represents three independent biological replicates and two biological replicates for cell viability assays. Significance was assessed using nested ANOVA on the comparison between two variables: LV-GFP (as control) and LV-gene overexpression. Two way nested ANOVA was used to find gene overexpression and MPP(+) treatment interaction effects. Such interaction effects were identified for cell viability after HIP1R (E) and WWC1 (F) overexpression and for mitochondrial activity after ALDH1A1 (G) overexpression (* p value< 0.05, ** p value < 0.01, *** p value < 0.001). Error bars present standard error of the mean.

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treated cells. WWC1 overexpression decreased total neurite length and count by 15%. The effect on neurite length was lost in cells treated with MPP(+) but the neurite count was still decreased by 11% in 0.5mM MPP(+) treated cells. HIP1R overexpression also affected neurite length and count, but as mentioned before, due to the low number of surviving cells after HIP1R overexpression, the neu-rite outgrowth data are based on measurements in a very small population of cells. Similarly to HIP1R, the small population of surviving FOXO4 overexpress-ing cells also showed an increase of total neurite length.

Two genes only affected neurite length but not neurite count when over-expressed in SH-SY5Y cells (Figure 4C). CTDSP1 significantly decreased neurite length in surviving cells by around 35% (also in low dose MPP(+) treated cells). PTMA overexpression increased neurite length by 13% only in cells treated with high dose MPP(+).

Overexpression of RGMA only affected the number of neurites per cell. RGMA overexpression reduced the number of neurites per cell by about 18%. Low dose MPP(+) treatment combined with RGMA overexpression did not affect the neurite count, where as RGMA overexpression in 0.5mM MPP(+) treated cells decreased neurite count in these cells by 23%.

Discussion

A high-content RNA interference screen was used to test the role of 62 genes in mitochondrial activity and neurite outgrowth in SH-SY5Y cells, a DAe-rgic cell model for PD. Genes were selected based on their altered expression in the SN of PD patients and on their potential role in one or more of the above-mentioned processes (Bossers et al., 2009; chapter 2). A subset of 14 genes was thereafter also tested using LV-mediated overexpression. The HCS of all genes was performed in naïve RA-differentiated SH-SY5Y cells and in cells treated with a low or high dose of the mitochondrial toxin MPP(+). The use of MPP(+) allows the study of gene function in cells that exhibit mitochondrial impairment (chap-ter 3), a feature characteristic of DAergic neurons in PD patients. The results of the HCS are summarized in Table 4.

Gene function can be studied by either knockdown or overexpression. We first performed a knock-down screen of 62 genes and identified 4 genes with an effect on mitochondrial activity (RGMA and PTMA), or neurite outgrowth (FOXO4 and KLK6). This number of hits is relatively small (6%), considering that the 62 genes were preselected based on putative roles in cell survival, mitochon-drial activity, and/or neurite outgrowth. A high content knockdown screen may be prone to false negative results due to incomplete knockdown, slow protein turnover, or redundancy of protein function. We therefore decided to query the function of 14 genes by overexpression. In this HCS we included the 4 knock-down hits and 10 additional genes that failed to show an effect in the knock-down screen but were predicted to have a role in important aspects of PD-pathology.


169

We found that 12 of the 14 selected genes (86%) had an effect on at least one of the cellular parameters investigated. Of the 4 knockdown hits, 3 (RGMA, PTMA, and FOXO4) also demonstrated effects after overexpression. Ideally, knockdown and overexpression of a particular gene would give an opposing phenotype. In contrast, the three genes that were identified in these screens demonstrated complex effects (Table 4), that could be due to their involvement in the molecular pathways that affect multiple cellular processes (see below for extended discus-sion on individual genes).

Of the nine genes upregulated in the SN of the PD brain, five genes (CTD-SP1, FOXO4, HIP1R, PTMA, WWC1) induced cell death, of which 3 also induced mitochondrial activity (CTDSP1, PTMA, SOX2) after overexpression in SH-SY5Y cells. A transcriptional profiling study of PD SN DAergic neurons isolated with laser capture microscopy provides evidence for mitochondrial impairment at the transcriptional level in these neurons (Elstner et al., 2011) in accordance with established mitochondrial dysfunction in PD (Henchcliffe and Beal, 2008). Is the increase in mitochondrial activity a sign of cell stress and upcoming cell death? This is suggested by the observation that 3 of these genes also induce cell death. Mitochondrial membrane permeabilization is one of the major decisive events in any type of cell death (Kroemer et al., 2007).

Four of the nine genes with enhanced expression in PD diminish neurite outgrowth following overexpression in SH-SY5Y cells (CTDSP1, RGMA, SOX2, and WWC1). The HCS identified these genes as candidates that could play a role in the observed retrograde degeneration of dopaminergic projections in the striatum (reviewed in Burke and O’Malley, 2012). Moreover, five genes (CTDSP1, PTMA, RGMA, SLITK5 and WWC1) have effects on cell survival as well as on neu-rite outgrowth.

The effects of 3 genes (ALDH1A1, HIP1R, and WWC1) interacted with the mitochondrial toxin MPP+, suggesting that their mode of action is linked to mito-chondrial function. These genes are of particular interest, since in PD mitochon-drial function is compromised in the DAergic neurons in the SN.

Identification of genes that induce cell death in DAergic cells

IPA revealed that 45 genes in the ‘cell death’ biological process are altered in PD (chapter 2). Sixteen of these genes were functionally tested by knockdown, and 5 by overexpression. Overexpression of ALDH1A1, FOXO4, and PTMA af-fected cell viability. Both FOXO4 and PTMA are significantly upregulated in the PD SN, whereas ALDH1A1 was downregulated in DAergic neurons, on the mRNA and on the protein level (Bossers et al., 2009 chapter 2). These genes may there-fore play a role in the degeneration of DAergic neurons in PD.

ALDH1A1 is an aldehyde dehydrogenase enzyme, involved in alcohol and dopamine metabolism. It oxidizes the toxic compound 3,4-dihydroxyphenylac-etaldehyde - a product of DA degradation - into non toxic 3,4-dihydroxyphenyl-

CH A PTER 4

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↓0

00

SLI

TRK

50.

46

OV

00

00

0.01

MP

P+

0↑

↓↓

0.5

MP

P+

↓0

0↓

SO

X2

1.86

OV

0↑

↓↓

0.01

MP

P+

00

↓↓

0.5

MP

P+

00

↓↓

WW

C1

1.69

OV

↓0

↓↓

0.01

MP

P+

↓0

00

0.5

MP

P+

↓0

0↓

Tabl

e 4.

Ove

rvie

w o

f the

HCC

S re

sults

for 1

4 PD

gen

es. T

he e

ffect

s of o

vere

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ssio

n or

kno

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f 14

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. Gen

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d M

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with

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men

t.

CH A PTER 4

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acetic acid. The number of tyrosine hydroxylase positive SN DAergic neurons in ALDH1A1 knockout mice, which are impaired in the detoxification of aldehydes, decreases (Wey et al., 2012). siRNA knockdown of ALDH1A1 in the retina re-sulted in increased susceptibility to oxidative stress (Choudhary et al., 2005). ALDH1A1 overexpression interacted with MPP(+) treatment in mitochondrial activity and increased cell death after high dose MPP(+) treatment, which con-tradicts the suggested neuroprotective role of this gene. ALDH1A1 has also been shown to be a RA producing enzyme in midbrain DAergic neurons (Jacobs et al., 2007; Jacobs et al., 2011). As RA enhances the sensitivity of SH-SY5Y cells to mi-tochondrial loss of membrane potential induced by 6-hydroxydopamine (Lopes et al., 2010), Complex I inhibition by MPP(+) may result in a more robust induc-tion of apoptosis signaling.

FOXO4 is involved in cellular differentiation, proliferation and apoptosis (van der Heide et al., 2004). Overexpression of FOXO4 in SH-SY5Y cells decreased cellular viability. Interestingly, FOXO1, another member of the FOXO transcrip-tion factor family, mediates neuronal death through direct phosphorylation by LRRK2 in Drosophila neurons (Kanao et al., 2010). FOXO4 knockdown increased neurite outgrowth, most probably by improving cell viability and sustaining neu-ronal differentiation. FOXO4 has also been implicated in an anti-oxidant stress response in neurons (Araujo et al., 2011). However, high levels of FOXO4 did not promote survival of MPP(+) treated SH-SY5Y cells. FOXO4 upregulation in DAe-rgic neurons in the PD SN (Bossers et al., 2009) may thus have a pro-apoptotic effect.

HIP1R was not identified by IPA as a gene involved in cell death (chapter 2). Overexpression of HIP1R, a regulator of the clathrin-mediated endocytic ma-chinery and actin assembly, induced the most dramatic decrease in cellular vi-ability in SH-SY5Y cells. HIP1R has been linked to neuronal and 293T cell death by enhancing caspase 3 and 9 activity (Metzler et al., 2007; Kim et al., 2009). Furthermore, HIP1R was recently identified as a genetic risk factor for PD (Nalls et al., 2011). Since HIP1R1 overexpression showed an interaction effect with mi-tochondrial inhibition, the role of this gene in PD-associated neurodegeneration deserves more attention.

Finally, overexpression of NETO2 and ROBO2 decreased cellular viability only in MPP(+) treated cells, but showed no effect after knockdown. These two genes are downregulated in DAergic neurons in the PD SN (chapter 2) and have a primary function in axon guidance. Although these genes decreased cellular vi-ability only when combined with MPP(+) treatment, they did not show a signifi-cant interaction effect, suggesting that the decreased cellular viability may not be directly linked to the mitochondrial inhibition induced by MPP(+) treatment. NETO2, whose function is not entirely clear, modulates glutamate signaling in the brain through NMDA and kainite receptor regulation (Zhang et al., 2009b; Copits et al., 2011). So far there have been no reports linking this gene to cell death.


173

ROBO2 is a receptor for SLIT2 that plays a role in, mainly, repulsive axon guidance and cell migration. SLIT2 and ROBO2 have been linked to repulsive axon guidance of DAergic neurons (Lin and Isacson, 2006; Dugan et al., 2011) and to tumor growth suppressing signaling and apoptosis (Kim et al., 2008). On the other hand, overexpression of ROBO2 in the developing ureteric bud did not increase cellular apoptosis (Ji et al., 2012). Like NETO2, the ROBO2-induced de-crease in cell viability is difficult to interpret in the context of PD, as ROBO2 is downregulated in the PD SN.

Neurite outgrowth is most significantly affected by the cellular differ-entiation factor SOX2

Alterations in axon guidance signaling have been previously implicated in the pathology of PD (Lesnick et al., 2007; Bossers et al., 2009). Retraction of nigrostriatal axonal terminals is an early event in PD and could contribute to the death of DAergic neurons (Dauer and Przedborski, 2003; Cheng et al., 2010; Burke and O’Malley, 2012). With our list of target genes we aimed at identifying identifying molecules that affect axon outgrowth and that might contribute to retrograde axonal degeneration in PD.

DLK and KLK6 had small effects on neurite growth after overexpression (DLK1) or knock-down (KLK6). Neither of these genes have been linked to PD or to axon guidance, although DLK1 has been shown to stimulate midbrain DAergic neuron differentiation (Jacobs et al., 2009; Jacobs et al., 2011). The physiological relevance of the complex functional outcome of the HCS for these genes can only be further unraveled by studies on the function of these genes in vivo.

The biggest decrease in neurite outgrowth was induced by overexpression of SOX2. SOX2 is a transcription factor required for stem cell maintenance in the central nervous system during development and adulthood (Qu and Shi, 2009). SOX2 deficiency causes neurodegeneration in the thalamus, striatum and sep-tum of the adult mouse brain (Ferri et al., 2004). SOX2 together with three other transcriptional regulators (OCT4, NANOG and LIN28), is sufficient to reprogram human somatic cells into pluripotent stem cells (Yu et al., 2007). The 50% de-crease of neurite length and neurite count in differentiated SH-SY5Y cells after SOX2 overexpression could be the consequence of a cellular de-differentiation process regulated by this transcription factor. MPP(+) treatment had no addi-tional effects on these cells. SOX2 mRNA is 86% upregulated in the human PD SN tissue. SOX2 is expressed in both melanin positive and negative SN neurons (chapter 2). Bossers et al. noted a 104% increase in neuromelanin-negative neu-rons and a 51% decrease of neuromelanin-positive neurons in the PD SN (2009). This observation could be explained by the loss of intracellular melanin by DAer-gic neurons, during the progression of the disease. Alternatively, as SOX2 de-dif-ferentiated DAergic neurons in culture, the upregulation of SOX2 expression may de-differentiate SN DAergic neurons in PD. This may contribute to the observed loss of melanin-positive neurons and the increase in melanin-negative neurons.

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Although the concept of neuronal de-differentiation in the adult nervous system is not yet well understood, some evidence of neuronal de-differentiation has been documented in the adult rat brainstem after cochlear injury (Zheng et al., 2011). The dramatic effect of SOX2 overexpression in SH-SY5Y cells does point to a possible role in the differentiation state of DAergic neurons in PD, although more research is needed to obtain support for this hypothesis.

RGMA, PTMA, CTDSP1, WWC1 and SLITRK5 have effects on cell sur-vival and neurite outgrowth

RGMA, a glycosylphosphatidylinositol-anchored and secreted repulsive axon guidance molecule (Monnier et al., 2002; Niederkofler et al., 2004), is upreg-ulated after traumatic injury and contributes to the repulsive environment of the CNS scar (Schwab et al., 2005a; Schwab et al., 2005b; Hata et al., 2006; reviewed in Mueller et al., 2006; and Yamashita et al., 2007). Overexpression of RGMA in SH-SY5Y cells results in a small but significant reduction in the number of neu-rites, which is consistent with its function as a repulsive axon guidance mole-cule. A similar RGMA-induced reduction in neurite growth has been observed in many other neuronal cell types (Hata et al., 2006; Conrad et al., 2007; Metzger et al., 2007; Kubo et al., 2008; Yoshida et al., 2008), and overexpression of LMO4, a downstream component of the RGMA signaling pathway, also decreased neurite length and neurite count in SH-SY5Y cells (Schaffar et al., 2008). Interestingly, RGMA overexpression did not reduce the number of neurites in low dose MPP(+) treated cells, suggesting a new link between RGMA and mitochondrial function, suggested by a trend of significant interaction between RGMA overexpression and MPP(+) treatment.

Neogenin is a receptor for RGMA (Wilson and Key, 2007; Yamashita et al., 2007). Apart from axonal guidance, RGMA-Neogenin signaling regulates neuro-nal survival. Neurogenin is a so-called “dependence” receptor. In the absence of its ligand, the cytoplasmic domain of Neogenin is cleaved by caspase 3 which ini-tiates cellular apoptosis (Matsunaga et al., 2004; Matsunaga and Chedotal, 2004; Matsunaga et al., 2006). In line with these observations, we here show that RGMA knockdown in SH-SY5Y cells increases mitochondrial activity in the presence of 0.01mM MPP(+), and that cells with reduced RGMA expression show a stronger MPP(+) dependent decrease in cell viability compared with control cells. RGMA thus appears to promote cell survival, and to protect cells from MPP(+) induced toxicity. Indeed, in a mouse retina injury model, an increase in RGMA-Neogenin signaling reduced caspase activity and promoted survival of retinal ganglion cells (Koeberle et al., 2010). The synergistic effects on cell survival of RGMA knockdown and low dose MPP(+) treatment further suggests that there may be an as yet undiscovered functional link between RGMA and mitochondrial activ-ity.

Our results suggest that RGMA can act as a protective factor for SH-SY5Y cells with compromised mitochondrial function. At the same time, RGMA exhib-


175

its a moderate repulsive activity on the processes formed by these DAergic cells. The increased expression of RGMA in the SN neurons of PD patients, as shown by us (Bossers et al., 2009; chapter 2) and others (Neurocrine Biosciences, 2012), could indicate that RGMa normally protects DAergic neurons in the PD affect-ed SN against oxidative stress. However, axonal transport of enhanced levels of RGMA and increased secretion in the striatum could have a repulsive effect on synaptic terminals in the striatum. This latter scenario would be in support of the dying back hypothesis (Dauer and Przedborski, 2003; Cheng et al., 2010; Burke and O’Malley, 2012). To further elucidate this apparent dual role of RGMA in PD, we need to study its function in vivo in the complex and physiologically more relevant environment of the adult CNS (chapter 7).

PTMA (prothymosin alpha) has two functions in neurons. Firstly, it inhibits necrosis and initiates apoptosis (Ueda et al., 2007). We here corroborate the in-volvement of PTMA in neuronal death as PTMA overexpression reduced viability of differentiated SH-SY5Y cells. Secondly, PTMA is a transcriptional regulator of the cellular oxidative stress response. PTMA liberates the transcription factor NRF2 from the NRF2-Keap1 inhibitory complex, enabling its transportation into the nucleus, thereby activating the anti-oxidative stress response (Karapetian et al., 2005). At the same time, PTMA initiates ubiquitin-mediated NRF2 degrada-tion in the nucleus (Niture and Jaiswal, 2009). Although RA-differentiated SH-SY5Y cells express high levels of NRF2 (chapter 3), overexpression of PTMA does not improve cellular viability in elevated oxidative stress conditions after MPP(+) treatment. The main effect of PTMA overexpression may therefore be to stimu-late NRF2 degradation in SH-SY5Y cells. The increase in cell death after PTMA overexpression suggests that enhanced expression levels of PTMA in the SN DAe-rgic neuron in PD may play a causative role in the degeneration of these neurons.

Cells treated with 0.5mM MPP(+) exhibited increased neurite length. This effect could be evidence for a PTMA driven initiation of the anti-oxidative stress response (identified as a trend for interaction between overexpression and MPP(+) treatment). This would allow cells to grow longer neurites compared to GFP-overexpressing cells. The dual role of PTMA in cell death and neurite out-growth warrants further study on its role in DAergic neurons and its impact on neurodegeneration in MPTP mouse models of PD.

CTDSP1 is a transcriptional silencer of neuronal gene expression in non-neuronal cells (Yeo et al., 2005). Although it has not been associated with cell death, overexpression of this protein in differentiated SH-SY5Y cells induced a dramatic decrease in cellular viability. Furthermore, CTDSP1 decreased neurite length by ~30%. Both effects may be due to a general silencing of neuronal gene expression. Upregulation of this gene in the human PD SN may therefore directly cause neuronal death, as well as contribute to DAergic axon retraction from the striatum.

WWC1, a cytoplasmic phosphoprotein involved in synaptic plasticity, also induced cell death when overexpressed in SH-SY5Y cells, and showed an inter-

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action effect with MPP(+) treatment, linking its function with mitochondria or mitochondrial activity. Polymorphisms in WWC1 have been associated with memory performance (Kauppi et al., 2011) and late stage Alzheimer’s disease (Corneveaux et al., 2010). Furthermore, WWC1 has been shown to be an up-stream regulator of the Hippo signaling pathway (Baumgartner et al., 2010; Genevet et al., 2010), a pathway crucially involved in neuronal fate specification and maintenance (Jukam and Desplan, 2011). Thus, WWC1 may induce apoptosis via the Hippo pathway in SH-SY5Y cells. Similarly, the upregulation of WWC1 in the PD SN may be an important step in initiating DAergic neuron degeneration. Alternatively, WWC1 may also have a function in mitochondrial activity and/or oxidative stress response, since WWC1 overexpression in low dose MPP(+) treated cells seemed to slightly improve cellular survival. WWC1 overexpression also decreased neurite outgrowth. This specific effect may contribute to the re-pulsive stimulation of DAergic axons in PD and further contribute to the loss of synaptic connections in the PD striatum.

Finally, SLITRK5 decreased both cell viability and neurite count in SH-SY5Y cells after overexpression only when combined with MPP(+). In fact, SLITRK5 overexpression showed a trend of interaction with MPP(+) treatment, linking the function of this gene to the downstream effects of mitochondrial inhibition. SLITRK5, a member of the internal membrane protein SLITRK family, is involved in repulsive axon guidance signaling (Nguyen-Ba-Charvet and Chedotal, 2002; Aruga and Mikoshiba, 2003). Here we show a new role of SLITRK5 as a molecule controlling cellular viability. SLITRK5 is significantly downregulated in DAe-rgic neurons in the PD SN (Bossers et al., 2009, chapter 2). SLITRK5 has been shown to play an essential role in the formation of corticostriatal synapses and its deficiency leads to obsessive compulsive-like behavior in mice (Shmelkov et al., 2010). SLITRK5 knockdown did not show any effects in SH-SY5Y cells. The gained insight into the new function of SLITRK5 as a cell survival regulator and the link of this function to mitochondrial activity should be studied further.


177

Supplementary TablesGene name

siRNA sequence 1 siRNA sequence 2 siRNA sequence 3 siRNA sequence 4

AAK1 GACAUGCACUGCCUAAUUA GUACAGAACUCUCCCAUUC GAUGAAAUGUGCCUUGAAA GAAGGUGGAUUUGCUAUUG

AGTR1 GCACUGGUCCCAAGUAGUA CUAAACUGCUGUUAAUUGA AUACGUGACUGUAGAAUUG CCAAGAUGAUUGUCCCAAA

ALDH1A1 GGACAAUGCUGUUGAAUUU GCACUGAGCUGUGGAAACA CCACGUGGCAUCUUUAAUA GAACAGUGUGGGUGAAUUG

AMPH GAACUUCACCCGACGCUUA GAAAAUGGUUGGUGAGAAA CGAGUUGGAUUUUAUGUUA CUACGGAGCAGAAGCCUAU

ARHGEF2 GGACAAGCCUUCAGUGGUA CAACAUUGCUGGACAUUUC GAAUUAAGAUGGAGUUGCA GUGCGGAGCAGAUGUGUAA

CA2 GAAAUAUGCUGCAGAACUU GCGAGCAGGUGUUGAAAUU GGAUGGCACUUACAGAUUG GCACUUACAGAUUGAUUCA

CALN1 GCGAACAGCUGGCUAAUAU GGAAUUACCUCAACCGAUC GAGACCACCUAACGAUGAA GAUUGCAGCCAACCAGAUA

CASP7 GGGCAAAUGCAUCAUAAUA GAAACUCUACUUCAGUCAAU UACCGUCCCUCUUCAGUAA CCAGACCGGUCCUCGUUUG

CDK5 UGACCAAGCUGCCAGACUA GAGCUGAAAUUGGCUGAUU CAACAUCCCUGGUGAACGU GGAUUCCCGUCCGCUGUUA

COMT GAACGUGGGCGACAAGAAA GGCCUACUGUGGCUACUCA ACACCAAGGAGCAGCGCAU CUAACACUGGCUAGCUAUA

CTDSP1 GAACAACGCGGACUUCAUC GGGCAAAGGUGACCAGAAG GGACAGCUCGGCCGUCAUU CAAGUACGCAGACCCAGUA

DDC UCAAAGGACUGCAGGCUUA GCUAAAGGGUUCCAACAAA CAAAGCGGCUGGCCUGAUU GUUAAUUGGUGGAGUGAAA

DJ1 CAACACACCCUCUUGCUAA AAAGAGGGACCAUAUGAUG GGGACCAGCUUCGAGUUUG GAGGCGAGCUGGGAUUAAG

DLK1 GGGAAAGGACUGCCAGAAA GGUCUCACCUGUGUCAAGA GGACGAUGGCCUCUAUGAA GCUACGAGUGUCUGUGCAA

DNM3 GAAAUAAGCUAUGCAAUCA GCAAAGGAAUGUAUACAAA GAAGCUAGCUAAAGAAGUU GAAGGCAUCUCUACUAAGA

DOK5L CAAUGCAGAUCACUCAUGA CAUGAAAGAUUAAUGCUAG UCACAUCACUCGUCAGAAC GAGAUACGGUCGGGACUCA

DYNC1I1 GGAAAUUCGUGCUAACAGA CAAGGGAAGUAGUGUCCUA GACAAUCGCAGUCAUCGAA CGGGAGACGUCAAUAACUU

EDG2 UCUCUAUGCUCACAUCUUU GCAAUCGAGAGGCACAUUA GACAAAGAAAUGAGCGCCA UGGACUAUGGCCAUCGUUA

EHBP1 GCAAGUACCUCUAUGCUGA UAUAAGACCUGUGGAUAUG GAACUACAACAGCCUAUCA UCUCCGGACUGAACGAUUA

EN1 GAGCGCAGGGCACCAAAUA GAACAGCAGCCGGAACCUA CAACCCGGCUAUCCUACUU GCAAACCGCUACAUCACGG

FOXA1 CCUCGGAGCAGCAGCAUAA GCGCUGAGCCCGAGCGGCA CGGGAAGACCGGCCAGCUA GUGUAGACAUCCUCCGUAU

FOXO4 GGACUGGACUUCAACUUUG CCACGAAGCAGUUCAAAUG GAGAAGCGACUGACACUUG GACCAGAGAUCGCUAACCA

FST GGGCAGAUCUAUUGGAUUA GGACUACAGCUUUGGUAUA GUAAAGAAACGUGUGAGAA GUAAAGAGCAGCCAGAACU

GBP1 CGAAAGGCAUGUACCAUAA GAACAGGAGCAACUACUAA CAGAUGAGUACCUGACAUA CUGAGAAGAUGGAGAACGA

HIP1R CAGCUCAACUCGUGAACUA CUGUGGAGAUGUUUGAUUA CCUCUUCGAUCAGACGUUU CCGACAUGCUGUACUUCAA

HN1 GCAGGUGCCAAGUCUAGUG AAAAGUAGCCAGAUAGUAA CCACAGGCGUGUUGUUUUA CCGGAGACUUCUUAGAUCU

HPRT1 GAUAUGCCCUUGACUAUAA GUUUAUUCCUCAUGGACUA CUAUUGACAUCGCCAGUAA GACUGAACGUCUUGCUCGA

KCNJ6 CCAAAGAGCUGGCCGAGUU GCUCGAAGCUCCUACAUCA UGGCAAACCUGGAGAAUGA GAGCCAAGUUGAUCAAAUC

KIFAP3 GAACAGCUAUUACGAGUUG CGAAAGGUCUGUGAUAAUA GAACCGCCGUGAUUCAUUG CGAAAUUGACUUGGAACUCA

KLK6 GCCAAACUCUCUGAACUCA UGACAUACAUGGAAUAGCA ACAUCUACCUCCCGACCUA GAUAAGGAUGAUACAGUCU

LASS6 GAAGUGAUAUUGAGUCUAG CAAGCACGCUGACGAGGUU CGCCAUAGCCCUCAACAUU CUUCUGGUCUUACUUGAUU

LRDD ACUCGCACCUGAAGAAUGU GCAGAUCCGUCACAUGCUC GGACGUGGCUGAAGAGGUG CCAGAAAUGCCCAGACUGU

LTF AGAAAGAUCUGCUGUUCAA GGAUAGACCUGUGGAAGGA GGAAGCCAGUGGACAAGUU GCCACGAACUCACUAUUAU

MAGEE1 GGACAGAACUAGUGGUACU GAUCAGAGCAAGUACCCUA GCACAUUGUUUAGCUCUAG CCUCAAUACUUCCCGGGUU

MAPK9 GGAAAGAGCUAAUUUACAA AAAGAGAGCUUAUCGUGAA CAAGAUGUGUAUUUGGUUA GAAGAAAGAAGCAAGAAUG

MDH1 CAAAGGAACUGACAGAAGA CAUCAAGGCUCGAAAACUA GUUGAAGGUCUCCCUAUUA AAGGUGAAAUUGCAAGGAA

MRPS25 AGGUCAUGACAGUGAAUUA UGGUGGAUGUGGAGACCAA CCGUGAAGGUCAUGACAGU GAGGAAACCCUCAGGGAAG

NECAP1 GCAGAUAUCCUUUUAGAUU GGGAGAUGCCUUCGACUUU CGACCGAGUUGGAGUACGA GCUUAAAAGGCCAGCGUCU

NELL2 GCAAAUCGAUAUGCCAAUU GAAUUUGAGUCCUGGAUAG GAGCCUGUAUUGCCGCUAA UAAGCACAAUGGUCAGAUU

NETO2 GUUCCUAGAUUAUCAAAUG GAAACUUCGUUGCAGUCUA GAUGAAGGUAGUCGGCUUA GUAGUUACACUUUCAAACA

NR4A2 CCACGUGACUUUCAACAAU ACAUUCAGAUGCACAACUA GGACAAGCGUCGCCGGAAU CCACCUUGCUUGUACCAAA

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178

Gene name

siRNA sequence 1 siRNA sequence 2 siRNA sequence 3 siRNA sequence 4

P2RX7 GGAGACAUCUUCCGAGAAA GAAGGUGUGUAGUGUAUGA GCGAUGGACUUCACAGAUU CGAGAAACAGGCGAUAAUU

PARKIN GGAGUGCAGUGCCGUAUUU UCAAGGAGGUGGUUGCUAA UUAAAGAGCUCCAUCACUU GUAAAGAAGCGUACCAUGA

PFDN4 AAACAAAUUUGCACGGAAU CAAUGUUACUUUCGAAGAU CAACAUAAACCUUGAAGCU AGAAGAAACGCAAGAAAUG

PHLPP GAUCUAAGGUUGAACGUAA GAUAUUGGCCAUAAUCAAA UGAUCUAGAUGCUAUGAUU GAAUGUAUAAUGUCCGUAA

PINK1 GAAAUCCGACAACAUCCUU GAGCAUCGGCCUGCAGUUG GGAGCCAUCGCCUAUGAAA GCAAAUGUGCUUCAUCUAA

PITX3 GAGCACAGCGACUCAGAAA CCAAACAGCACGCCUCCUU CCAGAGGACGGUUCGCUGA CCGCCAAGACCUUUCCAUU

PTMA UAACGGGAAUGCUAAUGAG UGACAAUGAGGUAGACGAA GCUCCGAAAUCACCACCAA GGAAGUUGUGGAAGAGGCA

RGMA CGAGCUGGAUGGAUGGGUA CGACAAUAAUUACCUGAAC GUUGGAGGAUGUCAAGAUG GGGAGAGGCUAGUGGUAAC

ROBO2 GCACGGAGCUGGAACACUA UGAACGAAGUGCUGUCUUA GCCAUUCGGUCCGUAAUAA GGACUAAUGAGCAAUGGAA

SDC2 CAAAGAUACUGUUGACUAG GAAACCACGACGCUGAAUA UAUCAGAAGGCACCUACUA GUGUAUCGCAUGAGAAAGA

SEMA5A GAGCAACGAUUCCGAUACA GGCAAGAUCCAGUAGCGUA GGACGUGAUCCUGCCAUUU UGGAGGAAAUAGUCGGAUA

SLC18A2 GAUCACAACUGCCCUAUUA GGAGUGUGCUCUAUGAGUU GCAUUAAGCAUGAGAAGAA GAAGAGAGAGGCAACGUCA

SLC25A4 CUAUAGAGCUGCCAUCUUC GGAGGAAGAUUGCAAAAGA GCUUGGAGCUUCCUAAAGG GUAUUGGUGUUGUAUGAUG

SLITRK5 GCAAUAGCCUCCCGGAAUA ACGAAUAUCUGGAGUUAAA GAUCUGGGCCUCAACGUAA CAUCUAGGUAGCAAUGUUA

SNAP91 GCAUAGACCUGUUUAGUAC GAGCAAGUUGGUAUUGAUA GCUGGGUGGUUGUGUUUAA UAGCGGAUCUUAACAUCAA

SNCA CUACGAACCUGAAGCCUAA GAGCAGUGGUGACGGGUGU GCAAGUGACAAAUGUUGGA UGGCAACAGUGGCUGAGAA

SOX2 GCUCUUGGCUCCAUGGGUU UCAUGAAGAAGGAUAAGUA GCUCGCAGACCUACAUGAA ACAACAUGAUGGAGACGGA

TGIF1 GAGAAAGGAUGGCAAAGAU CAAACGGGCUGCAGAGAUG GAAACGAGCUCUGUGGAGU GUGCAGAUUCUUCGGGAUU

TH GAAGGUGUUUGAGACGUUU GAGAUCGCCUUCCAGUACA CGUACACGCUGGCCAUCGA UGAAGGUGUUUGAGACGUU

TRIM36 UCAUGGAAUUGAUAGCUAA AAUUGAUAGCUAAAGGCAA AUUGAUAGCUAAAGGCAAG AGAUGAGUGAAUUUGGCUA

UBASH3B GCAAAUUAGUUGUUUCAGA CACAAUAUCUUGAAAGGUU GGUGAAGCCUUAUUAGAGA GCACAGAAGCUUUCCGACU

UCHL1 UAGAUGACAAGGUGAAUUU CCGAGAUGCUGAACAAAGU UCAAGCCGAUGGAGAUCAA GAAGGGACAAGAAGUUAGU

VAV3 GCAGAGACCGAACUUAUUA GCAAAGCACAUCAAGAUUU AGACCGAACUUAUUAAUAG GUAUGCAGCCCUCGUGUAA

VPS41 GCACCGAACUCAAAUGAAA GAAAUAGUGUCUCAGUUUG GAGAAUGAAUGUAGAGAUU GACAAACCACCAUUUAUUA

WWC1 GAGAAAGCCUCACCUGAUA GGUUGGAGAUUACUUCAUA GAUUGCGCCUUCGAUAUGA GGGACCGGCUGAUCCUUAU

Supplementary Table 1. siRNA siGENOME SMART pool (Dharmacon) sequences for 62 selected human PD target genes and 4 known PD genes used for prove of principle studies. Each siRNA pool consists of 4 siRNA sequences indicated in 4 columns.


179

Gene name


qPCR primer forward qPCR primer reverse

Housekeeping genes

NY-SAR-48 NM_033417 GCAATACAGGACATTCGCCAC TCTAAGAGCTGCTGCCCATCTC

NDUFV2 NM_021074 CTGCATGCTTCGAAACTCTGA TCTCCCCAACCTTTATTCCAAG

PPP1R8 NM_138558 GGCACTTTCTTGGGTCACAT GGCAATGTCTGAGGCTTCTC

UQCRFS1 NM_006003 GGAAATTGAGCAGGAAGCTG TGGGTACACAGCCAAGATGA

Genes of interest

ALDH1A1 NM_000689.3 TGTTGAGCGGGCTAAGAA CTCCTCCACATTCCAGTTT

CTDSP1 NM_021198.1 GCATCCTCCACTCACTCTTCT GCTCCATTCTCCTCCACAA

DLK1 NM_003836.4 CTCAACAAGTGCGAGACCTG CTTCTCGGGGAAGATGATGT

FOXO4 NM_005938.2 GTGCTGGCGGAGGAAATA GGGAATGGGAAGAGGTGAG

HIP1R NM_003959.1 GCCAGGAACTGAAACCCA TCCTCCGCACAGCATCTT

KLK6 NM_001012964.1 AACCGAATCTTCAGGTCTTCC GGCGGCATCATAGTCAGG

NETO2 NM_018092.3 TGGCAGACTTGTCGGAAGA ACAGTGGTGGTCGTGGAT

P2RX7 NM_002562.4 GACGCTCTGTTCCTCTGA GGTCTTCTGGTTCCCTTC

PTMA NM_002823.4 GCTCCGAAATCACCACCA CTCATTGTCAGCCTCCTG

RGMA NM_020211.1 GTACATCGGCACCACCAT CCCAGTCCTCCACAGCAT

ROBO2 NM_002942.3 CAACCTCCACAGCCTCCA TCTTCGTCGTCGGCATCA

SLITRK5 NM_015567.1 GTCGGTGCCCTTGTCTGT GTCGCTCTGGTTCTTCTTCC

SOX2 NM_003106.2 CTCGCCCACCTACAGCAT GACTTGACCACCGAACCC

WWC1 NM_015238.2 TGTCTCAGCCGCCGTATC CACCCACTGCTTCCGATT

Supplementary Table 2. Sequences of forward and reverse primer used for qPCR overexpres-sion detection. Gene name and NCBI reference number is indicated in the 1st two columns. Names and primer sequences of housekeeping genes are also indicated.

180

CHAPTER 5

Modeling early Parkinson’s disease pathology with chronic

low dose MPTP treatment

J.A. Korecka1, R. Eggers1, D.F. Swaab2, K. Bossers1, J. Verhaagen1

Manuscript accepted and soon to be published in RNN


Amsterdam, The Netherlands2 Neuropsychiatric Disorders, Netherlands Institute for Neuroscience, An Institute of the Royal Neth-

erlands Academy of Arts and Sciences, Meibergdreef 47, 1105BA, Amsterdam, The Netherlands

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Abstract

Purpose: Parkinson’s disease (PD) is a movement disorder mainly charac-terized by progressive neurodegeneration of dopaminergic (DAergic) neurons in the substantia nigra (SN). As yet, unknown molecular changes contribute to the development of PD leading to a great need for in vivo models that herald this disorder. Here we characterize an animal model presenting early PD pathology. Methods: Young, adult C57/BL6 mice were treated for five weeks twice a week with 15mg/kg 1-methyl-4-phenyl1,2,3,6-tetrahydropyridine (MPTP) in combi-nation with 250mg/kg probenecid. During the treatment mice were tested on their dopamine dependent movement skills. The integrity of their nigrostriatal system was examined through immunohistochemical studies. Results: During the treatment, mice developed dopamine-dependent movement deficits induced by loss of tyrosine hydroxylase (TH) positive nigrostriatal axon terminals. Im-munohistochemical study identified astrogliosis and microgliosis in the SN but no decrease of TH immunostaining, demonstrating lack of DAergic neuron de-generation. We also observed formation of α-synuclein inclusion bodies in the SN. Conclusions: The combined features of this MPTP model appear to represent an early neurotoxic cellular stress to the SN neurons bearing a striking resem-blance to the early stages of PD neuropathology. This model might prove very useful to investigate early neurodegenerative events in the nigrostriatal DAergic system and to study the effects of potential treatment strategies counteracting the early PD cellular changes.

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1. Introduction

Parkinson’s disease (PD), the second most prevalent age-related neurode-generative disease, is characterized by a progressive loss of nigrostriatal dopa-minergic (DAergic) terminals and a selective loss of DAergic neurons in the sub-stantia nigra pars compacta (SN), thereby inducing a movement disorder (Dauer & Przedborski, 2003). Additionally, there is a progressive formation of ubiqui-tin and α-synuclein positive cytoplasmic inclusions during the progression of the disease, starting in the lower brainstem areas and ascending to the higher cortical levels of the brain (Braak et al., 2003). The etiology of PD appears to be multifactorial, involving both genetic and environmental components (Gorell et al., 2004). So far several cellular mechanisms, such as aberrant protein folding, oxidative stress and mitochondrial dysfunction have been linked to the develop-ment and progression of this disease, but these cannot fully explain the underly-ing neuropathology (Greenamyre & Hastings, 2004). Therefore, there is a great need in PD research for animal models to further explore the role of specific mo-lecular players in PD pathology and to test novel, potential treatments. So far, multiple PD mouse models have been developed by either genetic manipulation (such as mice overexpressing human α-synuclein protein) or acute treatment with neurotoxic compounds that selectively damage DAergic neurons in the SN (rotenone, 6-Hydroxydopamine (6-OHDA) or 1-methyl-4-phenyl1,2,3,6-tetrahy-dropyridine (MPTP) (Betarbet et al., 2002; Bove et al., 2005; Schober, 2004).

The neurotoxin MPTP was discovered in 1982, after drug addicts have been found to self-administrate this meperidine analog synthesis by-product. These addicts rapidly developed PD symptoms and proved responsive to treatment with L-DOPA. Later neuropathological examination of these patients’ brains re-vealed moderate to severe loss of DAergic neurons in SN (Langston et al., 1999). After crossing the blood brain barrier, MPTP is taken up by astrocytes and con-verted by monoamine oxidase B to its active toxic component 1-methyl-4-phe-nyl-pyridium ion (MPP(+)). MPP(+) is then released and taken up specifically by DAergic neurons via the dopamine transporter (DAT). In neurons, MPP(+) spe-cifically inhibits the mitochondrial complex 1 of the electron transport chain, re-sulting in ATP depletion, loss of mitochondrial membrane potential and the for-mation of reactive oxygen species (ROS). These stress events eventually lead to the selective loss of DAergic neurons, similar to neuronal degeneration in the PD SN (Nicotra & Parvez, 2002; Beal, 2003).

In an attempt to reproduce the chronic and slowly progressive nature of PD associated neurodegeneration, a rat model was developed based on multiple increasing intrastriatal dosage of 6-OHDA (Fleming et al., 2005), and a mouse model based on multiple low dose injections of MPTP (Petroske et al., 2001). This mouse model was based on a chronic 5 week 25mg/kg MPTP treatment scheme in combination with probenecid. Probenecid inhibits MPTP clearance from the periphery and increases its efficiency in crossing the blood brain bar-

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rier to the CNS. This chronic treatment regimen, apart from inducing progressive DAergic neuron degeneration in the SN, decreased the number of DAergic nerve terminals in the striatum, the DA levels in the striatum (Petroske et al., 2001), and induced glial reactivity in the midbrain (Schintu et al., 2009a; Schintu et al., 2009b). Also, this treatment is the only toxicological treatment so far that can induce the formation of α-synuclein and ubiquitin positive inclusions in the cyto-plasm of DAergic and cortical neurons (Meredith et al., 2002). Although chronic and progressive, after a 5-week treatment period this model still represents an end stage PD-like phenotype as most of the DAergic neurons have already degen-erated by this time.

In this study, we describe the early neurodegenerative characteristics of a PD mouse model, based on a 5-week chronic 15mg/kg MPTP treatment scheme. This treatment leads to movement deficits, the loss of nigrostriatal terminal projections, gliosis in the SN and the formation of α-synuclein positive inclusion bodies. Importantly, we did not observe DAergic neuronal cell loss in this model. These combined features bear a striking resemblance to the dying-back hypoth-esis in PD, where striatal denervation is the initiating event in the loss of the SN DAergic neurons (Dauer & Przedborski, 2003). Thus, we are the first to report that this early PD model provides an interesting window of opportunity to study the mechanisms that underlie the early neurodegenerative events that initiate the cellular death of DAergic neurons, and can be a useful tool to explore ap-proaches to rescue the PD-phenotype during the earliest stages of development.

2. Materials and Methods

2.1. Reagents

MPTP hydrochloride was purchased from Sigma-Aldrich (St. Louis, MO, USA) and dissolved in 0.9% NaCl (10mg aliquots, prepared fresh before each in-jection session). Probenecid (Sigma-Aldrich) was dissolved first in 1N NaOH and adjusted to pH of 7.4 with 0.1M Tris-HCl (pH 6.8) prior to injection. The final con-centration of probenecid was 12.5mg/ml. Fresh aliquots were used for each in-jection session.

2.2. Animal care and MPTP chronic model PD generation

21 male C57/BL6 mice 12 weeks of age (weight ~25g) were used (Harlan, Zeist, The Netherlands). Animals were housed socially (5 animals per cage) in a standard plastic housing with food and water ad libitum, 12 hour light and dark cycles in 20°C controlled housing facility. All the experimental procedures and post treatment care were carried out in accordance with the Animal Experimen-tal Committee of the Royal Netherlands Academy of Arts and Sciences.


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Mice were randomly divided into three groups prior to the behavioral test-ing. The first group consisted of a control group (n=8) receiving subcutaneous (s.c.) saline injections along with intraperitoneal (i.p.) 250mg/kg probenecid, a MPTP clearance inhibitor having no effects on the DAergic system (Barber-Singh et al., 2009). The second group (n=6) received 15mg/kg MPTP s.c. and 250mg/kg i.p. probenecid injections and the third group (n=7) received 25mg/kg MPTP s.c and 250mg/kg i.p. probenecid in order to recreate the model previously de-scribed in Petroske et al (Petroske et al., 2001). All animals received a total of 10 injections, every 3.5 days for 5 weeks. Following the treatment, all cages were placed on heating pads overnight, and throughout the experiment animals re-ceived sucrose gel packs. Safety measures were followed according to previously published guidelines (Przedborski et al., 2001; Jackson-Lewis & Przedborski, 2007).

2.3. Behavioral testing

All animals were behaviorally tested using the grid test where movement coordination and balance were assessed. This test assesses forepaw use, in par-ticular the use of distal musculature and digit manipulation sensitive to dopa-minergic input in the striatum (Tillerson & Miller, 2003). Briefly, mice were sus-pended upside down on a metal grid and allowed to move freely throughout the grid. A successful trial meant that an animal had taken at least 10 steps in at least 10 seconds. Each trial lasted a maximum of 30 seconds. The number of steps with both forepaws was counted as well as each unsuccessful step with either forepaw. For each animal, the three runs were averaged and the ratio between the total forepaw foot faults/total forepaw steps was calculated (Meredith & Kang, 2006).Tests were performed once a week, always before the MPTP injec-tions to avoid the reduction of movement bias that may occur directly after the treatment. The first test took place on the day of the first MPTP treatment and the last test was performed 3 days after the last MPTP treatment (total of 6 test-ing sessions).

2.4. Tissue processing

3.5 days after the last MPTP treatment all mice were sacrificed by an i.p. overdose with Pentobarbital (50mg/µl) and transcardially perfused with 0.9% saline followed by 4% paraformaldehyde (PFA, Sigma-Aldrich) in sodium phos-phate buffer (PBS) pH 7.4. The brains were further post-fixed overnight and 4 series of 30µm thick coronal sections of the entire SN and the striatum were cut on a vibratome. The anatomical level of the sections was identified using Mouse Brain Atlas (Paxinos.G. & Franklin.K.B.J., 2001) and sections were collected starting at the posterior end of the SN and ending at the anterior side of the stria-tum. The sections were stored free-floating at 4°C in 1% PFA in PBS pH 7.6.

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2.5. Immunohistochemistry

Prior to the free-floating immunostaining, sections were washed twice times for 10 minutes with 1x tris buffered saline (TBS) (Sigma-Aldrich) with 0.2% Triton X-100 (Sigma) (TBS-T) and then blocked in blocking buffer (2.5% fe-tal calf serum (FCS) (DAKO A/S, Glostrup, Denmark) in TBS-T) for 1 hour at room temperature. Sections were then incubated for 1 hour at room temperature, fol-lowed by overnight incubation at 4°C in TBS-T 2.5% FCS containing 1:1000 anti-tyrosine hydroxylase (TH) rabbit polyclonal antibody (Institute Jacques Boy SA, Reims, France for SN sections and Pel-Freez Biologicals P40101, AR, USA for stri-atal sections) or 1:1000 anti-TH mouse monoclonal antibody, clone LNC1 (Milli-pore MAB318, Temecula, CA, USA) in combination with either anti-glial fibrillary acidic protein (GFAP)-Cy3 conjugated mouse monoclonal antibody (Sigma) at 1:1500 dilution, anti-Iba1 rabbit polyclonal antibody (activated microglia marker, Wako, Osaka, Japan) at 1:2000 dilution, anti-VAMT2 polyclonal antibody (Chemi-con International, CA, USA) at 1:400 dilution, or anti-α-synuclein monoclonal an-tibody (BD Biosciences, Breda, The Netherlands) at 1:500 dilution. Subsequently, sections were washed 3 times with TBS-T and incubated with anti-rabbit or anti-mouse Alexa 488 antibody at 1:800 (Invitrogen, Carlsbad, CA, USA), anti-rabbit Cy3 1:800 (Jackson Laboratories, PA, USA) and Hoechst 33258 1:10000 (BioRad, Hercules, CA, USA;) for 1 hour at room temperature in blocking buffer. Sections were then mounted on chrome-aluin and gelatin coated glass slides and embed-ded in Mowiol (0.1 M Tris pH 8.5, 25% glycerol, 10% w/v Mowiol 4-88 (Sigma)).

2.6. Image acquisition and analysis

Images were obtained on an AxioPlan 2 microscope (Zeiss, Sliedrecht, The Netherlands) with Planapochromat objectives, using Evolution QEi black and white camera (MediaCybernetics) and ImagePro software. 10x magnification pictures were taken for SN sections and 2.5x magnification pictures were taken for the striatum sections with fixed exposure times for each channel. The ex-posure time was selected so the fluorescence signal was not overexposed. High resolution confocal z stack images were acquired using the Leica confocal micro-scope (Wetzlar, Germany).

Masking and quantification were processed blinded to the treatment groups. In SN sections, based on the TH staining and anatomical borders, an area of interest was outlined in the ImagePro Plus Measure Threshold macro repre-senting the SN pars compacta (SNpc) structure and an area just outside of the SN to measure the background fluorescence levels (Figure 1A, B and C). Total inten-sity of TH, GFAP and Iba1 was measured in both areas and the background value was subtracted from the SN measure. The total intensity value was then correct-ed for the size of the outline area, resulting in the measure of average intensity in that area. Striatal sections were outlined based on the Hoechst staining and the anatomical borders (Figure 1E and F). Here also TH and GFAP fluorescence in-


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Figure 1. Masking procedure for fluorescence intensity quantification. A. Image of control SN stained for both TH (green) and GFAP (red). Immunefluorescent intensity was measured in the SN (red outline) and the background (blue outline). B. Gray image of TH immunefluorescent signal in the SN outline. C. Gray image of GFAP immunefluorescent signal in the SN outline. D. For TH positive area measurement TH signal higher then 2x background was marked in each image (red mask). The area of this signal within the outlined SN (rad outline) and background outline (blue outline) was quantified. Scale bas represents 0.25mm. E. Gray image of Hoechst immunefluores-cent signal in the mouse striatum section. Based on this signal a striatal area (red outline) and background area (blue outline) in the cortex was outlined. F. Image of control striatum stained for TH (green), GFAP (red) and Hoechst (blue). Immunefluorescent intensity was measured in the SN (red outline) and the background outlines (blue outline). Scale bar represents 1mm.

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tensity was measured and corrected for background and size of the area. Finally all sections from each animal were averaged out, resulting in a readout of aver-age fluorescence intensity in the SN or the striatum for each animal.

Furthermore, the total area positive for TH immunofluorescence was mea-sured in the SN and background outlines (outlines are indicated in Figure 1D). Only TH signal higher than 2x average background value of all sections was mea-sured. In case any signal was detected in the background outline, these values were subtracted from the SN area. For each animal an average of TH positive area per section was calculated.

2.7. Statistical Analysis

Statistical analysis was performed using SPSS PASW Statistics software version 18. The Mann Whitney U test was used to estimate the differences be-tween all treatment conditions. A p-value < 0.05 was considered significant.

3. Results

3.1. Both low and high dose chronic MPTP-probenecid treatments induce movement deficits in mice

All animals were weighed and subjected to a weekly grid test to asses their movement skills starting before the first MPTP treatment (week 0) and ending 3.5 days after the last treatment (week 5, Figure 2). MPTP and probenecid injec-tions had no significant effect on an animal’s weight throughout the treatment period (Figure 2A). The neurotoxic treatment in both concentrations induced behavioral deficits already after two injections (week 2B, p=0.016 and 0.017). For the high dose regimen (25mg/kg) this effect continued until the end of the experiment (week 5, p=0.005). A low dose regimen of 15mg/kg MPTP caused an increase in the number of forepaw faults made by the animals until the 3rd week after the start of the experiment (p=0.003). Further treatments did not show this behavior deficit either at week 4 and 5 (p=0.108, and p=0.368 respectively). No significant difference was seen between the high and low dose treatment groups in any of the time points. Control animals did not show any effect of probenecid treatment on their movement skills.

3.2. Only high dose chronic MPTP treatment induced DAergic neuron degeneration

Immunohistochemical analysis of the SN revealed that a high dose MPTP regimen induces DAergic neuron cell death (Figure 3). In these animals, TH fluorescence levels, marking cell bodies and axons of DAergic neurons, signifi-cantly decreased in comparison to the control situation (65% fluorescence loss


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p<0.001) and to 15mg/kg MPTP treated mice (p=0.001, arrows in Figure 3A and C, quantification Figure 3E). In contrast to the observations in the high dose MPTP regimen, the 15mg/kg MPTP treatment did not significantly decrease TH immunoreactivity in the SN (18% decline in fluorescence compared to control, p=0.142).

Similarly, average TH positive area in the SNpc also showed a significant decrease in 25mg/kg MPTP treated animals compared to both control (decrease of 75%, p=0.002, Figure 3E) and 15mg/kg MPTP treated animals (p=0.014). 15mg/kg MPTP treatment showed a slight trend towards decreasing the average TH positive area in the SNpc compared to the probenecid only treated animals (36% decrease, p=0.181).

3.3. Both low and high dose MPTP treatments result in astrogliosis and microgliosis in the SN

Interestingly, animals treated with 15mg/kg and 25mg/kg MPTP both dis-played significantly higher levels of GFAP immunoreactivity in the SN in com-parison to the control group (p=0.003 and p< 0.001 respectively, arrow heads in Figure 3A and B, quantification Figure 3F). Additionally, Iba1 immunoreactivity

Figure 2. Effects of MPTP treatment in mice on weight and motor behavior. A. Weight distribu-tion of all animals treated with two doses of MPTP and saline. Animals were weighed twice a week before each MPTP injection. No significant differences in weights were observed between the three treatment groups. B. 5 week regimen of MPTP in both 25 mg/kg and 15mg/kg dosage with probenecid induces movement deficits measured by grid test already in the 1st week after two injections. This behavior deficit continues until the end of the experiment for the 25mg/kg regimen (week 5), whereas in the 15mg/kg dosage the movement deficit declines on the 4th week of treatment (seventh MPTP injection). The ratio represents the number of forepaw faults over the total of forepaw steps (* p value < 0.5, ** p value < 0.01, *** p value <0.001, black ‘*’ show time points where both treatments induced significant movement deficit, gray “*” shows time point where only 25mg/kg MPTP induced a significant movement deficit). A baseline behavior mea-surement was taken right before the start of the MPTP treatment (week 0). Error bars represent standard error of mean.

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Figure 3. Tyrosine hydroxylase (TH), glial fibrillary acidic protein (GFAP) and Iba1 immunological detection in mouse SN after low and high dose MPTP treatment. A and B. Photographs represent SN of mice treated with saline, 15mg/kg MPTP and 25mg/kg MPTP stained for TH (green) and GFAP (red). Panel B represents a high magnification Z stack confocal image of panel A. Arrows point to the loss of TH staining in the SN, whereas arrowheads point to the increase of GFAP staining. C and D. Photographs represent SN of mice treated with saline, 15mg/kg MPTP and 25mg/kg MPTP stained for TH (green) and Iba1 (red). Panel D represents a high magnification Z stack confocal image of panel C. Arrows point to the loss of TH staining in the SN, whereas arrowheads point to the activated microglia stained for Iba1.The scale bars in A and C represent 0.25 mm, and in B and D 20µm. E. Effect of MPTP treatment on TH expression. TH average fluo-rescence intensity levels (gray level/mm2) and TH positive area (mm2) in the SN were quantified in saline (black bars), 15mg/kg (light gray bars) and 25mg/kg (dark gray bars) treated animals. TH immunoreactivity levels and TH positive area were significantly reduced in 25mg/kg MPTP treated mice compared to the saline and the 15mg/kg MPTP treated mice (* p <0.05, ** p < 0.01, *** p <0.001). F. MPTP treatment induces gliosis in the SN. GFAP and Iba1 fluorescent intensities were significantly increased in the SN in both MPTP treatment groups compared to the saline injected mice (* p <0.05, ** p < 0.01, *** p <0.001). Error bars represent standard error of mean.


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indicated higher levels of activated microglia in the SN in both of the MPTP treat-ment groups compared to the control situation (15mg/kg group p= 0.002, 25mg/kg group p=0.021, arrowheads Figure 3C and D, quantification Figure 3F). Mor-phology of microglia confirmed their activated state (Figure 3D).

3.4. Chronic low and high dose MPTP treatments result in a loss of nigrostriatal endings in the striatum

We also investigated the effect of MPTP treatment on the integrity of axonal projections of SN DAergic neurons to the whole mouse striatum. Interestingly, in both MPTP treatment groups a decrease in TH immunoreactivity in the striatum was observed, suggesting a loss of SN DAergic nerve endings in this structure (Figure 4). This amount of denervation was dose dependent (significant differ-ence between two MPTP treatments, p value=0.022), with a 53% decrease of TH immunoreactivity in the 15mg/kg MPTP group (p=0.02) and an 85% decrease in the 25mg/kg group (p< 0.001, Figure 4D). Similarly, VMAT2 fluorescence levels decreased in MPTP treated animals by 50% compared to the saline treated mice when measured in three randomly selected animals for each group (p=0.039 and p=0.044, Figure 4C and E). GFAP levels were not significantly different between the treatment groups (p=0.95 and p=0.78, Figure 4D).

3.5. Chronic MPTP treatment induces formation of α-synuclein posi-tive inclusion bodies in SNpc

Immunohistochemical detection of α-synuclein revealed a large presence of large α-synuclein positive puncta in the SN of the MPTP treated animals (Figure 5). We also observed an increased amount of α-synuclein positive inclusions in the SN with higher dosage of MPTP treatment (Figure 5A and 5B). High magnifi-cation revealed α-synuclein positive diffuse staining and large granular puncta in the TH positive and other SN neurons (Figure 5C). There were a few α-synuclein positive small puncta present in the saline treated animals, but much less when compared to the MPTP treated animals.

4. Discussion

In this study, we present a chronic PD mouse model based on a 5-week low dose (15mg/kg) MPTP treatment in combination with probenecid. This model is characterized by movement deficits and loss of DAergic nigrostriatal projections. We are the first to report that this model is also associated with astrogliosis and microgliosis in the SN and formation of α-synuclein positive inclusions. Interest-ingly, we did not observe a significant loss of TH-positive DAergic neurons in the SN in this model, in contrast to DAergic neuron death in the well characterized high dose (25mg/kg) MPTP model. These interesting features of the 15mg/kg model resemble early pathogenic events in PD, and this could therefore be a use-

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Figure 4. Tyrosine hydroxylase (TH), glial fibrillary acidic protein (GFAP), Hoechst and VMAT2 immunofluorescence levels in the mouse striatum after MPTP treatment. A. Immunofluorescent detection of TH (green), GFAP (red) and Hoechst (blue) in the striatum of mice treated with saline, 15mg/kg MPTP and 25mg/kg MPTP. B. High magnification Z stack confocal image of panel A. C. Immunofluorescent detection of VMAT2 (red), another marker of dopaminergic terminals


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ful model to study the early neurodegenerative events that initiate the cellular death of DAergic neurons.

We observed a significant loss of TH immunoreacitivty in the whole stria-tum of both the low and high dose MPTP mice. This is in accordance with earlier reports where both these doses induced loss of DA and DA uptake in the stria-tum resulting in movement impairments (Xu et al., 2010; Schintu et al., 2009a; Schintu et al., 2009b; Lau et al., 1990; Petroske et al., 2001; Novikova et al., 2006). Indeed, our observation of impaired performance in both the low and high dose MPTP groups on the grid test, a test that is sensitive to DA levels and DA uptake in the striatum (Tillerson & Miller, 2003), suggests that the loss of striatal TH expression induced these movement deficits. Two MPTP/probenecid injections were needed for the mice to show a significant increase in errors during the grid test, suggesting that at early stages of this model there is already depletion of DA in the striatum. This DA depletion in the striatum has been previously shown already 1 day after a single 15mg/kg MPTP/probenecid injection and lasting up to 7 days post injection (Lau et al., 1990). The only other report testing behav-ioural impariments during the MPTP treatment showed no signifcant increase in error rate at beam transveral test after the 1st 25mg/kg MPTP/probenecid injection, but only after the 10th injection, suggesting the progressive nature of this model (Schintu et al., 2009a). As no testing was performed between the first and tenth injection, we can not directly compare their data to our results. How-ever, a significant delay in pellet retreaval during an olfactory test was reported already after the 1st MPTP/probenecid injection (Schintu et al., 2009a). Although a non-motor symptom, olfactory dysfunction is one of the earliest deficits in PD (Haehner et al., 2007).

In the high dose MPTP/probenecid treatment motor deficit is seen to last until 6 months after the treatment (Petroske et al., 2001; Schintu et al., 2009b). In our study, the low dose group shows recovery directly at the end of the treat-ment. This recovery phenomenon has been reported by others after many dif-

ascending from the SNpc. Although to a lesser extent than the TH staining, VMAT2 also shows a decreased fluorescent level in both MPTP treated groups when compared to control. The images here are representative of three animals per treatment group. D. Quantification of TH and GFAP fluorescent intensity (gray level/mm2) in mouse striatum. TH levels were significantly reduced in both 15mg/kg (light gray bar) and 25mg/kg (dark gray bar) MPTP treatment groups compared to saline (black bar), and to each other (* P< 0.05, *** P< 0.001). GFAP staining was not significantly different between treatment conditions. Statistical differences were assessed by Mann Whitney test. E. Quantification of VMAT2 fluorescent intensity (gray level/mm2) in mouse striatum. VMAT2 levels were significantly reduced in both 15mg/kg (light gray bar) and 25mg/kg (dark gray bar) MPTP treatment groups compared to saline (black bar) in a selection of three animals per each group (* P< 0.05). Statistical differences were assessed by student T test. Error bars represent standard error of mean. The scale bars represent 1 mm in panel A, 20 µm in panel B, 0.5mm in panel C.

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ferent MPTP treatment regimens, where mice performed as good or even better (referred to as so called ‘overshooting’) as their control groups, despite deficien-cies in the DAergic system (Meredith & Kang, 2006; Sedelis et al., 2001). A similar recovery may have also taken place in our low dose MPTP treated mice. There are several possible explanations for this effect. Since we do not see DAergic neu-ronal death in the SN of the low dose group, these neurons may have increased the production of DA during the recovery phase to compensate for the possible

Figure 5. MPTP treatment induces formation of α-synuclein inclusion in the SN. All panels represent the same image. A. Identification of mouse SN by TH immunoreactivity (green, arrows identify the decrease of TH staining in 25mg/kg MPTP treated animals). The images here are rep-resentative of three animals per each treatment group. B. Presence of α-synuclein (red) inclusion bodies is detected in the SN of 15mg/kg and 25mg/kg MPTP treated mice, but not in the saline injected mice (arrow heads). C. High magnification z stack confocal images of panels A and B illustrate in both MPTP dosage treated animals large α-synuclein immunoreactive puncta (arrow heads), large puncta present in the TH positive neurons (white arrows) and diffused α-synuclein staining in TH positive neurons (red arrows), . A few of the α-synuclein positive puncta can also be identified in the saline treated animals, but to a much lesser extent then in the MPTP treated animals. The scale bar in A represents 0.25 mm, and in C 20µm.


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loss of this neurotransmitter in the striatum. Such a compensatory mechanism has been previously reported and resulted in an increased transmitter-metabo-lite ratio in the striatum of MPTP treated mice (Schwarting et al., 1999; Yurek et al., 1989). Also, there may be an increase of DA receptors in the surviving stria-tal terminals, increasing the efficiency of DA uptake. One study illustrated that this effect indeed takes place three weeks after the MPTP treatment, which is in line with the onset of recovery in our study (Weihmuller et al., 1990). Lastly, the effect of neurotransmitter ‘volume transmission’ may play a role here, where the released DA diffuses over longer distances in the striatum and affects mul-tiple synapses throughout the structure. This effect has been described in MPTP treated cats (Schneider et al., 1994).

One of the hallmarks of PD is gradual and progressive gliosis in the affected SN (Langston et al., 1999; McGeer & McGeer, 2008). Both microgliosis and as-trogliosis have been reported in the human PD SN and in the monkey PD-MPTP model (Langston et al., 1999; Hirsch et al., 2003; McGeer & McGeer, 2008; Barcia et al., 2003). We observed a large increase in the number of reactive astrocytes and activated microglia in the SN of both the low and high dose MPTP treated an-imals. This has been previously corroborated for the 25mg/kg MPTP treatment (Alvarez-Fischer et al., 2008; Novikova et al., 2006; Schintu et al., 2009a; Schintu et al., 2009b). We are however the first to report that glial activation also occurs in the low dose MPTP treatment. Gliosis can either be a result of neuronal stress or can itself induce neuronal damage, for instance by secretion of pro-inflamma-tory cytotoxins by microglia (Hanisch, 2002). Schintu et al showed that the glial response preceded neuronal loss in the high dose MPTP-probenecid model, sug-gesting a causal role of the gliosis in the process of neurodegeneration (2009b). Indeed, the anti-inflammatory reagent rosiglitazone prevented neuronal loss in the SN, fully inhibiting microglial activation and partially reducing astroglial ac-tivation in these mice (Schintu et al., 2009a). Based on these reports, our data on the low dose MPTP group suggests that gliosis in the SN plays a prominent initi-ating role in the introduction of DAergic deficits after MPTP treatment, and may be sufficient to significantly reduce TH levels in the striatum.

The most intriguing finding of our study was the lack of a significant de-crease of TH levels in the SN of the low dose MPTP treated mice, suggesting that this treatment does not induce a loss of SN DAergic neurons. This is in contrast to the high dose regimen, where the loss of TH immunoreactivity is consistent with the reports of DAergic neuron loss after the application of MPTP (Meredith et al., 2009; Novikova et al., 2006). The phenotype of the low dose MPTP model (similar TH immunoreactivity in the SN compared to controls combined with gliosis in the SN, loss of the TH levels in the striatum and movement deficits) ap-pear to support the ‘dying back’ hypothesis of PD (reviewed in Cheng et al., 2010; Dauer & Przedborski, 2003; Burke & O’Malley, 2012). In this hypothesis, the TH-positive terminal loss in the striatum is the first neurodegenerative event in PD, which later induces neuronal degeneration in the SN. Evidence for this can be observed in different PD animals models such as in rats overexpressing human

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α-synuclein in the SN (Chung et al., 2009), in the α-synuclein (Tofaris et al., 2006) and LRRK2 transgenic mouse models (Li et al., 2009b), and in MPTP treated mice (Li et al., 2009a). The present low dose MPTP model might therefore represent an early PD-like phenotype expressing early PD pathology. The current observa-tions suggest that the SN DAergic neurons are initially stressed by the combined toxic effects of MPTP and gliosis and as consequence lose their terminal connec-tions in the striatum. Additionally, the presence of α-synuclein inclusion bodies, previously reported to be present in the 25mg/kg MPTP model (Meredith et al., 2002; Meredith et al., 2008) further supports early neuronal disfunction in this low dose model. It would be interesting to follow these animals for a longer pe-riod of time to asses whether these initial neurodegenerative events will even-tually lead to a more advanced neurodegenerative state in the SN and further induce neuronal loss in the ventral tegmental area (VTA). Advanced SN dam-age is indeed reported in two recent studies, which used similar 5 week MPTP treatment strategies, where severe degeneration of SN DAergic neurons was ob-served either 4 weeks post-treatment with 15mg/kg MPTP (Xu et al., 2010) or 12 weeks post-treatment with 12.5mg/kg toxin concentration(Ahmad et al., 2009). In the latter, a significant decrease of TH positive neurons in the VTA was also observed (Ahmad et al., 2009). These late stage data suggest that the combined effects of first time reported gliosis in the SN and observed loss of TH-positive terminals in the striatum directly after the low dose MPTP treatment period are sufficient to induce the main hallmark of PD- the loss of DAergic neurons in the SN. Interestingly, in contrast to our findings, the same low dose chronic MPTP treatment regimen in older, more sensitive mice (6-12 months old) resulted in a loss of TH positive neurons in the SN directly after the MPTP treatment (Lau et al., 2011; Barber-Singh et al., 2009). As age has been reported to play a dramatic role in the sensitivity to MPTP, with older animals being more vulnerable to this treatment (Jossan et al., 1989; Ricaurte et al., 1987; Przedborski et al., 2001), we hypothesize that the age difference between these two exeriments underlies this apparent discrepancy.

In conclusion, we have extensively characterized the immediate effects on neuropathology, gliosis and behavior in a PD mouse model induced by a 5-week 15mg/kg chronic MPTP-probenecid treatment. Immediately after the treatment period, this model is characterized by movement deficits, loss of TH-positive fi-bers in the striatum, and astro-gliosis and micro-gliosis in the SN without loss of DAergic neurons. Together, these neuropathological features closely resemble events associated with the ‘dying-back’ hypothesis in PD. This model may there-fore prove useful for the investigation of the early neurodegenerative events in the nigrostriatal DAergic system and shed more light on the molecular processes involved in the development of PD. Moreover, it can be an excellent tool to study the effects of potential treatment strategies that counteract the early cellular changes observed in Parkinson’s disease.

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CHAPTER 6

Comparison of AAV serotypes for gene delivery to

dopaminergic neurons in the Substantia Nigra

J.A. Korecka1, M. Schouten1, a, R. Eggers1, A. Ulusoy2, D.F. Swaab1, K. Bossers1, J. Verhaagen1

Viral Gene Therapy 2011, July; Ch: 10: 205-24, ISBN: 978-953-307-539-6, Intech


Amsterdam, The Netherlands2 German Center for Neurodegenerative Disease (DZNE), Ludwid-Erhard Allee 2, 53175,

Bonn, GermanyA Present address: Department of Structural and Functional Neuroplasticity, Center for

Neuroscience, Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH, Amsterdam, The Netherlands

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A AV SEROT Y PE COMPA R ISON IN MOUSE A ND R AT SN

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1. Introduction

Targeted viral vector-mediated gene transfer to specific population of neu-rons in the central nervous system (CNS) is a relatively novel, but fast develop-ing approach to study gene function in a number of neurodegenerative diseases (Manfredsson and Mandel, 2010; Korecka et al., 2007). Moreover, several early phase clinical trials based on viral vector-mediated therapeutic gene transfer have been completed or are underway for neurological disorders (Tuszynski et al., 2005; Marks, Jr. et al., 2010; Korecka et al., 2007; Kaplitt et al., 2007; Kaplitt et al., 2007; Muramatsu et al., 2010). Gene therapy is especially attractive for dis-eases where neuronal degeneration is largely restricted to a single neuronal pop-ulation in a specific anatomical area. Parkinson disease (PD) is a neurodegenera-tive disease mainly characterized by a progressive degeneration of dopaminergic (DAergic) neurons in the Substantia Nigra (SN) (Dauer and Przedborski, 2003). It would be desirable to direct transgene expression to the dopaminergic neurons in animal models for neurodegenerative diseases, allowing for a range of investi-gations into the function of that gene in normal, adult DAergic neurons or follow-ing neurotoxic insult.

Lentiviral vectors (LV) and adeno-associated viral vectors (AAV) are in-creasingly regarded as the two most useful gene therapy vectors for the CNS. Both vectors have been successfully used to express a foreign gene in a variety of brain regions and neuronal cell types (Manfredsson and Mandel, 2010; Papale et al., 2009; Lim et al., 2010; Schneider et al., 2008). LV vectors have been shown to direct long-lasting expression of a number of transgenes in the brain (Lundberg et al., 2008) including in neurons in the rat SN (Deglon et al., 2000). AAV vectors are considered to be the most appealing vectors for transgene expression in the CNS, due to their efficient neuronal transduction, their capacity to direct long-term transgene expression and their safety profile (McCown, 2005; Mandel et al., 2006; Kaplitt et al., 2007). The early AAV vectors were based on AAV serotype 2 (Kaplitt et al., 1994; Peel and Klein, 2000), but subsequent vectors have been generated with novel serotypes that differ in their tissue and cellular tropism (Wu et al., 2006).

So far, three studies engaged in exploring the possibility of AAV transgene expression in the mouse SN. In two studies only AAV vectors based on serotype 2 were used inducing either alpha-synuclein (St Martin et al., 2007) or dual leucine zipper kinase (Chen et al., 2008) expression in the DAergic neurons of the mouse SN. In the third study AAV serotypes 1, 2, 5, 7 and 8 were injected into the mouse SN and compared for their tropism for DAergic neurons (Taymans et al., 2007). Although, AAV1 and 5 displayed the most promising transduction rates, this data was qualitatively assessed. In contrast, the rat dopaminergic system has been studied much more extensively with five studies investigating the performance of various AAV serotypes tropism. These studies compared the levels of GFP ex-pression in the rat SN after injection of AAV vector serotype 1, 2 and 5 (Burger et

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al., 2004; Paterna et al., 2004), AAV8 (McFarland et al., 2009; Klein et al., 2006), and AAV9 and 10 (Klein et al., 2008). A general conclusion for all these studies es-tablishes AAV2 as the lowest transducing vector of dopaminergic neurons in the rat SN. Finally and most recently, one AAV serotype study has been performed in primate CNS, where AAV1 to 6 viral vectors were injected into the SN (Markakis et al., 2010). In the primate AAV5 displays the most promising transduction of neurons in this area.

In the following study, we have compared multiple AAV serotypes for trans-duction of mouse and rat mesencephalic DAergic neurons. AAV vectors were de-veloped to contain either a cytomegalovirus (CMV) promoter or the human syn-apsin 1 (SYN) promoter. We demonstrate that the synapsin promoter leads to higher nigral transduction compared to the CMV promoter in mice. Additionally, we also show AAV serotype 5 and 7 give the highest transduction rate of DAergic neurons in the mouse SN, where as rat SN can be equally well transduced with all serotypes tested. We compare our study with the published data and underline the differences in the methodology and outcome measures.

2. Methods

2.1 AAV constructs and production

Lentiviral vectors were produced as described before (Hendriks et al., 2007). Two plasmids, designated pTRCGw and pTRUF20B-SEW, were used for the production of AAV. The pTRCGW plasmid contained inverted terminal repeats of AAV2 flanking a cytomegalovirus (CMV) promoter driving expression of GFP, a woodchuck hepatitis virus posttranscriptional regulatory element (WPRE), and a polyadenylation signal (Ruitenberg et al., 2002). The second plasmid, des-ignated pTRUF20B-SEW, was a generous gift from Prof. Deniz Kirik (Lund Uni-versity, Sweden). This plasmid also contained two inverted terminal repeats of AAV2 flanking a human synapsin 1 (SYN) promoter driving expression of GFP, a WPRE, and a polyadenylation signal. For the production of different serotypes helper plasmids were used provided by J.A. Kleinschmidt (AAV1 to 6) (Grimm et al., 2003) and J.M. Wilson (AAV7 and 8) (Gao et al., 2002). For each serotype eight 15 cm petridishes containing 1x107 HEK293T cells were transfected with the use of polyethylenimine (PEI, MW25000; Polysciences Inc., Warrington, PA, USA). Cells were grown in Dulbecco’s modified Eagle’s medium (DMEM) contain-ing 10% fetal calf serum (FCS) and 1% penicillin/streptomycin (GIBCO-Invitro-gen Corp, New York, NY, USA). pTRCGW or pTRUF20B-SEW AAV plasmids were cotransfected with packaging plasmids in different ratios as follows: AAV1 to 6 in a ratio of AAV plasmid over capsid plasmid 1:3 with a total amount of 50µg of DNA per plate, and AAV7 and 8 in a ratio of 1:2:2 of AAV plasmid over help-er plasmid pAd∆F6 and capsid plasmid with total amount of 62.5µg of DNA per plate. Two days after the transfection cells were harvested in D-phosphate buff-


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ered saline (PBS) (Gibco) containing 10µg/ml DNAseI (Roche Diagnostics GmbH, Mannheim, Germany) and incubated for 1 hour at 37°C. Cells were lysed by three freeze-thaw cycles, spun down 30 min at 4000rpm and crude lysate was col-lected. Virus was purified by the iodixanol gradient ultra-centrifugation method (Zolotukhin et al., 1999; Hermens et al., 1999), diluted in D-PBS/5% sucrose and concentrated using Amicon 100kDA MWCO Ultra-15 device (Millipore, Billerica, MA, USA). All AAV vectors were stored at -80°C until use. Titers were determined by repeated quantitative PCR for viral genomic copies extracted from DNAse-treated viral particles using WPRE directed primers (forward: CAGGTGTATTGC-CACAAGACAAA and reverse: TGCACAGGTGAAGACCAAGCAA). Table 1 provides an overview of all viral stocks and their titers used in this study.

2.2 Experimental animals and surgical procedures

A total of 43 male C57BL/6 mice weighing 20-25g and 16 female Sprague-Dawley rats weighing 200-250g were used (Harlan, Zeist, The Netherlands). Ani-mals were housed with food and water ad libitum, with 12 hour light and dark cycles. All the experimental procedures and postoperative care was carried out in accordance with the local animal experimental ethical committee.

The viral injections were carried out with the use of glass capillaries (0.78/1.0mm internal/external diameter; Harvard Apparatus, Holliston, MA, USA) with an 80µm tip. These glass capillaries were connected to Portex poly-ethylene tubing in turn connected to a Hamilton syringe fixed in a micro-infu-sion pump (PHD2000, Harvard Apparatus). The system was filled with water and a target volume of 1µl and an infusion rate of 0.2µl/min was set for mice in-jections and target volume of 2µl and an infusion rate of 0.4 µl/min for rats. The glass needles were mounted on a stereotactic device (David Kopf Instruments, Tujunga, CA, USA). A total of 1.1µl of virus was loaded for mice and 2.3 µl for rats for each injection separately.

Mice were intraperitoneally (IP) injected with FFM mix made of Hypnorm (0.1 mg/kg Fentanyl citrate/ 3.3 mg/kg Fluanisone HCl, Janssen Pharmaceuti-cals) and Dormicum (8.3 mg/kg Midazolam, Roche) and placed into a stereotac-tic device where they were fixed and the skull was exposed. The skull was lev-eled based on the heights of bregma, lambda and two additional and very crucial lateral measurements of 2.0 mm from bregma. The injection coordinates were calculated from bregma with anterior posterior (AP) being -2.8 mm and lateral (L) -1.3 mm. Ventral dorsal (VD) coordinate was measured from the dura of ei-ther -4.1, -4.2 or -4.3 mm depending on the viral injection (see table 1). Subse-quently, the needle was lowered into the brain 0.1 mm below the VD coordinate and retracted back up to the correct level. After the infusion, the needle was left in place for 5min before retraction.

Rats were anesthetized by intramuscular injection of 0.08ml/100g of Hyp-norm and mounted in the stereotact. The skull level was controlled by measure-ment of bregma and lambda. 2µl of each AAV virus was injected at the following

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coordinates with VD being measured from dura: AP -5.2, L -2.0, and VD 7.2 (Ulu-soy et al., 2009).

All of the animals recovered on a heating pad at 37°C and were allowed to survive for 4 weeks post surgery after which they were sacrificed by an IP over-dose with Pentobarbital (50mg/µl) and transcardially perfused with 0.9% saline followed by 4% paraformaldehyde (PFA, Sigma-Aldrich Co., St. Louis, MO, USA) in PBS pH 7.4. The brains were further post-fixed overnight and 4 series of 30µm thick coronal sections were cut on a vibratome. The sections were stored free-floating at 4°C in 1% PFA in PBS pH 7.6.

2.3 Immunohistochemistry and histological quantification

All immunohistochemical (IHC) stainings were performed on free-floating sections. Prior to the staining, one series of sections was pre-blocked in 1x tris buffered saline (TBS) (Sigma) with 2.5% fetal calf serum (FCS) and 0.2% Triton-X (Sigma) for 1 hour at room temperature. Sections were then incubated with anti-tyrosine hydroxilase (TH) rabbit polyclonal antibody (Institute Jacques Boy SA, Reims, France) at 1:1000 dilution in blocking buffer and anti-GFP (Millipore) chicken monoclonal antibody at 1:1000 for 1 hour at room temperature followed by overnight incubation at 4°C. Secondary goat anti-rabbit antibody Alexa 594 (1:800, Invitrogen, Carlsbad, CA, USA) was used for the detection of the TH an-tibody and donkey anti-chicken Alexa 488 (1:800, Invitrogen) for the detection of the GFP antibody. These antibodies were incubated for 1 hour at room tem-

Serotype Titer (GCs/ml)

Injection coordinates in mice

Injection coordinates in rats

LV-CMV 9.0x10^9 AP -2.8, L -1.3, VD -4.2

AAV1-CMV 6.6x10^12 AP -2.8, L -1.3, VD -4.1

AAV2-CMV 1.0x10^12 AP -2.8, L -1.3, VD -4.1

AAV5-CMV 7.1x10^11 AP -2.8, L -1.3, VD -4.1

AAV6-CMV 1.5x10^12 AP -2.8, L -1.3, VD -4.1

AAV7-CMV 3.2x10^12 AP -2.8, L -1.3, VD -4.2

AAV8-CMV 9.9x10^11 AP -2.8, L -1.3, VD -4.1

AAV5-SYN*** 1.2x10^13 AP -2.8, L -1.3, VD -4.3 AP -5.2, L -2.0, VD -7.2

AAV6-SYN 3.7x10^12 AP -2.8, L -1.3, VD -4.3 AP -5.2, L -2.0, VD -7.2



Table 1. Viral vectors, titers and injection coordinates. All AAV batches have a similar range of ti-ter with an exception of AAV5-SYN, which has a significantly higher titer than the other AAV-SYN viruses (after multiple testing, P<0.001, one way ANOVA). The injection coordinates are indicated for mice and rats respectively. Abbreviations: CMV- cytomegalovirus, SYN-synapsin, GCs/ml- ge-nomic copies per milliliter, AP- Anterior Posterior, L- lateral, and VD- Ventral Dorsal distances from bregma.


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perature. Sections were then mounted on chrome-aluin and gelatin coated glass slides.

Images were acquired with an Axioplan microscope (Zeiss, Sliedrecht, The Netherlands). Images for quantification of the transduced neurons of the SN were taken at 10x magnification for mice and 5x magnification for rats with fixed ex-posure times for both TH and GFP signal. The sections of the striatum area were photographed at 2.5x magnification also with fixed exposure times for both TH and GFP fluorescent signal.

ImagePro Plus Fluorviewer software (Media cybernetics, Bethesda, MD, USA) was used for the SN transduction quantification. All TH-positive neurons were manually counted in a single-blinded setup. Furthermore, TH and GFP co-localization was assessed using cellular morphology and fluorescent intensity parameters. For each section the percentage of GFP-positive and TH-positive cells was determined and all values from all of the sections were averaged to give the total percentage of colocalized cells in the whole structure. In the AAV-SYN comparison study one animal in AAV8 group, which the injection had missed the SN structure, was excluded from further statistics unless specified. Caudate quantification was performed with the use of ImagePro Plus Measure Threshold macro. The striatal areas in both hemispheres were outlined based on the TH ex-pression in the striatal fibers. The average GFP background signal measured in cortex areas in both hemispheres was subtracted from each ipsilateral striatum signal. Next, the recalculated intensity from the non-injected striatum was sub-tracted from the injected side. Finally, this average intensity value in the injected striatum was multiplied by the size of the area resulting in total GFP intensity of the measured area.

3. All AAV serotype vectors with the CMV promoter direct poor transgene expression in DAergic neurons of the mouse SN

Vectors based on AAV serotypes 1, 2, 5, 7, 8 and LV that contained the CMV-GFP expression cassette were injected into the mouse SN. Four weeks after the injection, the number of TH-positive neurons expressing GFP was quantified. All AAV serotypes and the LV vector showed very low numbers of transduced TH-positive neurons (Figure 1B). AAV7 directs the highest transduction rate with 8% of the TH-positive SN cells expressing GFP. Most of the serotypes, with the exception of AAV2, showed high rates of cellular transduction in and around the SN, but the transduced neurons were TH-negative (Figure 1A). AAV1 and LV also transduced glial cells particularly in the area directly surrounding the injection site (data not shown). Glial transduction has not been observed with any other AAV serotypes.

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Three groups have reported on AAV-mediated gene transfer to the mouse SN (Taymans et al., 2007; St Martin et al., 2007; Chen et al., 2008). Experimental details, including the serotype and promoter used in these studies are summa-rized in Table 2.

A comparative analysis of AAV1, 2, 5, 7 and 8 showed efficient transduction of cells in the SN area (Taymans et al., 2007). AAV 1 and 5 showed robust GFP expression in the fibers of the striatum. In contrast AAV7 and 8 directed only low GFP levels in this projection area of the SN DAergic neurons. Additionally, a few GFP positive cells were observed in the striatum in all of the serotypes. Consistent with our observations, AAV2 showed poor transgene expression in the SN. The efficiency of AAV-CMV driven GFP expression was assessed quali-tatively and no specification of the DAergic lineage of the transduced cells was performed. We have also found high numbers of GFP expressing cells with AAV-CMV vectors in and around the SN, however, quantification of the TH-positive GFP-labeled cells revealed very low numbers of GFP expressing DAergic neurons in the SN (Figure 1).

The other two studies, performing AAV mediated gene transfer in mouse SN used only serotype 2. In the first study, injection of AAV2 into the SN showed between 10 and 80% of TH-positive neurons that express GFP in individual sec-tions (St Martin et al., 2007). In the second study AAV2 was injected into the pos-

Figure 1. AAV-CMV-mediated GFP expression in the mouse Substantia Nigra. A. Confocal Z-stack image of an immunohistochemical staining of the mouse SN showing GFP transgene expression in a small number of dopaminergic neurons identified by TH staining (arrows indicate the double labeled cells) but also in non-dopaminergic neurons (arrowheads) after AAV6-CMV injection. TH neurons are shown in red, GFP is shown in green. The scale bar indicates 50µm. B. Quantification of transduced DAergic neurons in the mouse SN (n=3) using LV-CMV-GFP and AAV-CMV-GFP viral vectors. The bars represent the percentage of TH positive neurons in the SN expressing GFP. AAV7 shows the highest transduction of 8% of DAergic neurons in the SN. Error bars indicate the SEM.


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terior SN, which resulted in transduction of 71.1±6.0% of TH-positive neurons (Chen et al., 2008). The number of GFP transduced cells in both of these stud-ies is much higher compared to our study, where AAV2-CMV led to the lowest transduction rate of SN neurons. Although both studies used slightly different injection coordinates than we did, it is unlikely that this caused significant dif-ferences in AAV2 transduction efficiencies. The most likely explanation for this difference is the use of the chicken β-actin (CBA) promoter, a promoter known to drive stronger and more persistent expression in several population of neurons (Fitzsimons et al., 2002). Unfortunately there were no other serotypes used in these studies.

4. AAV vectors that harbor the synapsin promoter di-rect high-level transgene expression in dopaminergic neurons of the mouse SN

Based on our results and the available literature, the CMV promoter ap-pears to direct less efficient transgene expression in different cell types, includ-ing striatal neurons (Jakobsson et al., 2003), cochlea cells (Liu et al., 2007), hu-man embryonic stem cells (Orban et al., 2009) and finally rat SN neurons (Wang et al., 2005; Paterna et al., 2000). Therefore we conclude that the CMV promoter leads to a limited transduction in the mouse SN and may not be suitable to drive viral vector-mediated transgene expression in the DAergic neurons of the mouse SN. The human synapsin 1 promoter, on the other hand, has been shown to be an excellent neuron specific promoter in co-cultured primary hippocampal neurons isolated from embryonic brain (Kugler et al., 2003b), in primary dorsal root gan-glion cultures (Sims et al., 2008) and in vivo following injection of an adenoviral vector in rat brain, including the SN (Kugler et al., 2003a; Kugler et al., 2003b; Hermening et al., 2006). We therefore produced 4 AAV vectors (AAV5, 6, 7 and 8) that harbored a GFP reporter gene under the human synapsin 1 promoter. The performance of these AAV vectors was tested in mice and rats after injection in the SN.

Study Viral vector used Analysis parameters Used promoterTaymans et al., 2007 AAV1, 2, 5, 7 and 8 GFP expression in the SN

& the striatumCMV

St Martin et al., 2007 AAV2 GFP and TH colocalization in the SN

CBA

Chen et al., 2008 AAV2 GFP and TH colocalization in the SN

CBA

Table 2. Summary of literature reports using AAV vectors for gene transfer in mouse SN.

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4.1. AAV-synapsin-GFP drives transgene expression in tyrosine hy-droxylase positive neurons.

Vectors based on AAV serotypes 5, 6, 7 and 8 that contained a SYN-GFP ex-pression cassette were injected in the SN in the same fashion as the AAV-CMV-GFP viral vectors. All serotypes directed GFP expression in neurons throughout the midbrain, including the SN. AAV7 injected mice showed the most widespread viral transduction with GFP-positive neurons in multiple midbrain areas (data not shown).

Subsequently, we specifically investigated the transduction efficiency of DAergic neurons of the SN. Immunohistochemical staining showed that all sero-types transduce TH positive neurons in the mouse SN (Figure 2). Interestingly, the level of GFP expression in the individual TH positive cells appears to be lower than in other TH-negative neurons in the SN area. This was also observed fol-lowing transduction with AAV-CMV vectors. In addition, large numbers of GFP positive fibers were observed in the SN. Based on cellular morphology, no other cell types expressed GFP. This indicates that the AAV-SYN-GFP construct drives neuron-specific expression.

4.2. AAV5 and AAV7 mediate the highest transduction of TH positive neurons in the mouse SN

Quantification of the number of TH-positive and GFP-positive neurons in the SN demonstrated a much higher proportion of double labeled neurons with all AAV-SYN vectors compared to the AAV-CMV vectors. AAV5 and AAV7 lead to significantly higher percentage of the GFP labeled DAergic neurons compared to AAV6 and AAV8. These two serotypes directed GFP expression in 76-80%of TH-positive neurons (Figure 3A). The homogeneous distribution of the TH and GFP-positive neurons from the posterior to the anterior side of the SN corroborates the superiority of AAV5 and AAV7 compared to AAV6 and AAV8 at each anatomi-cal level (figure 3B, for more details see supplementary figure 1).

In conclusion, AAV5-SYN and AAV7-SYN are the most effective vectors for transduction of DAergic neurons in mouse SN. Interestingly, even though AAV5 had a significantly higher titer in comparison to AAV7, it transduces a compa-rable number of DAergic neurons throughout the SN. In contrast, AAV8 injected animals, apart from a relatively low total percentage of TH and GFP-positive neu-rons, display a decrease in the number of these neurons in the anterior portion of the SN. AAV6 shows quite poor transduction efficiency throughout the SN. This is in accordance with the relative low overall percentage of TH-positive neurons that express GFP (Figure 3A).


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Figure 2. GFP expression in AAV-SYN injected mouse SN. GFP stained (green) and TH stained (red) neurons are visualized in confocal images. Arrows point to examples of GFP positive and TH positive cells in all viral serotypes. A. AAV5-SYN-GFP; B. AAV6-SYN-GFP; C. AAV7-SYN-GFP; and D. AAV8-SYN-GFP. The scale of 50µm is represented by a bar in panel A.

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4.3. AAV7 shows the most GFP positive fibers ascending through the nigrostriatal tract

The DAergic neurons of the substantia nigra anatomically project to the striatum creating the nigral-striatal pathway. Accordingly, when the DAergic neurons in the substantia nigra are transduced their fibers in the striatum are expected to be GFP positive. To investigate this relationship, we have quantified the intensity of GFP fluorescent signal in the mouse striatum and compared this to the effectiveness of the AAV serotypes to target the DAergic neurons in the SN (Figure 4). While AAV5-SYN-GFP and AAV7-SYN-GFP display a high fluorescence intensity of GFP, AAV6-SYN-GFP and AAV8-SYN-GFP show a low level of GFP ex-pression in the striatum. Furthermore, AAV7-SYN directs significantly higher levels of GFP expression in the striatum compared to AAV5-SYN (Figure 4 E). Moreover, we have found a significant correlation between the transduction ef-ficiency of the SN and the labeling intensity of the fibers in the striatum (Figure 4F). This corroborates the superiority of the AAV7 and AAV5 serotypes in trans-ducing DAergic neurons in the mouse SN.

Figure 3. AAV-SYN-GFP transduction of mouse SN. A. Quantification of TH positive (TH+) and GFP positive (GFP+) neurons in mouse SN transduced with different AAV serotypes. In the AAV5 and AAV7 groups, almost 80% of TH+ neurons express GFP, which is significantly higher than the AAV6 group where < 20% of the DAergic neurons are GFP positive (P<0.001), and the AAV8 group where 35% of the DAergic neurons express GFP (P<0.01). B. Quantification of GFP expressing TH+ cells per serotype in SN serial sections arranged according to the Allan Brain Atlas TH in situ hybridization (Lein et al., 2007) with 1 being most posterior and 8 being the most anterior part of the SN (supplementary figure 1). Throughout the groups there was no statistical significant differ-ence between AAV5 and AAV7, however in section groups 2, 4, 5, 6 and 7 AAV7 showed signifi-cantly higher average of GFP+/TH+ cells than the other two serotypes (* P < 0.05, ** P < 0.01, *** P < 0.001), where as in section 3 only comparing to AAV6 (P < 0.01). AAV5 showed a significantly higher GFP expression in comparison to AAV6 and AAV8 serotypes in section groups 4, 5, 6, 7 and 8 and in section 2 and 3 to AAV6 only. AAV8 shows significantly higher GFP expression to AAV6 in group 3 and 4 (* P < 0.05, **P < 0.01, *** P < 0.001).


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Figure 4. GFP expression in the mouse striatum after SN AAV transduction. A-D. Mouse striatal sections stained with anti-TH (red) and-GFP (green) antibody transduced with different AAV sero-type. The scale bar represents 1mm. E. Quantification of GFP fluorescent intensity in all AAV-SYN serotypes. Each striatal section was measured for GFP intensity and corrected for the measured area (gray level*mm2). Statistical analysis indicates AAV7-SYN-GFP results in the highest GFP expression in the striatum, with AAV5 inducing the second best expression (*P<0.05, **P< 0.01 and ***P<0.001). F. The percentage of TH+ neurons expressing GFP in the SN and the level of GFP fluorescence in the striatum are significantly correlated (Pearson correlation, R2=0.729, P<0.001). Each individual animal belonging to a specific AAV serotype injection group is depicted by differ-ent marker described in the figure legend. Animal with missed injection in AAV8-SYN group (as described in Methods section) was also included in this analysis.

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Taken together, these observations demonstrate that AAV7-SYN is the best vector for the transduction of TH-positive neurons of mouse SN among the test-ed serotypes regarding the specificity and the transduction rate. Although both AAV5 and AAV7 effectively transduced large numbers of TH-positive neurons in the SN, AAV7 showed significantly higher GFP expression in the striatum. Injec-tion of AAV7-SYN also resulted in a substantial transduction of other neurons in the midbrain. This indicates that AAV7 spreads further than other serotypes and/or has a more ubiquitous neuronal tropism in the mouse brain. It would be worthwhile to investigate whether it is possible to more specifically target only DAergic neurons in the SN by e.g. lowering the volume of the viral vector solution that is injected into the SN. Finally, we have not seen any signs of toxicity follow-ing the injection of high titer AAV vectors in the mouse brain.

5. All AAV-vectors harboring the synapsin promoter direct similar level of transgene expression in the rat SN and the striatum

5.1. All AAV-synapsin serotypes show similar GFP expression throughout the rat SN.

Female Sprague-Dawley rats were injected with AAV-SYN-GFP viral vec-tors 5, 6, 7 and 8 into the SN. The viral stocks used were the same as in mouse SN injections. To estimate the transduction efficiency, the TH-positive and GFP-positive neurons of the SN were quantified in the same fashion as described in the mouse study. All AAV serotypes showed similar numbers of GFP-positive neurons in the rat SN (Figure 5A) with no significant differences between the serotypes. For AAV5 and AAV7 the proportion of transduced TH-positive neu-rons is lower in the rat SN compared to the mouse SN. AAV6 directed transgene expression in a higher proportion of DAergic neurons in the rat SN (27%) than in mouse SN (16%), whereas AAV8 shows slightly higher number of GFP-positive neurons in the mouse SN (36%). These results suggest differential AAV tropism for DAergic neurons in rats comparing to mice.

Analysis of the distribution of the GFP-positive neurons within the SN also shows no major differences between the AAV serotypes (Figure 5B) except for two anatomical levels where AAV5 shows significantly higher amount of TH-positive and GFP-positive cells when compared to AAV7 in section 1, and AAV7 shows more GFP-positive DAergic neurons when compared to AAV8 in section 8. Although significant, these differences are not prominent enough to allow us to speculate on either of the serotype superiority in transducing rat DAergic neu-rons.


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5.2. All AAV-SYN serotypes show GFP expression in the fibers of the rat striatum

As in the mouse study, we have quantified the intensity of GFP signal in the rat striatum to compare the effectiveness of AAV serotype transduction of the rat SN anatomical projection (Figure 6). All AAV serotypes showed similar, relatively high levels of GFP expression in the striatum (Figure 6E). A correla-tion analysis revealed a significant correlation between the numbers of TH and GFP-positive neurons and the levels of GFP expression in striatum (Figure 4F). This further supports that all AAV serotypes are equally effective in targeting rat substantia nigra DAergic neurons. In addition, we have observed a transduc-tion of the globus pallidus fibers by AAV5 and AAV7 serotypes. This may suggest more spread of these viral vectors in the rat brain.

Figure 5. AAV-SYN-GFP transduction of rat SN. A. Quantification of TH positive (TH+) and GFP positive (GFP+) neurons in rat SN transduced by different AAV serotypes. All serotypes showed similar GFP expression in about 30-40%of DAergic neurons. B. Quantification of GFP expressing TH-positive cells per serotype in the SN serial sections arranged in posterior-distal direction ac-cordingly to the ‘The rat brain atlas’ by Paxinos and Watson (2007) (arrangement was based on the stereotact anatomical slides and adjacent Acetylcholinesterase (AChE) stainings with 1 being most posterior area and 8 being the most anterior area of the SN (supplementary figure 2)). All of the serotypes show similar GFP distribution within the SN structure with two exceptions: section 1 shows AAV5 expressing significantly higher amount of GFP + in TH+ cells comparing to AAV7 (* P < 0.05) and section 8 where AAV7 has greater amount of GFP+ DAergic cells than AAV8 (* P < 0.05).

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Figure 6. GFP expression in the rat striatum after SN AAV injection. A-D. Rat striatal sections stained with anti-TH (red) and-GFP (green) antibodies. The scale bar represents 1mm. E. GFP fluo-rescent intensity quantification in the striatum for all AAV-SYN serotypes. Whole striatum was cut, stained and each section was measured for GFP intensity and corrected for the measured area (gray level*mm2). Statistical analysis shows no differences in GFP expression levels between the different AAV serotypes. F. The percentage of TH+ neurons expressing GFP in the SN and the level of the GFP fluorescence in the striatum are significantly correlated (Pearson correlation R2=0.357, P<0.05). Each individual animal belonging to a specific AAV serotype injection group is depicted by different marker described in the figure legend.


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5.3. AAV7 viral vector injection decreases the amount of TH-positive cells in the rat SN.

We observed a > 50% decrease of number of TH-positive neurons in rat SN after AAV7 injection when compared to the non injected contra-lateral side of the structure (Figure 7). We also studied the expression of vesicular monoamine transporter-2 (VMAT2), another DAergic phenotype marker, and found its pro-tein levels also strongly decreased in the injected SN (data not shown). Interest-ingly, the number of TH-positive and GFP-positive neurons in the SN is not less than in the other serotypes (Figure 5) as well as the intensity of GFP-positive fibers in the striatum (Figure 6).

Figure 7. AAV7 decrease of TH immunohistochemical signal in rat SN. All of the images were obtained from the same brain section. A. and C. Rat SN injected with AAV7-SYN-GFP B. Contra-lateral non injected side of the rat SN. Section was stained for TH (red), a nuclear marker Hoechst (blue) and GFP (green). The scale bar in panel C represents 0.5mm. D. Quantification of the TH positive neurons in the rat SN after AAV7 transduction. TH positive neurons were counted in both the AAV7 injected side of the SN and the contra-lateral side in each section. One way ANOVA indicated a significant decrease of TH+ neurons in the AAV7 injected SN (** P < 0.01).

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6. Discussion & concluding remarks

Targeted gene delivery to mesencephalic DAergic neurons can be a very valuable approach to study the molecular mechanisms that underlie the devel-opment and progression of PD. Gene delivery to DAergic neurons has also a po-tential to evolve into a new therapeutic strategy for PD. In this study we have compared the capacity of multiple AAV serotypes to deliver a reporter gene to DAergic neurons in the adult mouse and rat SN. We have quantified the trans-duction efficiency of AAV vectors harboring two different promoters: the CMV and human synapsin 1 (SYN) promoter. We have demonstrated that following stereotactic injection of vectors containing the SYN promoter, a large number of DAergic neurons express GFP in the mouse as well as the rat SN. AAV7 is the most effective serotype for transduction of mouse SN DAergic neurons. AAV5 also dis-played high transduction efficiency for TH-positive neurons, but the GFP expres-sion levels in the striatum were consistently lower when compared to AAV7. In the rat, all AAV-SYN vectors efficiently transduced DAergic neurons in the SN. AAV vectors containing the CMV promoter directed expression only in a small proportion of TH-positive SN neurons in mice, thereby demonstrating superior-ity of the synapsin promoter in this specific neuronal subtype. Collectively, these observations are useful for future experiments that aim to study the function of specific genes in the mesencephalic DAergic system.

So far, one study has compared five AAV serotypes (AAV 1, 2, 5, 7 and 8) for gene delivery to the mouse SN (Taymans et al., 2007). All vectors, except for AAV2, showed positive transduction of the SN area, with AAV1 and AAV5 im-plicating to direct highest levels of GFP in the striatal fibers. This study did not show quantifications of the numbers of GFP and TH-positive neurons and GFP expression in striatal fibers, and can therefore not be directly compared to our study.

For the rat SN, the four tested AAV serotypes directed equally efficient transduction in DAergic neurons. In comparison, AAV5 and AAV8 appear to dis-play the most consistent transduction efficiencies in the literature (Klein et al., 2006; Paterna et al., 2004; McFarland et al., 2009). Additionally, AAV9 and AAV10 have also been tested and indicated to have higher tau expression in the SN area and higher TH neuronal loss evoked by tau expression comparing to AAV2 and AAV8 (Klein et al., 2008). These observations in combination with our results indicate that multiple AAV serotypes share relatively high tropism for DAergic neurons of the rat SN.

In the mouse SN, AAV vectors with the SYN promoter were superior to the AAV vectors containing the CMV promoter. In contrast, in the rat, a range of pro-moters have been used very successfully to direct the transgene expression in the DAergic neurons of the SN via an AAV vector including the CMV (McFarland et al., 2009), CBA (Ulusoy et al., 2009; Burger et al., 2004; Paterna et al., 2004; Klein et al., 2006; Klein et al., 2006), CMV/CBA hybrid (Klein et al., 2008) and


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PDGV (Paterna et al., 2000)) promoters. This suggests that for experiments in the rat the choice of the promoter is not as critical as it appears to be for the mouse.

Following AAV7-SYN-GFP injection, a dramatic decline in TH and VMAT2 expression occurred in the DAergic neurons in the rat SN. Klein et al. also ob-served a decrease in the number of TH-positive cells following high titer AAV8-GFP application, but not after AAV8-empty vector. Moreover, following the ap-plication of lower AAV8-GFP viral titer, no decrease of TH signal was noted. Therefore the authors suggest that the high concentrations of GFP can be neuro-toxic to the DAergic neurons of the rat SN (Klein et al., 2006). Ulusoy et al. also re-ported a neurotoxic effect of high titer AAV5-GFP viral vectors. In this study not only TH was diminished, but also the expression of VMAT2. In subsequent ex-periments with low titer AAV5-GFP injections this effect was not seen anymore (Ulusoy et al., 2009). We speculate that in our case, the high tropism of AAV7 for DAergic neurons induces more GFP expression, and as a consequence causes DAergic neurotoxicity. We do not see this effect on TH expression in mice SN af-ter the AAV7 injection.

As presented here, the specifications of the delivery vehicle can be crucial for successful and accurate cellular transduction. We have demonstrated that targeting SN in the mouse is difficult and could only be successfully achieved in our set up with AAV serotypes 7 and 5 harboring the SYN promoter. In contrast targeting rat SN can be efficiently achieved by multiple AAV viral vectors. It is therefore necessary to determine the vector potential for each animal species before pursuing genetic manipulation in the DAergic system. This can also be valid for human clinical PD gene therapy studies. So far AAV2 has been the only vector injected into the human brain as a delivery vehicle for PD gene therapy (Muramatsu et al., 2010; Marks, Jr. et al., 2010; Kaplitt et al., 2007). As discussed before, AAV2 seams to be the least efficient vector in the transduction of DAer-gic neurons in the rodent brain. Understandably human serotype studies are not possible, but primate studies may shed more light on the transduction efficiency of different delivery vehicles and can improve the efficiency of the gene therapies dramatically. One such study has recently indicated AAV5 to be the most effi-cient in transducing neurons in the area of SN but also glial cells, whereas glial transduction by AAV5 is not observed in the rodent brain (Markakis et al., 2010). This clearly illustrates the differences between viral vector transduction prefer-ences between animal species.

Another major concern at the moment in the field of gene therapy is the specification of the target area. Two of the above mentioned clinical studies have targeted the putamen of PD patients (Muramatsu et al., 2010; Marks, Jr. et al., 2010) and one the subthalamic nucleus (Kaplitt et al., 2007). Depending on the function of the target gene, the location of the target area is crucial for successful therapeutic application. It is therefore rational to apply gene therapy for dopa-mine synthesis enzymes such as AADC to the putamen to increase the dopamine production at that area to alleviate the motor-related clinical symptoms (Mu-

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ramatsu et al., 2010). On the other hand, it may not be as beneficial to induce an expression of a neurotrophic factor in the area not significantly affected by neuronal death (Marks, Jr. et al., 2010). It was therefore extensively discussed and suggested for the future to target the SN DAergic neurons when applying pro-survival and regenerative therapeutic agents (Benabid, 2010; Marks, Jr. et al., 2010). Concluding, it is therefore necessary to apply the right vectors in the specific animal species and target the appropriate area of interest, depending on the function of the expression gene, for the most effective targeted gene delivery.

7. Acknowledgements

The work presented in this paper was funded by Top Institute Pharma, Leiden, The Netherlands, project T5-207

8. Supplementary Figures

Supplementary figure 1. Quantitative overview of AAV-SYN-GFP transduction throughout the mouse SN in 4 different viral serotypes. A. The sorting of SN anatomical areas through section groups 1-8 is based on a TH in situ hybridization presented by the Allen Brain Atlas (Lein et al., 2007). Section group 1 is the most posterior group and section group 8 the most anterior. B-E. Quantification of SN AAV transduction throughout the structure in 4 different viral serotypes in individual animals. Values represent mean of all quantified sections belonging to the sorted sec-tion group and their SEM.


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Supplementary figure 2. Quantitative overview of AAV-SYN-GFP transduction throughout the rat SN in 4 different viral serotypes. A. The sorting of SN anatomical areas through section groups 1-8 is based on the anatomical AChE stainings presented by ‘The rat brain atlas’ by Paxinos and Watson (2007). Section group 1 is the most posterior group and section group 8 the most anterior with indicated distances from the bregma. B-E. Quantification of SN AAV transduction through-out the structure in 4 different viral serotypes in individual animals. Values represent mean of all quantified sections belonging to the sorted section group and their SEM.

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CHAPTER 7

Repulsive guidance molecule a (RGMa) induces degeneration

of dopaminergic neurons in the mouse Substantia Nigra:

implications forParkinson’s disease

J.A. Korecka1, R. Eggers1, N. Ras-Verloop1, R.J. Pasterkamp2, D.F. Swaab1, A.B. Smit3,

R.E. Van Kesteren3, K. Bossers1, J. Verhaagen1, 3

Manuscript in preparation

1 Department of Neuroregeneration, Netherlands Institute for Neuroscience, An Institute ofthe Royal Netherlands Academy of Arts and Sciences, Meibergdreef 47, 1105BA,

Amsterdam, The Netherlands2 Department of Neuroscience and Pharmacology, Rudolf Magnus Institute, Utrecht

University, Universiteitsweg 100, 3584 CG, Utrecht, The Netherlands3 Center for Neurogenomics and Cognitive Research, Neuroscience Campus Amsterdam,

VU University, Amsterdam, The Netherlands

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Abstract

Repulsive guidance molecule a (RGMa) is 2.5-fold upregulated in dopami-nergic (DAergic) neurons of the SN in Parkinson’s disease (PD) (Bossers et al., 2009). siRNA-mediated knockdown of RGMa in SH-SY5Y neuroblastoma cells reduced cell viability, whereas overexpression of RGMa did not alter cell viabil-ity but reduced the neurite numbers formed by these cells (Chapter 4). Based on these results, we postulate that RGMa normally protects DAergic neurons from cell death, but that enhanced expression of this chemorepulsive protein may contribute to the retraction of nigrostriatal axons as observed in PD. To inves-tigate the effects of RGMa on mesencephalic dopaminergic neurons in vivo, we overexpressed mouse RGMa in adult mouse SN DAergic neurons with the use of an adeno-associated viral vector harboring the RGMa coding sequence under the control of a synapsin promoter. Overexpression of RGMa in mesencephalic DAe-rgic neurons resulted in: i) decreased tyrosine hydroxylase (TH) expression in the SN and in the striatum, ii) degeneration of SN neurons, iii) astro- and micro-gliosis, and iv) motor impairments that are characteristic of striatal dopamine deficiency. Interestingly, overexpression of RGMa did not affect the number of calbindin positive neurons in the SN pars compacta, a population of neurons that is also relatively preserved in PD. More work is required to unravel the mecha-nisms by which RGMa induces these neuropathological changes, but these pre-liminary data suggest that RGMa is a regulator of DAergic neuron survival and is a potential molecular target in the development of a regenerative treatment for PD.

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Introduction

Repulsive guidance molecule, member a (RGMa), is a glycosylphosphati-dylinositol-anchored glycoprotein that can be processed by extracellular pro-teases generating multiple membrane bound and soluble forms of this protein (Tassew et al., 2012). RGMa acts as repulsive axon guidance molecule in the developing amphibian, bird and mammalian central nervous system (CNS) (Monnier et al., 2002; Niederkofler et al., 2004; Samad et al., 2004; Matsunaga et al., 2006; reviewed in Mueller et al., 2006; and Yamashita et al., 2007). Af-ter traumatic brain and spinal cord injury RGMa is upregulated in infiltrating fi-broblasts, reactive astrocytes and microglia, and it contributes to the repulsive environment of the CNS scar (Schwab et al., 2005a; Schwab et al., 2005b; Hata et al., 2006; reviewed in Mueller et al., 2006; and Yamashita et al., 2007). RGMa has been linked to multiple sclerosis by genetic association studies (Nohra et al., 2010) and was shown to be involved in the T cell-mediated pro-inflammatory response in a model for multiple sclerosis autoimmune encephalomyelitis (Mu-ramatsu et al., 2011; Kubo et al., 2011). In contrast, during acute inflammation, RGMa was identified as an inhibitor of leukocyte migration (Mirakaj et al., 2011). Moreover, a novel chromosome microdeletion encompassing the RGMa gene has been linked in a single case study to the features of a neurogenetic developmen-tal disorder called Angelman syndrome (Capelli et al., 2012).

RGMa, as well as netrin, both bind to the transmembrane receptor Neogenin (Itokazu et al., 2012). Neogenin is a so-called ‘dependence receptor’ (Mehlen and Bredesen, 2011). Dependence receptors mediate apoptosis in the absence of their ligand, while upon ligand binding they support proliferation, differentiation or cell survival (Matsunaga et al., 2006; Cole et al., 2007; Metzger et al., 2007; Lah and Key, 2012). Neogenin is cleaved by caspase-3 in the absence of RGMa and this initiates cellular apoptosis (Matsunaga et al., 2004; Matsunaga and Chedotal, 2004; Matsunaga et al., 2006). In an adult mouse retina injury model, intraocular injection of RGMa protein decreased caspase activity and reduced injury-induced retinal ganglion cell (RGC). Dependence receptor signaling appears therefore to play a key role in the protection of injured RGCs (Koeberle et al., 2010).

RGMa-Neogenin signaling also regulates growth cone collapse and axonal repulsion (reviewed in Wilson and Key, 2007; Yamashita et al., 2007). This oc-curs through the activation of RhoA/Rho-kinase and PKC, and is further mediat-ed by myosin II phosphorylation leading to a reduction of F-actin in growth cones (Conrad et al., 2007; Kubo et al., 2008). Many neuronal cell types are sensitive to RGMa-Neogenin axon repulsive signaling, including cerebellar granule neurons (Hata et al., 2006; Kubo et al., 2008), embryonic cortical neurons (Yoshida et al., 2008), embryonic dorsal root ganglion cells (Conrad et al., 2007), enteric neuro-nal progenitors (Metzger et al., 2007) and embryonic retinal explants (Monnier et al., 2002; Tassew et al., 2012).

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Two recent transcriptional profiling studies revealed that RGMa is upregu-lated in dopaminergic (DAergic) neurons of the substantia nigra (SN) of patients with Parkinson’s disease (PD) (Bossers et al., 2009; chapter 2; Neurocrine Biosci-ences, 2012). In a high content cellular screen (HCS, chapter 4), we showed that overexpression of RGMa in human DAergic neuroblastoma SH-SY5Y cells results in a small but significant reduction in the number of neurites per cell. This is con-sistent with RGMa’s function as a repulsive axon guidance molecule. In contrast, RGMa knockdown in the same SH-SY5Y cells decreased cellular viability and in-creased mitochondrial activity when cells were treated with the mitochondrial complex I inhibitor 1-methyl-4-phenylpyridinium (MPP(+)).Thus, whereas RGMa overexpression seems to reveal its axon repulsive function, RGMa knockdown appears to highlight the dependence receptor properties of Neogenin in the ab-sence of ligand. Taken together, RGMa appears to play a protective role in cul-tured DAergic neuron-like cells, while it also exhibits a moderate repulsive activ-ity on the processes formed by these cells.

Based on the upregulation of RGMa in the human SN and the functional data obtained in the HCS, we hypothesized that RGMa normally protects DAer-gic neurons in PD from cell death, but that axonal transport of enhanced levels of RGMa and secretion in the striatum would have a repulsive effect on synap-tic terminals of the nigrostriatal pathway, thereby ultimately inducing neuronal loss in the SN. As a first step to test this hypothesis we overexpressed RGMa in adult mouse SN DAergic neurons with the use of an adeno-associated viral vec-tor (AAV). Overexpression of RGMa induced neuronal degeneration in the SN and the loss of DAergic nigrostriatal axonal projections. Long-term overexpression of RGMa induced a movement disorder typical for a loss of DA in the striatum. These preliminary data suggest that RGMa is a regulator of the survival of DAe-rgic neurons, and a potential molecular target in the development of a regenera-tive treatment for PD.

Methods

AAV constructs and viral vector production

The pAAV2Sna-SW and pTRUF20B-SEW plasmids, both generous gifts from Prof. Deniz Kirik (Lund University, Sweden), were used for cloning and production of AAV. Each plasmid contained two inverted terminal repeats of AAV2 flanking a human synapsin 1 (SYN) promoter driving expression of hu-man α-synuclein (pAAV2Sna-SW plasmid) or GFP (pTRUF20B-SEW plasmid), followed by a woodchuck hepatitis virus post-transcriptional regulatory ele-ment (WPRE) and a polyadenylation signal. For the construction of the empty vector (pAAV2-SYN) the pAAV2Sna-SW plasmid was cut with BamHI to remove the α-synuclein sequence and religated. For the construction of the vector con-taining mouse RGMa (pAAV2-SYN-RGMa) the pcDNA4/HisB-RGMaFL plasmid (a


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generous gift from Dr. J. Pasterkamp, Utrecht University, The Netherlands), was cut with Dra1 and Xho1 to isolate the full length mouse RGMa sequence and this fragment was ligated into the pAAV2Sna-SW backbone cut with EcoRV and Xho1.

Production of AAV7-Empty, AAV7-RGMa and AAV7-GFP viruses was per-formed using capsid and helper plasmids provided by J.M. Wilson (Gao et al., 2002). For each viral vector stock eight 15 cm petridishes containing 1x107 hu-man embryonic kidney 293T (HEK293T) cells were transfected with the use of polyethylenimine (PEI, MW25000; Polysciences Inc., Warrington, PA, USA). Cells were grown in Dulbecco’s modified Eagle’s medium (DMEM) containing 10% fetal calf serum (FCS) and 1% penicillin/streptomycin (GIBCO-Invitrogen Corp, New York, NY, USA). pAAV2-SYN, pTRUF20B-SEW and pAAV2-SYN-RGMa plas-mids were cotransfected with packaging plasmids in a 1:2:2 ratio (AAV-gene plasmid:helper plasmid pAd∆F6 : AAV7 capsid plasmid) with a total amount of 62.5µg of DNA per plate. Two days after transfection cells were harvested in Dulbecco’s phosphate buffered saline (D-PBS) (Gibco) containing 10µg/ml DNAseI (Roche Diagnostics GmbH, Mannheim, Germany) and incubated for 1 hour at 37°C. Cells were lysed by three freeze-thaw cycles, spun down 30 min at 4000rpm and the crude lysate was collected. The virus was purified by iodixa-nol gradient ultra-centrifugation (Zolotukhin et al., 1999; Hermens et al., 1999) diluted in D-PBS/5% sucrose and concentrated using an Amicon 100kDA MWCO Ultra-15 device (Millipore, Billerica, MA, USA). Viral vector stocks were aliquoted and stored at -80°C until use. Titers were determined by quantitative PCR for viral genomic copies extracted from DNAse-treated viral particles using WPRE directed primers (forward: CAGGTGTATTGCCACAAGACAAA and reverse: TGCA-CAGGTGAAGACCAAGCAA). The titer of the AAV7-Emtpy virus was 8.63x10^12 genomic copies/ml (GCs/ml), the titer of AAV7-GFP virus was 3.0x10^12 GCs/ml and the titer of the AAV7-RGMa virus was 9.71x10^12 GCs/ml.

Experimental animals and surgical procedures

A total of 38 male C57BL/6 mice weighing 20-25g (Harlan, Zeist, The Neth-erlands) were socially housed with food and water ad libitum, in 12 hour light and dark cycles. All the experimental procedures and postoperative care were carried out in accordance with the Institutional Animal Care and Use Committee of the Royal Netherlands Academy of Arts and Sciences.

The viral injections were carried out with the use of glass capillaries (0.78/1.0mm internal/external diameter; Harvard Apparatus, Holliston, MA, USA) with an 80µm tip connected via Portex polyethylene tubing to a Hamilton syringe fixed in a micro-infusion pump (PHD2000, Harvard Apparatus). The sys-tem was filled with water. The glass needles were mounted on a stereotactic de-vice (David Kopf Instruments, Tujunga, CA, USA) and a total of 1.1µl of virus was loaded into the system. Two groups of animals were injected with different viral titers (Table 1).

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Mice were intraperitoneally (IP) injected with an anesthetic mix consist-ing of Hypnorm (0.1 mg/kg Fentanyl citrate/ 3.3 mg/kg Fluanisone HCl, Janssen Pharmaceuticals) and Dormicum (8.3 mg/kg Midazolam, Roche) and placed into a stereotactic device where they were fixed and the skull was exposed. The skull was leveled using the heights of bregma, lambda and two lateral measurements 2.0 mm from bregma. The injection coordinates were -2.8 mm anterior posterior (AP) and -1.3 mm lateral (L) from bregma and -4.3 mm ventral dorsal (VD) from the dura. Subsequently, the needle was lowered into the brain 0.1 mm below the VD coordinate, retracted back up to the correct level and the infusion of 1µl at speed of 0.2µl/min was initiated. After the infusion, the needle was left in place for 3 min before retraction. Animals recovered from the anesthesia on a heating pad set to 37°C until fully recovered. Experimenters were blinded to the viral genotype.

Statistical Analysis

Unless mentioned otherwise, the Mann Whitney U test was used to esti-mate the differences between treatment groups. A P value < 0.05 was considered significant.

Behavioural testing

The behavior of 30 animals injected with the titer-matched viral batches (Table 1, experimental group 2) was assessed with the following tests: narrow beam test, grid test, cylinder test, swing test and tremor assessment. During the first 3 weeks post surgery, all tests were performed twice a week and subse-quently once a week until week 12 post surgery. Baseline testing was performed 2 days before the surgery and the first test was performed 1 week after the sur-gery. The two investigators scoring the behavior tests were blinded for the treat-ment groups.

Experimental group 1 Experimental group 2

Virus AAV7-RGMa, AAV7-Empty AAV7-RGMa, AAV7-Empty, AAV7-GFP, Saline

Titer 9.7x10^12 3.0x10^12

Number of animals per group N=4 N=8, for saline N=6

Survival time 3.5 weeks 12 weeks

Table 1. Experimental animal groups used in this study. Two experimental groups were used in this study. The viral vector, titer, number of animals and survival time of the animals is indicated for each experimental group.


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Grid test

The grid test was employed to study forepaw use, in particular the use of distal musculature and digit manipulation that are sensitive to dopaminergic input in the striatum (Tillerson and Miller, 2003). Mice were suspended upside down on a metal grid and allowed to move freely throughout the grid. For a suc-cessful trial, an animal had to hold on to the grid for a minimal 10 seconds and take at least 10 steps. The maximum trial length was 30 seconds. The number of steps with both forepaws was counted as well as the number of unsuccessful steps (overshoot, misgrab, grab with a wrist, loss of grip) with either forepaw by two blinded observers independently. Each animal performed three runs and the averaged ratio between the total forepaw faults/total forepaw steps over these three runs was calculated (Meredith and Kang, 2006).

Cylinder test

The cylinder test was performed to assess preference of front paw use dur-ing rearing behavior (Liu et al., 1999; Ulusoy et al., 2009). Animals were allowed to move freely in a glass cylinder for 5 minutes or until they performed 20 full rearing movements. For each rearing, it was recorded if the mouse used its left, right or both paws. The percentage of right paw use was calculated over the total number of the rearing score.

Narrow beam test

The hind limb placement was tested using the narrow beam test. Mice had to cross an 8 mm wide, 100 cm long and 15 cm elevated beam. The total number of correct hind limb steps and hind limb slips was counted and averaged over 3 complete runs. Two observers, blinded to the treatment, performed the scoring. Animals were pretrained for this test daily, a week before the surgery.

Tremor

A semi-subjective tremor assessment was performed during the narrow beam test when animals were stationary on the platforms. A positive tremor score required that the animal was shaking while stationary, had a shaky tail when stretched and showed an unstable and shaky front paw placement when exploring the environment.

Swing test

The swing test was performed as described by Iancu et al. (2005). The di-rection of body rotation was measured by suspending mice 5cm above the bot-tom of a cage while holding them at the base of their tail for 30 sec. During that time the direction of each swing above a 30° angle was scored.

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Tissue processing

Animals were sacrificed at 3.5 weeks (Group 1, Table 1) or 12 weeks (Group 2, Table 1) after injection of the viral vector by an IP overdose with Pentobarbital (50mg/µl) and transcardially perfused with 0.9% saline followed by 4% para-formaldehyde (PFA, Sigma-Aldrich Co., St. Louis, MO, USA) in sodium phosphate buffer (PBS, Sigma) pH 7.4. The brains were post-fixed overnight and 6 series of 30µm thick coronal sections were cut on a vibratome, containing both SN the striatum. The sections were stored free-floating at 4°C in 1% PFA in PBS pH 7.6.

Fluorescent Immunohistochemistry

All immunohistochemical (IHC) stainings were performed on free-floating sections. Prior to the staining, sections were blocked in blocking buffer (Tris buff-ered saline (TBS, Sigma) with 2.5% fetal calf serum (FCS, DAKO A/S, Glostrup, Denmark) and 0.2% Triton-X 100 (Sigma)) for 1 hour (h) at room temperature (RT). Sections were incubated with anti-tyrosine hydroxylase (TH) antibody (either rabbit polyclonal (Pel-Freez Biologicals, AR, USA), or mouse monoclonal, clone LNC1 (Millipore MAB318, Temecula, CA, USA).The staining was combined with either anti-RGMa (D-16 (sc-46482), Santa Cruz, CA, USA) goat polyclonal antibody at 1:100, anti- glial fibrillary acidic protein (GFAP)-Cy3 conjugated mouse monoclonal antibody (G-A-5, Sigma, dilution 1:1500) or anti-Iba1 rabbit polyclonal antibody (activated microglia marker, Wako, Osaka, Japan, dilution 1:2000) . Primary antibody incubations were performed in blocking buffer for 1h at RT followed by overnight incubation at 4°C. The following secondary anti-bodies were used for fluorescent staining: goat anti-rabbit/mouse/chicken Alexa 488 (1:800, Invitrogen, Carlsbad, CA, USA) for the detection of the TH antibody, donkey anti-goat Cy3 (1:800, Invitrogen) for the detection of RGMa and donkey anti rabbit DyLight (1:800, Invitrogen) for the detection of Iba1. These antibod-ies were incubated for 1h at RT in blocking buffer followed by 20 min incubation in PBS containing Hoechst 33258 (1:10000, BioRad, Hercules, CA, USA). Sections were then mounted on gelatin coated glass slides and embedded in Mowiol (0.1 M Tris pH 8.5, 25% glycerol, 10% w/v Mowiol 4-88 (Sigma)).

Cresyl Violet and Calbindin Immunohistochemistry

Sections were incubated with anti-calbindin D-28K mouse monoclonal an-tibody at dilution 1:500 (McAB 300, Swant, Switzerland). Primary antibody in-cubation was performed in blocking buffer for 1h at RT followed by overnight incubation at 4°C. For calbindin detection, sections were incubated with biotin labeled donkey anti-mouse antibody (1:400, Vector Laboratories, Burlingame, CA, USA) followed by an incubation with ABC Vectastain complex (1:800, Vector Laboratories) in 1xTBS for 1h. Finally, sections were incubated with DAB solu-tion for 10min, washed in water, mounted and dried overnight at 37°C. Next day


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sections were dehydrated and counterstained with 0.1% Cresyl Violet (Aldrich Chemical Company, Inc. Milwaukee, USA).

Image processing and quantification

Images were acquired with an AxioPlan 2 microscope (Zeiss, Sliedrecht, The Netherlands) with Planapochromat objectives, using Evolution QEi black and white or Evolution MP colour camera (MediaCybernetics) and ImagePro soft-ware. For each staining, all sections were imaged with the same exposure times.

Estimation of neuronal density in the SN

For each animal, one Cresyl violet and Calbindin stained series was used for cellular density measurement similarly as described by Bao et al.(2005), and Huitinga et al., (2000). Briefly, the entire SN structure in the non-injected side of the brain was identified at 2.5x magnification using the color camera on the Ax-ioskop microscope. The anatomical borders of the non-injected SN were defined and outlined using the mouse brain atlas (Paxinos.G. and Franklin.K.B.J., 2001) and the outlined area was projected in a mirror fashion on the SN of the injection side, with slight adjustments to fit the anatomy of the contralateral SN. Addition-ally a smaller area in the post-thalamic nucleus just above the SN was outlined to serve as a comparison reference area. The outlined areas were subdivided into a rectangular grid using an Image Pro Plus macro, with each grid field represent-ing one image at 40x magnification. For the SN, based on the standard deviation of the number of counted neurons per field, sampling of 35% of the total number of fields was sufficient to estimate the neuronal density. For the post thalamic nucleus, 100% of the fields were counted. Each neuron was identified based on the presence of a nucleus with a nucleolus and its morphological shape. Calbin-din-positive and –negative neurons were counted separately. The total number of neurons in the two areas of interest from injected and non-injected side of brain was corrected for the size of the outlined area and thickness of each section to yield the average neuronal density in mm3. Based on these measurements, the decrease of neuronal density may also include neuronal atrophy, additionally to neuronal loss. Neuronal atrophy decreases the size of cells to be comparable to glial cells eliminating them from the counting criteria.

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Results

Overexpression of RGMa decreases TH immunoreactivity in the SN pars compacta and striatum

High levels of RGMa expression were observed 3.5 weeks after unilateral injection of AAV-RGMa into the mouse SN in 3 out of 4 mice (Figure 1, Experi-mental group 1, Table 1). RGMa immunoreactivity was also observed in the stria-tum of 3 out of 4 AAV7-RGMa animals (Figure 2). We did not detect RGMa im-munoreactivity in the SN of mice injected with the AAV7-Empty vector (Figure 1 and 2). In one animal injected with AAV7-RGMa (animal 2), RGMa expression was hardly detectable in the SN and in the striatum. In this animal, the injection of AAV7-RGMa apparently missed the SN pars compacta and some RGMa was pres-ent in the SN pars reticulata (Figure 1, animal 2).

High levels of RGMa expression in the injected SN were accompanied by a significant decrease of TH immunoreactivity as compared to the non-injected site (Figure 1). Additionally, we observed a significant decrease of TH immunore-activity in the right striatum, the projection area of DAergic neurons transduced with AAV7-RGMa (Figure 2). Reduced TH immunoreactivity in both the SN and striatum was not observed in the AAV-Empty injected animals. Interestingly, in the non-injected SN and the striatum TH immunoreactivity was observed to be at higher level than in control AAV-Empty animals (Figure 1 and 2).

RGMa decreases neuronal density in the SN.

Although TH immunoreactivity was clearly down in the RGMa injected SN, we investigated whether this is due to downregulation of TH expression, or in-deed due to loss of SN DAergic cells. Cresyl-violet staining of the mouse midbrain revealed a dramatic change of the cellular composition of the SN pars compacta in the animals overexpressing RGMa but not in the animals injected with AAV7-Empty (Figure 3). In animals injected with AAV-Empty, large neurons were pres-ent throughout the SN pars compacta. Overexpression of RGMa in the SN pars compacta resulted in a significant decrease in the number of large neuronal pro-files in this area when compared to the contralateral SN or to the AAV-Empty injected animals (Figure 3C). There was no difference in neuronal density in the SN in AAV-Empty injected animals compared to the contralateral non-injected SN (p=0.35). Since RGMa expression was increased in a large area of the mid-brain after transduction with AAV7-RGMa (Figure 1A), we next investigated if RGMa affected the neuronal density of the post thalamic nucleus (PTN). We ob-served a trend towards a decrease when comparing neuronal densities of the PTN in the AAV-RGMa injected midbrain to the contralateral PTN or to the AAV-Empty injected PTN, but this decrease was not statistically significant (p= 0.13 and p=0.09 respectively, Figure 3D).


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Figure 1. Overexpres-sion of RGMa in the mouse SN is associated with a decrease in TH expression. Immuno-histochemical staining for tyrosine hydroxylase (TH, green) and RGMa (red) in mouse SN injected with AAV-Empty (CTRL) or AAV-RGMa (RGMa) virus. The two panels for each animal represent the injected and non-injected SN pars compacta. Note the lack of TH staining in 3 out of 4 RGMa injected SN sections. RGMa animal 2 (A2) displayed TH immunoreactivity comparable to the CTRL animals. In this animal the injection of AAV7-RGMa appeared to have missed the SN. Arrow heads in this animal point to low levels of RGMa overexpression in some TH positive DAergic neurons of the SN pars compacta (upper arrow head) and in some neurons of the SN pars reticulata (lower arrow head). Scale bar represents 0.25mm.

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Calbindin positive neurons in the SN of PD patients are less affected by the degeneration process as compared to the DAergic neurons (Yamada et al., 1990; German et al., 1992). It was therefore interesting to determine whether RGMa overexpression in the SN does affect calbindin positive neurons in the SN. RGMa overexpression did not significantly alter the number of calbindin positive neu-rons in the SN pars compacta when compared to AAV-Empty injection (p=0.62, Figure 3B and E), but there is a significant decrease in calbindin positive neuron density when comparing RGMa injected to non injected SN. Additionally, we ob-served an increase in diffuse calbindin immunoreactivity within the SN retic-ulata and around the SN pars compacta in RGMa-injected animals (Figure 2A), whereas in control animals calbindin immunostaining is confined to the SN re-ticulata with low levels detected in the lateral SN pars compacta (Figure 3A and B).

RGMa overexpression activates astrocytes and microglial cells in the mouse SN

In addition to the loss of neurons in the SN following overexpression of RGMa, we also observed an increase in the amount of small cells. To investigate whether RGMa overexpression had an effect on the glial response in the SN, we analyzed the expression of the astrocytic marker GFAP and of Iba1, a marker for reactive microglia. GFAP immunoreactivity showed only a slight increase in the SN pars compacta and reticulata injected with AAV-RGMa (Figure 4A and B). Ad-ditionally, there was a significant activation of microglia in the SN pars compacta transduced with AAV7-RGMa but not with AAV7-Empty virus (Figure 4C and D). Apart from RGMa associated gliosis, a slight increase of astrocytic reactivity was observed aligning the needle track in animals injected with AAV-Empty and AAV-RGMa. This was most probably caused by the mechanical damage inflicted by the penetration of the needle (Figure 4A and B, note in particular control animal 2).

Figure 2 (Previous page). Overexpression of RGMa in the SN results in decreased TH and in-creased RGMa expression in the striatum (experiment 1). A. Overview images of TH (green) and RGMa (red) immunohistochemical staining in coronal sections of the right (injected side) and left (non-injected side) striatum. Note that in 3 out of 4 animals injected with AAV7-RGMa the TH staining was decreased in the right striatum and RGMa staining was increased (RGMa A1, 3 and 4). Scale bar represents 0.5mm B. RGMa protein is expressed in the striatum in all four AAV7-RGMa injected animals, albeit at much lower level in the misinjected animal 2. In animals 1 and 3 hardly any TH-positive fibers (green) were observed whereas in animal 4 a clear decline in TH immunoreactivity was observed. In the misinjected animal (animal 2) TH-immunoreactivity was hardly affected. Cell nuclei have been stained with Hoechst (blue). Scale bar represents 0.05mm.

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Figure 3. Overexpression of RGMa decreased neuronal density in SN pars compacta. A. RGMa overexpression in the SN disrupted the anatomical structure of the SN. Arrowheads mark neu-rons aligned in the SN structure. In AAV-Empty injected control animals (CTRL A1 and 2) and in the misinjected AAV-RGMa animal 2 (RGMa A2), the SN neurons are compact and aligned on top of to the SN pars reticulata (SN pars compacta- black arrowheads, SN reticulata- red arrow). In contrast, in RGMa overexpressing animals the cellular composition of the SN structure is disor-ganized (black arrowheads). Scale bar represents 0.25mm. B. Large magnification images of the lateral SN injected with AAV-Empty or AAV-RGMa virus. The large SN neurons are indicated by black arrowheads and calbindin positive neurons by white asterisk. Scale bar represents 0.1mm. C. RGMa overexpression decreases neuronal density in the SN. RGMa overexpression in SN pars compacta resulted in a decrease in the density of large neurons compared to the contralateral not injected SN and AAV-Empty injected SN. D. Neuronal density in the post thalamic nucleus (PTN) is not decreased after RGMa overexpression when comparing to AAV-Empty injected SN (p=0.09). E. RGMa overexpression did not affect the density of calbindin positive neurons in the mouse SN when comparing to the AAV-Empty injected SN (p=0.39), but there was a significant decrease in the density of calbindin positive neurons when comparing the RGMA injected to non-injected SN. Misinjected animal RGMa A2 was excluded from the statistical analysis. Due to low number of animals paired and non-paired student was used for all analyses (* p<0.05).


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Figure 4. Glial response after RGMa overexpression in the mouse SN. A. GFAP immunoreactivity (red) was slightly increased in the RGMa injected SN. TH immunoreactivity is visualized in green. Increased levels of GFAP immunofluorescence can also be seen in the SN reticulata. Noteworthy, needle penetration of the tissue also induced a reactive astrogliosis, in particular in CTRL 2. B. High magnifications of panel A. C. Iba1 immunoreactivity (red), marking reactive microglia, indicated a vast reaction in the AAV-RGMa injected SN. Hoechst fluorescence (blue) additionally suggested a massive influx of cells in this area. D. High magnifications of panel C. Scale bars in A and C represent 0.25mm and in B and D 0.025mm.

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RGMa overexpression induces progressive motor impairments

We next investigated whether overexpression of RGMa in the SN does also affect motor performance. Mice injected with AAV-RGMa in the SN (Experimen-tal group 2, Table 2, with titer matched AAV injections leading to three times lower AAV-RGMa titer then in experimental group 1) developed behavioral motor deficits in the grid and cylinder tests (Figure 5). No deficits were observed in any of the control animals injected with either saline, AAV-Empty or AAV-GFP. The most striking behavioral deficit was revealed by the grid test, which is designed to measure accuracy of front paw placement and is significantly correlated with striatal dopamine levels(Tillerson and Miller, 2003). RGMa overexpressing ani-mals performed progressively worse in this test (p<0.001), unlike the three con-trol groups. The dysfunction started at 3.5 weeks and continued until almost the end of the experiment (Figure 5A). At week 12, RGMa animals showed a small degree of recovery, but performed still significantly worse than the AAV-GFP and saline injected animals.

In the cylinder test, overexpression of RGMa showed a significant progres-sive preference of right paw use during rearing behavior compared to either both paws or left paw only in time of the experiment (Figure 5B, p<0.001). At six time points (week 4, 6, 8, 10, 11 and 12), this preference was significantly different from the control groups. This suggests a dysfunction of the left front paw. Left front paw movements are controlled by the contra-lateral nigrostriatal system, which was injected with AAV-RGMa.

Although the error rate was slightly higher in the RGMa group, the narrow beam test did not reveal significant impairment of these mice in general motor function and hind limb placement skills (Figure 5C). The swing test also did not reveal a preference in turning behavior in any of the treatment groups (Figure 5D). A tremor assessment indicated more positive events within the AAV-RGMa injected animals. This behavior was highly variable within the AAV-RGMa in-jected group (Figure 5E), yet at week 6, RGMa overexpressing animals showed significantly more tremor compared to AAV-GFP and saline injected animals. Fi-nally, RGMa overexpression had no impact on body weight (Figure 5F).

Discussion

We hypothesized that RGMa normally protect DAergic neurons from cell death, but that increased expression of RGMa, and axonal transport and secre-tion of this repulsive protein in the striatum would have a negative effect on syn-aptic terminals of the nigrostriatal pathway, subsequently inducing retrograde degeneration of mesencephalic DAergic neurons in the SN. AAV mediated over-expression of RGMa in adult mouse mesencephalic DAergic neurons resulted in i) reduced TH expression in the SN and in the striatum, ii) degeneration or atrophy of neurons in the SN, iii) astro- and microgliosis, and iv) a movement disorder


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Figure 5. Behavioral deficits after RGMa overexpressing in mouse SN. A. Grid test performance identified a progressive increase of front paw placement errors in the RGMa group (red) (Fried-man test p<0.001) and not in the three control groups (AAV-Empty (blue), AAV-GFP (green) and saline (black). From week 3.5 until week 11 RGMa overexpressing mice showed significantly higher error rates compared to all three control groups (Mann Whitney U test, p<0.05). At week 12, RGMa mice performed worse compared to both GFP and saline animals (p= 0.009 and p=0.01 respectively), but not compared to the AAV-Empty animals (p=0.105). B. Preference of bilateral or unilateral front paw use was measured in a cylinder test. The ratio of right paw only rearing over the total rearing was determined. RGMa overexpressing mice progressively in-creased their right paw use during the time of experiment (Friedman test p=0.0001) compared to control groups. RGMa animals showed a significant use of raw paw compared to saline treated animals at week 4, 8 and 12 (black asterisk), to the AAV-Empty group at week 6 (blue asterisk), to saline and GFP at week 11 (green asterisk), and to all three control groups saline, Empty and GFP at week 10 (red asterisk). C. Hind limb placement was measured by narrow beam test. RGMa overexpressing mice showed more hind limb slip errors compared to AAV-GFP at week 7 and 11 (green asterisks). D. The swing test revealed no significant differences in the rotation preference of the mice between any of the treatment groups. E. Tremor was observed in RGMa overexpress-ing mice significantly more often at week 6 compared to AAV-GFP and saline injected animals. F. None of the treatment groups showed any significant differences in weight gain. For all tests,

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characteristic of striatal dopamine deficiency indicating that RGMa has dramatic effects on the viability of SN DAergic neurons. More work is required to unravel the mechanisms by which RGMa induces these neuropathological and behavioral changes. Below we will discuss three likely possibilities.

Overexpression of RGMa induced degeneration of neurons in the SN - potential mechanisms

RGMa binding to its receptor Neogenin blocked the pro-apoptotic activity of Neogenin in chick embryos (Matsunaga et al., 2004; Matsunaga and Chedotal, 2004), and rescued adult RGCs from injury induced cell death (Koeberle et al., 2010). In a DAergic cell line, RGMa knockdown reduces cell viability, and this ef-fect is amplified in cells with compromised mitochondrial function (chapter 4). Together, this supports a role of RGMa as a positive modulator of cell survival. In contrast, we show here that neuron-specific overexpression of RGMa in vivo in adult mouse SN neurons decreased TH expression in the nigrostriatal system and induced neuronal loss or atrophy. In order to understand the mechanism by which overexpression of RGMa leads to neuronal degeneration in the SN further studies are required. We envision three possible scenarios: i) axonal transport and secretion of increased amounts of RGMa from the SN to the striatum may in-duce a loss of nigrostriatal synaptic contacts, axonal retraction, and finally neu-ronal death and/or atrophy in the SN, consequently inducing a glial response, ii) overexpression of RGMa in DAergic neurons may result in enhanced secretion of RGMa in the SN where it directly activates astro- and microgliosis leading to the production of pro-inflammatory cytokines and subsequent neuronal death and/or atrophy, and finally iii) enhanced RGMa expression may induce both axonal repulsion in the striatum and a glial response, and those events may simultane-ously lead to neuronal cell death and/or atrophy.

In support of the first scenario, following neuron-specific expression of RGMa in the SN we observed elevated RGMa protein levels in the ipsilateral striatum. RGMa immunoreactivity was distributed in a diffuse pattern in what appear to be thin fibers and extracellular matrix. This indicates that RGMa was most probably transported to the striatum via nigrostriatal projections. The presence of RGMa protein in the striatum may induce repulsive signaling in the DAergic nigrostriatal projections leading to synapse loss. Overexpression of RGMa in DAergic SH-SY5Y cells indeed decreased the number of neurites, supporting its function as a repulsive axon guidance regulator in DAergic cells (chapter 4). The induction of retrograde neuronal death and/or atrophy would

week 0 is the baseline measurement performed 2 days before the AAV injection. Non-parametric statistics were used where Friedman test was used to find differences within group in time and Mann Whitney U test was used to look for group differences at each testing time point (* p< 0.05, ** p< 0.01).


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be in support of the dying back hypothesis (Dauer and Przedborski, 2003; Cheng et al., 2010). This hypothesis states that the primary neurodegenerative event in PD is the loss of dopaminergic nigrostriatal presynaptic terminals and the sub-sequent retraction of axons and degeneration of DAergic neurons in the SN. The glial response that we observe in the midbrain would thus be a secondary event induced by the neuronal cell death and/or atrophy.

In the second scenario, RGMa overexpressed in neurons is secreted locally in the SN and activates astrocytes and microglia in the SN leading to cytokine production and consequential neuronal death and/or atrophy. Indeed, RGMa im-munoreactivity is observed in the extracellular space between the neuronal cell bodies of the SN after injection of AAV7- RGMa. Gliosis is known to occur in the PD SN (Langston et al., 1999; McGeer and McGeer, 2008), and may play a crucial role in the progression of neuronal degeneration by increased release of cyto-kines and chemokines (Hanisch, 2002; Hirsch et al., 2003; Barcia et al., 2003). Neogenin is expressed by microglia, macrophages and in the CD4+ T cells in the spinal cord (Hata et al., 2006; Muramatsu et al., 2011), and in the cells of blood vessels after lens injury and optic nerve crush (Schnichels et al., 2011). RGMa secreted by DAergic neurons in the mouse SN may therefore bind to neogenin expressed by these pro-inflammatory cells and this may result in cytokine and chemokine production, consequently inducing neuronal stress and neurotoxicity (Hanisch, 2002). RGMa may also bind to Neurogenin on blood vessels and T cells and attract more pro-inflammatory cells, a phenomenon that is observed in the EAE mouse model for MS (Muramatsu et al., 2011). RGMa-induced recruitment of pro-inflammatory cells could induce neuronal degeneration.

Finally, although we did observe a decrease in neurite numbers follow-ing RGMa overexpression in SH-SY5Y cells, cellular viability was not affected in these cells. RGMa signaling may thus induce both axonal repulsion in the stria-tum and glial activation in the SN, which together would lead to neuronal cell death (scenario 3). Alternatively, the lack of cell death in SH-SH5Y cells overex-pressing RGMa may reflect a difference between the response of this cell line and DAergic neurons in vivo to RGMa

The data presented here are insufficient to conclude which of these three mechanisms is implicated in the degeneration of SN DAergic neurons after RGMa overexpression. Firstly, it has to be determined which of the pathological events takes place first: loss of DAergic nigrostriatal presynaptic terminals and the sub-sequent retraction of axons, or gliosis and pro-inflammatory responses in the SN. Secondly, it should be established whether increased RGMa levels exert their effects on DAergic neurons in a Neogenin-dependent or –independent manner, e.g. by overexpression of RGMa in conditional Neogenin knockout mice.

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RGMa overexpression in mouse SN – similarities to PD etiology

The effects of overexpression of RGMa in the mouse midbrain bear com-monalities with the neuropathology of PD. As discussed above, overexpression of RGMa in the adult mouse SN decreases neuronal number and/or induces atrophy and activates astrocytes and microglia, both well known characteristics of PD. Additionally, RGMa overexpression induced movement deficits characteristic of DA loss in the striatum (Tillerson and Miller, 2003). These movement deficits de-veloped in a progressive manner and lasted for at least 8 weeks, mimicking the progressive clinical symptoms in PD patients.

RGMa overexpression did not alter the density of calbindin positive neurons in the SN pars compacta, when compared to the AAV-Empty injection. Interest-ingly, in PD SN pars compacta the number of calbindin positive neurons does not decrease as dramatically as the calbindin negative SN neurons showing higher resistance to ongoing neurodegenerative process (Yamada et al., 1990; German et al., 1992). This effect is also observed in MPTP treated monkeys (Lavoie and Parent, 1991; German et al., 1992) and in a genetically induced PD mouse model, the aphakia mice (Luk et al., unpublished). We found a decrease of calbindin pos-itive neurons in RGMa overexpressing SN when compared to the contralateral SN, but this effect is smaller than the decrease of total neuronal density, further arguing towards more resistance of calbindin neurons against the neurodegen-eration. This decrease may also not be RGMA specific, since AAV-Empty injected SN also showed a trend towards a decreased calbindin positive neuron density, suggesting that the mechanical brain injection or neuronal AAV transduction may have an effect on the calbindin expression.

Besides the decrease in the number of neurons in SN, we found a slight trend towards a decrease of PTN neuron density after RGMa overexpression. Al-though, not significant, RGMa signaling may be activated in PTN neurons, lead-ing to a decreased neuronal survival or neuronal atrophy. As we have shown only an upregulation of RGMa in the PD SN (Bossers et al., 2009), and not studied the PTN in PD, we cannot judge the possible role of this effects in translation to PD pathology. Nevertheless, it is noteworthy that RGMa may have a more broad effect on midbrain neurons, besides the DAergic neurons of the SN.

To further investigate the commonalities between overexpression of RGMa in the mouse midbrain and neuropathology of PD, we aim to study other features that are prominent in PD, such as Lewy body formation, and mitochondrial dys-function. If these aspects of PD pathology are also present in RGMa overexpress-ing mice, this will further contribute to the relevance and importance of this tar-get gene in the development and/or progression of PD.

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CHAPTER 8

General discussion

J.A. Korecka1, K. Bossers1, R.E. van Kesteren2, D.F. Swaab3, J. Verhaagen1,2


Amsterdam, The Netherlands2 Center for Neurogenomics and Cognitive Research, Neuroscience Campus Amsterdam,

VU University, Boelelaan 1085, 1081HV, Amsterdam, The Netherlands3 Neuropsychiatric Disorders, Netherlands Institute for Neuroscience,

An Institute of the Royal Netherlands Academy of Arts and Sciences, Meibergdreef 47, 1105BA, Amsterdam, The Netherlands

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GENER A L DISCUSSION

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Summary

Parkinson’s disease (PD) is a progressive neurodegenerative movement disorder. Neuropathological changes in sporadic PD involve multiple neuronal systems (Braak et al., 2003). Neurodegeneration of dopaminergic (DAergic) neu-rons in the substantia nigra (SN) is one of the most widely studied neuropatho-logical hallmarks of the disease, as it leads to the development of the clinical mo-tor symptoms. Only 5% of the PD cases are familial, while the rest of the patients suffer from a sporadic form of the disease for which the causes are largely un-known (Dauer and Przedborski, 2003). The current treatments, both pharmaco-logical and surgical, diminish the symptoms of both familial and sporadic forms of the disease, but merely temporarily improve the quality of life of the patients (reviewed in Olanow et al., 2009). As of yet, no genuine treatments ceasing the progression or curing the disease are available, although currently cell replace-ment and gene therapy approaches are being investigated. These approaches aim to either replace the damaged cells or prevent neuronal degeneration by stimu-lating regenerative and neuro-protective mechanisms in the affected tissue (re-viewed in Chapter 1).

Mitochondrial activity, protein aggregation and the oxidative stress re-sponse have been linked to the development of PD based on mutations found in familial forms of the disease (reviewed in Hardy et al., 2006; Bonifati, 2007; Maguire-Zeiss et al., 2008; Hardy, 2010). However, for sporadic PD the specific molecular alterations leading to the typical neuropathological changes in the SN still need to be elucidated. The etiology of the disease appears to be multi-factorial, involving both biological and environmental components (Dauer and Przedborski, 2003; Olanow et al., 2009). More research is required into the basic cellular and molecular changes that occur in the brains of sporadic PD patients.

The work presented in this thesis is based upon a gene expression study in-dentifying 287 genes differentially expressed in the SN of PD patients compared to matched controls (Bossers et al., 2009). Since the tissue used for this study was from end stage PD patients these gene expression changes may be either causal to the development and/or progression of sporadic PD, or may be the con-sequence of the disease process. The main challenge of the research described in this present thesis was therefore to translate the alternations in gene expression into concrete biological mechanisms that may underlie the degeneration of DAe-rgic neurons in the SN of PD patients, with a potential for development of novel therapeutic targets.

The first step to identify the key players in the neurodegenerative process of PD was the selection of target genes (from the total set of 287 genes) that are potentially involved in this process based on Ingenuity pathway analysis, gene ontology analysis, and literature search (Figure 1, Chapter 2). We based our gene selection on the potential roles that these genes play in cell death, axon guidance, neurotrophic support, synaptic transmission, mitochondrial function

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and cellular metabolism. This approach resulted in the identification of 79 genes that are linked to one or more of these processes and may therefore be specifi-cally involved in the development of PD neuropathology.

The second stage was to 1) identify the cell type in which these dysregu-lated genes are expressed in the human brain, and determine whether their cellular localization changes during the disease process (Chapter 2), and 2) es-tablish a suitable cell model to study target gene function (Chapter 3). Cellular localization studies of 34 target genes, using in situ hybridization and immuno-histochemistry, revealed that these genes are almost exclusively expressed in neurons in the SN, and not in reactive astrocytes or activated microglia (Figure 1, Chapter 2). The neuronal localization of the majority of the target genes moti-vated us to use retinoic acid (RA) differentiated SH-SY5Y neuroblastoma cells as a cellular platform for functional high content screens (HCS). Genome-wide tran-scriptional profiling combined with gene ontology and pathway analysis dem-onstrated that these cells 1) contain the main cellular and molecular properties that are characteristic of DAergic cells, 2) are sensitive to environmental factors that are known to contribute to PD, and 3) are readily available and can be easily expanded in culture (Chapter 3).

The SH-SY5Y cellular model was used to functionally validate the role of 62 target genes in cell viability, neurite outgrowth and mitochondrial activity in HCS (Figure 1, Chapter 4). This integrative approach, using siRNA mediated knockdown and LV-mediated overexpression, identified 12 genes significantly affecting one or more of these parameters. The most dramatic effects on both cellular viability and neurite outgrowth were observed after overexpression of 4 genes that are also highly upregulated in PD SN neurons: CTDSP1, RGMA, PTMA and WWC1.

As a first step to study the role of one of these target genes in vivo, we over-expressed RGMA in the mouse SN (Figure 1, Chapter 7). In order to do this, we first performed a comparative study of four adeno-associated viral (AAV) vec-tor serotypes and found that AAV7 is the best tool to use for targeted gene de-livery to the mouse SN (Chapter 6). Overexpression of RGMA in the SN of mice appeared to induce degeneration of DAergic neurons, behavioral abnormalities that are typical for the loss of striatal DA input, and microglia and astroglial acti-vation in the SN. Below we will discuss how this result may enhance our under-standing of development of PD pathology.

In the future, we would also like to examine the other three candidate gene targets (CTDSP1, PTMA and WWC1) in vivo and additionally test their function in a mouse model that mimics the early stages of PD based on a chronic low dose MPTP treatment (Chapter 5).


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Figure 1. The experimental approach: PD genes were selected that may play a key role in the neurodegenerative process of PD. The subsequent steps that were undertaken to select the most promising target genes to be tested in vivo are indicated.

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Discussion

The multi step experimental approach: from gene expression chang-es in the human brain to studies of individual genes in the mouse SN - have we been successful?

To answer the key question whether enhanced expression of CTDSP1, PTMA, RGMA and WWC1 in the PD SN contributes to the degeneration of DAe-rgic neurons in PD patients follow-up research will have to be performed in hu-man brain tissue, animals and tissue culture. Central questions are: How early in the disease process is the gene expression enhanced? Is the enhanced expression of CTDSP1, PTMA, RGMA and WWC1 selective for the neurons of the SN? Do PD patients have single nucleotide polymorphisms in these genes that cause dys-regulation of their function? We will briefly discuss these questions below and answers to these questions will determine whether CTDSP1, PTMA, RGMA and WWC1 will indeed be good target molecules for the development of a regenera-tive therapy for PD.

1. Selection of a suitable in vitro model and appropriate biological read-outs enables successful identification of PD target genes

To identify specific genes which may play a key role in the neurodegenera-tive process of PD we used a multi step experimental approach. As illustrated in Figure 1, we started our study with 287 differentially regulated genes in PD SN. The primary selection of genes for functional validation was based on their involvement in key processes implicated in PD. Moreover, it was also partially based on personal interest in specific molecular pathways, e.g. axon mainte-nance and guidance. The further ‘filtration process’ of PD gene target selection was based on experimental data and objective inclusion/exclusion parameters leading to a final selection of 4 target genes with a potential role in PD develop-ment: CTDSP1, PTMA, RGMA and WWC1. The prioritization of candidate genes based on our multi step approach depended on a number of essential parame-ters: 1) selection of an in vitro cell system that is relevant to the gene expression changes in PD, 2) selection of appropriate biological readouts, and 3) the ability to successfully manipulate gene expression for many genes. These specific re-quirements for our experimental approach are discussed below.

As almost all of the 34 genes investigated in Chapter 2 are expressed in SN neurons (Chapter 2, Figure 1), we hypothesized that a similar proportion of the 79 selected target genes would predominantly be expressed by the SN neurons as well. In order to functionally validate the role of these genes in a manner that is relevant to PD, we chose to use the neuronal-like RA differentiated DAergic SH-SY5Y cells (Chapter 3).


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To detect target gene functions relevant to PD neuropathology, the cellular readouts in the HCS have to directly reflect the PD affected biological functions. The selection of 79 genes was based, therefore, on their potential involvement in cell death, axon guidance, neurotrophic support, synaptic transmission, mi-tochondrial function and cellular metabolism. We opted for the Cell Titer Blue cell viability assay to reflect the role of genes in cell death or cellular viability. The MitoTracker staining was used to measure effects of genes on mitochondri-al function and cellular metabolism. The β-tubulin staining was used to detect genes with functions in axon guidance and neurotrophic support. The only pa-rameter that we were unable to study was synaptic transmission. This was not possible due to the cellular model we used, as SH-SY5Y cells do not develop syn-apses and do not make synaptic contacts.

Finally, we had to be able to successfully manipulate gene expression of a large number of genes. We have used a commercially available siRNA library to achieve gene knockdown. Even though siRNAs may only partially knock down target genes (see Chapter 4 and below), it is the only viable option for medium-throughput gene knockdown. It is not realistic to create knockout cell lines for all target genes. To achieve stable gene overexpression, we have used LV medi-ated transduction. To be able to generate a relatively large number of viral con-structs, we have used the Gateway cloning system by Invitrogen. This optimized and time-efficient approach allowed us to generate viral vectors for 14 target genes. Because of the amount of work involved in creating viral vectors, the num-ber of genes in the knockdown screen is much higher than in the overexpression screen. In view of this, it is noteworthy that the most potent effects on the inves-tigated cellular readouts occurred after gene overexpression. The hit rate of the knockdown studies was 6% (4 out of 62), whereas 86% (12 out of 14) of the over-expressed genes significantly affected one or more readouts (Figure 1). As dis-cussed in Chapter 4, this effect may in part be attributed to false negative results due to incomplete and transient effects of knock down, slow protein turnover, and redundancy of protein function. Overexpression studies on the other hand lead to high protein levels and stable protein expression within the time frame of culture. However, one should keep in mind that persistent high level overexpres-sion outside of the physiological range may also induce false positive effects.

2. Upregulation of gene expression displays the highest impact on neuro-nal integrity

Out of 287 disregulated genes in the PD SN, only 40 were upregulated in their expression (Bossers et al., 2009). Since more genes were downregulated in PD SN, one would expect that the downregulation of specific transcripts (‘loss of function’) would have a large potential impact on the survival of DAergic neu-rons. Yet, from our in vitro study, the only 4 genes that showed an effect after knockdown were all upregulated in the PD SN (FOXO4, KLK6, PTMA, and RGMA). This was a rather unexpected observation. None of the genes which were down-

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regulated in PD, showed any effect on mitochondrial activity or neurite out-growth in vitro after ‘loss of function’. It may be possible that partial downregu-lation of a single gene in the SN DAergic neuron may not have a great impact on its function, e.g. because its function can be compensated for by another gene with a similar role. However, downregulated gene expression in the PD SN also never resulted in a complete loss of mRNA molecules for a particular gene: many genes were downregulated to about 50% of normal levels. It may therefore be necessary, both in vitro and in the human brain, for multiple genes to be down-regulated simultaneously to affect a cellular function relevant for PD neuropa-thology. On the other hand, a ‘gain of function’ effect achieved by overexpression may be more potent in altering cellular processes, especially if a gene is involved in a molecular pathway involved in the induction of cell death, as was observed for 4 of the genes overexpressed in vitro (ALDH1A1, FOXO4, PTMA and WWC1, Chapter 4).

The HCS analysis of the knockdown of 62 PD target genes, and overexpres-sion of 14 PD genes, led to the identification of 12 genes playing a role in the vi-ability and neurite outgrowth of differentiated SH-SY5Y cells. The final phase of the multi step approach consisted of the selection of candidate genes for in vivo validation, and was based on 3 criteria: 1) the gene should be upregulated in the PD SN, 2) their overexpression should affect both cellular viability and neurite outgrowth in vitro, and 3) genes should not have been implicated in PD before (Figure 1). This selection resulted in identification of the final 4 target genes: CTDSP1, RGMA, PTMA and WWC1. Indeed, when we overexpressed RGMA in the adult mouse SN, we observed severe degeneration of the nigrostriatal system. Thus, to answer the question posed above, “have we been successful in our multi step experimental approach identifying novel target genes for sporadic PD?” I am inclined to state “yes, we have” (see also below: ‘Unraveling the role of RGMA in axonal degeneration in PD). In the near future, we will investigate if the over-expression of the other 3 target genes (CTDSP1, PTMA and WWC1) in the mouse SN would also negatively affect the integrity of the adult mouse nigrostriatal sys-tem.

Future studies to elucidate the roles of CTDSP1, PTMA, RGMA and WWC1 in PD-associated neurodegeneration

1. The sequence of neuropathological changes in PD: nigrostriatal axon retraction precedes massive neuronal loss in PD

At the moment of the onset of clinical symptoms in PD patients, about 30% of SN DAergic neurons are lost whereas already 50-60% of striatal DA terminals are degenerated. Only at the terminal end of the disease there is about 70% loss of DAergic neurons in the SN and almost complete loss of striatal DAergic pro-jections (Figure 2). Based on human brain studies, the α-synuclein and LRRK2 transgenic animal models, and 1-methyl-4-phenyl-1,2,3,6-tetrahydropyrine


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Figure 2. Development and progression of PD: the two most likely sites where the disease could start: in the SN (containing cell bodies) or in the caudate-putamen (containing DAergic projec-tions). DAergic neurons in the SN pars compacta (SNpc) project their axons to caudate and putamen (A). In PD at the onset of 1st clinical symptoms 50-60% axon terminal loss occurs, ac-companied by 30% of the DAergic SNpc cell loss (B & C). At the end stage of PD, 80-90% of axon terminals are lost and 70% of cell bodies in the SNpc (D). Molecular changes take place before the onset of 1st clinical symptoms in PD and last until the end of the disease process. Axon terminal loss seems to be a primary neuropathology of PD as stated by the dying-back hypothesis. There may be two mechanisms by which this even is induced: B. Local changes in the SN negatively af-fect the viability of DAergic neurons (1) leading to the degeneration of axonal projections (2), or C. Molecular changes in the striatum compromise synaptic terminals of the SN DAergic neurons leading to the loss of axonal connectivity (1), and ultimately degeneration of SN DAergic neurons (2). Figure 2 is adapted frDauer & Przedborski (2003), whereas the statistical data on axonal and neuronal degeneration is based on Burke and O’Malley and Cheng et al., reviews (2010; 2012).

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(MPTP) toxicity models axon degeneration in the striatum seams to take place first, before the loss of neuronal soma in the SN (reviewed in Cheng et al., 2010; and Burke and O’Malley, 2012). These observations support the ‘dying back’ hy-pothesis which states that the striatal DA nerve terminals are the primary tar-gets of the degeneration process in PD, and that the loss of nerve terminals trig-gers neuronal death in the SN of PD patients (Dauer and Przedborski, 2003).

Interestingly, gene expression data and genome wide association studies identified genes involved in axon guidance to be associated with PD (Lesnick et al., 2007; Bossers et al., 2009; Edwards et al., 2010). Out of the list of 79 primary target genes, 8 genes had a direct connection with axon guidance, whereas of the 12 genes that showed an effect on DAergic cell function and survival in vitro, 6 of them (50%) also affected neurite outgrowth (chapter 4). These numbers sup-port the idea that the dying-back of DAergic axons may be a primary event in PD pathology (Figure 2). Yet it is still unclear which mechanisms cause this early retraction of axons and initiate damage to the nigrostriatal system. Two possible sequences of events may lead to DAergic terminal loss in the striatum: 1) local changes in the SN negatively affect the viability of DAergic neurons leading to the degeneration of axonal projections and ultimately degeneration of SN DAergic neurons (Figure 2B), or 2) changes in the striatum compromise synaptic termi-nals of the SN DAergic neurons, leading to the loss of connectivity and ultimately, degeneration of SN DAergic neurons (Figure 2C). Below we will propose experi-ments that aim to elucidate the role of CTDSP1, PTMA, RGMA and WWC1 in PD associated axon retraction and neuronal degeneration.

2. Are CTDSP1, PTMA, RGMA and WWC1 altered early or late during the course of PD development?

The in vitro and, in the case of RGMA, in vivo data suggest that CTDSP1, PTMA, RGMA and WWC1 alter both cell viability and neurite outgrowth. There-fore these genes have a potential to induce axon retraction in early PD. To gain more insight into functional consequences of their altered expression in and importance for the disease process that occurs in PD, it is essential to establish when and where the expression of CTDSP1, PTMA, RGMA and WWC1 is altered during the progression of PD. It is therefore our primary aim to establish the temporal expression profile of these genes in the human PD brain. We will study mRNA and protein expression of these 4 genes in the SN, putamen and caudate of control and PD brains in the course of early to late disease stages based on the Braak staging (Braak et al., 2003). We will also study the localization of the protein to determine whether the transport of the increased levels of protein to the striatum may affect the nigrostriatal projections. The data on temporal and localization expression patterns for these 4 genes may help us to better under-stand the pathological sequences of events leading to the degeneration of the SN DAergic neurons in PD. For example, if CTDSP1, PTMA and WWC1 protein levels are locally increased in the cell bodies of SN DAergic neurons in the early stages


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of the disease, it is likely that they contribute to a reduced cellular viability, which may in turn negatively affect synaptic contacts in the striatum and lead to axonal retraction as first pathological correlate (hypothesis 1, Figure 2B). Conversely, increased protein levels of RGMA in the extracellular matrix of the striatum may induce repulsive signaling in the striatal axonal terminals and lead to the loss of connectivity, followed by the degeneration of the SN DAergic cell bodies (hypoth-esis 2, Figure 2C).

3. Are CTDSP1, PTMA, RGMA and WWC1 players in a common signaling pathway?

CTDSP1, PTMA, RGMA and WWC1 alter both cell viability and neurite out-growth in vitro. We were interested to see if their molecular signaling pathways included any common players. We therefore conducted an IPA analysis to identify interaction partners. In general there was no interesting common link between these 4 genes. This could be due to the fact that CTDSP1, PTMA and WWC1 have not been directly linked to neurite outgrowth before, and therefore the molecu-lar players associated with this function are still unknown. On the other hand, PD is a heterogeneous disease with the involvement of multiple cellular mecha-nisms, and it may be that the downstream signaling pathways of these genes are indeed not connected. It is therefore important, as a first step, to overexpress CTDSP1, PTMA and WWC1 in the adult mouse SN and assess whether and how these genes affect the integrity of the adult mouse nigrostriatal system. If these genes affect the viability of DAergic neurons, we will have to answer the question whether the axonal loss precedes the cellular loss, or whether these processes take place simultaneously. Such primary in vivo experiments have the potential to help us form a hypothesis whether the dysregulation of these genes in PD po-tentially plays an important role in the disease development and/or progression.

As a second step, promoter region studies should be performed to search for a possible common regulator of these 4 genes. Promoter sequences should be compared between these genes to determine if they are regulated by com-mon transcription factor(s). It would be extremely interesting if a single tran-scription factor, or a defined set of transcription factors, would regulate the expression of these 4 genes. Apart from linking these genes to each other, most importantly, this analysis would further identify an early potential mechanism that is involved in the early stages of PD. Moreover, it would be extremely inter-esting to conduct transcription factor binding site overrepresentation analysis on the whole set of disregulated PD genes (287). Recent bioinformatics analysis approaches have shown this is feasible for other large gene expression data sets (Geeven et al., 2011).

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4. Genetic studies

It would be very interesting to study large PD patient cohorts to confirm CTDSP1, PTMA, RGMA and WWC1 dysregulation and additionally search for the specific underlying SNP’s. RGMA mRNA was found to be upregulated in PD SN in two independent gene transcription profiling studies (in one 7 PD and 8 con-trol samples were used (Bossers et al., 2009) and in the other 3 PD and 5 control samples were used (Neurocrine Biosciences, 2012)). So far, none of these four genes has been identified as a PD susceptibility gene in genome wide association studies (GWAS). Use of larger cohorts may further identify more genetic risk fac-tors. Additionally, GWAS was argued to be inefficient in identifying rare variants associated with disease susceptibility. Instead, whole genome resequencing us-ing next generation sequencing techniques should be employed, which recently identified GBA as a PD susceptibility gene previously not found by GWAS (Mitsui et al., 2009). Another possibility is to specifically sequence the promoter region of CTDSP1, PTMA, RGMA and WWC1 in a large PD cohort to assess whether dif-ferential expression is due to alternations in the regulation of mRNA synthesis.

Unraveling the role of RGMA in axonal degeneration in PD

RGMA overexpression induced dramatic changes in the adult mouse nigros-triatal DAergic system (Chapter 7). Upregulation of RGMA in DAergic neurons of the SN may lead to axonal transport and secretion of increased amounts of RGMA in the striatum. Based on its Neogenin-dependent axon-repulsive charac-teristics, high RGMA levels in the striatum may induce loss of nigrostriatal syn-aptic contacts and axonal retraction inducing ‘pathological pruning’ and finally neuronal death in the SN (Figure 2C). Below we propose experimental strate-gies to test this hypothesis and unravel the mechanism of RGMA induced DAergic neuron death.

1. RGMA mechanism of action

Firstly, as our in vitro assays were based on neuroblastoma cells, it is im-portant to confirm the function of RGMA as a cell viability and neurite outgrowth modulator in primary DAergic neurons. Moreover, RGMA knockdown in SH-SY5Y cells showed an interaction effect with MPP(+) treatment, whereas RGMA over-expression did not rescue these cells from MPP(+) toxicity. We hypothesize that this is a consequence of Neogenin being already occupied by endogenous RGMA protein. These observations should also be confirmed in primary DAergic cell cultures.

Secondly, it is important to determine the exact mechanisms that are in-volved in DAergic neuronal death after RGMA overexpression in mouse SN. By using Neogenin knockout mice, we can determine if this process is Neogenin de-pendent. These mice have recently become available through collaboration with Jean-Francois Cloutier (McGill University, Canada, and Jeroen Pasterkamp, Utre-


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cht University). Further, to validate our proposed hypothesis, it should be deter-mined whether the primary effect of RGMA is indeed to induce axonal retraction from the striatum. This can be investigated by increasing RGMA protein levels specifically in the mouse striatum through either RGMA protein infusion direct-ly into the ventricle system, or by astrocyte specific RGMA AAV-mediated over-expression in the striatum. The astrocytic expression prevents the confounding effect of neuron-mediated RGMA transport to other brain areas. Alternatively, we can track the DAergic axons and follow their retraction after RGMA overex-pression in the SN at specific time points during the development of the neuro-pathology. If axons retract from the striatum before the DAergic neuronal loss in the SN this may be evidence that the protein is required in the projection area and thus is causally involved in the axonal degeneration process. Finally, we can determine if RGMA signaling in the midbrain DAergic neurons has any effect on mitochondrial activity, as suggested by our in vitro studies, by investigating im-munohistochemically the expression of mitochondrial activity and other stress markers.

2. Intervention studies modulating RGMA signaling

Our data suggests that inhibition of RGMA signaling in the striatum may reduce pathological pruning induced by RGMA overexpression. As discussed in Chapter 7, RGMA binds to its dependence receptor Neogenin, activating the axon repulsion signaling pathway via RhoA/Rho-kinase and PKC (Braak et al., 2003; reviewed in Yamashita et al., 2007; Wilson and Key, 2007). To reverse the axon repulsion activity of RGMA it is possible to block the RGMA-Neogenin binding us-ing either RGMA functional blocking antibodies, previously used in mouse EAE model (Muramatsu et al., 2011) and in a rat spinal cord injury model (Hata et al., 2006), or peptides that act as antagonists of RGMA, which have so far only been tested in vitro (Suda et al., 2008). There is one potential pitfall to this approach. Neogenin is a dependence receptor and it has to be occupied by its ligand or oth-erwise it will induce apoptosis (Mehlen and Bredesen, 2011). Therefore block-ing RGMA-Neogenin binding with an antagonist has to be carefully controlled so that some RGMA can still bind to its receptor on neuronal cell bodies (at levels that presumably bind in a control SN (see Chapter 2 for RGMA expression in con-trol SN)).

Repulsive RGMA signaling can be also blocked directly at the level of the RhoA/Rho-kinase. This approach has been previously considered and extensive-ly discussed as a clinical application after spinal cord injury (Kubo and Yamashi-ta, 2007). Although this approach may influence other repulsive signaling path-ways in neurons, since it would block the general activity of Rho kinase and its downstream signaling, this may be an advantage for the degenerating axons of DAergic neurons, as possible other repulsive guidance signaling is blocked. One of the Rho-kinase inhibitors, fasudil, has been on the market for over 10 years in Japan for the treatment of cerebral vasospasm and was clinically tested in the US for cardiovascular disorders (reviewed in Olson, 2008). It crosses the blood

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brain barrier and is therefore an attractive approach to be tested in adult mice overexpressing RGMA in DAergic neurons.

Apart from blocking RGMA signaling, stimulating the regeneration of lost axons and reestablishment of their connectivity to striatal targets is a promising therapeutic approach. Interestingly, a recent study showed successful regrowth of axons within the adult nigrostriatal projections after a 6-OHDA leasion by ac-tivation of Akt/mTor signaling in the surviving SN DAergic neurons (Kim et al., 2011). Activation of this intrinsic signaling pathway may stimulate the surviving 70% of DAergic cells in the early PD SN to sprout and extend their axons towards their projection areas. Interestingly, Kim et al., showed that there was no need for additional steering of the axons to reach their correct targets, as they fol-lowed their original projection trajectories very accurately (2011). It is therefore very well possible that the adult nervous system, if not mechanically disrupted, as in axotomy or stroke, contains in its parenchyma molecular signals that guide axons to the correct localization and stabilize the new axonal tracts that are formed. This in turn allows new neurites to follow these tracts and functionally integrate with their original targets. Therefore a combination of the inhibition of RGMa signaling and Akt/mTOR induced axon regrowth can be an interesting approach to rescue and stimulate DAergic neurons to regain their function and successfully once again deliver DA into the striatum.

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Reference List

260

Ahmad,S.O., Park,J.H., Stenho-Bittel,L., & Lau,Y.S. (2009). Effects of endurance exercise on ventral tegmental area neurons in the chronic 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine and probenecid-treated mice. Neurosci.Lett., 450(2), 102-105.Albers DS, Weiss SW, Iadarola MJ, Standaert DG (1999) Immunohistochemical localization of N-methyl-D-aspartate and alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionate receptor subunits in the substantia nigra pars compacta of the rat. Neuroscience 89:209-220.Alvarez-Fischer,D., Guerreiro,S., Hunot,S., Saurini,F., Marien,M., Sokoloff,P., Hirsch,E.C., Hartmann,A., & Michel,P.P. (2008). Modelling Parkinson-like neurodegeneration via osmotic minipump delivery of MPTP and probenecid. J.Neurochem., 107(3), 701-711.Araujo J, Breuer P, Dieringer S, Krauss S, Dorn S, Zimmermann K, Pfeifer A, Klockgether T, Wuellner U, Evert BO (2011) FOXO4-dependent upregulation of superoxide dismutase-2 in response to oxidative stress is impaired in spinocerebellar ataxia type 3. Hum Mol Genet 20:2928-2941.Aruga J, Mikoshiba K (2003) Identification and characterization of Slitrk, a novel neuronal transmembrane protein family controlling neurite outgrowth. Mol Cell Neurosci 24:117-129.Bao AM, Hestiantoro A, Van Someren EJ, Swaab DF, Zhou JN (2005) Colocalization of corti-cotropin-releasing hormone and oestrogen receptor-alpha in the paraventricular nucleus of the hypothalamus in mood disorders. Brain 128:1301-1313.Barber-Singh,J., Seo,B.B., Nakamaru-Ogiso,E., Lau,Y.S., Matsuno-Yagi,A., & Yagi,T. (2009). Neuroprotective effect of long-term NDI1 gene expression in a chronic mouse model of Par-kinson disorder. Rejuvenation.Res., 12(4), 259-267.Barcia,C., Fernandez,B.A., Poza,M., & Herrero,M.T. (2003). Parkinson’s disease and inflamma-tory changes. Neurotox.Res., 5(6), 411-418.Baumgartner R, Poernbacher I, Buser N, Hafen E, Stocker H (2010) The WW domain protein Kibra acts upstream of Hippo in Drosophila. Dev Cell 18:309-316.Beal,M.F. (2003). Mitochondria, oxidative damage, and inflammation in Parkinson’s disease. Ann.N.Y.Acad.Sci., 991, 120-131.Beissbarth T, Speed TP (2004) GOstat: find statistically overrepresented Gene Ontologies within a group of genes. Bioinformatics 20:1464-1465.Benabid AL (2010) Gene therapy for Parkinson’s disease: do we have the cure? Lancet Neurol 9:1142-1143.Bender A, Krishnan KJ, Morris CM, Taylor GA, Reeve AK, Perry RH, Jaros E, Hersheson JS, Betts J, Klopstock T, Taylor RW, Turnbull DM (2006) High levels of mitochondrial DNA dele-tions in substantia nigra neurons in aging and Parkinson disease. Nat Genet 38:515-517.Berman SB, Hastings TG (1999) Dopamine oxidation alters mitochondrial respiration and induces permeability transition in brain mitochondria: implications for Parkinson’s disease. J Neurochem 73:1127-1137.Betarbet,R., Sherer,T.B., & Greenamyre,J.T. (2002). Animal models of Parkinson’s disease. Bioessays, 24(4), 308-318.Beyer K, Domingo-Sabat M, Humbert J, Carrato C, Ferrer I, Ariza A (2008) Differential expression of alpha-synuclein, parkin, and synphilin-1 isoforms in Lewy body disease. Neu-rogenetics 9:163-172.Biedler JL, Roffler-Tarlov S, Schachner M, Freedman LS (1978) Multiple neurotransmitter synthesis by human neuroblastoma cell lines and clones. Cancer Res 38:3751-3757.

R EFER ENCE LIST

261

Blackmore MG, Moore DL, Smith RP, Goldberg JL, Bixby JL, Lemmon VP (2010) High content screening of cortical neurons identifies novel regulators of axon growth. Mol Cell Neurosci 44:43-54.Bonifati V (2007) Genetics of parkinsonism. Parkinsonism Relat Disord 13 Suppl 3:S233-S241.Bonifati V, Rizzu P, van Baren MJ, Schaap O, Breedveld GJ, Krieger E, Dekker MC, Squitieri F, Ibanez P, Joosse M, van Dongen JW, Vanacore N, van Swieten JC, Brice A, Meco G, van Duijn CM, Oostra BA, Heutink P (2003) Mutations in the DJ-1 gene associated with autosomal recessive early-onset parkinsonism. Science 299:256-259.Bossers K, Meerhoff G, Balesar R, van Dongen JW, Kruse CG, Swaab DF, Verhaagen J (2009) Analysis of gene expression in Parkinson’s disease: possible involvement of neurotrophic support and axon guidance in dopaminergic cell death. Brain Pathol 19:91-107.Bossers K, Ylstra B, Brakenhoff RH, Smeets SJ, Verhaagen J, van de Wiel MA (2010) Intensity-based analysis of dual-color gene expression data as an alternative to ratio-based analysis to enhance reproducibility. BMC Genomics 11:112.Bove,J., Prou,D., Perier,C., & Przedborski,S. (2005). Toxin-induced models of Parkinson’s disease. NeuroRx., 2(3), 484-494.Braak H, Del TK, Rub U, de Vos RA, Jansen Steur EN, Braak E (2003) Staging of brain pathol-ogy related to sporadic Parkinson’s disease. Neurobiol Aging 24:197-211.Braak,H., Del,T.K., Rub,U., de Vos,R.A., Jansen Steur,E.N., & Braak,E. (2003). Staging of brain pathology related to sporadic Parkinson’s disease. Neurobiol.Aging, 24(2), 197-211.Brill LB, Bennett JP, Jr. (2003) Dependence on electron transport chain function and intra-cellular signaling of genomic responses in SH-SY5Y cells to the mitochondrial neurotoxin MPP(+). Exp Neurol 181:25-38.Burger C, Gorbatyuk OS, Velardo MJ, Peden CS, Williams P, Zolotukhin S, Reier PJ, Mandel RJ, Muzyczka N (2004) Recombinant AAV viral vectors pseudotyped with viral capsids from se-rotypes 1, 2, and 5 display differential efficiency and cell tropism after delivery to different regions of the central nervous system. Mol Ther 10:302-317.Burke RE, O’Malley K (2012) Axon degeneration in Parkinson’s disease. Exp Neurol.Burke WJ, Li SW, Williams EA, Nonneman R, Zahm DS (2003) 3,4-Dihydroxyphenylacetalde-hyde is the toxic dopamine metabolite in vivo: implications for Parkinson’s disease pathogen-esis. Brain Res 989:205-213.Burke,R.E. & O’Malley,K. (2012). Axon degeneration in Parkinson’s disease. Exp.Neurol..Bustos G, Abarca J, Campusano J, Bustos V, Noriega V, Aliaga E (2004) Functional interactions between somatodendritic dopamine release, glutamate receptors and brain-derived neuro-trophic factor expression in mesencephalic structures of the brain. Brain Res Brain Res Rev 47:126-144.Cahoy JD, Emery B, Kaushal A, Foo LC, Zamanian JL, Christopherson KS, Xing Y, Lubischer JL, Krieg PA, Krupenko SA, Thompson WJ, Barres BA (2008) A transcriptome database for astrocytes, neurons, and oligodendrocytes: a new resource for understanding brain develop-ment and function. J Neurosci 28:264-278.Cantuti-Castelvetri I, Keller-McGandy C, Bouzou B, Asteris G, Clark TW, Frosch MP, Standaert DG (2007) Effects of gender on nigral gene expression and parkinson disease. Neurobiol Dis 26:606-614.

262

Capelli LP, Krepischi AC, Gurgel-Giannetti J, Mendes MF, Rodrigues T, Varela MC, Koiffmann CP, Rosenberg C (2012) Deletion of the RMGA and CHD2 genes in a child with epilepsy and mental deficiency. Eur J Med Genet 55:132-134.Castro DS, Martynoga B, Parras C, Ramesh V, Pacary E, Johnston C, Drechsel D, Lebel-Potter M, Garcia LG, Hunt C, Dolle D, Bithell A, Ettwiller L, Buckley N, Guillemot F (2011) A novel function of the proneural factor Ascl1 in progenitor proliferation identified by genome-wide characterization of its targets. Genes Dev 25:930-945.Chen X, Rzhetskaya M, Kareva T, Bland R, During MJ, Tank AW, Kholodilov N, Burke RE (2008) Antiapoptotic and trophic effects of dominant-negative forms of dual leucine zipper kinase in dopamine neurons of the substantia nigra in vivo. J Neurosci 28:672-680.Cheng HC, Ulane CM, Burke RE (2010) Clinical progression in Parkinson disease and the neurobiology of axons. Ann Neurol 67:715-725.Cheng,H.C., Ulane,C.M., & Burke,R.E. (2010). Clinical progression in Parkinson disease and the neurobiology of axons. Ann.Neurol., 67(6), 715-725.Cheung YT, Lau WK, Yu MS, Lai CS, Yeung SC, So KF, Chang RC (2009) Effects of all-trans-retinoic acid on human SH-SY5Y neuroblastoma as in vitro model in neurotoxicity research. Neurotoxicology 30:127-135.Choudhary S, Xiao T, Vergara LA, Srivastava S, Nees D, Piatigorsky J, Ansari NH (2005) Role of aldehyde dehydrogenase isozymes in the defense of rat lens and human lens epithelial cells against oxidative stress. Invest Ophthalmol Vis Sci 46:259-267.Chuaqui RF, Bonner RF, Best CJ, Gillespie JW, Flaig MJ, Hewitt SM, Phillips JL, Krizman DB, Tangrea MA, Ahram M, Linehan WM, Knezevic V, Emmert-Buck MR (2002) Post-analysis follow-up and validation of microarray experiments. Nat Genet 32 Suppl:509-514.Chung,C.Y., Koprich,J.B., Siddiqi,H., & Isacson,O. (2009). Dynamic changes in presynaptic and axonal transport proteins combined with striatal neuroinflammation precede dopaminergic neuronal loss in a rat model of AAV alpha-synucleinopathy. J.Neurosci., 29(11), 3365-3373.Cicchetti F, Drouin-Ouellet J, Gross RE (2009) Environmental toxins and Parkinson’s disease: what have we learned from pesticide-induced animal models? Trends Pharmacol Sci 30:475-483.Cole SJ, Bradford D, Cooper HM (2007) Neogenin: A multi-functional receptor regulating diverse developmental processes. Int J Biochem Cell Biol 39:1569-1575.Conn KJ, Ullman MD, Larned MJ, Eisenhauer PB, Fine RE, Wells JM (2003) cDNA microar-ray analysis of changes in gene expression associated with MPP+ toxicity in SH-SY5Y cells. Neurochem Res 28:1873-1881.Conrad S, Genth H, Hofmann F, Just I, Skutella T (2007) Neogenin-RGMa signaling at the growth cone is bone morphogenetic protein-independent and involves RhoA, ROCK, and PKC. J Biol Chem 282:16423-16433.Copits BA, Robbins JS, Frausto S, Swanson GT (2011) Synaptic targeting and functional modulation of GluK1 kainate receptors by the auxiliary neuropilin and tolloid-like (NETO) proteins. J Neurosci 31:7334-7340.Corneveaux JJ, et al. (2010) Evidence for an association between KIBRA and late-onset Al-zheimer’s disease. Neurobiol Aging 31:901-909.

R EFER ENCE LIST

263

Cuende J, Moreno S, Bolanos JP, Almeida A (2008) Retinoic acid downregulates Rae1 leading to APC(Cdh1) activation and neuroblastoma SH-SY5Y differentiation. Oncogene 27:3339-3344.Cuenin S, Tinel A, Janssens S, Tschopp J (2008) p53-induced protein with a death domain (PIDD) isoforms differentially activate nuclear factor-kappaB and caspase-2 in response to genotoxic stress. Oncogene 27:387-396.Damier P, Hirsch EC, Agid Y, Graybiel AM (1999) The substantia nigra of the human brain. II. Patterns of loss of dopamine-containing neurons in Parkinson’s disease. Brain 122 ( Pt 8):1437-1448.Dauer W, Przedborski S (2003) Parkinson’s disease: mechanisms and models. Neuron 39:889-909.Dauer,W. & Przedborski,S. (2003). Parkinson’s disease: mechanisms and models. Neuron, 39(6), 889-909.Dawson TM, Dawson VL (2003) Molecular pathways of neurodegeneration in Parkinson’s disease. Science 302:819-822.Deglon N, Tseng JL, Bensadoun JC, Zurn AD, Arsenijevic Y, Pereira de AL, Zufferey R, Trono D, Aebischer P (2000) Self-inactivating lentiviral vectors with enhanced transgene expression as potential gene transfer system in Parkinson’s disease. Hum Gene Ther 11:179-190.Dijk F, Kraal-Muller E, Kamphuis W (2004) Ischemia-induced changes of AMPA-type glu-tamate receptor subunit expression pattern in the rat retina: a real-time quantitative PCR study. Invest Ophthalmol Vis Sci 45:330-341.Ding Q, Bruce-Keller AJ, Chen Q, Keller JN (2004) Analysis of gene expression in neural cells subject to chronic proteasome inhibition. Free Radic Biol Med 36:445-455.Driver JA, Logroscino G, Gaziano JM, Kurth T (2009) Incidence and remaining lifetime risk of Parkinson disease in advanced age. Neurology 72:432-438.Dugan JP, Stratton A, Riley HP, Farmer WT, Mastick GS (2011) Midbrain dopaminergic axons are guided longitudinally through the diencephalon by Slit/Robo signals. Mol Cell Neurosci 46:347-356.Duke DC, Moran LB, Pearce RK, Graeber MB (2007) The medial and lateral substantia nigra in Parkinson’s disease: mRNA profiles associated with higher brain tissue vulnerability. Neurogenetics 8:83-94.Dull T, Zufferey R, Kelly M, Mandel RJ, Nguyen M, Trono D, Naldini L (1998) A third-genera-tion lentivirus vector with a conditional packaging system. J Virol 72:8463-8471.Edwards TL, Scott WK, Almonte C, Burt A, Powell EH, Beecham GW, Wang L, Zuchner S, Konidari I, Wang G, Singer C, Nahab F, Scott B, Stajich JM, Pericak-Vance M, Haines J, Vance JM, Martin ER (2010) Genome-wide association study confirms SNPs in SNCA and the MAPT region as common risk factors for Parkinson disease. Ann Hum Genet 74:97-109.Elstner M, Morris CM, Heim K, Bender A, Mehta D, Jaros E, Klopstock T, Meitinger T, Turnbull DM, Prokisch H (2011) Expression analysis of dopaminergic neurons in Parkinson’s disease and aging links transcriptional dysregulation of energy metabolism to cell death. Acta Neu-ropathol 122:75-86.Ernsberger U (2000) Evidence for an evolutionary conserved role of bone morphogenetic protein growth factors and phox2 transcription factors during noradrenergic differentiation

264

of sympathetic neurons. Induction of a putative synexpression group of neurotransmitter-synthesizing enzymes. Eur J Biochem 267:6976-6981.Ferri AL, Cavallaro M, Braida D, Di CA, Canta A, Vezzani A, Ottolenghi S, Pandolfi PP, Sala M, DeBiasi S, Nicolis SK (2004) Sox2 deficiency causes neurodegeneration and impaired neuro-genesis in the adult mouse brain. Development 131:3805-3819.Fitzsimons HL, Bland RJ, During MJ (2002) Promoters and regulatory elements that improve adeno-associated virus transgene expression in the brain. Methods 28:227-236.Fleming,S.M., Delville,Y., & Schallert,T. (2005). An intermittent, controlled-rate, slow pro-gressive degeneration model of Parkinson’s disease: antiparkinson effects of Sinemet and protective effects of methylphenidate. Behav.Brain Res., 156(2), 201-213.Galter D, Buervenich S, Carmine A, Anvret M, Olson L (2003) ALDH1 mRNA: presence in hu-man dopamine neurons and decreases in substantia nigra in Parkinson’s disease and in the ventral tegmental area in schizophrenia. Neurobiol Dis 14:637-647.Gao GP, Alvira MR, Wang L, Calcedo R, Johnston J, Wilson JM (2002) Novel adeno-associated viruses from rhesus monkeys as vectors for human gene therapy. Proc Natl Acad Sci U S A 99:11854-11859.Geeven G, Macgillavry HD, Eggers R, Sassen MM, Verhaagen J, Smit AB, de Gunst MC, van Kesteren RE (2011) LLM3D: a log-linear modeling-based method to predict functional gene regulatory interactions from genome-wide expression data. Nucleic Acids Res 39:5313-5327.Geffard M, Buijs RM, Seguela P, Pool CW, Le MM (1984) First demonstration of highly specific and sensitive antibodies against dopamine. Brain Res 294:161-165.Genevet A, Wehr MC, Brain R, Thompson BJ, Tapon N (2010) Kibra is a regulator of the Salva-dor/Warts/Hippo signaling network. Dev Cell 18:300-308.German DC, Manaye KF, Sonsalla PK, Brooks BA (1992) Midbrain dopaminergic cell loss in Parkinson’s disease and MPTP-induced parkinsonism: sparing of calbindin-D28k-containing cells. Ann N Y Acad Sci 648:42-62.Gorell JM, Peterson EL, Rybicki BA, Johnson CC (2004) Multiple risk factors for Parkinson’s disease. J Neurol Sci 217:169-174.Greenamyre,J.T. & Hastings,T.G. (2004). Biomedicine. Parkinson’s--divergent causes, conver-gent mechanisms. Science, 304(5674), 1120-1122.Greene JG (2012) Current status and future directions of gene expression profiling in Parkin-son’s disease. Neurobiol Dis 45:76-82.Grimm D, Kay MA, Kleinschmidt JA (2003) Helper virus-free, optically controllable, and two-plasmid-based production of adeno-associated virus vectors of serotypes 1 to 6. Mol Ther 7:839-850.Grunblatt E, Mandel S, Jacob-Hirsch J, Zeligson S, Amariglo N, Rechavi G, Li J, Ravid R, Roggendorf W, Riederer P, Youdim MB (2004) Gene expression profiling of parkinsonian sub-stantia nigra pars compacta; alterations in ubiquitin-proteasome, heat shock protein, iron and oxidative stress regulated proteins, cell adhesion/cellular matrix and vesicle trafficking genes. J Neural Transm 111:1543-1573.Grunblatt E, Zehetmayer S, Jacob CP, Muller T, Jost WH, Riederer P (2010) Pilot study: pe-ripheral biomarkers for diagnosing sporadic Parkinson’s disease. J Neural Transm 117:1387-1393.

R EFER ENCE LIST

265

Haehner,A., Hummel,T., Hummel,C., Sommer,U., Junghanns,S., & Reichmann,H. (2007). Olfac-tory loss may be a first sign of idiopathic Parkinson’s disease. Mov Disord., 22(6), 839-842.Hanisch UK (2002) Microglia as a source and target of cytokines. Glia 40:140-155.Hardy J (2010) Genetic analysis of pathways to Parkinson disease. Neuron 68:201-206.Hardy J, Cai H, Cookson MR, Gwinn-Hardy K, Singleton A (2006) Genetics of Parkinson’s disease and parkinsonism. Ann Neurol 60:389-398.Hata K, Fujitani M, Yasuda Y, Doya H, Saito T, Yamagishi S, Mueller BK, Yamashita T (2006) RGMa inhibition promotes axonal growth and recovery after spinal cord injury. J Cell Biol 173:47-58.Hauser MA, Li YJ, Xu H, Noureddine MA, Shao YS, Gullans SR, Scherzer CR, Jensen RV, McLaurin AC, Gibson JR, Scott BL, Jewett RM, Stenger JE, Schmechel DE, Hulette CM, Vance JM (2005) Expression profiling of substantia nigra in Parkinson disease, progressive supranu-clear palsy, and frontotemporal dementia with parkinsonism. Arch Neurol 62:917-921.Henchcliffe C, Beal MF (2008) Mitochondrial biology and oxidative stress in Parkinson dis-ease pathogenesis. Nat Clin Pract Neurol 4:600-609.Hendriks WT, Eggers R, Verhaagen J, Boer GJ (2007) Gene transfer to the spinal cord neural scar with lentiviral vectors: predominant transgene expression in astrocytes but not in men-ingeal cells. J Neurosci Res 85:3041-3052.Hermening S, Kugler S, Bahr M, Isenmann S (2006) Improved high-capacity adenoviral vec-tors for high-level neuron-restricted gene transfer to the CNS. J Virol Methods 136:30-37.Hermens WT, ter BO, Dijkhuizen PA, Sonnemans MA, Grimm D, Kleinschmidt JA, Verhaagen J (1999) Purification of recombinant adeno-associated virus by iodixanol gradient ultracentri-fugation allows rapid and reproducible preparation of vector stocks for gene transfer in the nervous system. Hum Gene Ther 10:1885-1891.Hirsch EC, Breidert T, Rousselet E, Hunot S, Hartmann A, Michel PP (2003) The role of glial reaction and inflammation in Parkinson’s disease. Ann N Y Acad Sci 991:214-228.Huitinga I, van der Cammen M, Salm L, Erkut Z, van DA, Tilders F, Swaab D (2000) IL-1beta immunoreactive neurons in the human hypothalamus: reduced numbers in multiple sclero-sis. J Neuroimmunol 107:8-20.Iancu R, Mohapel P, Brundin P, Paul G (2005) Behavioral characterization of a unilateral 6-OHDA-lesion model of Parkinson’s disease in mice. Behav Brain Res 162:1-10.Itokazu T, Fujita Y, Takahashi R, Yamashita T (2012) Identification of the neogenin-binding site on the repulsive guidance molecule A. PLoS One 7:e32791.Jackson-Lewis,V. & Przedborski,S. (2007). Protocol for the MPTP mouse model of Parkinson’s disease. Nat.Protoc., 2(1), 141-151.Jacobs FM, Smits SM, Noorlander CW, von OL, van der Linden AJ, Burbach JP, Smidt MP (2007) Retinoic acid counteracts developmental defects in the substantia nigra caused by Pitx3 deficiency. Development 134:2673-2684.Jacobs FM, van der Linden AJ, Wang Y, von OL, Sul HS, Burbach JP, Smidt MP (2009) Identifi-cation of Dlk1, Ptpru and Klhl1 as novel Nurr1 target genes in meso-diencephalic dopamine neurons. Development 136:2363-2373.Jacobs FM, Veenvliet JV, Almirza WH, Hoekstra EJ, von OL, van der Linden AJ, Neijts R, Koerkamp MG, van LD, Holstege FC, Burbach JP, Smidt MP (2011) Retinoic acid-dependent

266

and -independent gene-regulatory pathways of Pitx3 in meso-diencephalic dopaminergic neurons. Development 138:5213-5222.Jain S, Heutink P (2010) From single genes to gene networks: high-throughput-high-content screening for neurological disease. Neuron 68:207-217.Jain S, van Kesteren RE, Heutink P (2012) High content screening in neurodegenerative diseases. J Vis Expe3452.Jakobsson J, Ericson C, Jansson M, Bjork E, Lundberg C (2003) Targeted transgene expression in rat brain using lentiviral vectors. J Neurosci Res 73:876-885.Jankovic J (2008) Parkinson’s disease: clinical features and diagnosis. J Neurol Neurosurg Psychiatry 79:368-376.Ji J, Li Q, Xie Y, Zhang X, Cui S, Shi S, Chen X (2012) Overexpression of Robo2 causes defects in the recruitment of metanephric mesenchymal cells and ureteric bud branching morphogen-esis. Biochem Biophys Res Commun.Jossan,S.S., Sakurai,E., & Oreland,L. (1989). MPTP toxicity in relation to age, dopamine up-take and MAO-B activity in two rodent species. Pharmacol.Toxicol., 64(3), 314-318.Jukam D, Desplan C (2011) Binary regulation of Hippo pathway by Merlin/NF2, Kibra, Lgl, and Melted specifies and maintains postmitotic neuronal fate. Dev Cell 21:874-887.Kanao T, Venderova K, Park DS, Unterman T, Lu B, Imai Y (2010) Activation of FoxO by LRRK2 induces expression of proapoptotic proteins and alters survival of postmitotic dopaminergic neuron in Drosophila. Hum Mol Genet 19:3747-3758.Kaplan DR, Matsumoto K, Lucarelli E, Thiele CJ (1993) Induction of TrkB by retinoic acid mediates biologic responsiveness to BDNF and differentiation of human neuroblastoma cells. Eukaryotic Signal Transduction Group. Neuron 11:321-331.Kaplitt MG, Feigin A, Tang C, Fitzsimons HL, Mattis P, Lawlor PA, Bland RJ, Young D, Strybing K, Eidelberg D, During MJ (2007) Safety and tolerability of gene therapy with an adeno-associated virus (AAV) borne GAD gene for Parkinson’s disease: an open label, phase I trial. Lancet 369:2097-2105.Kaplitt MG, Leone P, Samulski RJ, Xiao X, Pfaff DW, O’Malley KL, During MJ (1994) Long-term gene expression and phenotypic correction using adeno-associated virus vectors in the mammalian brain. Nat Genet 8:148-154.Karapetian RN, Evstafieva AG, Abaeva IS, Chichkova NV, Filonov GS, Rubtsov YP, Sukhacheva EA, Melnikov SV, Schneider U, Wanker EE, Vartapetian AB (2005) Nuclear oncoprotein prothymosin alpha is a partner of Keap1: implications for expression of oxidative stress-protecting genes. Mol Cell Biol 25:1089-1099.Kauppi K, Nilsson LG, Adolfsson R, Eriksson E, Nyberg L (2011) KIBRA polymorphism is related to enhanced memory and elevated hippocampal processing. J Neurosci 31:14218-14222.Kim HK, Zhang H, Li H, Wu TT, Swisher S, He D, Wu L, Xu J, Elmets CA, Athar M, Xu XC, Xu H (2008) Slit2 inhibits growth and metastasis of fibrosarcoma and squamous cell carcinoma. Neoplasia 10:1411-1420.Kim JH, Yoon S, Won M, Sim SH, Ko JJ, Han S, Lee KA, Lee K, Bae J (2009) HIP1R interacts with a member of Bcl-2 family, BCL2L10, and induces BAK-dependent cell death. Cell Physiol Biochem 23:43-52.

R EFER ENCE LIST

267

Kim SR, Chen X, Oo TF, Kareva T, Yarygina O, Wang C, During M, Kholodilov N, Burke RE (2011) Dopaminergic pathway reconstruction by Akt/Rheb-induced axon regeneration. Ann Neurol 70:110-120.Kito K, Ito T, Sakaki Y (1997) Fluorescent differential display analysis of gene expression in differentiating neuroblastoma cells. Gene 184:73-81.Kittler R, Putz G, Pelletier L, Poser I, Heninger AK, Drechsel D, Fischer S, Konstantinova I, Habermann B, Grabner H, Yaspo ML, Himmelbauer H, Korn B, Neugebauer K, Pisabarro MT, Buchholz F (2004) An endoribonuclease-prepared siRNA screen in human cells identifies genes essential for cell division. Nature 432:1036-1040.Klein RL, Dayton RD, Leidenheimer NJ, Jansen K, Golde TE, Zweig RM (2006) Efficient neuro-nal gene transfer with AAV8 leads to neurotoxic levels of tau or green fluorescent proteins. Mol Ther 13:517-527.Klein RL, Dayton RD, Tatom JB, Diaczynsky CG, Salvatore MF (2008) Tau expression levels from various adeno-associated virus vector serotypes produce graded neurodegenerative disease states. Eur J Neurosci 27:1615-1625.Koeberle PD, Tura A, Tassew NG, Schlichter LC, Monnier PP (2010) The repulsive guidance molecule, RGMa, promotes retinal ganglion cell survival in vitro and in vivo. Neuroscience 169:495-504.Korecka JA, Verhaagen J, Hol EM (2007) Cell-replacement and gene-therapy strategies for Parkinson’s and Alzheimer’s disease. Regen Med 2:425-446.Kroemer G, Galluzzi L, Brenner C (2007) Mitochondrial membrane permeabilization in cell death. Physiol Rev 87:99-163.Kubo T, Endo M, Hata K, Taniguchi J, Kitajo K, Tomura S, Yamaguchi A, Mueller BK, Yamashita T (2008) Myosin IIA is required for neurite outgrowth inhibition produced by repulsive guidance molecule. J Neurochem 105:113-126.Kubo T, Tokita S, Yamashita T (2011) Repulsive Guidance Molecule-a and Demyelination: Implications for Multiple Sclerosis. J Neuroimmune Pharmacol.Kubo T, Yamashita T (2007) Rho-ROCK inhibitors for the treatment of CNS injury. Recent Pat CNS Drug Discov 2:173-179.Kugler S, Kilic E, Bahr M (2003a) Human synapsin 1 gene promoter confers highly neuron-specific long-term transgene expression from an adenoviral vector in the adult rat brain depending on the transduced area. Gene Ther 10:337-347.Kugler S, Lingor P, Scholl U, Zolotukhin S, Bahr M (2003b) Differential transgene expres-sion in brain cells in vivo and in vitro from AAV-2 vectors with small transcriptional control units. Virology 311:89-95.Kurimoto K, Saitou M (2010) Single-cell cDNA microarray profiling of complex biological processes of differentiation. Curr Opin Genet Dev 20:470-477.Lah GJ, Key B (2012) Dual roles of the chemorepellent axon guidance molecule RGMa in establishing pioneering axon tracts and neural fate decisions in embryonic vertebrate fore-brain. Dev Neurobiol.Lander ES, et al. (2001) Initial sequencing and analysis of the human genome. Nature 409:860-921.

268

Langston JW, Forno LS, Tetrud J, Reeves AG, Kaplan JA, Karluk D (1999) Evidence of active nerve cell degeneration in the substantia nigra of humans years after 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine exposure. Ann Neurol 46:598-605.Lanoue AC, Dumitriu A, Myers RH, Soghomonian JJ (2010) Decreased glutamic acid decar-boxylase mRNA expression in prefrontal cortex in Parkinson’s disease. Exp Neurol 226:207-217.Lau,Y.S., Patki,G., Das-Panja,K., Le,W.D., & Ahmad,S.O. (2011). Neuroprotective effects and mechanisms of exercise in a chronic mouse model of Parkinson’s disease with moderate neurodegeneration. Eur.J.Neurosci., 33(7), 1264-1274.Lau,Y.S., Trobough,K.L., Crampton,J.M., & Wilson,J.A. (1990). Effects of probenecid on striatal dopamine depletion in acute and long-term 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-treated mice. Gen.Pharmacol., 21(2), 181-187.Lavoie B, Parent A (1991) Dopaminergic neurons expressing calbindin in normal and parkin-sonian monkeys. Neuroreport 2:601-604.Lein ES, et al. (2007) Genome-wide atlas of gene expression in the adult mouse brain. Nature 445:168-176.Leroy E, Boyer R, Auburger G, Leube B, Ulm G, Mezey E, Harta G, Brownstein MJ, Jonnalagada S, Chernova T, Dehejia A, Lavedan C, Gasser T, Steinbach PJ, Wilkinson KD, Polymeropoulos MH (1998) The ubiquitin pathway in Parkinson’s disease. Nature 395:451-452.Lesnick TG, Papapetropoulos S, Mash DC, Ffrench-Mullen J, Shehadeh L, de AM, Henley JR, Rocca WA, Ahlskog JE, Maraganore DM (2007) A genomic pathway approach to a complex disease: axon guidance and Parkinson disease. PLoS Genet 3:e98.Lewandowski NM, Ju S, Verbitsky M, Ross B, Geddie ML, Rockenstein E, Adame A, Muham-mad A, Vonsattel JP, Ringe D, Cote L, Lindquist S, Masliah E, Petsko GA, Marder K, Clark LN, Small SA (2010) Polyamine pathway contributes to the pathogenesis of Parkinson disease. Proc Natl Acad Sci U S A 107:16970-16975.Lewis PA, Cookson MR (2011) Gene expression in the Parkinson’s disease brain. Brain Res Bull.Li,L.H., Qin,H.Z., Wang,J.L., Wang,J., Wang,X.L., & Gao,G.D. (2009a). Axonal degeneration of nigra-striatum dopaminergic neurons induced by 1-methyl-4-phenyl-1,2,3,6-tetrahydropyri-dine in mice. J.Int.Med.Res., 37(2), 455-463.Li,Y., Liu,W., Oo,T.F., Wang,L., Tang,Y., Jackson-Lewis,V., Zhou,C., Geghman,K., Bogdanov,M., Przedborski,S., Beal,M.F., Burke,R.E., & Li,C. (2009b). Mutant LRRK2(R1441G) BAC transgen-ic mice recapitulate cardinal features of Parkinson’s disease. Nat.Neurosci., 12(7), 826-828.Lim ST, Airavaara M, Harvey BK (2010) Viral vectors for neurotrophic factor delivery: a gene therapy approach for neurodegenerative diseases of the CNS. Pharmacol Res 61:14-26.Lin L, Isacson O (2006) Axonal growth regulation of fetal and embryonic stem cell-derived dopaminergic neurons by Netrin-1 and Slits. Stem Cells 24:2504-2513.Liu Y, Kim D, Himes BT, Chow SY, Schallert T, Murray M, Tessler A, Fischer I (1999) Trans-plants of fibroblasts genetically modified to express BDNF promote regeneration of adult rat rubrospinal axons and recovery of forelimb function. J Neurosci 19:4370-4387.Liu Y, Okada T, Nomoto T, Ke X, Kume A, Ozawa K, Xiao S (2007) Promoter effects of adeno-associated viral vector for transgene expression in the cochlea in vivo. Exp Mol Med 39:170-175.

R EFER ENCE LIST

269

Lopes FM, Schroder R, da Frota MLJ, Zanotto-Filho A, Muller CB, Pires AS, Meurer RT, Colpo GD, Gelain DP, Kapczinski F, Moreira JC, Fernandes MC, Klamt F (2010) Comparison between proliferative and neuron-like SH-SY5Y cells as an in vitro model for Parkinson disease stud-ies. Brain Res 1337:85-94.Lopez-Carballo G, Moreno L, Masia S, Perez P, Barettino D (2002) Activation of the phospha-tidylinositol 3-kinase/Akt signaling pathway by retinoic acid is required for neural differen-tiation of SH-SY5Y human neuroblastoma cells. J Biol Chem 277:25297-25304.Lotharius J, O’Malley KL (2000) The parkinsonism-inducing drug 1-methyl-4-phenylpyri-dinium triggers intracellular dopamine oxidation. A novel mechanism of toxicity. J Biol Chem 275:38581-38588.Lundberg C, Bjorklund T, Carlsson T, Jakobsson J, Hantraye P, Deglon N, Kirik D (2008) Ap-plications of lentiviral vectors for biology and gene therapy of neurological disorders. Curr Gene Ther 8:461-473.MacGillavry HD, Stam FJ, Sassen MM, Kegel L, Hendriks WT, Verhaagen J, Smit AB, van Kesteren RE (2009) NFIL3 and cAMP response element-binding protein form a transcrip-tional feedforward loop that controls neuronal regeneration-associated gene expression. J Neurosci 29:15542-15550.Maden M (2007) Retinoic acid in the development, regeneration and maintenance of the nervous system. Nat Rev Neurosci 8:755-765.Maguire-Zeiss KA, Mhyre TR, Federoff HJ (2008) Gazing into the future: Parkinson’s disease gene therapeutics to modify natural history. Exp Neurol 209:101-113.Mandel RJ, Manfredsson FP, Foust KD, Rising A, Reimsnider S, Nash K, Burger C (2006) Recombinant adeno-associated viral vectors as therapeutic agents to treat neurological disorders. Mol Ther 13:463-483.Mandel S, Grunblatt E, Riederer P, Amariglio N, Jacob-Hirsch J, Rechavi G, Youdim MB (2005) Gene expression profiling of sporadic Parkinson’s disease substantia nigra pars compacta reveals impairment of ubiquitin-proteasome subunits, SKP1A, aldehyde dehydrogenase, and chaperone HSC-70. Ann N Y Acad Sci 1053:356-375.Manfredsson FP, Mandel RJ (2010) Development of gene therapy for neurological disorders. Discov Med 9:204-211.Maraganore DM, de AM, Lesnick TG, Strain KJ, Farrer MJ, Rocca WA, Pant PV, Frazer KA, Cox DR, Ballinger DG (2005) High-resolution whole-genome association study of Parkinson disease. Am J Hum Genet 77:685-693.Markakis EA, Vives KP, Bober J, Leichtle S, Leranth C, Beecham J, Elsworth JD, Roth RH, Samulski RJ, Redmond DE, Jr. (2010) Comparative transduction efficiency of AAV vector se-rotypes 1-6 in the substantia nigra and striatum of the primate brain. Mol Ther 18:588-593.Marks WJ, Jr., et al. (2010) Gene delivery of AAV2-neurturin for Parkinson’s disease: a double-blind, randomised, controlled trial. Lancet Neurol 9:1164-1172.Matsunaga E, Chedotal A (2004) Repulsive guidance molecule/neogenin: a novel ligand-re-ceptor system playing multiple roles in neural development. Dev Growth Differ 46:481-486.Matsunaga E, Nakamura H, Chedotal A (2006) Repulsive guidance molecule plays multiple roles in neuronal differentiation and axon guidance. J Neurosci 26:6082-6088.

270

Matsunaga E, Tauszig-Delamasure S, Monnier PP, Mueller BK, Strittmatter SM, Mehlen P, Chedotal A (2004) RGM and its receptor neogenin regulate neuronal survival. Nat Cell Biol 6:749-755.McCown TJ (2005) Adeno-associated virus (AAV) vectors in the CNS. Curr Gene Ther 5:333-338.McFarland NR, Lee JS, Hyman BT, McLean PJ (2009) Comparison of transduction efficiency of recombinant AAV serotypes 1, 2, 5, and 8 in the rat nigrostriatal system. J Neurochem 109:838-845.McGeer PL, McGeer EG (2008) Glial reactions in Parkinson’s disease. Mov Disord 23:474-483.Mehlen P, Bredesen DE (2011) Dependence receptors: from basic research to drug develop-ment. Sci Signal 4:mr2.Mena-Segovia J, Winn P, Bolam JP (2008) Cholinergic modulation of midbrain dopaminergic systems. Brain Res Rev 58:265-271.Meredith GE, Kang UJ (2006) Behavioral models of Parkinson’s disease in rodents: a new look at an old problem. Mov Disord 21:1595-1606.Meredith,G.E., Totterdell,S., Beales,M., & Meshul,C.K. (2009). Impaired glutamate homeosta-sis and programmed cell death in a chronic MPTP mouse model of Parkinson’s disease. Exp.Neurol., 219(1), 334-340.Meredith,G.E., Totterdell,S., Petroske,E., Santa,C.K., Callison,R.C., Jr., & Lau,Y.S. (2002). Lyso-somal malfunction accompanies alpha-synuclein aggregation in a progressive mouse model of Parkinson’s disease. Brain Res., 956(1), 156-165.Meredith,G.E., Totterdell,S., Potashkin,J.A., & Surmeier,D.J. (2008). Modeling PD pathogenesis in mice: advantages of a chronic MPTP protocol. Parkinsonism.Relat Disord., 14 Suppl 2, S112-S115.Metzger M, Conrad S, Skutella T, Just L (2007) RGMa inhibits neurite outgrowth of neuronal progenitors from murine enteric nervous system via the neogenin receptor in vitro. J Neuro-chem 103:2665-2678.Metzler M, Gan L, Wong TP, Liu L, Helm J, Liu L, Georgiou J, Wang Y, Bissada N, Cheng K, Roder JC, Wang YT, Hayden MR (2007) NMDA receptor function and NMDA receptor-dependent phosphorylation of huntingtin is altered by the endocytic protein HIP1. J Neurosci 27:2298-2308.Miller RM, Kiser GL, Kaysser-Kranich TM, Lockner RJ, Palaniappan C, Federoff HJ (2006) Robust dysregulation of gene expression in substantia nigra and striatum in Parkinson’s disease. Neurobiol Dis 21:305-313.Miloso M, Villa D, Crimi M, Galbiati S, Donzelli E, Nicolini G, Tredici G (2004) Retinoic acid-induced neuritogenesis of human neuroblastoma SH-SY5Y cells is ERK independent and PKC dependent. J Neurosci Res 75:241-252.Minones-Moyano E, Porta S, Escaramis G, Rabionet R, Iraola S, Kagerbauer B, Espinosa-Par-rilla Y, Ferrer I, Estivill X, Marti E (2011) MicroRNA profiling of Parkinson’s disease brains identifies early downregulation of miR-34b/c which modulate mitochondrial function. Hum Mol Genet 20:3067-3078.Mirakaj V, Brown S, Laucher S, Steinl C, Klein G, Kohler D, Skutella T, Meisel C, Brommer B, Rosenberger P, Schwab JM (2011) Repulsive guidance molecule-A (RGM-A) inhibits leukocyte migration and mitigates inflammation. Proc Natl Acad Sci U S A 108:6555-6560.

R EFER ENCE LIST

271

Mitsui J, Mizuta I, Toyoda A, Ashida R, Takahashi Y, Goto J, Fukuda Y, Date H, Iwata A, Yama-moto M, Hattori N, Murata M, Toda T, Tsuji S (2009) Mutations for Gaucher disease confer high susceptibility to Parkinson disease. Arch Neurol 66:571-576.Mizuta I, Satake W, Nakabayashi Y, Ito C, Suzuki S, Momose Y, Nagai Y, Oka A, Inoko H, Fukae J, Saito Y, Sawabe M, Murayama S, Yamamoto M, Hattori N, Murata M, Toda T (2006) Multiple candidate gene analysis identifies alpha-synuclein as a susceptibility gene for sporadic Par-kinson’s disease. Hum Mol Genet 15:1151-1158.Moffat J, Grueneberg DA, Yang X, Kim SY, Kloepfer AM, Hinkle G, Piqani B, Eisenhaure TM, Luo B, Grenier JK, Carpenter AE, Foo SY, Stewart SA, Stockwell BR, Hacohen N, Hahn WC, Lander ES, Sabatini DM, Root DE (2006) A lentiviral RNAi library for human and mouse genes applied to an arrayed viral high-content screen. Cell 124:1283-1298.Monnier PP, Sierra A, Macchi P, Deitinghoff L, Andersen JS, Mann M, Flad M, Hornberger MR, Stahl B, Bonhoeffer F, Mueller BK (2002) RGM is a repulsive guidance molecule for retinal axons. Nature 419:392-395.Moore DL, Blackmore MG, Hu Y, Kaestner KH, Bixby JL, Lemmon VP, Goldberg JL (2009) KLF family members regulate intrinsic axon regeneration ability. Science 326:298-301.Moran LB, Duke DC, Deprez M, Dexter DT, Pearce RK, Graeber MB (2006) Whole genome expression profiling of the medial and lateral substantia nigra in Parkinson’s disease. Neuro-genetics 7:1-11.Mueller BK, Yamashita T, Schaffar G, Mueller R (2006) The role of repulsive guidance mol-ecules in the embryonic and adult vertebrate central nervous system. Philos Trans R Soc Lond B Biol Sci 361:1513-1529.Muramatsu R, Kubo T, Mori M, Nakamura Y, Fujita Y, Akutsu T, Okuno T, Taniguchi J, Ku-manogoh A, Yoshida M, Mochizuki H, Kuwabara S, Yamashita T (2011) RGMa modulates T cell responses and is involved in autoimmune encephalomyelitis. Nat Med 17:488-494.Muramatsu S, Fujimoto K, Kato S, Mizukami H, Asari S, Ikeguchi K, Kawakami T, Urabe M, Kume A, Sato T, Watanabe E, Ozawa K, Nakano I (2010) A phase I study of aromatic L-amino acid decarboxylase gene therapy for Parkinson’s disease. Mol Ther 18:1731-1735.Nakamura K, Bindokas VP, Marks JD, Wright DA, Frim DM, Miller RJ, Kang UJ (2000) The selective toxicity of 1-methyl-4-phenylpyridinium to dopaminergic neurons: the role of mito-chondrial complex I and reactive oxygen species revisited. Mol Pharmacol 58:271-278.Naldini L, Blomer U, Gallay P, Ory D, Mulligan R, Gage FH, Verma IM, Trono D (1996) In vivo gene delivery and stable transduction of nondividing cells by a lentiviral vector. Science 272:263-267.Nalls MA, Plagnol V, Hernandez DG, Sharma M, Sheerin UM, Saad M, Simon-Sanchez J, Schulte C, Lesage S, Sveinbjornsdottir S, Stefansson K, Martinez M, Hardy J, Heutink P, Brice A, Gas-ser T, Singleton AB, Wood NW (2011) Imputation of sequence variants for identification of genetic risks for Parkinson’s disease: a meta-analysis of genome-wide association studies. Lancet 377:641-649.Neurocrine Biosciences I (2012) Human body index- transcriptional profiling.Nguyen-Ba-Charvet KT, Chedotal A (2002) Role of Slit proteins in the vertebrate brain. J Physiol Paris 96:91-98.Nicotra A, Parvez S (2002) Apoptotic molecules and MPTP-induced cell death. Neurotoxicol Teratol 24:599-605.

272

Niederkofler V, Salie R, Sigrist M, Arber S (2004) Repulsive guidance molecule (RGM) gene function is required for neural tube closure but not retinal topography in the mouse visual system. J Neurosci 24:808-818.Nikolaus S, Antke C, Muller HW (2009) In vivo imaging of synaptic function in the central nervous system: II. Mental and affective disorders. Behav Brain Res 204:32-66.Nishimura-Akiyoshi S, Niimi K, Nakashiba T, Itohara S (2007) Axonal netrin-Gs transneuro-nally determine lamina-specific subdendritic segments. Proc Natl Acad Sci U S A 104:14801-14806.Niture SK, Jaiswal AK (2009) Prothymosin-alpha mediates nuclear import of the INrf2/Cul3 Rbx1 complex to degrade nuclear Nrf2. J Biol Chem 284:13856-13868.Nohra R, Beyeen AD, Guo JP, Khademi M, Sundqvist E, Hedreul MT, Sellebjerg F, Smestad C, Oturai AB, Harbo HF, Wallstrom E, Hillert J, Alfredsson L, Kockum I, Jagodic M, Lorentzen J, Olsson T (2010) RGMA and IL21R show association with experimental inflammation and multiple sclerosis. Genes Immun 11:279-293.Novikova,L., Garris,B.L., Garris,D.R., & Lau,Y.S. (2006). Early signs of neuronal apoptosis in the substantia nigra pars compacta of the progressive neurodegenerative mouse 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine/probenecid model of Parkinson’s disease. Neuroscience, 140(1), 67-76.Okada H, Matsushita N, Kobayashi K, Kobayashi K (2004) Identification of GABAA receptor subunit variants in midbrain dopaminergic neurons. J Neurochem 89:7-14.Olanow CW, Stern MB, Sethi K (2009) The scientific and clinical basis for the treatment of Parkinson disease (2009). Neurology 72:S1-136.Olson MF (2008) Applications for ROCK kinase inhibition. Curr Opin Cell Biol 20:242-248.Orban TI, Apati A, Nemeth A, Varga N, Krizsik V, Schamberger A, Szebenyi K, Erdei Z, Varady G, Karaszi E, Homolya L, Nemet K, Gocza E, Miskey C, Mates L, Ivics Z, Izsvak Z, Sarkadi B (2009) Applying a “double-feature” promoter to identify cardiomyocytes differentiated from human embryonic stem cells following transposon-based gene delivery. Stem Cells 27:1077-1087.Pan J, Kao YL, Joshi S, Jeetendran S, Dipette D, Singh US (2005) Activation of Rac1 by phos-phatidylinositol 3-kinase in vivo: role in activation of mitogen-activated protein kinase (MAPK) pathways and retinoic acid-induced neuronal differentiation of SH-SY5Y cells. J Neurochem 93:571-583.Papale A, Cerovic M, Brambilla R (2009) Viral vector approaches to modify gene expression in the brain. J Neurosci Methods 185:1-14.Papapetropoulos S, Ffrench-Mullen J, McCorquodale D, Qin Y, Pablo J, Mash DC (2006) Multiregional gene expression profiling identifies MRPS6 as a possible candidate gene for Parkinson’s disease. Gene Expr 13:205-215.Paquet M, Tremblay M, Soghomonian JJ, Smith Y (1997) AMPA and NMDA glutamate receptor subunits in midbrain dopaminergic neurons in the squirrel monkey: an immunohistochemi-cal and in situ hybridization study. J Neurosci 17:1377-1396.Paterna JC, Feldon J, Bueler H (2004) Transduction profiles of recombinant adeno-associated virus vectors derived from serotypes 2 and 5 in the nigrostriatal system of rats. J Virol 78:6808-6817.

R EFER ENCE LIST

273

Paterna JC, Moccetti T, Mura A, Feldon J, Bueler H (2000) Influence of promoter and WHV post-transcriptional regulatory element on AAV-mediated transgene expression in the rat brain. Gene Ther 7:1304-1311.Paxinos.G. & Franklin.K.B.J. (2001). The Mouse Brain in in Stereotaxic Coordinates. Aca-demic Press: New York.Peel AL, Klein RL (2000) Adeno-associated virus vectors: activity and applications in the CNS. J Neurosci Methods 98:95-104.Petroske,E., Meredith,G.E., Callen,S., Totterdell,S., & Lau,Y.S. (2001). Mouse model of Parkin-sonism: a comparison between subacute MPTP and chronic MPTP/probenecid treatment. Neuroscience, 106(3), 589-601.Pifl C, Hornykiewicz O, Giros B, Caron MG (1996) Catecholamine transporters and 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine neurotoxicity: studies comparing the cloned human noradrenaline and human dopamine transporter. J Pharmacol Exp Ther 277:1437-1443.Przedborski,S., Jackson-Lewis,V., Naini,A.B., Jakowec,M., Petzinger,G., Miller,R., & Akram,M. (2001). The parkinsonian toxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP): a technical review of its utility and safety. J.Neurochem., 76(5), 1265-1274.Qu Q, Shi Y (2009) Neural stem cells in the developing and adult brains. J Cell Physiol 221:5-9.Ravid R, Van Zwieten EJ, Swaab DF (1992) Brain banking and the human hypothalamus--factors to match for, pitfalls and potentials. Prog Brain Res 93:83-95.Ricaurte,G.A., Irwin,I., Forno,L.S., DeLanney,L.E., Langston,E., & Langston,J.W. (1987). Aging and 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine-induced degeneration of dopaminergic neurons in the substantia nigra. Brain Res., 403(1), 43-51.Rossino P, Defilippi P, Silengo L, Tarone G (1991) Up-regulation of the integrin alpha 1/beta 1 in human neuroblastoma cells differentiated by retinoic acid: correlation with increased neurite outgrowth response to laminin. Cell Regul 2:1021-1033.Ruitenberg MJ, Eggers R, Boer GJ, Verhaagen J (2002) Adeno-associated viral vectors as agents for gene delivery: application in disorders and trauma of the central nervous system. Methods 28:182-194.Samad TA, Srinivasan A, Karchewski LA, Jeong SJ, Campagna JA, Ji RR, Fabrizio DA, Zhang Y, Lin HY, Bell E, Woolf CJ (2004) DRAGON: a member of the repulsive guidance molecule-related family of neuronal- and muscle-expressed membrane proteins is regulated by DRG11 and has neuronal adhesive properties. J Neurosci 24:2027-2036.Saraf A, Virshup DM, Strack S (2007) Differential expression of the B’beta regulatory subunit of protein phosphatase 2A modulates tyrosine hydroxylase phosphorylation and catechol-amine synthesis. J Biol Chem 282:573-580.Schaffar G, Taniguchi J, Brodbeck T, Meyer AH, Schmidt M, Yamashita T, Mueller BK (2008) LIM-only protein 4 interacts directly with the repulsive guidance molecule A receptor Neo-genin. J Neurochem 107:418-431.Schintu,N., Frau,L., Ibba,M., Caboni,P., Garau,A., Carboni,E., & Carta,A.R. (2009a). PPAR-gamma-mediated neuroprotection in a chronic mouse model of Parkinson’s disease. Eur.J.Neurosci., 29(5), 954-963.Schintu,N., Frau,L., Ibba,M., Garau,A., Carboni,E., & Carta,A.R. (2009b). Progressive dopami-nergic degeneration in the chronic MPTPp mouse model of Parkinson’s disease. Neurotox.Res., 16(2), 127-139.

274

Schneider B, Zufferey R, Aebischer P (2008) Viral vectors, animal models and new therapies for Parkinson’s disease. Parkinsonism Relat Disord 14 Suppl 2:S169-S171.Schneider,J.S., Rothblat,D.S., & DiStefano,L. (1994). Volume transmission of dopamine over large distances may contribute to recovery from experimental parkinsonism. Brain Res., 643(1-2), 86-91.Schnichels S, Heiduschka P, Julien S (2011) Different spatial and temporal protein expres-sions of repulsive guidance molecule a and neogenin in the rat optic nerve after optic nerve crush with and without lens injury. J Neurosci Res 89:490-505.Schober,A. (2004). Classic toxin-induced animal models of Parkinson’s disease: 6-OHDA and MPTP. Cell Tissue Res., 318(1), 215-224.Schoffelmeer AN, Drukarch B, De Vries TJ, Hogenboom F, Schetters D, Pattij T (2011) Insulin modulates cocaine-sensitive monoamine transporter function and impulsive behavior. J Neurosci 31:1284-1291.Schwab JM, Conrad S, Monnier PP, Julien S, Mueller BK, Schluesener HJ (2005a) Spinal cord injury-induced lesional expression of the repulsive guidance molecule (RGM). Eur J Neurosci 21:1569-1576.Schwab JM, Monnier PP, Schluesener HJ, Conrad S, Beschorner R, Chen L, Meyermann R, Mueller BK (2005b) Central nervous system injury-induced repulsive guidance molecule expression in the adult human brain. Arch Neurol 62:1561-1568.Schwarting,R.K., Sedelis,M., Hofele,K., Auburger,G.W., & Huston,J.P. (1999). Strain-dependent recovery of open-field behavior and striatal dopamine deficiency in the mouse MPTP model of Parkinson’s disease. Neurotox.Res., 1(1), 41-56.Schwarzer C, Berresheim U, Pirker S, Wieselthaler A, Fuchs K, Sieghart W, Sperk G (2001) Distribution of the major gamma-aminobutyric acid(A) receptor subunits in the basal gan-glia and associated limbic brain areas of the adult rat. J Comp Neurol 433:526-549.Sedelis,M., Schwarting,R.K., & Huston,J.P. (2001). Behavioral phenotyping of the MPTP mouse model of Parkinson’s disease. Behav.Brain Res., 125(1-2), 109-125.Shmelkov SV, Hormigo A, Jing D, Proenca CC, Bath KG, Milde T, Shmelkov E, Kushner JS, Baljevic M, Dincheva I, Murphy AJ, Valenzuela DM, Gale NW, Yancopoulos GD, Ninan I, Lee FS, Rafii S (2010) Slitrk5 deficiency impairs corticostriatal circuitry and leads to obsessive-compulsive-like behaviors in mice. Nat Med 16:598-602, 1p.Shou J, Rim PC, Calof AL (1999) BMPs inhibit neurogenesis by a mechanism involving degra-dation of a transcription factor. Nat Neurosci 2:339-345.Simon-Sanchez J, et al. (2009) Genome-wide association study reveals genetic risk underly-ing Parkinson’s disease. Nat Genet 41:1308-1312.Sims K, Ahmed Z, Gonzalez AM, Read ML, Cooper-Charles L, Berry M, Logan A (2008) Target-ing adenoviral transgene expression to neurons. Mol Cell Neurosci 39:411-417.Simunovic F, Yi M, Wang Y, Macey L, Brown LT, Krichevsky AM, Andersen SL, Stephens RM, Benes FM, Sonntag KC (2009) Gene expression profiling of substantia nigra dopamine neu-rons: further insights into Parkinson’s disease pathology. Brain 132:1795-1809.Smidt MP, Burbach JP (2007) How to make a mesodiencephalic dopaminergic neuron. Nat Rev Neurosci 8:21-32.Smyth GK (2004) Linear models and empirical bayes methods for assessing differential expression in microarray experiments. Stat Appl Genet Mol Biol 3:Article3.

R EFER ENCE LIST

275

Spillantini MG, Schmidt ML, Lee VM, Trojanowski JQ, Jakes R, Goedert M (1997) Alpha-synu-clein in Lewy bodies. Nature 388:839-840.St Martin JL, Klucken J, Outeiro TF, Nguyen P, Keller-McGandy C, Cantuti-Castelvetri I, Gram-matopoulos TN, Standaert DG, Hyman BT, McLean PJ (2007) Dopaminergic neuron loss and up-regulation of chaperone protein mRNA induced by targeted over-expression of alpha-synuclein in mouse substantia nigra. J Neurochem 100:1449-1457.Stam FJ, MacGillavry HD, Armstrong NJ, de Gunst MC, Zhang Y, van Kesteren RE, Smit AB, Verhaagen J (2007) Identification of candidate transcriptional modulators involved in suc-cessful regeneration after nerve injury. Eur J Neurosci 25:3629-3637.Suda M, Hata K, Sawada A, Nakamura Y, Kubo T, Yamaguchi A, Yamashita T (2008) Peptides derived from repulsive guidance molecule act as antagonists. Biochem Biophys Res Commun 371:501-504.Tassew NG, Charish J, Seidah NG, Monnier PP (2012) SKI-1 and Furin generate multiple RGMa fragments that regulate axonal growth. Dev Cell 22:391-402.Taymans JM, Vandenberghe LH, Haute CV, Thiry I, Deroose CM, Mortelmans L, Wilson JM, Debyser Z, Baekelandt V (2007) Comparative analysis of adeno-associated viral vector sero-types 1, 2, 5, 7, and 8 in mouse brain. Hum Gene Ther 18:195-206.Tepper JM, Lee CR (2007) GABAergic control of substantia nigra dopaminergic neurons. Prog Brain Res 160:189-208.Tillerson,J.L. & Miller,G.W. (2003). Grid performance test to measure behavioral impairment in the MPTP-treated-mouse model of parkinsonism. J.Neurosci.Methods, 123(2), 189-200.Tofaris,G.K., Garcia,R.P., Humby,T., Lambourne,S.L., O’Connell,M., Ghetti,B., Gossage,H., Emson,P.C., Wilkinson,L.S., Goedert,M., & Spillantini,M.G. (2006). Pathological changes in dopaminergic nerve cells of the substantia nigra and olfactory bulb in mice transgenic for truncated human alpha-synuclein(1-120): implications for Lewy body disorders. J.Neurosci., 26(15), 3942-3950.Truckenmiller ME, Vawter MP, Cheadle C, Coggiano M, Donovan DM, Freed WJ, Becker KG (2001) Gene expression profile in early stage of retinoic acid-induced differentiation of hu-man SH-SY5Y neuroblastoma cells. Restor Neurol Neurosci 18:67-80.Tsuji S (2010) Genetics of neurodegenerative diseases: insights from high-throughput rese-quencing. Hum Mol Genet 19:R65-R70.Tuszynski MH, Thal L, Pay M, Salmon DP, HS U, Bakay R, Patel P, Blesch A, Vahlsing HL, Ho G, Tong G, Potkin SG, Fallon J, Hansen L, Mufson EJ, Kordower JH, Gall C, Conner J (2005) A phase 1 clinical trial of nerve growth factor gene therapy for Alzheimer disease. Nat Med 11:551-555.Twine NA, Janitz K, Wilkins MR, Janitz M (2011) Whole transcriptome sequencing reveals gene expression and splicing differences in brain regions affected by Alzheimer’s disease. PLoS One 6:e16266.Ueda H, Fujita R, Yoshida A, Matsunaga H, Ueda M (2007) Identification of prothymosin-alpha1, the necrosis-apoptosis switch molecule in cortical neuronal cultures. J Cell Biol 176:853-862.Ulusoy A, Sahin G, Bjorklund T, Aebischer P, Kirik D (2009) Dose optimization for long-term rAAV-mediated RNA interference in the nigrostriatal projection neurons. Mol Ther 17:1574-1584.

276

van der Heide LP, Hoekman MF, Smidt MP (2004) The ins and outs of FoxO shuttling: mecha-nisms of FoxO translocation and transcriptional regulation. Biochem J 380:297-309.van Horssen J., Otte-Holler I, David G, Maat-Schieman ML, van den Heuvel LP, Wesseling P, de Waal RM, Verbeek MM (2001) Heparan sulfate proteoglycan expression in cerebrovascular amyloid beta deposits in Alzheimer’s disease and hereditary cerebral hemorrhage with amy-loidosis (Dutch) brains. Acta Neuropathol 102:604-614.Vandesompele J, De PK, Pattyn F, Poppe B, Van RN, De PA, Speleman F (2002) Accurate nor-malization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol 3:RESEARCH0034.Venter JC, et al. (2001) The sequence of the human genome. Science 291:1304-1351.Verney C (2003) Phenotypic expression of monoamines and GABA in the early development of human telencephalon, transient or not transient. J Chem Neuroanat 26:283-292.Wang CY, Guo HY, Lim TM, Ng YK, Neo HP, Hwang PY, Yee WC, Wang S (2005) Improved neu-ronal transgene expression from an AAV-2 vector with a hybrid CMV enhancer/PDGF-beta promoter. J Gene Med 7:945-955.Wartiovaara K, Barnabe-Heider F, Miller FD, Kaplan DR (2002) N-myc promotes survival and induces S-phase entry of postmitotic sympathetic neurons. J Neurosci 22:815-824.Weihmuller,F.B., Bruno,J.P., Neff,N.H., & Hadjiconstantinou,M. (1990). Dopamine receptor plasticity following MPTP-induced nigrostriatal lesions in the mouse. Eur.J.Pharmacol., 180(2-3), 369-372.Wey MC, Fernandez E, Martinez PA, Sullivan P, Goldstein DS, Strong R (2012) Neurodegener-ation and motor dysfunction in mice lacking cytosolic and mitochondrial aldehyde dehydro-genases: implications for Parkinson’s disease. PLoS One 7:e31522.Wilson NH, Key B (2007) Neogenin: one receptor, many functions. Int J Biochem Cell Biol 39:874-878.Winther M, Berezin V, Walmod PS (2012) NCAM2/OCAM/RNCAM: cell adhesion molecule with a role in neuronal compartmentalization. Int J Biochem Cell Biol 44:441-446.Wirdefeldt K, Adami HO, Cole P, Trichopoulos D, Mandel J (2011) Epidemiology and etiology of Parkinson’s disease: a review of the evidence. Eur J Epidemiol 26 Suppl 1:S1-58.Wu Z, Asokan A, Samulski RJ (2006) Adeno-associated virus serotypes: vector toolkit for hu-man gene therapy. Mol Ther 14:316-327.Xu,G., Xiong,Z., Yong,Y., Wang,Z., Ke,Z., Xia,Z., & Hu,Y. (2010). Catalpol attenuates MPTP induced neuronal degeneration of nigral-striatal dopaminergic pathway in mice through elevating glial cell derived neurotrophic factor in striatum. Neuroscience, 167(1), 174-184.Yamada T, McGeer PL, Baimbridge KG, McGeer EG (1990) Relative sparing in Parkinson’s dis-ease of substantia nigra dopamine neurons containing calbindin-D28K. Brain Res 526:303-307.Yamashita T, Mueller BK, Hata K (2007) Neogenin and repulsive guidance molecule signaling in the central nervous system. Curr Opin Neurobiol 17:29-34.Yeo M, Lee SK, Lee B, Ruiz EC, Pfaff SL, Gill GN (2005) Small CTD phosphatases function in silencing neuronal gene expression. Science 307:596-600.Yoshida J, Kubo T, Yamashita T (2008) Inhibition of branching and spine maturation by repulsive guidance molecule in cultured cortical neurons. Biochem Biophys Res Commun 372:725-729.

R EFER ENCE LIST

277

Yu J, Vodyanik MA, Smuga-Otto K, Antosiewicz-Bourget J, Frane JL, Tian S, Nie J, Jonsdottir GA, Ruotti V, Stewart R, Slukvin II, Thomson JA (2007) Induced pluripotent stem cell lines derived from human somatic cells. Science 318:1917-1920.Yurek,D.M., Deutch,A.Y., Roth,R.H., & Sladek,J.R., Jr. (1989). Morphological, neurochemical, and behavioral characterizations associated with the combined treatment of diethyldithio-carbamate and 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine in mice. Brain Res., 497(2), 250-259.Zhang EE, Liu AC, Hirota T, Miraglia LJ, Welch G, Pongsawakul PY, Liu X, Atwood A, Huss JW, III, Janes J, Su AI, Hogenesch JB, Kay SA (2009a) A genome-wide RNAi screen for modifiers of the circadian clock in human cells. Cell 139:199-210.Zhang W, St-Gelais F, Grabner CP, Trinidad JC, Sumioka A, Morimoto-Tomita M, Kim KS, Straub C, Burlingame AL, Howe JR, Tomita S (2009b) A transmembrane accessory subunit that modulates kainate-type glutamate receptors. Neuron 61:385-396.Zhang Y, James M, Middleton FA, Davis RL (2005) Transcriptional analysis of multiple brain regions in Parkinson’s disease supports the involvement of specific protein processing, energy metabolism, and signaling pathways, and suggests novel disease mechanisms. Am J Med Genet B Neuropsychiatr Genet 137B:5-16.Zhao F, Wu T, Lau A, Jiang T, Huang Z, Wang XJ, Chen W, Wong PK, Zhang DD (2009) Nrf2 promotes neuronal cell differentiation. Free Radic Biol Med 47:867-879.Zheng Y, Begum S, Zhang C, Fleming K, Masumura C, Zhang M, Smith P, Darlington C (2011) Increased BrdU incorporation reflecting DNA repair, neuronal de-differentiation or possible neurogenesis in the adult cochlear nucleus following bilateral cochlear lesions in the rat. Exp Brain Res 210:477-487.Zhou JN, Riemersma RF, Unmehopa UA, Hoogendijk WJ, van Heerikhuize JJ, Hofman MA, Swaab DF (2001) Alterations in arginine vasopressin neurons in the suprachiasmatic nucleus in depression. Arch Gen Psychiatry 58:655-662.Zimmermann M, Gardoni F, Marcello E, Colciaghi F, Borroni B, Padovani A, Cattabeni F, Di LM (2004) Acetylcholinesterase inhibitors increase ADAM10 activity by promoting its traffick-ing in neuroblastoma cell lines. J Neurochem 90:1489-1499.Zolotukhin S, Byrne BJ, Mason E, Zolotukhin I, Potter M, Chesnut K, Summerford C, Samulski RJ, Muzyczka N (1999) Recombinant adeno-associated virus purification using novel meth-ods improves infectious titer and yield. Gene Ther 6:973-985.

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Identificatie van nieuwe moleculaire mechanismen die mogelijk betrokken zijn bij de ontwikkeling van de ziekte van Parkinson

De ziekte van Parkinson is een neurodegeneratieve ziekte waarbij zenuw-cellen in de substantia nigra en een aantal andere hersengebieden langzaam af-sterven. De zenuwcellen in de substantia nigra produceren de neurotransmitter dopamine, hebben hun uitlopers in het striatum, en vormen daarmee de nigros-triatale zenuwbaan. Het afsterven van dopaminerge zenuwcellen veroorzaakt een aantal symptomen die typisch zijn voor de ziekte van Parkinson, zoals tremor, rigiditeit (stijfheid), akinesie (bewegingsarmoede) en een maskergelaat. Er zijn verschillende oorzaken van de ziekte van Parkinson bekend. Een klein percentage van de patiënten is erfelijk belast. Er zijn op dit moment zeven genen bekend die een mutatie kunnen bevatten waardoor de ziekte van Parkinson ont-staat. Verder kan blootstelling aan een aantal chemische stoffen, zoals bepaalde bestrijdingsmiddelen gebruikt in de landbouw of de stof MPTP (1-methyl-4-phenyl1,2,3,6-tetrahydropyridine; een verontreiniging die ontstaat bij het syn-thetiseren van meperidine), de ziekte van Parkinson veroorzaken. Leeftijd speelt ook een rol. In verreweg het grootste deel van de patiënten is de oorzaak van de ziekte niet bekend.

Wanneer bij iemand de ziekte van Parkinson geconstateerd wordt, wordt veelal een behandeling gestart met levodopa, een dopamine preparaat dat het gebrek aan dopamine aanvult. In latere stadia wordt tegenwoordig in toene-mende mate diepe hersenstimulatie toegepast. Deze behandelingen bestrijden wel de symptomen maar zetten het ziekteproces niet stil. Er is op dit moment geen behandeling die de ziekte echt tot staan brengt. Om zo’n behandeling te ontwikkelen is veel meer kennis nodig van de cellulaire en moleculaire verand-eringen die optreden in het hersenweefsel van Parkinsonpatiënten. De essentiële vraag – waarom gaan dopaminerge zenuwcellen dood? – is momenteel onbeant-woord. Het werk waarvan in dit proefschrift verslag wordt gedaan probeert een bijdrage te leveren aan het opvullen van deze leemte.

Het werk in dit proefschrift is gebaseerd op de resultaten van een “microar-ray” of genexpresie analyse die eerder door ons werd uitgevoerd op substantia nigra weefsel van Parkinson patiënten en controles. Het weefsel voor deze mi-croarray studie werd verkregen via de Nederlandse Hersenbank. In deze studie werden veranderingen in de expressie van 287 genen gedetecteerd.

Dit proefschrift beschrijft fundamenteel neurobiologisch vervolgonderzoek naar de mogelijke functionele betekenis van deze veranderingen in genexpressie in de substantia nigra van Parkinsonpatiënten. Het onderzoek werd uitgevoerd in 3 stappen: 1) selectie van de interessantste genen (hoofdstuk 2), 2) functio-nele screening van 62 genen in cellulaire assays (hoofdstuk 4), en 3) onderzoek naar een van de meest veelbelovende geïdentificeerde targetmoleculen (Repul-

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sive Guidance Molecule A – RGMA) in vivo (hoofdstuk 7). De tussenliggende hoofdstukken beschrijven de noodzakelijke karakterisering van de dopaminerge cellijn die gebruikt is voor de cellulaire screening (hoofdstuk 3) en het opzetten van de diermodellen en de virale vector-gemedieerde gentransfer voor het in vivo onderzoek (hoofdstukken 5 en 6).

Hoofdstuk 2 beschrijft hoe een eerste selectie gemaakt werd uit de totale pool van 287 genen. Genen waarvan bekend was of met enige zekerheid ver-moed kon worden dat zij betrokken zijn bij processen die verstoord zijn bij de ziekte van Parkinson vormen de “shortlist” van uiteindelijk 79 genen voor verder onderzoek. Deze “shortlist” bestond voornamelijk uit genen met een mogelijke rol in celdood, neurotrofe ondersteuning van zenuwcellen, synaptische transmis-sie, mitochondriaal dysfunctioneren en “axon guidance”. De axon guidance genen hadden vanaf het begin onze bijzondere aandacht omdat deze genen betrokken zouden kunnen zijn bij het langzaam afsterven van nigrostriatale verbindingen vanuit het striatum naar de substantia nigra in het Parkinson brein, een feno-meen dat bekend staat als axonale “dye back”. We laten in dit hoofdstuk we zien dat verreweg de meeste genen die we geselecteerd hebben tot expressie komen in dopaminerge neuronen en niet in gliacellen in de substantia nigra van Parkin-sonpatiënten.

Omdat de meeste van onze targetgenen in zenuwcellen tot expressie komen lag het voor de hand de in vitro studies naar de functie van deze genen uit te vo-eren in een neuronale cellijn. In hoofdstuk 3 karakteriseren wij de SH-SY5Y cel-lijn en tonen aan dat deze cellen veel eigenschappen bezit van dopaminerge cel-len en dat deze cellijn ook het grootste deel van onze targetgenen tot expressie brengt. In hoofdstuk 4 melden wij de resultaten van een aantal grote functionele screens gebruikmakend van de SH-SY5Y cellijn. Deze screens werden uitgevoerd met als doel vast te stellen welke van onze targetgenen een effect heeft op het overleven, de mitochondriale activiteit en de uitgroei van zenuwuitlopers (neu-rieten) in SH-SY5Y cellen. De meest uitgesproken effecten op zowel cellulaire overleving als neurietuitgroei werden gevonden na overexpressie van 4 genen: CTDSP1, RGMA, PTMA and WWC1. Deze 4 genen waren ook opgereguleerd in de substantia nigra van Parkinsonpatiënten en het is daarom zeer goed mogelijk dat hun verhoogde expressie bijdraagt aan de inductie en/of de progressie van het ziektebeeld.

In hoofdstuk 7 testen wij of de overexpressie van RGMA (ingebracht door middel van een virale vector) in dopaminerge neuronen in de substantia nigra van de muis leidt tot het dysfunctioneren of afsterven van deze zenuw-cellen. Overexpressie van RGMA in de substantie nigra van muizen induceerde inderdaad degeneratie van dopaminerge neuronen, en leidde tot verslechtering van de motorcoördinatie die zo typisch is voor de ziekte van Parkinson. In onze studies in de muis hebben wij waargenomen dat RGMA wordt getransporteerd naar het striatum via de uitlopers van de dopaminerge neuronen alwaar het ver-volgens in het striatum wordt uitgescheiden. Omdat RGMA een repulsief effect

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heeft op zenuwuiteinden denken wij dat de verhoogde niveaus van dit eiwit in het striatum “dye back” van nigrostriatale verbindingen kan induceren en dat dit dan geleidelijk aan kan resulteren in het afsterven van dopaminerge neuronen. In vervolgonderzoek in muizen zullen wij verder uitzoeken of dit mechanisme inderdaad ten grondslag zou kunnen liggen aan de negatieve effecten van RGMA op de overleving van dopaminerge neuronen.

Om de kernvraag te kunnen beantwoorden of de verhoogde expressie van RGMA in de substantia nigra bijdraagt aan het afsterven van dopaminerge neu-ronen in Parkinsonpatiënten, moet er vervolgonderzoek worden verricht op hu-maan hersenweefsel, in proefdieren en in celkweek. Vragen die centraal staan zijn dan: Hoe vroeg in het ziektebeloop komt RGMA al verhoogd tot expressie? Is de verhoging specifiek voor de dopaminerge neuronen in de substantia nigra? Door welke moleculaire factoren, signalen of omgevingsfactoren wordt RGMA expressie gereguleerd? Hebben Parkinsonpatiënten single nucleotide polymor-fismen in het RGMA-gen die zorgen voor dysregulatie van het RGMA-gen? Ant-woorden op deze vragen zullen bepalen of RGMA kan worden gezien als een se-rieus kandidaat molecuul voor de ontwikkeling van een regeneratieve therapie voor de ziekte van Parkinson.

Acknowledgements

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Thank you words

This book is a fruit of 5 years of work. These 5 years have been least to say eventful- with many ups and many downs as any PhD project. I am not surprised people say that a PhD is not for anyone. It is a tough experience but the rewards are great. I have learned a lot and gained many skills that I know I will be able to use anywhere. As some of my friends would agree, doing a PhD project has deep-ened my OCD a little, but it’s a small side effect. Of course I would never be able to do this by myself and I am very grateful to many people who have helped me through this journey.

I would like to 1st thank my husband, Kasper. We met in the lab during our PhD while sharing a lab bench. You have not only been a great mental support, but also a great friend to discuss my project with. Your mind, constructed and going of tangents so different than mine, has been a great help through these years. And the moments of celebrations, even of the small successes, helped me a lot to recharge and strike through the next problem. Thank you.

Dear Joost, thank you for giving me this opportunity. Between many things that you have taught me, I value the most the independence and confidence I have gained while being under ‘your wings’. Writing this book was a bit of a struggle for both of us and I realize I still have a way to go before I can gain your full ap-proval in scientific writing. I hope to surprise you soon.

Koen, at the beginning of my PhD I would bother you constantly with random small questions, and funny enough, this was the same at the end of my PhD. Thanks for keeping your doors open. Working closely together, we both enjoyed seeing this project bloom into something significant. And who knew that you are so good in cleaning after mice:)!

Dick, thank you for your fast comments and suggestions and always a support-ive word. I really appreciated the fact that your doors were always open despite your busy schedule. That is an amazing skill.

Ruben, Unga and Rawien- without any of you this thesis would have had huge holes and be worthless. Thank you so much for your professional opinion, time and help. I enjoyed working together a lot. It sometimes got scary (DM2 in whole body suits trying not to inject ourselves with MPTP), frustrating (generating ISH probes forever and ever…) or just plain boring (10,000th grip, 10,001, 10,002…) but you guys always supported me and where my pillars through all these times. I would also like to thank you Ruben & Unga for being great friends to me.

Erich, thanks for your patience with many of my many questions. And for tak-ing the monkey off my shoulders.

Nitish -you are a patient man- all those times me talking to myself, freaking out and playing defiantly not your style of music - you are the best roommate ever!

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Vasil & Rubén- thanks for being such generous and honest friends.

Elisabeth & Kerstin- good luck on you last meters to the end line. I really en-joyed talking with you as woman to woman in this 'manly' group.

Ari - lets go party again soon!

Barbara, thank you for helping me out once in a while and for the fact that it was never a problem.

Matthew- thanks for your advice on PCR and cloning. I will keep your cloning protocol for ever.

Tam, Nathalie, Jinte & Karianne- I miss our room! You guys are wonderful. Thanks for all your support throughout the years. Also thank you for taking me in to join your room and helping me find myself in this PhD-thing in my 1st year. Let’s go out for dinner soon! Jinte- especially thank you for helping me with fo-cusing on my future and giving me great advice.

Ronald & Guus, thank you for your time, professional help and advice.

Eva, thanks for teaching me cell culture and cool cellomics. Although you are out of the lab, we should continue with our dinners and keep in touch.

Wilma- thank you for your amazing help with the writing.

Frank & Martijn- you guys started the process of my ‘creation’ as a scientist. Thanks for your teachings and the fun time we had in the lab.

Afra, Marleen, Petra, Paul & Michiel- I love working with you guys and I ad-mire the passion you have for your work. Michiel thanks for your support and enthusiasm.

Joop- thank you for all fantastic help with the microscopy, masking, counting and quantification. Also thanks for helping me with my students. You are great with people. Oh and the candy- always good.

Elly & Inge- thank you for your support and good advice about my project and my future.

Arja & Jaqueline- thank you for help and support in the lab.

Simone- I really enjoyed our study/PhD partnership. Thanks for all the support and listening. I really enjoyed talking with you.

Astro girls- fun fun fun! Good luck with your work. I enjoyed popping in ran-domly to your room (maybe a little more then you did :)).

Elske- your key prooved to be very valuable. I am going to pass it on and keep the tradition.

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Kochania rodzinko- dedykuję tą pracę Wam. Tak jak m�j doktorat, przez te ostatnie 5 lat przeszliśmy przez wiele wzlot�w i upadk�w. I tak jak ta praca mnie ‘wzmocniła’ tak nasze przeżycia wzmocniły nasze więzi.

Kochani rodzice- przez całe moje życie wspomagaliście mnie jak tylko mogliście. Ta przygoda zaczeła sie już 10 lat temu, kiedy tak chcieliście, szczegol-nie ty tata, abym pojechała do Holandii na studia. No i patrzcie- c�rka ma tytuł doktora! Dziekuję wam bardzo za wasze wsparcie, poradę i cierpliwość.

Braciszku- tobe szczeg�lnie dziekuję za twoje wsparcie i entuzjazm jaki za-wsze mieleś dla mojej pracy- nawet nie wiesz ile otuchy mi to dodawało.

Siostrzyczko- tobie dziekuję za bycie słodką i zawsze optymistyczną.

Dziadziu- dziekuję za twoje nieustające wsparcie. Ma ono wielkie znaczenie.

Tine- thank you for always being so sweet and supportive.

The Wednesday dinner people: Alex, Charlotte, Marianna, Stef, Rachel, Ar-jan, Joris, Ray & those significant others- thanks for listening to my science bla bla. Although, most of the time you had no idea what I was talking about, I re-ally enjoyed explaining what I do in trying-to-be-normal EnglishJ. And thanks for the Wednesday dinners-as I have mentioned many times, they really helped with dealing with work stress and gave a little push to survive until the weekend. Of course the stress relieving weekend parties also played a significant role! Char-lotte- thanks for your professional advice on the cover design.

Ania- kochana dzięki za super rok w Amsterdamie!

Niel- your positivity about my research always overwhelmed me. I miss you!

Jan- thanks for your sweet support in the last months of the struggle.

Leila- you told me once something very special: ‘you cannot let it all overwhelm you so much’ thank you for that. I try my best.

LIST OF PU BLICATIONS

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List of Publications

Korecka JA, Eggers R, Swaab DF, Bossers K, Verhaagen J, Modeling early Parkinson’s disease pathology with chronic low dose MPTP treatment. Manu-script accepted for publishing at Restorative Neurology and Neuroscience

van den Berge SA, van Strien ME, Korecka JA, Dijkstra AA, Sluijs JA, Kooij-man L, Eggers R, De Filipps L, Vescovi AL, Verhaagen J, van den Berg WD, Hol EM (2011). The proliferative capacity of the subventricular zone is maintained in the parkinsonian brain. Brain 2011, Nov; 134(Pt 11);3249-63

Korecka JA, Schouten M, Eggers R, Ulusoy A, Bossers K. and Verhaagen J, (2011). Comparison of AAV serotypes for gene delivery to dopaminergic neurons in the substantia nigra, Viral Gene Therapy, Ke Xu (Ed.), ISBN: 978-953-307-539-6, InTech,

Tannemaat MR, Korecka J, Ehlert EM, Mason MR, van Duinen SG, Boer GJ, Malessy MJ, Verhaagen J. Human neuroma contains increased levels of semapho-rin 3A, which surrounds nerve fibers and reduces neurite extension in vitro. J Neurosci. 2007 Dec 26;27(52):14260-4.

Korecka JA, Verhaagen J, Hol EM, Cell-replacement and gene-therapy strat-egies for Parkinson’s and Alzheimer’s disease. Regen Med. 2007 Jul;2(4):425-46.

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Curriculum Vitae

Joanna Aleksandra Korecka-Roet was born on the 24th of November 1982 in Gdansk, Poland. When she was three, she moved with her family to Shanghai, China and lived there for seven years. In 1992 she moved back to Gdynia, Poland and finished her middle school education. In 1997 she moved back to Shanghai, followed her high school education in Shanghai American School and gradu-ated in 2001. In September 2001 she started her Bachelor education at Utrecht University College and graduated with honors in 2004 with a Science major and Anthropology and Psychology minors. During summer school she completed a practical course in cognitive neuroscience and molecular neuroscience This strengthened her interests in neuroscience and she pursued a prestige masters in Experimental and Clinical Neuroscience at University Utrecht for two years. During this program she completed two practical internships. The first one at the Rudolf Magnus Institute (RMI), Dept. Neurodevelopment entitled ‘DNA bind-ing site selection for the transcription factors Pitx3 and FoxO6’ and supervised by Dr. Frank M.T. Jacobs and Prof. Marten P. Smidt. This internship gave her a deep understanding of molecular biology, DNA transcription and taught her ba-sic laboratory techniques. For her second internship she chose to join the Labora-tory for Neuroregeneration at the Netherlands Institute for Neuroscience (NIN) where she studied Semaphorin 3A expression and inhibition of nerve regenera-tion in human peripheral nerve neuroma supervised by Dr. Martijn Tannemaat and Prof. Joost Verhaagen. Working with human material in a direct clinical set-ting inspired Joanna’s interest in neurodegenerative diseases. To expand her theoretical knowledge she wrote a master’s thesis on new therapies for Parkin-son’s and Alzheimer disease with Prof. Elly Hol. In 2006 she accepted a PhD posi-tion with Prof. Joost Verhaagen and Dr. Koen Bossers to investigate the molecular basis of Parkinson’s disease development. During her PhD she has met her hus-band Kasper Roet while sharing a laboratory bench. Currently, as a postdoc with Prof. Joost Verhaagen, Joanna is following-up the discoveries described in this thesis to deepen the understanding of the role of RGMA in Parkinson’s disease development.

Documents

Identification of new molecular mechanisms potentially - TI Pharma