Neuroepigenetics of Learning and Memory

Epigenetics and Memory 1

Running head: EPIGENETICS AND MEMORY

Neuroepigenetics of Learning and Memory

A Thesis Submitted to the Faculty of

Baylor University

In Partial Fulfillment of the Requirements for the

Honors Program

By

Travis Chapman

Waco, Texas

May 2011


Abstract

Long-term memory formation requires changes in gene expression. One mechanism for

altering gene expression involves chemical modifications of DNA or its associated

histone molecules. These “epigenetic” tags have long been studied by developmental

biologists for their role in cell differentiation, but recent evidence suggests they also

coordinate behavior in terminally differentiated neurons. Epigenetic chemical

modifications include DNA methylation as well as histone methylation, acetylation,

phosphorylation, ubiquitylation, and sumoylation. DNA methylation and histone

modifications—in particular acetylation, methylation, and phosphorylation—play a key

role in regulating memory-related behavior. Moreover, neuroscientists investigating

epigenetics have identified potential targets for therapeutic intervention in diseases like

Alzheimer’s, especially with regard to histone deacetylases (HDACs).


Table of Contents

Introduction ………………………………………………………………………...…….4

What is epigenetics? ………………………………………………………………...........5

Histone Acetylation ……………………………………………………..……….....…...12

Histone Phosphorylation and Methylation ………………………………………...……26

DNA Methylation .............................................................................................................31

Challenges and Future Research ......................................................................................38

References ........................................................................................................................41


Epigenetics is a contentious topic in contemporary biology. On one hand, it is the

subject of increasing media attention and excitement among scientists: both PBS and the

BBC recently had specials highlighting the revolutionary new field. Many scientists are

optimistic that understanding epigenetics will lead to a holistic picture of how the

environment and our genes interact. On the other hand, there is no clear consensus among

scientists about what epigenetics is, much less about its implications for molecular

biology or medicine. Yet the hype surrounding the epigenome continues, even as Wren

(2009) shows that about 37% of genes in the human transcriptome have no publications

characterizing their functions—a potential problem for understanding epigenetic

regulation of these genes. Though further research will tell if the mainstream media’s

popularization of epigenetics is justified by data, this new approach is already changing

how many scientific disciplines look at complex problems. One such discipline,

neuroscience, is turning to epigenetics seeking a molecular explanation for memory

formation, storage, and retrieval as well as understanding disorders of memory like

Alzheimer’s. As this paper will outline, the epigenetic approach to memory has made

significant progress in recent years—even as a young sub-discipline. The main questions

to address in order to understand this progress are as follows:

1. What is epigenetics and how have memory and dementia researchers

approached it?

2. How does epigenetics affect memory and dementia?

3. What are some challenges in this research and what are future directions for it?


CHAPTER ONE

What is epigenetics?

Definitions for epigenetics are varied and ambiguous. As early as 1957, Conrad

Hal Waddington proposed a definition for epigenetics, though he obviously was not as

familiar with its molecular mechanisms as scientists are now. In his book The Strategy of

the Genes, he related epigenetics to epigenesis, or how genotypes give rise to phenotypes

throughout development. This definition does not incorporate contemporary molecular

biology research, so it has become largely irrelevant. Bird (2007) cites Arthur Riggs and

colleagues for proposing a more contemporary definition in 1996. Epigenetics, they

claim, is “the study of mitotically and/or meiotically heritable changes in gene function

that cannot be explained by changes in the DNA sequence” (p. 396). However, this

definition is problematic because it leaves mechanisms for these “changes” open to

interpretation and even makes heritability a necessity. Simply put, this is not consistent

with contemporary usage of the word “epigenetics.” Bird (2007) subsequently proposes a

very broad definition: “the structural adaptation of chromosomal regions so as to register,

signal, or perpetuate altered activity states” (p. 398). Levenson and Sweatt (2005), on the

other hand, argue that epigenetics “is the mechanism for the stable maintenance of gene

expression that involves physically ‘marking’ DNA or its associated proteins” (p. 109).

Broadly speaking, then, epigenetics involves relatively stable chemical modifications to

DNA or histones that in turn affect gene expression. Moreover, epigenetics does not

involve changes in the DNA sequence itself. It is also important to note that the above

definition is somewhat controversial, as many insist epigenetics should include only

heritable supra-genetic changes in the cell—as opposed to metastable or transient


chemical markings (Bonasio, Tu, & Reinberg, 2010). This standard would exclude most

neuroscience research from epigenetics proper since neurons are terminally

differentiated, postmitotic cells. Epigenetic signals can be either cis or trans as well. Cis

signals are inherited by chromosome segregation and physically associated with DNA or

chromatin. Trans signals, on the other hand, are maintained in the cytosol by feedback

loops independent of the inherited chromatin structure (Bonasio et al., 2010). With this

definition of epigenetics as a heuristic, it is now necessary to discuss the main chemical

modifications studied by neuroscientists.

DNA methylation plays a key role in epigenetic regulation of gene expression;

and the relatively well-characterized histone modifications involved in gene regulation

are histone methylation, acetylation, and phosphorylation. This discussion of epigenetics

will be limited to the aforementioned chemical marks, though various small RNAs

(sRNAs) and even transcription factors are sometimes considered epigenetic gene

regulators.

DNA Methylation

DNA methylation occurs when a methyl (--CH3) group attaches to the 5-position

of a cytosine residue (Santi, Garrett, & Barr, 1983; Chen et al., 1991). There are four

known enzymes—called DNA methyltransferases (Dnmts)—that catalyze this reaction in

mammals: Dnmt1 (Bestor, Laudano, Mattaliano, & Ingram, 1988), Dnmt2 (Yoder &

Bestor, 1998), Dnmt3A, and Dnmt3B (Okano, Xie, & Li, 1998). Interestingly, a recently

reported enzyme called Gadd45b has demethylase activity in neurogenesis. Given

Gadd45b’s close relationship to memory research, it will be discussed extensively later in

this review. The roles of these Dnmts are varied, overlapping, and depend on the cellular


context at any given time. That said, their functions will be discussed later. It is notable,

though, that sequence analysis has shown identical cells from the same lineage

expressing disparate DNA methylation patterns, suggesting DNA methylation patterns

are not replicated as judiciously as the nucleotides themselves (Silva, Ward, & White,

1993). This could give rise to significant variations in phenotype for individual cells or

groups of cells. Moreover, DNA methylation generally occurs at cytosine residues

followed by guanine—known as CpG dinucleotides. This is distinct from the term for

CpG-rich areas called CpG islands. CpG islands are proximal to (or in) promoters for

many “housekeeping” genes like actin (Gardiner-Garden & Frommer, 1987). It logically

follows that DNA methylation is associated with transcriptional silencing. For instance,

the protein methyl CpG-binding protein 2 (MECP2) binds to methylated DNA

(independent of the underlying DNA sequence) and has been implicated in transcriptional

silencing by recruiting histone remodeling proteins (Jones et al., 1998). Some

transcription factors—erythroblastosis 1 (ETS1), for instance—bind to unmethylated

DNA and eschew the methylated variety (Maier, Colbert, Fitzsimmons, Clark, &

Hagman, 2003). About 70% of CpG dinucleotides are methylated (Cooper & Krawczak,

1989). Finally, methylation may involve either de novo DNA methyltransferases or

maintenance DNA methyltransferases. The former initiate the transfer of a methyl group

from S-adenosyl methionine to non-methylated cytosine nucleosides while the latter add

a methyl group to the complimentary strand of hemi-methylated DNA (i.e. DNA with no

methyl group on one strand) (Day & Sweatt, 2010).

Histone Modifications


Before discussing histone modifications, it is important to review the structure of

histone molecules. Core histones are organized in an octamer of four subunits, with each

nucleosome containing two copies of every subunit: H2A, H2B, H3, and H4. In addition,

each subunit has N-terminus “tails” that project beyond the rest of the protein. These tails

are important in transcriptional regulation and memory, which will be addressed later.

The two “linker” histones, H1 and H5, hold the histone octamer and DNA together as a

“nucleosome,” but these will be discussed less than the others in this essay. The DNA

wraps around each octamer with about 150 bp and may be either tightly or loosely

wrapped depending on the chemical environment. This packaging results in two different

kinds of chromatin: heterochromatin and euchromatin. Constitutive heterochromatin is

generally tightly packed, found at centromeres and telomeres, and transcriptionally silent.

Euchromatin, on the other hand, is the loosely packed form of chromatin associated with

transcriptional activation. Another kind, facultative heterochromatin, silences gene

expression in some cell types and activates it in others.

Major histone modifications include methylation, acetylation, phosphorylation,

sumoylation, and ubiquitylation. SUMO and ubiquitin are small proteins that attach to

histone and other molecules as post-translational modifiers. Their roles in memory

regulation via histone modification remain mysterious, although there are numerous

examples of post-translational changes on memory-related molecules. For example,

ubiquitin-mediated proteolysis degrades the regulatory subunit of PKA, causing deficits

in long term memory (Chain, Schwartz, & Hegde, 1999). Methylation, acetylation, and

phosphorylation involve the addition of a methyl (CH3) group, acetyl (COCH3) group, or

phosphate (PO4) group, respectively, to certain amino acids of histone tails. For instance,


molecules called histone acetyltransferases (HATs) transfer an acetyl group from acetyl-

CoA to lysine residues on histones. Complementarily, histone deacetylases (HDACs)

catalyze the removal of acetyl groups on lysine residues. There are also histone

methyltransferases (HMTs) and demethylases for transfer of a methyl group to or from

histones, respectively. Kinases and phosphatases add and remove phosphate groups,

respectively. Drugs called HDAC inhibitors pharmacologically inhibit the activity of

HDACs—which has therapeutic potential since increasing histone acetylation (and thus

gene expression) may help ameliorate memory loss. Table 1 and Figure 1 summarize

known HDAC isoforms, HDAC inhibitors associated with them, and the sites of DNA

and histone modifications (image credit: Roth & Sweatt, 2009). These basic molecular

changes will be discussed throughout this essay; below is a specific example of

epigenetic change in neural development that shows the enormous impact of epigenetics

in the nervous system.

Table 1.


Figure 1.

Neural cell differentiation is an example of the potent effects of chromatin

remodeling. Clearly neurons have striking differences from other cells in the body.

Besides maintaining an ionic gradient conducive to action potential firing, they have a

distinctive molecular toolkit involved in excitability and synapse function. So neurons

must develop this functional distinctiveness from other cell types. Promoter regions for

neuronal genes contain a neuron-restrictive silencer element (NRSE) (Maue, Kraner,

Goodman, & Mandel, 1990; Mori, Schoenherr, Vandenbergh, & Anderson, 1992). Other


cell types ubiquitously express a transcription factor, RE-1-silencing transcription factor

(also known as REST or NRSF) that silences expression of neuronal genes (Chong et al.,

1995). Transcriptional repression with REST involves changes in chromatin structure.

Two proteins, SIN3A and CoREST, bind to REST and affect HDAC1 and HDAC2,

respectively (Huang, Myers, & Dingledine, 1999). Although expression of SIN3A

mirrors expression levels of REST, CoREST is more restricted—perhaps because SIN3A

mediates most NRSE-associated gene silencing whereas CoREST serves a particular role

in subtypes of neural cells (Grimes et al., 2000). Both SIN3A and CoREST increase

histone deacetylase activity by their interaction with the aforementioned HDACs. The

REST/CoREST complex is also associated with increased DNA methylation, and it

targets not only genes with the NRSE but also genes proximal to an NRSE (Lunyak et al.,

2002). So silencing of neural genes in non-neural cells occurs by the activity of a

chromatin remodeling complex that decreases histone acetylation and increases DNA

methylation. Epigenetic markings thus have an enormous impact on neural phenotype.

The specific neuroepigenetic correlates of learning and memory will be discussed

extensively throughout this review. Particular attention will be given to the better-

characterized correlates of learning and memory, including DNA methylation, histone

acetylation, histone phosphorylation, and ubiquitylation.


CHAPTER TWO

How does epigenetics affect memory and dementia?

Histone Acetylation

The best-characterized epigenetic modifications in memory research are histone

acetylation, phosphorylation, and methylation as well as DNA methylation. Thus, these

will be addressed in detail throughout this review.

Two influential studies by Alarcón et al. (2004) and Korzus et al. (2004)

addressed the importance of altered histone acetylation patterns in memory formation.

Scientists used a model of Rubinstein-Taybi syndrome (RTS) to investigate the

epigenetic cause of the severe mental retardation seen in RTS. This model originally

piqued the interest of researchers in learning and memory because RTS is caused by a

mutation in the CREB binding protein (CBP) gene, and CREB has been reported as a

major protein involved in the late phase of long-term potentiation (LTP). First,

researchers investigated the phenotype of a heterozygous (cbp+/-) mutant mouse, which

shows symptoms similar to RTS in humans. Despite no change in baseline motor activity,

anxiety, or short-term memory, the mice showed significant deficits in long-term memory

as measured by contextual fear conditioning, cued fear conditioning, and novel object

recognition paradigms (Alarcon et al., 2004). However, they showed normal performance

in the Morris water maze task—the authors suggest this is due to practice in this task (in

contrast, fear conditioning depended on one noxious event). Moreover, there were

electrophysiological signs of late phase LTP deficits in the cbp+/- mice at Schaffer

collateral synapses. Mutant mice expressing a constitutively active form of CREB did not

show normal memory capacity, suggesting there is another mechanism involved. Alarcón


and colleagues suggest histone acetylation as a possible mechanism. They tested their

hypothesis pharmacologically, giving cbp +/- mice the histone deacetylase (HDAC)

inhibitor SAHA. In addition to causing increased H2B acetylation, SAHA restored

contextual memory and electrophysiological response to wild-type levels. Korzus et al.

(2004) investigated this phenomenon further with a different mouse model of RTS. Given

that the aforementioned mutant mice are susceptible to developmental abnormalities that

could confound results, Korzus and colleagues (2004) developed a mouse with spatial

and temporal restriction of CBP deficits. In particular, CA1 and dentate gyrus

hippocampal neurons express a form of CBP without histone acetyltransferase (HAT)

activity only after treatment with tetracycline. These (CBP{HAT+/-}) mice are

substantially impaired in their ability to perform a visual-paired comparison task as well

as the Morris water maze task (for spatial memory). However, additional practice

restored performance on the Morris task, lending credence to the hypothesis Alarcon et

al. (2004) gave about their RTS model’s Morris task abilities. Termination of the

tetracycline diet as well as treatment with the HDAC inhibitor trichostatin A (TSA)

ameliorated the memory-related symptoms of the RTS model mice, indicating that the

HAT activity of CBP is critical to memory formation (Korzus, Rosenfeld, & Mayford,

2004). These results have been further confirmed and elaborated on. Although TSA was

assumed to work by nonspecifically increasing gene expression, it has actually been

shown to regulate expression of specific genes in a CREB:CBP-dependent mechanism

(Vecsey et al., 2007).

Researchers at Baylor College of Medicine validated a critical role for histone

acetylation in memory later that year. Levenson et al. (2004) first trained mice in a


contextual fear conditioning paradigm and collected tissue samples from the

hippocampus either 1 hour or 24 hours afterwards. Compared to control subjects, fear-

conditioned mice showed a two-fold increase in acetylation of histone H3 (Lys-14) after

1 hour. However, the increase was transient; they observed decreased acetylation (normal

levels) after 24 hours. Mice unable to form an association between the unconditioned

stimulus and the context in which it was received also showed normal acetylation levels

(a well-characterized phenomenon called latent inhibition). This indicates that memory

formation requires increased acetylation in certain areas of the chromosomes—a

transformation of heterochromatin. Their findings are also persuasive because they

treated other mice with NMDA or MEK antagonists, relating canonical LTP pathways to

the putative mechanism of chromatin remodeling. As predicted by other studies,

acetylation levels were normal and mice failed to consolidate significant fear

conditioning when treated with NMDA or MEK antagonists. In addition, treatment of

mice with HDAC inhibitors (TSA or sodium butyrate) enhanced induction of LTP,

demonstrated as an increase in freezing in the fear conditioning paradigm. This

enhancement of LTP was due, at least in part, to a three to five-fold

increase in acetylation of histone H4. They also found electrophysiological hallmarks

similar to Alarcón et al. (2004) at Schaffer collateral synapses (Levenson et al., 2004).

The dependence of latent inhibition on H4 changes and fear conditioning on H3 changes

suggests a “histone code” for specific types of memories (Levenson & Sweatt, 2005).

Understanding HDAC inhibition as an area for therapeutic intervention in

learning and memory processes will likely require basic knowledge of the roles of

HDACs themselves. As mentioned before, there are 11 known HDAC isoforms, so


identifying discrete roles for each of them is itself a daunting task. HDAC1 research will

be addressed later, as it ties in with a neurodegeneration study by Fischer and colleagues

(2007). HDAC2 and HDAC3, however, have been characterized as negative regulators of

learning and memory.

Guan et al. (2009) implicates HDAC2, and excludes HDAC1, in negative

regulation of memory formation and synaptic plasticity. First, they created mutant mouse

lines overexpressing HDAC1 and HDAC2 (called HDAC1OE mice and HDAC2OE,

respectively) in areas important for memory, such as pyramidal neurons in the

hippocampus. The HDAC1 and HDAC2 coding sequences were placed in frame with

endogenous Tau, with Tau mutants showing no memory deficits compared to wild type

mice. HDAC2OE mice had about 70% less histone 4 lysine 12 (H4K12) acetylation

compared to wild type mice as well as significantly less H4K5 acetylation but no change

in Ac-H4K14. HDAC1OE mice also had significantly less overall acetylated lysine, but

there was no effect on H4K12 and H4K5 as in HDAC2OE mice. HDAC1OE mice had no

deficits in associative conditioning (freezing in tone-dependent and contextual fear

conditioning). On the other hand, HDAC2OE mice showed ~20% less freezing in tone-

dependent conditioning as well as ~45% less freezing in contextual fear conditioning

experiments. HDAC1OE mice also had similar escape latency and quadrant affiliation as

wild type mice in the Morris water maze task. HDAC2OE mice had much higher escape

latency than HDAC1OE and wild type mice in addition to spending much less time in the

quadrant containing the platform. Correspondingly, HDAC2 knockout mice had more

histone acetylation as well as increased freezing behavior. Gross anatomical analysis of

HDAC KO and OE mice indicated no developmental abnormalities as well. With regard


to spine density in the CA1 region of the hippocampus, HDAC2OE mice had

significantly less than wild type mice while HDAC2 KO mice had much more. An

immunoreactive synaptophysin assay also showed less synapse formation in HDAC2OE

mice and more synapse formation in HDAC2 KO mice. HDAC inhibition (HDACi) with

SAHA restored memory functioning in HDAC2OE mice. Finally, HDAC2 KO mice had

increased electrophysiological signs of LTP (fEPSPs) over 40 minutes of testing while

HDAC2OE mice showed decreased LTP. In addition, a variety a memory-related genes

interact with HDAC2 at their promoter regions, and HDAC2 preferentially associates

with CoREST. This could pave the way for a potential mechanism by which HDAC2

functions. Given the important role CoREST plays in neuronal gene repression (outlined

above), it is plausible that HDAC2 mediates learning and memory by interacting with

basic neuronal regulatory mechanisms. Taken together, this indicates a critical role for

HDAC2 in memory formation, particularly as a negative regulator of molecular,

behavioral, and electrophysiological signs of memory in mice (Guan et al., 2009).

HDAC3 performs a similar role as HDAC2, according to McQuown et al. (2011).

Researchers probed the role of HDAC3 using a genetic and pharmacological approach.

Using a combination of mutant mice and viral infection, they created homozygous

deletions of HDAC3 in area CA1 in the dorsal hippocampus. Moreover, they used the

selective inhibitor RGFP136 to pharmacologically block normal HDAC3 functioning in

the hippocampus. Assayed by immunohistochemistry, both conditions increased histone

acetylation in CA1. As expected, genetic and pharmacological HDAC3 manipulation

enhanced performance in long-term memory tests. There was also increased hippocampal

expression of the memory-related genes nuclear receptor subfamily 4 group A, member 2


(Nr4a2) and c-fos. However, hippocampus-specific delivery of small interfering RNA

(siRNA) targeting Nr4a2 blocked the memory enhancements associated with HDAC3

deletion (but not pharmacological inhibition), suggesting a potential mechanism for

HDAC3’s negative regulation of long-term memory (McQuown et al., 2011).

Besides a role in associative and spatial memory formation, histone acetylation

changes are also implicated in animal models of Alzheimer’s and neurodegeneration. It

has been previously demonstrated that recovery of learning and memory in mice with

significant brain atrophy and loss of memory is associated with environmental

enrichment (EE). Findings by Fischer, Sananbenesi, Wang, Dobbin, and Tsai (2007)

show that histone proteins are involved in synaptic plasticity and mediate the memory-

influencing effects of environmental enrichment for mice.

Fischer et al. (2007) used CK-p25 Tg mice—in which a doxycycline diet induces

expression of the neurotoxic protein p25—to induce symptoms of dementia to compare

with a control. Neuronal populations were cut in half in the cingulate cortex—assayed by

the presence of NeuN, a neuron-specific, nuclear protein. The transgenic mice were split

into two groups: those reared with EE and those reared without EE. The EE group

recovered long-term memories significantly better than the non-EE group, with about

30% savings for the water maze and fear conditioning tasks—even when p25-induced

changes in anxiety and locomotor activity were taken into account. In addition, the EE

and non-EE transgenic groups showed similar brain atrophy levels, suggesting EE leads

to the recovery of long-term memories. Finally, environmental enrichment resulted in

significant lysine acetylation increases on histones H3 and H4 in both the cortex and

hippocampus. The acetylation effect continued over 2 weeks of measurements after


behavioral memory tests. Levels of synaptophysin assessed by an immunoreactivity assay

in the anterior cingulate cortex indicated significantly more synapses in environmentally

enriched animals as well.

To investigate whether chromatin remodeling mimics the effects of environmental

enrichment, Fischer et al. (2007) used the HDAC inhibitor sodium butyrate (SB). Some

Tg mice were given daily injections of SB to induce chromatin remodeling while others

were treated with saline solution. Similar to the EE and non-EE groups, the SB group

showed about 45% savings for fear conditioning and about 30% savings for the water

maze task compared to mice injected with saline solution. Given a period of 4 weeks for

consolidation of a fear-conditioning task, the SB-injected mice had similar improvement

over mice injected with saline solution. In many tests SB-treated mice performed as well

as or nearly as well as wild type mice. Moreover, there were more synapses and up-

regulated histone acetylation of H3 and H4 lysine residues despite no apparent increase in

the number of neurons. This supports the hypothesis that increasing histone-tail

acetylation mimics the memory-enhancing effects of environmental enrichment, induces

synaptic rewiring, and even leads to the recovery of inaccessible long-term memories in

mice (Fischer et al., 2007).

Given the importance of characterizing HDAC functioning to understand how

HDAC inhibition works, researchers also considered the effects of the CK-p25 Tg mouse

model on HDAC1. Cell cycle changes and DNA damage are becoming important areas of

interest in neurodegeneration research, and expression of p25 initiates many hallmarks of

aberrant cell cycle activity and DNA damage before atrophy occurs. Messenger RNA

levels of many cell cycle markers are up-regulated by p25 toxicity in the hippocampus,


including cyclin B, cyclin E, cdc25a, p21, MCM3, MCM6, and MCM7. In addition,

protein levels of the DNA damage markers gH2AX and Rad51 were greatly up-regulated

in the forebrain after p25 induction. Increased comet tails on a micrograph and increased

immunoreactivity of damage markers in fluorescence imaging also indicated DNA

damage. Loss of HDAC1 by RNAi or pharmacological inhibition of HDAC1 activity

with the class I HDACi MS-275 yielded similar results as p25 toxicity (i.e. DNA damage,

aberrant cell cycle activity, and atrophy). More directly linking p25 cell damage and

HDAC1 function, overexpression of HDAC1 in p25 cells protected against cell toxicity

and DNA damage. This approach to ameliorate p25 damage was effective in cultured

neurons as well as in an in vivo ischemia model (Kim et al., 2008). It is therefore clear

HDAC1 plays a role in neurodegeneration in the p25 model of cell toxicity, but

researchers are also interested in traditional Alzheimer’s pathology.

The traditional molecular hallmarks of AD, amyloid plaques and neurofibrillary

tangles, are also important to incorporate in an epigenetic perspective on memory.

Although the data is somewhat preliminary given the relative youth of epigenetics as a

discipline, there is accumulating evidence that directly implicates epigenetics in

canonical Alzheimer’s pathways. Amyloid-β precursor protein (APP) is cleaved in the

transmembrane domain by γ-secretase. This cleavage results in amyloid β plaques on the

extracellular side as well as a more mysterious domain on the intracellular side.

Cao and Südhof (2001) investigated the APP cytoplasmic (intracellular) domain

using a two-hybrid system. The two-hybrid system allows researchers to investigate

interactions among proteins by taking advantage of the distinct functional units, or

domains, in transcription factors. Transcription factors typically have a DNA binding


domain (DBD) as well as an activation domain (AD). To accomplish the two-hybrid

approach, researchers first attach a protein of interest to the DBD of a transcription factor

(this fusion protein is called the “bait”). Second, a protein that presumably interacts with

the domain of interest is attached to the AD of a transcription factor (this protein is called

the “prey”). If there is, in fact, an interaction between the “bait” and “prey” proteins,

transcription will be greatly up-regulated on a reporter gene (usually lacZ). This is

because the interacting proteins bring the DBD and AD in such close proximity that they

can function similarly to the normal transcription factor and thus initiate transcription. Of

course, if there is little or no interaction between two proteins there will be little or no up-

regulation of transcription of the reporter gene. The most common transcription factors

used in the two-hybrid approach are yeast Gal4 and bacterial LexA (Little, 2010).

Cao and Südhof (2001) characterized protein-protein interactions of the APP

cytoplasmic domain using cell culture models (PC12, HEK293, COS, and HeLa cells).

The DBDs of Gal4 or LexA were fused with full length, intracellular APP695. They also

cotransfected the cells with a Gal4/LexA-dependent plasmid containing luciferase (the

reporter gene) to analyze transcription changes. There was a small change in transcription

levels in the Gal4/LexA transcription factor fusion APP, but >2000-fold transcription

increases occurred in cells cotransfected with Fe65. This indicates interaction between

exogenous APP and Fe65. Additionally, the increase in transcription did not occur in

APP with a point mutation that blocks Fe65 binding; nor was there an increase in

transcription when the “prey” was Mint1/X11 (i.e. the effect is specific to Fe65). Cao and

Südhof (2001) reported similar results in all cell types they tested. Both PTB1 and PTB2

were required domains for Fe65 functioning in their assay. Additionally, the same two-


hybrid assay was used with a different reporter in COS cells to examine interactions

between Fe65 and a HAT reported in many cancer studies, Tip60. There was a dramatic

transcriptional increase when Gal4-Tip60 was co-expressed with Fe65 and APP, but

either no increase or very little increase with mutant APP, Fe65 alone, or APP alone. This

implies that Tip60 histone acetyltransferase forms a complex with both Fe65 and the

cytoplasmic domain of cleaved APP to remodel chromatin and increase gene

expression—directly linking epigenetics and canonical Alzheimer’s pathways (Cao &

Südhof, 2001). Since epigenetic modifications happen in the nucleus (where

chromosomes are localized), Cao and Südhof (2001) determined by fluorescence

microscopy that Tip60 is in the nucleus under every condition tested while Fe65 is

nuclear only in the absence of APP (or in the presence of mutant APP). APP was

localized in the cytoplasm, but because of assay limitations this did not preclude the

possibility that some (<5%) APP might be in the nucleus.

There is additional evidence suggesting the APP intracellular domain (AICD)

functions in a similar manner to the Notch intracellular domain (NICD) (Sastre et al.,

2001; Kimberly, Zheng, Guenette, & Selkoe, 2001). However, an important study notes

that the AICD also has a pathway of its own and regulates its own precursor’s

transcription via the multiprotein complex described by Cao and Südhof (2001) (von

Rotz et al., 2004). Using a combination of confocal microscopy with inducible

fluorescence tagging and co-immunoprecipitation, von Rotz and colleagues (2004)

determined that Tip60 localized in the nucleus. However, fluorescent AICD localized in

the nucleus with Tip60 only in the presence of Fe65 in HEK293 cells. The AICD-Fe65-

Tip60 complex (called AFT) had structural damage in a mutant of Tip60, abolishing the


spherical nuclear spots that indicated nuclear localization of AFT. Gamma-secretase

inhibitors also blocked formation of the AFT complex. Besides the AFT complex, Tip60

and AICD also form an association with the APP adaptor protein Jip1b. The AICD-Jip1b-

Tip60 (AJT) complex serves a similar function as AFT, with Jip1b aiding in transport of

AICD to the nucleus and docking it to Tip60. Consistent with Cao and Südhof (2001),

Mint1/X11α trapped AICD in the cytosol. Finally, there is an apparent positive feedback

mechanism involved in AICD signaling. Induced expression of AICD resulted in

increased expression of APP and Tip60, but not the Notch-effector gene Hes1 (von Rotz

et al., 2004). Although present studies of APP intracellular signaling are far from

providing a comprehensive view of how epigenetics and amyloid-β are connected, there

is already evidence that epigenetic intervention in APP signaling could lead to better

treatments of Alzheimer’s.

Additional evidence for epigenetic involvement in APP signaling comes from a

mutant mouse model, APP/PS1dE9. APPswe/PS1dE9 mice have contextual memory

deficits after 6 months of life due to overexpression of presenilin-1 (PS1) and the

presence of a Swedish mutation, which is linked to early-onset AD. Kilgore et al. (2010)

demonstrated the beneficial effects of HDACi on class I HDACs in the aforementioned

AD model mouse. Chronic (2-3 week), intraperitoneal injection (IP) of sodium valproate,

sodium butyrate, or vorinostat (SAHA) into the mutant mouse enhanced histone

acetylation and contextual memory task performance to wild type levels. Amelioration of

memory function in the mutant mice happened without affecting baseline exploratory

behavior or immediate freezing. Thus, state-dependent effects were not an issue and

HDACi of class I HDACs is a potential therapeutic pathway for Alzheimer’s researchers.


Most strikingly, SAHA affected each class of HDAC to achieve its therapeutic effect.

Given that vorinostat is already a T-cell lymphoma drug marketed as Zolinza, clinical

trials in AD would be much easier to pursue. As expected, memory improvement

correlated with histone acetylation increases (Kilgore et al., 2010).

Besides its relationship with APP biology, Alzheimer’s is also an age-related

disease diagnosed most frequently in people over 65 years of age. Given the likelihood of

memory-related problems occurring later in life, Peleg et al. (2010) designed an

experiment to relate hippocampal histone acetylation changes to aging in mice. Levels of

histone tail acetylation in three-month-old mice were compared to sixteen-month-old

mice in a contextual fear conditioning task. Given that mice live 26-28 months on

average, 16-month-old mice could be considered elderly. Behaviorally, 16-month-old

mice performed significantly less freezing and had increased platform-locating latency in

the Morris task (besides spending significantly less time in the target quadrant). The

lysine acetylation assay was performed in control mice as well as mice 10 min., 30 min.,

60 min., and 24 hours after fear conditioning training. Residues analyzed for acetylation

changes include H3K9, H3K14, H4K5, H4K8, H4K12, and H4K16. The histone

acetylation profile of every group was similar with two notable exceptions. H4K5

showed increased acetylation at 30 min. after fear conditioning in 16-month-old mice

while there was no such increase in 3-month-olds. Since other time points showed a

similar acetylation profile in young and aged mice at H4K5, this result is much less eye-

catching than the following one. H4K12 acetylation did not increase in 16-month-old

mice as a response to fear conditioning at any time point, whereas in 3-month-old mice

every fear-conditioned group had increased acetylation. This happened without any


change in baseline HAT/HDAC or H4 levels in the cell. This led researchers to conclude

that deregulation of H4K12 in aged rats after fear conditioning leads to their impaired

memory performance. Furthermore, microarray analysis of hippocampal gene expression

1 hour after fear conditioning showed 2229 gene transcript changes (increase or decrease)

in 3-month-old mice, with 1539 of those genes previously linked to associative learning.

On the other hand, 16-month-old mice had only 6 gene expression changes after fear

conditioning. Some gene expression profiles deciphered by data mining were also

verified with real-time PCR. Baseline gene expression was virtually identical in 3-month

vs. 16-month control groups. Taken together, this means deregulation of H4K12

acetylation following fear conditioning in aged mice results in drastically different gene

expression profiles than young mice. Similar to other studies, SAHA treatment of 16-

month-old mice increased freezing behavior in an associative learning task. Interestingly,

H4K12 acetylation increased significantly in response to SAHA treatment whereas no

other lysine residues had a statistically significant increase, including H4K5 (which had

increased acetylation at the 30 min. time point in the old group). Finally, H4K12

acetylation increased at the promoter regions of the formin 2 and Prkca genes, and a

variety of other genes had increased H4K12 acetylation at coding regions. Increased

H4K12 acetylation at coding regions correlated with increased gene expression as well.

There was no change in the 16-month-old group’s ability to find a visible platform,

exploratory behavior, or response to foot shock; various markers of hippocampal

plasticity and integrity were similar between young and old mice. Thus, aging’s negative

effect on memory capacity in mice is related to H4K12 acetylation changes rather than

loss of structural integrity, exploratory behavior, or response to foot shock (Peleg et al.,


2010). Epigenetics could, therefore, offer insight into the cognitive decline seen with

natural aging.


CHAPTER THREE


Histone Phosphorylation and Methylation

There has recently been an explosion of knowledge gathered about the

relationship between histone acetylation, DNA methylation, and memory, with

comparatively little work done on histone phosphorylation and methylation. At the very

least, however, the latter two chemical alterations appear important in early hippocampal

memory consolidation. Notably, there is currently no work published on prefrontal cortex

changes with respect to histone phosphorylation and methylation, which puts this

research significantly behind other epigenetic approaches. That is not to say work is not

currently being done on this. The Lubin lab at the University of Alabama has already

given oral presentations of forthcoming work relating histone methylation to prefrontal

cortex memory consolidation.

It has been previously reported that cellular stress and activation of immediate

early genes correlates with increases in histone phosphorylation (Thomson, Clayton, &

Mahadevan, 2001). Two early studies have also indicated the importance of histone

phosphorylation in early memory consolidation in the hippocampus. Crosio, Heitz, Allis,

Borrelli, and Corsi (2003) demonstrated that multiple signaling pathways can trigger

histone phosphorylation in the hippocampus. Researchers used a dopaminergic receptor

agonist (SKF82958), mACh receptor agonist (pilocarpine), and a kainate glutamate

receptor agonist (kainic acid), all of which induced chromatin remodeling in hippocampal

neurons. Marks of chromatin remodeling included H3 serine 10 phosphorylation and

lysine 14 acetylation. Validating previous results, activation of these signaling pathways


also increased c-fos transcription (Crosio et al., 2003). However, these results do not

necessarily indicate that histone phosphorylation is important in learning and memory.

They only show that hippocampal neurons use it in response to stimulation.

More directly implicating histone phosphorylation in learning processes, Chwang,

O’Riordan, Levenson, and Sweatt (2006) found phosphorylation and acetylation

increases (on H3S10 and H3K14) as a result of ERK/MAPK activation in vitro. The

process was NMDA receptor-dependent since the NDMA-R anatagonist MK801 blocked

the effect. More importantly, though, contextual fear conditioning increased area CA1

histone phosphorylation transiently (1-2 hours after training). MEK works just upstream

of ERK in the ERK signaling cascade, and administration of the MEK inhibitor SL327

blocked H3S10 phosphorylation changes after fear conditioning. This result was verified

with a phospho-ERK assay, which made sure phosphorylation (activation) of ERK was,

in fact, inhibited by SL327 (Chwang et al., 2006). Although phenomenological results are

important, it is clinically beneficial to identify target kinases and phosphatases involved

in epigenetic modification for therapeutic intervention. ERK/MEK signaling has long

been considered an important pathway in modulation of gene expression, but an

important study by Lubin and Sweatt (2007) elucidates the role of a well-studied immune

response kinase in memory reconsolidation.

Memory maintenance requires reconsolidation after recall. In rats, contextual fear

conditioning normally involves shocking the animal in a novel context (the conditioning

chamber) and testing freezing behavior after the initial training. Reestablishment of

contextual conditioned fear (CCF) memory, accomplished by re-exposing the animal to

the novel context, can be blocked with inhibition of protein synthesis—ERK/MAPK


inhibition, for instance (Lubin & Sweatt, 2007). Lubin and Sweatt (2007) specifically

looked at signaling with the transcription factor nuclear factor kappa B (NF-κB) to see

whether there was an effect on histone phosphorylation during reconsolidation.

It is first necessary to review information on NF-κB signaling, which has been

primarily implicated in response to inflammation. NF-κB is inhibited by inhibitor kappa

B (IκB); thus modification of IκB is required in order to activate NF-κB. IκB proteins are

marked for degradation when they are phosphorylated by the IκB kinase (IKK) complex.

The IKK complex has α, β, and regulatory γ subunits. Once IKK frees IκB from NF-κB,

NF-κB translocates to the nucleus and binds genes with the κB consensus sequence in

their promoter. However, components of the NF-κB signaling pathway have been shown

to add phosphate and acyl groups to histones in nonneuronal cells, so the NF-κB DNA

binding complex is likely not the whole story; this was the impetus for investigating

chromatin remodeling by NF-κB in hippocampus cells.

First, the NF-κB inhibitor diethyldithiocarbamate (DDTC) was administered (via

IP injection) to a group of rats after a memory test. Although vehicle and DDTC rats

exhibited similar freezing behavior during the first memory test, freezing decreased in

DDTC-treated rats during tests 2 days and 7 days after training, suggesting NF-κB

inhibition interferes with CCF memory. Phosphorylated IKKα serine 180—and not IKKβ

serine 181—levels also increased in area CA1 1 hour after training. DDTC treatment

blocked the increase. Increased IKKα phosphorylation only occurred in rats re-exposed

to the context after initial context + shock training, as there was no such increase in

animals only exposed to the context (over 1 or 2 days) or only given contextual fear

conditioning. DNA binding activity of NF-κB assessed by an electrophoretic mobility


shift assay (EMSA) also rose following conditioning and attenuated in DDTC groups.

DDCT injection ultimately resulted in decreased H3 phosphorylation after CCF training.

Surprisingly, pharmacological inhibition of IKK with sulfasalazine (SSZ) reversed the

behavioral and molecular effects of context re-exposure. Another pharmacological tool,

SN50, blocks NF-κB’s normal interaction with DNA binding sites. SN50 administration

decreased freezing behavior in the CCF paradigm, but there was no effect on histone

phosphorylation. On the other hand, IKKα inhibition decreased phosphorylation at the

promoters of the immediate early gene Zif268 as well as IκBα. Taken together, the

results impart a critical role for IκB kinase (IKK) in regulation of chromatin structure

after CCF memory training in area CA1 of the hippocampus. Regulation of chromatin

structure by IKKα happens upstream of regulation by NF-κB’s transcription complex to

affect learning and memory (Lubin & Sweatt, 2007). The kinase activity of IKKα thus

represents a promising target for therapeutic intervention in diseases of memory.

Histone methylation’s involvement in memory-related processes remains more

mysterious than other epigenetic factors. Gupta et al. (2010) was the first to investigate

hippocampus-specific histone methylation patterns after fear conditioning. Unlike

previous epigenetic marks discussed in this review, researchers demonstrated

transcriptional activation and silencing with histone methylation. This is due to the well-

characterized capacity of lysine residues to be monomethylated, dimethylated, or

trimethylated. Each of these result in a different transcriptional hallmark depending on

the lysine residue of interest. Tissue collection 1 hour after fear conditioning from area

CA1 of the hippocampus showed an increase in both H3 trimethylation at lysine 4

(H3K4me3) as well as H3K9me2. H3K9 dimethylation, however, decreased below


control levels 24 hours after fear conditioning while H3K4 trimethylation returned to the

baseline. Latent inhibition (i.e. exposure to the context before context+shock pairing)

decreased freezing behavior and blocked the transient increase in H3K4me3, so proper

timing is crucial for transient trimethylation. Deficits in a methyltransferase, Mll, with

specific activity on H3K4 resulted in decreased freezing behavior. Finally, promoters

regions for Zif268 and BDNF also had an increase in H3K4me3 after fear conditioning.

HDAC inhibition with sodium butyrate also helped increase trimethylation and decrease

dimethylation, confirming pervious studies. The trimethylation increase correlated with

altered DNA methylation at Zif268 promoters, increased mRNA levels, and altered

MeCP2 binding (Gupta et al., 2010). Histone methylation therefore functions to alter

memory consolidation in area CA1 of the hippocampus in concert with histone

acetylation and phosphorylation. However, there is currently no evidence of histone

methylation as a mark of memory maintenance. This concludes the discussion of histone

modifications in learning and memory, but DNA methylation also impacts learning-

related behavior.


CHAPTER FOUR


DNA Methylation

As outlined previously, DNA methylation involves the enzyme-catalyzed addition

of a methyl (--CH3) group at the 5’ position of cytosine pyrimidine rings. There is

increasing evidence that transcriptional regulation by DNA methylation aids in both

memory formation in the hippocampus as well as memory maintenance in the cortex.

Miller and Sweatt (2007) reported an important role for DNA methylation by

DNMTs in contextual fear conditioning experiments. Context + shock animals showed

dramatically up-regulated mRNA levels of DNMT3A, DNMT3B, and c-fos 30 minutes

following fear conditioning (compared to context only animals) in area CA1 of the

hippocampus. Infusion of global DNMT inhibitors 5-azadeoxycytidine (5-aza) or

zebularine (zeb) into area CA1 of the hippocampus immediately after training in a

contextual fear conditioning task blocked freezing behavior. This effect was not seen in

animals injected with a DNMT inhibitor 6 hours after training. Notably, the decrease in

freezing was transient—DNMT inhibited animals in later tests had similar freezing times

as control animals in the test 1 day after training. A CpG island analyzed in the memory

suppressor gene protein phosphatase 1 (PP1) was dramatically more methylated than

context-only controls 1 hour after learning, and DNMT inhibition occluded this effect

while increasing mRNA of PP1 in area CA1. Reelin (Reln) methylation also decreases

after fear conditioning; the effect is larger with DNMT inhibition. These results suggest a

critical role for covalent modification of DNA in memory formation in CA1 of the

hippocampus (Miller & Sweatt, 2007).


Similar to studies on the native function of HDACs in the chapter on histone

acetylation, some DNMTs have been analyzed for specific functional properties. Feng et

al. (2010) implicates Dnmt1 and Dnmt3a in synaptic function, learning, and memory.

Although mice with mutations in Dnmt1, Dnmt3a, or Dnmt3b are not viable, Feng et al.

(2010) developed a conditional knockout model for adult forebrain neurons that eschews

viability issues—more specifically they used a CaMKIIa-Cre93 transgene to induce

deletion exclusively in postmitotic neurons postnatally. Researchers knocked out Dnmt1,

Dnmt3a, or both; no significant gene knockout occurred by postnatal day 3 (P3), but by

P14 and into 4 months of life knockout was accomplished. Stereological analysis of

double knockout (DKO) mice revealed slightly decreased hippocampus and dentate gyrus

volume while single knockout mice had no obvious anatomical differences from control

mice. Regardless, optical fractionator analysis indicated that the decrease in total volume

was not a result of atrophy but rather a decrease in volume of individual neurons. First,

DKO mice had disrupted LTP at Schaffer collateral-CA1 synapses and enhanced LTD in

a stimulation protocol that normally fails to induce LTD. Behaviorally, DKO mice took

more time to find the platform in the Morris water maze and spent less time in the target

quadrant than control mice with no change in baseline swimming speeds. This indicates

deficits in spatial learning and memory in DKO mice. Knockout animals also exhibited

less freezing behavior 24 hours after contextual fear conditioning, another indicator of

learning and memory deficiency. Microarray and real time PCR analysis revealed

upregulated immune genes important in learning and memory, including MHC-I and

Stat1. Interestingly, Reln and PP1 levels did not change in DKO mice. These genes will

be discussed in more detail later. Bisulfite sequencing also showed significantly less


DNA methylation at the Stat1 promoter from -895 to -1,010 bp in DKO mice. This did

not occur in single knockout mice, suggesting Dnmt1 and Dnmt3a compensate for one

another. In addition, demethylation occurred only in cells that tested positive for NeuN in

fluorescence-activated cell sorting (FACS)—an indicator of neuronal populations.

Finally, demethylation was verified with a variant of mass spectrometry, and bisulfite

sequencing found demethylation on the promoters for Dhh, Kcne1, and two regions of

Pten. Overall, these results strongly suggest Dnmt1 and Dnmt3a work together to

maintain methylation patterns in adult forebrain neurons. Their regulation of DNA

methylation ultimately perpetuates proper synaptic function for learning and memory

(Feng et al., 2010).

One of the most important results with regard to DNA methylation comes from

Miller et al (2010). While previous studies investigated transient epigenetic marks after

learning in animals, Miller et al. (2010) found long-lasting DNA methylation patterns

maintaining memory. Since behavioral memories persist multiple molecular lifetimes,

maintaining these memories would likely involve such a self-perpetuating mechanism.

Consequently, DNA methylation is a good candidate for maintenance of transcriptional

repression. However, one of the most compelling aspects of Miller et al. (2010) is its

description of DNA methylation as a potential mechanism for remote memory

maintenance in a prefrontal cortical area called the anterior cingulate cortex (ACC). It has

been demonstrated previously that the ACC maintains remote contextual fear memory. In

particular, activity-dependent expression of c-fos and Zif268 (genes implicated in

memory) increases during remote memory maintenance in the ACC. Moreover, a null α-

CaMKII mutation and pharmacological inactivation of the ACC with lidocaine block


remote memory (Frankland, Bontempi, Talton, Kaczmarek, & Silva, 2004). However, a

mechanism for long-term memory storage remains elusive. The prefrontal cortex is a

popular candidate for involvement in epigenetic memory maintenance—hippocampal

epigenetic marks return to baseline levels after a maximum of about one day after

learning. There are now results implicating DNA methylation in the consolidation

process. Miller et al. (2010) first used immunoprecipitation to examine dorsomedial

prefrontal cortex (dmPFC) DNA methylation levels on learning-related genes that have

large GC-rich CpG islands in rodents. The immediate early gene Erg1 was demethylated

at all time points. On the other hand, reelin (Reln) was hypermethylated 1 hour after

training, with levels of hypermethylation decreasing over time. This result is somewhat

surprising since reelin is considered a positive regulator of memory and hypermethylation

is associated with transcriptional silencing. Finally, methylation of the phosphatase and

memory suppressor gene calcineurin (CaN, Ppp3ca) did not change shortly after training.

Rather, hypermethylation measured by bisulfite sequencing occurred within 1 day of

training and persisted in tests both 7 days and 30 days after training. This is more

intuitive than results for Reln since CaN is a memory suppressor gene. Thus, CaN was

used as a proxy for global dmPFC DNA methylation changes occurring after contextual

fear conditioning. To further confirm that the observed DNA methylation changes

represent associative learning persisting in the cortex, a group of rats tested 7 days post-

training were injected with the NMDA antagonist MK-801. Besides blocking acquisition

of the fear memory, MK-801 administration interfered with dmPFC hypermethylation of

CaN and Reln (with no effect on Erg1), suggesting that specific environmental signals

induce hypermethylation of CaN and Reln. Notably, hypermethylation of CaN was


accompanied by considerable decreases in CaN mRNA and protein levels 30 days after

training. But none of this determines whether DNA methylation is a necessary factor in

maintaining remote memory. Pharmacological inhibitors of DNMTs (5-

azadeoxycytidine, zebularine, RG108) administered in the ACC (a subregion of the

dmPFC) 30 days after training decreased freezing behavior by 45-60% in the memory

test, in addition to reducing CaN DNA methylation levels and increasing CaN mRNA

levels. Intra-ACC injections of DNMT inhibitors had no effect on fear memory 2 days

after training; nor was there an effect in these rats 30 days after training, so

administration of DNMT inhibitors to disrupt remote memory in the ACC must occur

after necessary cortical DNA methylation events. Moreover, there was no indication of

major damage to the ACC itself (Miller et al., 2010).

DNA methylation also appears to be crucial in BDNF’s ability to spur dendritic

growth and positively regulate learning and memory. Lubin, Roth, and Sweatt (2008)

first found a large increase in BDNF transcription in area CA1 of the hippocampus 2

hours after fear conditioning. The increase was specific to exon IV of BDNF, but others

increased slightly in context-only controls. Fear conditioning was accompanied by

methylation decreases at exons I and IV, and methylation increases at exon VI of BDNF.

The appropriate increase or decrease in BDNF exon mRNA was confirmed with real time

PCR. Similar to previous studies, DNMT inhibition (with zeb and RG108) reversed these

behavioral and molecular hallmarks and changed BDNF expression. Researchers also

found alterations in chromatin remodeling as measured by histone acetylation as a result

of contextual fear conditioning and DNMT inhibition; and the process was NMDA

receptor-dependent (Lubin et al., 2008). Similar results were reported by Martinowich et


al. (2003) for cultured neurons after depolarization. CpG methylation of the exon IV

promoter decreased after depolarization while BDNF synthesis increased. This increase

in transcription involved changes in a chromatin remodeling complex. The MeCP2-

HDAC1-mSin3A repression complex dissociated from the BDNF promoter, allowing the

increase in transcription (Martinowich et al., 2003). Taken together, Martinowich et al.

(2003) and Lubin, Roth, and Sweatt (2008) indicate that BDNF’s important role in

dendrite survival and learning depends on DNA methylation.

As mentioned in the introduction, molecules with DNA demethylase activity have

been elusive in mammals. Even the existence of demethylases was the subject of

controversy. After all, a large amount of energy is required to break the covalent carbon

bonds of methylated DNA, and this could be prohibitive on a realistic biological

timescale. There have previously been reports of such proteins in C. elegans, but Ma et

al. (2009) was the first to characterize a mammalian protein with specific demethylase

activity and a role in adult neurogenesis, Gadd45b. Electroconvulsive treatment (ECT) of

adult mice causes upregulation of hippocampal neurogenesis, and Ma et al. (2009) found

a large induction of Gadd45b mRNA (growth arrest and DNA-damage-inducible protein

45 beta) 1-3 hours after ECT. What’s more, in situ hybridization also confirmed the

increase in Gadd45b after ECT. Even exploration of a novel environment significantly

increased Gadd45b expression in the dentate gyrus (measured 1 hour after exploration by

immunostaining). Gadd45a had already been demonstrated as a demethylase in human

cultured cells, so Gadd45b was a good candidate to investigate for demethylase activity

controlling neurogenesis induction. Intriguingly, the dramatic mRNA increase was not

seen for Gadd45a and Gadd45g in the hippocampus, implicating Gadd45b specifically in


the ECT/exploratory response process. The Gadd45b induction process depends on the

NMDA receptor, as a NMDAR antagonist (CPP) administered in vivo before ECT

specifically blocked Gadd45b up-regulation. A cell proliferation assay with BrdU in the

dentate gyrus also showed that shRNA-induced knockdown of Gadd45b abolished

normal ECT-dependent proliferation. Finally, the frequency of methylation at individual

CpG sites of BDNF IX and FGF-1B increased to control levels in Gadd45b KO mice

after ECT. The methylation increase was accompanies by decreased dendritic length of

samples in the dentate gyrus (Ma et al., 2009). Since Gadd45b modulates neurogenesis

and learning-related gene expression with demethylase activity, it will be the subject of

more extensive research in the coming years. It is an exciting result because of its

potential to give neural DNA methylation research another avenue for therapeutic

intervention (similar to HDAC inhibition). This could be an important advance in

treatment of Alzheimer’s disease, as age-specific DNA methylation pattern alterations

have already been reported in late-onset AD patients (Wang, Oelze, & Schumacher,

2008). Normal aging even correlates with loss of genomic 5-methyldeoxycytidine

(Wilson, Smith, Ma, & Cutler, 1987).


CHAPTER FIVE

Challenges and Future Directions

Given that epigenetics is a relatively new discipline, the literature is currently

somewhat vague. For instance, most epigenetics of memory studies incorporate HDACs

like sodium butyrate, which modulates expression of a large number of genes in a

shotgun attempt to increase those that actually help memory. However, scientists do not

fully understand what all of these genes do—or in other words why increased expression

of a set of genes results in enhanced performance for mice in a fear conditioning task.

And getting to that point will take time. It will require advanced knowledge of very

specific HDACs, HDAC inhibitors, HATs, DNMTs, etc.—knowledge that could require

decades of research and substantial funding. Targeting specific histone residues to

improve memory is a daunting task in itself, not to mention figuring out which ones

improve memory without deleterious side-effects. That is not to say it is a far-fetched

idea, though. EnVivo Pharmaceuticals recently announced that a drug similar in structure

to SAHA reached phase 2 clinical trials for treatment of Alzheimer’s, according to

private correspondence with one of their consultants, David Sweatt. Given the current

intrigue with results like Fischer et al. (2007), in which the memory-related symptoms of

neurodegeneration were greatly decreased despite the atrophy, funding may soon be

easier to acquire for this research. After all, clinical implications this compelling have

certainly received attention from governments seeking decreased medical care costs for

the elderly and start-up companies looking for a panacea. While some clinical trials with

HDACs have already failed in phase 3, it may only be a matter of time before the right

molecules are tested if current mouse models are truly revelatory; the appeal of HDACs


or HATs for the treatment of diseases may not just be hype. Sananbenesi and Fischer

(2009) argue that many inherited and sporadic epigenetic deregulations in brain diseases

seem causally involved in disease progression unlike any other potential treatment

options. This could be why HDAC inhibitors have both neuroprotective and

neurodegenerative potential—epigenetics might be the key bottleneck to understanding

these diseases. Though the “histone code” is not nearly as well understood as DNA’s

traditional “code,” deciphering it may be challenging and exciting for neuroscience.

Indeed, there is even debate about whether the epigenetic marks outlined above integrate

to form a histone code at all. Beyond this problem, there are few studies indicating that

lifelong memories could be stored by such a histone code. The first studies suggesting

this possibility relate long term epigenetic changes to early life stress and nurturing

(Roth, Lubin, Funk, & Sweatt, 2009; Weaver et al., 2004). Still, it will take more research

to fully answer the question of how lifelong memories are stored. Epigenetic states will

even differ between brain regions to integrate behavior, and understanding this could take

years of research as well (Day & Sweatt, 2011). Epigenetic modifications could very well

act independently to affect gene expression.

Another interesting implication of neuroepigenetics is its challenge to

physiological psychology’s doctrine of Hebbian learning—“cells that fire together wire

together.” While it may be true that interactions at thousands of synapses for each cell

create neural circuits, epigenetics would require some rethinking of the initial hypothesis.

Chemical changes in the nucleus of one cell could completely silence genes involved in

plasticity, and thus shut down the neural circuit. So there could be at least two


mechanisms at play in the process of behavioral plasticity—epigenetic and Hebbian

(Roth & Sweatt, 2009).

Regardless of these challenges, one thing remains clear: epigenetic manipulation

is one of the most promising avenues for therapeutic intervention in Alzheimer’s right

now. An epigenetic perspective could bridge the gap between known genetic

predispositions for Alzheimer’s and the necessary cellular events that trigger it over time.


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Neuroepigenetics of Learning and Memory