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Part III Innovative Development Tools for Modern Biopharmaceuticals j93 Modern Biopharmaceuticals: Recent Success Stories, First Edition. Edited by Jörg Knäblein. # 2013 Wiley-VCH Verlag GmbH & Co. KGaA. Published 2013 by Wiley-VCH Verlag GmbH & Co. KGaA.

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Page 1: Modern Biopharmaceuticals (Recent Success Stories) || Standardized Solutions for Quantitative and Real-Time RT-PCR to Accelerate Biopharmaceutical Development

Part IIIInnovative Development Tools for Modern Biopharmaceuticals

j93

Modern Biopharmaceuticals: Recent Success Stories, First Edition. Edited by Jörg Knäblein.# 2013 Wiley-VCH Verlag GmbH & Co. KGaA. Published 2013 by Wiley-VCH Verlag GmbH & Co. KGaA.

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5Standardized Solutions for Quantitative and Real-Time RT-PCRto Accelerate Biopharmaceutical DevelopmentDirk Löffert

5.1Introduction

One of the promises of the human genome project has been that the determinationof transcription profiles will help accelerate drug development processes and maylead to diagnostic tests for personalized medicine based on gene expression data.Meanwhile, gene expression analysis has become a cost-effective, standard methodin many stages of the development process for biopharmaceuticals.Gene expression analysis is based on two major technologies: gene expression

microarrays and real-time reverse transcription polymerase chain reaction(RT-PCR). Microarrays are ideal tools for target discovery since they enable thescreening for downregulation and upregulation of thousands of genes in parallelin a single sample. Comparison of transcriptional profiles of different tissues or othersample types gains valuable insight into which genes may be affected at thetranscriptional level as a consequence of a disease or may be the cause of a disease.However, it has been shown that microarrays can be susceptible to a great degree ofvariability. Multiplatform as well as multilaboratory meta-analysis studies are beingconducted to gainmore insight into this issue [1–3]. It is therefore necessary to validatethe initial hits obtained bymicroarray analysis in order to eliminate false positives andto demonstrate reproducibility with a greater number of samples. Ideally, validation isconductedwith an independentmethodsuchas real-timeRT-PCR.Although real-timeRT-PCR cannot usually reach the same level of parallel gene expression analysis, itdoes offer several advantages over microarrays: increased sensitivity and a widerdynamic range for quantitative analysis. This enables the detection of even low-abundant transcripts as well as the analysis of minute sample material, such as laser-microdissected tissues. Due to its lower variability, real-time RT-PCR also providesbetter statistically relevant data per defined sample number.Since its introduction to molecular biology laboratories in 1996 [4,5], quantitative,

real-time RT-PCR has become a powerful tool for investigating the effects of adisease state or a putative drug on gene expression. Real-time PCR instruments havebeen continuously improved since then to increase throughput and reduce costs,

j95

Modern Biopharmaceuticals: Recent Success Stories, First Edition. Edited by Jörg Knäblein.# 2013 Wiley-VCH Verlag GmbH & Co. KGaA. Published 2013 by Wiley-VCH Verlag GmbH & Co. KGaA.

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streamlining many steps in the drug development process. Improvements includeshorter overall reaction times through fast cycling methods as well as the capabilityto quantify different transcripts in a single reaction through the detection of distinctfluorescent dyes. However, although modern instruments enable the simultaneousdetection of up to five fluorophores, lack of appropriate reagents and tediousoptimization for multiplex assays have limited the efficient use of the instruments’throughput.This chapter provides a comprehensive overview of current state-of-the-art real-

time PCR instrumentation and reagents, focusing on the use of quantitative,multiplex, real-time RT-PCR to increase the throughput and accuracy of geneexpression analysis. Since accuracy of gene expression analysis is also heavilydependent on the quality of the startingmaterial, this chapter also describes effectivemethods for sample handling and preservation of gene expression profiles and newstreamlined methods for performing real-time RT-PCR directly from cultured cells[e.g., for validation of small interfering ribonucleic acid (siRNA)-mediated geneknockdown] to speedup development of biopharmaceuticals.

5.2Potential of Real-Time RT-PCR in Biopharmaceutical Development

Many costly steps need to be undergone before a biopharmaceutical can be releasedonto the market. This process can be generally segmented into the drug discoveryphase and the drug development phase. Drug discovery comprises steps such astarget identification, target validation, compound screening, and lead selection andoptimization. Drug development starts with a proof of concept and goes frompreclinical to clinical phases, which are conducted to determine drug safety,tolerability, and efficacy. Drug discovery and development can take more than 10years and is associated with enormous financial investments. It is therefore essentialto reduce the overall costs of this process by selecting themost promising targets anddrug candidates early in discovery. Thus, there is continuous pressure to improveexisting molecular biology technologies to help streamline the overall discoveryprocess, allowing early elimination of false-positive candidates and enablingResearch and Development (R&D) resources to focus on the most promisingcandidates.Nowadays, real-time RT-PCR has become an indispensable tool in drug discovery

and development. The early discovery stages aim to determine how a disease iscaused at the molecular level, leading to initial gene targets that are assumed to playa role in establishing and/or maintaining a disease state. Here, microarray-basedtarget identification plays a central role. However, since microarrays can besusceptible to a great degree of variability [1–3], real-time RT-PCR is often chosento validate initial hits frommicroarray results. In target validation, real-time RT-PCRis used to determine the expression level and the modulation of target genes. Insubsequent discovery and development stages, real-time RT-PCR is also oftenemployed to provide surrogate readouts when studying the pharmacological and

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toxicological effects as well as the efficacy of drug candidates. In addition to its use ingene expression analysis, this versatile technology can be easily used to discover thegenetic basis of a disease by analyzing disease genes for single nucleotide polymor-phisms and mutations.Thus, real-time RT-PCR has become a means to reduce costs significantly and to

increase productivity at early stages of drug development. For example, MillenniumPharmaceuticals reported a 350% gain in productivity in their drug target discoveryprogram after integrating quantitative, real-time RT-PCR into their discoveryprocess [6]. However, the quality of real-time RT-PCR as a validation tool is largelydependent on upstream and downstream methods, such as the preanalyticalmethod as well as the method chosen for data analysis.

5.3Accurate Gene Expression Analysis Depends on Standardized Preanalytical Steps

Preanalytical steps comprise sample collection and storage, sample disruption andhomogenization, RNA isolation, and RNA storage as well as potential shipment ofthe sample or isolated RNA prior to gene expression analysis. Each individual stepcan contribute to the variability of the gene expression profile since samples arecollected from different sources and methods of obtaining and storing samples andisolating RNA may vary significantly. Specific and nonspecific degradation ofcellular RNA and transcriptional induction can be the result of such steps,introducing rapid changes to the transcriptome prior to analysis [7,8] that arenot related to the original in vivo condition (Figure 5.1).Since different transcripts will be affected differently, these changes will lead to

unreliable gene expression analysis. To minimize such artificial changes to the geneexpression pattern, it is essential to stabilize cellular RNA upon sample collection.

Figure 5.1 Drastic changes in gene expression profiles can occur when using conventionaltechniques for RNA purification. These changes are caused by enzymatic degradation of genetranscripts and gene induction and/or downregulation.

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Only a few standardized methods are available to date, such as PAXgene Blood RNATubes (PreAnalytiX) for immediate stabilization of cellular RNA in whole blood(Figure 5.2) or RNAlater products (QIAGEN, Ambion) for tissue samples. CellularRNA from cultured cells is usually well stabilized upon addition of common lysisbuffers used in RNA isolation protocols. These buffers contain denaturing chaot-ropic salts that effectively inhibit RNases [9].RNA isolation methods need to start with efficient disruption and homogeniza-

tion of the biological sample to effectively release total RNA. Disruption andhomogenization are usually carried out in the presence of denaturing reagents,such as phenol-based organic solvents or high concentrations of chaotropic salts thatinhibit endogenous RNases. Disruption methods vary depending on the sampletype. They include the simple addition of lysis buffer to cultured cells or the use of arotor–stator, bead mill, or mortar and pestle for more complex samples. Homoge-nization methods for reducing the overall viscosity of lysates make use of rotor–stators, simple vortexing, or simple spin column–based homogenizers.Subsequent RNA isolation usually comprises either selective capture of messen-

ger RNA (mRNA) or, more commonly, isolation of total cellular RNA. CapturingmRNA to wells of microtiter plates streamlines RNA isolation for higher throughputapplications and also allows solid-phase complementary/copy deoxyribonucleic acid(cDNA) synthesis with subsequent storage of the generated cDNA in a multiwell-plate format ([10]; e.g., TurboCapture mRNA Kits, QIAGEN). Although this simplemethod is advantageous for automated protocols, selective mRNA purification mayintroduce in some cases a bias against mRNAs with shorter poly Aþ tails, affectingquantification of certain very low-abundant transcripts. Other RNA isolation meth-ods rely on the isolation of total RNA and make use of either organic extraction [11]or adsorption of RNA to silica supports, such as membranes or magnetic beads, inthe presence of chaotropic salts and alcohol [12,13]. RNA extraction methods based

Figure 5.2 Blood was collected and RNA waspurified at the time points shown using either(a) standard methods (collection in EDTAtubes, no stabilization, RNA purification using aguanidine-based method) or (b) the PAXgene

Blood RNA system (for RNA stabilization andpurification). The graphs show changes inexpression of 12 genes after blood collectionmeasured using real-time RT-PCR.

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on organic solvents require the use of hazardous reagents and need some handlingexperience from the researcher, and may also contaminate the RNA with residualinhibitors such as phenol, affecting downstream cDNA synthesis. Additionally, lowcontamination by acid-phenol affects absorbance readings [14], which may lead tooverestimation of the actual RNA content of the isolated RNA sample. Such artifactscan be avoided with a simple cleanup step using silica-based purification columns. Itis thereforemore straightforward to use silica-based RNA isolationmethods that useeither silica membranes or silica-coated magnetic particles. They are usually morereliable and offer a simple and fast alternative method that can be readily automatedon robotic instruments with differing throughput capabilities [15]. These methodsalso easily integrate a deoxyribonuclease (DNAse) treatment step during RNAisolation to prevent contamination of the isolated RNA with residual genomicDNA (gDNA). A gDNA removal step can contribute significantly to accuratequantification of gene expression levels. This is because the transcript of interestmay be identical or nearly identical in sequence to pseudogenes in the genome. Also,some genes contain a single exon, which makes design of a transcript-specific assayimpossible. Thus, removal of residual gDNA prior to gene expression analysisprevents overestimating gene expression levels, especially for low-expression genes.

5.4Accuracy of Real-Time RT-PCR Depends on Efficient cDNA Synthesis

The first step in real-time RT-PCR is the reverse transcription of RNA into cDNA, anappropriate starting template forDNA-dependentDNApolymerases such asTaqDNApolymerase. cDNA synthesis is conducted with reverse transcriptases that are isolatedfrom retroviral sources. Some DNA polymerases, including those obtained fromThermus aquaticus or,more commonly, fromThermus thermophilus, are also capable ofreverse transcribing RNA into cDNA. However, they are generally less efficient thanviral reverse transcriptases, sometimes causing lower sensitivity of detection [16]. Theoverall impact of the reverse transcription reaction on the accuracy and reproducibilityof real-time RT-PCR-based gene expression analysis has long been underestimatedand only recently gained more awareness [17]. Reverse transcription can add somevariability to the quantification of transcripts due to many factors that are difficult toproperly control. Firstly, it has been shown that reverse transcriptases can exhibit aninhibitory effect on downstream PCR [18]. Themechanism is largely unknown, but itis likely that the relatively tight attachment of reverse transcriptase to the nucleic acidtemplate makes displacement by Taq DNA polymerase difficult. Secondly, reversetranscriptases are relatively sensitive to template impurities such as alcohols, phenol,and salts carried over from some RNA isolation procedures. In addition, the conver-sion of RNA to cDNA is dependent on the total amount of RNA in the cDNA synthesisreaction. Thirdly, salt in the cDNA synthesis reaction itself can affect downstreamPCR, resulting in shifted CTvalues (Figure 5.3). This makes it necessary to determinehow the volume of reverse transcription reaction used in real-time RT-PCR affects thelinearity of the assay.

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Thus, cDNA synthesis efficacy and therefore accurate representation of transcriptsin the synthesized cDNAmay be largely dependent on the reverse transcriptase used,the secondary structures of the RNA, the starting amount of RNA in the reaction, andthe cDNA synthesis priming strategy used. Also, it should be noted that most reversetranscription chemistries have not been developed to representatively synthesizecDNA for quantitative downstream analysis, but rather to provide full-length repre-sentation of transcripts in the final cDNA pool for construction of cDNA libraries.Consequently, there is still room for improving cDNA synthesis chemistries, tailoredto meet the specific needs of real-time RT-PCR-based gene expression analysis.Sensiscript Reverse Transcriptase (for total RNA amounts less than 50ng; QIAGEN)and Omniscript Reverse Transcriptase (for total RNA amounts greater than 50ng;QIAGEN) have been developed to provide optimal performance from differentstarting amounts of RNA. More recently, the QuantiTect Reverse Transcription Kit(QIAGEN) and the iScript cDNA Synthesis Kit (Bio-Rad) were introduced as the firstdedicated reverse transcription chemistries for real-time RT-PCR.

5.5Integration of Preanalytical Steps Streamlines Gene Expression Analysis

Integration of multiple processing steps reduces variability in gene expressionanalysis. The multiple steps associated with RNA isolation and cDNA synthesis canbe reduced in novel, simple workflows that allow the preparation of cDNA directlyfrom biological samples without any RNA purification (FastLane Cell cDNA Kit,QIAGEN; Cells-to-cDNA Kit, Ambion). General prerequisites for these simplifiedworkflows are a short duration, minimal handling steps, and a uniform temperature

Figure 5.3 Real-time PCR was carried outusing plasmid DNA as template. The volumesof the RT reaction (without template RNA)indicated above were added to the PCR to

determine their effect on amplification. Higherinput volumes lead to increased CT valuesindicating inhibition.

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at all steps to facilitate automation (Figure 5.4). In addition, since the RNApurification step is eliminated, the workflows need to maintain the integrity ofthe transcripts and must not have an inhibitory effect on downstream real-time RT-PCR (Figure 5.5).

Technologies that prepare cDNA directly from biological samples, instead of high-quality RNA for long-term storage, are ideal tools for screening projects based onreal-time RT-PCR, such as validation of siRNA-mediated gene knockdown.In the future, it can be expected that integration of processing steps from sample

preparation and reaction setup to real-time RT-PCR and data acquisition will beavailable as single disposable devices, probably based on microfluidic technologies.

Figure 5.4 Simplified workflow for direct cDNA synthesis for real-time RT-PCR from cell lysates.

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5.6Overview of Methods for Real-Time RT-PCR

5.6.1Chemistries for Amplification and Detection

Real-time RT-PCR allows accurate quantification of starting amounts of transcripts.Fluorescence is measured in each PCR cycle, which greatly increases the dynamicrange of the reaction since the amount of fluorescence is proportional to the amountof PCR product. Detection of PCR products can be conducted using fluorescent dyessuch as SYBRGreen I that bind preferably to double-stranded DNA ([19]; Figure 5.6)or quenched oligonucleotide probes that emit light upon binding to PCR products.Themechanism by which oligonucleotide probes emit light varies depending on thetype of probe. Molecular Beacons, Eclipse probes, and QuantiProbes undergo aconformational change upon binding a PCR product, which causes separation of thefluorophore and quencher [20,21]. TaqMan probes are hydrolyzed by the inherent50 ! 30 exonuclease activity of Taq DNA polymerase, which results in the release offree fluorophore ([5]; Figure 5.7). Other less frequently used types of probe includeLUX primers [22], Amplifluor primers [23], Scorpions primers [24], and fluores-cence resonance energy transfer (FRET) probes [25]. FRETprobes require a specificdetection system that is currently available only on LightCycler real-time PCRinstruments (Roche).A prerequisite for quantification using SYBR Green I is high PCR specificity

since the dye also binds to nonspecific PCR products, which would contribute to

Linearity Cell NumberHepG2

25

2729

31

33

3537

39

41

1x10e54x10e416000640025601024Cell Number (seeded)

CT

FastLane

RNeasy

Figure 5.5 Comparison of a direct cell lysismethod (FastLane Cell cDNA kit; QIAGEN) witha procedure starting with a silica-based columnRNA purification step (RNeasy Mini Kit,QIAGEN) followed by reverse transcription.Various cell numbers were seeded into cell-

culture plate wells and analyzed by real-timePCR for the expression of the GAPDHtranscript. Both methods show similar CT

values over a wide range of input cell numbersindicating no apparent inhibition when usingthe cell lysate directly.

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Figure 5.7 A TaqMan probe binds during thecombined annealing/extension step to thecomplementary target DNA sequence. AsTaq DNA polymerase progresses from theprimer, it hydrolizes the fluorescent probe

with its inherent 50-30 exonuclease activitythereby separating quencher andfluorophore. Without the quenching moietyin close proximity, the liberated dye emitslight upon excitation.

Figure 5.6 Working principle of dsDNA-specificfluorescent dyes used in real-time PCR. Thefluorescent dye SYBR Green I is not bound tosingle-stranded DNA during the denaturationstep. At the annealing step primer binds to thecomplementary DNA sequence and becomes

extended during the extension step by Taq DNApolymerase. SYBR Green I binds preferentially todsDNA, which is required for increased emissionof fluorescence. Therefore, the fluorescent signalis always directly proportional to the amount ofPCR product present in the reaction.

5.6 Overview of Methods for Real-Time RT-PCR j103

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the overall fluorescent signal of the reaction and compromise the accuracy ofquantification. In contrast to SYBR Green I, sequence-specific oligonucleotideprobes detect specific PCR products. However, high PCR specificity is also aprerequisite for accurate quantification when using sequence-specific probessince competition between specific and nonspecific PCR products can compro-mise dynamic range, PCR efficiency, and sensitivity. Both detection chemistriesare to date available as ready-to-use real-time RT-PCR assays that offer theresearcher a time-saving and cost-effective alternative to self-designed assays.QIAGEN introduced in 2005, along with its genomewide range of siRNAsgenomewide QuantiTect Primer Assays, for use in SYBR Green-based real-time RT-PCR. The assays cover all transcripts from the genomes of human,mouse, rat, and other species, and are compatible with two-step and one-step RT-PCR on all real-time PCR instruments. Gene expression assays based on TaqManprobes are available from Applied Biosystems, and are recommended for use intwo-step RT-PCR on real-time PCR instruments from the same company. Inter-estingly, it is commonly observed that SYBR Green-based real-time RT-PCR assaysoften provide lower CT values than probe-based assays. This is because manySYBR Green molecules bind to each PCR product, while only one sequence-specific probe binds to each PCR product. Thus, SYBR Green detection enablesgreater fluorescence per PCR product.

5.6.2Choosing Between Two-Step and One-Step RT-PCR

There are two methods of conducting real-time RT-PCR: two-step RT-PCR and one-step RT-PCR, the latter also known as one-tube RT-PCR. With two-step RT-PCR,RNA is first reverse transcribed into cDNA using oligo-dT primers, randomoligomers, or gene-specific primers. An aliquot of the reverse transcription reactionis then used in real-time PCR. Use of oligo-dT primers or random oligomers forreverse transcription means that several transcripts from one cDNA sample can beanalyzed by real-time PCR.In one-step RT-PCR, both reverse transcription and PCR take place in the same

reaction vessel, with the reverse transcription step preceding the PCR step. This fastprocedure enables rapid processing of multiple samples and is easy to automate.The reduced amount of handling results in high reproducibility from sample tosample and minimizes the risk of cross-contamination. Real-time PCR chemistriesfor both methods are available from several vendors, including Applied Biosystems,Invitrogen, Roche, and QIAGEN.

5.6.3Multiplexing Increases Accuracy and Throughput of Real-Time RT-PCR

Multiplex, real-time RT-PCR brings the advantages of real-time RT-PCR to anotherlevel. Multiplex, real-time RT-PCR not only increases throughput by combiningseveral assays in a single reaction vessel, but also reduces reagent costs and

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conserves precious sample material when this is limited. Furthermore, multiplex,real-time RT-PCR adds another level of reliability: reaction variability is signifi-cantly reduced by coamplification of internal controls, such as so-called house-keeping genes, in the same reaction well. Thus, variability due to separatepipetting steps and well-to-well variation within the microtiter plate are elimi-nated. Additionally, multiplex PCR allows the use of internal controls, which canbe added to the reaction at a defined copy number (e.g., in pathogen detection toserve as an internal control to identify false-negative reactions). However,although most real-time PCR instruments are capable of multiplex analysis,the need for long and tedious optimization means that multiplex, real-timeRT-PCR is currently not widely used.

5.6.4Common Problems in Optimizing Multiplex, Real-Time RT-PCR

Multiplex, real-time RT-PCR has been a challenge since it usually requires extensiveoptimization, which compromises the cost savings and increase in throughputpromised by this technology. Several factors contribute to the inherent difficulty inoptimizing multiplex assays: (a) different PCR products compete for reactionresources such as deoxyribonucleotide triphosphates (dNTPs) andDNApolymerase.These resources can become limiting during the course of the reaction, usuallyaffecting amplification of less abundant transcripts; (b) more abundant transcriptsare preferentially amplified; (c) amplification of nonspecific PCR products due tounspecific primer extension also consumes precious reaction resources; (d) primerand probe hybridization efficiencies may not be the same for all targets; and (e) acomprehensive range of compatible fluorescent dyes and quenchers has not yetbeen identified for the various real-time PCR instruments.All these factors contribute to the variability of multiplex assays and strongly affect

the reaction kinetics, destroying the quantitative nature of the amplificationreactions that needs to be preserved throughout the multiplex reaction. Figure 5.8illustrates the typical effects on a real-time RT-PCR assay when two amplificationreactions are combined in a single reaction vessel.Figure 5.8a shows a real-time RT-PCR assay for the human HSP89 gene with

various template dilutions (10 ng to 10 pg of cDNA). Figure 5.8b shows the sameassay again, but with each template dilution spiked with 106 copies of an additionaltarget gene for coamplification. This simulates the presence of a highly expressedgene with a proportionally steadily decreasing number of HSP89 transcripts.As a result of the coamplification, CT values shift toward higher cycle numbers,

and low template amounts are not detected and cannot be quantified (Figure 5.8b).Optimization strategies for multiplex assays commonly involve increasing poly-

merase, nucleotide, and magnesium concentrations in order to provide the assaywith sufficient reaction resources [26]. However, this has the disadvantage ofincreasing the probability of generating nonspecific PCR products, which thenalso compete for reaction resources and therefore lower PCR efficiency andsensitivity. Often, adjustment of the magnesium concentration is also necessary

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to improve hybridization of primers and probes that do not bind with comparableefficiency to their target cDNA. Another commonly recommended optimizationstrategy is the limitation of the primer concentration for more abundant transcripts([27]; User Bulletin #5, Applied Biosystems, 1998). This strategy often yieldssatisfactory results by delaying competition between different PCR products untilthe less abundant transcripts are efficiently amplified. However, primer limitation

(a)

(b)

Figure 5.8 (a) Gene expression analysisusing TaqMan probes specific for the humanHSP89 gene starting from 10 ng, 1 ng,100 pg, and 10 pg cDNA. (b) Geneexpression analysis using TaqMan probes

specific for the human HSP89 gene startingfrom 10 ng, 1 ng, 100 pg, and 10 pg cDNA.Additionally, each reaction contains 106copies of a GAPDH-encoding plasmid DNAas coamplification target.

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must be tested for each primer/probe combination, and care should be taken not toimpact the efficiency of the respective amplification reactions.

5.6.5Novel Chemistries for Standardization of Multiplex, Real-Time RT-PCR

Multiplex, real-time RT-PCR has long been considered to be impractical due to theneed for extensive optimization. Furthermore, comparability of data is still ques-tionable because data are generated on different real-time PCR instruments usingreagents specifically optimized for these instruments. This situation can be over-come by a multiplex, real-time PCR reagent that has been developed by QIAGEN(QuantiTect Multiplex PCR and RT-PCR Kits). This novel reagent yields comparableresults on different real-time PCR instruments without the need for extensiveoptimization, promising standardization in multiplex assays. This reagent is basedon two innovations. The first is a chemically inactivated hot start DNA polymerasethat is reactivated by temperature rather than by pH. This provides a more stringenthot start than antibody-mediated hot start procedures and also enables amplificationreactions to take place at an optimal pH. The second innovation is a dedicatedreaction buffer that increases PCR specificity due to special ion combinations and,more importantly, the inclusion of a synthetic polymer that increases hybridizationefficiency of suboptimal primers and probes by inducing macromolecular crowding(Figure 5.9).Macromolecular crowding increases the hybridization kinetics of primers and

probes, which helps to reduce differences in amplification and detection efficiencyof the various targets in a multiplex reaction. The reagent allows amplification of allPCR products in a multiplex reaction with the same PCR efficiencies as in thecorresponding single-amplification reactions, resulting in comparable sensitivities.High throughput and high precision can be achieved in gene expression analysis intwo-step and one-step RT-PCR procedures (Figures 5.10 and 5.11). Thus, this pre-optimized reagent that is available for standardized real-time multiplex RT-PCRmakes efficient use of the fluorescence detection capabilities of today’s real-timePCR instruments.

Figure 5.9 (a) NHþ4 ions prevent

nonspecific primer annealing to thetemplate. (b) Synthetic factor MP increasesthe local concentration of primers andprobes at the template. Together with Kþ

cations, synthetic factor MP stabilizesspecifically bound primers and probes,allowing efficient coamplification anddetection of several primer/probe pairs inmultiplex reaction.

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5.7Developments in Real-Time PCR Instrumentation

New technological developments have led to rapid changes in real-time PCRinstrumentation over the past few years. Instrument sizes have shrinked signifi-cantly and detection systems based on lasers have been widely replaced by systemsusing other fluorescence excitation sources such as halogen lamps and lightemitting diodes (LEDs), allowing better multiplexing capabilities. A range ofsuppliers provide a broad selection of real-time PCR cyclers that allow high-throughput analysis in 384-well format (e.g., ABI PRISM 7900 and LightCycler 480),multiplex analysis (e.g., RotorGene Q, Applied Biosystems 7500, LightCycler 2.0,LightCycler 480, and Mx3005P), or high-speed analysis through fast cycling (e.g.,LightCycler, SmartCycler, and Applied Biosystems 7500). Overall costs for real-timePCR instrumentation are falling, enabling most laboratories to invest in thistechnology. Other developments can be foreseen in the coming years: reactionvolumes will further decrease to allow more affordable high-throughput geneexpression analysis. Hardware developers such as BioTrove have already demon-strated the feasibility of real-time PCR chips that carry several thousand nanoliter-

Figure 5.10 Serial dilutions (1/4) of a templatemix containing a target and an endogenouscontrol were analyzed in triplicate by real-time,duplex PCR on the ABI PRISM 7900. Either theQuantiTect Multiplex PCR Kit from QIAGEN(main pictures) or a kit from another supplier(insets) was used. The target was detectedusing an FAM-labeled TaqMan probe and the

endogenous control using a VIC-labeledTaqMan probe. The QuantiTect Kit providedminimal variation within replicates, enablingdifferent template amounts to be clearlydistinguished. Data kindly provided by DrVirginia M. Litwin, Bristol-Myers SquibbCompany, Pennington, NJ, USA.

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sized reaction wells per chip. These chips enable the analysis of gene expressionlevels of thousands of transcripts in parallel with a higher dynamic range andprecision compared with today’smicroarray platforms. Thus, it may be expected thatsuch technological developments will eventually merge the capabilities of both real-time PCR and microarray analysis: parallel gene expression analysis of largenumbers of transcripts combined with highly sensitive and linear quantification.Another trend is the development of more integrated systems that require less userinteraction for sample preparation, reaction setup, and data acquisition. Examples ofsuch development are lab-in-a-tube technology from IQuum, which promises theability to carry out both sample preparation and real-time PCR in a single tube, andthe GeneXpert system from Cepheid.

5.8The Need for Better Standardization of Quantification Methods

While recent developments in instrumentation and reagents have improved thethroughput and the ease-of-use of real-time PCR, there is still a need for betterstandardization of methods for relative quantification. With relative quantification,the amount of a target molecule is normalized by dividing it by the amount of acontrol molecule in the same sample. Various types of control molecules have beenproposed, including gDNA, artificial internal control transcripts, and, most

Figure 5.11 Triplex, real-time, one-step RT-PCR was performed using the QuantiTectMultiplex RT-PCR Kit (QIAGEN) and TaqManprobes. The template was 20 ng total RNA fromthe Burkin’s lymphoma cell line Ramos.Reactions were performed in triplicate. 28SrRNA was detected using a HEX-labeled probe.POLD3 (accessory subunit of DNA polymerase

delta 3) was detected using a FAM-labeledprobe. CDK2 (cell cycle-dependent kinase 2)was detected using a Cy5-labeled probe. Forcomparison, the targets were also quantified bysingle, real-time, one-step RT-PCR (blackcurves). Curves for triplex PCR and single PCRsoverlap, demonstrating comparableamplification (i.e., equivalent CT values).

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commonly, internal reference genes such as ribosomal RNA transcripts or otherinternal reference transcripts [28]. In gene expression analysis experiments, relativequantification can be used, for example, to compare the differential expression of agene in different tissues. Reliable comparison depends on the use of an internalreference gene whose expression level remains unchanged under various exper-imental conditions. However, many researchers continue to use the most popularhousekeeping genes, such as b-actin, glyceraldehyde-3-phosphate dehydrogenasegene (GAPDH), or ribosomal RNA (rRNA), as internal reference genes withoutvalidating whether their expression levels vary or not. It is known for over twodecades that transcript levels of housekeeping genes do change depending onexperimental or environmental conditions [29–32]. Consequently, using the wronghousekeeping gene for relative quantification may lead to significant under- oroverestimation of the expression of the gene of interest.Inaccuracies in quantifying gene expression by real-time PCRmay also be caused

by the particular method used for relative quantification. The most popular is the so-called DDCT method [33], which relies on direct comparison of CT values withoutcreating standard curves for quantification of the gene of interest. An example of thismethod is shown in Table 5.1.Success with theDDCTmethod depends on comparable amplification efficiencies

for the gene of interest and the internal reference gene, independent of the inputamount of cDNA or RNA in the real-time reaction. This method can yield inaccuratequantitative results if the PCR efficiencies of the gene of interest and the internalreference gene are not the same. Since the error of quantification is a function ofPCR efficiency and cycle number, the error becomes greater for lower-expressedgenes (i.e., genes that give higher CT values). Recently, software tools such as theRelative Expression Software Tool (REST; [34]) have been introduced. They cancorrect for efficiency-related errors and prove useful for accurate quantification ofgene expression levels.However, determining the amplification efficiency for each real-time PCR assay

may not be practical, especially if a large number of genes need to be analyzed withina short time frame. Standardized, commercially available real-time PCR assays andchemistries do not eliminate the need for assay validation, but do lower the overallrisk of poor quantitation results. Ready-to-use primer pairs or primer-probe sets are

Table 5.1 Calculation of TNF expression levels in Jurkat cells using the DDCT method.

SampleAverageCT TNF

Average CT

HPRTDCT TNF-HPRT

DDCT DCT -DCT

calibrator

Expression ofTNF composed tocalibrator (2�DDCT)

Untreated(calibrator sample)

36.5 22.8 13.7 0 1

PMA 31.0 23.1 7.9 �5.8 55.7

Jurkat cells were used untreated or treated with phorbol 12-myristate 13-acetate (PMA). Total RNA wasisolated and after real-time RT-PCR the relative amounts of target and reference RNAwere determined.

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available from vendors such as Applied Biosystems and QIAGEN. They are designedaccording to highly stringent design parameters, are often pretested for basicvalidation parameters such as PCR ef fi ciency, and are subjected to extensive qualitycontrol. For example, QIAGEN offers a genomewide range of matching siRNAs andreal-time RT-PCR gene expression assays for human, mouse, and rat (www.qiagen.com/GeneGlobe), suitable for drug discovery and target validation. In addition,genomewide real-time RT-PCR gene expression assays are available for otherorganisms, including dog, chicken, drosophila, and Arabidopsis.

5.9Conclusion and Outlook

Quantitative, real-time PCR has become the standard method for accurate geneexpression analysis over the past decade. In combination with microarrays used intarget discovery, real-time PCR has become an indispensable method to validate andaccurately quantify changes in gene expression levels, providing significant cost-savings in the drug development process. The latest real-time PCR instrumentationand reagents enable increased throughput and quantification accuracy throughhigher-density reaction plate formats and multiplexing. Eventually, both real-timePCR and microarray platforms may merge, resulting in a high-throughput, high-density method with the unparalleled dynamic range and sensitivity of real-timePCR. Further integration of workflows such as sample preparation and real-timePCR together with ready-to-use off-the-shelf real-time PCR assays will help tofurther standardize gene expression analysis.However, great care must be taken when planning experiments, since many

environmental and experimental parameters can significantly affect the outcome ofa quantification experiment. Currently, the important issues are sample collectionand stabilization, where instantaneous freezing of the gene expression patternwithin the sample is crucial, as well as validation of normalization and quantificationmethods, which still await improvements to enable standardized gene expressionanalysis. This again will boost the development process of biopharmaceuticalsconcerning the early choice of the right candidate and hence speeding up the overalltime to market.

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