quantitative proteomic analysis of induced …...jung-il chae1, dong-wook kim1, nayeon lee†1,...

Biochem. J. (2012) 446, 359–371 (Printed in Great Britain) doi:10.1042/BJ20111495 359

Quantitative proteomic analysis of induced pluripotent stem cells derivedfrom a human Huntington’s disease patientJung-Il CHAE*1, Dong-Wook KIM*1, Nayeon LEE†1, Young-Joo JEON*, Iksoo JEON†, Jihye KWON†, Jumi KIM†, Yunjo SOH*,Dong-Seok LEE‡, Kang Seok SEO§, Nag-Jin CHOI¶, Byoung Chul PARK‖, Sung Hyun KANG‖, Joohyun RYU‖, Seung-Hun OH†,Dong Ah SHIN**, Dong Ryul LEE†, Jeong Tae DO†, In-Hyun PARK††‡‡, George Q. DALEY†† and Jihwan SONG†2

*Department of Oral Pharmacology, School of Dentistry and Institute of Dental Bioscience, BK21 project, Chonbuk National University, Jeonju 651-756, Korea, †CHA Stem CellInstitute, Department of Biomedical Science, CHA University, Seoul 135-081, Korea, ‡College of Natural Sciences, Kyungpook National University, Daegu 702-701, Korea, §Departmentof Animal Science and Technology, Sunchon National University, Suncheon 540-742, Korea, ¶Department of Animal Science, College of Agricultural and Life Science, ChonbukNational University, Jeonju 651-756, Korea, ‖Medical Proteomics Research Center, KRIBB, Daejeon 305-333, Korea, **Department of Neurosurgery, Yonsei University College ofMedicine, Seoul, Korea, ††Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, U.S.A., and ‡‡Department of Genetics, YaleUniversity School of Medicine, New Haven, CT 06520, U.S.A.

HD (Huntington’s disease) is a devastating neurodegenerativegenetic disorder caused by abnormal expansion of CAG repeats inthe HTT (huntingtin) gene. We have recently established two iPSC(induced pluripotent stem cell) lines derived from a HD patientcarrying 72 CAG repeats (HD-iPSC). In order to understandthe proteomic profiles of HD-iPSCs, we have performedcomparative proteomic analysis among normal hESCs (humanembryonic stem cells; H9), iPSCs (551-8) and HD-iPSCs atundifferentiated stages, and identified 26 up- and down-regulatedproteins. Interestingly, these differentially expressed proteins areknown to be involved in different biological processes, such asoxidative stress, programmed cell death and cellular oxygen-associated proteins. Among them, we found that oxidative stress-related proteins, such as SOD1 (superoxide dismutase 1) and Prx(peroxiredoxin) families are particularly affected in HD-iPSCs,implying that HD-iPSCs are highly susceptible to oxidative stress.

We also found that BTF3 (basic transcription factor 3) is up-regulated in HD-iPSCs, which leads to the induction of ATM(ataxia telangiectasia mutated), followed by activation of the p53-mediated apoptotic pathway. In addition, we observed that theexpression of cytoskeleton-associated proteins was significantlyreduced in HD-iPSCs, implying that neuronal differentiation wasalso affected. Taken together, these results demonstrate that HD-iPSCs can provide a unique cellular disease model system tounderstand the pathogenesis and neurodegeneration mechanismsin HD, and the identified proteins from the present study mayserve as potential targets for developing future HD therapeutics.

Key words: apoptosis, cytoskeleton-associated proteins, Hunt-ington’s disease, induced pluripotent stem cell (iPSC), oxidativestress, proteomic analysis.

INTRODUCTION

HD (Huntington’s disease) is a devastating autosomal-dominantneurodegenerative disorder, caused by abnormal expansion ofCAG (cytosine-adenine-guanine) repeats in exon 1 of theHtt (huntingtin) protein-encoding HTT gene [1]. Eventually,these abnormal expansions will be translated into poly(Q)s(polyglutamines) in the N-terminus of the Htt protein, whichform aggregates in the cytoplasm and nucleus. Notably, in thebrain of a HD patient, the aggregated N-terminal fragmentsof elongated Htt protein are located as neuronal intranuclearinclusions and dystrophic neuritis in cortex and striatum [2]. Itis known that several factors are involved in pathogenesis ofHD, including excitotoxicity, impaired energy metabolism andoxidative stress [3]. People carrying the HD mutation graduallydevelop personality changes, involuntary movements, weight lossand eventually dementia. There are currently no cures for HD.

To understand the pathogenesis and to develop therapeuticsin HD, various model systems have been developed that includetransgenic mice carrying the normal or mutant htt gene, fibroblastsfrom HD patients or immortalized neurons expressing a mutantN-terminal fragment of human HTT gene [2]. Previously, wehave isolated two HD-iPSC (induced pluripotent stem cell; HDand HD2) lines derived from the skin fibroblast of a juvenile HDpatient carrying 72 CAG repeats [4], which was generated byretroviral infection of four pluripotency factors {Oct4 (Octamer-binding protein 4), Sox2 [SRY (sex-determining region Y)-box2], Klf4 (Kruppel-like factor 4) and c-Myc}. Compared withtransgenic animal models or immortalized cell lines, it is believedthat the iPSC model system can represent the pathology ofHD better. Moreover, the pluripotent nature of HD-iPSCs canprovide an unlimited supply of cells for biochemical studies, drugscreening, cell therapy and so on. In order to be used in celltherapy, it will be essential that the mutation of the HTT gene

Abbreviations used: ATM, ataxia telangiectasia mutated; Bid, BH3-interacting domain death agonist; BTF3, basic transcription factor 3; Chk2, checkpointkinase 2; Cfl-1, Cofilin-1; Cytc, cytochrome c; DAPI, 4′,6-diamidino-2-phenylindole; 2-DE, two-dimensional electrophoresis; DM, differentiation medium;DSB, double-strand break; Facn-1, Fascin-1; Gpx1, glutathione peroxidase 1; GST, glutathione transferase; H2A.x, histone H2A.x; HD, Huntington’sdisease; hESC, human embryonic stem cell; hiPSC, human iPSC; Htt, huntingtin; iPSC, induced pluripotent stem cell; Klf4, Kruppel-like factor 4; LC-MS/MS, liquid chromatography tandem MS; MAP2, microtubule-associated protein 2; NES, neuroectodermal sphere; NF-κB, nuclear factor κB; PARP,poly(ADP-ribose) polymerase; p-ATM (S1981), ATM phosphorylated at Ser1981; Prx, peroxiredoxin; qRT-PCR, quantitative real-time PCR; ROS, reactiveoxygen species; Sept, septin; SOD1, superoxide dismutase 1; Stmn-1, Stathmin-1; tBid, truncated Bid; TBST, 10 mM Tris/HCl (pH 7.4), 140 mM NaCl and0.1% Tween-20; TUNEL, terminal deoxynucleotidyltransferase-mediated dUTP nick-end labelling.

1 These authors contributed equally to this study.2 To whom correspondence should be addressed (email [email protected]).

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360 J.-I. Chae and others

in HD-iPSCs should be corrected prior to grafting. For clinicalapplication, it will be also important to generate transgene-freereprogrammed iPSC under GMP (Good Manufacturing Practice)conditions.

In the present study, we employed a proteomic approach usingtwo previously established HD patient-derived iPSC lines (HD-iPSCs, HD and HD2) [4] to identify and address the differences ofHD-iPSCs in protein expression profiles, compared with normalhESCs (human embryonic stem cells; H9) and iPSCs (551-8)at undifferentiated stages. The proteome techniques used arevery powerful tools to understand the mechanisms of biologicalprocess. However, there are only a few studies reporting proteomicanalyses on iPSCs, and no study has been reported regardingHD-iPSCs. To identify and characterize the changes of proteomeprofiles in HD-iPSCs, when compared with those of H9 and551-8 cells, we carried out high-throughput image analysis,followed by LC-MS/MS (liquid chromatography tandem MS) onthe differentially expressed proteins in each sample. We foundthat the differentially expressed proteins are key regulators inoxidative stress, DNA damage and expression of cytoskeleton-associated proteins. As a result, it is likely that HD-iPSCs exhibitincreased apoptotic cell death and reduced neuronal differenti-ation, compared with H9 and 551-8 cells. Our results indicate thatHD-iPSCs are highly susceptible to oxidative stress, followed byapoptotic cell death. Therefore HD-iPSCs can serve as a uniquecellular disease model system to understand the pathogenesis andneurodegeneration mechanisms in HD. Moreover, the identifiedproteins from the present study can provide useful clues on thepotential targets for developing future HD therapeutics.

MATERIALS AND METHODS

Culture and neuronal differentiation of H9, 551-8 and HD cells

hESCs (H9), normal iPSCs (551-8) and HD-iPSCs (HD andHD2 cells) were cultured and maintained according to themethods described previously [4–6]. Neuronal differentiation wasinduced by co-culturing the cells with PA6 stromal cells [6].To do this, undifferentiated H9, 551-8 and HD colonies weremechanically dissected and transferred on to freshly preparedPA6 cells in DM (differentiation medium)-PA6, and 4 dayslater, KO-SR (knock-out serum replacement) in DM-PA6 wasreplaced by N2 supplements. In the following ∼11–13 days,definitive neural rosette-like structures containing neuroepithelialcells were formed, which were mechanically detached andtransferred on to a non-sticky Petri dish for suspension culturefor 6 days to form neurospheres. To differentiate into matureneurons, neurospheres were directly plated on to PLO/FN(polyornithine and fibronectin)-coated dishes and were culturedfor one week in DM supplemented with 20 ng/ml BDNF (brain-derived neurotrophic factor; R&D Systems) in the absence ofbFGF (basic fibroblast growth factor). To quantify the efficiencyof neuronal differentiation, the number of colonies forming neuralrosette-like structures out of the total number of colonies wascounted. The areas containing neural rosette-like structures outof the entire areas in each colony were measured using ImageJ(http://rsbweb.nih.gov/ij/).

Immunocytochemistry

To analyse the marker expression of H9, 551-8, HD andHD2 cells, the following primary antibodies were used: anti-(human-specific nuclei) (1:200 dilution, Chemicon), anti-(human-specific mitochondria) (1:200 dilution, Chemicon), anti-(typeIII β-tubulin) (Tuj1) (1:500 dilution, Chemicon), anti-MAP2(microtubule-associated protein 2; 1:200 dilution, Chemicon),

anti-Prx (peroxiredoxin) 1 (1:100 dilution, Santa Cruz Biotech-nology), anti-Prx2 (1:100 dilution, Santa Cruz Biotechnology),anti-Prx6 (1:100 dilution, Santa Cruz Biotechnology), anti-Cfl-1(Cofilin-1; 1:500 dilution, Abcam), anti-Stmn-1 (Stathmin-1;1:100 dilution, Santa Cruz Biotechnology), anti-Facn-1 (Fascin-1; 1:100 dilution, Santa Cruz Biotechnology) and anti-Sept(septin)-2 (1:100 dilution, Santa Cruz Biotechnology). Secondaryantibodies used were goat anti-(mouse IgG)-conjugated AlexaFluor® 555 (1:200 dilution, Molecular Probes), goat anti-(rabbitIgG)-conjugated Alexa Fluor® 488 (1:200 dilution, MolecularProbes) and goat anti-(mouse IgM)-conjugated Alexa Fluor®

555 (1:200 dilution, Molecular Probes). The staining patternswere examined and photographed using a confocal laser-scanningmicroscope imaging system (LSM510, Carl Zeiss).

Western blot analysis

Aliquots (30 μg) of protein extracts from H9 hESCs, 551-8 hiPSCs (human iPSCs), and HD- and HD2-iPSCs atundifferentiated or differentiated stages were loaded and separatedby SDS/PAGE (12 and 15% gels). The proteins were thentransferred on to a nitrocellulose membrane, which was blockedfor 2 h at 25 ◦C with 3% BSA in TBST [10 mM Tris/HCl(pH 7.4), 140 mM NaCl and 0.1 % Tween-20] and incubated withpolyclonal antibodies against SOD1 (superoxide dismutase 1),Prx1, Prx2, Prx6 (Ab Frontier), BTF3 (basic transcription factor 3;Santa Cruz Biotechnology), phospho-ATM (ataxia telangiectasiamutated), phospho-H2A.x (histone H2A.x; Millipore), phospho-p53, Bid (BH3-interacting domain death agonist; cleavedform), caspase-9, caspase-3 (cleaved form), caspase-7 (cleavedform), PARP [poly(ADP-ribose) polymerase; cleaved form; CellSignaling Technology] and β-actin (Santa Cruz Biotechnology)at 4 ◦C overnight. After washing with TBST, the membraneswere incubated with secondary antibodies for 1 h at 37 ◦Cand visualized by enhanced chemiluminescence (AmershamBiosciences). The membranes were then scanned and the signalintensity of each band was determined using LAS 3000 (Fuji).The relative protein levels in each sample were normalized to thelevel of β-actin.

RNA extraction and qRT-PCR (quantitative real-time PCR)

Total RNA was isolated from H9 hESCs, 551-8 hiPSCs, HD andHD2 cells using TRIzol® reagent (Invitrogen). RNA (1 μg) wasreverse-transcribed into cDNA. qRT-PCR primers were targetedagainst BTF and ATM. Quantification of genes was performedusing SYBR Green gene expression assays (Eppendorf Realplex2). PCR amplification was generated using gene-specific primers(Table 1). The level of target gene expression was determined bythe comparative Ct method, whereby the target is normalized toendogenous β-actin. The Ct value is the cycle number at which thefluorescence level reaches threshold. The �Ct value is determinedby subtracting the Ct value of the β-actin control from the Ct valueof the target gene [�Ct = Ct(target) − Ct(β-actin)]. This relativevalue of target to endogenous reference is described as the fold ofβ-actin = 2−�Ct .

Table 1 Primer sets used in qRT-PCR analysis

Target gene Primer (5′→3′)

BTF3 Forward, TCTCCTTAAAGAAGTTAGGGGTAAACAReverse, CGGCCAGTCTCCTTAAACTAGTCA

ATM Forward, AGCTGTCTCCATTACTGATGATACTReverse, TCCGTAAGGCATCGTAACACATA


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Proteomic analysis of Huntington’s disease iPSCs 361

Figure 1 Morphological characteristics and neuronal differentiation of H9, 551-8, HD and HD2 cells

(A) Experimental scheme showing the culture conditions for maintaining undifferentiated cells, as well as the step-wise differentiation procedures into neuronal lineages. (B) Representativemorphology at undifferentiated (Stage 1), neural rosette (Stage 3), neurosphere (Stage 4) and mature neuron (Stage 5) stages in H9, 551-8, HD and HD2 cells. AA, ascorbic acid; BDNF, brain-derivedneurotrophic factor; bFGF, basic fibroblast growth factor; DMEM, Dulbecco’s modified Eagle’s medium; GMEM, Glasgow minimum essential medium; KO-SR, knock-out serum replacement; MEF,mouse embryonic fibroblasts; PLO/FN, polyornithine and fibronectin. Scale bar = 100 μm.

TUNEL (terminal deoxynucleotidyltransferase-mediated dUTPnick-end labelling) assay

H9, 551-8, HD and HD2 cells at undifferentiated and differen-tiated neuronal stages were fixed in 4% paraformaldehyde inPBS for 20 min at room temperature (25◦C). After three washesin PBS for 10 min, they were stained using the In Situ CellDeath Detection Kit (Roche) according to the manufacturer’sprotocol. All of the samples were counterstained with DAPI (4′,6-diamidino-2-phenylindole). The number of TUNEL-positive cellswere counted and processed for statistical analysis.

Computational pathway analysis

The dataset was uploaded to the MetaCoreTM software (GeneGo)to elucidate regulatory pathway in HD-iPSCs. The differentiallyexpressed proteins were mapped in the pathway using thetranscription regulation algorithm in the MetaCoreTM software,and the molecular relationships among genes were graphicallyrepresented.

RESULTS

Morphological characteristics and neuronal differentiationof H9, 551-8 and HD cells

In order to study the proteomic profiles of HD-iPSCs, we initiallycarried out comparative morphological analyses among HD-iPSCs, H9 hESCs (control) and 551-8 hiPSCs (normal iPSCcontrol), in which different stages of neuronal differentiationwere compared in each cell line simultaneously. We also includedanother HD-iPSC line, called HD2, which was derived from thesame HD patient simultaneously when HD-iPSC was established.Since HD cells exhibited very similar properties with HD2cells, considering the limitation of sample numbers, our initialproteomic analysis was carried out using HD cells alone, althoughneuronal differentiation studies, as well as validation studies usingdifferentially expressed marker proteins were performed on bothHD-iPSC lines (see below).

Figure 1(A) outlines our five-stage differentiation protocol,which involves undifferentiated cells maintained on mouseembryonic fibroblasts (Stage 1), co-culture of undifferentiated



Figure 2 Efficiency of neuronal differentiation in H9, 551-8 and HD cells at Stage 5

(A) Immunocytochemical staining using an antibody against MAP2 showing the morphological features of neuronal cells at Stage 5 in each cell. (B) Histogram showing the percentage of MAP2-positive neurons, which have been counterstained with DAPI. (C) Sigma plot diagram showing the distribution and average length of neurites in MAP2-positive neurons. The significance of differenceswas evaluated by one-way ANOVA (SAS version 8.0). *P < 0.05, **P < 0.001. Scale bar = 50 μm.

cells with PA6 stromal cells (Stage 2), and isolation ofneural rosettes (Stage 3), followed by neurosphere formation insuspension culture (Stage 4). Afterwards, we further differentiatedthe neurospheres into mature neurons (Stage 5). Figure 1(B)shows morphological characteristics of each cell line at variousdifferent stages of neuronal differentiation, in which, althoughthe undifferentiated stages exhibit the highest similarity, somevariable morphological differences were detected in each cell lineat later stages.

We have recently shown that the initial neural-formingefficiency of HD and HD2 at Stage 3 was lower, comparedwith normal hESC (H9) and iPSC (F5) lines [7]. In the presentstudy, when the number of colonies forming neural rosette-like structures was counted out of total number of colonies atStage 3, we found that H9 forms the highest percentage ofrosette-forming efficiency (86.60 +− 1.83%), and that F5, HDand HD2 cells exhibit significantly reduced rosette-formingefficiency (18.28 +− 0.81%, 32.97 +− 1.90% and 26.82 +− 1.57%respectively) [7]. In the present study, we observed that thepercentage of rosette-forming colonies of 551-8 cells was29.32 +− 1.56%. Similarly, we also showed that the total areasof rosettes to be formed in each colony at Stage 3 werehighest in H9 (71.37 +− 1.67%) and were reduced in F5, HD andHD2 cells (27.32 +− 9.29%, 42.09 +− 8.53% and 31.61 +− 3.56%respectively) [7]. We also observed that the percentage of rosette-forming areas in 551-8 cells was 32.61 +− 3.322%, indicating theefficiency of initial neuronal differentiation in HD-iPSCs at Stage3 is significantly lower than in H9 cells and slightly higher thanin F5, 551-8 and HD2 cells. As for the reduced efficiency ofneuronal differentiation in 551-8 or F5 cells compared with HDcells, we speculate that this might be due to the residual expression

of the KLF4 transgene that was used in making the iPSCs, whichwas shown to control the expression of miR-371-3 [8]. It is alsopossible that HD-iPSC lines can be influenced by the expressionof the KLF4 transgene, but their proteomic expression profiles andthe subsequent validation results clearly indicate that HD-iPSClines are intrinsically different from 551-8 or F5 cells.

In the present study, we extensively examined the efficiencyof neuronal differentiation at Stage 5, in which neurosphereswere attached to form neurite outgrowth. In this case, sinceonly the selected population of neural rosette-like structures wasallowed to form neurospheres, we speculated that the efficiencyof mature neuron formation would be comparable unless there aresignificant intrinsic differences among each cell line. To comparethe extent of neuronal differentiation and neurite outgrowth ineach cell line, we immunostained the Stage 5 samples using anantibody against MAP2 (Figure 2A) and counted the total numberof MAP2-positive cells (Figure 2B). As expected, we foundthat H9 forms the highest percentage of MAP2-positive neurons(83.50 +− 1.62%). However, unlike Stage 3, 551-8 forms moreMAP2-positive neurons than HD and HD2 cells (50.95 +− 1.81%,43.33 +− 2.19% and 36.70 +− 2.60% respectively) at Stage 5. Nomeasurements were made for F5 cells. We also measured theaverage length of neurites in MAP2-positive neurons (Figure 2C),and found that the extent of neuronal differentiation and neuriteoutgrowth were significantly reduced in both HD and HD2lines (352.88 +− 7.97 μm and 336.99 +− 18.06 μm respectively),compared with H9 or 551-8 cells (506.86 +− 13.29 μm and417.31 +− 16.59 μm respectively). Interestingly, we observed thatthe extent of neuronal differentiation and neurite outgrowth in551-8 cells was lower than in H9 cells, but higher than in HD andHD2 cells (Figures 2B and 2C).



Proteome analysis of differentially expressed proteins amongH9, 551-8 and HD cells

To determine the proteome differences of each cell line, we con-ducted high-resolution 2-DE (two-dimensional electrophoresis)mapping using whole proteins extracted from H9, 551-8 and HDcells at undifferentiated stages. Total proteins were separated on2-DE gels and visualized through silver staining. Approximately,more than 2500 protein spots were mapped individually fromthe H9, 551-8, and HD 2-DE gels (Supplementary FigureS1 at http://www.BiochemJ.org/bj/446/bj4460359add.htm). Weprimarily focused on spots that showed more than 2-foldchanges in H9 compared with 551-8, 551-8 compared withHD and H9 compared with HD cells, and then selecteddifferentially expressed protein spots in each group. Theselected protein spots were excised from the 2-DE gels foridentification process. A total of 26 spots were analysed byLC-MS/MS, and then the identified peptides were comparedwith known proteins using the IPI human protein database(http://www.ebi.ac.uk/IPI/IPIhuman.html). Among the identifiedpeptides, spots which showed a statistically significant difference(P < 0.05) were selected and summarized in Table 2.

As shown in Table 2, when H9 and 551-8 cells were compared,we observed that a total of 14 proteins showed different expressionpatterns, in which eight proteins were up-regulated and sixproteins were down-regulated in H9 and 551-8 cells respectively.By contrast, when 551-8 and HD cells were compared, wefound that 17 proteins were differentially expressed (Figure 3,Table 2 and Supplementary Figure S1). Figure 3(A) shows somerepresentative protein spots that were differentially expressed,whereas Figure 3(B) shows fold changes of each candidate proteinexpression in each cell. In the case of HD-iPSCs, seven proteinswere down-regulated and ten proteins were up-regulated whencompared with 551-8 cells. When compared with H9 cells,HD cells showed 20 differentially expressed protein patterns,in which ten proteins were down-regulated and ten proteinswere up-regulated. These results suggest that there are someintrinsic differences at protein levels in HD patient-derived iPSC(HD), when compared with normal hESCs (H9) and iPSCs (551-8), which will, in turn, also alter the cellular and biochemicalproperties of HD-iPSCs.

Classification and biological network analysis of the identifiedproteins from H9, 551-8 and HD cells

In order to characterize the differentially expressed proteins, atotal of 26 proteins were classified into functional categoriesaccording to biological processes using information fromGene Ontology (http://www.geneontology.org) and UniProt(http://www.expasy.uniprot.org). As a result, they were groupedinto several different categories as follows: cell death regulation(23%), oxidative and cellular stress (10%), reactive oxygenspecies metabolic process, catabolic process, and redoxhomoeostasis (20%) and others (47%) (Supplementary FigureS2 at http://www.BiochemJ.org/bj/446/bj4460359add.htm). Im-portantly, we found that programmed cell death, oxidative stress-and cellular oxygen-associated proteins, including SOD1 and Prxfamilies, constitute the major portion of differentially expressedproteins in HD-iPSCs (53% of classified biological processes).These results strongly suggest that HD patient-derived iPSCs maybe highly susceptible to intracellular or extracellular stresses, suchas oxidative stress and apoptosis signals.

To deduce the possible relationships among the identifiedproteins by 2-DE analysis, we carried out biological networkanalysis using MetaCoreTM software. After the networks were

Figure 3 Analysis of differentially expressed protein spots among H9, 551-8 and HD cells

(A) Enlarged images showing the differentially expressed protein spots. Note the up-regulatedspots (Prx1, Prx2, Prx6 and BTF3) and down-regulated spots (SOD1, GST, Gpx1, Cfl-1 andStmn-1) in HD-iPSCs. Arrows indicate the differentially expressed protein spots in eachsample. (B) Quantification of differentially expressed protein spots. Intensities [optical density(OD)/background)] of each spot were analysed and presented in a histogram. Results are means+− S.E.M for at least three independent experiments. The significance of differences was evaluatedby paired two-tailed Student’s t test (SAS version 8.0). *P < 0.05, ‡P < 0.01 and †P < 0.001compared with H9 cells.

built by the shortest paths algorithm, our 26 proteins were up-loaded and were mapped on the transcriptional regulation pathway(Supplementary Figure S3 at http://www.BiochemJ.org/bj/446/bj4460359add.htm). This network shows that our identifiedproteins may play a role in the regulation of various transcriptionfactors, such as p53, c-Myc, E2F1, YY1 (Yin and Yang 1)and NF-κB (nuclear factor κB) in HD-iPSCs, which are knownas common transcriptional factors and play important rolesin the regulation of various cellular processes, including cellproliferation, differentiation and development. Although we didnot detect these transcription factors directly in the 2-DE analysis,it will be likely that alterations of transcription factors can happenthrough the gene regulation network by identified proteins inHD-iPSCs.

Up-regulation of oxidative stress-related proteins in HD-iPSCs

To verify the 2-DE-based proteome data, we performed Westernblotting using the same protein samples used in the 2-DE analysis(Figure 4). In this case, we also included protein samples fromHD2 cells to confirm whether both HD and HD2 cells give riseto similar results. Among the identified proteins from the 2-DEanalysis, we selected SOD1, GST (glutathione transferase), Gpx1


http://www.BiochemJ.org/bj/446/bj4460359add.htm

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364J.-I.Chaeand

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Table 2 Identification of differentially expressed proteins in H9, 551-8 and HD cells

NEDD, neural-precursor-cell-expressed developmentally down-regulated.

Fold changes

Spot number Accession number* Identified proteins Sequence coverage† Matched peptide pI‡ Mass (Da) Mascot score H9/551-8 H9/HD 551-8/HD

1 IPI00011416 δ(3,5)-δ(2,4)-Dienoyl-CoA isomerase, mitochondrial 4 1 8.16 36136 30 0.9 +− 0.1 0.3 +− 0.05 0.3 +− 0.152 IPI00024095 Annexin A3 44 21 5.63 36524 1064 0.4 +− 0.1 1.2 +− 0.08 3.2 +− 0.183 IPI00017334 Prohibitin 94 32 5.57 29843 1465 0.7 +− 0.05 0.5 +− 0.14 0.8 +− 0.24 IPI00000760 NG,NG-dimethylarginine dimethylaminohydrolase 2 21 5 5.66 29911 192 1.0 +− 0.005 0.6 +− 0.02 0.6 +− 0.075 IPI00218693 Adenine phosphoribosyltransferase 45 7 5.78 19766 357 0.9 +− 0.2 0.4 +− 0.1 0.4 +− 0.36 IPI00479997 Stmn 15 2 5.76 17292 136 0.8 +− 0.05 0.6 +− 0.1 0.7 +− 0.177 IPI00479997 Stmn 30 5 5.76 17292 198 0.7 +− 0.07 0.5 +− 0.07 0.7 +− 0.138 IPI00218733 SOD [Cu-Zn] 24 3 5.7 16154 154 0.6 +− 0.09 0.7 +− 0.12 1.3 +− 0.29 IPI00012011 Cfl-1 15 2 8.22 18719 96 0.7 +− 0.12 0.5 +− 0.08 0.6 +− 0.2

10 IPI00927606 Glutathione peroxidase 13 2 6.15 22193 35 0.5 +− 0.07 0.3 +− 0.04 0.6 +− 0.1111 IPI00019755 GST ω-1 isoform 1 18 5 6.23 27833 233 0.3 +− 0.05 0.3 +− 0.06 1.2 +− 0.112 IPI00032139 Serpin B9 17 7 5.61 43004 224 2.4 +− 0.12 1.9 +− 0.15 0.8 +− 0.2713 IPI00216592 Isoform C1 of heterogeneous nuclear ribonucleoproteins C1/C2 16 5 4.94 32375 243 2.0 +− 0.07 1.2 +− 0.05 0.6 +− 0.1214 IPI00011416 δ(3,5)-δ(2,4)-Dienoyl-CoA isomerase, mitochondrial 9 2 8.16 36136 116 0.8 +− 0.1 0.4 +− 0.05 0.5 +− 0.1515 IPI00220301 Prx-6 71 23 6 25133 461 1.2 +− 0.01 2.2 +− 0.1 1.8 +− 0.1116 IPI00220301 Prx-6 5 1 6 25133 33 1.5 +− 0.16 1.8 +− 0.1 1.2 +− 0.2617 IPI00221035 Isoform 1 of transcription factor BTF3 9 5 9.41 22211 99 2.2 +− 0.22 3.3 +− 0.36 1.5 +− 0.5718 IPI00218918 Annexin A1 6 2 6.57 38918 76 0.8 +− 0.05 1.9 +− 0.2 2.4 +− 0.2519 IPI00025796 NADH dehydrogenase [ubiquinone] iron–sulfur protein 3, mitochondrial 9 2 6.99 30337 144 0.6 +− 0.13 1.4 +− 0.07 0.7 +− 0.220 IPI00220301 Prx-6 64 12 6 25133 321 1.4 +− 0.18 2.3 +− 0.2 1.56 +− 0.321 IPI00026964 Cytochrome b–c1 complex subunit Rieske, mitochondrial 2 1 8.55 29934 48 0.8 +− 0.03 1.9 +− 0.15 2.2 +− 0.1722 IPI00643041 RAN GTP-binding nuclear protein Ran 15 4 7.01 24579 92 0.85 +− 0.4 2.1 +− 0.24 2.5 +− 0.2723 IPI00027350 Prx-2 44 15 5.66 22049 472 0.8 +− 0.1 2.5 +− 0.42 3.1 +− 0.5324 IPI00000874 Prx-1 5 1 8.27 22324 40 0.8 +− 0.1 2.5 +− 0.23 3.3 +− 0.3325 IPI00003949 Ubiquitin-conjugating enzyme E2 N 19 2 6.13 17184 104 0.4 +− 0.2 2.2 +− 0.26 5.1 +− 0.426 IPI00022597 NEDD8-conjugating enzyme Ubc12 10 2 7.57 21172 48 1.2 +− 0.04 2.0 +− 0.11 1.7 +− 0.15

*IPI (International Protein Index) accession numbers.†The percentage of matched sequence in the total protein sequence (the percentage of the database protein sequence covered by matching peptides).‡The isoelectric point of the intact protein.

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Figure 4 Expression of oxidative stress-related proteins in H9, 551-8, HD and HD2 cells

(A) Total proteins were extracted from H9, 551-8, HD and HD2 cells, and were used for Western blot analysis. Oxidative stress-related antibodies including SOD1, GST, Gpx1, Prx1, Prx2 andPrx6 were used with β-actin as a loading control. (B) Quantification of protein expression levels after normalization using β-actin. Results are means +− S.E.M for three independent experiments.The significance of differences was evaluated by paired two-tailed Student’s t test (SAS version 8.0). §P < 0.01 and *P < 0.001 compared with H9 cells; + P < 0.05, ‡P < 0.01 and †P < 0.001compared with 551-8 cells. (C) Immunocytochemical staining showing the expression of Prx1, Prx2 and Prx6 in each cell. (D) Histograms showing the relative expression of Prx1 in cytoplasm andnucleus. Scale bar = 50 μm.

(glutathione peroxidase 1) and Prx families (Prx1, Prx2 and Prx6), which are all known as representative antioxidant molecules,for further verification. This was because oxidative stress and therole of antioxidants for defence are known to be important inseveral degenerative diseases, including HD [9,10].

In the Western blotting analysis, we observed that SOD1, GSTand Gpx1 were strongly expressed in both H9 and 551-8 cells,compared with HD and HD2 cells, and their expression levelswere the lowest in both HD-iPSC lines (Figure 4A). It is knownthat SOD, GST and Gpx1 have roles in reducing intracellularsuperoxide levels, detoxifying endogenous compounds, suchas peroxidized lipids, and protecting the organism fromoxidative damage. Therefore reduced levels of SOD1, GST

and Gpx1 in the HD-iPSC lines suggest that they are highlysusceptible to oxidative stress, compared with the H9 and 551-8cells.

On the other hand, we found that expression of Prx familymembers, including Prx1, Prx2 and Prx6, were up-regulated in thetwo HD-iPSC lines, compared with H9 and 551-8 cells. Prxs havebeen implicated as important indicators for cellular ROS (reactiveoxygen species) signals, since they mediate antioxidant processesand control cytokine-induced peroxide levels. Therefore elevationof the cellular levels of Prxs under an oxidative stress environmentcan protect oxidative stress-mediated toxicity through theirantioxidant activities. In our 2-DE results, we found that Prx1,Prx2 and Prx6 were highly up-regulated in HD-iPSCs compared



with H9 and 551-8 cells. Consistent with these observations,the Western blotting results also showed the elevation of Prx1,Prx2 and Prx6 expression in both the HD- and HD2-iPSC lines(Figure 4A). Therefore we speculated that elevation of Prx1, Prx2and Prx6 levels in HD-iPSC lines is a defence mechanism againstcellular oxidative stress, which may have been transmitted fromthe specific pathological conditions of the HD patient.

Figure 4(B) shows the fold changes of each candidate proteinexpression, in which SOD1, GST and Gpx1 expression decreasessignificantly in HD-iPSC lines, whereas Prx family expressionincreases conversely in both the HD and HD2 lines. Whencompared with H9 cells, the fold changes of expression levelsof each marker in HD and HD2 cells were as follows: SOD1(0.48 +− 0.03 and 0.34 +− 0.02), GST (0.6 +− 0.03 and 0.45 +− 0.05),Gpx1 (0.27 +− 0.02 and 0.19 +− 0.02), Prx1 (1.93 +− 0.12 and1.95 +− 0.12), Prx2 (1.76 +− 0.12 and 1.91 +− 0.19) and Prx6(1.95 +− 0.16 and 1.97 +− 0.18).

We also performed immunocytochemical staining usingantibodies against Prx1, Prx2 and Prx6, in order to examine thelocalization patterns of Prx proteins under specific conditions.Prx1, Prx2 and Prx6 are normally expressed in the cytoplasm,although Prx1 is also known to be expressed in the nucleus,especially when the cells are attacked by ROS [11]. From ourimmunocytochemical staining results, both Prx2 and Prx6 werelocalized in the cytoplasm, regardless of the cell type. However,in the case of Prx1, which was mainly expressed in the cytoplasmof H9 and 551-8 cells, was predominantly detected in thenucleus of HD and HD2 cells (Figures 4C and 4D). This resultraises the possibility that oxidative stress in HD-iPSCs may giverise to the up-regulation of Prx1 protein, which resulted in thetranslocation to the nucleus [11].

In a parallel experiment, we further differentiated H9, 551-8, HD and HD2 cells into mature neurons (Figure 1B, Stage5) and carried out Western blot and immunocytochemicalanalyses using markers specific for oxidative stress (SOD1,GST, Gpx1, Prx1, Prx2 and Prx6). The Western blot analysisshowed their expression patterns are similar to those from un-differentiated stages (Supplementary Figure S4A at http://www.BiochemJ.org/bj/446/bj4460359add.htm). Fold change analysisfurther revealed that two HD-iPSC lines persistently respondto oxidative stress after neuronal differentiation, and theirexpression levels were adjusted to those of H9 cells.Fold changes of expression levels of marker proteins inHD and HD2 cells of differentiated stage (Stage 5) werecompared with those of undifferentiated stage (Stage 1) asfollows: SOD1 (HD, − 0.37 +− 0.02 compared with − 0.52 +− 0.04and HD2, − 0.51 +− 0.02 compared with − 0.65 +− 0.02),GST (HD, − 0.43 +− 0.02 compared with − 0.4 +− 0.03 andHD2, − 0.49 +− 0.02 compared with − 0.55 +− 0.05), Gpx1(HD, − 0.53 +− 0.01 compared with − 0.73 +− 0.02 and HD2,− 0.61 +− 0.01 compared with − 0.81 +− 0.02), Prx1 (HD,4.37 +− 0.3 compared with 1.92 +− 0.12 and HD2, 4.71 +− 0.31compared with 1.95 +− 0.2), Prx2 (HD, 3.52 +− 0.17 compared with1.76 +− 0.12 and HD2, 4.58 +− 0.33) and Prx6 (HD, 3.46 +− 0.3compared with 1.95 +− 0.16 and HD2, 3.63 +− 0.3 compared with1.97 +− 0.18) (Supplementary Figure S4B). We also carried outimmunocytochemical analysis on the differentiated neurons andfound that the expression levels of Prx1, Prx2 and Prx6 proteinswere highly increased in HD and HD2 cells compared with H9cells (Supplementary Figure S4C). Interestingly, we also observedthat these proteins are slightly increased in 551-8 cells, suggestingoxidative stress might also affect normal iPSCs after neuronaldifferentiation.

Taken together from our Western blotting and immunocyto-chemical staining results, up-regulation of Prx1, Prx2 and Prx6

proteins and down-regulation of SOD1, GST and Gpx1 proteinsin HD and HD2 cells indicate a strong induction or recruitmentof factors that have protective roles against oxidative stress thatmay come from HD pathological conditions.

Induction of DNA damage-mediated apoptosis in HD-iPSCs

Since it is well known that apoptotic cell death can becaused by stressful conditions, including oxidative stress,we next investigated whether there are more apoptotic cellsin HD-iPSC lines, compared with H9 and 551-8 cells. Toaddress this question, we used a TUNEL assay and foundthat TUNEL-positive cells were significantly higher in HD(23.51 +− 2.57%) and HD2 cells (26.57 +− 0.80%) than in H9(1.37 +− 0.73%) or 551-8 (7.22 +− 2.85%) cells at undifferentiatedstages (Figure 5A). Similarly, we also found that TUNEL-positive cells were significantly higher in HD (36.14 +− 1.61%)and HD2 cells (40.47 +− 2.85%) than in H9 (9.49 +− 2.45%) or551-8 (14.96 +− 2.33%) cells at differentiated neuronal stages(Figure 5B).

Next we investigated whether the apoptotic cell death in HD-iPSCs was caused by DSBs (double-strand breaks) or DNAfragmentation that take place under stressful conditions, includingoxidative stress, metabolic disorder or genetic mutation. Amongthe specifically up-regulated proteins in HD-iPSCs, BTF3 [alsoknown as NACB (nascent-polypeptide-associated complex βpolypeptide)] is a well-known transcription factor, which isinvolved in the transcription initiation through direct binding toTATA and CAAT box sequences in the proximal promoter [12,13].In addition, ATM was recently proposed as a target gene of BTF3.As it is well known that ATM is activated under oxidative stressand plays an important role in DNA-damage-mediated signalling[14], we speculated that, when the cells are attacked by ROSand oxidative stress, BTF3 might up-regulate ATM and thenthe apoptotic signal is transmitted by ATM activation to induceapoptotic changes in the cells. Having this in mind, we examinedthe expression levels of BTF3 and ATM transcripts in H9, 551-8,HD and HD2 cells using qRT-PCR. Interestingly, both BTF3 andATM expression were significantly up-regulated in HD and HD2cells compared with H9 and 551-8 cells (Figure 6A).

We also examined the translational control of key componentsinvolved in apoptosis, such as BTF3, ATM and p53 expression byWestern blot analysis. According to the Western blotting results,BTF3 was significantly up-regulated both in HD and HD2 cellsand its expression level was 3.29 +− 0.15- and 3.57 +− 0.13-foldhigher than those of H9 and 551-8 cells, of which results aresimilar to the qRT-PCR results (i.e. 3.45 +− 0.46 and 3.7 +− 0.32).Since ATM is known as a downstream target of BTF3 underoxidative stress, we examined the status of phosphorylation ofATM on Ser1981 that normally occurs in response to oxidativestress-inducers such as H2O2, which is critical for sustainedoccupancy of ATM on DNA DSB sites [14,15]. p-ATM (S1981)[ATM phosphorylated at Ser1981] was increased in HD-iPSCswhen the total proteins were reacted to an antibody againstp-ATM (S1981) (Figures 6B and 6C). Auto-phosphorylationof ATM makes subsequent modification of downstreamregulators, such as p53 (Ser15), MDM2 (murine double minute 2)(Ser395), Chk2 (checkpoint kinase 2; Thr68) and H2A.X (Ser139)through its activated kinase in response to DSBs [16]. Forthis reason, we then examined the expression levels of p53(Ser15) and H2A.X (Ser139) and observed an increased level ofphosphorylation at each specific site in the HD-iPSC lines. Theseresults suggest that HD-iPSCs undergo oxidative-stress-mediated





Figure 5 TUNEL assay showing the proportions of apoptotic cells in H9, 551-8, HD and HD2 cells

(A) Immunocytochemical staining of TUNEL-positive cells at undifferentiated stages. DAPI was used for counter-staining the cells. Histograms showing the relative expression of TUNEL-positivecells at undifferentiated stages. Scale bar = 20 μm. (B) Immunocytochemical staining of TUNEL-positive cells at differentiated stages and their quantifications. Scale bar = 50 μm. **P < 0.001.

cellular apoptosis, which is involved with DNA damage throughoxidation of DNA.

To further investigate the apoptotic processes in HD-iPSCs,we examined the expression of central regulators and effectorsinvolved in apoptosis. As shown in Figure 6(D), cleaved Bid,which is an active form of Bid, was significantly increased. Inaddition, we detected high levels of active forms of caspases(cleaved forms of caspase-9, -3, and -7) from HD and HD2 cells.Finally, a DNA repair-involved protein, PARP, which is known asa marker for undergoing apoptosis, was more extensively cleavedin HD and HD2 cells (Figures 6D and 6E).

Taken together, these results strongly suggest that cellularoxidative stress in HD-iPSCs can cause DNA damage, followedby activation of consecutive ATM-mediated signalling (i.e.phosphorylation of p53 and H2A.X) via its kinase activity.Activation of substrates of ATM in HD-iPSCs can lead to DNA-damage-induced apoptotic cell death through the mitochondrialpathway.

Down-regulation of cytoskeleton-associated proteins in HD-iPSCs

We then investigated whether increased apoptotic cell deathin HD-iPSCs in response to oxidative stress could affect theexpression of cytoskeleton-associated proteins, including Cfl-1,Stmn-1, Facn-1 and Sept-2 at differentiated neuronal stages (Stage5) among each cell line (H9, 551-8, HD and HD2 cells). Theseproteins are previously known to be strongly expressed duringneuronal differentiation [17–19]. To compare the expressionlevels, we performed a Western blot analysis and found that after

the differentiation of H9, 551-8, HD and HD2 cells into neuronallineages, although high levels of Cfl-1, Stmn-1, Facn-1 and Sept-2proteins were detected in H9 and 551-8 cells, their expression wassignificantly decreased in both HD and HD2 cells (Figures 7A and7B). Immunocytochemical staining further confirmed that theseproteins are significantly down-regulated in HD and HD2 cells(Figure 7C). Taken together, these results suggest that expressionof cytoskeleton-associated proteins was highly reduced in HD-iPSCs. Although it is currently unknown whether these proteinsare directly involved in neuronal differentiation, it appears thatneuronal differentiation was highly affected in HD-iPSCs.

DISCUSSION

HD is a progressive and autosomal dominantly inherited neuro-degenerative disorder, characterized by selective degeneration ofmedium spiny projection neurons in the striatum, which leadsto severe impairments of motor functions, such as chorea. Inaddition to genetic causes, in which CAG repeats abnormallyexpand in HD patients, several factors are also known to beinvolved in the pathogenesis of HD, which include excitotoxicity,impaired energy metabolism and oxidative stress [20]. In thepresent study, we performed a comparative proteomic analysisusing protein samples from undifferentiated H9, 551-8 and HDcells, in an attempt to identify and characterize the differentiallyexpressed proteins in HD patient-derived iPSCs (SupplementaryFigure S1). In our comparative studies, we mainly focused on thedifferentially expressed proteins in HD-iPSCs compared with H9or 551-8 cells. Although more iPSC samples are needed in order



Figure 6 Analysis of apoptotic cell death in H9, 551-8, HD and HD2 cells

(A) qRT-PCR analyses showing relative expression levels of BTF3 (left-hand panel) and ATM (right-hand panel) transcripts. After normalization with β-actin, results are means +− S.E.M for threeindependent experiments. (B) Western blots showing the expression of key components involved in apoptosis, such as BTF3, ATM, p53 and H2A.x. (C) Histograms showing the fold changes oftheir relative expression levels. (D) Western blots showing the expression of mitochondria-dependent caspase signalling components. (E) Histograms showing the fold changes of their relativeexpression levels. The significance of differences was evaluated by paired two-tailed Student’s t test (SAS version 8.0). §P < 0.01 and *P < 0.001 compared with H9 cells; + P < 0.05, ‡P < 0.01and †P < 0.001 compared with 551-8 cells. p-, phospho-.

to generalize our results, the present study nevertheless representsthe first proteomic analysis on HD-iPSCs and will provide usefulinsights on the pathogenesis and neurodegeneration of HD.

According to our results, compared with normal hESCs(H9) or hiPSCs (551-8), HD-iPSCs (HD and HD2) are

shown to be highly susceptible to oxidative stress, which actsas one of the major factors involved in HD pathogenesis[21–23]. More recently, Parkinson’s disease-related LRRK2(leucine-rich repeat serine/threonine-protein kinase 2) mutantiPSC-derived dopaminergic neurons are also shown to have



Figure 7 Expression of cytoskeleton-associated proteins at the differentiated neuronal stage

(A) Western blots showing the expression levels of Cfl-1, Stmn-1, Fscn-1 and Sept-2. (B) Histograms showing the fold changes of their relative expression levels. The significance of differenceswas evaluated by paired two-tailed Student’s t test (SAS version 8.0). §P < 0.01 and *P < 0.00 compared with H9 hESCs; + P < 0.05, ‡P < 0.01 and †P < 0.001 compared with 551-8 cells.(C) Immunocytochemical staining showing the expression patterns of Cfl-1, Stmn-1, Facn-1 and Sept-2 at Stage 5 in each cell line. Scale bars = 50 μm in upper images and 20 μm in lower images.

increased susceptibility to oxidative stress [24], reiterating thesignificance of oxidative stress in neurodegeneration. In ourproteomic analysis, several oxidative stress response proteins,such as Prxs (Prx1, Prx2 and Prx6) were strongly up-regulatedin HD-iPSC lines (Figures 3 and 4). Prxs reduce H2O2 andperoxynitrite through their catalytic cysteine residues, so they canprotect the cells from oxidative cellular damage via their self–oxidization upon reaction with peroxide under oxidative stressconditions [25]. In keeping with our findings, it has been shownpreviously that Prx1, Prx2 and Prx6 were significantly inducedin the stratum of HD patients [23]. Prx1, Prx2 and Prx6 arenormally expressed in the cytoplasm, but we observed that Prx1 ispredominantly expressed in the nucleus (Figures 4C and 4D). Itis known that, whereas cytoplasmic Prx1 regulates H2O2-dependent NF-κB activation, nuclear Prx1 regulates NF-κB–DNA binding through elimination of H2O2 as a p50subunit oxidant. Therefore, it is likely that translocated Prx1 inthe nucleus under HD pathological environment can facilitate thedegeneration of cells. Prx1 also acts as a H2O2 scavenger whenthe cells are attacked by ROS. It will be important to identify thesignals which make Prx1 translocate to the nucleus in HD-iPSCs.

In contrast with Prxs, antioxidant enzymes, such as SOD1, GSTand Gpx1, were shown to be down-regulated in HD-iPSCs. SODcan convert superoxide to H2O2, thereby reducing intracellularsuperoxide level, and the decreased SOD activity acceleratesthe production of ROS. In the nervous system, SOD is mainlydetected in neurons at high levels, especially in the cortical layer.Therefore when the cells are damaged, SOD activity is down-regulated rapidly. In the present study, we found that SOD activity

is highly decreased in HD-iPSCs, which may lead to an increaseof intracellular ROS. GST is another antioxidant enzyme, whichcatalyses the conjugation of reduced glutathione and detoxifiesthe endogenous compounds, such as peroxidized lipids. Gpxcatalyses the reduction of hydroperoxides to the correspondingalcohol at the expense of GSH. Gpx1 is the most abundant enzymethat is largely restricted to the cytosol, but is also present inmitochondria. Its antioxidant activity is very important in thebrain, as demonstrated in Gpx1-knockout mice. We speculatethat down-regulation of these antioxidant enzymes is due to theincreased level of ROS, which may be related to the mutant Httproteins in HD-iPSCs. It is likely that mutant Htt proteins candirectly affect the production of ROS.

In our proteomic analysis, we also found that BTF3 ispredominantly up-regulated in HD-iPSCs (Figures 3 and 6). BTF3is a transcription factor that can activate transcription of RNApolymerase II through physiological binding to promoter regionssuch as the TATA and CAAT boxes [12,26]. BTF3 is also knownto be involved in cell-cycle regulation and apoptosis [27–29].More recently, it is known that BTF3 can activate ATM [30],which is involved in the DNA-damage-related apoptosis pathway[16]. When DNA is damaged by genotoxic stresses such asUV, γ -irradiation or ROS, ATM can phosphorylate the tumoursuppressors p53 and Chk2 [16]. Subsequently, the activatedp53 via phosphorylation induces its target gene, Bax, which isinvolved in mitochondrial apoptotic pathway by release of Cytc(cytochrome c), followed by activation of caspases [31]. In thepresent study, BTF3 is strongly up-regulated in HD and HD2cells, in response to oxidative stress/damage, and/or metabolic



dysfunction, which, in turn, will trigger the induction of the DNAdamage-repair protein ATM, followed by activation of the p53-mediated apoptosis pathway.

DNA damage by oxidative stress, such as ROS, leads toapoptosis via activation of ATM in mitochondria. ROS activatesMAPK (mitogen-activated protein kinase) that activates both p38and JNK (c-Jun N-terminal kinase) through phosphorylation.These subsequent activations cleave Bid, which is translocatedto mitochondria by Bax and subsequently facilitates Cytc releasefrom mitochondria [32]. Bax, a Bcl-2 protein family member, isrequired for translocation of tBid (truncated Bid), which can beinduced through phosphorylation of p53 at Ser15 [31,33]. Theinteracted form as a dimer of tBid and Bax in mitochondriamembrane can release Cytc. The released Cytc, coupled witha key initiator caspase, caspase-9, which acts as a proteosome,in turn further activates the effector caspases, such as caspase-3 and -7 [34]. Activation of these effector caspases results inthe cleavage of a DNA-repair-involved protein, PARP, whichgives rise to apoptosis via stimulation of AIF (apoptosis-inducingfactor) released from mitochondria [35]. In the present study,we observed the elevated levels of cleaved Bid, cleaved caspases(caspase-9, -3 and -7) and cleaved PARP in HD and HD2 cells.Moreover, TUNEL-positive cells were significantly increased.Therefore these results demonstrate that ROS is generated in HD-iPSCs, and then the mitochondria-dependent apoptotic pathwayis triggered through sequential activation of caspases.

From our analysis, we also found that the expressionof cytoskeleton-associated proteins, including Cfl-1, Stmn-1,Facn-1 and Sept-2, are highly down-regulated in HD-iPSCs.Cytoskeleton is composed of actin and microtubule filaments.Actin is a major cytoskeletal protein in neurons, and thedynamics of its assembly are involved in many aspects ofcell motility, vesicle transport and membrane turnover [36].Thus disorganization of actin results in failure of neuronaldifferentiation. Cfl-1 plays as a key regulator, together with theADF (actin depolymerizing factor) in actin dynamics, whichis implicated in neuronal function [37]. Abnormal expressionof Cfl-1 or neurodegenerative stimulation could form rod-like inclusions in neurons [38]. Stmn-1 is associated with theassembly of microtubule filaments and is highly expressedin the brain [39,40]. It is also known that Stmn-1 candestabilize microtubules through a direct interaction with tubulin[41]. Furthermore, we have previously reported that Stmn-1is highly expressed in hESC-derived NESs (neuroectodermalspheres), which can differentiate into three neural lineages:astrocytes, oligodendrocytes and mature neurons [18]. Facn-1has important regulatory roles in cell motility and invasionvia the regulation of cytoskeletal structures [42,43]. Previousreports suggest that Facn-1 is expressed in the developingnervous system at high levels and its expression is mainlydetected in medullary epithelium of human fetal and adultbrains [19,44]. Sept-2 is required for the organization of actincytoskeleton such as cellular membranes, actin filaments andmicrotubules [45,46]. Septins can oligomerize with other Septinfamily members such as Sept-4–Sept-5–Sept-8, Sept-7–Sept-9b–Sept-11 and Sept-2–Sept-6–Sept-7. Among these hetero-oligomerized complexes, only the Sept-2–Sept-6–Sept-7 complexcan assemble into filaments [47,48]. It was also reported thatSept-2 is expressed in NESs at high levels [18]. Accordingto our results, expression of cytoskeleton-associated proteins ishighly affected in HD and HD2 cells (Figures 7A and 7B).Moreover, expression patterns of these proteins at differentiatedneuronal stage (Stage 5) suggest that neuronal differentiationis also impaired in the HD-iPSC lines (Figure 7C). Althoughit is currently unknown whether these proteins are directly

involved in neuronal differentiation, it is likely that oxidative-stress-induced cell death in HD-iPSCs affects the formation ofcytoskeleton-associated proteins, which will, in turn, influenceneuronal differentiation either directly or indirectly. Furthermore,we observed that the differentially expressed antioxidant enzymesin HD-iPSC lines at undifferentiated stages were similarly alteredduring neuronal differentiation (Supplementary Figure S4). It isalso possible that antioxidant enzymes, such as SOD1, GST, Gpx1and the Prx family (Prx1, Prx2 and Prx6) might cause a delay inneuronal differentiation in the HD-iPSC lines.

In summary, we have carried out a comparative proteomicanalysis, and isolated and characterized the differentiallyexpressed proteins in HD-iPSCs at undifferentiated stage. Sincepathogenic features of HD only become apparent at certain agesand only in specific brain regions, mostly medium spiny projectionneurons in the striatum, it is striking that significant changesare detected in undifferentiated HD-iPSCs at proteomic levels.Interestingly, we found that HD-iPSCs are highly susceptible tooxidative stress, which leads to increased apoptotic cell death.HD-iPSCs also exhibit dysregulation of cytoskeleton-associatedproteins, which affects neuronal differentiation. Considering thesignificance of iPSC research and the increasing interests inproteome profiles of iPSCs, in particular from disease-specificiPSC lines, the present study provides the first report on thequantitative proteomic analysis of an iPSC line derived from ajuvenile HD patient carrying 72 CAG repeats, which containssome useful information or insights on the pathogenesis orneurodegeneration mechanisms of HD using HD-iPSCs. As forthe early onset of HD phenotypes at the proteomic level, despite noobvious cellular phenotype judged by the absence of mutant Httprotein expression (results not shown), it will be mainly due to thehigh numbers of CAG repeats (i.e. 72 CAG repeats). Therefore inorder to draw generalized conclusions on HD-iPSC, we obviouslyneed to extend the present study using more HD-iPSC lines, inparticular those carrying different lengths of CAG repeats. Inaddition, since HD-iPSC carries genetic mutations, it will beessential to correct the mutant gene in order to be used for celltherapy. In this case, it will be interesting to examine whetherthe increased expression of oxidative stress-related proteins, etc.discovered from the present study will diminish and/or return tonormal levels in proteomic analysis after gene correction of HDmutant genes in HD-iPSCs.

AUTHOR CONTRIBUTION

Jung-Il Chae contributed to conception and design of the study, and wrote the paper. Dong-Wook Kim wrote the paper and performed the Western blot and protein network analyses.Nayeon Lee performed stem cell culture and differentiation experiments, includingimmunocytochemical analysis. Young-Joo Jeon, Joohyun Ryu and Byoung Chul Parkcarried out the proteomic analysis and quantitative evaluation. Iksoo Jeon, Jihye Kwonand Jumi Kim performed the TUNEL assay and immunocytochemical analysis. Yunjo Soh,Dong-Seok Lee, Kang Seok Seo, Nag-Jin Choi and Sung Hyun Kang provided theoreticalinput and critical advice on the biochemical experiments. Seung-Hun Oh, Dong Ah Shin,Dong Ryul Lee and Jeong Tae Do participated in the data analysis. In-Hyun Park andGeorge Daley originally established the 551-8, F5 and HD-iPSC lines and also providedtheoretical and technical advice for stem cell experiments. Jihwan Song designed andsupervised the entire research, and wrote the paper.

ACKNOWLEDGEMENTS

We thank Professor Patrik Brundin and Professor Jiayi Li (Lund University, Lund, Sweden),Dr Manho Kim, Dr Wooseok Im and Dr Hoon Ryu (Seoul National University, Seoul,Korea) and Dr Seung-Jae Lee (Konkuk University, Seoul, Korea) for useful discussions onHuntington’s disease and its pathogenesis. We also thank members of the Song laboratoryfor useful discussion and support throughout the present study.



FUNDING

This work was supported by the Next-Generation BioGreen 21 Program [grant numberPJ008116062011], the Rural Development Administration, Republic of Korea (to J.-I.C.),the Korea Food and Drug Administration [grant number S-11-04-2-SJV-993-0-H] and theKorea Health Technology R&D Project of the Ministry of Health and Welfare of the Republicof Korea [grant number A111016 (to J.S.)], the Basic Science Research Program throughthe National Research Foundation of Korea (NRF) funded by the Ministry of Education,Science and Technology [grant numbers 2012R1A1A2006827 (to J.S.), 2010-0021532(to J.-I.C.) and 2011-0026986 (to D.-W.K.)], and research funds of Chonbuk NationalUniversity in 2012 (to D.-W.K.).

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Received 17 August 2011/21 May 2012; accepted 13 June 2012Published as BJ Immediate Publication 13 June 2012, doi:10.1042/BJ20111495


Biochem. J. (2012) 446, 359–371 (Printed in Great Britain) doi:10.1042/BJ20111495

SUPPLEMENTARY ONLINE DATAQuantitative proteomic analysis of induced pluripotent stem cells derivedfrom a human Huntington’s disease patientJung-Il CHAE*1, Dong-Wook KIM*1, Nayeon LEE†1, Young-Joo JEON*, Iksoo JEON†, Jihye KWON†, Jumi KIM†, Yunjo SOH*,Dong-Seok LEE‡, Kang Seok SEO§, Nag-Jin CHOI¶, Byoung Chul PARK‖, Sung Hyun KANG‖, Joohyun RYU‖, Seung-Hun OH†,Dong Ah SHIN**, Dong Ryul LEE†, Jeong Tae DO†, In-Hyun PARK††,‡‡, George Q. DALEY†† and Jihwan SONG†2

*Department of Oral Pharmacology, School of Dentistry and Institute of Dental Bioscience, BK21 project, Chonbuk National University, Jeonju 651-756, Korea, †CHA Stem CellInstitute, Department of Biomedical Science, CHA University, Seoul 135-081, Korea, ‡College of Natural Sciences, Kyungpook National University, Daegu 702-701, Korea, §Departmentof Animal Science and Technology, Sunchon National University, Suncheon 540-742, Korea, ¶Department of Animal Science, College of Agricultural and Life Science, ChonbukNational University, Jeonju 651-756, Korea, ‖Medical Proteomics Research Center, KRIBB, Daejeon 305-333, Korea, **Department of Neurosurgery, Yonsei University College ofMedicine, Seoul, Korea, ††Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, U.S.A., and ‡‡Department of Genetics, YaleUniversity School of Medicine, New Haven, CT 06520, U.S.A.

MATERIALS AND METHODS

2-DE analysis and protein identification

The total quantity of protein (200 μg) for the analytical runswas transferred on to IPG (immobilized pH gradient) strip holderchannels (Bio-Rad Laboratories). 2-DE protein mixtures wereseparated by IEF (isoelectric focusing) in the first dimension andSDS/PAGE (12% gel) in the second dimension. Total proteinswere mixed with rehydration solution [7 M urea, 2 M thiourea,4% (w/v) CHAPS, 50 M DTT (dithiothreitol) and a trace ofBromophenol Blue] for a final volume of 300 μl. Proteins werethen incubated for 12 h at room temperature before separationby IEF at 250 V for 15 min, 1000 V for 2 h, or 1000 V for 6 h,with 50 mA of current per gel strip. The gel strips were thenimmediately equilibrated in equilibrium buffer [50 mM Tris/HCl(pH 8.8), 6 M urea, 30 % (v/v) glycerol and 2 % (w/v) SDS]. Afterequilibration, the IPG strips were transferred on to SDS/PAGEgels for the second dimension of separation. Separation in thesecond dimension was carried out using 12 % SDS/PAGE in aProtean II xi 2-DE cell (Bio-Rad Laboratories) at 20 mA untilthe Bromophenol Blue reached the bottom of the gel. Purifiedproteins were analysed by 2-DE PAGE, which typically consistedof a broad-range IEF step with a pH gradient of 3–10, followed byelectrophoresis in a 10 % gel. The 2-DE gels were stained using asilver staining kit (Amersham Biosciences). Briefly, the gels werefixed in 40% ethanol and 10% acetic acid for 30 min and thensensitized in a solution of 25 % (w/v) ethanol glutaraldehyde,5% (w/v) sodium thiosulfate and 17 g of sodium acetatefor 30 min. Finally, they were washed three times with water for15 min each. The gels were subsequently immersed in 2.5% (w/v)silver nitrate and 37% (w/v) formaldehyde for 20 min and thendeveloped in a mixture of 6.25 g of sodium carbonate and 37 %(w/v) formaldehyde for 2–5 min. The reaction was then stoppedin EDTA-Na2-2H2O.

In-gel protein digestion

Protein bands of interest were excised and digested in-gelwith sequencing grade modified trypsin (Promega), as describedpreviously [1]. In brief, each protein spot was excised from the gel,placed in a polypropylene (Eppendorf) tube and washed 4–5 timesuntil the gel was clear with 150 μl of 1:1 acetonitrile/25 mM

ammonium bicarbonate (pH 7.8). The gel slices were dried in aSpeedvac concentrator and then rehydrated in 30 μl of 25 mMammonium bicarbonate (pH 7.8) and 20 ng of trypsin. Afterincubation at 37 ◦C for 20 h, the liquid was transferred to a newtube. Tryptic peptides remaining in the gel matrix were extractedfor 40 min at 30 ◦C with 20 μl of 50% (v/v) aqueous acetonitrilecontaining 0.1% formic acid. The combined supernatants wereevaporated in a Speedvac concentrator and dissolved in 8 μl of5% (v/v) aqueous acetonitrile solution containing 0.1% formicacid for MS analysis.

LC-MS/MS analysis

The tryptic peptides were extracted three times to recover allof the peptides from the gel particles. The recovered peptideswere concentrated by drying the final volume of the extractsin a vacuum centrifuge. The concentrated peptides were thenmixed with 20 μl of 0.1% formic acid in 3% acetonitrile inpreparation for LC-MS/MS analysis. Nano LC of the trypticpeptides was performed using Waters Nano LC system equippedwith a Waters C18 nano column (75 μm×15 cm nanoAcquityTM

UPLCTM column). Binary solvent A1 contained 0.1 % formicacid in water and binary solvent B1 contained 0.1% formic acidin acetonitrile. Samples (5 μl) were loaded on to the column.Peptides were eluted from the column with a gradient rangingfrom 2% to 40% binary solvent B1 for 30 min at 0.4 μl/min.The lock mass, [Glu1]fibrinopeptide at 400 fmol/μl, was deliveredfrom the auxiliary pump of the Nano LC system at 0.3 μl/min tothe reference sprayer of the NanoLockSprayTM source.

MS configuration

MS analysis of the tryptic peptides was performed using WatersSynaptTM HDMS. The mass spectrometer was operated in V-modefor all of the measurements. All of the analyses were performedusing a positive-mode Nano ESI with a NanoSpray source. Thelock mass channel was sampled every 30 s. The mass spectrometerwas calibrated using a [Glu1]fibrinopeptide solution (400 fmol/μl)delivered through the reference sprayer of the NanoLockSpraysource. Accurate mass LC-MS/MS data were collected via theDDA (data-dependent acquisition) mode.

1 These authors contributed equally to this study.2 To whom correspondence should be addressed (email [email protected]).


J.-I. Chae and others

Data processing and protein identificationContinuum LC-MS/MS data were processed and used indatabase searches using the PLGS (Protein Lynx GlobalServer) version 2.4 (Waters). The spectra were automaticallysmoothed, background-subtracted, centred and deisotoped withthe automatic tolerance settings. In addition, the charge statewas reduced, and the masses were corrected based on referencescans. Ion detection, clustering and normalization were performedusing PLGS. The processed data were used to search theIPI human version 3.83 [2,3]. Processed ions were sequenced

Figure S1 2-DE gel electrophoresis

Total proteins were isolated from H9, 551 and HD cells at undifferentiated stage, and 2-DE gel electrophoresis was carried out using pH 3–11 non-linear IPG (immobilized pH gradient) strips onSDS/PAGE (12 % gels). Afterwards, the gels were visualized by silver staining. Differentially expressed protein spots are indicated as arrowheads, and the spot numbers are summarized in Table 1 ofthe main text. MW, molecular mass (kDa).

and mapped against the IPI human database using the PLGS andMASCOT DAEMON programs (http://www.matrixscience.com).The PLGS search parameters were defined as follows. Peptideswere restricted to tryptic fragments with a maximum of onemissed cleavage, oxidation of methione (variable modification)and carbamidomethylation of cysteine (fixed modification).The MASCOT search parameters were restricted to trypticpeptides (one missed cleavage, methione oxidation and cysteinecarbamidomethylation) with precursor ion tolerance of 30 p.p.m.and fragment ion tolerance of 0.1 Da in the IPI human database.


http://www.matrixscience.com

Proteomic analysis of Huntington’s disease iPSCs

Figure S2 Classification of differentially expressed proteins in HD-iPSCs

A total of 26 identified proteins were categorized according to biological functions using GeneOntology (http://www.geneontology.org) and their results are shown as a pie chart. Each proteinwas classified as 14 different categories of biological functions, and the percentages indicatethe proportion of the 26 proteins in each group.

Figure S3 Gene regulation networks of differentially expressed proteins in HD-iPSCs

A total of 26 differentially expressed proteins were uploaded to the MetaCoreTM software and mapped by the shortest paths algorithm. Proteins marked with blue and red circles are those identifiedin HD-iPSCs. The colour lines between nodes denote activation/positive (green), inhibition/negative (red) and unspecified (black), and the cyan lines indicate the canonical pathways. GPCR,G-protein-coupled receptor.


http://www.geneontology.org

J.-I. Chae and others

Figure S4 Expression of oxidative stress-related proteins in H9, 551-8, HD and HD2 cells after neuronal differentiation

(A) Total proteins were extracted from H9, 551-8, HD and HD2 cells after neuronal differentiation and used for Western blot analysis. Oxidative stress-related antibodies including SOD1, GST, Gpx1,Prx1, Prx2 and Prx6 were used, and β-actin was used as a loading control. (B) Quantification of protein expression levels after normalization using β-actin. Results are means+−S.E.M for threeindependent experiments. The significance of differences was evaluated by paired two-tailed Student’s t test (SAS version 8.0). §P < 0.01 and *P < 0.001 compared with H9 cells; + P < 0.05,‡P < 0.01 and †P < 0.001 compared with 551-8 cells. (C) Immunocytochemical staining showing the expression of Prx1, Prx2 and Prx6 in each cell. Scale bar = 50 μm.

REFERENCES

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2 Liu, T., Qian, W. J., Strittmatter, E. F., Camp, II, D. G., Anderson, G. A., Thrall, B. D. andSmith, R. D. (2004) High-throughput comparative proteome analysis using a quantitativecysteinyl-peptide enrichment technology. Anal. Chem. 76, 5345–5353

3 Wang, H., Qian, W. J., Mottaz, H. M., Clauss, T. R., Anderson, D. J., Moore, R. J., Camp, II,D. G., Khan, A. H., Sforza, D. M., Pallavicini, M. et al. (2005) Development and evaluationof a micro- and nano-scale proteomic sample preparation method. J. Proteome Res. 4,2397–2403

Received 17 August 2011/21 May 2012; accepted 13 June 2012Published as BJ Immediate Publication 13 June 2012, doi:10.1042/BJ20111495


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