Proteomic Analysis of Monkey Embryonic Stem Cell during

Proteomic Analysis of Monkey Embryonic Stem Cell during Differentiation Davood Nasrabadi,† Mehran Rezaei Larijani,† Leila Pirhaji,† Hamid Gourabi,‡ Abdolhossein Shahverdi,† Hossein Baharvand,*,†,§ and Ghasem Hosseini Salekdeh*,†,| Department of Stem Cells, Cell Science Research Center, Royan Institute, ACECR, Tehran, Iran, Department of Genetics, Cell Science Research Center, Royan Institute, ACECR, Tehran, Iran, Department of Developmental Biology, University of Science and Culture, ACECR, Tehran, Iran, and Department of Physiology and Proteomics, Agricultural Biotechnology Research Institute of Iran, Karaj, Iran Received October 29, 2008

Proteome analyses of embryonic stem cells (ESCs) will help to uncover mechanisms underlying cellular differentiation, expansion, and self-renewal. We applied a 2-DE based proteomic approach coupled with mass spectrometry to identify genes controlling monkey ESCs proliferation and differentiation. We analyzed proteome of ESCs during proliferation and different stages of spontaneous differentiation (day 3, 6, 12, and 30) by embryoid body formation. Out of about 663 ( 15 protein spots reproducible detected on gels, 127 proteins showed significant changes during differentiation. Mass spectrometry analysis of differentially expressed proteins resulted in identification of 95 proteins involved in cell cycle progression and proliferation, cell growth, transcription and chromatin remodeling, translation, metabolism, energy production and Ras signaling. In addition, we created protein interaction maps and distinctly different topology was observed in the protein interaction maps of the monkey ESC proteome clusters compared with maps created using randomly generated sets of proteins. Taken together, the results presented here revealed novel key proteins and pathways that are active during ESC differentiation. Keywords: Proteomics • Embryonic stem cells • Differentiation • monkey • interaction network

Introduction Nonhuman primate species, such as rhesus and cynomolgus monkeys, are important model organisms for biomedical research and behavioral studies. Moreover, their close phylogenetic relationship to man, and hence their clinical relevance increased the value of them. Therapies based on embryonic stem cells (ESCs) of nonhuman primates, would provide extremely accurate models for human ESC-based therapies. Monkey ESCs are remarkably similar to human ESCs in many aspects, including morphology, cell surface marker expression, growth velocity, dependence on feeder cells for self-renewal, and differentiation to ectodermal, mesodermal, and endodermal derivatives. These features indicate that monkey ESCs have the potential to represent a source of primary cell populations for a variety of applications including studies on the functional genomics, cell-based therapy for a broad spectrum of diseases, * To whom correspondence should be addressed. Hossein Baharvand, Department of Stem Cells, Royan Institute, P.O. Box 19395-4644, Tehran, Iran. Tel, +98-21-22172330; fax, +98-21-22414532; e-mail, Baharvand@ RoyanInstitute.org. Ghasem Hosseini Salekdeh, Department of Physiology and Proteomics, Agricultural Biotechnology Research Institute of Iran (ABRII), P.O. Box 31535-1897, Karaj, Iran. Tel, +98-261-2702893; fax, +98-2612704539; e-mail, [email protected]. † Department of Stem Cells, Cell Science Research Center, Royan Institute, ACECR. ‡ Department of Genetics, Cell Science Research Center, Royan Institute, ACECR. § Department of Developmental Biology, University of Science and Culture, ACECR. | Agricultural Biotechnology Research Institute of Iran. 10.1021/pr800880v CCC: $40.75

 2009 American Chemical Society

and targets for drug discovery and toxicology screens. Additionally, it is clear that stem cells are extremely important as research subjects in and by themselves, as the mechanisms underlying cellular differentiation, expansion, and self-renewal can be studied along with aforementioned applications. Microarray and proteomics analyses proved to be strong approaches to elucidate these mechanisms. Extending the analysis to genes that are up- or down-regulated upon differentiation allows identification of putative genes associated with pluripotency that, in turn, could lead to the isolation of factors critical to the propagation of undifferentiated ESCs in a defined medium without the confounding contamination of serum or feeder cells. Recently, Byrne et al.2 reported transcriptional profiling of monkey ESCs by DNA microarray. Despite transcriptome merit, which includes the wide availability of gene expression at the RNA level, such studies did not show the change in protein expression or indeed the steady-state level of a protein and post-translational modification events.3 Accordingly, to identify key regulatory molecules and potential biomarkers, it is becoming increasingly important to characterize the protein profile directly and determine the ‘proteome’ of pluripotent stem cells in addition to their ‘transcriptome’.4 Furthermore, the proteome comparison of ESCs may identify fundamental differences that might explain their distinct and common behavior. The application of proteomics to study molecular mechanisms of ESC differentiation in mouse5-7 and human8 has been reported before. Journal of Proteome Research 2009, 8, 1527–1539 1527 Published on Web 02/18/2009

research articles To further understand the mechanism underlying selfrenewal, we employed a proteomic approach to profile the protein changes of monkey ESCs during differentiation. To our best knowledge, this is the first report utilizing proteomics to discover differentiation associated protein in monkey ESCs.

Materials and Methods Monkey ESC Culture and Sample Preparation. The cynomolgus monkey (Macaca fascicularis) ESC line9 at passages 70-90 was cultured on mouse embryonic fibroblast (MEF) feeder layers derived from explanted day 12.5 fetuses (that was mitotically inactivated with 10 µg/mL mitomycin C (Sigma, M0503)). The medium was Dulbecco’s modified Eagle /Ham’s F-12 medium (DMEM/F12, Gibco, 21331-020) supplemented with 20% knockout serum replacement (KSR, Gibco, 10828-028), 2 mM L-glutamine (Gibco, 25030-024), 0.1 mM β-mercaptoethanol (Sigma; M7522), 1% nonessential amino acids (Gibco, 11140-035), and 100 units/mL penicillin and 100 µg/mL streptomycin (Gibco, 15070-063). Cells were grown in 5% CO2 and 95% humidity, and they were further passaged, every 2-3 days enzymatically with 1 mg/mL of Collagenase type IV pipetting. For use in proteome analysis, ESCs were isolated from MEFs by treatment of the cells by 1 mg/mL collagenase IV, and replating for 2 × 1.5 h onto precoated gelatin (0.1% w/v) plates containing ESC medium. In each case, the supernatant was collected and centrifuged (5 min, 1200 rpm). The cell pellet was washed with 10 mL of PBS and centrifuged. After discarding the PBS, the cell pellet was frozen in liquid nitrogen, and the samples were stored at -80 °C for sample preparation and proteomic analysis. To promote differentiation, ESCs were first cultured in suspension in ESC medium without KSR and containing fetal bovine serum (FBS) (Gibco), where they were developed into multicellular aggregates called embryoid bodies (EBs). The EBs were cultured in suspension for 12 days and then plated on gelatin-coated dishes for 18 days in the same medium to form a pool of spontaneously differentiated cells. We used the term nonlineage-differentiated cells to highlight the fact that these spontaneously differentiated cells represent a mixture of various cell types in the outgrowths of the EBs. For proteomics analysis, we collected cells in three independent replications from ESCs (d0) and differentiating ESCs (dif-ESC) at day 3 (d3), day 6 (d6), day 12 (d12), and day 12 + 18 (d12 + 18 ) d30). Karyotype Analysis. For karyotype analysis, the cells were treated with thymidin (0.01 gr/mL, Sigma) for 16 h at 37 °C in 5% CO2. After washing, the cells were left for 5 h and then treated with Colcemid (Gibco, 0.15 µg/mL, 30 min). Isolated ESCs were exposed to 0.075 M KCl at 37 °C for 16 min and then were fixed with ice-cold 3:1 methanol/glacial acetic acid (repeated three times) and dropped onto precleaned chilled slides. Chromosome spreads were banded and Giemsa stain analyzed for chromosomal status. At least 50 metaphase spreads were screened and 10 banded karyotypes were evaluated for chromosomal rearrangements. Flow Cytometric Analysis of ESCs. All staining was performed in staining buffer consisting of PBS supplemented with 1% heat-inactivated FBS, 0.1% sodium azide, and 2 mM EDTA. The cells were washed two times in staining buffer and fixed in 4% paraformaldehyde 10 min at room temperature. For permeabilization, Triton X-100 0.5% was used for 5 min. Nonspecific antibody binding was blocked for 15 min at 4 °C with a combination of 10% heat-inactivated rat and goat serum 1528

Journal of Proteome Research • Vol. 8, No. 3, 2009

Nasrabadi et al. (prepared in our laboratory) in staining buffer, and (3-5) × 105 cells were used per sample. Cells were incubated with appropriate primary antibodies or appropriate isotype matched controls (eBioscience, or Dako Cytomation) for 1 h at 4 °C. Cells were incubated with primary antibody for 1 h at 37 °C, washed, and incubated with FITC-conjugated secondary antibodies, anti-mouse IgM (1:100, Sigma, F9259), anti-rat IgG (1:100, Sigma, F1763), and anti-mouse IgG (1:200, Sigma, F9006) as appropriate for 1 h at 37 °C. Primary antibodies were anti TRA1-60 (1:100, Chemicon MAB4360), TRA-1-81 (1:100, Chemicon MAB4381), Oct-4 (1:100, Santa Cruz Biotechnology, SC-5279), and SSEA-4 (1:100, Chemicon, MAB4304). The cells were washed twice in staining buffer and incubated for 45 min at 4 °C with fluorescein isothiocyanate (FITC)conjugated anti-mouse IgM (1:100, Sigma, F9259), anti-rat IgG (1:100, Sigma, F1763), and anti-mouse IgG (1:200, Sigma, F9006). Cells were washed as before and fixed with 2% paraformaldehyde. Flow cytometric analysis was performed with a BD-FACS Caliber Flow Cytometer (Becton Dickinson). The experiments were replicated at least three times. Acquired data was analyzed by using WinMDI software. Protein Extraction. Triplicate cell line samples (at least 106 cells per each replication) from ESCs (d0) and dif-ESCs (d3, d6, d12 and d30) were vortexed and suspended in 10% (w/v) trichloroacetic acid in acetone with 0.07% (w/v) dithiothreitol (DTT) at -20 °C for 1 h, followed by centrifugation for 15 min at 35 000g. The pellets were washed with ice-cold acetone containing 0.07% DTT, incubated at -20 °C for 1 h and centrifuged again at 4 °C. This step was repeated three times and then the pellets were lyophilized. The sample powder was then solubilized in lysis buffer [9.5 M urea, 2% (w/v) CHAPS, 0.8% (w/v) Pharmalyte pH 3-10, 1% (w/v) DTT] and the protein concentration was determined by the Bradford assay (Bio-Rad) with BSA as the standard. 2-D Gel Electrophoresis. Isoelectric focusing (IEF) of approximately 120 µg (for preparative gels 1-1.5 mg) of total protein was carried out on immobilized pH gradient 24-cm pH 4-7 L strips on Multiphor II (GE healthcare). The running condition was as follows: 500 V for 1 h, followed by 1000 V for 1 h, and finally 3500 V for 20 h. The focused strips were equilibrated twice for 15 min in 10 mL of equilibration solution. The first equilibration was performed in a solution containing 6 M urea, 30% (w/v) glycerol, 2% (w/v) SDS, 1% (w/v) DTT, and 50 mM Tris-HCl buffer, pH 8.8. The second equilibration was performed in a solution modified by the replacement of DTT by 2.5% (w/v) iodoacetamide. Separation in the second dimension was performed by SDS-PAGE in a vertical slab of acrylamide (12% total monomer, with 2.6% cross-linker) using a Dodeca Cell (Bio-Rad). The analytical 2D gels were stained with silver nitrate as described by Blum et al.10 with some modifications. After termination of the second-dimension run, the gels were immersed in fixative solution (methanol/distilled water/acetic acid, 40/50/10). The gels were sensitized by exposure to thiosulfate reagent (0.02% sodium thiosulfate), followed by impregnation with silver nitrate reagent [0.2% silver nitrate, 0.02% formaldehyde (37%)] for 30 min and developing in developing solution [3% sodium carbonate, 0.05% formaldehyde (37%), 0.0005% sodium thiosulfate]. The development was stopped using 5% Glycine for 5 min and gels were rinsed with water several times prior to densitometry. Preparative gels were stained with colloidal Coomassie Brilliant Blue (CBB) G 250.11

Proteome Analysis of Monkey ESC Differentiation Image Analysis. The silver stained gels were scanned at a resolution of 600 dots per inch on a GS-800 densitometer (BioRad). The scanned gels saved as TIF images for subsequent analysis. Spot quantitation was carried out using the Melanie 3 software (GeneBio, Geneva, Switzerland). The parameters for protein spot detection as follows: number of smooths, 2; Laplacian threshold, 3; partial threshold, 3; saturation, 90; peakness increase, 100; minimum perimeter, 35. After image treatment, spot detection, protein quantification, and spot pairing were carried out based on Melanie 3 default settings. Then, spot pairs were investigated visually and the scatter plots between gels of each data point were displayed to estimate gel similarity and experimental errors. The molecular masses of proteins on gels were determined by coelectrophoresis of standard protein markers (Amersham Pharmacia Biotech) and pI of the proteins were determined by migration of the protein spots on 18 cm IPG (pH 4-7 linear) strips. Three two-dimensional gels per cell line were run and percent volume of each spot was estimated and analyzed by one-way analyses of variance (ANOVA). Only those statistically significant spots (P e 0.01) were accepted and they had to be consistently present in all replications. Protein Identification and Database Search. Protein spots were excised from CBB and silver stained gels, and analyzed using Applied Biosystems 4700 Proteomics Analyzer at Protein and Proteomics Centre in National University of Singapore (Mass Spectrometry Services, Protein, and Proteomics Centre, Department of Biological Sciences). Protein digestion, desalting, and concentration of samples were carried out using Montage In-Gel Digestion Kits (Millipore and Applied Biosystems, Foster City, CA). Stained gel spots were sliced in narrow pieces (1-2 mm diameter) and placed into the ZipPlate wells. The spots were washed and dehydrated by adding 100 µL of 25 mM ammonium bicarbonate (ABC)/5% acetonitrile (HPLC grade, Merck, Darmstadt, Germany), followed by incubation for 30 min. The wells were emptied using vacuum. Then, 100 µL of Buffer (25 mM ABC/50% acetonitrile) was added to each well, followed by incubation for 30 min. This step was repeated once and then 200 µL of 100% acetonitrile was added to each well, followed by incubation for 10 min and removing acetonitrile by vacuum. Proteins were digested by adding 15 µL of the prepared Trypsin Solution [11 ng/µL trypsin (Sequencing grade Modified Trypsin from Promega, Madison, WI) in 25 mM ABC buffer)] to each well, followed by incubation for 3 h at 37 °C. To extract the protein, 8 µL of 100% acetonitrile was added directly onto the resin or the bottom of the well, followed by incubation for 15 min at 37 °C. Then, 130 µL of Extraction/ Wash Solution [0.2% trifluoroacetic acid (TFA) HPLC grade from Sigma-Aldrich, St. Louis, MO] was added to each well. After incubation at room temperature for 30 min, the wells were emptied by partial vacuum (5-7′′ Hg). The peptides were washed twice with 100 µL of Extraction/Wash Solution and dried with vacuum. Then, 20 µL of Elution Solution (0.1% TFA/ 50% acetonitrile) was dispensed into the center of the wells containing gel pieces and peptide extracts were dried on a speed-vacuum at room temperature. The samples were dissolved in solvent consisting of 0.1% trifluoroacetate and 50% acetonitrile in MilliQ Water. A total of 0.5 µL of peptide mixtures was spotted on a 192-well target plate and crystallized with 0.5 µL of R-cyano 4-hydroxy cinnamic acid (CHCA) matrix solution (5 mg/mL). Peptides were analyzed with Applied Biosystems 4700 Proteomics Analyzer

research articles MALDI-TOF/TOF Mass Spectrometer (S/N 34700098, production year 2004, Applied Biosystems, Framingham, MA). Before each analysis, the instrument was calibrated with the Applied Biosystems 4700 Proteomics Analyzer Calibration Mixture. MS data were automatically acquired using Exclusion List containing trypsin autodigestion peaks and selecting the 10 most intense ions for MS/MS. The collision gas used was Nitrogen with the collision energy setting of 1 kV. GPS Explorer software Version 3.5 (Applied Biosystems) was used to create and search files with MASCOT search engine (version 2.0; Matrix Science) for peptide and protein identification. S/N ratio in MS/MS mode for peak identification was greater than 40. Combined MS-MS/MS searches were conducted with the selection of following criteria: NCBInr database 060427 (3 525 863 sequences; 1 211 011 241 residues), all entries, parent ion mass tolerance at 50 ppm, MS/MS mass tolerance of 0.2 Da, carbamidomethylation of cysteine (fixed modification) and methionine oxidation (variable modification). The threshold for positive identification was a MOWSE score of >78 (P < 0.05). Each candidate ID derived from the above search was then manually examined in the Swiss-Prot database to eliminate redundancy of synonymous proteins. A protein’s name and accession number were reported based on SwissProt except for proteins that are only deposited in the NCBI database. The single-protein member of a multiprotein family were singled out by comparing experimental pI and MW with theoretical pI and MW of different members of gene family, the sequenced covered by PMF and MS/MS, and ion-score of MS/MS data. Western Blot Analysis. Fifty micrograms of proteins separated by 12% SDS-PAGE electrophoresis (120 V for 1 h) using a Mini-PROTEAN 3 electrophoresis cell (Bio-Rad) and proteins were transferred to nitrocellulose membrane (Bio-Rad) by semidry blotting (Bio-Rad) using Dunn carbonate transfer buffer (10 mM NaCHO3, 3 mM Na2CO3, 20% methanol). Membranes were blocked for 1.5 h using Western blocker solution (Sigma, W0138) and incubated overnight 4 °C with respective primary monoclonal antibodies, anti-NPM1 (1:1000) and anti-Tpt1 (1:2000). At the end of the incubation time, membranes were rinsed three times (15 min each) with PBSTween-20 (0.05%) and incubated with the peroxidase-conjugated secondary antibodies, anti-mouse (1:180000, Sigma, A9044) and anti-rat (1:160000, Sigma, A5795) as appropriate for 30 min at room temperature. Finally, the blots were visualized using ECL detection reagent (Sigma, CPS-1-120). Subsequently, the films were scanned with densitometer (GS800, Bio-Rad) and quantitative analysis was performed using UVI bandmap software (UVItec, Cambridge, U.K.). To investigate the uniformity of proteins amount loaded on gels, the membranes were stained by Fast Green (FCF, Sigma, F7252). Gene Expression Clustering. Total significant proteins were clustered by k-means clustering method. The correct number of clusters was determined by measuring how similar a gene in a cluster was to genes in its own cluster compared to genes in other clusters which were measured by the average of intracluster and intercluster distance.12,13 MATLAB software (version 7.3) was used for both k-means clustering and k-means clustering profile figures. Heatmaps of k-means clustering are represented using MeV (MultiExperiment Viewer) software. Analysis of Protein Interaction Network. The protein-protein interaction network was extracted using search tool String.14 The network includes 65 proteins (nodes) which match 48 differentially expressed proteins of our analysis and 141 Journal of Proteome Research • Vol. 8, No. 3, 2009 1529

research articles interactions (edges) between them. A protein interaction map was generated from these proteins and compared with protein interaction maps from 100 different randomly generated sets of genes with equal size. Moreover, the number of hub proteins was determined. A protein was designated as a hub if it had g5 interactions with other proteins.15 A distinction between party hubs and date hubs has also been made. The average of Pearson correlation coefficients (PCC) between the hub and each of its respective partners for protein expression was calculated for each hub.15

Results and Discussion Characterization of hESCs. The monkeys ESCs propagated on feeder cells in (Figure 1A) and grow as compact colonies with a high nuclear cytoplasmic ratio and prominent nucleoli (Figure 1B). Moreover, the monkey ESC line had a normal karyotype (42, XY) (Figure 1C). To evaluate the percentage of undifferentiated monkey ESCs, we analyzed the expression of key hESC markers, including Oct-4 (Figure 1D), SSEA-4 (Figure 1E), Tra-1-81 (Figure 1F), Tra-1-60 (Figure 1G), and SSEA-4 and Tra-1-60 or Tra-1-81 using two-color flow cytometry (Figure 1H,I). Under these conditions, the cells expressed Oct-4 (91.66 ( 3.51%), SSEA-4 (94.33 ( 3.51%), Tra-1-60 (88.33 ( 5.51%), and Tra-1-81 (88.33 ( 4.51%) (Figure 1N). The cells were also double positive for SSEA4/Tra-1-60 (80.33 ( 5.51%) and SSEA4/ Tra-1-81 (80.33 ( 4.51%) (Figure 1N). To induce differentiation, monkey ESCs were cultured as EBs. The EBs were cultured in suspension for 12 days (Figure 1, panels J (day3), K (day6), and L (day12), and then plated for 18 days in the same medium (panel M, day12 + 18). Proteome Pattern. Proteomics analyses showed to be a powerful approach to discover the regulatory networks driving differentiation of ESCs.4 In the present study, we applied a 2-DE based proteomics approach to discover ESC-associated proteins by comparing ESCs and dif-ESCs (Figure 2). With the use of Melanie 3 software, we could reproducibly detect 665, 678, 665, 669, and 648 protein spots in three replications in d0, d3, d6, d12, and d30, respectively. Six proteins were only detected in ESCs, three spots were only detected in EBs, 100 spots were down-regulated, and 18 spots were up-regulated in EBs compared to ESCs. Proteins with fluctuated expression levels along the differentiation were excluded from analysis. Protein Identification Using Mass Spectrometry. For MS analysis, 105 ESC-associated proteins with persistent expression patterns were excised from the CBB-stained gels and the proteins therein were subsequently digested with trypsin. The protein spots were analyzed by MALDI TOF-TOF MS/MS on the basis of a combined peptide mass fingerprinting and MS/ MS analysis, leading to the identification of 95 proteins (Table 1 and Supplementary Table 1 in Supporting Information). The protein spots were analyzed by MALDI TOF-TOF MS/MS on the basis of a combined peptide mass fingerprinting and MS/ MS analysis, leading to the identification of 95 proteins (Table 1 and Supplementary Table 1 in Supporting Information). Of them, 66 and 12 proteins were down- or up-regulated, respectively. Thirteen proteins could not be detected at least in one stage of differentiation, whereas two proteins were below the detection limit in ESCs. These identified protein spots were categorized in 5 expression groups (Figure 3) which belonged to different biological process including metabolic process (33%), cell cycle proliferation/regulation (8%), protein modification/transport (18%), transcription/transcriptional regulation (8%), translation/translational regulation (8%), development/ 1530


Nasrabadi et al. biogenesis (3%), signal transduction (1%), DNA replication (3%), response to stress (2%), unclassified proteins (7%), and miscellaneous (9%) (Figure 4). In addition to proteins detected only in ESCs or dif-ESCs, the expression level of proteins markedly varied from more than 17-folds up-regulation to more than 13folds down-regulation during differentiation. Two proteins which were not detected in dif-ESCs were identified as alphacrystallin A chain (spot 41) and NAC alpha (spot 298). The expression level of Lysozyme (spot 4), ATP synthase, H+ transporting (spot 30), deoxyuridine 5′-triphosphate nucleotidohydrolase (spot 31), translationally controlled tumor protein (spot 42), proteasome subunit alpha (spot 73), anhydrolase domain containing 10 (spot 144), 3-hydroxyisobutyrate dehydrogenase (spot 177), clathrin, light polypeptide (spot 206), poly(rC)-binding protein 1 (spot 302), deoxyhypusine hydroxylase (spot 430), serpin B6 (spot 464), adipose differentiationrelated protein (spot 465), and T-complex protein 1 (spot 610) were below detection limit in at least one stage of differentiation. Proteins including adenylate kinase isoenzyme 1 (spot 24), proteasome subunit alpha type 2 (spot 60), eukaryotic translation initiation factor 4E (spot 173), mitochondrial 28S ribosomal protein S22 (spot 350), arginase-2 (spot 441), dimethylarginine dimethylaminohydrolase 1 (spot 559), keratin, type II cytoskeletal 8 (spot 598), protein disulfide-isomerase (spot 659), and Ras GTPase-activating protein-binding protein 1 (spot 679) were down-regulated more than 5-fold in at least one stage of differentiation. One isoform of alpha-1-antiproteinase (spot 756) could not be detected in ESCs and two other isoforms of alpha-1-antiproteinase (spots 727 and 757) and alpha-2-HSglycoprotein (spot 726) were up-regulated more than 10-fold during differentiation. Surprisingly, most of highly regulated proteins belonged to energy production and metabolism (spots 24, 30, 31, 144, 177, 441, and 559), protein synthesis, folding and degradation (spots 42, 73, 173, 298, 350, 464, 659, 727, 756, and 757). Significant changes in expression were also observed in proteins involved in cell proliferation, differentiation, signal transduction, transcription and chromatin remodeling. In addition to several known ESC-associated proteins, differential expression of novel proteins such as RCN1, CDV3 homologue, PCNP, TTC1, G3BP, HDGF, and RUVBL1 were also detected at proteome level. Possible involvements of these functional groups and other major groups in ESCs proliferation and differentiation will be discussed below. Protein Synthesis, Folding and Degradation. The undifferentiated ESCs are rapidly proliferating and coupling of cell growth and cell division is demonstrated by the fact that disruption of ribosome biogenesis impairs proliferation.16 It would not be unexpected to find that several ribosomal proteins and translational regulators are overexpressed in proliferating cells and affect the translation of specific target mRNAs.17,18 We observed that proteins associated with the control of cell growth, such as those involved in the synthesis, and maturation of ribosomes, such as mitochondrial 39S ribosomal protein L46 (spot no. 164), mitochondrial 28S ribosomal protein S22 (spot nos. 350 and 386) or in translational control such as eukaryotic translation initiation factor 1A, X-chromosomal (spot no. 20), elongation factor 1-beta (spot no. 106), eukaryotic translation initiation factor 4E (spot no. 173), eukaryotic translation elongation factor 1 delta (spot nos. 290 and 316) were enriched in undifferentiated ESCs.

Proteome Analysis of Monkey ESC Differentiation

research articles

Figure 1. Morphological and flow cytometry analyses of undifferentiated and differentiated monkey ESCs. (A) Phase contrast photomicrographs of a colony of ESC grown on feeder cells condition. Cells demonstrate a typical undifferentiated morphology with a clear border. (B) High magnification of ESCs. Each cell displays a compact morphology and a high nucleus/cytoplasmic ratio and containing prominent nucleoli typical of undifferentiated ESC. (C) The ESC line had a normal karyotype (42 XY). Representative flow cytometric analysis of key ESC markers including Oct-4 (D), SSEA-4 (E), Tra-1-60 (F), Tra-1-81 (G) expression in ESCs. The cells expressing marker compared with isotype control (white peaks) were termed marker positive population. Percentages of double positive for SSEA4/TRA-1-60 (H) and SSEA-4/TRA-1-81(I) were indicated in the dot plots. The percentages of undifferentiated and differentiated Monkey ESCs were presented in (N). The differentiating EBs were cultured in suspension for 12 days [(J) day3, (K) day6, and (L) day12], and then plated for 18 days in the same medium [(M) day12 + 18].

Three isoforms (spot nos. 659 and 682) of protein disulfide isomerase-associated 3, best known as a chaperone in the endoplasmic reticulum lumen, was identified as highly downregulated proteins (up to 5-fold in spot 659) during differentiation. Some of preferentially expressed proteins in undifferentiated cells were proteasome subunits (spots nos. 60, 73, 165, 195, 220) which may play a key role in ESC proliferations. The

most up-regulated proteins during differentiation were identified as different isoforms of alpha-1-antiproteinase (spot nos. 727, 755, 756, and 757). Further studies are needed to elucidate the detailed and specific roles of these proteins in ESCs proliferation and differentiation. Energy Production and Metabolism. A large number of ESC enriched proteins such as deoxyuridine 5′-triphosphate nucleJournal of Proteome Research • Vol. 8, No. 3, 2009 1531

research articles

Nasrabadi et al.

Figure 2. 2-DE PAGE protein profile of monkey ESCs. Protein (120 µg) was loaded on 24 cm IPG stripe with a linear gradient (pH 4-7) and SDS-PAGE was performed with a 12% gel. Proteins were visualized by silver staining. The identified protein spots are marked with black arrow.

otidohydrolase (spot nos. 23 and 31), adenylate kinase isoenzyme 1 (spot no. 24), ATP-synthase (spot no. 30), acyl-protein thioesterase 1 (spot no. 69), adenine phosphoribosyl transferase (spot no. 72), enoyl-CoA hydratase (spot no. 133), 5′(3′)deoxyribonucleotidase (spot no. 140), anhydrolase domain containing 10 (spot no. 144), phosphoglyceratemutase isozyme (spot no. 158), 3-hydroxyisobutyrate dehydrogenase (spot no.177), ADP-sugar pyrophosphatase (spot no. 332), Transaldolase (spot no. 360), L-lactate dehydrogenase B chain (spot no. 414), arginase-2 (spot no. 441), CKB protein (spot no. 461) and dimethylarginine dimethylaminohydrolase 1 (spot no. 559) were involved in energy production and metabolisms. This implies that the differentiation of ESC is accompanied by the reduction of proteins associated with energy production and metabolisms suggesting more active metabolisms in proliferating ESCs. Wei et al.19 observed that mouse ESCs had a greater capacity to generate ATP, compared to human ESCs, and had a higher metabolic activity powered by mitochondrial oxidation. This was attributed to higher proliferation rate of mouse ESCs which had to be sustained by a higher metabolic rate. Cell Growth, Cell Cycle Progression, and Proliferation. Some of the proteins enriched in proliferating hESCs were involved in cell growth, cell cycle progression, and proliferation including translationally controlled tumor protein (TPT1), nucleophosmin (Npm1), proliferation-inducing gene 20 (RCN1), CDV3 homologue, and PEST-containing nuclear protein (PCNP). 1532


TPT1, also known as IgE-dependent histamine-releasing factor, P23 and TCTP, is a highly conserved and abundantly expressed protein in all eukaryotes. We identified two isoforms of Tpt1 (spots 17 and 42) which were highly down-regulated during differentiation. The expression level of spot 42 reached to the below of detection level at d30. Down-regulation of Tpt1 during differentiation was further confirmed using Westernblotting (Figure 5). Tpt1 is implicated in cellular processes, such as cell growth, cell cycle progression, malignant transformation and protection of cells against various stress conditions and apoptosis (for review, see ref 20). Tpt1 is associated with microtubules and the mitotic spindle in a cell cycle-dependent manner, indicating that it might be involved in processes important for cell proliferation.21 It has been suggested that Tpt1 plays an important role in neural differentiation of mouse ESCs possibly through modulating its binding to Ca2+, tubulin, and Na+K-ATPase.22,23 This view is in line with the observation that P23/TPT1 is preferentially expressed in proliferating, but not in terminally differentiated cells of the polyp Hydra vulgaris.24 The down-regulated protein (spot no. 385) was identified as nucleophosmin (Npm1), a nuclear chaperone. Western blot analysis showed that the level of this protein decreased during differentiation (Figure 5). Npm1 belongs to a family of nuclear chaperones which are found throughout the animal kingdom. Npm1 was first identified as a phosphoprotein that was highly expressed in the nucleolus.25 It is the most studied of the NPM


research articles

Figure 3. K-means clustering of protein expression pattern of 95 differentially expressed at ESCs, d3, d6, d12, and d30. Input data for preprocessing was the induction factor that was calculated by dividing the percentage volume of each protein spot at the defined EB stage by the percentage volume of the same protein spot at the undifferentiated stage. One-dimensional K-means gene clustering was performed and proteins were clustered in 6 groups (A-F). Mass spectrometry identified proteins are shown on the right. Sampling stages are shown on the top. All quantitative information is transmitted using a color scale in which the color ranges from green (-1) for the highest down-regulation to red (+1) for the highest up-regulation. Dark boxes (0) indicate no changes in expression pattern of EBs compare to ESC. Journal of Proteome Research • Vol. 8, No. 3, 2009 1533

1534

4 11 17 20 23 24 30 31 41 42 48 60 69 70 72 73 78 86 91 93 100 101 106 133 139 140 141 144 149 158 160 164 165 173 174 177 190 195 202 206 219 220 263 264 275 286 290 298 302 305

spot ID

a

exp. pI/MW

4.4/22 4.8/22 5.0/26 5.2/22 5.3/20 5.4/20 5.6/25 5.6/25 5.8/22 5.8/20 4.8/27 6.4/22 6.6/26 6.5/26 6.4/26 6.3/24 5.9/26 5.5/26 5.0/27 4.9/29 4.7/30 4.6/30 4.6/33 5.9/28 6.0/29 6.0/27 6.1/27 6.1/28 6.3/28 6.8/30 6.5/30 6.3/30 6.1/30 6.0/31 6.0/31 5.9/30 5.6/32 5.5/31 4.5/35 4.5/36 5.8/33 5.9/33 6.2/36 6.1/37 6.1/40 5.7/39 5.0/37 5.8/39 4.4/38 4.4/37

b

theo. pI/MW

9.2/15 5.1/53 4.8/19 5.0/16 9.7/27 5.7/21 5.5/18 6.1/17 5.7/19 4.8/19 6.8/18 6.9/25 6.0/23 6.6/22 6.3/20 4.7/26 5.9/23 5.7/30 4.9/18 4.8/28 5.7/24 4.7/27 4.5/24 8.3/31 5.9/25 6.2/23 5.9/25 8.8/33 6.1/25 6.7/28 6.8/29 6.5/31 6.5/24 5.8/25 5.6/29 8.4/35 5.7/29 5.4/27 5.5/11 5.5/11 6.1/27 5.7/29 5.13/59 6.0/27 6.11/36 6.25/57 4.8/28 4.57/22 6.7/37 4.5/23

c

accession no. P61626 Q4R4X4 P61288 P47813 P33316 Q9R0Y5 B1ASE1 P33316-2 P02488 P13693 Q8WW12 P25787 O75608-2 Q5RCG9 Q6PK77 Q5U0A0 Q28514 P15497 Q9NWV4 Q9CQV8 Q5R587 Q5R651 P24534 P30084 Q5R4J7 Q8TCD5 Q5R4J7 Q9NUJ1 Q9TSM5 P18669 Q3MJC3 Q9H2W6 O00233 P06730 Q9Y5Y2 P31937 O95865 Q9UL46 Q2PFR5 Q53XZ1 Q9UKY7 Q4R4V3 P13645 Q9UKY7 Q6IA55 Q59ET3 Q4VBZ6 Q6Y256 Q15365 Q5R9I9

d

LYZ VIM TPT1 EIF1AX DUT Ak1 Atp5h DUT CRYAA TPT1 PCNP PSMA2 LYPLA1 VBP1 Aprt Psma5 GSTP1 APOA1 C1orf123 Ywhab POLR2E YWHAZ EEF1B2 ECHS1 GRB2 NT5C GRB2 ABHD10 GSTM1 PGAM1 ERP29 MRPL46 PSMD9 EIF4E NUBP2 HIBADH DDAH2 PSME2 CLTA CLTA CDV3 PSME3 KRT10 CDV3 SRR CCT6A EEF1D NACA PCBP1 NACA

gene name

protein name Lysozyme Vimentin Translationally controlled 1 Eukaryotic translation initiation factor 1A Deoxyuridine 5′-triphosphate nucleotidohydrolase Adenylate kinase isoenzyme 1 ATP synthase, H+ transporting Deoxyuridine 5′-triphosphate nucleotidohydrolase Alpha-Crystallin A chain Translationally controlled tumor protein PEST proteolytic signal-containing nuclear protein Proteasome subunit alpha type 2 Acyl-protein thioesterase 1 Prefoldin subunit 3 Adenine phosphoribosyl transferase Proteasome subunit alpha Glutathione S-transferase Apolipoprotein A-I UPF0587 protein C1orf123 14-3-3 protein beta/alpha DNA-directed RNA polymerase II 14-3-3 protein zeta/delta Elongation factor 1-beta Enoyl-CoA hydratase Growth factor receptor-bound protein 2 5′(3′)-deoxyribonucleotidase Growth factor receptor-bound protein 2 Anhydrolase domain containing 10 Glutathione S-transferase Mu 1 Phosphoglyceratemutase isozyme Endoplasmic reticulum protein 29 39S ribosomal protein L46, mitochondrial 26S proteasome non-ATPase regulatory Eukaryotic translation initiation factor 4E Nucleotide-binding protein 2 3-hydroxyisobutyrate dehydrogenase N(G),N(G)-dimethylarginine dimethylaminohydrolase 2 Proteasome activator complex subunit 2 Clathrin, light polypeptide Clathrin, light polypeptide Protein CDV3 homologue Proteasome activator complex subunit 3 Keratin, type I cytoskeletal 10 Protein CDV3 homologue SRR protein chaperonin subunit 6A Eukaryotic translation elongation factor 1 delta NAC alpha Poly(rC)-binding protein 1 Nascent polypeptide-associated complex subunit alpha

Table 1. Proteins Identified Using MALDI TOF/TOF Mass Spectrometry

score/ % cov 101/33 165/13 151/47 297/44 572/60 521/59 107/41 520/65 411/40 288/50 144/28 720/55 448/54 121/38 429/65 172/41 394/50 310/52 146/73 100/39 326/55 116/36 361/40 442/46 661/84 584/62 247/57 136/34 122/41 441/57 537/47 249/29 86/37 95/18 257/27 257/42 415/30 188/37 185/28 123/28 205/41 363/50 187/33 198/36 268/43 483/33 112/29 391/28 142/20 96/12

e

MS/ MS-MS 7/1 11/5 14/4 11/4 15/5 17/7 8/3 16/6 14/6 16/6 7/3 20/9 13/5 9/1 14/6 11/3 17/7 21/7 10/3 12/2 18/6 15/3 14/6 22/6 30/10 20/8 15/5 12/2 12/3 18/6 20/8 12/4 9/2 6/2 12/6 20/6 15/6 5/16 4/2 4/2 11/3 20/7 19/3 14/5 17/7 29/9 12/4 9/4 10/3 5/2

f

d6 ND -1.58 -1.39 -1.26 -1.84* -1.84* ND ND ND -1.81** -1.67* -3.08 -2.71 -1.28* -1.15 ND -1.90* -1.14 1.50 -2.21* -1.56 -1.15 -2.47 -1.43** -1.25 -1.69 -1.36 -3.32 -1.94* -2.05* -1.34 -1.46* -1.51 -1.39* -2.51** ND 1.06* -1.69 -1.22 ND -1.56* -1.13 -1.99* -2.99* -1.74* -1.79* -4.06 ND ND -2.19**

d3 -3.91* -1.23 -1.26 1.07 -1.84* -1.65* 1.00 1.74 ND -2.13** -1.38 -1.87* -2.11* -1.23* -1.37* 1.18 -2.00* -1.04 1.15 -1.47* -1.73* -2.09* -1.08 -1.67** 1.03 -1.15 -1.66* -2.07 -1.71* -1.65* 1.21 -1.11 1.24 -1.15 -1.47* -5.10* -1.23 -1.88 -1.61 -1.37 -1.27 -1.27 -2.03* -2.81* -1.96* -1.79** -1.56* ND -3.58 -1.40

ND -3.97* -2.10 -1.62 -2.67* -1.77** ND ND ND -1.99* -1.67* -2.18 -2.05 -1.13 -1.39 ND -1.35 -1.07 2.14* -1.21 -2.70* -1.37** -2.72 -1.42** -1.58** -1.50 -1.21* ND 1.33 -2.85** -1.68* -2.03** -2.38* -1.72** -1.94** -3.82* 1.91** -3.22* 2.38* ND -1.39 1.00 -1.96* -1.89* -1.60 -1.83* -1.84** ND -2.28 -1.28*

d12

expressiong d30 ND -1.82 -2.34** -2.88* -2.76* -9.57** ND ND ND ND -2.18** -6.98** -2.78* -1.98* -2.18* ND -1.38 -2.22* -1.07 -1.91 -1.91* -1.47* -3.55* -1.90* -2.00* -2.11* -1.63** ND 1.12 -1.64 -2.68* -1.87** -1.80* -6.55* -2.07** -2.41 1.25 -2.63* 1.79* ND -2.00* -2.37* -2.41* -2.32 -1.71* -1.71* -1.91* ND ND -1.59**

research articles


Nasrabadi et al.

spot ID

exp. pI/MW

4.4/38 5.0/36 4.7/32 5.2/36 6.6/39 6.4/38 6.3/43 6.3/40 6.2/40 5.9/42 5.9/37 4.8/33 4.8/38 4.7/32 4.9/41 4.9/41 5.4/36 5.8/42 5.7/41 5.7/41 4.8/39 4.7/40 6.4/49 5.8/48 5.9/47 6.8/51 6.6/52 6.3/54 6.0/53 5.7/51 6.4/65 6.5/63 6.9/65 6.3/64 6.4/83 6.0/58 5.8/77 6.0/59 5.9/59 4.5/63 4.5/63 5.3/64 5.2/64 5.1/64 6.1/32

b

theo. pI/MW

4.5/23 4.8/28 4.9/35 4.9/24 7.7/41 6.4/37 5.9/47 4.6/28 7.7/41 5.6/42 5.7/36 4.9/37 4.4/19 4.9/40 4.8/33 6.0/38 5.4/36 5.3/42 5.4/43 6.3/48 4.7/32 4.7/26 6.4/47 5.6/42 6.1/54 5.5/31 6.0/50 6.0/57 5.9/49 5.5/53 6.3/60 6.5/65 6.2/60 5.9/73 6.0 /69 5.9/57 5.4/52 5.9/57 5.4/48 5.3/39 6.0/46 6.0/46 6.0/46 6.0/46 8.9/19

c

accession no. Q5R9I9 Q4VBZ6 Q4R4H7 Q9UKK9 P82650 P37837 Q4R596 Q9BYG9 P82650 P49903 Q4R5B6 Q9BU89 Q15293 Q96S82 Q99614 P78540 Q96IZ0 Q6FG40 Q4R3G2 Q99541 P58774 P51858 P17182 Q59FV6 Q5REK3 O94760 Q9Y265 Q4R6F8 P31943 P05787 P80318 P68133 Q4R963 Q3ZCH0 P15311 P27773 Q13283 P27773 B2M1R6 P12763 P34955 P34955 P34955 P34955 Q923W4

d

gene name NACA EEF1D ANXA5 NUDT5 MRPS22 TALDO1 AHCY NPM1 MRPS22 SEPHS1 LDHB DOHH RCN1 UBL7 TTC1 ARG2 PAWR CKB SERPINB6 ADFP Tpm2 HDGF Eno1 None PMPCB DDAH1 RUVBL1 CCT2 HNRNPH1 KRT8 Cct3 ACTA1 CCT3 HSPA9B EZR Pdia3 G3BP Pdia3 Hnrpk AHSG SERPINA1 SERPINA1 SERPINA1 SERPINA1 Hdgfrp3

protein name Nascent polypeptide-associated complex subunit alpha Eukaryotic translation elongation factor 1 delta Annexin A5 ADP-sugar pyrophosphatase Mitochondrial 28S ribosomal protein S22 Transaldolase Adenosylhomocysteinase Nucleophosmin/B23.2 28S ribosomal protein S22, mitochondrial Selenide, water dikinase 1 L-lactate dehydrogenase B chain Deoxyhypusine hydroxylase proliferation-inducing gene 20 Ubiquitin-like protein 7 Tetratricopeptide repeat protein 1 Arginase-2, mitochondrial PRKC apoptosis WT1 regulator protein CKB protein Serpin B6 Adipose differentiation-related protein Tropomyosin beta chain Hepatoma-derived growth factor Alpha-enolase ARP3 actin-related protein 3 homologue variant Mitochondrial-processing peptidase subunit beta Dimethylarginine dimethylaminohydrolase 1 RuvB-like 1 T-complex protein 1 subunit beta Heterogeneous nuclear ribonucleoprotein H Keratin, type II cytoskeletal 8 T-complex protein 1 subunit gamma Actin, alpha skeletal muscle T-complex protein 1 subunit gamma Heat shock 70 kDa protein 9B Ezrin Protein disulfide-isomerase Ras GTPase-activating protein-binding protein 1 Protein disulfide-isomerase A3 Heterogeneous nuclear ribonucleoprotein K Alpha-2-HS-glycoprotein Alpha-1-antiproteinase Alpha-1-antiproteinase Alpha-1-antiproteinase Alpha-1-antiproteinase Hepatoma-derived growth factor-related protein 3

score/ % cov 144/40 112/29 529/61 89/20 332/38 89/14 306/38 137/27 172/17 245/27 476/47 150/37 226/33 235/35 116/34 391/44 232/31 483/47 483/49 106/40 202/38 114/32 125/19 112/22 116/19 466/44 87/26 267/20 314/35 198/25 208/26 219/29 210/17 430/35 286/30 485/46 470/53 418/49 146/37 338/28 692/29 348/10 428/27 249/25 106/27

e

MS/ MS-MS 9/4 12/5 26/9 6/2 22/8 4/2 28//7 9/3 8/3 18/8 26/8 11/2 13/3 11/4 13/4 19/6 10/3 24/7 23/7 4/2 16/5 10/3 12/4 14/3 12/4 19/6 13/4 12/6 20/6 17/5 25/5 12/4 12/5 25/7 25/9 29/8 29/7 30/9 18/4 12/4 23/9 20/7 22/7 17/6 8/3

f

d6 1.32 -1.55 P 1.35 -1.48* -1.36* -1.17 -1.43 -1.96* -1.05 -1.74 -1.32 -1.41 1.47 -1.33 -1.45 -2.56** 1.22* ND -1.68 -5.05 -1.29 -2.75* -1.20 -1.12 -3.29** -1.35* -1.69* -1.30 -1.27 -2.05* -1.63 -1.06 -1.76 -3.06** -1.63* -2.21* -1.95 -4.36** 13.78* 18.15* 4.58* P 18.52 -2.03

d3 -1.47* -1.60* P 1.61* -1.81 -1.38 1.41 -1.83* -1.20 1.14 -1.08 1.29* -1.30 1.13 -1.19 -1.68* -1.44 -1.13 -4.13* 1.28 -2.72** -3.93* -1.07 -2.50* -1.41 -1.89* -1.26 -1.79* -2.73** -1.19 -1.26 -1.38 -1.38 -1.49 -1.69* -1.34 -1.08 -1.66 -3.55** 11.88** 15.98** 4.60** P 17.14** -1.21

-1.41 -1.14 P 1.62 -1.61* 1.29 2.22* -1.69* -1.82* -1.55* -1.55* ND -2.47** 1.43* -1.19 -1.85 -2.38** 1.78* ND -1.32 -5.15* 1.11 -2.75* -1.50* -1.05 -2.42* -1.06 -1.35 -1.42 1.05 1.17 -1.54 1.26 1.01 -1.24 -5.40** -4.23* -3.21** -2.40** 12.26* 16.05* 3.22* P 14.04* 1.33

d12

expressiong d30 -2.04** -1.80* P 3.13** -8.84** -2.13** -1.42 -1.85* -1.58 -3.18** -3.11** ND -1.97* 2.26* -2.18* -12.89** -1.63* 2.83* -2.75* ND -1.38** 1.67 -1.11 -2.04 -2.59* -13.39** -1.87* -1.65* -1.51 -9.85* -3.54** -4.16* ND -3.61* -2.13* -1.86 -6.15** -3.04** -1.24 14.80* 17.84* 3.82* P 17.60* 2.27*

a The numbering corresponds to the 2D gel in Figure 2. b Experimental pI and MW. c Theoretical pI and MW. d Accession number in Swiss-Prot. e Mascot score and percent coverage resulted from combined MS-MS/MS search. f Number of peptide identified by PMF and MS/MS. g Fold change in expression (percent volume of differentiated cells/percent volume of ESCs) during differentiation d3, three days after differentiation; d6, six days after differentiation; d12, 12 days after differentiation; d30, 30 days after differentiation; ND, protein was not detected in dif-ESCs; P, protein was only detected in dif-ESCs. *Change statistically significant in dif-ESC compared to ESC when P < 0.05. **Change statistically significant in dif-ESC compared to ESC when P < 0.01.

306 316 320 332 350 360 378 385 386 394 414 430 431 436 440 441 458 461 464 465 512 513 541 553 554 559 568 577 591 598 601 602 610 632 652 659 679 682 683 726 727 755 756 757 820

a

Table 1. Continued


research articles

Journal of Proteome Research • Vol. 8, No. 3, 2009 1535

research articles

Figure 4. Functional annotation of the identified proteins classified by biological function

Figure 5. Western blots of total protein extracts of monkey ESCs. Fifty micrograms of proteins extracted from three independent replications of ESCs and Dif-ESCs was subjected to SDS-PAGE followed by Western blotting. ESCs and Dif-ESCs were analyzed with antibodies against Tpt1 and Npm1, which were markedly enriched in monkey ESCs.

family members, largely due to the fact that it is often up-regulated in tumors and is a frequent target of genetic alterations in cancers. Npm1 is more abundant in proliferating cells than in normal resting cells.26 It showed to be among the most abundant protein of proliferating human ESCs27 and were down-regulated during differentiation in mouse ESC.6 Wang et al.28 showed that the suppression of Npm1 expression in ESCs resulted in reduced cell proliferation and suggested that Npm1 may have an essential role in ESC proliferation. We also observed down-regulation of proliferation-inducing gene 20 (spot no. 431). This protein, also know as reticulocalbin 1 (RCN1), is a calcium-binding protein located in the lumen of the ER. The protein contains six conserved regions with similarity to a high affinity Ca2+-binding motif, the EF-hand. High conservation of amino acid residues outside of these 1536


Nasrabadi et al. motifs, in comparison to mouse reticulocalbin, is consistent with a possible biochemical function besides that of calcium binding. It is assumed to play a role in protein synthesis, modification and intracellular transport because of its localization.29 The RCN1 molecule is necessary for normal behavior of cells because homozygous deletion in mice of RCN1 could contribute to the lethality.30 It has been reported that RCN1 was overexpressed in hepatoma cancer cells compared to normal liver cells.31 Tong et al.32 showed that suberonylanilide hydroxamic acid, which remarkably inhibited proliferation of hepatocarcinoma cells (HepG2), suppressed the expression of RCN1. These studies suggested that RCN1 may be implicated with cell proliferation. Spots 219 and 264 were down-regulated during differentiation and were identified as CDV3 homologue, a protein possibility involved in cell division and proliferation. Differentially expression analysis pf genes associated with HER-2/ neu overexpression in human breast cancer revealed that CDV3 is involved in cell proliferation.12 By performing a comparative and mutational analysis, Miyagishima et al. (2005) suggested that CDV3 was involved in cell division and mediated divisionsite determination in cyanobacteria. A PEST-containing nuclear protein (PCNP) was also identified as differentially expressed proteins (spot no. 48). Proteins with ‘PEST sequences’ are known to be degraded rapidly, often via the ubiquitin-proteasome pathway. PEST proteins are generally involved in cell regulatory mechanisms, and proteolysis plays major roles in controlling their functions.33 Mori et al.34 suggested that PCNP and its ubiquitin ligase (Np95/ ICBP90-like RING finger protein) may constitute a novel signaling pathway with some relation to cell proliferation. Expression Pattern of Proteins Involved in Transcription. Several protein involved in transcription showed to be down-regulated during differentiation including DNAdirected RNA polymerase II (spot no. 100), Poly(rC)-binding protein 1 (spot no. 302), RuvB-like 1 (spot no. 568), hepatomaderived growth factor (spot no. 513), heterogeneous nuclear ribonucleoprotein H (spot no. 591), and heterogeneous nuclear ribonucleoprotein K (spot no. 683),. Hepatoma-derived growth factor (HDGF) was originally identified in a human hepatomaderived cell line but is ubiquitously expressed in several cell lines and normal tissues.35 Sequence analysis of HDGF revealed that it shares homology with the high mobility group (HMG) protein. It has recently been shown that HMG proteins have a significant relation to cellular proliferation. HDGF might show growth stimulating activity by acting as a transcription factor after internalization. RUVBL1, also know as Rvb1 and Pontin, has been reported to be components of the ATP-dependent chromatin-remodeling complexes and affects genes regulated by the complex.36 RUVBL1 binds to the transactivation region of c-Myc37 to remodel the chromatin to activate or repress the gene expression linked to c-Myc. Ras Signaling. Ras is a small GTPase responsible for transducing signals from a vast array of receptor tyrosine kinases and other receptors. It acts as a molecular switch, cycling between the active, GTP-bound form and the inactive GDPbound form. Ras biological activity is controlled by a regulated GDP/GTP cycle. The cellular control of GDP/GTP cycling is modulated by two types of regulatory proteins. Guanine nucleotide exchange factors (GEFs) promote formation of the active GTP-bound state and Ras GTPase activating proteins (GAPs) promotes formation of the inactive GDP-bound state.38,39


research articles

Figure 6. Hub protein network in monkey ESC clusters. The protein-protein interaction network was extracted using search tool String.14 Hubs were defined as proteins with at least five determined protein interactions among the regulated proteins.15 We showed two types of hub including party hubs (marked with green stars), which interact with most of their partners simultaneously, and date hubs (marked with red stars), which bind their different partners at different times or locations.

Two proteins likely involved in ras signaling, tetratricopeptide repeat protein 1 (TTC1), also known as TPR1 (spot no. 440), and Ras-GTPase activating protein SH3 domain binding protein (G3BP) (spot no. 679) were identified in our study. TTC1 is a 292-amino-acid protein with three TPR motifs usually present in tandem arrays of 3-16 units. The proteins harboring TPR motifs are important for basic cellular functions, including DNA replication, transcriptional control, cell division, protein chaperoning, and mitochondrial and peroxisomal protein transport.40 TPR motifs generally mediate protein-protein interactions. Using Saccharomyces cerevisiae two-hybrid screening, Marty et al.41 found that TTC1 was a novel adaptor protein for Ras and selected Ga´ proteins that may be involved in protein-protein interaction relating to G-protein signaling. It was found that TTC1 interacts with Ras, preferably Ras-GTP, and its overexpression promoted accumulation of active Ras.41 G3BP can unwind partial RNA/DNA and RNA/RNA duplexes in an ATP-dependent fashion. This enzyme is a member of the heterogeneous nuclear RNA-binding proteins and is also an element of the Ras signal transduction pathway. The first G3BP

family member to be discovered, G3BP1, was isolated in a screen for proteins that bind the SH3 domain of Ras GTPase Activating Protein (RasGAP).42 The RasGAP G3BP1 complex detected in proliferating cells is consistent with the interpretation that both proteins are recruited to activated Ras.43 In addition, G3BP1 is up-regulated in proliferating Retinal Pigment Epithelial (RPE) cells, which are characteristic of proliferative vitreoretinopathy (PVR).44 G3BP1 may bind and regulate c-Myc mRNA. c-Myc is an important transcription factor predominantly involved in the regulation of cell cycle progression.45 Cytoskeleton. The current study demonstrates that specific proteins related to cytoskeleton and cell shape are downregulated during differentiation including vimentin (spot no. 11), keratin, type I cytoskeletal 10 (spot no. 263), ARP3 actinrelated protein 3 (spot no. 553), keratin, type II cytoskeletal 8 (spot no. 598), actin alpha skeletal muscle (spot no. 602), and ezrin (spot no. 652). While differentiation may cause changes in cell shape, several studies have noted that changes in cell shape themselves can regulate biological processes such as proliferation46 and differentiation.47,48 Journal of Proteome Research • Vol. 8, No. 3, 2009 1537

research articles Human mesenchymal stem cells (hMSCs) differentiate into adipocytes, osteoblasts, and chondrocytes when exposed to various growth factor combinations.49 It was shown that differentiation into these lineages only occurred if cells were plated at appropriate densities. McBeath et al.50 suggested that these differences in cell density confer differences in cell shape and that cell shape acts as a cue in the commitment process. Changes in cell shape may be transduced into a regulatory signal by several structures in the cell, including the actin cytoskeleton itself.51 It has been reported that mechanical tension, acting through the actin filament complex, can control the differentiation status of adult stromal stem cells.50 This process could be manipulated through the RhoA protein, a GTPase affecting the actin cytoskeleton50 Proteins Interactions Map. Protein interactions among the regulated proteins were explored and an interaction map was created using STRING based on reported protein interaction (Figure 6). Moreover, the presence of hubs was determined among the nodes of protein-protein interactions. In total, 24 hubs were identified (Supplemental Table 2 in Supporting Information) whereas only 14.4 hubs were identified on average in the equally sized random data sets (Supplemental Figure 1 in Supporting Information). The results illustrated that in real networks the number of hub proteins were significantly (Pvalue , 10-5) greater than random networks. Fifty-six out of 141 edges of protein-protein interaction networks were between hub proteins which revealed a higher connectivity between them compared with randomly generated data sets that show lower connectivity. The average PCCs were calculated only for the hubs with available expression values for all of their respective partners (Supplementary Table 3 in Supporting Information). We applied an arbitrary average PCC cutoff of 0.4 to discriminate party hubs, which interact with most of their partners simultaneously, with the high average of PCCs from date hubs, which interact with their partners at different times or locations. We also measured the average PCCs for two proteins AK1 and YWHAZ with one and two of their interaction partners, respectively. The average PCCs for both of them are lower than 0.4 in any value for these two interaction partners. Our analysis suggested CCT3, AK1, and YWHAZ as date hubs and PSMA2, PSMA5, and PSMD9 as party hubs. In an interactome network, the date hubs as regulators, mediators or adaptors connect modules.15 Party hub represent integeral elements within distinct modules and tend to function at a lower level of the organization of the proteome.15 Party hubs in our interaction networks are involved in a wide range of molecular process including signal transduction, metabolisms, and protein folding. The major party hub, tyrosine 3/tryptophan 5-monooxygenase activation protein, zeta polypeptide (YWHAZ), belongs to the 14-3-3 family of proteins which mediate signal transduction by binding to phosphoserinecontaining proteins. The antiapoptetic function of YWHAZ has also been suggested.52 Additional studies are needed to elucidate the importance of the specific hub proteins identified here. Furthermore, these proteins may represent interesting targets for knockout and overexpression studies as they potentially serve as key proteins in ESC differentiation.

Conclusion The current study has characterized changes in proteome pattern of monkey ESCs during differentiation. Our results 1538


Nasrabadi et al. revealed that the differentially regulated proteins were involved in various biological processes within hESCs. Of particular interest was a remarkable change in expression of proteins involved in metabolisms and protein synthesis, folding and degradation. In addition to several known ESC-associated proteins, we observed changes in expression of novel key proteins involved in cell proliferation (RCN1, CDV3 homologue, PCNP), ras signaling (TTC1 and G3BP), transcription regulation and chromatin remodeling (HDGF, RUVBL1). The results presented here suggest the possible implication of these proteins in ESCs differentiation. However, further studies are still needed to elucidate the precise function of these differentially expressed proteins. Abbreviations: ESCs, embryonic stem cells; EBs embryoid bodies; dif-ESCs, differentiated ESCs.

Acknowledgment. We would like to thank Vahid Hajhosseini for his help in analyzing data. This project was funded by grants from Royan Institute. Supporting Information Available: Supplementary Figure 1, the interaction map of real network with 24 hub proteins compared with randomly generated interaction map with 12 hub proteins; Supplementary Table 1, list of proteins identified using MALDI TOF/TOF mass spectrometry; Supplementary Table 2, list of hub proteins and their degree of interaction; Supplementary Table 3, average PCCs of the hubs. This material is available free of charge via the Internet at http://pubs.acs.org. References (1) Wolf, D. P.; Kuo, H. C.; Pau, K. Y. F.; Lester, L. Progress with nonhuman primate embryonic stem cells. Biol. Reprod. 2004, 71, 1766–1771. (2) Byrne, J. A.; Mitalipov, S. M.; Clepper, L.; Wolf, D. P. Transcriptional profiling of rhesus monkey embryonic stem cells. Biol. Reprod. 2006, 75 (6), 908. (3) Gygi, S. P.; Rochon, Y.; Franza, B. R.; Aebersold, R. Correlation between protein and mRNA abundance in yeast. Mol. Cell. Biol. 1999, 19 (3), 1720. (4) Baharvand, H.; Fathi, A.; van Hoof, D.; Salekdeh, G. H. Concise review: trends in stem cell proteomics. Stem Cells 2007, 25 (8), 1888. (5) Kurisaki, A.; Hamazaki, T. S.; Okabayashi, K.; Iida, T.; Nishine, T.; Chonan, R.; Kido, H.; Tsunasawa, S.; Nishimura, O.; Asashima, M.; Sugino, H. Chromatin-related proteins in pluripotent mouse embryonic stem cells are downregulated after removal of leukemia inhibitory factor. Biochem. Biophys. Res. Commun. 2005, 335 (3), 667–675. (6) Baharvand, H.; Fathi, A.; Gourabi, H.; Mollamohammadi, S.; Salekdeh, G. H. Identification of mouse embryonic stem cellassociated proteins. J. Proteome Res. 2008, 7 (1), 412–423. (7) Guo, X.; Ying, W.; Wan, J.; Hu, Z.; Qian, X.; Zhang, H.; He, F. Proteomic characterization of early-stage differentiation of mouse embryonic stem cells into neural cells induced by all-trans retinoic acid in vitro. Electrophoresis 2001, 22 (14), 3067–3075. (8) Van Hoof, D.; Passier, R.; Ward-Van Oostwaard, D.; Pinkse, M. W.; Heck, A. J.; Mummery, C. L.; Krijgsveld, J. A quest for human and mouse embryonic stem cell-specific proteins. Mol. Cell. Proteomics 2006, 5 (7), 1261–1273. (9) Suemori, H.; Nakatsuji, N. Growth and differentiation of cynomolgus monkey ES cells. Methods Enzymol. 2003, 365, 419–429. (10) Blum, H.; Beier, H.; Gross, H. J. Improved silver staining of plant proteins, RNA and DNA in polyacrylamide gels. Electrophoresis 1987, 8, 93–99. (11) Neuhoff, V.; Arold, N; Taube, D; Ehrhardt, W. Improved staining of proteins in polyacrylamide gels including isoelectric focusing gels with clear background at nanogram sensitivity using Coomassie Brilliant Blue G-250 and R-250. Electrophoresis 1988, 9 (6), 255–262. (12) Ray, S.; Turi, R. H. Determination of number of clusters in k-means clustering and application in colour image segmentation. Proceed-

research articles


(13)

(14)

(15)

(16) (17) (18)

(19)

(20) (21) (22) (23) (24) (25)

(26)

(27) (28)

(29)

(30)

(31)

(32)

ings of the 4th International Conference on Advances in Pattern Recognition and Digital Techniques (ICAPRDT’99), Calcutta, India 1999, pp 137-143. Kaufman, L.; Rousseeuw, P. J. Finding Groups in Data. An Introduction to Cluster Analysis. Wiley Series in Probability and Mathematical Statistics. Applied Probability and Statistics; Wiley: New York, 1990. von Mering, C.; Jensen, L. J.; Kuhn, M.; Chaffron, S.; Doerks, T.; Kruger, B.; Snel, B.; Bork, P. STRING 7srecent developments in the integration and prediction of protein interactions. Nucleic Acids Res. 2007, 35 (Database issue), D358. Han, J. D. J.; Bertin, N.; Hao, T.; Goldberg, D. S.; Berriz, G. F.; Zhang, L. V.; Dupuy, D.; Walhout, A. J. M.; Cusick, M. E.; Roth, F. P. Evidence for dynamically organized modularity in the yeast protein-protein interaction network. Nature 2004, 430 (6995), 88– 93. Jorgensen, P.; Tyers, M. How Cells Coordinate Growth and Division. Curr. Biol. 2004, 14 (23), 1014–1027. Ruggero, D.; Pandolfi, P. P. Does the ribosome translate cancer. Nat. Rev. Cancer 2003, 3 (3), 179–192. Desrivie`res, S.; Kuhn, K.; Mu ¨ ller, J.; Gla¨ser, M.; Laria, N. C. P.; Korder, J.; Sonnentag, M.; Neumann, T.; Schwarz, J.; Scha¨fer, J. Comparison of the nuclear proteomes of mammary epithelial cells at different stages of functional differentiation. Proteomics 2007, 2007, 2019–2037. Wei, C. L.; Miura, T.; Robson, P.; Lim, S. K.; Xu, X. Q.; Lee, M. Y. C.; Gupta, S.; Stanton, L.; Luo, Y.; Schmitt, J. Transcriptome profiling of human and murine ESCs identifies divergent paths required to maintain the stem cell state. Stem Cells 2005, 23, 166–185. Bommer, U. A.; Thiele, B. J. The translationally controlled tumour protein (TCTP). Int. J. Biochem. Cell Biol. 2004, 36 (3), 379–385. Gachet, Y.; Tournier, S.; Millar, J. B. A.; Hyams, J. S. A MAP kinasedependent actin checkpoint ensures proper spindle orientation in fission yeast. Nature 2001, 412, 352–354. Wang, D.; Gao, L. Proteomic analysis of neural differentiation of mouse embryonic stem cells. Proteomics 2005, 5 (17), 4414–4426. Wang, D.; Gao, L. Proteomic analysis of neural differentiation of mouse embryonic stem cells. Proteomics 2005, 5 (17), 4414–4426. Yan, L.; Fei, K.; Bridge, D.; Sarras Jr, M. P. A cnidarian homologue of translationally controlled tumor protein (P23/TCTP). Dev. Genes Evol. 2000, 210 (10), 507–511. Kang, Y. J.; Olson, M. O. J.; Busch, H. Phosphorylation of acidsoluble proteins in isolated nucleoli of novikoff hepatoma ascites cellsseffects of divalent cations. J. Biol. Chem. 1974, 249 (17), 5580– 5585. Chan, W. Y.; Liu, Q. R.; Borjigin, J.; Busch, H.; Rennert, O. M.; Tease, L. A.; Chan, P. K. Characterization of the cDNA encoding human nucleophosmin and studies of its role in normal and abnormal growth. Biochemistry 1989, 28 (3), 1033–1039. Baharvand, H.; Hajheidari, M.; Ashtiani, S. K.; Salekdeh, G. H. Proteomic signature of human embryonic stem cells. Proteomics 2006, 6 (12), 3544–3549. Wang, B. B.; Lu, R.; Wang, W. C.; Jin, Y. Inducible and reversible suppression of Npm1 gene expression using stably integrated small interfering RNA vector in mouse embryonic stem cells. Biochem. Biophys. Res. Commun. 2006, 347 (4), 1129–1137. Tachikui, H.; Navet, A. F.; Ozawa, M. Identification of the Ca2+binding domains in reticulocalbin, an endoplasmic reticulum resident Ca2+-binding protein with multiple EF-hand motifs. J. Biochemistry 1997, 121 (1), 145. Kent, J.; Lee, M.; Schedl, A.; Boyle, S.; Fantes, J.; Powell, M.; Rushmere, N.; Abbott, C.; van Heyningen, V.; Bickmore, W. A. The reticulocalbin gene maps to the WAGR region in human and to the small eye harwell deletion in mouse. Genomics 1997, 42 (2), 260–267. Yu, L. R.; Zeng, R.; Shao, X. X.; Wang, N.; Xu, Y. H.; Xia, Q. C. Identification of differentially expressed proteins between human hepatoma and normal liver cell lines by two-dimensional electrophoresis and liquidchromatography-ion trap mass spectrometry. Electrophoresis 2000, 21 (14), 3058–3068. Tong, A.; Zhang, H.; Li, Z.; Gou, L.; Wang, Z.; Wei, H.; Tang, M.; Liang, S.; Chen, L.; Huang, C. Proteomic analysis of liver cancer

(33) (34) (35)

(36) (37) (38) (39) (40) (41)

(42)

(43)

(44)

(45) (46) (47) (48)

(49)

(50) (51)

(52)

cells treated with suberonylanilide hydroxamic acid. Cancer Chemother. Pharmacol. 2008, 61 (5), 791–802. Rechsteiner, M.; Rogers, S. W. PEST sequences and regulation by proteolysis. Trends Biochem. Sci. 1996, 21 (7), 267–271. Mori, T.; Li, Y.; Hata, H.; Kochi, H. NIRF is a ubiquitin ligase that is capable of ubiquitinating PCNP, a PEST-containing nuclear protein. FEBS Lett. 2004, 557 (1-3), 209–214. Nakamura, H.; Izumoto, Y.; Kambe, H.; Kuroda, T.; Mori, T.; Kawamura, K.; Yamamoto, H.; Kishimoto, T. Molecular cloning of complementary DNA for a novel human hepatoma-derived growth factor. Its homology with high mobility group-1 protein. J. Biol. Chem. 1994, 269 (40), 25143–25149. Jo´nsson, Z. O.; Jha, S.; Wohlschlegel, J. A.; Dutta, A. Rvb1p/Rvb2p recruit Arp5p and assemble a functional Ino80 chromatin remodeling complex. Mol. Cell 2004, 16 (3), 465–477. Wood, M. A.; McMahon, S. B.; Cole, M. D. An ATPase/Helicase complex is an essential cofactor for oncogenic transformation by c-Myc. Mol. Cell 2000, 5 (2), 321–330. Boguski, M. S.; McCormick, F. Proteins regulating Ras and its relatives. Nature 1993, 366 (6456), 643–654. Quilliam, L. A.; Khosravi-Far, R.; Huff, S. Y.; Der, C. J. Guanine nucleotide exchange factors: activators of the Ras superfamily of proteins. BioEssays 1995, 17 (5), 395–404. Blatch, G. L.; Laessle, M. The tetratricopeptide repeat: a structural motif mediating protein-protein interactions. BioEssays 1999, 21 (11), 932–939. Marty, C.; Browning, D. D.; Ye, R. D. Identification of tetratricopeptide repeat 1 as an adaptor protein that interacts with heterotrimeric G proteins and the small GTPase Ras. Mol. Cell. Biol. 2003, 23 (11), 3847–3858. Parker, F.; Maurier, F.; Delumeau, I.; Duchesne, M.; Faucher, D.; Debussche, L.; Dugue, A.; Schweighoffer, F.; Tocque, B. A RasGTPase-activating protein SH3-domain-binding protein. Mol. Cell. Biol. 1996, 16 (6), 2561–2569. Gallouzi, I.; Parker, F.; Chebli, K.; Maurier, F.; Labourier, E.; Barlat, I.; Capony, J. P.; Tocque, B.; Tazi, J. A novel phosphorylationdependent RNase activity of GAP-SH3 binding protein: a potential link between signal transduction and RNA stability. Mol. Cell. Biol. 1998, 18 (7), 3956–3965. Kociok, N.; Esser, P.; Unfried, K.; Parker, F.; Schraermeyer, U.; Grisanti, S.; Toque´, B.; Heimann, K. Upregulation of the RASGTPase activating protein (GAP)-binding protein (G3BP) in proliferating RPE cells. J. Cell. Biochem. 1999, 74, 194–201. Dang, C. V. c-Myc target genes involved in cell growth, apoptosis, and metabolism. Mol. Cell. Biol. 1999, 19, 1–11. Chen, C. S.; Mrksich, M.; Huang, S.; Whitesides, G. M.; Ingber, D. E. Geometric control of cell life and death. Science 1997, 276 (5317), 1425. Watt, F. M.; Jordan, P. W.; O’Neill, C. H. Cell shape controls terminal differentiation of human epidermal keratinocytes. Proc. Natl. Acad. Sci. U.S.A. 1988, 85 (15), 5576–5580. Roskelley, C. D.; Desprez, P. Y.; Bissell, M. J. Extracellular matrixdependent tissue-specific gene expression in mammary epithelial cells requires both physical and biochemical signal transduction. Proc. Natl. Acad. Sci. U.S.A. 1994, 91 (26), 12378–12382. Pittenger, M. F.; Mackay, A. M.; Beck, S. C.; Jaiswal, R. K.; Douglas, R.; Mosca, J. D.; Moorman, M. A.; Simonetti, D. W.; Craig, S.; Marshak, D. R. Multilineage potential of adult human mesenchymal stem cells. Science 1999, 284 (5411), 143. McBeath, R.; Pirone, D. M.; Nelson, C. M.; Bhadriraju, K.; Chen, C. S. Cell shape, cytoskeletal tension, and RhoA regulate stem cell lineage commitment. Dev. Cell 2004, 6 (4), 483–495. Hynes, R. O.; Huang, S.; Chen, C. S.; Ingber, D. E. Control of Cyclin D1, p27Kip1, and cell cycle progression in human capillary endothelial cells by cell shape and cytoskeletal tension. Mol. Biol. Cell 1998, 9 (11), 3179–3193. Bruneel, A.; Labas, V.; Mailloux, A.; Sharma, S.; Royer, N.; Vinh, J.; Pernet, P.; Vaubourdolle, M.; Baudin, B. Proteomics of human umbilical vein endothelial cells applied to etoposide-induced apoptosis. Proteomics 2005, 5 (15), 3876–3884.

PR800880V

Journal of Proteome Research • Vol. 8, No. 3, 2009 1539

Proteomic Analysis of Monkey Embryonic Stem Cell during

Recommend Documents