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. Author manuscript; available in PMC: 2007 Apr 24.
Published in final edited form as: Stem Cells. 2005 Nov 17;24(3):516–530. doi: 10.1634/stemcells.2005-0143

Assessing self-renewal and differentiation in hESC lines

Jingli Cai 1,5, Jia Chen 2,5, Ying Liu 1, Takumi Miura 1, Yongquan Luo 1, Jeanne F Loring 3, William J Freed 2, Mahendra S Rao 1, Xianmin Zeng 2,4
PMCID: PMC1855239  NIHMSID: NIHMS18391  PMID: 16293578

Abstract

Like other cell populations, undifferentiated human embryonic stem cells (hESCs) express a characteristic set of proteins and mRNA that is unique to the cells regardless of culture conditions, number of passages and methods of propagation. We have sought to identify a small set of markers that would serve as a reliable indicator of the balance of undifferentiated and differentiated cells in hESC populations. Markers of undifferentiated cells should be rapidly down-regulated as the cells differentiate to form embryoid bodies (EBs), while markers that are absent or low during the undifferentiated state but are induced as hESCs differentiate could be used to assess the presence of differentiated cells in the cultures. In this manuscript we describe a list of markers that reliably distinguish undifferentiated and differentiated cells. An initial list of approximately 150 genes was generated by scanning published MPSS, EST scan and microarray datasets. From this list, a subset of 109 genes was selected that included 55 candidate markers of undifferentiated cells, 46 markers of hESC derivatives, 4 germ cell markers and 4 trophoblast markers. Expression of these candidate marker genes was analyzed in undifferentiated hESCs and differentiating EB populations in four different lines by immunocytochemistry, RT-PCR, microarray analysis and quantitative RT-PCR (qPCR). We show that qPCR with as few as 12 selected genes can reliably distinguish differentiated cells from undifferentiated hESC populations.

Keywords: Human embryonic stem cell, Embryoid body, Differentiation

Introduction

Currently, more than 100 distinct human embryonic stem cell (hESC) lines have been derived and efforts at new derivations are ongoing. Approximately 20 lines from the 78 derivations undertaken before August 9, 2001 are available in sufficient quantities for general research use (NIH stem cell registry, http://stemcells.nih.gov/research/registry). Of these, only a small subset of lines is available for detailed characterization [1-8]. As expected, various hESC lines have a number of similarities. For example, undifferentiated hESCs are similar in expressing surface antigens and markers characteristic of the undifferentiated ESC state including Oct4 (POU5F1), Nanog, UTF1, DPPA5, TERT, gap junction proteins, SSEA and TRA antigens [1-8]. hESCs are also similar in their ability to proliferate and differentiate into cell types of the three germ layers in vitro and in vivo [9-16]. Properties of hESCs have also been compared using microarray, EST scan, SAGE and MPSS [4; 17-27]. These studies suggest that it is likely that markers shared by hESC lines but absent in other cell populations exist.

Although these studies have highlighted similarities among hESC lines and markers that distinguish them from mouse ESCs, it is likely that differences also exist. These include potential differences in methylation patterns [28; 29], likely HLA differences [25], allelic differences, variability of X-inactivation and adaptation of cells to different culture conditions [17, 2; 30; 31]. Indeed, important differences between hESC lines in growth rates, methods of propagation and karyotype have been reported using a variety of different techniques, suggesting that while shared markers may exist, care will be needed to identify them. Identifying such shared markers, however, remains an easier task than the technically challenging experiments of direct comparing hESCs under identical culture conditions-experiments that are being undertaken at the Stem Cell Center at the NIH (Dr. McKay) and at the International Stem Cell Initiative (Dr. Andrews) to identify fundamental differences among cell lines. Such experiments are beyond the scope of our laboratories. The available data, however, indicate that identifying a common pattern of gene expression that is conserved independent of culture conditions and reflects the fundamental properties of hESC is possible.

Several other experiments suggest that a unique molecular signature can be defined to distinguish undifferentiated hESCs from their differentiated progeny, and that this signature can be used to define the states of hESCs [17-19]. These experiments used MPSS, EST scan, and microarray data to suggest that a large pool of potential markers that could distinguish embryoid bodies (EBs) and other differentiated cells from hESCs exist. We have reasoned, therefore, that at the current level of resolution of techniques, it is possible to identify a core set of genes that are conserved and/or required to maintain hESC identity. These genes should be expressed irrespective of the conditions of culture, numbers of passages and methods of propagation as long as undifferentiated hESCs are present. Moreover, these core markers should be present regardless of the methods of hESC derivation and ethnic phenotypes of the blastocysts used. If present at lower levels, they should be detectable by RT-PCR as well as by SAGE/MPSS, and if robust by SAGE and microarray. Furthermore, if the expression of such genes is examined in EBs, then a subset of markers that are rapidly downregulated or rapidly induced as cells differentiate can be identified [19]. A combination of such markers can serve to reliably assess the states of ESCs and EBs.

To test this hypothesis we have performed a meta-analysis of published reports examining hESCs and EBs, and identified a list of potential markers. We tested a substantial number of these markers by quantitative RT-PCR (qPCR) and immunocytochemistry and identified a combination of markers to distinguish hESCs from EBs.

Materials and Methods

hESC culture and in vitro differentiation via EB

hESC lines BG01, BG02, BG03 and I6 were either maintained on inactivated mouse embryonic fibroblast (MEF) feeder cells in medium comprised of Dulbecco’s Modified Eagle’s Medium/Ham’s F12 supplemented with 20% knockout serum replacement, 2 mM non-essential amino acids, 2 mM L-glutamine, 50 μg/ml Penn-Strep (all from Invitrogen; Carlsbad, CA; http://www.invitrogen.com), 0.1 mM β-mercaptoethanol (Specialty Media; Phillipsburg, NJ; http://www.specialtymedia.com), and 4 ng/ml of basic fibroblast growth factor (bFGF, Sigma; St. Louis, MO; http://www.sigmaaldrich.com), or on fibronectin (BD Biosciences, Bedford, MA;http://www.bdbiosciences.com) coated dishes in medium conditioned with MEF for 24 hours as previously described [4; 25].

Differentiation via EB formation was performed as preciously described [4]. Briefly, hESCs were dissociated into small clumps by collagenase IV (Sigma) and grown as floating spheres in hESC medium without bFGF for up to 2 weeks, with a medium change every second day.

RT-PCR and qPCR analysis

Total RNA was extracted from undifferentiated hESCs or EBs (7-day and 14-day) using RNA STAT-60 (Tel-Test Inc., Friendswood, TX). cDNA was synthesized by using a reverse transcription kit (RETROscript, Ambion, Austin, TX) according to the manufacturer’s recommendations. The PCR primers are listed in Supplementary Table 1.

Real-time qPCR was used to quantify the levels of mRNA expression of 12 selected genes (Oct4, Nanog, Sox2, UTF1, DPPA5, Lin41, Sox1, DCN, H19, IGF2, GATA4 and Hand1) in hESCs or EBs at different times of differentiation. PCR reactions were carried out by DNA Engine Opticon Fluorescence Detection System (MJ Research, Waltham, MA) using a DyNAmo SYBR Green qPCR kit according to the manufacturer’s instructions. The content of selected genes was normalized to the content of 18S-rRNA and standard curves were generated using 10 to 1000 ng cDNA per 20 μl reaction volume. All PCR products were checked by melting curve analysis to exclude the possibility of multiple products or incorrect product size. PCR analyses were conducted in triplicate for each sample.

Immunocytochemistry

Immunocytochemistry and staining procedures were as described previously [32]. Briefly, hESCs grown either on MEF feeder cells or under feeder-free conditions, 7-day and 14-day EBs either attached or floating were fixed with 2% paraformaldehyde for half an hour. Parts of EBs were embedded in O.C.T. Blocks were cut on a cryostat to obtain 8 μm sections. Fixed cells and sections were blocked in blocking buffer (5% goat serum, 1% BSA, 0.1% Triton X-100) for 1 hour followed by incubation with the primary antibody at 4°C overnight. Appropriately coupled secondary antibodies (Molecular Probes) were used for single and double labeling. All secondary antibodies were tested for cross reactivity and non-specific immunoreactivity.

The following antibodies were used: Nanog (1:1000, R&D Systems AF1997), ITGB1 (CD29/Integrin β1, 1:1000, Chemicon MAB1951), CDH1 (E-Cadherin, 1:2500, R&D Systems MAB1838), PODXL (Podocalyxin, 1:500, R&D Systems MAB1658), Sox2 (1:1000, R&D Systems MAB2018), Oct4 (1:1000, R&D Systems AF1759), Brachyury (1:1000, R&D Systems AF2085), ACTC (Cardiac Actin, 1:50, Research Diagnostics, Inc., PRO61075), GATA4 (1:100, Santa Cruz sc-25310), GATA6 (1:100, Santa Cruz sc-9055), AFP (alpha-fetoprotein, 1:500, Sigma A8452) and TUBB3 (βIII tubulin 1:2000, Sigma T8660). Bis-benzamide (Dapi, 1:1000, Sigma) was used to identify the nuclei. Images were captured on an Olympus fluorescence microscope.

Microarray analysis using BeadArray platform

RNAs from undifferentiated BG01, BG02 and BG03 cells and the matched 14-day EBs were hybridized to prototype Illumina RefSeq-8 BeadChips, which contained more than 24,000 genes [33]. A detailed description of the BeadChip system has been provided elsewhere [33]. Samples were coded and run in duplicates and the results were analyzed using standard bioinformatics tools and the Bead Studio, a tool kit developed by Illumina. A detailed analysis of these and other samples will be reported elsewhere [Jeanne Loring, Burnham Institute, personal communication].

Results

Meta-analysis procedure

A large dataset on gene expression of undifferentiated hESCs and EBs that differentiated from them using large scale array experiments including MPSS, EST enumeration and microarrays has been generated and described by a variety of investigators [17-24]. To generate a list of genes characteristic of undifferentiated hESCs and differentiated EBs, we examined three published reports on gene expression in hESCs and EBs. These were: 1) a list of ninety-two genes identified as “stemness” genes which are expressed at high levels in six hESC lines as assessed by a 16,695 seventy base pair oligonucleotide microarray [18], 2) a comprehensive list of genes common to undifferentiated hESCs obtained by MPSS analysis using pooled hESCs samples [17], and 3) a large list of genes that are highly expressed in differentiated EBs detected by both MPSS and EST scan [19] (A complete list of EST scan data are obtained from http://www.ncbi.nlm.nih.gov/UniGene/library.cgi?all=yes&ORG=Hs&LID=14183 http://www.ncbi.nlm.nih.gov/UniGene/library.cgi?all=yes&ORG=Hs&LID=14184).

The criteria for selection were that the levels of expression should differ between hESCs and EBs by at least three fold by array data or by five fold for EST scanning and MPSS, the levels of expression should be high (>10 tpm for MPSS, >5 by EST scan) and that the genes must be detected by at least one independent method and in more than one hESC line. One exception to these selection criteria is that we included some genes that were not detected by MPSS or EST scanning but are used as ESC marker by convention, and a few genes that were highly expressed in both hESCs and EBs or expressed at higher level in EBs but were reported as ESC specific genes by microarray analysis when compared to human universal RNA [18] (Table 1), or because of being a potential cell surface marker. A list of several hundred genes generated after this selection was pruned to a list of about one hundred by examining published literature with the goal of including known genes with approximately half of them being candidate genes highly expressed in undifferentiated hESCs (but not in EBs or down-regulated in EBs), and the other half being those that are expressed in EBs (but lower or absent in hESCs). We did not include any unknown genes even though many of them were significantly differentially expressed in hESCs and EBs [19].

Table 1.

hESC specific markers

Gene symbol Gene ID (Locus ID) UniGene Description Tpm (hESC) Tpm (hEB) Micro-array (hESC) Micro-array (hEB) EST scan (hESC) EST scan (hEB) Reference
Stem cell marker
LIN28 79727 Hs.86154 lin-28 homolog (C. elegans) 1962 178 3944.1 1421.6 25 13 24
DNMT3B 1789 Hs.251673 DNA (cytosine-5-)-methyltransferase 3 beta 1274 56 3391 274.5 58 3 24
CLDN6 9074 Hs. 533779 claudin 6 1063 151 2247.2 581.1 14 0 24
IFITM1 8519 Hs.458414 interferon induced transmembrane protein 1 (9-27) 920 221 8844 2188.5 4 1 4
POU5F1 5460 Hs.249184 POU domain, class 5, transcription factor 1 658 20 694.4 28.9 23 1 41
ITGB1 3688 Hs.429052 integrin, beta 1 (fibronectin receptor, beta polypeptide, antigen CD29 includes MDF2, MSK12) 545 2246 3726.7 8211.2 16 70
SFRP2 6423 Hs.481022 secreted frizzled-related protein 2 505 31 1353.9 93.1 7 1 4
GJA1 2697 Hs.74471 gap junction protein, alpha 1, 43kDa (connexin 43) 452 406 2404.4 2926.1 27 24 8
SOX2 6657 Hs.518438 SRY (sex determining region Y)-box 2 344 11 N.D. N.D. 11 1 42
CD9 928 Hs.114286 CD9 antigen (p24) 221 13 2930.8 1267.2 1 0 43
GAL 51083 Hs.278959 galanin 221 28 1043.3 97.5 N.D. N.D. 44
LIN41 Non Hs.517884 LOC131405: similar to abnormal cell LINeage LIN-41, heterochronic gene; Drosophila dappled/ vertebrate TRipartite Motif protein related; B-box zinc finger, Filamin and NHL repeat containing protein (123.8 kD) (lin-41) 165 41 N.D. N.D. 3 2 45
IMP-2 10644 Hs.35354 IGF-II mRNA-binding protein 2 140 133 1206 1163.2 5 8 4
LECT1 11061 Hs.421391 leukocyte cell derived chemotaxin 1 116 3 N.D. N.D. 4 0 4
ZNF206 84891 Hs.334515 Zinc finger protein 206 109 0 1504.5 71.3 26 0
GABRB3 2562 Hs.302352 gamma-aminobutyric acid (GABA) A receptor, beta 3 96 7 482.7 28 5 1
GYLTL1B 120071 Hs.86543 glycosyltransferase-like 1B 92 0 1066.6 69.3 4 1
UTF1 8433 Hs.458406 undifferentiated embryonic cell transcription factor 1 90 0 1444.1 81.3 N.D. N.D. 46
NR6A1 2649 Hs.20131 nuclear receptor subfamily 6, group A, member 1 79 17 N.D. N.D. N.D. N.D. 47
LEFTY1 10637 Hs.278239 left-right determination, factor 1 72 0 6579.6 73.1 4 0
SCGB3A2 117156 Hs.483765 Secretoglobin, family 3A, member 2 65 0 890.5 12.2 1 0
KIT 3815 Hs.479754 v-kit Hardy-Zuckerman 4 feline sarcoma viral oncogene 46 5 188.9 42.2 1 0
CKMT1 1159 Hs.425633 creatine kinase, mitochondrial 1 (ubiquitous) 42 0 742.4 46.2 1 0
TDGF1 6997 Hs.385870 teratocarcinoma-derived growth factor 1 38 0 3169 200.2 16 1 18
FOXD3 27022 Hs.546573 forkhead box D3 37 0 N.D. N.D. N.D. N.D. 48
DIAPH2 1730 Hs.226483 diaphanous homolog 2 (Drosophila) 27 4 1971.1 261.4 N.D. N.D.
NUMB 8650 Hs.509909 numb homolog (Drosophila) 24 1 618.3 778.9 0 4
CER1 9350 Hs.248204 cerberus 1 homolog, cysteine knot superfamily (Xenopus laevis) 23 0 151.5 23.4 N.D. N.D.
PMAIP1 5366 Hs.96 Phorbol-12-myristate-13-acetate-induced protein 1 23 1 1601.5 336.6 4 0
CDH1 999 Hs.461086 cadherin 1, type 1, E-cadherin (epithelial) 20 0 1972.9 793.1 11 0
LEFTY2 7044 Hs.520187 Left-right determination factor 2 (LEFTY2) 16 4 944.1 100.1 1 0
NANOG 79923 Hs.329296 Nanog homeobox 16 0 56.9 10.7 1 0 36, 49
SMAD2 4087 Hs.12253, Hs.465061 SMAD, mothers against DPP homolog 2 (Drosophila) 13 0 332.8 397.4 1 1
BRIX 55299 Hs.38114 BRIX 9 0 1833.6 1261.5 3 3 4
REST 5978 Hs.401145 RE1-silencing transcription factor 6 0 18.5 15.4 1 1
ZFP42 (Rex1) 132625 Hs.335787 zinc finger protein 42 5 0 159.3 34.5 2 0 50
EDNRB 1910 Hs.82002 endothelin receptor type B 0 0 346.8 119.8 0 1
PTEN 5728 Hs.500466 phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 0 0 138.4 125.6 1 0
NOG 9241 Hs.248201 noggin 0 0 N.D. N.D. N.D. N.D.
GDF3 9573 Hs.86232 growth differentiation factor 3 N.D. N.D. 236.5 27.2 N.D. N.D. 24
GBX2 2637 Hs.184945 gastrulation brain homeo box 2 N.D. N.D. 44.5 14.7 N.D. N.D.
TFCP2L1 29842 Hs.156471 transcription factor CP2-like 1 N.D. N.D. N.D. N.D. N.D. N.D.
COMMD3 23412 Hs.534398 COMM domain containing 3 N.D. N.D. N.D. N.D. N.D. N.D.
TERT 7015 Hs.492203 telomerase reverse transcriptase N.D. N.D. N.D. N.D. 1 0
PODXL 5420 Hs.16426 podocalyxin-like N.D. N.D. 498.2 394.2 60 23 4
FGF4 2249 Hs.1755 fibroblast growth factor 4 (heparin secretory transforming protein 1, Kaposi sarcoma oncogene) N.D. N.D. N.D. N.D. 1 0 51
NR5A2 2494 Hs.33446 nuclear receptor subfamily 5, group A, member 2 N.D. N.D. N.D. N.D. N.D. N.D.
IFITM2 10581 Hs.174195 interferon induced transmembrane protein 2 (1-8D) N.D. N.D. 129.2 204 2 0
GRB7 2886 Hs.86859 growth factor receptor-bound protein 7 N.D. N.D. 105.4 11.6 2 0
DPPA5 359942 Hs.125331 developmental pluripotency associated 5 N.D. N.D. N.D. N.D. N.D. N.D. 52
NODAL 4838 Hs.370414 nodal homolog (mouse) N.D. N.D. N.D. N.D. 1 0
LCK 3932 Hs.470627 Lymphocyte-specific protein tyrosine kinase N.D. N.D. 500 10.7 N.D. N.D.
NTS 4922 Hs.80962 Neurotensin N.D. N.D. 1313 137.7 N.D. N.D.
ITGB1BP3 9270 Hs.135458 Integrin beta 1 binding protein 3 N.D. N.D. N.D. N.D. 2 0
CHST4 10164 Hs.251383 Carbohydrate (N-acetylglucosamine 6-O) sulfotransferase 4 N.D. N.D. N.D. N.D. 2 0
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The final list of 109 potential markers included 55 stem cell markers in which most of them were highly expressed in undifferentiated hESCs. For potential markers of the EB state, 46 markers were selected including representative genes from each germ layer with 12 ectoderm, 15 mesoderm and 19 endoderm markers that are likely over-expressed in EBs. In addition, 4 trophoblast markers and 4 germ cell markers were included (Tables 1 and 2, Supplementary Table 1).

Table 2.

EB specific markers

Gene symbol Gene ID (Locus ID) UniGene Description Tpm (hESCs) Tpm (hEBs) Micro-array (hEB) Micro-array (hEB) EST scan (hESC) EST scan (hEB) Reference
Ectoderm marker
VIM 7431 Hs.533317 vimentin 626 9881 6262.9 16146.1 38 114 53
CRABP2 1382 Hs.405662 cellular retinoic acid binding protein 2 26 396 1549.9 3187.6 9 5 54
SEMA3A 10371 Hs.252451 sema domain, immunoglobulin domain (Ig), short basic domain, secreted, (semaphorin) 3A 1 16 214.1 180.2 1 1 55
MSI1 4440 Hs.158311 musashi homolog 1 (Drosophila) 0 11 1968 787.6 5 1 56
MAP2 4133 Hs.368281 microtubule-associated protein 2 0 10 N.D. N.D. 1 1 57
GFAP 2670 Hs.514227 glial fibrillary acidic protein 0 0 34.7 15 N.D. N.D. 58
OLIG2 10215 Hs.176977 oligodendrocyte lineage transcription factor 2 0 0 13.4 1.7 N.D. N.D. 59
SOX1 6656 Hs.202526 SRY (sex determining region Y)-box 1 N.D. N.D. 21.2 10.1 N.D. N.D. 60
NES 10763 Hs.527971 nestin 386. 50. 2935.8 2471.3 4 6 61
NEUROD1 4760 Hs.72981 neurogenic differentiation 1 N.D. N.D. N.D. N.D. N.D. N.D. 62
TH 7054 Hs.435609 tyrosine hydroxylase N.D. N.D. 158.4 107.8 N.D. N.D. 63
TUBB3 10381 Hs.511743 tubulin, beta 3 N.D. N.D. N.D. N.D. 2 8 64
Endoderm marker
FN1 2335 Hs.203717 fibronectin 1 3661 21250 3243.5 12913.2 34 351 65
DCN 1634 Hs.156316 decorin 2 2008 95.6 1550.2 0 18 66
H19 283120 Hs.551588 H19, imprinted maternally expressed untranslated mRNA 64 2176 N.D. N.D. 2 136
AFP 174 Hs.518808 alpha-fetoprotein 30 1829 1089.1 9765 0 5 67
LAMB1 3912 Hs.489646 laminin, beta 1 186 614 126.7 504.2 15 19 68
LAMC1 3915 Hs.497039 laminin, gamma 1 (formerly LAMB2) 203 352 2098.4 4340.9 14 13 69
BMP2 650 Hs.73853 bone morphogenetic protein 2 35 69 63.1 68.4 1 1 70
SERPINA1 5265 Hs.525557 serine (or cysteine) proteinase inhibitor, clade A (alpha-1 antiproteinase, antitrypsin), member 1 0 61 136.3 1045.2 1 1 71
FLT1 2321 Hs.507621 fms-related tyrosine kinase 1 (vascular endothelial growth factor/vascular permeability factor receptor) 38 46 N.D. N.D. 2 0 72
ACVR1B 91 Hs.438918 activin A receptor, type IB 22 42 237.8 187.2 4 3 73
GATA4 2626 Hs.243987 GATA binding protein 4 2 13 83.2 145.2 3 4 74
GCG 2641 Hs.516494 glucagon N.D. N.D. N.D. N.D. N.D. N.D. 75
INS 3630 Hs.89832 insulin N.D. N.D. 122.7 70.4 N.D. N.D. 76
PECAM1 5175 Hs.514412 platelet/endothelial cell adhesion molecule (CD31 antigen) N.D. N.D. 40 49.1 N.D. N.D. 77
FABP2 2169 Hs.282265 fatty acid binding protein 2, intestinal N.D. N.D. N.D. N.D. N.D. N.D. 78
HNF4A 3172 Hs.116462 hepatocyte nuclear factor 4, alpha N.D. N.D. 16 10 N.D. N.D. 79
FGF8 2253 Hs.57710 fibroblast growth factor 8 (androgen-induced) N.D. N.D. N.D. N.D. N.D. N.D. 80
HGF 3082 Hs.396530 Hepatocyte growth factor N.D. N.D. 32.2 39.4 0 1 81
FOXA2 3170 Hs.155651 Forkhead box A2 N.D. N.D. 94.2 83.2 2 0 82
Mesoderm marker
COL1A1 1277 Hs.172928 collagen, type I, alpha 1 3889 68430 208.7 2424.2 67 658 83
HAND1 9421 Hs.152531 heart and neural crest derivatives expressed 1 0 500 389.8 9466.3 0 8 84
MSX1 4487 Hs.424414 msh homeo box homolog 1 (Drosophila) 15 218 467.3 2198.1 1 3 85
ACTC 70 Hs.118127 actin, alpha, cardiac muscle 112 141 952.2 2963.6 1 4 86
GATA6 2627 Hs.514746 GATA binding protein 6 4 53 206.7 964.2 N.D. N.D. 87
COL2A1 1280 Hs.408182 collagen, type II, alpha 1 (primary osteoarthritis, spondyloepiphyseal dysplasia, congenital) 70 49 144.5 632.6 1 19 88
HBZ 3050 Hs.449632 hemoglobin, zeta 0 34 30 408.7 N.D. N.D. 89
T 6862 Hs.389457 T, brachyury homolog (mouse) N.D. N.D. N.D. N.D. N.D. N.D. 90
WT1 7490 Hs.408453 Wilms tumor 1 N.D. N.D. 40.6 0.9 N.D. N.D. 91
MYF5 4617 Hs.178023 myogenic factor 5 N.D. N.D. 20.2 12.1 N.D. N.D. 92
DES 1674 Hs.471419 desmin N.D. N.D. 6.6 4.5 N.D. N.D. 93
NPPA 4878 Hs.75640 natriuretic peptide precursor A N.D. N.D. N.D. N.D. N.D. N.D. 94
HBB 3043 Hs.523443 hemoglobin, beta N.D. N.D. 33.1 46 N.D. N.D. 95
RUNX2 860 Hs.535845 runt-related transcription factor 2 N.D. N.D. 21.9 5.3 0 3 96
IGF2 3481 Hs.523414 insulin-like growth factor 2 (somatomedin A) N.D. N.D. 115.8 5369.7 1 18 97
Trophoblast
EOMES 8320 Hs.147279 eomesodermin homolog (Xenopus laevis) 10 0 247.2 63.4 N.D. N.D. 98
CDX2 1045 Hs.174249 caudal type homeo box transcription factor 2 0 5 13.4 343.9 0 1 99
GCM1 8521 Hs.28346 glial cells missing homolog 1 (Drosophila) N.D. N.D. 16.5 9.4 N.D. N.D. 100
KRT1 3848 Hs.80828 keratin 1 (epidermolytic hyperkeratosis) N.D. N.D. 13.4 17.1 N.D. N.D. 101
Germ Cells
SYCP3 50511 Hs.506504 synaptonemal complex protein 3 N.D. N.D. N.D. N.D. N.D. N.D. 102
DDX4 54514 Hs.223581 DEAD (Asp-Glu-Ala-Asp) box polypeptide 4 N.D. N.D. 10 5.5 N.D. N.D. 103
IFITM1 8519 Hs.458414 Fragilis-1 N.D. N.D. 8844 2188.5 4 1 104
IFITM2 10581 Hs.174195 Fragilis-2 N.D. N.D. 129.2 204 2 0 105
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Markers of the ESC state

Forty-four genes highly expressed in undifferentiated hESCs but down-regulated in EBs were selected as markers of stem cells to represent the undifferentiated ESC state (Table 1). Several of these genes such as Oct4, Nanog and TERT are generally accepted markers of pluripotency. Many genes in the list including UTF1, Sox2, Lin28, Lin 41, PODXL, LeftyB, GJA1, FoxD3 and Rex1 (ZFP42) have recently been reported to be expressed in undifferentiated hESCs by several research groups [4; 17-19; 34]. Other undifferentiated markers included genes that encoded transcriptional factors, growth factors, signal transducers, cell surface antigens and receptors. In addition, 11 genes were included as ESC markers although they did not meet our selection criteria. Of them, eight genes, NOG, TFCP2L1, CommD3, TERT, NR5A2, DPPA5, NODAL, ITGB1BP3, were selected by convention. Two genes, GJA1 and IMP2, were selected because they expressed at significant higher levels in hESCs when compared to human universal RNA by microarray analysis, although their expression were equally high in EBs. Finally, despite higher level expression in EBs, ITGB1 was included because it is a cell surface receptor which may bind fibronectin that has been reported to be a substrate capable of supporting hESC growth [35; 36].

Markers of the EB state

To represent the complexity of EBs, we included as many types of early markers of differentiation as possible, and selected the following: 1) 12 ectoderm markers including markers for neural precursors such as nestin and Sox1, and for terminal differentiated neural cells like Tuj1 (TUBB3), TH and GFAP, 2) 19 endoderm markers including pancreatic marker insulin, imprinted maternally expressed gene H19, HNF and AFP, 3) 15 mesoderm markers including collagen, Brachyury and ACTC, 4) Four trophoblast markers, KRT1, EOMES, GCM1 and CDX2, and 5) Four germ cell markers SYCP3, DDX4, IFITM1, IFITM2 (Table 2).

Expression of candidate markers by RT-PCR

Our selection criteria indicated that candidate markers will be expressed in the appropriate stage of development and should be detected by RT-PCR. We therefore generated a PCR primer list for all 109 genes (Supplementary Table1) and tested 35 genes (Fig. 1 and data not shown, highlighted in Supplementary Table 1) using three different cell lines. Representative results for a subset of markers for the I6 line are shown. Of the 7 ESC markers shown, all were expressed in undifferentiated hESCs. A subset (Dppa5, UTF1 and ZFP42) were undetectable in 14-day EBs while the others were down-regulated (GAL, Lin28, Lin41 and TDGF1) in EBs (Fig. 1, left panel). Likewise, the 7 EB specific markers (AFP, FoxA2, Hand1, HGF, IGF2, Msx1 and MSI1) were expressed in EBs but absent (AFP, HNF3b, IGF2 and Msx1) in undifferentiated hESCs or only slightly expressed (Hand1, HGF and MSI1) in undifferentiated hESCs (Fig. 1, right panel). These results showed the relatively specific pattern of expression of candidate ESC and EB markers and indicate the suitability of using some or all of these to assess the overall state of cultured cells.

Fig 1.

Fig 1

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Differential expression of ESC or EB specific genes by RT-PCR. Expression of selected markers of ESC (Dppa5, GAL, LIN28, LIN41, TDGF1, UTF1, and ZFP42) and EB (AFP, FoxA2, HAND1, HGF, IGF2, Msx1, MSI1) was examined by RT-PCR in undifferentiated hESCs, 7-day and 14-day EBs. Consistent with other independent analyses, all the ESC markers are highly expressed in hESCs but quickly down regulated in the two EB populations, whereas all the EB markers are detected in EB samples, but not or slightly expressed in undifferentiated hESCs.

Antibodies to test the expression of candidate markers

Of the 109 genes, we were able to locate commercially available antibodies for about two thirds (76) with reactivity against human antigens and these antibodies and their source are provided in Supplementary Table 1. We tested a subset of these commercial available antibodies by immunocytochemistry and at least 15 of them worked well (highlighted in Supplementary Table 1). Representative staining of ESC or EB specific genes in 7-day and 14-day differentiated EBs and undifferentiated hESCs are shown in Figs. 2 and 3. In general, all the ESC markers (Nanog, Oct4, ITGB1, CDH1 and PODXL) were strongly positive in undifferentiated hESCs but weakly expressed in 7-day EBs, and not expressed in 14-day EBs (Fig.2, panel A-L). The one exception was Sox2, which was expressed in both undifferentiated hESCs and the two stages of EBs (Fig. 2, panel M-O). All the markers of differentiation examined (Brachyury, ACTC, AFP, GATA4, GATA6, TUBB3) were strongly expressed in both 7-day and 14-day EBs but negative or only weakly expressed in undifferentiated hESCs (Fig. 3). In addition to these markers, known pluripotency markers SSEA (SSEA3 and 4) and TRA (TRA-1-60, 1-81) were down-regulated in differentiated EBs and Table 3 summarizes the results of immunocytochemistry. Thus antibodies to most of the candidate markers exist and a significant subset can be used for immunocytochemistry. We notice, however, that ITGB1 was strongly positive stained in undifferentiated hESC but down-regulated in EBs which is in conflict with the MPSS and array data. This suggests that not all genes could be used in all methodologies.

Fig 2.

Fig 2

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Staining of ESC markers on undifferentiated hESCs, 7-day and 14-day EBs. ESC markers Nanog, ITGB1, CDH1, PODXL, Oct4, and Sox2 are expressed by most of undifferentiated hESCs (A, D, G, J, M), while their expression were downregulated in both 7-day and 14-day EBs (B-C, E-F, H-I, K-L, red in N-O) except Sox2 (green in N-O), which is also a neural stem cell marker.

Fig 3.

Fig 3

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Staining of differentiated markers on 7-day and 14-day EBs and undifferentiated hESCs. Mesoderm markers Brachyury and ACTC, endoderm markers AFP, GATA4, and GATA6, and ectoderm marker TUBB3 were detectable in both 7-day and 14-day EBs (A-B, D-E, G-H, J-K, M-N), while their expression were not detected in undifferentiated hESCs (C, F, I, L, O). Spontaneously differentiated hESCs also expressed Brachyury (C), GATA4 and GATA6 (I).

Table 3.

Expression levels of ESC and EB markers in hESCs.

Markers ESCs EB
IC PCR IC PCR
ESC LIN28 N.A ++ N.A -/+
POU5F1 (Oct4) +++ +++ - -/+
GJA1 N.A +++ N.A ++
SOX2 +++ +++ + -/+
GAL N.A +++ N.A -/+
LIN41 N.A ++ N.A -/+
UTF1 N.A +++ N.A -
TDGF1 N.A +++ N.A -/+
FOXD3 N.A ++ N.A N.A
CDH1 +++ N.A - N.A
NANOG +++ +++ - -
ZFP42 (Rex1) N.A ++ N.A -
TERT N.A ++ N.A -
PODXL +++ N.A - N.A
FGF4 N.A +++ N.A N.A
DPPA5 N.A + N.A -
Tra-1-60 ++ N.A. - N.A.
Tra-1-81 ++ N.A. - N.A.
SSEA-1 +++ N.A. - N.A.
SSEA-4 +++ N.A. - N.A.
ITGB1 (CD29) +++ N.A. - N.A.
Ectoderm MSI1 N.A. -/+ N.A. ++
MAP2 N.A. -/+ N.A. ++
SOX1 N.A. - N.A. ++
NES -/+ N.A +++ N.A
TH - - ++ ++
TUBB3 - N.A +++ N.A
Endoderm DCN N.A - N.A +++
H19 N.A - N.A +++
AFP - - ++ +++
GATA4 - - +++ +++
HGF N.A. - N.A. ++
FoxA2 N.A. - N.A. ++
Mesoderm HAND1 N.A. -/+ N.A. +++
MSX1 N.A. - N.A. ++
ACTC - N.A. +++ N.A.
GATA6 - N.A. + N.A.
T (Brachyury) - - ++ ++
IGF2 N.A. - N.A. +
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Monitor differentiation by microarray

Although offering sufficient resolution, RT-PCR and immunocytochemistry are difficult to perform for a large number of genes and cannot be easily automated. To test whether differences in gene expression were of a sufficient magnitude that they could be detected by a more global and less quantitative measurement, we assessed the expression of candidate ESC and EB markers by analyzing their expression in three hESC lines derived by BresaGen (three undifferentiated hESC samples of BG01, 02 and 03 and EBs derived from them) using the Illumina BeadArray containing about 48,000 unique features. All samples were examined in duplicate and only data from duplicates samples that showed 99% or greater correlation was used. The present results were focused on expression of the genes that were selected as candidate markers of the ESC and EB state.

Global pairwise comparisons between different hESC lines (Fig. 4, panel A, and Supplementary Table 2) or different EBs (Fig. 4, panel B), showed similar levels of gene expression and around 90% of the genes detected at greater than 99% confidence limit were expressed at approximately similar levels (within the 2.5-fold range) (Fig. 4F). Pairwise comparisons of hESCs with hESCs or EBs with EBs showed a high degree of similarity of samples (correlation coefficient greater than 0.90). Most of the differential expression seen in Fig.4 A and B is the result of biological differences between the cultures; technical replicates have correlation coefficients greater than 0.90 (Loring, et al., in preparation). Comparisons of hESCs to EBs showed a much lower degree of similarity (correlation coefficient <0.8, Fig. 4, panel C). This suggests that different hESCs are similar to each other and that this similarity is greater than that between hESC and EB derived from the same line. The entire comparison is presented in Supplementary Table 2 and a restricted list of genes which were selected as ESC or EB markers that showed a greater than 2.5-fold difference in expression is shown in Fig. 4 (Panel G and H). The large difference between hESCs and EBs detected by this global comparison indicates that arrays can readily distinguish hESCs from EBs derived from them.

Fig 4.

Fig 4

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Assessment of potential hESC and EB markers using microarrays. Three different ESC lines (BG01, 02 and 03) and 14-day EBs that differentiated from them were compared using an Illumina Bead array. (A-B) Comparisons of gene expression among three hESC lines or three EBs show similar levels with a correlation coefficient (r2) greater than 0.93. (C) Pairwise comparisons of undifferentiated hESCs with their matched EBs reveal that about 50% of the genes are expressed with at least a 2.5-fold difference. (D) Summary of the numbers of genes detected in this array. (E-F) Selected genes that are differentially expressed in three hESC lines (BG01, 02 and 03) and in their matched EBs. Note that only the genes that are detected at >0.99 confidence (blue dots) are considered valid for further analysis. Dots that fall between the thin red lines represent genes that are commonly expressed in hESCs and EBs, while dots outside red lines correspond to differentially expressed genes at >2.5 fold.

To further test whether the similarity in gene expression between hESC lines can be generalized, we analyzed an additional hESC lines H9, obtained from WiCell Institute (Madison, WI, http://www.wicell.org) rather than from BresaGen. As shown in Fig. 4D, gene expression profiles of H9 was remarkably similar to the BG lines, with a correlation coefficient of 0.93 when compared to BG01. This suggests that gene expression profiles in hESC lines derived from different laboratories are similar.

qPCR to monitor differentiation

Our results suggested that a global assessment by a relatively non-quantitative method such as RT-PCR or microarray could be used to detect differentiation. Given the dramatic differences in gene expression, we reasoned that assessing a smaller number of markers using a more quantitative measurement could be sufficient in monitoring the overall state of hESCs. To test this hypothesis, we selected a small number of genes from the 109-list and tested their expression in undifferentiated hESCs and in two differentiating stages of EBs (7-day and 14-day) using BG03. These included 6 undifferentiated ESC markers (Oct4, Nanog, UTF1, DPPA5, Lin 41 and Sox2) and 6 markers of differentiation with at least one gene from each germ layer (Sox1, DCN, H19, IGF2, GATA4 and Hand1). The expression level of these genes were determined as the ratio to the level of 18S RNA, and differential expression of these genes in undifferentiated hESCs and EBs were shown as the ratio of expression in hESC to EB (ESC markers) or EB to hESC (EB markers).

As expected, the expression of ESC markers Oct4, Nanog, UTF1, DPPA5 and Lin41 were higher in undifferentiated hESCs than in EBs, whereas the expression of EB markers Sox1, DCN, H19, IGF2, GATA4 and Hand1 were up-regulated in EBs compared to in undifferentiated hESCs (Fig. 5). In particular, expression of UTF1 and Nanog was rapidly down-regulated upon differentiation with more than a 10-fold decrease in 7-day EBs and 200-fold lower in 14-day EBs. Down-regulation of Oct4, an important gene for the maintenance of pluripotency in both hESCs and mESCs, was less marked with only 5-fold decrease in 14-day EBs. Sox2 was expressed in both undifferentiated hESCs and differentiated EBs (3-fold higher in 14-day EB and 5-fold higher in 7-day EB) which is expected as Sox2 is known to express in neural stem cells which are present in EBs. Interestingly, expression of Lin41 was rapidly decreased in 7-day EBs but the expression level increased in 14-day EBs (Fig. 5).

Fig 5.

Fig 5

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qPCR analysis of 12 genes during hESC differentiation. Expression of 6 markers of each ESC and EB were quantified by qPCR. (A) Amplification curves corresponding to IGF2 and 18S RNA (standard curve) are shown from left to right: IGF2 of 14-day EB (blue and red); 18S RNA of 14-day EB (red and blue); 18S RNA of undifferentiated hESCs (green and red); and IGF2 of undifferentiated hESCs (blue and yellow). (B) The expression level of these genes were determined as the ratio to the level of 18S RNA, and differential expression of these genes in undifferentiated hESCs and EBs were shown as the ratio of expression in hESC to EB (ESC markers) or EB to hESC (EB markers).

All of the differentiation markers, except for Decorin, were rapidly induced as the cells differentiated. The most dramatic changes were seen for an imprinted gene IGF2 whose levels were several thousand fold higher in EBs than in undifferentiated hESCs. Expression of the imprinted gene H19 as well as Hand1 and GATA4 was also rapidly increased as the cells underwent differentiation.

qPCR detects changes that may be missed by immunocytochemistry

To test whether our qPCR assay can detect more subtle changes in hESC cultures that affect the undifferentiated state, we examined hESC cultures maintained with bFGF and cultures where bFGF was withdrawn for a period of 72 hours by qPCR and immunocytochemistry. For qPCR assay, we chose to analyze two markers of the ESC (UTF1 and Nanog) and EB (IGF2 and Hand1) state as expression of these four genes changed most significantly upon differentiation in our qPCR analysis (Fig. 4). No change in expression of either ESC (SSEA4 and Oct4) or EB markers (AFP) could be detected in this time period by immunocytochemistry (Fig. 6). However, qPCR readily detected a significant change in cultures maintained without bFGF for 72 hours: IGF2 and Hand1 were expressed 3.6-fold and 2.3-fold higher in hESC cultures without bFGF, whereas no significant changes were observed for the two most differentially expressed ESC markers (UTF: 1.4-fold and Nanog: 1.5-fold) detected by our qPCR analysis. These changes, despite smaller than those seen in 7-day and 14-day EBs, were similar in profile to changes when cells undergo differentiation.

Fig 6.

Fig 6

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No difference in ESC and EB marker expression by immunocytochemistry between hESC cultures maintained with bFGF and cultures where bFGF was withdrawn for a period of 72 hours. (A-B) Immunostaining of SSEA4 (red) shows similar expression levels in these two cell populations (with and without supplement bFGF). (C-D) Immunostaining of Oct4 (red) shows most of the cells are positive, while only occasional AFP positive cells (green) are seen outside the colonies in both hESC populations. Scale bar=100 μm.

Discussion

Since the first derivation of hESC lines in 1998, information on gene expression in hESCs and other human stem cells has been accumulated rapidly using a variety of techniques such as microarray, SAGE, EST scan and MPSS [17-21; 24]. A large number of genes have been identified that are expressed at high levels in undifferentiated hESCs and “stemness” genes that define a stem cell state have been proposed [18; 37]. Expression of many of these genes is down-regulated as hESCs differentiate, and parallel to this, many genes are induced during differentiation. Nevertheless, there are no defined set of markers that can be routinely used for assessing the different states of hESCs, i.e., the undifferentiated ESC stage and different stages of differentiating EBs. In the present study, we compared published reports on gene expression in ESCs and EBs and selected a set of 109 known genes including 55 stem cell, 12 ectoderm, 19 endoderm, 15 mesoderm, 4 trophoblast and 4 germ cell markers as potential ESC or EB specific markers. We show that this set of genes can serve as indicators of the states of hESCs using four independent methods, qPCR, immunocytochemistry, RT-PCR and microarray, using at least three different hESC lines for each method.

It is clear that no single marker is sufficient to define the state of hESCs. Several surface antigens including SSEA and TRA are useful markers for undifferentiated hESCs as their level of expression is down-regulated as hESCs differentiate. The genes encoding them however, have yet to be identified. Other pluripotency genes including two well-characterized transcription factors, Oct4 and Nanog, are good markers to assess the presence of undifferentiated hESCs. Oct4 and Nanog are essential for the maintenance of pluripotency in both hESCs and mESCs and knock-out or knock-down of either gene causes differentiation [38; 39]. Oct4 and Nanog are, however, not uniquely expressed in undifferentiated hESCs: Oct4 is expressed in germ cells and Nanog has recently been reported to be expressed in mature tissues [40; 41]. Moreover, the expression of Oct4 declines slowly as cells differentiate and the change in levels is small. For example, we have detected Oct4 expression in hESCs that underwent differentiation for a week or underwent neuronal differentiation on PA6 cells for 2 weeks (unpublished results). Our qPCR results likewise showed only a moderate decrease in Oct4 expression in 7-day EBs and only a 5-fold decrease in 14-day EBs. Taken together, we believe that while SSEA, TRA, Oct4 and Nanog are useful for distinguishing undifferentiated hESCs from their differentiated progeny, expression of these markers alone or in combination is not enough to define the undifferentiated hESC populations. Likewise, expression of a single marker is not a definitive indicator of the differentiated EB state. Indeed, some of the early differentiation genes including keratin, actin and tubulin were expressed at low levels in undifferentiated hESCs; however, their expression was strongly up-regulated as hESCs formed EBs [19]. Since the differentiated progeny of hESCs include a number of cell types, it is important to assess EBs using a combination of endoderm, mesoderm and ectoderm markers.

Our assessment of RT-PCR as a method of examining hESC cultures showed that even though it is not quantitative, it is quite robust provided appropriate genes are selected for assessment. Primers were designed to all 109 genes and the expression of 35 candidate ESC and EB genes was confirmed by RT-PCR. Our data showed that undifferentiated hESCs could be readily distinguished from differentiating EBs by assessing 10-20 markers using semi-quantitative RT-PCR. The relatively specific expression of ESC and EB markers in undifferentiated hESCs and in EBs provides a simple method to assess the quality of RNA samples for different purposes and to estimate the level of differentiation in hESC culture.

In addition to the confirmation of differential expression in hESCs and EBs by RT-PCR, we examined the expression of many of these genes by immunocytochemistry. These included markers that have not previously been analyzed by antibody staining in hESCs such as PODXL, ITGB1 and Nanog. Nanog, PODXL, ITGB1 and CDH1 were down-regulated in 7-day EBs, and further decreased in 14-day EBs. Similarly, expression of differentiation markers such as AFP, GATA4 and GATA6 were strongly up-regulated in 7-day EBs. These markers, together with the SSEA and TRA surface markers can reliably detect the differentiation of hESCs and can be used for routine examination of differentiation in hESC cultures. Although immunostaining is relatively more time consuming, it offers unprecedented resolution allowing one to rapidly assess the degree of contamination or the extent of differentiation.

RT-PCR and immunocytochemistry, however, are not suitable for scaling up or processing of a large number of markers. We therefore examined if the genes identified as candidate markers can be used to assess differentiation using a microarray platform. Our results showed that many though not all genes show detectable changes in gene expression even in a relatively poor quantitative method such as microarray. For example, Oct4, Lin28, TDGF1 and GDF3 were present at significantly higher levels in hESCs than in EBs; while Col2A1, Col1A1 and SerpinA1 were present higher in EBs using the Illumina BeadArray. The difference in gene expression were present in five hESC lines tested in this study and in six other cell lines evaluated (Jeanne Loring, Burnham Institute, personal communication), indicating that these genes may serve as a standard measure of changes irrespective of the cell line being used. Other genes that were expected to serve as useful markers and showed utility in immunocytochemistry and RT-PCR were not as useful in this microarray format. Such genes included Nanog, Sox2 and Sox1 (see Supplementary Table 2 for a complete list), indicating that candidate genes will have to be assessed in each individual platform to determine if they are adequate within the limitations of that particular technology.

Among the 109 genes, six of each undifferentiated and differentiated markers (at least one marker of each germ layer) were further examined by qPCR in undifferentiated hESCs and two stages of EBs (7-day and 14-day). We reasoned that careful quantitation may allow one to use only a small subset of markers. Indeed our results showed that as few as six markers may be sufficient provided both positive and negative markers were used. Whereas down-regulation of Oct4 was gradual during differentiation, expression of Nanog and UTF1 declined more than 200-fold in 14-day EBs, suggesting that these markers are good indicators of the undifferentiated ESC state. Dramatic up-regulation of expression in EBs was also found for an imprinted gene IGF2, and for Hand1. Expression of IGF2 and Hand1 were quickly up-regulated in 7-day EBs by several thousand folds and by day 14, the expression levels were 3 million-fold higher for IGF2. It therefore seems that undifferentiated hESCs and their derivatives can be discriminated by examining a few genes using a quantitative method, if the genes are appropriately selected. UTF1 and Nanog are excellent candidates for markers of the undifferentiated state, whereas IGF2 and Hand1 are good markers for differentiated EBs. The dramatic changes in expression level of these four genes upon differentiation can be reliably used for assessing the undifferentiated ESC and differentiated states. Moreover, negative markers (differentiated EB markers) are more sensitive than positive markers (undifferentiated ESC markers) in detecting differentiation in hESCs. These conclusions are supported by experiments designed to detect smaller changes of differentiation in hESC cultures where bFGF was removed for a period of three days. Whereas immunocytochemistry could not detect any difference in bFGF treated and bFGF withdrawn cultures using ESC or EB markers, bFGF withdrawn hESC cultures could be readily distinguished from their sister culture maintained with bFGF by qPCR using negative markers (IGF2 and Hand1).

As more data on hESCs are collected, additional markers for undifferentiated and differentiated cells will undoubtedly be identified. For example, a large number of novel genes or genes of unknown function that show a similar robust alteration in expression levels as hESCs differentiate [18] may be included in future arrays or qPCR sets to provide an additional level of sensitivity to allow a finer dissection of the state of differentiation. The present lists, however, provides useful information for evaluating the states of hESC populations, extent of differentiation or for quality control of hESC cultures. Our results suggest that any of the four methods we describe here can be used to monitor the transition of undifferentiated hESCs to differentiated EBs when a combination of ESC and EB markers from our list were tested.

Conclusion

Our strategy of including a combination of genes that are down-regulated and up-regulated during differentiation which includes genes that represent different cell types (undifferentiated cells and cell types of the three germ layers, as well as trophoblast and germ cells) allows one to identify a set of markers that can be readily assessed by routine molecular or cellular biology methods. We believe that any of the methods we tested is sufficient to monitor the state of hESC but each method has its advantages and disadvantages. If qPCR is used, a small number of genes are sufficient provided both positive and negative markers are used [see present results and 42]. However, the most cost-effective method for the wealth of information obtained may be a focused array that includes many markers such as the genes we have described. Efforts to generate such an array are in progress [43, Ian Lyons, Invitrogen, personal communication]. Alternatively, microfluidic plates allow to custom design markers and have the advantages of being able to be adapted to very small number of cells.

Acknowledgements

We acknowledge the support of CNS foundation, NIA, NIDA and the Packard Center. We thank Drs. Tim McDaniel and David L Barker for sharing the Illumina BeadArray analysis and Rose Amable for technical assistance.

References

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