| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
|
|
|
|||||||
|
|||||||||
a Terry Fox Laboratory, BC Cancer Agency, Vancouver, British Columbia, Canada;
b Michael Smith Laboratories, University of British Columbia, Vancouver, British Columbia, Canada;
c Department of Cancer Endocrinology, BC Cancer Agency, Vancouver, British Columbia, Canada;
d Departments of Chemical and Biological Engineering,
e Medicine, and
f Surgery, University of British Columbia, Vancouver, British Columbia, Canada
Key Words. Embryonic stem cells • Markers • Pluripotency • Leukemia inhibitory factor • Gene expression • Microarray
Correspondence: Cheryl D. Helgason, Ph.D., Department of Cancer Endocrinology, BC Cancer Agency, 675 West 10th Avenue, Vancouver, BC, Canada, V5Z 1L3. Telephone: 604-675-8011; Fax: 604-675-8183; e-mail: chelgaso{at}bccrc.ca
 |
ABSTRACT |
|---|
 Top Abstract IntroductionMaterials and MethodsResultsDiscussionSummaryReferences |
|---|
|
INTRODUCTION |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionSummaryReferences |
|---|
Unlike hematopoietic stem cells, for which quantitative assays of stem cell potential have been defined and validated, no such assays currently exist for ESCs. In the murine system, self-renewal is measured by the ability of mouse ESCs to continuously proliferate in culture while maintaining an undifferentiated colony morphology [6]. The most rigorous in vivo assay to establish functionality of cultured mouse ESCs is blastocyst injection and measurement of their ability to give rise to chimeric mice because it requires ESC contribution to all adult tissue, including germ cells [1]. However, injection of 10 to 15 ESCs into a single blastocyst does not provide a quantitative measure of stem cell potential at the single-ESC level. Two in vitro assays have been used extensively as surrogates for chimera formation when testing culture reagents or examining the consequences of genetic manipulation. The colony-forming cell (CFC) assay is used to determine the plating efficiency of ESC populations under various conditions and thus may be considered indicative of self-renewal potential. Formation of embryoid bodies (EBs) can be performed at a clonal level in vitro and reflects multilineage differentiation potential [7]. The correlation between these in vitro assays and chimera generation has not been determined. Assessment of pluripotency has also relied on the expression of selected molecular markers. For murine ESCs, these have included alkaline phosphatase, the POU transcription factor Oct-4, and stage-specific embryonic antigen 1 (SSEA-1) [8]. However, the correlation between marker expression and the various functional assays has not been extensively studied. Knowledge of the intricate mechanisms regulating ESC pluripotency and differentiation potential is currently limited to a few signaling pathways (i.e., leukemia inhibitory factor [LIF]) and regulatory factors (i.e., Oct-4 and Nanog). Thus, very little is known about the tolerance limits of different culture conditions for maintaining stem cell function during expansion or how these relate to altered gene expression patterns in ESCs. Identification of molecular markers that correlate with pluripotency would be invaluable to enrich for the desired cells, as well as to monitor their maintenance during expansion protocols.
Achieving the goal of defining the core stem cell regulatory network requires a precise characterization of the functional capacities of the cells for which the transcriptional profile is described. In this study, we established gene expression profiles during early differentiation of the well-defined R1 ESC line [9] and correlated gene expression changes with both phenotypic and functional assessment of the same cells. Functional capacity was determined by blastocyst injections for chimeric mouse formation, EB assays, and CFC counts. Undifferentiated ESCs and ESCs cultured without LIF for 18 or 72 hours were chosen for gene-array analysis. We identified 473 unique genes as significantly differentially expressed during early ESC differentiation, and approximately one third of these have unknown biological function. Among the 275 genes whose expression decreased with ESC differentiation were several factors previously identified as important for, or markers of, ESC pluripotency, including Stat3, Rex1, Sox2, Gbx2, and Bmp4. A significant number of the decreased genes also overlapped with previously published mouse and human ESC data. Reverse transcription–polymerase chain reaction (RT-PCR) validation showed high correlation with the gene-array data, and several genes were also shown to have similar changes after LIF removal in two other murine ESC lines. Expression of the commonly used ESC markers Oct-4 and SSEA-1 was also examined in parallel with the functional assays. However, a close correlation was not observed. Interestingly, among a subset of 48 decreased genes that showed the closest correlation with the functional assays was the stem cell factor (SCF) receptor c-Kit that can be a useful marker of undifferentiated ESCs.
|
MATERIALS AND METHODS |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionSummaryReferences |
|---|
MEFs were maintained at 37°C humidified air with 5% CO2 in DMEM supplemented with 10% FBS, 100 U/ml penicillin, 100 µg/ml streptomycin, and 100 µM MTG. Cells to be irradiated were trypsinized, resuspended in 2 ml of medium, and exposed to 60 Gy from an x-ray source before replating for use as feeder cells. Alternatively, MEFs for RNA isolation were grown in ESC maintenance media, trypsinized, pelleted, and placed in Trizol reagent (Invitrogen).
Preparation of ESCs for Differentiation
ESCs were thawed and cultured for two passages over 96 hours as described above. To prepare cells for differentiation, they were harvested and washed as described above, resuspended in ESC maintenance medium, and preplated on tissue culture plates for 1 hour at 37°C, 5% CO2 to deplete contaminating MEFs. At the end of this preplating step, the nonadherent ESCs were discarded and the loosely adherent ESCs were collected by gently washing the surface of the tissue culture plate. Cells were pelleted by centrifugation, and viable cell numbers were determined. The frequency of contaminating MEFs in the undifferentiated (day 0) ESC samples was estimated to be less than 0.2% based on cell size during counting.
A portion of the preplated ESCs was suspended at a density of 1 to 2 x 107 cells per 50 ml in liquid differentiation medium consisting of Iscove’s modified Dulbecco’s medium (IMDM), 15% FBS selected for its ability to support ESC differentiation, 2 mM glutamine, 150 µM MTG, and 40 ng/ml murine STI and plated into 4 x 100-mm Petri-style culture dishes (Falcon). Cells were cultured overnight (18 hours) at 37°C, 5% CO2. The following morning, EBs, both in suspension and loosely attached, were harvested and allowed to settle to the bottom of a 50-ml conical tube for approximately 10 minutes. The supernatant, containing mainly single cells, was removed, and the spontaneously pelleting EB fraction was collected by centrifugation at 1,200 rpm for 7 minutes. EBs were disrupted by incubation in T/E for 3 minutes at room temperature followed by passage through a 21-gauge needle to achieve single-cell suspensions. The cells were washed with 10% DMEM and suspended in 2 ml of IMDM to count.
The remainder of the preplated ESCs was plated at a density of 104 cells per 35-mm low-adherence Petri dish in IMDM-based ES differentiation methylcellulose consisting of 0.9% methylcellulose, 15% FBS, 2 mM glutamine, 150 µM MTG, and 40 ng/ml murine SCF. Cultures were grown for 3 days and all EBs in each dish were harvested by carefully flooding the dish with IMDM and collecting the methylcellulose/EB solution. EBs were washed twice in DMEM plus 10% FBS to remove the residual methylcellulose and were then pooled and disrupted as described above.
Blastocyst Injection
C57Bl/6J mice (used as blastocyst donors) and B6C3 F1 females (used as pseudopregnant blastocyst recipients) were purchased from the in-house breeding program at the BC Cancer Agency Animal Resource Center. All mice were maintained with sterilized food, water, and bedding. All protocols were conducted according to guidelines set forth by the Canadian Council for Animal Care and approved by the Animal Care Committee at the University of British Columbia. R1 ESCs were thawed and maintained for two passages on irradiated MEFs with daily feeding of maintenance medium. After the second passage, cells were harvested and subjected to 1 hour of preplating on plastic to deplete remaining MEFs. Cells were then plated onto gelatin-coated tissue culture dishes and fed with maintenance medium without LIF for the indicated lengths of time. To produce chimeras, 15 test cells (either ESCs or differentiated) were injected into 3.5-day blastocysts from C57Bl/6 mice as described previously [12] and implanted back into pseudopregnant recipient females to gestate normally. Coat color was used to identify chimerism of the resulting pups. Two independent experiments were performed.
Embryoid Body Formation Assays
Single-cell suspensions were collected on day 0 or prepared, as outlined above, during differentiation. Defined numbers of cells (500 to 20,000, depending on time after LIF removal) we replated in 35-mm Petri-style dishes in the ESC differentiation methyl-cellulose medium described above to determine the efficiency of EB formation. EB numbers were determined microscopically after 5–6 days of culture, and colonies were qualitatively scored as large or small. Three independent experiments were performed. The percent EB formation efficiency was calculated by dividing the total number of EBs formed by the number of cells plated multiplied by 100.
CFC Assay
Single-cell suspensions collected on day 0 or during differentiation were plated at various densities (500 to 20,000 cells per gelatinized 60-mm gridded tissue culture dish) to determine ESC CFC plating efficiency. Colonies were microscopically enumerated after 5–6 days of growth. To enable differential assessment of the colonies, the protocols outlined in the alkaline phosphatase detection kit (Sigma; 86-R) were modified for staining in 60-mm dishes. In brief, the medium was removed from the dishes, and 1 ml of room temperature fixative (prepared as per the Sigma protocol) was added for 30 seconds. The fixative was removed, and colonies were washed with 2 ml phosphate-buffered saline (PBS). Next, 1.5 ml alkaline dye mixture (prepared as per the Sigma protocol) was added; the dish was incubated in the dark at room temperature for 15 minutes. Finally, the dye mixture was removed and the colonies were covered with 2 ml PBS for microscopic evaluation. The numbers of stained (undifferentiated) versus unstained (differentiated) colonies were determined. Three independent experiments were performed. The percent CFC plating efficiency was calculated by dividing the total number of alkaline phosphatase–positive colonies by the number of cells plated multiplied by 100.
RNA Extraction and Array Hybridization
Single-cell suspensions of test cells were prepared as described above and resuspended in Trizol (Invitrogen Life Technologies) at a density of 107 cells per ml. RNA was extracted following the manufacturer’s instructions. Standard Affymetrix amplification protocols were used to prepare probe RNA for Affymetrix arrays with 5 µg of starting total RNA. Biotin-labeled amplified RNA was fragmented, and hybridization cocktails were prepared according to the Affymetrix protocol. The mouse GeneChip (MG) U74v2 chips were hybridized on a GeneChip System (Affymetrix) at the Genome Science Centre, BC Cancer Agency, Vancouver, British Columbia, Canada, according to the manufacturer’s instructions. All experiments were performed in triplicate with the exception of the MEF samples, which were analyzed in duplicate. The MIAME (minimal information about a microarray experiment) guidelines were followed for data presentation [13].
Data Analysis
The Affymetrix software MicroArray Suite 5.0 (MAS 5.0) was used to generate absolute expression estimates (absence/ presence calls) from the raw data. Software default thresholds were used to determine the present (P) or absent (A) calls (
1 = 0.04, 2 = 0.06, and 
= 0.015). The data obtained from MAS 5.0 were then normalized and further analyzed in the Gene-Spring software version 6.2 (Silicon Genetics, Redwood City, CA). Per-chip normalization was done as follows: Values below 0.01 were set to 0.01, and then each measurement was divided by the 50th percentile of all measurements in that sample. Per-gene normalization was done as follows: Each gene was divided by the median of its measurements in all samples. If the median of the raw values was less than 10, then each measurement for that gene was divided by 10. We judged genes to be differentially expressed during ESC differentiation only when the difference in expression between two time points was at least twofold, the gene was identified by MAS 5.0 as present in two out of three replicates or present or marginal in all three replicates at the time point with the highest expression level, and the extent of difference in expression was statistically significant (p < .05 in a parametric Welsh analysis of variance [ANOVA] t-test). Classification of genes into functional categories was done by collecting annotations and keywords with the Onto-Express Tool (http://vortex.cs.wayne.edu:8080/ontoexpress) [14],Affymetrix Net Affx (http://www.affymetrix.com/analysis/index.affx), and the Simplified Gene Ontology Tool included in the GeneSpring 6.2 Software. The GenMapp 2.0 software tool was used to analyze signaling pathways (http://www.genmapp.org).
Quantitative RT-PCR
RNA was isolated using Trizol, and the samples were then treated with DNase I (amplification grade) before RT-PCR according to the manufacturer’s recommendations (Invitrogen). Complementary DNA (cDNA) was generated by RT with random primers and the Superscript II enzyme and RNase inhibitor (Invitrogen). The RT reaction was incubated at 42°C for 50 minutes followed by 15 minutes at 70°C. The cDNA was stored at –20°C for subsequent quantitative PCR analysis. Gene transcripts were quantified by real-time PCR using the iCycler apparatus (BioRad Inc., Hercules, CA) and were detected with SYBR Green as fluorochrome (IQ SYBR Green Supermix, BioRad Inc.). Gene sequences for primer design were obtained from the NCBI Reference Sequences database (http://www.ncbi.nlm.nih.gov/RefSeq/). Primers were chosen using the Primer3 software (http://www.broad.mit.edu/cgi-bin/primer/primer3_www.cgi), and the specificity of all primer pairs was tested with electronic PCR using the mouse genome and the mouse transcript database (http://www.ncbi.nlm.nih.gov/sutils/e-pcr/reverse.cgi). Primer sequences are provided in the supplemental material (supplementary online Table 1). Primers were ordered and synthesized at Invitrogen Life Technologies (http://www.invitrogen.com/). The relative expression changes were determined with the 2–
CT method [15], and the housekeeping glyceraldehyde-3-phosphate dehydrogenase (GAPDH) gene transcript was used to normalize the results. PCR efficiency was tested for each primer pair by dilution series of cDNA to make sure that the efficiency was appropriate for the 2–CT method (i.e., 95% or above). To identify amplification of any contaminating genomic DNA and ensure the specificity and the integrity of the PCR product, melt-curve analyses were performed on all PCR products. No products were obtained with real-time PCR from RNA samples when RT was omitted. Samples without template were included for each primer pair to identify contamination. Pearson’s correlation and Deming regression analysis were used to determine correlation and agreement, respectively, between the microarray and quantitative RT-PCR results using the Excel plug-in software Analyse-It v1.73.
Flow Cytometry
Antibodies used for phenotype analysis included phycoerythrin -conjugated anti-CD117 (c-Kit, clone ACK45; BD Pharmingen, San Diego) as well as purified anti-SSEA-1 (Clone MC-480; Chemicon International Inc., Temecula, CA), which was detected using a fluorescein isothiocyanate–conjugated anti-mouse immunoglobulin M antibody (BD Pharmingen). Single-cell suspensions collected on day 0 or prepared from differentiating ESCs were blocked for 10 minutes on ice with 5 µg/ml anti-mouse CD16/CD32 (Fc Block, BD Pharmingen) in PBS (STI) plus 2% FBS (PF). Cells were washed once with PF and then incubated on ice for 20 minutes with the primary monoclonal antibody. Cells were then washed once, incubated with the secondary antibody if needed, washed again, and analyzed by flow cytometry using a FACSCalibur flow cytometer and CELL Quest software (BD Pharmingen). The forward- versus side-scatter profile was used to gate on viable cells, and an unstained sample was used to determine appropriate gating for quantification of expression. Cells to be stained for Oct-4 were resuspended in 100 µl of Hanks’ buffered saline solution (STI) plus 2% FBS (HF) and fixed with 100 µl of Intra Prep Permeabilization Reagent 1 (Immunotech, Westbrook, ME) for 15 minutes at room temperature. Cells were then washed with HF and permeabilized with IntraPrep Permeabilization Reagent 2 for 5 minutes before incubation with a 1:100 dilution of mouse anti-mouse Oct3/4 monoclonal antibody (Transduction Laboratories, Lexington, KY) for 15 minutes at room temperature. Cells were washed with HF before staining with allophycocyanin-labeled anti-mouse immunoglobulin G1 (BD Pharmingen). Samples were analyzed by flow cytometry as outlined above.
Comparison with Other Gene-Array Data
Genes indicated as "decreased" in supplementary online Table 2 were split into three separate lists based on the statistical significance of the fold change between 0 and 18 hours, 0 and 72 hours, and 18 and 72 hours. Each of these three gene lists was compared with the following data tables: Bhattacharya et al. [16], supplementary online Table 2; Brandenberger et al. [17], supplementary online Table 2; Ivanova et al. [18], supplementary online Table 1 (genes marked as either I or D); Ramalho-Santos et al. [19], database S1; Sato et al. [20], database 1; Sharov et al. [21], dataset S7; Sperger et al. [22], supporting supplementary online Table 6; Kelly et al. [23], supplementary online Table 1; and Ginis et al. [24], supplementary online Table 3A. Comparison between [18] and [19] was performed on the basis of Affymetrix gene IDs. In [19], supplementary online Table 1 was refiltered as outlined in the original publication. Comparisons with human ES data sets [16, 17, 20, 22] was done by converting public ID references from the human data sets into murine Affymetrix codes using EnsMart (http://www.ensembl.org/Multi/martview). For [21], custom U codes were converted to Unigene codes using the translation tool available (http://lgsun.grc.nia.nih.gov/geneindex/). Groups F, I, L, and O were chosen because these were the lists that contained genes expressed in ESCs grown in LIF but not expressed in ESCs grown without LIF for 4 or 18 hours. For [23], Genbank codes were converted to Affymetrix codes using EnsMart. Following automated comparisons performed as described above, manual comparison between known genes was performed using gene names to ensure accurate comparison.
|
RESULTS |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionSummaryReferences |
|---|
The baseline activities for undifferentiated ESCs in the three different assays were first determined. Undifferentiated, pre-plated R1 ESCs yielded 100% chimeric pups after blastocyst injection (27 blastocysts injected; six born and analyzed in two independent experiments), 6.9% ± 1.0% of plated cells differentiated into EBs in the EB formation assay, and 12.50% ± 2.2% of plated cells gave rise to alkaline phosphatase–positive ESC colonies in the CFC assay. These results were within the normal range for the R1 cell line. ESC differentiation was then initiated by LIF removal and replating without MEF. The morphology of the ESCs before and after LIF removal is shown in Figure 1
. At 18 and 24 hours after MEF and LIF removal, the ESCs looked very similar to one another and did not exhibit any clear signs of differentiation. Morphological differentiation was first apparent at 48 hours, and EBs could be seen after 72 hours. Despite the lack of appreciable phenotypic differentiation within the first 24 hours, there were significant changes in the functional properties of the ESCs. Cultured cells were harvested at various time points during this culture period and analyzed in the three different assays. The blastocyst injection assay showed a rapid decrease in the number of chimeras obtained after initiation of ESC differentiation (Fig. 2A). Only 28% of born pups (84 injected, 25 born and analyzed in two independent experiments) were chimeras when ESCs had differentiated for 24 hours, and less than 5% were chimeras after 72 hours of differentiation (66 injected, 29 born and analyzed in two independent experiments). The EB formation assay (Fig. 2B) showed approximately 5.5% ± 1.0%, 3.7% ± 0.3%, and 0.3% ± 0.1% readout at 18, 24, and 72 hours after LIF removal, respectively. In contrast, the frequency of cells replating in the CFC assay increased slightly during the first 24 hours but subsequently declined rapidly such that only 1.3% ± 0.3% retained this activity at 72 hours (Fig. 2C). In summary, all three assays showed clearly that most differentiation potential and self-renewing capacity was gone after 72 hours of differentiation. However, there was a high degree of variation during the first 24 hours amongst the in vitro and in vivo assays, with the EB formation assay correlating most closely with chimeric mouse formation. For the gene expression profiling, because both the EB formation and chimera assays showed a pronounced decrease within the first 18–24 hours, we elected to use the earlier time point, along with 72 hours of differentiation, to compare against the undifferentiated R1 ES.
|
|
). At 120 hours after LIF removal, 18.5% ± 1.1% of the cells retained expression of SSEA-1, whereas 40.6% ± 6.6% of the cells continued to express Oct-4. Thus there was no clear correlation between expression of these two markers and the various ESC functional assays.
Gene-Array Analysis
Cultured R1 ESCs from matched passage numbers were collected in three separate experiments at 0, 18, and 72 hours of differentiation after LIF removal and were analyzed using the Affymetrix GeneChip MG-U74v2 array containing 36,767 different probe sets. Duplicate samples of the MEF feeders were also collected and analyzed to assess any possible contamination of the undifferentiated ESCs. Hybridization, scanning, and production of raw data files were performed according to standard protocols. The MAS 5.0 software was used for the initial scaling and expression analysis. The data were then normalized and further analyzed using the GeneSpring software. To validate the reproducibility and the overall variation of the data, hierarchical clustering analysis was performed. The data were first filtered for genes present in at least one of the three time points (present in at least two out of three replicates), resulting in 13,002 different probe sets. The average number of present genes for each time point was 12,818 (coefficient of variation [CV], 6%) in undifferentiated ESCs, 11,806 (CV, 4%) at 18 hours, and 12,297 (CV, 1%) at 72 hours after LIF removal. The number of expressed genes at the different time points was not statistically significantly different. Hierarchical clustering was applied to the reduced gene set on individual array samples (three replicates for each time point) using Pearson’s correlation and average linkage clustering as implemented in GeneSpring. The individual samples from the three experiments clustered tightly together according to their respective time points, as seen in Figure 3, indicating that the overall interexperimental variation was low. The clustering also reflects the temporal progression of the ESC differentiation. As expected, the first two time points (0 and 18 hours) clustered more closely together, whereas the 72-hour time point showed a more distinct expression pattern, resulting in a greater relative distance from the other two time points, consistent with the functional data (Fig. 2).
|
Only preplated, loosely adherent ESCs were used in our experiments, and visual assessment of MEF contamination of undifferentiated ESCs suggested it was consistently less than 1 in 500. However, even with these measures, we sought to exclude the possibility that contaminating MEF cells may have distorted the data. Duplicate samples of MEFs were therefore also analyzed on the U74v2 GeneChip. The data from both the MEF and the R1 ESC was scaled in MAS 5.0 and normalized in GeneSpring 6.2 before 1% of the raw value (five times more than the estimated contamination) obtained for the gene in MEF was subtracted from the value of the same gene in the undifferentiated R1 ESCs. The analysis steps to find differentially expressed genes were then performed as described above. Only genes detected as decreased during differentiation in the original analysis were reanalyzed. Genes whose expression increased during differentiation would not be affected by MEF contamination in a way that would give false-positive results. This evaluation indicates that none of the genes that showed a significant twofold or greater decrease in the initial analysis lost their significance after MEF subtraction (data not shown) and suggests that the level of MEF contamination was not sufficient to distort the ESC gene expression data.
Gene Expression Validation
The expression patterns of some genes previously implicated in maintaining ESC pluripotency and self-renewal were analyzed to validate the data and the approach to identify differentially expressed genes (Table 1). Mouse ESCs are usually cocultured on a feeder layer of irradiated MEFs. In addition to providing a matrix for attachment, MEFs produce LIF, required for propagation of pluripotent mouse ESCs [28]. LIF-null MEFs cannot support self-renewal [29]. However, LIF also needs to be complemented by fetal calf serum to block differentiation. LIF binds to the gp130 receptor that leads to activation of the transcription factor Stat3 [1]. Stat3 was clearly detected in undifferentiated R1 ESCs, and LIF removal decreased Stat3 expression with the most pronounced effect during the first 18 hours (49% reduction). This was also seen for two other genes involved in the LIF/gp130 pathway, the Oncostatin M receptor, Osmr, and the interleukin 6 signal transducer, Il6st. A known Stat3 target gene, Pim1 [30], was also decreased significantly at the transcriptional level. Taken together, these observations confirm that the LIF/gp130/Stat3 pathway was rapidly shut down after MEF and LIF removal. The bone morphogenic proteins can act in combination with LIF to sustain self-renewal and preserve multilineage differentiation, chimera contribution, and germ line transmission properties [31]. Bmp4 transcript levels were significantly decreased during differentiation. However, the onset of the decrease was later than for Stat3 (between 18 and 72 hours, 80% reduction). The same was seen for Rex-1/Zfp42, known to be highly expressed in undifferentiated ESCs and downregulated after retinoic acid–induced differentiation [32, 33]. A 90% reduction in Rex-1/Zfp42 expression was seen between 18 and 72 hours after LIF removal. Transcript abundance of the Akp2 gene coding for alkaline phosphatase, commonly used as a marker for undifferentiated ESCs, was also decreased significantly (55% reduction between 18 and 72 hours). The POU transcription factor message, pou5f1, coding for Oct-4 was highly expressed in undifferentiated ESCs but was not changed significantly during the first 72 hours after LIF removal in keeping with the protein expression data (Fig. 2D). Transcript levels of the embryonal stem cell–specific gene 1 (Esg-1 or developmental pluripotency associated gene 5, Dppa5) did not change during differentiation. However, this observation is consistent with the observation that Esg-1 probably is a downstream target of Oct-4 and is downregulated slowly after Oct-4 suppression [34]. The abundance of FoxD3, a gene expressed early in mouse embryonic development, also remained unchanged during the first 72 hours after LIF removal. The SRY-box containing transcription factor Sox2 may act to maintain ESC pluripotency and is expressed in the ICM, epiblast, and germ cells, just like Oct-4 [35]. Sox2 was significantly decreased (60% reduction between 18 and 72 hours, p = .0136). Sox2, together with Oct-4, is involved in the regulation of fibroblast growth factor 4 (Fgf4), another factor confined to the ICM of the blastocyst [35]. Although Fgf4 transcripts were not significantly decreased (p = .09), it was reduced more than twofold (52% reduction between 18 and 72 hours). This was also the case for the newly discovered marker of ESC pluripotency Dppa3 [36], which decreased 78% between 0 and 72 hours (p = .073). Similarly, the regulatory factor Nanog, which can rescue ESCs from LIF/Stat3 dependence and maintain Oct-4 expression [37, 38], was not quite significantly decreased during the first 72 hours of differentiation (p = .07), and the reduction in expression was less than twofold (41%). Several genes indicative of ESC differentiation were increased after LIF removal. For example, the mesoderm marker Brachyury [39] increased 15-fold between 18 and 72 hours (p = .003). The ectoderm marker Nestin [40] increased approximately threefold between 18 and 72 hours (p = 0.04), and the epithelial cell marker Prominin 1 [41] increased fivefold between 18 and 72 hours (p = .0010). In conclusion, most of these changes are consistent with the loss of ESC pluripotency as measured in all three assays and indicate that the thresholds used to define differentially expressed genes in this study are reasonable.
|
), with a tendency that the PCR results showed greater changes than the array suggested (proportional bias 1.2 in a Deming method comparison analysis, not shown).
|
). Overall, there was a good correlation amongst all three ESC lines (Figs. 4B–4D). Specifically, RT-PCR analysis was able to verify the expression changes of genes such as Lox, Ankrd1, and c-Kit that showed significantly decreased transcript levels after 18 hours in all three ESC lines tested. Similarly, Rex1, Sox2, Leftb, and Mtf2 were all changed in a similar fashion in the R1, J1, and EFC cell lines. The RT-PCR results also confirmed that Oct-4 transcript levels were not decreased significantly during the first 72 hours of differentiation in any of the cell lines, in agreement with the gene-array results and the protein level observed (Fig. 2D). In contrast, although the decrease in Nanog transcripts was not quite significant in R1 ESCs according to the gene array, the RT-PCR results indicated a reduction. Nanog was reduced by 50%–70% after 72 hours in all three ESC lines according to the quantitative RT-PCR analysis but consistent with delayed reduction in Nanog upon differentiation (Table 2). Only two of the tested genes showed different expression patterns amongst the cell lines. The mesoderm marker Brachyury and the homeobox transcription factor Pbx3 were both increased during differentiation in the R1 and J1 ESCs, but not in the EFC cell line. This observation suggests that the various ESC lines might follow slightly altered differentiation pathways upon LIF removal.
|
Functional Classification of Differentially Expressed Genes
It is likely that genes showing similar functional properties and expression patterns form interacting networks that contribute to the phenotypic and functional characteristics of the cells of interest. Functional classification of the differentially expressed genes into appropriate biological processes was thus performed using the NetAffx and GeneOntology Express tools as well as the simplified gene ontology tool in the GeneSpring software package. The differentially expressed genes were separated into 13 main categories (Fig. 5A; see supplementary online Table 4 for complete lists). Many differentially expressed genes were, as expected, classified as being involved in development and differentiation (61 genes, 10%) or directly or indirectly involved in cell-cycle control and cell proliferation (32 genes, 5%). Furthermore, at least 81 genes (13%) were classified as being involved in intracellular signal transduction, cell–cell signaling, or response to external stimuli (supplementary online Table 4).
|
A signaling pathway that is of particular interest during ESC differentiation is the mitogen-activated protein kinase (MAPK) pathway. The self-renewal of ESCs is influenced by the MAPK pathway, in which expression of Erk and Shp-2 counteracts the proliferative effects of Stat3 and promotes differentiation [45]. According to the array results, the Erk gene (Mapk1 or Mapk3) and most other components in this pathway were already present in undifferentiated ESCs, and their expression levels did not change significantly at the transcription level during the first 72 hours of differentiation (data not shown). However, some genes in the MAPK pathway (e.g., Kras2 and Mapk12) had significantly increased transcript levels during differentiation, indicating an activation of the pathway (supplementary online Table 4). Furthermore, the gene coding for Grb2-associated binder 1 (Gab1) was significantly decreased (58% reduction between 18 and 72 hours, p = .0035). Gab1 binds to Shp-2 and is believed to suppress the MAPK pathway in ESCs; also, increased synthesis of Gab1 together with Oct-4 may suppress induction of differentiation [1]. Although most of the factors involved in the MAPK pathway are primarily regulated at the posttranscriptional level, the fact that transcripts for many pathway members were detected in undifferentiated ESCs suggests that they harbor the required components to quickly respond to signals that promote differentiation.
The Wnt signaling pathway is important for maintenance of pluripotency in undifferentiated ESCs, and a recent study also showed that activation of the Wnt pathway by pharmacological inhibition of Gsk-3 is able to maintain pluripotency in both human and mouse ESCs [46]. Most components of the Wnt signaling pathway could be detected in both undifferentiated and differentiated ESCs, but some factors were also significantly changed during differentiation (e.g., Fzd5, Wnt3, and CyclinD3; supplementary online Table 4). However, overall there was no dramatic change at the transcription level of several important factors belonging to this pathway during the first 72 hours of differentiation (e.g., ß-catenin, Gsk-3, and Axin; data not shown).
The Hedgehog signaling pathway plays a critical role during development and has been extensively studied in different species and tissues [47,48]. In this pathway, two receptors, Ptch and Ptch2, and two transcription factors, Gli1 and Gli2, were decreased significantly during ESC differentiation. Furthermore, at least one suggested downstream target of this pathway, the Bmp4 gene already discussed above, had significantly decreased transcription, providing additional evidence that this pathway might be involved in maintaining ESC self-renewal or pluripotency.
Importantly, out of 473 differentially expressed genes, the largest group consisted of 173 genes or expressed sequence tags with unknown biological function. Further analyses of the genes within this group whose expression changes closely correlate with loss of pluripotency may reveal novel mechanisms involved in ESC maintenance. Of the 275 genes significantly decreased during ESC differentiation, 48 genes showed a more than twofold decrease in transcript levels within the first 18 hours and continued to decrease or remained at a low level of expression until 72 hours (Table 3). Changes in the transcript levels for these genes correlated well with the functional assays, especially the chimera generation and EB formation assays (Fig. 1). At least half of them have been identified as ESC-enriched or to be downregulated during differentiation in previous studies [17–23] (see below), but several of these genes have unknown biological function or have not previously been implicated in ESC maintenance (e.g., Lox, Tnc, and Jag1; Table 3).
|
(complete list provided in supplementary online Table 5). At least 60 gene products (11%) were considered localized to the plasma membrane and might therefore be good candidates as markers for undifferentiated ESCs. Genes increased during differentiation were also included in this list of possible ESC markers because they can be used to detect the onset of differentiation or for negative selection strategies for isolating undifferentiated ESCs (Table 4). Protein expression analyses of some of these have already been conducted in relation to ESC differentiation, i.e., Cd9, Cd44, and Osmr [49–51]. Additional gene products of interest include the adhesion molecule Vcam1 and the hedgehog signaling pathway receptors Ptch and Ptch2. One gene of special interest encodes the SCF receptor c-Kit. According to the gene-array results, transcript level of the c-Kit gene was one of the most significant changes during differentiation (54% reduction between 0 and 18 hours and 75% reduction between 0 and 72 hours; p = .0016; Table 3), which also correlated well with the functional assays (Fig. 1). Furthermore, this finding was also verified in the R1, J1, and EFC ESC lines by quantitative RT-PCR (Table 2). No c-Kit ligand/SCF was added to the culture medium used in these experiments, and SCF was not detected in the undifferentiated R1 ESCs, although it was indeed present at high levels in the MEF according to the gene-array results (data not shown). Because c-Kit is expressed on several pluripotent cell types, including germ cells and hematopoietic stem cells, and antibodies are commercially available, we were able to compare the results of the array and RT-PCR experiments with protein expression levels measured by flow cytometry (Fig. 6). This analysis revealed that expression of c-Kit on the cell surface of differentiating ESCs closely paralleled the loss of functional potential as measured using the EB formation assay (Fig. 7). At later time points, the correlation was not as close (i.e., EB formation capacity continued to decrease while protein expression remained unchanged), suggesting the emergence of differentiated cell types expressing c-Kit protein.
|
|
|
The gene expression data reported here were compared with nine different gene-array data sets, comprising four studies on murine ESCs [18, 19, 21, 23], four studies on human ESCs [16, 17, 20, 22], and one study comparing human and mouse ESCs [24] (summarized in Table 5). Only genes downregulated during differentiation after LIF removal were used in the comparisons because most other studies only report ESC-enriched or ESC-specific genes. Complete gene lists derived from these comparisons can been found in supplementary online Table 6.
|
). The data set generated by Kelly et al. [23] stood out because of its high degree of overlap (35%), which can potentially be explained by the similarity in the two studies in terms of experimental design and the similarity of the genetic background of the ESCs used. However, this encompasses relatively few genes (6 out of 17 genes). Furthermore, many genes that we report as decreased during the first 72 hours were reported as also being present in human ESCs by Sato et al. [20]. However, they were not identified as differentially expressed in that study. This discrepancy could possibly be due to the later time point (3 weeks) used for determining differential expression in that study (data not shown).
No single gene was found enriched in every human and mouse ESC data set. Jade1, Leftb, and Smarcad1 were the most commonly identified genes in other data sets (i.e., in six of nine other data sets). Leftb is a transforming growth factor-beta family member, which is expressed on the left side of developing mouse embryos and is implicated in left-right determination [54]. Jade1 was recently identified as a gene involved in anteroposterior axis development [55]. Smarcad1 has previously been identified as a marker of preimplantation embryos [56]. The gene coding for Tenascin-C was downregulated within the first 18 hours after LIF removal (Table 3) and was also commonly observed as differentially expressed in other data sets (i.e., in four of eight data sets). Tenascin, also known as hexabrachion and cytotactin, is an extra-cellular matrix protein with a spatially and temporally restricted tissue distribution that is tightly regulated during embryonic development and in adult tissue remodeling [57]. Other commonly identified markers of undifferentiated ESCs were also found in this comparison. Sox2, Rex1, Bmp4, and Gbx2 were all observed in at least three other data sets. This also included the gene Lox, coding for lysyl oxidase, found in three other murine data sets [18, 19, 21]. It was in fact one of the most pronounced and rapidly downregulated genes detected (Table 3). At least one study identified c-Kit as enriched in ESCs, intriguingly in human ESCs [22]. Overall the comparison with previously published data indicated some intriguing similarities but also showed that most genes do not overlap in pairwise comparisons. This underlines the many differences that might arise when different sources of cells, culture conditions, microarray technique platforms, and data analysis tools are used and emphasizes the need to correlate expression changes with rigorous measures of ESC competence and differentiation potential.
|
DISCUSSION |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionSummaryReferences |
|---|
We combined defined culture and differentiation conditions with various measures of ESC pluripotency to determine optimal times for gene expression analysis using high-density oligonucleotide microarray. The results showed that the functional capacity of ESCs declines rapidly under differentiation conditions, with the most pronounced changes in function occurring during the first 18–24 hours of differentiation. The gene expression results were subsequently used to find genes whose expression correlated with loss of pluripotency and that could explain loss of this capacity during differentiation or serve as markers for pluripotent ESCs. Analysis of the gene-array data revealed that 473 genes were differentially expressed during the first 72 hours of ESC differentiation, suggesting they are potentially important for the maintenance of ESC pluripotency and self-renewal.
Important roles in the maintenance of undifferentiated ESCs have previously been demonstrated for several of the downregulated factors such as Stat3, Rex1, Sox2, Gbx2, and Bmp4. Intriguingly, one third of the differentially expressed genes have not been characterized in terms of involvement in biological processes. More important, a refined list of 48 genes whose transcript levels closely correlated with the functional assays (i.e., with early and persistent decreases in transcript levels after LIF removal) contains several genes with unknown function or genes that have not previously been suggested to play a role in ESC maintenance (Table 3). These genes may be novel candidates to play critical roles in the regulation of ESC pluripotency and self-renewal. Several of the genes in this list have also been found in previous gene expression studies in human or mouse ESCs (e.g., Tnc and Lox; Table 3). Furthermore, several promising candidate markers for pluripotent ESCs were identified from the gene-array analysis (Table 4). The changes in transcript levels observed for one gene, c-Kit, were also verified at the protein level and showed good correlation with functional measures of ESC pluripotency (Fig. 7). This finding was verified in two other murine ESC lines (Table 2). Two other commonly used ESC markers, Oct-4 and SSEA-1, were also analyzed in parallel with the functional assays used in this study but showed poor correlation with the outcome in these (Fig. 2D). Further studies are needed to determine if our candidates (e.g., c-Kit) are more reliable markers of, and useful to enrich for, undifferentiated pluripotent ESCs. Additional work is also required to determine the functional significance of these observations for ESC maintenance. It is also important to note in the context of these and other genes of interest that global gene expression profiling does not discriminate between changes arising at the level of transcription versus mRNA stability. Also, changes in transcript levels in a subset of cells may go undetected, and likewise subtle changes might arise from changes in just a small proportion of the cells.
Transcriptional profiling of various stem cell populations has been used to determine the types of regulatory factors and signaling pathways present in pluripotent cells, including ESCs [16–24, 34]. Comparing genes that were significantly decreased in our analysis with both murine and human data sets [16, 17, 20, 22] gave a large overlap with 176 of 298 genes identified in at least one of these other studies. Of note, 139 of these have been identified in other murine ESC studies. This analysis was not able to distinguish biological differences between human and murine ESCs because of the way it was performed. Undue emphasis was placed on the findings reported in this publication by comparing all publications with data. The level of overlap between our data and other murine studies was higher than the overlap with other human studies, but the difference can probably be accounted for by the increased difficulty of gene comparison between species. However, additional ESC gene expression profiling carried out in an analogous stringent manner (i.e., correlating measurable functional properties with transcript levels) is needed to accurately assess and determine the confidence in the degree of overlap in differentially expressed genes after ESC differentiation. Induction of ESC differentiation by alternative methods or using ESCs derived from mice of different genetic backgrounds will also be important to properly assess. Such analyses should be able to discriminate between treatment-specific or genetic-specific gene expression changes and those commonly observed under various conditions. These latter genes are more likely to play an important role in regulating ESC self-renewal and pluripotency.
|
SUMMARY |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionSummaryReferences |
|---|
|
ACKNOWLEDGMENTS |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionSummaryReferences |
|---|
|
REFERENCES |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionSummaryReferences |
|---|
This article has been cited by other articles:
|
|
 |
|
  S. J. Chamberlain, D. Yee, and T. Magnuson Polycomb Repressive Complex 2 Is Dispensable for Maintenance of Embryonic Stem Cell Pluripotency Stem Cells, June 1, 2008; 26(6): 1496 - 1505. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. D. O'Connor, M. D. Kardel, I. Iosfina, D. Youssef, M. Lu, M. M. Li, S. Vercauteren, A. Nagy, and C. J. Eaves Alkaline Phosphatase-Positive Colony Formation Is a Sensitive, Specific, and Quantitative Indicator of Undifferentiated Human Embryonic Stem Cells Stem Cells, May 1, 2008; 26(5): 1109 - 1116. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
Y. M.-S. Tay, W.-L. Tam, Y.-S. Ang, P. M. Gaughwin, H. Yang, W. Wang, R. Liu, J. George, H.-H. Ng, R. J. Perera, et al. MicroRNA-134 Modulates the Differentiation of Mouse Embryonic Stem Cells, Where It Causes Post-Transcriptional Attenuation of Nanog and LRH1 Stem Cells, January 1, 2008; 26(1): 17 - 29. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 A. P. Beltrami, D. Cesselli, N. Bergamin, P. Marcon, S. Rigo, E. Puppato, F. D'Aurizio, R. Verardo, S. Piazza, A. Pignatelli, et al. Multipotent cells can be generated in vitro from several adult human organs (heart, liver, and bone marrow) Blood, November 1, 2007; 110(9): 3438 - 3446. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. Pick, L. Azzola, A. Mossman, E. G. Stanley, and A. G. Elefanty Differentiation of Human Embryonic Stem Cells in Serum-Free Medium Reveals Distinct Roles for Bone Morphogenetic Protein 4, Vascular Endothelial Growth Factor, Stem Cell Factor, and Fibroblast Growth Factor 2 in Hematopoiesis Stem Cells, September 1, 2007; 25(9): 2206 - 2214. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. Heuser, B. Argiropoulos, F. Kuchenbauer, E. Yung, J. Piper, S. Fung, R. F. Schlenk, K. Dohner, T. Hinrichsen, C. Rudolph, et al. MN1 overexpression induces acute myeloid leukemia in mice and predicts ATRA resistance in patients with AML Blood, September 1, 2007; 110(5): 1639 - 1647. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
D. Wegmuller, I. Raineri, B. Gross, E. J. Oakeley, and C. Moroni A Cassette System to Study Embryonic Stem Cell Differentiation by Inducible RNA Interference Stem Cells, May 1, 2007; 25(5): 1178 - 1185. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 Z.-X. Wang, C. H.-L. Teh, J. L. L. Kueh, T. Lufkin, P. Robson, and L. W. Stanton Oct4 and Sox2 Directly Regulate Expression of Another Pluripotency Transcription Factor, Zfp206, in Embryonic Stem Cells J. Biol. Chem., April 27, 2007; 282(17): 12822 - 12830. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 S. Katiyar, X. Jiao, E. Wagner, M. P. Lisanti, and R. G. Pestell Somatic Excision Demonstrates that c-Jun Induces Cellular Migration and Invasion through Induction of Stem Cell Factor Mol. Cell. Biol., February 15, 2007; 27(4): 1356 - 1369. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 A. Bashamboo, A. H. Taylor, K. Samuel, J.-J. Panthier, A. D. Whetton, and L. M. Forrester The survival of differentiating embryonic stem cells is dependent on the SCF-KIT pathway J. Cell Sci., August 1, 2006; 119(15): 3039 - 3046. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
L. Palmqvist, B. Argiropoulos, N. Pineault, C. Abramovich, L. M. Sly, G. Krystal, A. Wan, and R. K. Humphries The Flt3 receptor tyrosine kinase collaborates with NUP98-HOX fusions in acute myeloid leukemia Blood, August 1, 2006; 108(3): 1030 - 1036. [Abstract] [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
| STEM CELLS | THE ONCOLOGIST | CME | ALPHAMED PRESS JOURNALS |
) was monitored at the indicated times during embryonic stem cell differentiation using flow cytometry, and expression levels were plotted as percent gated cells versus time (right axis). Embryoid body (EB)–forming cell frequency (
) determined on the same cell populations is also shown (percent EB formation indicated on the left axis).