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Combined mRNA and microRNA profiling reveals that miR-148a and miR-20b
control human mesenchymal stem cell phenotype via EPAS1
Karine Giraud-Triboult2*, Christelle Rochon-Beaucourt1£*, Xavier Nissan2, Benoite Champon2,
Sophie Aubert2, Geneviève Piétu1 **
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2
INSERM/UEVE U861, I-STEM, AFM 5 rue Desbruères 91030 Evry cedex, France
CECS, I-STEM, AFM 5 rue Desbruères 91030 Evry cedex, France
£ Present address: Cellectis BioResearch Parc Biocitech 102, Av. Gaston Roussel 93235
ROMAINVILLE Cedex
* These authors contributed equally to the work
Running title: miRNA and mRNA expression patterns in ES-MSC cells
** Correspondence:
Dr Geneviève PIETU
INSERM/UEVE UMR 861/ I-STEM
5 rue Henri Desbruères
Campus 1 Genopole
91030 Evry Cedex
France
Tel: 33 (0)1 69 90 85 24
Fax: 33 (0)1 69 90 85 21
E-mail: [email protected].
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Abstract :
Mesenchymal stem cells (MSC) are present in a wide variety of tissues during development of the
human embryo starting as early as the first trimester. Gene expression profiling of those cells has
focused primarily on the molecular signs characterizing their potential heterogeneity and their
differentiation potential. In contrast, molecular mechanisms participating to the emergence of MSC
identity in embryo are still poorly understood. In this study, human embryonic stem cells (hES)
were differentiated toward MSCs (ES-MSC) to compare the genetic patterns between pluripotent
hES and multipotent MSC cells by performing a large genome-wide expression profiling of mRNAs
and microRNAs (miRNAs). After whole-genome differential transcriptomic analysis, a stringent
protocol was used to search for genes differentially expressed between hES and ES-MSC, followed
by several validation steps to identify the genes most specifically linked to the MSC phenotype. A
network was obtained that encompassed 74 genes in 13 interconnected transcriptional systems
which are likely to contribute to MSC identity. Pairs of negatively correlated miRNAs and mRNAs,
which suggest miRNA-target relationships, were then extracted and validation sought using
PremiRs. We report here that under-expression of miR-148a and miR-20b in ES-MSCs, as
compared to ES, allows an increase in expression of the EPAS1 transcription factor that results in
the expression of markers of the MSC phenotype specification.
Key words: Mesenchymal Stem Cells, Human Embryonic Stem cells, miRNA, Microarray analysis
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Introduction
Mesenchymal stem cells (MSC), identified several decades ago as bone-forming progenitor cells in
the bone marrow (21), were subsequently defined phenotypically as CD29+, CD44+, CD90+,
CD105+ cells, negative for hematopoietic lineage markers and HLA-DR (68). They have more
recently attracted enormous attention because of their presence in a large number of other tissues in
the adult, including adipose tissue, peripheral blood, dental pulp, dermis, synovial liquid and
skeletal muscle (16, 50, 68, 74, 75). Of similar interest has been the demonstration of MSCs not
only in the adult but also at almost all stages of development, as early as the first trimester in the
human embryo (14), in the amniotic liquid (30), in the placenta (43) and in the umbilical cord blood
(68). Those populations of self-renewable multipotent MSCs share a large set of phenotypic
markers, although none has been shown to be specific to date, and they exhibit differentiation
abilities along the osteogenic, chondrogenic and adipogenic pathways.
MSCs appear, therefore, as a unique multipotent stem cell population with functional specificities
that distinguish them from differentiated cells as well as from other stem cells, either the immortal
pluripotent blastocyst-derived embryonic stem cells or the well localised less multipotent tissuespecific stem cells. Analysis of their gene expression profiles, focusing especially on the molecular
correlates of the heterogeneity among MSCs of different origins (25, 66, 68) and their
differentiation potential, has provided important clues to specialization routes for these cells (60,
73). Recent studies reported that gene expression profiling of MSC derived from human embryonic
stem cells (hES) was very similar from MSC derived from bone marrow (17) or from fetal tissues
(32). In contrast, molecular mechanisms participating to the emergence of MSC identity in embryo
have attracted less attention.
In the present study, we have compared the genetic pattern of the pluripotent hES cells and their
MSCs derivatives, seeking molecular clues specific of MSC identity. We have taken advantage of
recent protocols which trigger in vitro differentiation of MSCs from hES (thereafter called ESMSCs) (5, 6, 26, 37, 40, 45). Phenotypically-characterized cell populations obtained at nearhomogeneity in any desired amount, allowed us to perform a whole-genome differential
transcriptome profiling under the best technical conditions (59) correlated with analysis of
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microRNAs signatures. Extraction of negatively correlated pairs of miRNA and mRNA then
pointed to miRNA-target relationships.
Methods
Cell culture
Isolation and amplification of hES cells
The human ES cell line VUB01 (XY, passage 80) was derived at the Vrije Universiteit Brussels
(41) and H9 (XX, passage 50-60, WA09) by the National Stem Cell Bank. The human ES cell line
SA01 (XY, passage 40) is distributed by Cellartis (Sweden). VUB01 and H9 were maintained on a
feeder layer of mitomycin C-inactivated murine embryonic fibroblast (MEF) cells, in a humidified
10% CO2 incubator at 37°C in Knock-Out (KO)-DMEM supplemented with 20% KO Serum
Replacement (KSR), 1mM L-glutamine, 1% non-essential amino acids, 0.1mM -mercaptoethanol
and 4ng/ml bFGF (all from Invitrogen). SA01 was maintained on an inactivated human foreskin
fibroblast feeder in DMEM-F12 supplemented with 20% of KSR, 1mL-glutamine, 1% non-essential
amino acids, 0.1mM -mercaptoethanol and 4ng/ml bFGF, in a humidified 5% CO2 incubator at
37°C.
For the three cell lines, culture medium was changed daily and routine passages were performed by
mechanical cutting of ES cells on a fresh feeder layer every 4-5 days.
Isolation, Purification, and Expansion of hMSCs from the bone marrow
Bone marrow cells were obtained from iliac crest aspirates from healthy donors giving cells for
allogeneic transplantation purposes, after informed consent. They were used in accordance with the
procedures approved by the human experimentation and ethics committee of the Hopital St Antoine,
Paris, France. Isolation, purification and expansion were performed as previously described (8).
Differentiation of hES cells
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Mesenchymal differentiation was obtained based on a protocol described by Barberi et al (5).
Briefly, differentiation was induced by plating 2.104 ES cells/cm2 on 0.1% gelatine-coated dishes in
the presence of KO-DMEM medium supplemented with 20% Fetal Bovine Serum (FBS,
Invitrogen), 1mM L-glutamine, 1% non-essential amino acids, 1% penicillin-streptomycin and
0.1mM β-mercaptoethanol. Medium was changed every other day. Confluent cells were passed with
trypsin/EDTA 1X (Invitrogen) in new gelatin-coated dishes.
To induce osteoblastic differentiation, cells were plated at a density of 30 000 cells /cm2 in a
specific medium from Cambrex, containing dexamethasone, ascorbate and B-glycerophosphate.
After 21 days cells were analyzed by alkaline phosphatase activity using an enzyme kit from SigmaAldrich.
Adipogenic differentiation was induced by culturing the cells in the same medium as that used for
differentiation supplemented with 100µM linoleic acid. Adipogenesis was detected by the presence
of neutral lipids in the cytoplasm stained with Oil Red O.
Cell phenotyping
Immunophenotyping was carried out using a FACScalibur and the Cell Quest software
(Becton&Dickinson Biosciences). More than 10,000 events were acquired for each sample and
analysed. Cells were collected with trypsin (trypsin/EDTA 1X; Invitrogen) and resuspended at 5.105
cells in PBS-2% fetal bovine serum. Cells were stained for 20 min at room temperature with one of
the following anti-human antibodies: CD73-PE (SH3/NT5E), CD44-PE, CD54-PE (I-CAM-1),
CD29-PE (integrin 1), CD106-PE (VCAM), CD166-PE (ALCAM), CD14-PE, CD31-PE (PECAM1), CD56-PE (NCAM), HLA-ABC-PE, HLA-DR-PE, CD34-APC, CD45-FITC (all from
Becton&Dickinson Biosciences/Pharmingen); CD105-PE (SH2/Endoglin; Caltag); and primary
monoclonal antibody FORSE1, vimentin and Stro1 were used with mouse IgG- or IgM-Alexa as
secondary antibody. Mouse isotype antibodies served as respective controls (Becton&Dickinson).
For immunohistochemistry, cells were fixed in 4% paraformaldehyde solution for 20 min at room
temperature, washed with PBS three times, and exposed to blocking buffer (1%BSA/ 5% goat
serum) and 0.1% triton X100 when permeabilisation was required. Cells were stained for 2h with
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either the primary monoclonal antibody Stro1 or αSMA (alpha smooth muscle actin) and next with
the appropriate secondary antibody and Dapi for 1h.
The proliferation potential of MSCs was measured using a commercial kit (Cambrex), according to
the manufacturer’s protocol.
DNA microarrays
Total RNA was extracted from the cells using the RNeasy mini kit (Qiagen) according to the
manufacturer’s protocols. The quality of RNA was controlled using a BioAnalyser 2100 (Agilent). For
DNA micoarrays, each biological sample was processed in triplicate for both cell lines (VUB01 and
SA01), i.e. altogether six RNA preparations were analyzed for undifferentiated ES cells and six for ESMSCs. Analysis was performed using an Affymetrix platform (Institut Curie Paris, Réseau National
des Genopoles, France). RNA samples were processed for labelling and then hybridized on Affymetrix
HG_U133_Plus_2 human oligonucleotide arrays; the DNA chips were scanned according to the
Affymetrix protocols.
Real time RT-PCR
For quantitative RT-PCR, total RNA (500 ng) was reverse transcribed with Superscript III
(Invitrogen) as described in the manufacturer’s protocol.
Real-time PCR was performed using SYBR Green Core Reagents (Applied Biosystem) according
to the manufacturer’s protocol. The incorporation of the SYBR Green dye into the PCR products
was monitored in real time with the Chromo4 system (Biorad). The efficiency of the amplification
was determined for each pair of primers by comparison with a standard curve generated with
serially diluted cDNA. Target genes were quantified relative to a reference gene (β-TUBULIN),
using the mathematical model described by Pfaffl (49). All PCR reactions were performed in
triplicate. The complete list of the primers used is presented in supplementary Table S7.
Statistical analyses
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Array Assist 4.1 software (Stratagen) was used to achieve the statistical treatment of the expression
data. The GC-RMA algorithm was used for normalization. Next, a one way-ANOVA was
performed to eliminate genes which presented a significant variance between biological samples (pvalue < 0.05 corrected with Benjamini and Hoehberg False Discovery Rate)(7).
Paired Student t-tests were performed to compare the expression changes between samples. The
significantly modulated genes were defined as genes that showed a Fold Change (FC) ≥ 2 and a p
value ≤ 0.01 (p value corrected with Benjamini and Hoehberg False Discovery Rate). The ingenuity
software (www.ingenuity.com) was used to build gene networks.
Establishment of a list of MSC markers from the literature
Analysis was restricted to genes related to those previously described in the literature as differentially
attached to the MSC phenotype (12, 19, 27, 28, 45, 58, 65, 68). This generated a list of 262 genes
(Supplementary Table S4), out of which 2 were found in four of those studies, 14 in three, 31 in two
and 215 in one.
All listed genes that were up-regulated in ES-MSC samples were used as “leads” to identify in
silico all transcription regulators that positively regulated them. Then, all relevant transcription
regulators up-regulated in ES-MSC samples were sorted out. Another search in databases identified
all genes that were positively regulated by the selected set of transcription regulators and this list
was then cross-matched with up-regulated genes in ES-MSC samples. Altogether, this procedure
produced networks that contained all genes that were both up-regulated in ES-MSC samples (as
compared to undifferentiated ES cells) and linked, directly or indirectly, to MSC markers previously
identified in the literature.
miRNA analysis
MiRNA profil analysis was performed using TaqMan® Array encoding for the human miRNA panel
V1.0 (Applied Biosystems) on 3 independent RNA preparations for the undifferentiated hES and the
ES-MSC for each cell line VUB01, H9 and SA001. After induction of hES cells toward the neural
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lineage, neural precursors (ES-NP) were purified from neural rosettes (48) by cell sorting using the
pan-neuronal surface marker NCAM (Neural Cell Adhesion Molecule or CD56).
Eighty ng of total RNA was extracted using mirVanaTM Isolation kit (Ambion) and reverse
transcribed using the TaqMan MicroRNA reverse Transcription kit (Applied Biosystems) in a
multiplex RT system consisting of eight pre-defined RT primer pools containing up to 48 RT
primers each. All the 365 miRNAs targets were reverse-transcribed in eight separate RT reactions
and each RT reaction was pipetted into one of the eight filling ports on the TaqMan® Array.
Real time PCR was performed using no UNG no Ampersase TaqMan master mix (Applied
Biosystems) on an ABI 7900 and results were normalized against RNU 48, a small nucleolar RNAs
(snoRNAs).
Data are expressed using the mean and the standard deviation in the three independent RNA
preparations. Student’s t test was used to identify miRNAs differentially expressed between hES
and ES-MSC (or ES-NP) with a fold change ≥ 2 and a p-value ≤ 0.01.
Transfection of microRNA precursors
MSC cells were seeded at 30 to 40 000 cells per P24-well plates and transfected with
PremiRTmiRNA Precursor (Ambion) at a final concentration of 100nM using the Lipofectamine
RNAiMAX transfection reagent (Invitrogen). Total RNA and protein were collected 72 and 96h
post-transfection. A CyTM3-labeled AntimiR Negative Control (Ambion) was used as a control.
Extraction of total RNA, reverse transcription and analysis of Mir expression level by Real-time
PCR were performed as previously described.
Luciferase reporter assays
The GeneCopoeiaTM pEZX-MT01 target sequence expression clone containing the entire
human EPAS1 3’UTR sequence (Accession number NM_001430.3) which had Firefly
luciferase as the reporter gene was provided by LabOmics (Belgium). A tracking reporter
gene, Renilla luciferase, was also provided in the vector system, which allow indicators for
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successful transfection and expression of these miRNA target sequence constructs in target
cells.
For Luciferase reporter assays, HEK 293 cells were plated at the density of 15 000
cells/well in 96-well plates (Corning). Transfection of the miRNAs by Lipofectamine
RNAiMAX was performed 48h after plating. Cells were then transfected 24h later with the
pEZX-MT01 containing the EPAS1 3’UTR sequence plasmid or by the empty vector used
as a control by Lipofectamine LTX. Cells were lysed 72h after the first transfection and
assay for Firefly and Renilla luciferase activity using the Dual Glo Luciferase Assay
System (Promega) was performed according to the manufacture’s instructions and
measured on the Analyst GT (Molecular Device).
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Results
Differentiation of ES-MSCs displaying a phenotype similar to that described by previous authors (5,
6, 45) was readily obtained after about 20 days of culture (two passages). CD73+ cells amounted to
about 65% of the population at day 13 and reached over 98% at passage P2. ES-MSCs expressed
endoglin (CD105), integrin 1 (CD29), CD44, ALCAM (CD166), Vimentin, Stro1 and HLA-ABC
(Figure 1A). They were negative for hematopoietic markers (CD34, CD45 and CD14), neuronal
markers (NCAM/CD56 and FORSE1), and the endothelial marker CD31. Cells were
immunoreactive for Stro1 and -SMA (alpha smooth muscle actin) (Figure 1B). A profound
decrease in expression of OCT4 and NANOG was observed by quantitative RT-PCR as compared
to undifferentiated hES, demonstrating the absence of undifferentiated cells in the ES-MSC
population (Figure 1C). The ability of the cells to differentiate into osteoblasts and adipocytes was
assessed by the expression of both alkaline phosphatase and Oil red staining after treatment with the
inductive medium (Figure 1D). ES-MSCs retained the same phenotype for up to twenty passages or
two cycles of freezing (Supplementary Table S1) and their doubling time, evaluated using BrdU,
remained constant (Supplementary Figure S1).
A set of 5,543 genes was identified in ES-MSCs with a fold change superior to 2.0 as compared to
hES and a “p” value less than 0.01, including 2,018 up-regulated and 3,525 down-regulated genes
(Supplementary Table S2). 936 (17%) of those have no known functions, among which 25 downregulated genes had a fold change ≥ 20, suggesting that they may be associated to pluripotency. The
most marked decrease in expression was observed for known pluripotency transcription factors such
as NANOG (FC=260.8), SOX2 (FC=232.2) and OCT4/POU5F1 (FC=127.4) (Supplementary Table
S3) (11). Expression of TDGF1/CRIPTO, another transcription factor associated with ES cells (62),
even showed a negative fold change of 761.
Expression of MSC-associated genes in ES-MSCs
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A multi-step in silico strategy was applied to those data in order to sort out gene expression patterns
that would be specifically linked to the phenotypic MSC features. Up-regulated genes already
identified as MSC markers in the literature allowed us to retrieve all transcription regulators
positively associated with them from databases. In this general list, transcription regulators that were
up-regulated in ES-MSCs were then sorted out. Transcriptional networks were constructed by
identifying up-regulated genes in ES-MSCs that are known target genes of those transcription
regulators.
By comparison with a list of 262 genes derived from a literature search (see Methods), 95 upregulated genes were identified in ES-MSCs (Supplementary table S4). These comprised typical
MSC markers, such as CD44 (FC=110), CD73/NT5E (FC=83.7), ALCAM/CD166 (FC=14.5),
INTEGRIN αV/ITGAV (FC=10.5), INTEGRIN β1/ITGB1 (FC=8.8), VIMENTIN/VIM (FC=4.8),
and CD105/ENDOGLIN (FC=4.3), as well as FN1 (FC=152.02), COL1A1 (FC=90.28), COL6A3
(FC=86.01), COL1A2 (FC=55.22), COL4A2 (FC=21.94), CTGF (FC=20.72), RUNX2 (FC=10.84),
PLOD2 (FC=10.73), FTH1 (FC=2.44) and TMSB4X (FC=2.03). PPARG and SOX9 just missed
statistical significance (FC=1.6 and 2.2 fold, p value 0.05 and 0.02, respectively).
Thirty-six up-regulated transcription regulators were positively linked to 61 of those 95 “MSC
marker genes” in ES-MSCs (Supplementary Table S5). Gene networks were completed by adding 68
genes that were both listed in databases as positively controlled by one or more of those 36
transcription regulators and up-regulated in ES-MSCs (Table 1), among which 9 more transcription
regulators (DSCR1, MBD2, FOSL2, NFKB1, BCL3, PCAF, SQSTM1, CBFB, ETV6). This led to a
total of 165 genes with which networks were built using the Ingenuity software. This analysis
identified three networks. Two were not further studied because they seemed to associate in a nonspecific manner to differentiation. The first one comprised mostly genes associated to the cell cycle,
which is known to be different in the undifferentiated stage (20). The second one was centred on the
ubiquitous transcription factor JUN (Supplementary Figure S2).
In contrast, the third network –which consisted of 74 of the 165 selected genes- comprised the
largest panel of genes linked to the extracellular matrix and differentiation pathways toward main
MSC progeny (Figure 2 and Table 2). This network included altogether 13 transcription factors, 32
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known MSC markers, and 29 other genes. Interestingly, the expression level of transcription factors
up-regulated in ES-MSCs was quite similar compared to bone marrow-derived (BM-) MSCs
(Supplementary Figure S3).
miRNA profile and function in ES-MSCs
In order to elucidate the molecular mechanism that contributes to MSC identity, miRNAs that
targeted the transcription regulators implicated in the up-regulation of MSC marker genes, were
searched.
Out of 367 human miRNAs from which expression was compared in hES and ES-MSC cells, 40
were up-regulated and 127 down-regulated in ES-MSCs (Table S6). Among them, the most downregulated were the miRNAs known to be implicated in the maintenance of hES pluripotency such as
miR-372, 302a,b,c,d,, 367, 371, 373 and 520g. As a demonstration of the specificity of the analysis,
miR-9, miR-33 and miR-124a which are known to be implicated in neural differentiation as well as
miR-133a and miR133b expressed in cardiac and skeletal muscles were also down-regulated in ESMSCs. Conversely, up-regulated miRNAs comprised miR-27a, 27b, 148b, 210, and miR-143,145
that are known to be implicated in the MSC differentiation toward osteoblasts and adipocytes,
respectively (Table S6). To be further able to discriminate among the modulated miRNAs those that
could be more specifically associated to the establishment of the MSC phenotype, a parallel
“counter-test” was performed during the differentiation of hES toward hES-derived neural precursor
cells (ES-NP).
The miRNAs that target the 13 up-regulated transcription regulators in ES-MSCs were searched by
TargetScan (Table 3), and identified miRNAs that were preferentially down-regulated with a strong
fold change ratio (>5) in ES-MSCs, while up-regulated or unaffected in ES-NPs (Table 3). Twelve
miRNA matched those stringent criteria and were, therefore, good candidates for a role in MSC
specification: miR-9 which targets both FLT1 and EPAS1, the cluster that comprises miR-17p5,
miR-20a, miR-20b, miR-93, miR-106b and miR-148a, which targets EPAS1, miR-18a and b, which
targets ETV6, and miR-15a and miR-195, which targets TFAP2A.
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EPAS1 thus appeared as the most frequently targeted gene. We, therefore, specifically looked for
the functional effects of its control by miRNAs, using PremiR for miR-148a and miR-20b. miR429, which binds the unrelated transcription factor BHLHB3, was used as a control (Supplementary
figure S3). To test directly whether miR-148a and miR-20b can repress translation through the
binding to EPAS1, we used the luciferase reporter construct pEZX-MT01 with the entire
human EPAS1 3’UTR immediately following the Renilla coding sequence. HEK293 cells
were cotransfected sequentially with miRNAs (miR-148a, miR-20b, miR-429 or scramble miR)
followed by the luciferase/EPAS1 3’UTR reporter construct or the empty vector. In cells
transfected by miR-148a and miR-20b, a decrease of about 40% of the luciferase expression
was observed as compared to scramble miRNA, whereas miR-429 had a weaker effect
(Figure 3B). These data indicated that miR-148a and miR-20b can down regulated expression
from the EPAS1 mRNA carrying the 3’UTR.
The expression level of MSC markers linked to EPAS1 was then analyzed by Q-PCR. Control
levels of these marker genes were similar in ES-MSCs and BM-MSCs, whereas they were strongly
up-regulated as compared to hES (Figure 3C). Pre-miR treatment that induced overexpression of
either miR-148a or miR-20b led 72 hours after transfection (maintained or increased at 96 hours) to
a significant decrease in expression levels of the EPAS1-related genes GBE1, HIF1A PLOD2
(Figure 3C). PLAU and PLAUR, which are present but more remote in the composite network
drawn from transcriptome profiling results, were also significantly affected. Conversely DUSP1 and
LOX, though closely associated to EPAS1 in the network, were not. Pre-miR treatment for miR-429
did not affect any of these genes as compared to the antimiR negative control (Figure 3D). On the
contrary, hypoxia conditions did not affect the expression of these MSC markers (not shown).
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Discussion
The main result of this study has been the identification, in Human cells, of a network of thirteen
interconnected transcription factors, corresponding of a specific gene expression pattern of
mesenchymal stem cells compared to embryonic stem cells. Concurrent analysis of miRNA
expression profiles revealed that miR-148a and miR-20b might be implicated in the MSC identity
by controlling the expression of EPAS1.
Specific patterns of gene expression associated with the MSC phenotype
In our study, we have identified in our ES-MSC population expressed genes already known to be
associated with the MSC phenotype in various types of MSC (Table S4).
Only few studies reported gene expression profiling of MSC by comparison of hES-derived MSC to
hES (17, 37, 45). Lian et al. have identified highly expressed genes that encode for membrane
proteins that could be used for the isolation of MSC from differentiating hES. Here, we focused on
transcription regulators up-regulated in ES- MSC compared to hES.
The most differentially expressed transcription factor, out of the thirteen that together formed a
network associated to the embryonic to mesenchymal stem cells transition, was ARID5B. Although
the association of this gene with the mesodermal lineage has been shown in the mouse, its role was
suggested up to now in later stages of differentiation. The knock-out of Arid5b, has thus been
associated with a profound defect in adipogenesis in mice, suggesting an essential role for
accumulation of lipid stores in postnatal life (71). A role in smooth muscle differentiation has
additionally been suggested (70). In the mouse, in contrast, Arid3b is essential for mesodermal and
mesenchymal differentiation (64) whereas it was strongly down-regulated in ES-MSCsamples (FC:
-30). These results may reflect species differences. It cannot be excluded, however, that an earlier
step in the embryonic to mesenchymal transition was missed during which ARID3B was transiently
overexpressed. In any case, our results suggest that ARID5B is a key player in the specification of a
mesenchymal stem cell identity, before acting in differentiation pathways toward MSC derivatives.
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It is interesting to mention that this conclusion of a dual role in MSC identity and in later stages of
differentiation may apply to most transcription factors in the network associated to the MSC
phenotype in the present study. Indeed, while ARID5B was the only transcription factor in this
network with a major role in adipogenesis, others participate in essentially all potential
differentiation pathways of MSCs. This includes osteogenesis, in particular with TFAP2A, TWIST1
and FOSL1. TFAP2A contributes to patterning mesenchymal cells of neural crest origin that form
the craniofacial skeleton (54). Conversely, Twist proteins are “antiosteogenic” as they transiently
inhibit Runx2 function during skeletal development in mice (9). Accordingly, TWIST1 mutations
provoke Saethre-Chotzen syndrome, which is characterized by craniostenosis and various skeleton
abnormalities. FOSL1 is necessary for bone formation (18), by acting on expression of the bone
matrix genes osteocalcin, collagen 1A2 and matrix G1a protein. Also of interest was the upregulation of MYOCD, which is the only transcription factor known to be both necessary and
sufficient for vascular smooth muscle cell differentiation (36), as it underlined the potential role of
the ES-derived MSCs in the patterning of blood vessels early on in development. EPAS1 –which is
detailed below- and CITED2 appear to participate, in part associated to TFAP2A, to various aspects
of morphogenesis, in particular for the heart (2, 3, 55). In addition, FLI1 (and EPAS1) is associated
to the support function of MSCs for the hematopoietic system as its knock-out in mice also
provokes provokes aberrant haematopoiesis and haemorrhaging (61) associated to disruption of the
basement membrane and mesenchymal tissues, in which Fli1 is normally expressed.
Altogether, gene expression profiling in ES-MSCs revealed the expression of a number of
transcription factors that had previously been associated with later differentiation stages leading to a
diversity of MSC cell progenies. In the absence of analyses at the single cell level, a bias in the
present results cannot be excluded, originating from the combination of expression patterns from
already differentiating MSCs. This, however, appears unlikely, given the overall similarity of the
cells phenotype, both morphologically and in FACS analyses, and the possibility to maintain it
unaltered for a large number of passages. The present results rather suggested, that each of these
transcription factors may contribute to a dual role by taking part in MSC identity and then by
supporting differentiation into one specific derivative.
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Implication of miR-148a and miR-20b in MSC identity
In the search for additional molecular mechanisms that would control the transcription systems
associated to the MSC identity, miRNAs were additionally analyzed as their roles are more and
more demonstrated in cell specification (22, 39, 44, 51) and, in particular, stem cell differentiation
(4, 13, 34, 35, 53, 63). In hES cells, lineage–specific transcription factors can indirectly determine
the fate of differentiated cells by modulating the levels of lineage-specific miRNAs (10, 23, 24, 29,
38, 67). Although miRNA patterns of expression have been described in MSC (23, 33, 53), they
have, to our knowledge, been associated to further types and stages of differentiation of those cells
rather than the comparison to a less differentiated stage to MSC as in the present study. By taking
the embryonic stage as a reference, specifically down-regulated miRNAs were sought, the
association of which with specifically up-regulated transcription factors may indicate a role in the
MSC identity itself.
The present analysis revealed a particular number of miRNAs associated with EPAS1 that were
down-regulated specifically in MSCs as compared to ES, and two of them, miR-148a and miR-20b,
controlled negatively EPAS1 effects on MSC marker genes.
miR-148a had previously been associated with processes involved in the specification of
hematopoietic stem cells phenotype (42) and shown to be up-regulated during bone formation in
association with miR-15b (46) , as well as miR-20b (47).
Functional effect of miR-148a and miR-20b on the MSC specification by targeting EPAS1 has not
been yet described.
EPAS1, also called HIF-2
expressed transcription factor which is strongly induced by hypoxia. It was demonstrated to play a
critical role in embryonic development (1, 55). In stem cells, where oxygen level in the immediate
environment can influence stem cell function and differentiation, EPAS1 may participate to regulate
stem function through activation of Oct-4 (15).
EPAS1 appears instrumental in the differentiation of many MSC progenies, possibly due to a
particular functional importance in the specification of the MSC identity itself. Indeed, EPAS1 has
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been shown to promote adipogenesis and chondrogenesis under specific conditions (31, 57). Recent
studies demonstrated that EPAS1 also stimulates transcription of genes involved in the pathologic
transformation of osteoarthritic chondrocytes (52, 72). It may also contribute with FLI1 to support
haematopoiesis in the bone marrow as loss of Epas1 in mice provokes hypocellularity in the bone
marrow (55) and is an essential regulator of murine erythropoietin production (56). At a molecular
level, EPAS1 exerts a direct positive regulation on a number of genes expressed in MSC, such as
LOX, GBE1, NDRG1, PLOD2, CITED and PKIB (69). It also interacts with genes involved in the
remodelling of the extracellular matrix, PLAU and PLAUR. In our study, all these genes were found
to be up-regulated in MSC compared to hES whereas their expression levels were similar in bone
marrow MSC. We have demonstrated that this regulation might be controlled by a direct interaction
of miR-148a and miR-20b, alone or together, with EPAS1 by targeting its 3’UTR and was
independent of an hypoxic induction. Consequently, the forced expression of these miRNAs lead to
a significant decrease of the expression of some of them such as GBE1, NDRG1, PLOD2, PLAU
and PLAUR.
In summary, our data delineate two miRNAs participating to the MSC identity. The decrease of the
expression level of miR-148a and miR-20b observed in MSC compared to hES would result in the
overexpression of one of their targets, the transcription regulator EPAS1, which allows expression
of MSC genes contributing to the determination of the MSC phenotype.
18
Acknowledgments
The authors wish to thank Dr Marc Peschanski for continuous support and input during this study.
We thank Drs Karen Sermon for providing the VUB01 hES cell line, Morad Bensidhoum for the
hMSCs from the bone marrow, Ileana Mateizel and Christian Jorgensen for helpful contributions and
comments on the manuscript. This work was supported by the Association Française contre les
Myopathies (AFM), by the Agence Nationale de la Recherche and by the IngeCELL program of the
cluster Medicen Paris Region. C.R. was the recipient of a fellowship from MRT.
Author Information
The gene expression data have been deposited in GEO Data Bank with the accession number
GSE7879.
19
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Figure Legends
Figure 1: Characterization of the ES-MSC cell population. (A) Phenotyping using flow
cytometry (SA01). (B) Immunocytochemistry (SA01) for Stro-1 (left, red) and SMA (right,
green), counterstained with DAPI (nuclei in blue). (C) Expression analysis of the pluripotence genes
NANOG and OCT4 by quantitative RT-PCR in ES-MSC from VUB01 (blue) and SA01 (yellow).
(D) Osteogenic and adipogenic differentiation of ES-MSCS characterized by Alkaline phosphatase
and Oil Red coloration after treatment with inductive medium respectively.
Figure 2 : Network between modulated genes known to be expressed in MSCs, transcription
regulators and new markers of MSC. Networks were constructed using the Ingenuity software on
expression relationships described in the literature. For genes up-regulated in ES-MSCS compared
to hES in the transcriptome profiling analysis, the color intensities of gene expression (from pink to
red) were correlated to fold change intensities. Genes surrounded with an orange circle are known
to be expressed in MSC, blue circle are transcription regulators and black circle are new markers of
MSC. miRNA targeting transcription regulators are indicated in the blue box in which miRNA
over-expressed in functional analysis are indicated in red.
Figure 3 : Expression level of the MSC markers. (A) Matching sequences in 3’UTR EPAS1 with
miR-148a and miR-20b. (B) Analysis of the inhibitory effect of miRNAs on EPAS1 3’UTR, cloned
in pEZX-MT01 plasmid, measured by Luciferase expression in HEK cells. Results are presented
as the ratio of the reporter (Firefly luciferase) to control (Renilla luciferase) in relative luminescence
activity and plotted as a percentage of the value obtained for the scramble miRNA. NT : non
transfected cells; scrble :scramble miRNA. Error bars represent the standard deviation for n=4. (C)
Expression level estimated by quantitative RT-PCR in ES-MSCs compared to hES (Black box) or
ES-MSCs compared to adult bone-marrow derived MSCs (Grey box). (D) Expression level of the
genes of interest estimated by quantitative RT-PCR (compared to hES VUB01) in ES-MSCs
transfected by an Anti-miRTM Negative Control (CTRL) or by the pre-miR miRNA precursor for
26
148a, the pre-miR miRNA precursor for 20b or the pre-miR miRNA precursor for 429, 96h posttranfection. Histograms show the mean (± SEM) value of three different experiments.