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Cell Biology International (2011) 35, 29–37 (Printed in Great Britain)
Identification of microRNAs expressed highly in pancreatic islet-like cell clusters differentiated from human embryonic stem cells
Bo‑Zhi Chen*1, Sung‑Liang Yu†1, Sher Singh‡, Li‑Pin Kao*, Zong‑Yun Tsai§║, Pan‑Chyr Yang¶, Bai‑Hsiun Chen* and Steven Shoei‑Lung Li*║2
*Graduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 807, Taiwan, †Department of Clinical Laboratory Sciences and Medical Biotechnology, National Taiwan University College of Medicine, Taipei 100, Taiwan, ‡Department of Life Sciences, College of Science, National Taiwan Normal University, Taipei 116, Taiwan, §Department of Medicinal and Applied Chemistry, College of Life Sciences, Kaohsiung Medical University, Kaohsiung 807, Taiwan, ║Stem Cell Laboratory, Center of Excellence for Environmental Medicine, Kaohsiung Medical University, Kaohsiung 807, Taiwan, and ¶Department of Internal Medicine, National Taiwan University College of Medicine, Taipei 100, Taiwan


Type 1 diabetes is an autoimmune destruction of pancreatic islet beta cell disease, making it important to find a new alternative source of the islet beta cells to replace the damaged cells. hES (human embryonic stem) cells possess unlimited self-renewal and pluripotency and thus have the potential to provide an unlimited supply of different cell types for tissue replacement. The hES-T3 cells with normal female karyotype were first differentiated into EBs (embryoid bodies) and then induced to generate the T3pi (pancreatic islet-like cell clusters derived from T3 cells), which expressed pancreatic islet cell-specific markers of insulin, glucagon and somatostatin. The expression profiles of microRNAs and mRNAs from the T3pi were analysed and compared with those of undifferentiated hES-T3 cells and differentiated EBs. MicroRNAs negatively regulate the expression of protein-coding mRNAs. The T3pi showed very high expression of microRNAs, miR-186, miR-199a and miR-339, which down-regulated the expression of LIN28, PRDM1, CALB1, GCNT2, RBM47, PLEKHH1, RBPMS2 and PAK6. Therefore, these microRNAs and their target genes are very likely to play important regulatory roles in the development of pancreas and/or differentiation of islet cells, and they may be manipulated to increase the proportion of beta cells and insulin synthesis in the differentiated T3pi for cell therapy of type I diabetics.


Key words: expression profile, human embryonic stem cell, microRNA, mRNA, pancreatic islet-like cell, target identification

Abbreviations: bFGF, basic fibroblast growth factor; DMEM, Dulbecco's modified Eagle's medium, EBs, embryoid bodies, GSEA, MetaCore Gene Set Enrichment Analysis, hES, human embryonic stem, ITSF, insulin, transferrin, selenium, fibronectin, MEF, mouse embryonic fibroblast, miRNAs, microRNAs, NGN3, neurogenin 3, PDX1, pancreatic duodenal homeobox 1; RT, reverse transcription, T3EB, embryoid bodies differentiated from T3 cells, T3ES, hES-T3 cells grown on MEF feeder, T3pi, pancreatic islet-like cell clusters derived from T3 cells

1Bo-Zhi Chen and Sung-Liang Yu contributed equally to this work.

2To whom correspondence should be addressed (email lissl@kmu.edu.tw).

The original data of T3pi cells obtained from Affymetrix human genome U133 plus 2.0 GeneChip have been deposited to NCBI database, and the GEO series number is GSE14503.


1. Introduction

Diabetes mellitus is a major health problem and type I diabetes, insulin-dependent diabetes mellitus, is an autoimmune disease caused by the progressive destruction of the insulin-producing beta cells in the islets of Langerhans in the pancreas (Zimmet et al., 2001). Successful transplantation of pancreas or islets can free the patients from their dependency on insulin injections and prevent complications. However, the major obstacle in using transplantation for curing the disease is the limited source of donor tissue (Santana et al., 2006). hES (human embryonic stem) cells derived from the inner cell mass of blastocysts are capable of unlimited self-renewal and maintain pluripotency in vitro to differentiate into all three germ layers: endoderm, mesoderm and ectoderm (Thomson et al., 1998; Wobus and Boheler, 2005; Guhr et al., 2006). The hES cells have previously been shown to differentiate in vitro into insulin-producing cell clusters, which can secrete insulin and express other pancreatic markers (Segev et al., 2004; D'Amour et al., 2006; Xu et al., 2006; Jiang et al., 2007).

miRNAs (microRNAs) play important roles in mammalian embryo development and cell differentiation. Mammalian genomes encode many hundreds of miRNAs, which are predicted to regulate negatively expression of as many as 30% of protein-coding genes (Bartel, 2004; Griffiths-Jones et al., 2006). The impact of miRNAs on protein output was recently shown that, although some targets were repressed without detectable changes in mRNA levels, those translationally repressed by more than a third also displayed detectable mRNA destabilization, and for the more highly repressed targets, mRNA destabilization usually comprised the major component of repression (Baek et al., 2008; Selbach et al., 2008). Although the biological functions of most miRNAs remain to be elucidated, some miRNAs appear to participate in determination of cell fate and in control of cell proliferation, cell differentiation and cell apoptosis in animals (John et al., 2004; Alvarez-Garcia and Miska, 2005; Kloosterman and Plasterk, 2006). The miRNAs, such as miR-375, have previously been shown to regulate negatively insulin secretion as well as pancreatic islet development (Poy et al., 2004; Hennessy and O'Driscoll, 2008; Tang et al., 2008). Further analyses of miRNA expression during in vitro differentiation of human T3pi (pancreatic islet-like cell clusters derived from T3 cells) will provide an understanding of their functional roles and help in developing these islet cells for therapeutic uses as well as therapeutic targets in diabetes.

In this investigation, both miRNA and mRNA expression profiles from the T3pi were quantitatively determined and compared with those of undifferentiated T3ES [hES-T3 cells grown on MEF (mouse embryonic fibroblast) feeder] and T3EB [EBs (embryoid bodies) differentiated from hES-T3 cells]. Several target genes of pancreatic islet cell-specific miRNAs were identified by inverse expression levels between miRNAs and their target mRNAs.

2. Materials and methods

2.1. Human embryonic stem cell culture

Human embryonic stem cell line hES-T3, which is one of the five hES cell lines derived with institutional review board approval from preimplantation embryos donated at IVF (in vitro fertilization) clinics in Taiwan (Li et al., 2006), exhibits normal female karyotype (46, XX), and it has been continuously cultured on mitomycin C (10 μg/ml) mitotically inactivated MEF feeder in hES medium under 5% CO2 in air at 37°C and underwent freezing/thawing processes. The hES culture medium consisted of DMEM (Dulbecco's modified Eagle's medium)/F12 (1:1, GIBCO) supplemented with 20% KSR (knockout serum replacement; Invitrogen), 1% non-essential amino acids, 1 mM l-glutamine, 0.1 mM β-mercaptoethanol and 4 ng/ml human bFGF (basic fibroblast growth factor; Life Technologies). Routine passages of hES-T3 line every 5–7 days were done with collagenase (type IV, 1 mg/ml, Invitrogen) treatment and mechanical scrape.

2.2. In vitro differentiation of T3pi

The five-stage procedure (Figure 1) for in vitro differentiation of hES-T3 cells into T3pi was modified from previously published protocols (Lumelsky et al., 2001; Segev et al., 2004) as follows:

Stage I: Expansion of undifferentiated hES cells. The hES-T3 cells (passage 36) were maintained on MEF feeder in hES medium containing 4 ng/ml bFGF as described above. The hES-T3 cells grown on MEF feeder were designated as T3ES.

Stage II: Formation of EBs. The EBs were formed as described previously (Li et al., 2009). The undifferentiated hES-T3 colonies were mechanically dissected into pieces that were transferred and grown with very slow shaking (20 rev./min) in the EB medium containing 80% knockout DMEM, 20% ES-qualified FBS (fetal bovine serum; Gibco), 1% non-essential amino acids and 1 mM l-glutamine without MEF feeder layer in bacterial Petri dish plate (α-plus, 10 cm) under 5% CO2 in air at 37°C for 7 days with change of medium every 2 days. These EBs are designated as T3EB.

Stage III: Plating EBs in ITSF (insulin, transferrin, selenium, fibronectin) medium. The EBs were transferred to 0.1% gelatine-coated plates in DMEM/F12 medium supplemented with 1% ITS (1 mg/ml insulin, 0.55 mg/ml transferrin, 0.67 μg/ml selenium), 5 μg/ml fibronectin and 1 mM l-glutamine under 5% CO2 in air at 37°C for 7 days with change of medium every 2 days.

Stage IV: Expansion of pancreatic progenitor cells. The cells were dissociated with 0.05% trypsin at 37°C for 5 min and plated on 0.1% gelatin-coated dishes in DMEM/F12 medium supplemented with 1% N2 supplement (500 µg/ml insulin, 10 mg/ml transferrin, 0.63 µg/ml progesterone, 1.61 mg/ml putrascin and 0.52 μg/ml selenium, Gibco), 2% B27 supplement (Gibco), 1 mM l-glutamine and 10 ng/ml bFGF under 5% CO2 in air at 37°C for 7 days with change of medium daily.

Stage V: Formation of T3pi. The DMEM (containing no glucose)/F12 medium was supplemented with 1% N2 supplement, 2% B27 supplement, 1 mM l-glutamine and 10 mM nicotinamide (instead of bFGF) under 5% CO2 in air at 37°C for 7 days with change of medium every 2 days. These hES-T3-derived pancreatic islet-like cell clusters were designated as T3pi.

2.3. RT (reverse transcription)-PCR

The total RNAs were isolated using Qiagen RNA extraction mini kit from approximately 1×105 cells dissociated with 0.05% trypsin from T3pi. The cDNA was synthesized using MMLV (Moloney-murine-leukaemia virus) reverse transcriptase (Invitrogen) from 1 μg total RNAs. PCR primers, reaction conditions and product sizes are summarized in Supplementary Table S1 (at http://www.cellbiolint.org/cbi/035/cbi0350029add.htm). The PCR products were size fractionated on 2% agarose gel electrophoresis.

2.4. Real-time qPCR

The cDNA synthesized above was also used to determine levels of gene expression using iQ5 real-time PCR detection system (Bio-Rad Laboratories). PCR amplifications were carried out in a total volume of 25 μl, containing 12.5 μl of 2× SYBR Green supermix (Bio-Rad), 0.5 μl of 10 μM of each primer and 0.5 μl of cDNA samples and mixed with sterile water. The reaction was initiated at 95°C, 3 min, followed by 40 three-step amplification cycles consisting of 30 s denaturation at 95°C, 30 s annealing at 60°C, 15 s extension at 72°C. A final dissociation stage was run to generate a melting curve for verification of amplification product specificity. Real-time qPCR was monitored and analysed by the Bio-Rad IQ5 optical system software version 2.0 (Bio-Rad). Relative mRNA levels were calculated using the comparative Ct method (Bio-Rad instruction manual) and presented with ratio to biological controls. ACTB transcript levels were confirmed to correlate well with total RNA amounts and therefore used for normalization throughout. All primer pairs used were confirmed to approximately double the amount of product within one cycle and to yield a single product of the predicted size. Primer sequences and product sizes are summarized in Supplementary Table S2 (at http://www.cellbiolint.org/cbi/035/cbi0350029add.htm).

2.5. Immunocytochemical analysis

T3pi were washed and fixed at room temperature by 3.7% paraformaldehyde for 5 min and 0.1% Triton X-100/PBS for 15 min in the culture dishes. The cell clusters were then incubated with primary antibodies at room temperature for 1 h. The sources of antibodies and dilutions used were rabbit anti-C-peptide antibodies (Abcam, 1:100), rabbit anti-glucagon antibodies (Santa Cruz. 1:20), rabbit anti-somatostatin antibodies (Santa Cruz. 1:20). The immunostaining with rabbit polyclonal antibodies was detected with FITC-conjugated goat anti-rabbit IgG (Chemico) as described previously (Li et al., 2009).

2.6. mRNA microarray analysis

Total RNAs from approximately 1×106 cells on 10 cm plates were extracted using TRIZOL reagent, and the same total RNAs from each sample were used for mRNA microarray analysis, as well as miRNA quantification. The mRNA profilings of T3ES, T3EB and T3pi cells were analysed using Affymetrix Human Genome U133 plus 2.0 GeneChip according to the manufacturer's protocols (http://www.affymetrix.com) by the Microarray Core Facility of National Research Program for Genomic Medicine of National Science Council in Taiwan. This Affymetrix GeneChip contains 54675 probe sets to analyse the expression levels of 47400 transcripts and variants, including 38500 well-characterized human genes. GeneChips from the hybridization experiments were read by the Affymetrix GeneChip scanner 3000, and raw data were processed using GC-RMA algorithm. The raw data were also analysed by GeneSpring GX software version 7.3.1 (Silicon Genetics, http://www.chem.agilent.com). Affymetrix GeneChip expression analysis can be used as a stand-alone quantitative comparison, since the correlation between Affymetrix GeneChip results and TagMan RT-qPCR results was shown in a good linearity of R2 = 0.95 by the MicroArray Quality Control Study, a collaborative effort of 137 scientists led by the US-FDA (US Food and Drug Administration) (Canales et al., 2006; Shi et al., 2006). The GO (Gene Ontology) processes of highly (>3-fold) up-regulated genes in T3pi cells compared with T3Es cells were analysed using GSEA (MetaCore Gene Set Enrichment Analysis) software version 6.0 (GeneGo Inc.).

2.7. Quantification of miRNAs

The expression levels of 250 human miRNAs from T3ES, T3EB and T3pi cells were determined using the quantitative TagMan MicroRNA Assays (Applied Biosystems, http://www.appliedbiosystems.com) (Chen et al., 2005; Liang et al., 2007). The detailed procedure for miRNA quantification was described previously (Li et al., 2009).

2.8. Target identification of miRNAs

Target genes of miRNAs were predicted using the TargetCombo open source software (http://www.diana.pcbi.upenn.edu/cgi-bin/miRGen/v3/Targets.cgi), which predicts targets by the union of miRanda (http://microrna.org), PicTar (four-way, http://pictar.mdc-berlin-de) and TargetScanS (http://www.targetscan.org/) with a cutoff P-value<0.05 (Sethupathy et al., 2006). The targets of pancreatic islet cell-specific miRNAs were identified by inverse relationships (highly negative correlations) between expression levels of miRNAs and their predicted target mRNAs (Bagga et al., 2005; Farh et al., 2005; Lim et al., 2005; Sood et al., 2006; Stark et al., 2005; Baek et al., 2008; Selbach et al., 2008). The expression levels of the mRNAs targeted by miRNAs in T3ES and T3pi cells were analysed by the Volcano plot using parametric test and Benjamini–Hochberg false discovery rate for multiple testing correction. The significantly differentially expressed genes were defined by fold changes of >3 and a P-value cutoff of 0.05.

3. Results

3.1. Characterization of gene expression during in vitro differentiation

The hES-T3 cells (passage 36) with normal female karyotype (46, XX) established previously in our laboratories (Li et al., 2006) were induced to differentiate into T3pi by the modified five-stage protocol (Figure 1). The expression of pancreatic genes during different differentiation stages was analysed using RT-PCR reactions (Figure 2), and the expression of insulin, glucagon and somatostatin, as well as OCT4 and NANOG, genes during different differentiation stages were also quantitated using real-time qPCR (Figure 3). The expression of undifferentiated hES cell-specific OCT4 and NANOG genes decreased at stages II (EB) and III and then disappeared at stages IV and V (pi). The glucagon gene expressed from stage II (EB) through stage V (pi) and increased significantly at stage V (pi). Somatostatin, PDX1 (pancreatic duodenal homeobox 1) and glucokinase genes expressed in stage II (EB), stages III and V (pi), but not stage IV. Insulin and NGN3 (neurogenin 3) genes expressed only at stage V (pi), and insulin gene increased significantly at stage V (pi). The T3pi at stage V (pi) were further examined by immunocytochemistry for the presence of C-peptide (insulin), glucagon and somatostatin (Figure 4). Many cells appeared to be stained for C-peptide, glucagon and/or somatostatin.

3.2. Expression profiling of mRNAs

The genome-wide mRNA expression of T3pi was determined using Affymetrix human genome U133 plus 2.0 GeneChip. The original data have been deposited in the NCBI database, and the GEO series number is GSE14503. The GO biological processes of 3137 genes up-regulated >3-fold in T3pi cells compared with T3ES cells were analysed using MetaCore GSEA program, and the majority of top 20 GO processes are involved in development (Supplementary Table S3 at http://www.cellbiolint.org/cbi/035/cbi0350029add.htm). The expression levels of transcriptional regulators involved in the specification of pancreatic islet cell types (Best et al., 2008) from T3pi cell clusters are compared with those (GSE9440) of undifferentiatedT3ES cells and differentiated T3EBs determined previously (Li et al., 2009) (Table 1). The expression of gut endoderm-specific SOX17, GATA4 and FOXA2 genes were found to increase at stage II (T3EB) and decreased significantly at stage V (T3pi). The specification markers for islet cell subtypes (HNF4α, HNF1α, PAX6, NKX2-2, NKX6-1, ARX, MAFB and GATA6) were found to increase at stage V (T3pi), indicating that many of these cells had been fully differentiated into pancreatic islet-like cells. However, the presence of specification markers for pancreas (PDX1, SOX9, SOX4 and PBX1) and endocrine (NGN3, ISL1, NEUROD1 and IA1) at stage V (T3pi) suggested that many of these cells were immature pancreatic progenitor cells yet to be fully differentiated into islet-like cells.


Table 1 Expression level of transcriptional regulators involved in the specification of islet cell types

T3ES, hES-T3 grown on MEF feeder; data from GSE9440 (Li et al., 2009); T3EB, hES-T3-derived EBs; data from GSE9440 [22]; T3pi, hES-T3-derived pancreatic islet-like cell clusters; data from GSE14503. The expression levels were indicated by folds of overall mean. Bold-type indicates biomarker genes.

Transcription factors Cell types Functions
Gut tube T3ES T3EB T3pi
    SOX17 17.84 42.76 0.62 Formation of gut endoderm
    GATA4 2.61 24.19 4.89 Differentiation of both exocrine and endocrine lineage
    FOXA2 (HNF3β) 4.58 38.54 1.67 Required for α-cell lineage
Pancreas specification
    PDX1 0.91 0.65 1.31 Pancreatic development, differentiation of α- and β-cells
    SOX9 0.44 4.17 18.07 Expressed in all pancreatic progenitor cells, islet organization
    SOX4 5.88 7.48 11.79 Broadly expressed in pancreatic buds with subsequent restriction to islets
    PBX1 1.37 2.65 5.75 Required for both exocrine and endocrine differentiation
Endocrine specification
    NGN3 (NEO1) 0.79 1.80 3.45 Differentiation of endocrine lineage
    ISL1 0.85 64.50 12.13 Differentiation of all islet cell types
    NEUROD1 0.67 0.59 3.62 Differentiation of all islet cell types, transactivates insulin gene
    IA1 (INSM1) 1.03 1.36 83.42 Differentiation of α-, β- and δ-cells
Islet cell subtypes
    HNF4αα 1.04 1.05 2.48 Transactivation of HNF1α and insulin gene
    HNF1α (TCF1) 1.09 0.98 6.72 Transactivation of PDX1 and insulin gene
    PAX6 2.91 0.43 56.49 Differentiation of all islet cell types, transactivates glucagon gene
    NKX2-2 0.73 0.65 8.23 Transactivation of NKX6-1 and insulin genes in β-cell precursors
    NKX6-1 1.38 0.94 3.66 Differentiation of β-cells
    ARX 0.86 0.76 5.75 Co-expressed with PAX4, formation of α- and β-cells
    MAFB 0.57 0.92 4.66 Formation of α and β-cells, controls glucagon expression
    GATA6 3.40 10.86 12.91 Differentiation of endocrine lineage, expressed in β-cells



3.3. Expression profiling of miRNAs

The expression profiles of 250 human miRNAs from T3pi were quantitated using TagMan MicroRNA assays as described previously (Chen et al., 2005; Liang et al., 2007; Li et al., 2009), and the expression level of each miRNA was indicated as folds over U6 snRNA. The average values of triplicate analyses for 250 miRNAs from these T3pi cell clusters are compared with those of undifferentiated T3ES cells and differentiated T3EBs determined previously (Li et al., 2009) (Supplementary Table S4 at http://www.cellbiolint.org/cbi/035/cbi0350029add.htm). Three miRNAs, miR-186, miR-199a and miR-339, were found to be extremely abundantly (>500-fold of U6 snRNA) expressed and highly (>40-fold of changes) up-regulated in T3pi cell clusters compared with both T3ES and T3EB cells (Table 2). Six other miRNAs, miR-24, miR-191, miR-132, miR-181b, miR-30d and miR-181a, were abundantly (>10-fold of U6 snRNA) differentially (>3-fold of changes) expressed in T3pi cells compared with both T3MF and T3EB cells. The miRNA miR-375, which was previously reported to inhibit insulin secretion, decreased >3-fold in T3pi cells. Four hES cell-specific miRNAs, miR-302d, miR-367, miR-372 and miR-200c (Li et al., 2009), as well as four other miRNAs, miR-19b, miR-20b, miR-221 and miR-222, were significantly down-regulated in T3pi cell clusters. The other tissue (heart, liver, testis and placenta)-specific miRNAs were not expressed in T3pi cells.


Table 2 Levels of miRNAs expressed highly in T3pi cells

miRNAs T3ES T3EB T3pi pi/ES pi/EB Chromosome
miR-186 26.08 60.54 5376.23 206 89 1p31.1
miR-199a 44.84 42.13 2061.13 46 49 19p13.2, 1q24.3
miR-339 0.51 2.22 563.98 1106 254 6p22.3
miR-24 376.70 191.73 952.22 3 5 9q22.32, 11q24.1, 22q13.31
miR-191 30.65 80.04 220.78 7 3 3p21.12
miR-132 23.33 5.22 136.85 6 26 9q21.33, 15q26.1, 19p13.3
miR-181b 12.87 14.18 102.97 8 7 3q25.33
miR-30d 5.16 1.87 14.99 3 8 11q23.1
miR-181a 1.87 1.68 10.24 5 6 7q32.2



3.4. Target identification of miRNAs up-regulated in T3pi cell clusters

The potential targets of three highly up-regulated miRNAs miR-186, miR-199a and miR-339 were predicted by the union of miRanda, PicTar (four-way) and TargetScanS, and the targets of pancreatic islet cell-specific miRNAs were identified by inverse expression levels (highly negative correlations) between miRNAs and their target mRNAs (Table 3). Eight abundantly (>3-fold of overall mean) differentially (>3-fold of changes) expressed genes LIN28, PRDM1, CALB1, GCNT2, RBM47, PLEKHH1, RBPMS2 and PAK6 in T3ES and T3EB cells were found using a Volcano plot of >3-fold changes and a P-value cutoff of 0.05 to be targets of these three highly up-regulated miRNAs (Table 4).


Table 3 Negative correlation coefficients between expression levels of up-regulated miRNAs and their target mRNAs

Genes miR-186 miR-199a miR-339
LIN28 −0.99
PRDM1 −0.77
CALB1 −0.59
GCNT2 −0.97
RBM47 −0.88
PLEKHH1 −0.99
RBPMS2 −0.85
PAK6 −0.98




Table 4 The expression levels of mRNAs targeted by up-regulated miRNAs in T3pi cells

Gene symbol miRs Description UniGene
T3ES T3EB T3pi ES/pi EB/pi 186 199a 339
LIN28 487.30 438.70 6.26 77.8 70.1 186 Lin-28 homologue Hs.368563
PRDM1 4.62 12.53 0.29 15.8 42.9 186 Rho guanine nucleotide exchange factor (GEF) 7 Hs.508738
CALB1 48.29 7.32 1.97 24.5 3.7 186 Calbindin 1, 28kda, Ca-binding protein 1 Hs.420024
GCNT2 92.58 71.65 2.17 42.7 33.0 199a Glucosaminyl (n-acetyl) transferase 2, i-branching enzyme Hs.483238
RBM47 15.72 8.65 0.97 16.2 8.9 199a RNA-binding motif protein 47 Hs.696080
PLEKHH1 8.33 8.60 0.79 10.6 10.9 199a Pleckstrin homology domain containing, family h Hs.88252
RBPMS2 16.16 8.57 1.52 10.7 5.7 199a RNA binding protein with multiple splicing 2 Hs.489603
PAK6 3.25 3.90 0.64 5.1 6.1 339 P21(cdkn1a)-activated kinase 6 Hs.447458



4. Discussion

In this investigation, hES-T3 were differentiated into T3pi. The specification markers of pancreas, endocrine and islet cell types were found to be significantly increased, indicating the presence of differentiated islet cell types alpha (glucagon), beta (insulin) and delta (somatostatin) as well as immature pancreatic progenitor cells. A unique set of miRNAs during mouse pancreas development has been reported (Lynn et al., 2007), and miRNAs have also been shown to regulate insulin production, secretion and action, as well as indirectly control glucose homoeostasis and lipid metabolism (Poy et al., 2004; Hennessy and O'Driscoll 2008; Tang et al., 2008). For example, miR-375 has been shown to negatively regulate insulin secretion in mouse beta cell line (MIN6), and myotrophin was found to be a target of miR-375 (Poy et al., 2004). Four islet-specific miRNAs, miR-7, miR-9, miR-375 and miR-376, were recently reported to express at high levels during human pancreatic islet development (Joglekar et al., 2009). miR-9 inhibits insulin secretion by repressing the expression of onecut2 transcription factor and thereby increasing the level of granuphilin, which down-regulates insulin secretion.

Three miRNAs, miR-186, miR-199a and miR-339, most abundantly expressed in T3pi cells, and eight miRNA target genes, LIN28, PRDM1, CALB1, GCNT2, RBM47, PLEKHH1, RBPMS2 and PAK6 were identified by inverse expression levels of these miRNAs to their target mRNAs. The biological functions of these eight genes in pancreas islet development, as well as insulin production, secretion and action, remain to be elucidated experimentally. However, it is of interest to note that the LIN28, a target of the most abundantly expressed miR-186 in T3pi cells, was previously shown to be stage-specifically expressed in mouse embryonic muscle, neurons and epithelia (Yang and Moss, 2003). The Lin28 protein was further found to be essential for skeletal muscle differentiation by binding to Igf2, a growth and differentiation factor, in mice (Polesskaya et al., 2007). Recently, the Lin28 was shown to selectively block the processing of pri-let7 miRNAs, and Lin28 may play a central role in blocking miRNA-mediated differentiation in stem cells and in certain cancers (Viswanathan et al., 2008). The LIN28, along with OCT4, SOX2 and NANOG, was able to reprogramme human somatic cells to pluripotent stem cells that exhibit the essential characteristics of embryonic stem cells and maintain the developmental potential to differentiate into advanced derivatives of all three primary germ layers (Yu et al., 2007).

MicroRNA miR-186, as well as miR-150, down-regulate expression of the pro-apoptotic purinergic P2X7 receptor by activation of instability sites at the 3′-untranslated region of the gene that decreases steady-state levels of the transcript (Zhou et al., 2008). miR-199a is encoded by duplicated genes located within the intron of dynamin genes on chromosomes 1 and 19 and that miR-199a is highly up-regulated by activin A (Tsai et al., 2009). The miR-199a and miR-199a* (processed from the same miRNA precursor) were recently reported to down-regulate the MET proto-oncogene and its downstream effector ERK2 (extracellular-signal-regulated kinase 2) gene resulting in inhibiting cell proliferation of tumour cells (Kim et al., 2008). miR-199a and miR-199a* were shown to also inhibit the mRNA translation of IκB kinase β required for NF-κB activation in ovarian cancer cells (Chen et al., 2008).

5. Conclusions

hES-T3 cells were differentiated into T3pi and were shown to express pancreatic islet cell-specific markers of insulin, glucagon and somatostatin. The expression profiles of microRNAs and mRNAs from the T3pi were also analysed and compared with those of undifferentiated hES-T3 cells and differentiated EBs. T3pi exhibit very high expression of microRNAs, miR-186, miR-199a and miR-339, and these miRNAs were found to reduce the expression of their target genes LIN28, PRDM1, CALB1, GCNT2, RBM47, PLEKHH1, RBPMS2 and PAK6. Therefore, these microRNAs and their target genes probably play important regulatory roles in the development of pancreas and/or differentiation of islet cells.

Author contribution

Bo-Zhi Chen performed most of experiments and summarized the results. Sung-Liang Yu supervised the DNA microarray core facility of National Taiwan University College of Medicine. Sher Singh did bioinformatic analyses. Li-Pin Kao and Zong-Yun Tsai did parts of the experiments. Pan-Chyr Yang established and directed the microarray core facility of National Taiwan University College of Medicine. Bai-Hsiun Chen co-advised the MS thesis of Bo-Zhi Chen. Steven Shoei-Lung Li designed the experiments, analysed the results and wrote the manuscript.

Acknowledgements

We thank the technical assistance by the research assistants at Microarray Core Facility of National Research Program for Genomic Medicine of National Science Council in Taiwan.

Funding

This work was supported in part by a grant NSC98-2314-B-037-024-MY3 of the National Science Council in Taiwan and Center of Excellence for Environmental Medicine Project KMU-EM-97-1.3c to Steven Shoei-Lung Li.

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Received 3 July 2009/2 December 2009; accepted 25 August 2010

Published as Cell Biology International Immediate Publication 25 August 2010, doi:10.1042/CBI20090081


© The Author(s) Journal compilation © 2011 Portland Press Limited


ISSN Print: 1065-6995
ISSN Electronic: 1095-8355
Published by Portland Press Limited on behalf of the International Federation for Cell Biology (IFCB)