Differential Gene Expression Profiling of Human Umbilical Cord Blood–Derived Mesenchymal Stem Cells by DNA Microarray
http://www.100md.com
《干细胞学杂志》
Research Institute of Biotechnology, Histostem Co., Kangdong-Gu, Seoul, Korea
Key Words. Mesenchymal stem cells ? Human umbilical cord blood ? DNA microarray
Correspondence: Hoeon Kim, Ph.D., Research Institute of Biotechnology, Histostem Co. 518-4 Taijul Bldg., Doonchun-dong, Kangdong-gu, Seoul 134-060, Korea. Telephone: 82-2-488-8154; Fax: 82-2-470-6342; e-mail: hoeonkim@seoulcord.co.kr
ABSTRACT
Mesenchymal stem cells (MSCs), also dubbed marrow stromal stem cells, stromal precursor cells, mesenchymal progenitor cells, or colony-forming unit-fibroblastic (CFU-F) cells, are highly proliferating and adherent fibroblastic cells that express a panel of characteristic cell surface markers . MSCs retain not only the capacity to self-renew but also the potential to differentiate into a variety of connective tissues such as muscle, bone, cartilage, tendon, and fat, as well as nerve and liver tissues . These properties make them a possible alternative to embryonic stem cells (ESCs) in cell-based therapeutic applications, but little has been known about their nature, in vivo function, and developmental origin. In particular, the molecular parameters to define core stem cell properties have remained largely unexplored.
Self-renewal is one of the most fundamental properties of stem cells, and the cellular and molecular mechanisms underlying it have been a subject of extensive studies. Elaborated searches for key transcriptional players led to discoveries of Oct3/4 , leukemia inhibitory factor–activated Stat3 , and Nanog in ESCs, and a recent finding of Bmi-1 in both hematopoietic stem cells (HSCs) and neural stem cells (NSCs) . Also in efforts to envisage a molecular entity of stem cells in the genomic scale, the DNA microarray-based analyses were recently employed in human or mouse ESCs, HSCs, and NSCs, leading to identification of commonly expressed genes, called stemness genes or a stem cell molecular signature .
As in any other stem cells, the self-renewal of MSCs is likely to be operated by a defined set of molecular factors, but no molecular factor relevant to this function has been identified to date. The gene expression profile of MSCs has been previously investigated through serial analysis of gene expression (SAGE) and restriction fragment differential display . Although the studies provided us with a plausible framework to define the MSCs in the genetic level, the presence of abundant housekeeping genes prevented the correct assessment of MSC-specific genetic messages.
In the study reported here, with the specific aim to generate an MSC-specific transcriptome, we performed a DNA microarray-based differential gene expression analysis between a fraction of human umbilical cord blood (UCB)–derived mononuclear cells (MNCs) and its MSC subpopulation. UCB-derived cells were proven to be more advantageous in cell procurement, storage, and transplantation than their bone marrow (BM) counterpart and therefore better suited in tissue engineering and development of cell-based therapeutics. A number of reports from different laboratories , including ours , indicate that UCB-derived MSCs are highly similar to the cells of BM origin with respect to cell characteristics and multilineage differentiation potential. Therefore, this study may lead us to reveal the molecular signature that is specific to human MSCs but independent of their origins, and it will assist further studies on molecular mechanisms controlling various core stem cell properties.
MATERIALS AND METHODS
Reproducibility and Sensitivity of Microarray Experiments
Reproducibility in the microarray experiment from target preparation to data analysis was assessed by repeated experiments using separately prepared target RNAs from a MSC sample. A correlation coefficient between two microarray datasets obtained from repeated experiments turned out to be greater than .98 for all gene probes above noise, indicating that not only each microarray system per se but also a whole experimental procedure were highly reproducible. Figure 1 shows a scatter plot between the two datasets when all 20,289 gene probes were included. Almost all of the probes with a normalized intensity above 5.0 were located within a 1.5-fold limit, showing an excellent correlation in this portion of the data. However, such covariance quickly disappeared when the probe intensity was near 1.0. Therefore, any probe whose normalized intensity was below 1.0 was considered to be inaccurate. To eliminate this noise effect from low-level expression, spots quantified at <1.0 were replaced by the value 1.0 and subjected to further analyses.
Figure 1. Scatter plot of the two normalized microarray datasets that resulted from different target preparations of umbilical cord blood–derived mesenchymal stem cells. All 20,289 gene probes are represented in this plot. The outer red/orange lines indicate a 1.5-fold difference, while the green line represents equality. Abbreviations: CC, correlation coefficient.
Interdonor and Intercell Comparison of Gene Expression Patterns
The correlation coefficient between two MNC populations from donors 1 and 2 was about .95 for all probes above noise (Fig. 2), indicating that the gene expression pattern of cells in the neonatal blood system was almost invariable. This consistent gene expression pattern might be an outcome of the constant operation of genetic programs that are critical for cells and tissues, particularly for the cells in the blood stream, in all healthy individuals. The correlation coefficient between the MSC populations was estimated to be around .92, a little lower than the value of MNCs. However, when it is considered that those MSCs were sampled after extensive cell expansion, this difference is likely to be contributed by variations in culture or passage conditions, rather than intrinsic interindividual variation in the gene expression profile.
Figure 2. Tabulation of scatter graphs of the log intensity values and correlation coefficients (CCs) between any two of the four samples. The numbers in parentheses indicate the number of gene probes above noise that were present in both datasets and which were used in calculation of a CC. The mononuclear cells (MNCs) from donors 1 and 2 were freshly prepared, whereas the mesenchymal stem cells (MSCs) of donors 3 and 4 were cultured for three and five passages, respectively. Abbreviation: UCB, umbilical cord blood.
In contrast, when the gene expression profile was compared between two different types of cells—that is, MNCs and MSCs—a significant difference was observed, as demonstrated by widely dispersed patterns in the plots and correlation coefficients between .54 and .59 (Fig. 2). When all gene probes above noise were taken into a consideration, only 20%–25% were found to be located within a 1.5-fold limit, and the rest of the genes (75%–80%) could be considered to be differentially expressed between the two cell populations. Among differentially expressed genes, we were particularly interested in a subset of genes that was highly expressed in MSCs but rarely detectable in MNCs because it, as a whole or in part, could be regarded as the molecular signature of MSCs. The normalized intensity of each gene was averaged separately over the MNC and MSC populations. When the genes were ranked by the MSC-to-MNC ratios of average intensity and selected with a ratio greater than 50, a subset containing 47 different genes was generated (Table 1). Comparison of intensity scores of these genes with published SAGE data indicated that most (but not all) genes in this subset were rich in BM-derived MSCs. These genes were found to cluster together in the hierarchical clustering analysis, confirming again their coherent expression patterns (Fig. 3).
Table 1. Differentially expressed genes in UCB-derived MSCs
Figure 3. Hierarchical clustering of umbilical cord blood (UCB)–derived mesenchymal stem cell (MSC) and mononuclear cell (MNC) samples. The flagged probes were filtered out, and the resulting 11,662 probes were used in the calculation. The standard correlation was used as a similarity measure. The asterisk indicates a cluster of genes that was differentially expressed by MSCs versus MNCs.
Differentially Expressed Genes in UCB-Derived MSCs
The subset contains 42 known and 5 novel genes. Of the known genes, 28 genes (>65%) encode the extracellular molecules that either participate in biogenesis of the extracellular matrix (ECM) or belong to cytokine or related products. The former consists of structural proteins of ECM including seven different types of collagens (I1, I2, III1, IV1, IV2, VI2, and VI3), CTHRC1, CRTL1, lumican, and fibulin 4, as well as ECM biogenesis factors, including two types of serpins (SERPINE1 and SERPINH2) and three lysyl oxidases (LOXL1, LOX and its variant), whereas the latter consists of three different types of IGFBPs (IGFBP-6, IGFBP-7, and CTGF), PRSS11, OSF-2, CYR61, Wnt5B, PLAB, FAP, GAS6, and follistatin. It also contains four genes encoding membrane proteins—Thy-1, KDELR3, NDUFA4, and BNIP3—in which the former two proteins are destined to plasma and endoplasmic reticulum, respectively, whereas the latter two belong to mitochondrial membrane proteins. There are also five genes for cytoskeleton-associated proteins: transgelin, -B-crystallin, tropomyosin I, EPLIN, and RIL; four genes for soluble proteins: NNMT, PKCBP, P311, and PYCR1; and finally two nuclear genes: necdin and a LIM domain protein FHL2. It is noteworthy that among those genes, collagens types I, III, IV, and VI , transgelin , Thy-1 , and FAP were known as characteristics of MSCs and previously identified in human MSCs.
Of the five novel genes, MGC3047 and MGC17528 were recently predicted to encode an immunoglobulin superfamily protein limitrin and an S100 calcium-binding protein, A16, respectively. And our blast analysis of MGC3278 and FLJ12442, encoding hypothetical proteins containing 563 and 520 amino acids, respectively, showed that the former contains a DUF719 domain of unknown function but conserved in several eukaryotic proteins while the latter belong to a 5' nucleotidase protein family. However, the identity of AGENCOURT_6683145 could not be resolved.
Confirmation of Gene Expression by RT-PCR
To verify the gene expression profile determined by our microarray analysis, the expression levels of the top 10 genes in the subset were analyzed by RT-PCR, using total RNAs obtained from the four cell samples. The result showed that all tested genes were expressed highly in MSCs, but either weakly or negligibly in MNCs (Fig. 4A). This differential expression pattern was in a good agreement with that from the microarray analysis, confirming the high fidelity in microarray data and analytical methods. Moreover, when an additional pair of fresh MNC and MSC samples was analyzed by RT-PCR, they exhibited a differential expression pattern (Fig. 4B) that was consistent with those of the former samples (Fig. 4A). This finding implies that the gene expression profile determined in this study can be extrapolated to most, if not all, UCB from healthy individuals.
Figure 4. Reverse transcription polymerase chain reaction analysis of the selected differentially expressed genes. The top 10 most differentially expressed genes in mesenchymal stem cell’s (MSCs) were chosen, and their expression levels were examined in (A) the four cell samples used in the microarray experiment, as well as (B) an additional pair of samples from mononuclear cells (MNCs; from donor 5) and MSCs (from donor 6, at the second passage). Glyceraldehyde 3-phosphate dehydrogenase (GAPDH) was used as an internal control. Abbreviation: UCB, umbilical cord blood.
Comparison of Microarray Data with Published SAGE Data
A total of 7,898 unique genes resulted from integration of the microarray and SAGE datasets . The correlation coefficient between the two datasets was calculated to be around .46, but this figure still indicated a meaningful covariance when it was considered that the two analytic methods had different strengths and pitfalls in transcriptional profiling analysis . A scatter plot also showed that the two datasets were weakly but not randomly correlated (Fig. 5). After the genes were ranked and sorted by the microarray intensity score, the top 50 genes were pooled to constitute a subset of the most enriched genes in UCB-derived MSCs (Table 2). All of the genes were found to be also in high frequencies in the SAGE dataset, indicating that the correlation was generally higher for genes with higher expression levels. More than one half of these abundant genes are those involved in protein synthesis, including 24 different ribosomal proteins and three regulatory factors. The remaining genes encode known products, including four cytokines: CTGF, TIMP1, IGFBP7, and TGFBI; four glycolytic enzymes: GAPD, EN01, LDHA, and TPI1; six cytoskeletal proteins: vimentin, MYL6, transgelin, destrin, thymosin, and -actin; two heat shock proteins: HSPA8 and HSPB1; and other cytosolic or extracellular proteins. Among known products, CTGF, TAGLN, COL1A1, and IGFBP7 belong to MSC-specific molecules, as mentioned earlier. Most of the rest are housekeeping genes whose expression patterns are more or less constant in all proliferating cells. A most abundant gene is EEF1A1, which is responsible for the enzymatic delivery of aminoacyl tRNAs to the ribosome.
Figure 5. Log-log scatter plot between the microarray and serial analysis of gene expression (SAGE) datasets. Genes with no tag or tags that match multiple genes were excluded to generate a set of a total of 7,898 unique genes. The correlation coefficient between two datasets was about 0.46 for all data points.
Table 2. First 50 most enriched genes in UCB-derived MSCs
DISCUSSION
This research was supported by a grant (SC13032) from the Stem Cell Research Center of the 21st Century Frontier Research Program funded by the Ministry of Science and Technology, Republic of Korea. J.A. Jeong, S.H. Hong, and E.J. Gang contributed equally to this article.
REFERENCES
Tocci A, Forte L. Mesenchymal stem cell: use and perspectives. Hematol J 2003;4:92–96.
Minguell JJ, Erices A, Conget P. Mesenchymal stem cells. Exp Biol Med 2001;226:507–520.
Nichols J, Zevnik B, Anastassiadis K et al. Formation of pluripotent stem cells in the mammalian embryo depends on the POU transcription factor Oct4. Cell 1998;95:379–391.
Williams RL, Hilton DJ, Pease S et al. Myeloid leukaemia inhibitory factor maintains the developmental potential of embryonic stem cells. Nature 1988;336:684–687.
Niwa H, Burdon T, Chambers I et al. Self-renewal of pluripotent embryonic stem cells is mediated via activation of STAT3. Genes Dev 1988;12:2048–2060.
Matsuda T, Nakamura T, Nakao K et al. STAT3 activation is sufficient to maintain an undifferentiated state of mouse embryonic stem cells. EMBO J 1999;18:4261–4269.
Mitsui K, Tokuzawa Y, Itoh H et al. The homeoprotein Nanog is required for maintenance of pluripotency in mouse epiblast and ES cells. Cell 2003;113:631–642.
Chambers I, Colby D, Robertson M et al. Functional expression cloning of Nanog, a pluripotency sustaining factor in embryonic stem cells. Cell 2003;113:643–655.
Park I, Qian D, Kiel M et al. Bmi-1 is required for maintenance of adult self-renewing haematopoietic stem cells. Nature 2003;423:302–305.
Molofsky AV, Pardal R, Iwashita T et al. Bmi-1 dependence distinguishes neural stem cell-renewal from progenitor proliferation. Nature 2003;425:962–967.
Phillips RL, Ernst RE, Brunk B et al. The genetic program of hematopoietic stem cells. Science 2000;288:1635–1640.
Ramalho-Santos M, Yoon S, Matsuzaki Y et al. "Stemness": transcriptional profiling of embryonic and adult stem cells. Science 2002;298:597–600.
Ivanova NB, Dimos JT, Schaniel C et al. A stem cell molecular signature. Science 2002;298:601–604.
Bhattacharya B, Miura T, Brandenberger R et al. Gene expression in human embryonic stem cell lines: unique molecular signature. Blood 2004;103:2956–2964.
Tremain N, Korkko J, Ibberson D et al. MicroSAGE analysis of 2,353 expressed genes in a single cell-derived colony of undifferentiated human mesenchymal stem cells reveals mRNAs of multiple cell lineages. STEM CELLS 2000;18:408–418.
Silva WA Jr, Covas DT, Panepucci RA et al. The profile of gene expression of human marrow mesenchymal stem cells. STEM CELLS 2003;21:661–669.
Jia L, Young MF, Powell J et al. Gene expression profile of human bone marrow stromal cells: high-throughput expressed sequence tag sequencing analysis. Genomics 2004;79:7–17.
Monticone M, Liu Y, Tonachini L et al. Gene expression profile of human bone marrow stromal cells determined by restriction fragment differential display analysis. J Cell Biochem 2004;92:733–744.
Erices A, Conget P, Minguell JJ. Mesenchymal progenitor cells in human umbilical cord blood. Br J Heamatol 2000;109:235–242.
Goodwin HS, Bicknese AR, Chien SN et al. Multilineage differentiation activity by cells isolated from umbilical cord blood: expression of bone, fat, and neural markers. Biol Blood Marrow Transplant 2001;7:581–588.
Lee OK, Kuo TK, Chen WM et al. Isolation of multipotent mesenchymal stem cells from umbilical cord blood. Blood 2004;103:1669–1675.
Lee MW, Choi J, Yang MS et al. Mesenchymal stem cells from cryo-preserved human umbilical cord blood. Biochem Biophys Res Comm 2004;320:273–278.
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Gang EJ, Hong SH, Jeong JA et al. In vitro mesengenic potential of human umbilical cord blood-derived mesenchymal stem cells. Biochem Biophys Res Comm 2004;321:102–108.
Jeong JA, Gang EJ, Hong SH et al. Rapid neural differentiation of human cord blood-derived mesenchymal stem cells. Neuroreport 2004;15:1731–1734.
Gang EJ, Jeong JA, Hong SH et al. Skeletal myogenic differentiation of mesenchymal stem cells isolated from human umbilical cord blood. STEM CELLS 2004;22:617–624.
Chichester CO, Fernandez M, Minguell JJ. Extracellular matrix gene expression by human bone marrow stroma and by marrow fibroblasts. Cell Adhes Commun 1993;1:93–99.
Lawson D, Harrison M, Shapland C. Fibroblast transgelin and smooth muscle SM22alpha are the same protein, the expression of which is down-regulated in many cell lines. Cell Motil Cytoskeleton 1997;38:250–257.
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Key Words. Mesenchymal stem cells ? Human umbilical cord blood ? DNA microarray
Correspondence: Hoeon Kim, Ph.D., Research Institute of Biotechnology, Histostem Co. 518-4 Taijul Bldg., Doonchun-dong, Kangdong-gu, Seoul 134-060, Korea. Telephone: 82-2-488-8154; Fax: 82-2-470-6342; e-mail: hoeonkim@seoulcord.co.kr
ABSTRACT
Mesenchymal stem cells (MSCs), also dubbed marrow stromal stem cells, stromal precursor cells, mesenchymal progenitor cells, or colony-forming unit-fibroblastic (CFU-F) cells, are highly proliferating and adherent fibroblastic cells that express a panel of characteristic cell surface markers . MSCs retain not only the capacity to self-renew but also the potential to differentiate into a variety of connective tissues such as muscle, bone, cartilage, tendon, and fat, as well as nerve and liver tissues . These properties make them a possible alternative to embryonic stem cells (ESCs) in cell-based therapeutic applications, but little has been known about their nature, in vivo function, and developmental origin. In particular, the molecular parameters to define core stem cell properties have remained largely unexplored.
Self-renewal is one of the most fundamental properties of stem cells, and the cellular and molecular mechanisms underlying it have been a subject of extensive studies. Elaborated searches for key transcriptional players led to discoveries of Oct3/4 , leukemia inhibitory factor–activated Stat3 , and Nanog in ESCs, and a recent finding of Bmi-1 in both hematopoietic stem cells (HSCs) and neural stem cells (NSCs) . Also in efforts to envisage a molecular entity of stem cells in the genomic scale, the DNA microarray-based analyses were recently employed in human or mouse ESCs, HSCs, and NSCs, leading to identification of commonly expressed genes, called stemness genes or a stem cell molecular signature .
As in any other stem cells, the self-renewal of MSCs is likely to be operated by a defined set of molecular factors, but no molecular factor relevant to this function has been identified to date. The gene expression profile of MSCs has been previously investigated through serial analysis of gene expression (SAGE) and restriction fragment differential display . Although the studies provided us with a plausible framework to define the MSCs in the genetic level, the presence of abundant housekeeping genes prevented the correct assessment of MSC-specific genetic messages.
In the study reported here, with the specific aim to generate an MSC-specific transcriptome, we performed a DNA microarray-based differential gene expression analysis between a fraction of human umbilical cord blood (UCB)–derived mononuclear cells (MNCs) and its MSC subpopulation. UCB-derived cells were proven to be more advantageous in cell procurement, storage, and transplantation than their bone marrow (BM) counterpart and therefore better suited in tissue engineering and development of cell-based therapeutics. A number of reports from different laboratories , including ours , indicate that UCB-derived MSCs are highly similar to the cells of BM origin with respect to cell characteristics and multilineage differentiation potential. Therefore, this study may lead us to reveal the molecular signature that is specific to human MSCs but independent of their origins, and it will assist further studies on molecular mechanisms controlling various core stem cell properties.
MATERIALS AND METHODS
Reproducibility and Sensitivity of Microarray Experiments
Reproducibility in the microarray experiment from target preparation to data analysis was assessed by repeated experiments using separately prepared target RNAs from a MSC sample. A correlation coefficient between two microarray datasets obtained from repeated experiments turned out to be greater than .98 for all gene probes above noise, indicating that not only each microarray system per se but also a whole experimental procedure were highly reproducible. Figure 1 shows a scatter plot between the two datasets when all 20,289 gene probes were included. Almost all of the probes with a normalized intensity above 5.0 were located within a 1.5-fold limit, showing an excellent correlation in this portion of the data. However, such covariance quickly disappeared when the probe intensity was near 1.0. Therefore, any probe whose normalized intensity was below 1.0 was considered to be inaccurate. To eliminate this noise effect from low-level expression, spots quantified at <1.0 were replaced by the value 1.0 and subjected to further analyses.
Figure 1. Scatter plot of the two normalized microarray datasets that resulted from different target preparations of umbilical cord blood–derived mesenchymal stem cells. All 20,289 gene probes are represented in this plot. The outer red/orange lines indicate a 1.5-fold difference, while the green line represents equality. Abbreviations: CC, correlation coefficient.
Interdonor and Intercell Comparison of Gene Expression Patterns
The correlation coefficient between two MNC populations from donors 1 and 2 was about .95 for all probes above noise (Fig. 2), indicating that the gene expression pattern of cells in the neonatal blood system was almost invariable. This consistent gene expression pattern might be an outcome of the constant operation of genetic programs that are critical for cells and tissues, particularly for the cells in the blood stream, in all healthy individuals. The correlation coefficient between the MSC populations was estimated to be around .92, a little lower than the value of MNCs. However, when it is considered that those MSCs were sampled after extensive cell expansion, this difference is likely to be contributed by variations in culture or passage conditions, rather than intrinsic interindividual variation in the gene expression profile.
Figure 2. Tabulation of scatter graphs of the log intensity values and correlation coefficients (CCs) between any two of the four samples. The numbers in parentheses indicate the number of gene probes above noise that were present in both datasets and which were used in calculation of a CC. The mononuclear cells (MNCs) from donors 1 and 2 were freshly prepared, whereas the mesenchymal stem cells (MSCs) of donors 3 and 4 were cultured for three and five passages, respectively. Abbreviation: UCB, umbilical cord blood.
In contrast, when the gene expression profile was compared between two different types of cells—that is, MNCs and MSCs—a significant difference was observed, as demonstrated by widely dispersed patterns in the plots and correlation coefficients between .54 and .59 (Fig. 2). When all gene probes above noise were taken into a consideration, only 20%–25% were found to be located within a 1.5-fold limit, and the rest of the genes (75%–80%) could be considered to be differentially expressed between the two cell populations. Among differentially expressed genes, we were particularly interested in a subset of genes that was highly expressed in MSCs but rarely detectable in MNCs because it, as a whole or in part, could be regarded as the molecular signature of MSCs. The normalized intensity of each gene was averaged separately over the MNC and MSC populations. When the genes were ranked by the MSC-to-MNC ratios of average intensity and selected with a ratio greater than 50, a subset containing 47 different genes was generated (Table 1). Comparison of intensity scores of these genes with published SAGE data indicated that most (but not all) genes in this subset were rich in BM-derived MSCs. These genes were found to cluster together in the hierarchical clustering analysis, confirming again their coherent expression patterns (Fig. 3).
Table 1. Differentially expressed genes in UCB-derived MSCs
Figure 3. Hierarchical clustering of umbilical cord blood (UCB)–derived mesenchymal stem cell (MSC) and mononuclear cell (MNC) samples. The flagged probes were filtered out, and the resulting 11,662 probes were used in the calculation. The standard correlation was used as a similarity measure. The asterisk indicates a cluster of genes that was differentially expressed by MSCs versus MNCs.
Differentially Expressed Genes in UCB-Derived MSCs
The subset contains 42 known and 5 novel genes. Of the known genes, 28 genes (>65%) encode the extracellular molecules that either participate in biogenesis of the extracellular matrix (ECM) or belong to cytokine or related products. The former consists of structural proteins of ECM including seven different types of collagens (I1, I2, III1, IV1, IV2, VI2, and VI3), CTHRC1, CRTL1, lumican, and fibulin 4, as well as ECM biogenesis factors, including two types of serpins (SERPINE1 and SERPINH2) and three lysyl oxidases (LOXL1, LOX and its variant), whereas the latter consists of three different types of IGFBPs (IGFBP-6, IGFBP-7, and CTGF), PRSS11, OSF-2, CYR61, Wnt5B, PLAB, FAP, GAS6, and follistatin. It also contains four genes encoding membrane proteins—Thy-1, KDELR3, NDUFA4, and BNIP3—in which the former two proteins are destined to plasma and endoplasmic reticulum, respectively, whereas the latter two belong to mitochondrial membrane proteins. There are also five genes for cytoskeleton-associated proteins: transgelin, -B-crystallin, tropomyosin I, EPLIN, and RIL; four genes for soluble proteins: NNMT, PKCBP, P311, and PYCR1; and finally two nuclear genes: necdin and a LIM domain protein FHL2. It is noteworthy that among those genes, collagens types I, III, IV, and VI , transgelin , Thy-1 , and FAP were known as characteristics of MSCs and previously identified in human MSCs.
Of the five novel genes, MGC3047 and MGC17528 were recently predicted to encode an immunoglobulin superfamily protein limitrin and an S100 calcium-binding protein, A16, respectively. And our blast analysis of MGC3278 and FLJ12442, encoding hypothetical proteins containing 563 and 520 amino acids, respectively, showed that the former contains a DUF719 domain of unknown function but conserved in several eukaryotic proteins while the latter belong to a 5' nucleotidase protein family. However, the identity of AGENCOURT_6683145 could not be resolved.
Confirmation of Gene Expression by RT-PCR
To verify the gene expression profile determined by our microarray analysis, the expression levels of the top 10 genes in the subset were analyzed by RT-PCR, using total RNAs obtained from the four cell samples. The result showed that all tested genes were expressed highly in MSCs, but either weakly or negligibly in MNCs (Fig. 4A). This differential expression pattern was in a good agreement with that from the microarray analysis, confirming the high fidelity in microarray data and analytical methods. Moreover, when an additional pair of fresh MNC and MSC samples was analyzed by RT-PCR, they exhibited a differential expression pattern (Fig. 4B) that was consistent with those of the former samples (Fig. 4A). This finding implies that the gene expression profile determined in this study can be extrapolated to most, if not all, UCB from healthy individuals.
Figure 4. Reverse transcription polymerase chain reaction analysis of the selected differentially expressed genes. The top 10 most differentially expressed genes in mesenchymal stem cell’s (MSCs) were chosen, and their expression levels were examined in (A) the four cell samples used in the microarray experiment, as well as (B) an additional pair of samples from mononuclear cells (MNCs; from donor 5) and MSCs (from donor 6, at the second passage). Glyceraldehyde 3-phosphate dehydrogenase (GAPDH) was used as an internal control. Abbreviation: UCB, umbilical cord blood.
Comparison of Microarray Data with Published SAGE Data
A total of 7,898 unique genes resulted from integration of the microarray and SAGE datasets . The correlation coefficient between the two datasets was calculated to be around .46, but this figure still indicated a meaningful covariance when it was considered that the two analytic methods had different strengths and pitfalls in transcriptional profiling analysis . A scatter plot also showed that the two datasets were weakly but not randomly correlated (Fig. 5). After the genes were ranked and sorted by the microarray intensity score, the top 50 genes were pooled to constitute a subset of the most enriched genes in UCB-derived MSCs (Table 2). All of the genes were found to be also in high frequencies in the SAGE dataset, indicating that the correlation was generally higher for genes with higher expression levels. More than one half of these abundant genes are those involved in protein synthesis, including 24 different ribosomal proteins and three regulatory factors. The remaining genes encode known products, including four cytokines: CTGF, TIMP1, IGFBP7, and TGFBI; four glycolytic enzymes: GAPD, EN01, LDHA, and TPI1; six cytoskeletal proteins: vimentin, MYL6, transgelin, destrin, thymosin, and -actin; two heat shock proteins: HSPA8 and HSPB1; and other cytosolic or extracellular proteins. Among known products, CTGF, TAGLN, COL1A1, and IGFBP7 belong to MSC-specific molecules, as mentioned earlier. Most of the rest are housekeeping genes whose expression patterns are more or less constant in all proliferating cells. A most abundant gene is EEF1A1, which is responsible for the enzymatic delivery of aminoacyl tRNAs to the ribosome.
Figure 5. Log-log scatter plot between the microarray and serial analysis of gene expression (SAGE) datasets. Genes with no tag or tags that match multiple genes were excluded to generate a set of a total of 7,898 unique genes. The correlation coefficient between two datasets was about 0.46 for all data points.
Table 2. First 50 most enriched genes in UCB-derived MSCs
DISCUSSION
This research was supported by a grant (SC13032) from the Stem Cell Research Center of the 21st Century Frontier Research Program funded by the Ministry of Science and Technology, Republic of Korea. J.A. Jeong, S.H. Hong, and E.J. Gang contributed equally to this article.
REFERENCES
Tocci A, Forte L. Mesenchymal stem cell: use and perspectives. Hematol J 2003;4:92–96.
Minguell JJ, Erices A, Conget P. Mesenchymal stem cells. Exp Biol Med 2001;226:507–520.
Nichols J, Zevnik B, Anastassiadis K et al. Formation of pluripotent stem cells in the mammalian embryo depends on the POU transcription factor Oct4. Cell 1998;95:379–391.
Williams RL, Hilton DJ, Pease S et al. Myeloid leukaemia inhibitory factor maintains the developmental potential of embryonic stem cells. Nature 1988;336:684–687.
Niwa H, Burdon T, Chambers I et al. Self-renewal of pluripotent embryonic stem cells is mediated via activation of STAT3. Genes Dev 1988;12:2048–2060.
Matsuda T, Nakamura T, Nakao K et al. STAT3 activation is sufficient to maintain an undifferentiated state of mouse embryonic stem cells. EMBO J 1999;18:4261–4269.
Mitsui K, Tokuzawa Y, Itoh H et al. The homeoprotein Nanog is required for maintenance of pluripotency in mouse epiblast and ES cells. Cell 2003;113:631–642.
Chambers I, Colby D, Robertson M et al. Functional expression cloning of Nanog, a pluripotency sustaining factor in embryonic stem cells. Cell 2003;113:643–655.
Park I, Qian D, Kiel M et al. Bmi-1 is required for maintenance of adult self-renewing haematopoietic stem cells. Nature 2003;423:302–305.
Molofsky AV, Pardal R, Iwashita T et al. Bmi-1 dependence distinguishes neural stem cell-renewal from progenitor proliferation. Nature 2003;425:962–967.
Phillips RL, Ernst RE, Brunk B et al. The genetic program of hematopoietic stem cells. Science 2000;288:1635–1640.
Ramalho-Santos M, Yoon S, Matsuzaki Y et al. "Stemness": transcriptional profiling of embryonic and adult stem cells. Science 2002;298:597–600.
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