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First published online November 8, 2007
Stem Cells Vol. 26 No. 2 February 2008, pp. 356 -363
doi:10.1634/stemcells.2007-0625; www.StemCells.com
© 2008 AlphaMed Press

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TRANSLATIONAL AND CLINICAL RESEARCH: MESENCHYMAL STEM CELLS SERIES

Concise Review: MicroRNA Expression in Multipotent Mesenchymal Stromal Cells

Uma Lakshmipathya, Ronald P. Hartb

aStem Cells and Regenerative Medicine, Invitrogen Corporation, Carlsbad, California, USA;
bW. M. Keck Center for Collaborative Neuroscience, Rutgers University, Piscataway, New Jersey, USA

Key Words. MicroRNA • Gene regulation • Epigenetics • Human mesenchymal stem cells • Review

Correspondence: Uma Lakshmipathy, Ph.D., Invitrogen Corporation, 1600 Faraday Avenue, Carlsbad, California 92008, USA. Telephone: 760-268-7465; Fax: 760-602-6637; e-mail: uma.lakshmipathy{at}invitrogen.com

Received August 6, 2007; accepted for publication October 31, 2007.
First published online in STEM CELLS EXPRESS   November 8, 2007.


   ABSTRACT
Top
 Abstract
Introduction
 Disclosure of Potential...
 Acknowledgments
 References
 
Mesenchymal stem cells, or multipotent mesenchymal stromal cells (MSC), isolated from various adult tissue sources have the capacities to self-renew and to differentiate into multiple lineages. Both of these processes are tightly regulated by genetic and epigenetic mechanisms. Emerging evidence indicates that the class of single-stranded noncoding RNAs known as microRNAs also plays a critical role in this process. First described in nematodes and plants, microRNAs have been shown to modulate major regulatory mechanisms in eukaryotic cells involved in a broad array of cellular functions. Studies with various types of embryonic as well as adult stem cells indicate an intricate network of microRNAs regulating key transcription factors and other genes, which in turn determine cell fate. In addition, expression of unique microRNAs in specific cell types serves as a useful diagnostic marker to define a particular cell type. MicroRNAs are also found to be regulated by extracellular signaling pathways that are important for differentiation into specific tissues, suggesting that they play a role in specifying tissue identity. In this review, we describe the importance of microRNAs in stem cells, focusing on our current understanding of microRNAs in MSC and their derivatives.

Disclosure of potential conflicts of interest is found at the end of this article.


   INTRODUCTION
Top
 Abstract
 Introduction
Disclosure of Potential...
 Acknowledgments
 References
 
Global gene expression analysis of stem cells is one method to produce a clear understanding of the variations in biological conditions across different types of stem cells. A similar approach has begun to help us identify and understand the epigenetic signatures of stem cells. Several microarray-based techniques for the systematic analysis of epigenetic changes have become available, allowing broad-scale analysis on a new level of transcriptional and translational regulation, particularly for studying the regulation of microRNAs and their predicted mRNA targets. Understanding the importance of microRNAs in multipotent mesenchymal stromal cell (MSC) differentiation will require knowledge of the mechanisms explaining mRNA targeting, knowledge of the mechanisms underlying microRNA regulation, and an accurate assessment of microRNA-mRNA targeting.

The discoveries of artificial silencer RNAs and genomic-encoded microRNAs have led to an explosion in the study of small noncoding RNAs [1–7]. Various types of small, noncoding RNAs exist as modulators of gene expression, affecting transcription rate, mRNA stability, and mRNA translation into functional proteins. What was once believed to be a specialized function occurring only in plants [8, 9] or worms [1, 10] has now been shown to control regulatory pathways in several mammalian biological processes, such as cell growth and apoptosis [11–14], viral infection [15–19], neural function [20–23], and stem cell function [21, 24–37]. Here, we outline the issues related to microRNA expression profiling in MSC as an example of how these studies are useful for classifying differentiating cells and, potentially, understanding molecular networks active during differentiation.

MSC
The plastic-adherent, fibroblast-like cells isolated from bone marrow with osteogenic potential were first described by Friedenstein [38] and subsequently described by several studies [38–44]. Since then, the ability of these cells to differentiate into multiple connective tissue cell types has been reported [43–47], with the term mesenchymal stem cell first proposed by Caplan [48]. MSC have been isolated from multiple adult tissue sources, such as cord blood, placenta, adipose and dermal tissues, synovial fluid, deciduous teeth, and amniotic fluid [49–54]. This broad distribution of sources combined with their ability to differentiate into multiple mesenchymal phenotypes, such as bone, cartilage, tendon, and adipose tissue, has led them to be evaluated as potential therapeutic candidates for several disease and degenerative applications [55–61]. The varied sources and methodologies used for MSC isolation have also largely led to ambiguities resulting in the lack of an universally accepted criteria to define these cells. To address this issue, the International Society of Cellular Therapy has recently designated these cells as MSC [62] based on adherence to plastic, expression of specific surface antigen, and differentiation potential.

Despite this level of interest, a clear understanding of the factors involved in the growth regulation of MSC remains rudimentary. Several reports have described that only one-third of the expanded MSC colonies truly retain trilineage differentiation potential, that is, the ability to differentiate into adipocytes, osteocytes, and chondrocytes, with the remaining cells in MSC cultures thought to be either having only bi- or monolineage or to be committed progenitor cells [46, 63]. This could largely be due to clonal expansion, which in general could alter the phenotype of most stem cell types. Global gene expression analysis has revealed that MSC differentiation into specific mature cell types is a temporally controlled and regulated process involving the activities of various transcription factors, growth factors, and signaling pathways [64, 65]. However, microRNAs would be expected to regulate mRNA translation and/or stability, so perhaps the regulation of microRNA expression patterns represents a novel regulatory network in MSC.

What Are MicroRNAs?
MicroRNAs are single-stranded RNAs of 19–23 nucleotides that derive from a ~70-nucleotide precursor and are found in a wide variety of organisms, from plants to insects to humans. Estimates suggest that there are approximately 120 microRNA genes in each invertebrate species and at least 250 genes in mammals, with some groups predicting from 1,000 per genome [66–68] to as many as 10,000 [69]. After transcription, microRNA precursors are cleaved in the nucleus by Drosha [70], exported to cytoplasm by exportin [71, 72], and inserted into an RNA-induced silencing complex (RISC) after additional cleavage by Dicer [73]. Evidence for the requirement of the processing of microRNA in stem cell function and differentiation comes from studies of the Drosha complex partners Loquacious (homolog of human TAR (HIV-1) RNA binding protein 2), which is required for germ-line stem cell maintenance [74], and DGCR8 [75], which is required for embryonic stem cell self-renewal [37]. Similarly, Dicer knockouts exhibit defects in stem cell differentiation [25]. Clearly, microRNAs underlie key differentiation mechanisms.

Relatively little is known of the regulation of microRNA expression, although a few microRNA transcriptional control sequences have been described [14, 76–78]. Interestingly, microRNAs are often clustered in the genome, and two or more closely related microRNA precursors have been detected in polycistronic precursors [35, 79–81]. Other microRNAs are encoded within introns of other genes [82, 83], and some microRNAs are edited [84, 85], producing a dizzying mix of coexpression, predicted transcriptional control, and post-transcriptional modifications. There is much to learn about the regulatory mechanisms controlling microRNA expression.

MicroRNA Regulation Mechanisms and Target Prediction
MicroRNAs are known to negatively regulate gene expression. This could be achieved by direct mRNA cleavage [86–90], mRNA decay by deadenylation [91, 92], or translational repression [93]. Complexes containing microRNAs and those of the RISC involved in RNA interference are similar. RNA silencing, using a perfectly complementary small interfering RNA, normally cleaves an mRNA target. In animals, microRNAs usually have imperfect complementarity to a 3'-untranslated region (UTR) element in their mRNA targets and thus are primarily believed to attenuate translation of the target mRNA. Many studies suggest a continuum of RISC behaviors using similar components, since endogenous microRNAs with perfect complementarity can cleave mRNAs [94] and exogenously introduced siRNAs can attenuate translation of mRNAs having imperfect complementarity [95, 96].

Few target genes that are regulated by microRNAs are currently documented, but the ones identified have important roles in apoptosis, homeobox regulation, development [30, 97–101], cell growth and apoptosis [13, 14], viral infection [15, 19], and human cancer [81, 102–104]. This type of gene control represents a new regulatory mechanism and is predicted to affect many crucial cellular processes, including developmental programs.

An important challenge for incorporating microRNA regulation into gene expression mechanisms is the difficulty in predicting or verifying mRNA targets of specific microRNAs. Efforts to map microRNA binding sites specifically in the transcriptome in animal cells rely primarily on computational predictions. However, it has been suggested that microRNAs regulate gene expression of more than 30% of protein-coding genes in humans [105]. One clue to decoding this mystery is the conservation of microRNAs and mRNA target sequences across species. For example, more than one-third of the Caenorhabditis elegans microRNAs have easily recognizable homologs in humans [106]. Sequence conservation argues for conserved function throughout evolution. A number of prominent prediction algorithms have been developed [66, 69, 107–110], in most cases based on this observed conservation of complementary "seed" regions conserved across species. A recent review considers these methods and proposes an approach for applying these algorithms [111]. A few reports extend these predictions to collect supporting evidence for specific biochemical targeting interactions [112], microRNA-mRNA presence in polysomes [113], or RNA-protein complex composition [114, 115]. One direct method for validating targets uses a luciferase reporter plasmid with a replaceable 3'-UTR [13]. By cloning a 3'-UTR from the suspected target mRNA into this reporter and cotransfecting it with microRNA precursors, inhibition of luciferase production can be detected. In general, many of the computationally predicted targeting interactions are not consistent between algorithms, and relatively little direct experimental evidence substantiates these predictions. In our experience, computed target lists have a high rate of false positives (unpublished results).

MicroRNA Analysis Methods
Detection of microRNAs in tissues is possible with a variety of techniques. Several microarrays have been described [102, 103, 116–127] and many commercial sources of microRNA arrays can be found (Table 1). Most of these are based on the publicly available list of microRNAs found in the miRBase database maintained at the Sanger Institute (http://microrna.sanger.ac.uk) [128]. With most of the array-based methods, it is difficult to claim resolution of specific microRNAs within 1 nucleotide (nt) of the probe sequence since the melting temperatures are quite low compared with the longer probes often used for mRNA detection. However, higher specificity can be achieved using direct labeling of microRNAs to obtain RNA:DNA hybridization (NCode) or using locked nucleic acid oligo probes (MirCURY). Validation of microarray results originally depended on Northern blots but can also use quantitative real-time polymerase chain reaction (qPCR). In general, qPCR techniques yield the greatest dynamic range, improved specificity, and high sensitivity. In one case, qPCR allowed detection of microRNAs from single cultured neurons or even laser-captured somatodendritic compartments [129]. Other detection techniques include enzyme-linked immunosorbent assay-like or bead-anchored hybridizations using probes and labeling similar to array methods to perform high-throughput analyses [130]. A promising technology for detection and quantification of both known and novel microRNAs is massively parallel signature sequencing (MPSS). For example, Lu et al. [131] sequenced 721,044 17-nt cDNAs prepared from Arabidopsis inflorescence, of which 67,528 were unique. Of these, 77% matched genome sequences, exceeding by more than 10-fold the previously identified Arabidopsis microRNA library. However, later studies described the importance of filtering these results for genomic hairpin structures and other types of small RNA, reducing the number of predicted or novel structures [132, 133]. MPSS revealed novel microRNAs in Marek's disease virus that contribute to pathogenesis [134]. MPSS also revealed 447 new microRNAs in chimpanzee and human brains [135]. Furthermore, MPSS of mRNAs found ~25% uncharacterized or novel genes expressed in human embryonic stem cells (hESC) [42]. As MPSS becomes more widely available and the costs per sample come down, it is possible that direct tag sequencing may become an important technique in the study of microRNAs.


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  		Table 1. Commercial sources of microRNA microarrays

 
MicroRNAs in Embryonic and Adult Stem Cells
Several studies have identified populations of microRNAs that are associated with specific stem cell types or those that are regulated during stem cell differentiation (Table 2). MicroRNA has been shown to mediate regulation of stem cell division [27], as well as differentiation in adipocyte [116], cardiac [136], neural [24, 137], and hematopoietic lineages [88, 138]. For example, the involvement of miR-181 in differentiation of the hematopoietic lineage is well-established [88]. miR-181a is expressed at relatively low levels in Lin– bone marrow progenitor cells compared with B-lymphocytes and is expressed in high levels in thymus and primary lymphoid organs. Ectopic expression of miR-181a in hematopoietic stem cells leads to an increased fraction of B-cell lineage both in vitro and in vivo, suggesting it to be a positive regulator for B-cell differentiation [88]. MicroRNAs are also found to be highly expressed in the adult brain, suggesting their involvement in neuronal function and plasticity [139]. miR-124 and miR-128, both highly expressed in adult brain, are also expressed in neurons, whereas miR-23 is restricted to astrocytes. The induction of microRNA expression during neural differentiation of embryonic stem cells further suggests its importance in neural development [29].


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  		Table 2. Studies of miRNA in stem cells

 
The miR-15a-miR-16 cluster resides in a region of human chromosome 13 thought to harbor a tumor suppressor gene [102, 140] and also to target Bcl2, potentially modulating apoptosis [98]. MicroRNAs have also been found to control G1/S checkpoint bypass in Drosophila stem cells [27], demonstrating their intimate role in stem cell division.

A unique set of microRNAs is reported to be expressed in mouse embryonic stem cells (ESC) that changes with differentiation during differentiation via embryoid body (EB) formation [25, 26, 35, 141, 142]. Northern blot and cloning analysis identified several microRNAs in human ESC, several of which were identical to microRNAs previously reported in mouse ESC [143]. We recently reported that several microRNAs are highly expressed across multiple hESC lines [144]. Furthermore, as these cells differentiate, the microRNA profiles change significantly. Combining the profiling of microRNAs and mRNAs, correlation of gene and microRNA expression predicts regulatory interaction of microRNA and mRNAs involved in both maintenance of pluripotency and differentiation [145]. Based on this, microRNA expression pattern in human embryonic stem cells is included in the panel of tests suggested for qualification of human embryonic stem cells [146].

Consistent with the observation for individual microRNAs, mouse embryonic stem (ES) knockout cells lacking Dicer [25], required for cleavage of microRNA precursors, or DGCR8 [37], an RNA-binding protein essential for processing microRNAs, exhibit a failure to undergo differentiation and completely prevent mouse ESC from differentiating into embryoid bodies, suggesting that microRNAs are required to inhibit ES self-renewal. Furthermore, knockout mice lacking Argonaute2, the catalytic component of the RISC, exhibited severe defects in neural development, including the failure to close neural tube [147]. Collectively, these studies implicate the importance of microRNAs as key regulators during the process of stem cell maintenance and differentiation.

A unique set of microRNAs is expressed in embryonic stem cells (Table 3). Using Northern blot analysis, cloning, or array methods, a set of microRNAs specific to pluripotent cell types, such as mouse ES cells [35], mouse or human embryonic carcinoma cells [22], or human ESC [32, 143–145], has been identified. Although these studies could not yet ascribe regulatory functions to these microRNA populations, the unique presence of these populations in stem cells and their disappearance during differentiation suggest roles in maintaining "stemness" by suppressing pluripotency and/or restricting cell differentiation. In one example, miR-134 was found to be enriched after retinoic acid treatment of mouse ES cells, and miR-134 reduces expression of Nanog and LRH1 [30], enhancing differentiation to specific lineages.


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  		Table 3. MicroRNAs associated with embryonic stem cells

 
MicroRNA Expression in MSC and Derivatives
Compared with these examples examining microRNAs in ESC, relatively few studies have identified microRNA expression patterns in differentiating MSC or specific pathways that could be targeted (Table 4). In one case, miR-103 and miR-107 were found to be encoded within an intron of the PANK gene in a pattern that is conserved among a large array of organisms [148]. Both microRNAs (the high degree of sequence homology makes them virtually indistinguishable) are predicted to target a large number of genes involved in acetyl-CoA and lipid metabolism. Another study found that the modulation of a single microRNA could promote the formation of adipocytes from precursor cells [116]. This differential targeting was shown to be mediated by the translational regulation of ERK5, an intermediate in the leukemia inhibitory factor signaling pathway [116]. ERK5 is also known to mediate a neuronal survival response following retrograde signaling of neurotrophins [149, 150]. A third example found that miR-140 was expressed during cartilage development and that miR-140 may act by inhibiting HDAC4, a likely corepressor of Runx2 [151]. These initial examples show that, as was found in studies of ESC, microRNAs are likely to be mediators of key pathways during MSC differentiation.


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  		Table 4. MicroRNAs associated with MSCs

 
We have recently begun mapping microRNA changes during MSC differentiation using microarrays and qPCR validation (Goff et al., unpublished). In general, we observed a great deal of variability between individual donors, making generalizations difficult. For example, MSC prepared from two different donors had a correlation coefficient of 0.912 over all detected mRNAs, and MSC from the same donor prepared from two subsequent passages had a correlation of 0.804. However, using pooled samples of MSC cultures, we identified 27 human microRNAs as regulated during MSC differentiation into adipocytes, osteocytes, or chondrocytes. Expression patterns could be clustered to highlight specific microRNAs with restricted expression patterns, confirming previously described results (e.g., miR-143 and miR-145, enriched in adipocytes) as well as identifying novel markers (e.g., miR-638 and miR-663 in chondrocytes). We found that several of the regulated microRNAs were attributable to changes upon osteocyte differentiation. Standard gene expression analysis found that osteocyte differentiation included pathway signatures for platelet-derived growth factor (PDGF) stimulation, as was reported by Ng et al., unpublished. To determine whether the class of osteocyte-specific microRNAs could by regulated by PDGF-stimulated transcriptional mechanisms, we bioinformatically associated PDGF-responsive transcription factor position weight matrices with genomic sequences upstream of regulated microRNAs. Our results predict that a significant number of PDGF-responsive transcription factor sites are found upstream of regulated microRNAs, compared with expressed but unregulated microRNAs (Fig. 1). This prediction was confirmed by treating differentiating MSC with AG-370, a tyrphostin inhibitor of the PDGF signaling pathway. MicroRNAs ranking highly on a confidence list of predicted PDGF regulation targets were generally also inhibited by the addition of AG-370 during osteogenic differentiation (examples listed in Table 4). Taken together, these results identify an osteogenic class of microRNAs that are regulated by growth factor signaling during differentiation, demonstrating the regulation of specific microRNAs during MSC differentiation.


Figure 1
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  		Figure 1. Model of platelet-derived growth factor-regulated microRNAs modulating translation of targeted mRNAs. Abbreviations: PDGFR, platelet-derived growth factor receptor; RISC, RNA-induced silencing complex; TF-X, transcription factor X.

 
Predicted MicroRNA-Target Interactions
The importance of microRNA regulation in MSC differentiation is demonstrated in the increasing evidence for specific microRNAs participating in known pathways through mRNA target interactions. There are fewer known examples for bone and connective tissue differentiation, but we should expect to find target pathways as these microRNAs are described.

Recently, using a concept similar to the "biclustering" of gene expression data [152], we carried out correlation of an mRNA to each microRNA expression level in multiple hESC lines and their differentiated samples organized as separate groups [145]. A similar approach was also used to study the changes in microRNA expression during murine embryonic stem cell differentiation [32]. Such a cross-correlation clustering provides interpretable lists of microRNAs and associated mRNAs that may be hypothesized to interact through specific mechanisms, providing impetus toward recognizing microRNAs involved in controlling stem cell fate.

Future Directions
As the complexity of the regulatory network in differentiating stem cells begins to become known, identification of regulated microRNAs and their interactions with transcriptional networks and, ultimately, cellular regulatory systems, becomes valuable. The organization of the hierarchical order of all types of stem cells based on their pluripotency and linkage of their functional characteristics to genetic and epigenetic regulatory elements provide a novel means to understand and, potentially, manipulate cell fate. With the ultimate goal of using microRNAs to modulate differentiation of stem cells as potential therapeutic agents, we expect to produce a clearer understanding of microRNAs in specific cellular pathways such as development, proliferation, stem cell renewal, and differentiation and in diseases such as cancer.


   DISCLOSURE OF POTENTIAL CONFLICTS OF INTEREST
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 Abstract
 Introduction
 Disclosure of Potential...
Acknowledgments
 References
 
U.L. owns stock in and has a financial interest in Invitrogen.


   ACKNOWLEDGMENTS
Top
 Abstract
 Introduction
 Disclosure of Potential...
 Acknowledgments
References
 
R.P.H. is supported by the NIH, the New Jersey Commission on Spinal Cord Research, the New Jersey Commission on Science & Technology, and Invitrogen, Inc.


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 Introduction
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