Identification and Functional Analysis of Novel miRNA Target Genes That Control Mesenchymal Stem Cell Function
Authors: Roubelakis Maria , Zagoura Dimitra , Trohatou Ourania , Zotos Pantelis , Bitsika Vassiliki , Kossida Sophia , Pappa Kalliopi I , Antsaklis Aristidis , Anagnou Nicholas P. 
Published: April 2020

Abstract
Human mesenchymal stem cells (hMSCs) constitute a population of multipotent stem cells, easily expanded in culture and able to differentiate into many lineages. These features render MSCs a very attractive tool for developing new strategies for clinical applications based on cell therapy. So far, the most common sources of MSCs have been the bone marrow (BM) and the umbilical cord blood (UCB). Our group has recently isolated MSCs from a novel source, such as the amniotic fluid (AF) and characterized them based on their
phenotype, pluripotency, proliferation rate, differentiation potential and the generated for the first time proteomic profile (Stem Cells Dev.16:931, 2007).
To further decipher the molecular mechanisms as they relate to the MSCs from the other two sources, in the present study we investigated the comparative post-transcriptional regulation mechanisms of MSCs from the three sources at the miRNA level. miRNAs are single-stranded RNA molecules 20–23 nt long, regulating gene expression by interacting with target mRNAs at specific sites of their 3′ UTR to induce either a cleavage of the message or inhibit its translation. More specifically, the objectives of the study were
the detection of miRNA populations in AF, BM and UCB-MSCs, the validation of their expression levels using Real Time PCR, the generation of a new algorithm for the in silico detection of miRNA target-genes and the validation of miRNA binding on specific targets predicted by the algorithm application.
Initially we identified 67 different species of miRNAs expressed in all three types of MSCs but at different levels in each source, using miRNA arrays (miRCURY™ LNA αrray v.8.1). We then further established and compared the miRNA profiles among the three sources. The data revealed a characteristic pattern of a set of key miRNAs, unique for each type of MSCs. The results were further validated for the characteristic expression levels of specific miRNAs in AF-MSCs, such as miR-21, miR-221, miR-222, miR-572, miR-210 and let-7d, employing Real Time PCR. For predicting mRNA targets of specific miRNAs, we developed a novel stand-alone application, designated GOmir, consisting of two separate tools: JTarget and TAGGO. JTarget integrates miRNA target prediction and functional analysis, by combining the predicted target genes from TargetScan, miRanda, RNAhybrid and PicTar computational tools and by providing a full gene description and functional analysis for each target gene. On the other hand, TAGGO application is designed to automatically group gene ontology annotations, taking advantage of the Gene Ontology (GO), in order to extract the main attributes of sets of proteins. GOmir (by using up to four different databases) introduces, for the first time, miRNA predicted targets accompanied by
full gene description, functional analysis and detailed gene ontology clustering.
From the systematic miRNA array analysis, we detected higher expression levels of miR-21 and miR-100 in AF-MSCs compared to BM and UCB-MSCs. According to GOmir prediction, miR-21 and miR-100, are considered responsible for the regulation of key stem cell genes such as SOX-2 and FZD8, respectively, thus implying an important role on the self renewal of stem cells. To evaluate the predictive capacity of GOmir and the role of miR-21 in AF-MSCs in more detail, we performed functional studies using miR-21 antagonists and cloning strategies targeting for specific SOX-2 3′ UTR mRNA binding sites. These studies resulted in upregulation of the SOX-2 expression, providing the proof of principle for the validity of this combined approach. Thus, our data derived from this new strategy, are expected to clarify systematically the post-transcriptional regulation of MSCs from these different sources.