Abstract
We previous reported that miR-27a regulates lipid metabolism and cell proliferation during hepatic stellate cells (HSCs) activation. To further explore the biological function and underlying mechanisms of miR-27a in HSCs, global protein expression affected by overexpression of miR-27a in HSCs was analyzed by a cleavable isotope-coded affinity tags (cICAT) based comparative proteomic approach. In the present study, 1267 non-redundant proteins were identified with unique accession numbers (score ≥1.3, i.e. confidence ≥95%), among which 1171 were quantified and 149 proteins (12.72%) were differentially expressed with a differential expression ratio of 1.5. We found that up-regulated proteins by miR-27a mainly participate in cell proliferation and myogenesis, while down-regulated proteins were the key enzymes involved in de novo lipid synthesis. The expression of a group of six miR-27a regulated proteins was validated and the function of one miR-27a regulated protein was further validated. The results not only delineated the underlying mechanism of miR-27a in modulating fat metabolism and cell proliferation, but also revealed a novel role of miR-27a in promoting myogenic tans-differentiation during HSCs activation. This study also exemplified proteomics strategy as a powerful tool for the functional study of miRNA.
Highlights
MicroRNAs regulate gene expression post-transcriptionally by binding primarily to the 39untranslated region (39UTR) of their target mRNAs, resulting in mRNA destabilization or translational repression[1]
Several bioinformatics methods have been developed for miRNA target prediction, including TargetScan, miRanda, TarBase, PicTar et al since the mechanism of miRNA target recognition is still not fully understood, target gene prediction is not accurate and sometimes over predict [4]
We have previously reported that miR-27a,b suppresses fat accumulation and promotes cell proliferation during hepatic stellate cells (HSCs) activation [8]
Summary
MicroRNAs (miRNAs) regulate gene expression post-transcriptionally by binding primarily to the 39untranslated region (39UTR) of their target mRNAs, resulting in mRNA destabilization or translational repression[1]. Genes encoding 2042 mature human miRNAs have so far been identified (miRBase v.19) [2] and miRNAs are predicted to regulate the expression of up to 60% of human protein-encoding genes [3]. The best way to understand the biological function of a miRNA is to identify the genes that it regulates. Several bioinformatics methods have been developed for miRNA target prediction, including TargetScan De) et al since the mechanism of miRNA target recognition is still not fully understood, target gene prediction is not accurate and sometimes over predict [4]. Comprehensive understanding of the phenotypic effects of miRNAs at the cellular level is currently difficult
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