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Identification of novel targets for miR-29a using miRNA proteomics.

ABSTRACT: MicroRNAs (miRNAs) are short regulatory RNA molecules that interfere with the expression of target mRNA by binding to complementary sequences. Currently, the most common method for identification of targets of miRNAs is computational prediction based on free energy change calculations, target site accessibility and conservation. Such algorithms predict hundreds of targets for each miRNA, necessitating tedious experimentation to identify the few functional targets. Here we explore the utility of miRNA-proteomics as an approach to identifying functional miRNA targets. We used Stable Isotope Labeling by amino acids in cell culture (SILAC) based proteomics to detect differences in protein expression induced by the over-expression of miR-34a and miR-29a. Over-expression of miR-29a, a miRNA expressed in the brain and in cells of the blood lineage, resulted in the differential expression of a set of proteins. Gene Ontology based classification showed that a significant sub-set of these targets, including Voltage Dependent Anion Channel 1 and 2 (VDAC1 and VDAC2) and ATP synthetase, were mitochondrial proteins involved in apoptosis. Using reporter assays, we established that miR-29a targets the 3' Untranslated Regions (3' UTR) of VDAC1 and VDAC2. However, due to the limited number of proteins identified using this approach and the inability to differentiate between primary and secondary effects we conclude that miRNA-proteomics is of limited utility as a high-throughput alternative for sensitive and unbiased miRNA target identification. However, this approach was valuable for rapid assessment of the impact of the miRNAs on the cellular proteome and its biological role in apoptosis.

SUBMITTER: Bargaje R

PROVIDER: S-EPMC3428309 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Identification of novel targets for miR-29a using miRNA proteomics.

Bargaje Rhishikesh R Gupta Shivani S Sarkeshik Ali A Park Robin R Xu Tao T Sarkar Maharnob M Halimani Mahantappa M Roy Soumya Sinha SS Yates John J Pillai Beena B

PloS one 20120827 8

MicroRNAs (miRNAs) are short regulatory RNA molecules that interfere with the expression of target mRNA by binding to complementary sequences. Currently, the most common method for identification of targets of miRNAs is computational prediction based on free energy change calculations, target site accessibility and conservation. Such algorithms predict hundreds of targets for each miRNA, necessitating tedious experimentation to identify the few functional targets. Here we explore the utility of ...[more]

PMID: 22952654

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Project description:BackgroundKeloid has brought great trouble to people and currently has no uniformly successful treatment. It is urgent to find new targets to effectively prevent the progress of keloid. The current research mainly identifies the differentially expressed genes (DEGs) in keloid through high-throughput sequencing technology and bioinformatics analysis technology, to screen new therapeutic targets and potential biomarkers. However, due to the different samples, different control groups, and small sample sizes, the sequencing results obtained from different studies are quite different and lack reliability. It is necessary to analyze the existing datasets in a reasonable way.MethodsDatasets about keloid were filtered in Gene Expression Omnibus (GEO) and ArrayExpress databases according to the inclusion and exclusion criteria. The discovery datasets were used for summarizing significant DEGs, and the validation datasets were to validate the mRNA and miRNA expression levels. The Encyclopedia of RNA Interactomes (ENCORI) online platform was used to predict the interactions between miRNAs and their target mRNAs. Protein-protein interaction network (PPI network) analysis and functional enrichment analysis were conducted. miRNA-mRNA network was established by Cytoscape software and verified in keloid tissue (n = 8) by RT-qPCR. miR-29a-3p mimic and inhibitor were transfected into keloid fibroblasts (KFs) to preliminary verify its targets, the prognostic value of which was estimated by the receiver operating characteristic (ROC) curve.ResultsA total of 6 datasets involving 20 patients were included. 15 miRNAs and 12 target mRNAs were identified as potential biomarkers for keloid patients. The RT-qPCR results showed that miR-29a-3p, miR-92a-3p, and miR-143-3p were downregulated, and all their target mRNAs were upregulated in keloid tissue (P < 0.05). The expression of COL1A1, COL1A2, COL3A1, COL5A1, and COL5A2 decreased when miR-29a-3p was overexpressed but increased when miR-29a-3p was knocked down (P < 0.05). And these genes had a good performance in the diagnosis of keloid, especially when using keloid nonlesional skin or normal scar tissues as controls.ConclusionThe miRNA-mRNA network, especially miR-29a-3p and its targets, may provide insights into the underlying pathogenesis of keloid and serve as potential biomarkers for keloid treatment.

Dataset Information

Identification of novel targets for miR-29a using miRNA proteomics.

Publications

Identification of novel targets for miR-29a using miRNA proteomics.

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