Regulation of the IGFBP-5 and MMP-13 genes by the microRNAs miR-140 and miR-27a in human osteoarthritic chondrocytes

<p>Abstract</p> <p>Background</p> <p>MMP-13 and IGFBP-5 are important factors involved in osteoarthritis (OA). We investigated whether two highly predicted microRNAs (miRNAs), miR-140 and miR-27a, regulate these two genes in human OA chondrocytes.</p> <p>Methods</p> <p>Gene expression was determined by real-time PCR. The effect of each miRNA on IGFBP-5 and MMP-13 expression/production was evaluated by transiently transfecting their precursors (pre-miRNAs) and inhibitors (anti-miRNAs) into human OA chondrocytes. Modulation of IGFBP-5, miR-140 and miR-27a expression was determined upon treatment of OA chondrocytes with cytokines and growth factors.</p> <p>Results</p> <p>IGFBP-5 was expressed in human chondrocytes with its level significantly lower (p < 0.04) in OA. Five computational algorithms identified miR-140 and miR-27a as possible regulators of MMP-13 and IGFBP-5 expression. Data showed that both miRNAs were expressed in chondrocytes. There was a significant reduction (77%, p < 0.01) in miR-140 expression in OA compared to the normal chondrocytes, whereas miR-27a expression was only slightly decreased (23%). Transfection with pre-miR-140 significantly decreased (p = 0.0002) and with anti-miR-140 significantly increased (p = 0.05) IGFBP-5 expression at 24 hours, while pre-miR-27a did not affect either MMP-13 or IGFBP-5. Treatment with anti-miR-27a, but not with anti-miR-140, significantly increased the expression of both MMP-13 (p < 0.05) and IGFBP-5 (p < 0.01) after 72 hours of incubation. MMP-13 and IGFBP-5 protein production followed the same pattern as their expression profile. These data suggest that IGFBP-5 is a direct target of miR-140, whereas miR-27a down-regulates, likely indirectly, both MMP-13 and IGFBP-5.</p> <p>Conclusion</p> <p>This study is the first to show the regulation of these miRNAs in human OA chondrocytes. Their effect on two genes involved in OA pathophysiology adds another level of complexity to gene regulation, which could open up novel avenues in OA therapeutic strategies.</p

The Cardiac Transcription Network Modulated by Gata4, Mef2a, Nkx2.5, Srf, Histone Modifications, and MicroRNAs

The transcriptome, as the pool of all transcribed elements in a given cell, is regulated by the interaction between different molecular levels, involving epigenetic, transcriptional, and post-transcriptional mechanisms. However, many previous studies investigated each of these levels individually, and little is known about their interdependency. We present a systems biology study integrating mRNA profiles with DNA–binding events of key cardiac transcription factors (Gata4, Mef2a, Nkx2.5, and Srf), activating histone modifications (H3ac, H4ac, H3K4me2, and H3K4me3), and microRNA profiles obtained in wild-type and RNAi–mediated knockdown. Finally, we confirmed conclusions primarily obtained in cardiomyocyte cell culture in a time-course of cardiac maturation in mouse around birth. We provide insights into the combinatorial regulation by cardiac transcription factors and show that they can partially compensate each other's function. Genes regulated by multiple transcription factors are less likely differentially expressed in RNAi knockdown of one respective factor. In addition to the analysis of the individual transcription factors, we found that histone 3 acetylation correlates with Srf- and Gata4-dependent gene expression and is complementarily reduced in cardiac Srf knockdown. Further, we found that altered microRNA expression in Srf knockdown potentially explains up to 45% of indirect mRNA targets. Considering all three levels of regulation, we present an Srf-centered transcription network providing on a single-gene level insights into the regulatory circuits establishing respective mRNA profiles. In summary, we show the combinatorial contribution of four DNA–binding transcription factors in regulating the cardiac transcriptome and provide evidence that histone modifications and microRNAs modulate their functional consequence. This opens a new perspective to understand heart development and the complexity cardiovascular disorders

Crisp and fuzzy k-means clustering algorithms for multivariate functional data

Cluster analysis, Functional data analysis, Registration,