Integrative Bioinformatic Analyses of Global Transcriptome Data Decipher Novel Molecular Insights into Cardiac Anti-Fibrotic Therapies

Abstract

<jats:p>Integrative bioinformatics is an emerging field in the big data era, offering a steadily increasing number of algorithms and analysis tools. However, for researchers in experimental life sciences it is often difficult to follow and properly apply the bioinformatical methods in order to unravel the complexity and systemic effects of omics data. Here, we present an integrative bioinformatics pipeline to decipher crucial biological insights from global transcriptome profiling data to validate innovative therapeutics. It is available as a web application for an interactive and simplified analysis without the need for programming skills or deep bioinformatics background. The approach was applied to an ex vivo cardiac model treated with natural anti-fibrotic compounds and we obtained new mechanistic insights into their anti-fibrotic action and molecular interplay with miRNAs in cardiac fibrosis. Several gene pathways associated with proliferation, extracellular matrix processes and wound healing were altered, and we could identify micro (mi) RNA-21-5p and miRNA-223-3p as key molecular components related to the anti-fibrotic treatment. Importantly, our pipeline is not restricted to a specific cell type or disease and can be broadly applied to better understand the unprecedented level of complexity in big data research.</jats:p>

The Roles of Immune Cells in the Pathogenesis of Fibrosis

“…Preclinical studies in fibrotic animal models have provided important information on novel immune-based therapeutic strategies by targeting different immune cells. Moreover, the molecular insights into fibrogenesis have suggested clinical therapeutic potential by targeting key molecular components, including PI3K/mTOR and JAK-STAT pathways [ 183 , 184 , 185 , 186 ]. Future controlled clinical trials are essential to evaluate the safety and efficacy of potential therapies in patients with fibrotic diseases.…”

Approaches for the integration of big data in translational medicine: single‐cell and computational methods

“…It can be used to better comprehend the unique levels of complexity in big data studies in different cell types or diseases. 199 New translational approaches have been applied to improve diagnosis and treatment of patients suffering from interstitial lung fibrosis. These approaches have concentrated on surfactant-related proteins, 200,201 telomere pathway-associated gene variants, 202,203 and other genetic variants that have recently been recognized by linkage and genomewide association studies.…”

“…It is publicly available at the URL https://github.com/miracum/clearly-tRomics. It can be used to better comprehend the unique levels of complexity in big data studies in different cell types or diseases 199 …”

A practical guide for investigating cardiac physiology using living myocardial slices

“…Novel integrative bioinformatics pipelines are now being developed to decipher essential biological insights from global transcriptome profiling data. Fuchs et al recently applied this concept to LMS treated with anti-fibrotic compounds, resulting in the identification of two microRNAs linked to fibroblast signaling via the analysis of altered gene sets associated with fibroblast proliferation, ECM remodeling and wound healing [ 10 ] With regard to the protein content of MS, specific proteins can be detected and extracted using traditional techniques, including Western blot [ 28 , 36 ]. More detailed studies of the proteomic composition of LMS have been conducted.…”