Reconstruction of the miR-506-Quaking axis in Idiopathic Pulmonary Fibrosis using integrative multi-source bioinformatics

• Main Authors: Stevan D. Stojanović, Maximilian Fuchs, Chunguang Liang, Kevin Schmidt, Ke Xiao, Annette Just, Angelika Pfanne, Andreas Pich, Gregor Warnecke, Peter Braubach, Christina Petzold, Danny Jonigk, Jörg H. W. Distler, Jan Fiedler, Thomas Thum, Meik Kunz
• Format: Article
• Language: English
• Published: Nature Publishing Group 2021-06-01
• Series: Scientific Reports
• Online Access: https://doi.org/10.1038/s41598-021-89531-7

Abstract The family of RNA-binding proteins (RBP) functions as a crucial regulator of multiple biological processes and diseases. However, RBP function in the clinical setting of idiopathic pulmonary fibrosis (IPF) is still unknown. We developed a practical in silico screening approach for the characterization of RBPs using multi-sources data information and comparative molecular network bioinformatics followed by wet-lab validation studies. Data mining of bulk RNA-Sequencing data of tissues of patients with IPF identified Quaking (QKI) as a significant downregulated RBP. Cell-type specific expression was confirmed by single-cell RNA-Sequencing analysis of IPF patient data. We systematically analyzed the molecular interaction network around QKI and its functional interplay with microRNAs (miRs) in human lung fibroblasts and discovered a novel regulatory miR-506-QKI axis contributing to the pathogenesis of IPF. The in silico results were validated by in-house experiments applying model systems of miR and lung biology. This study supports an understanding of the intrinsic molecular mechanisms of IPF regulated by the miR-506-QKI axis. Initially applied to human lung disease, the herein presented integrative in silico data mining approach can be adapted to other disease entities, underlining its practical relevance in RBP research.