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.
Highlights
The family of RNA-binding proteins (RBP) functions as a crucial regulator of multiple biological processes and diseases
We screened for RBP-involvement with the disease using 264 annotated RBPs (GO:0003729 = mRNA binding; Supplementary Table 1)
We have demonstrated the feasibility of computational methodology to unravel understudied processes and potential pharmacological targets in lung fibrosis
Summary
The family of RNA-binding proteins (RBP) functions as a crucial regulator of multiple biological processes and diseases. 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. 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 RBPs Quaking (QKI) are interesting targets, as rescuing QKI expression has beneficial effects in doxorubicin-induced cardiotoxicity[5] It is unknown if QKI is a therapeutically relevant target in lung fibrosis. To explore the possibility of inhibiting miRs to restore QKI expression, we have applied a practical in silico screening approach using multi-sources data information and integrative molecular network bioinformatics. We have performed in vitro experiments modelling QKI interactions to confirm the accuracy of the computational predictions
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