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采用整合多源生物信息学方法重建特发性肺纤维化中的 miR-506-Quaking 轴。

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

机构信息

Institute of Molecular and Translational Therapeutic Strategies (IMTTS), Hannover Medical School, Hannover, Germany.

Chair of Medical Informatics, Friedrich-Alexander University (FAU) of Erlangen-Nürnberg, Erlangen, Germany.

出版信息

Sci Rep. 2021 Jun 14;11(1):12456. doi: 10.1038/s41598-021-89531-7.

DOI:10.1038/s41598-021-89531-7
PMID:34127686
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8203802/
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.

摘要

RNA 结合蛋白(RBP)家族作为多个生物学过程和疾病的关键调控因子发挥作用。然而,RBP 在特发性肺纤维化(IPF)的临床环境中的功能仍不清楚。我们开发了一种实用的计算筛选方法,用于使用多源数据信息和比较分子网络生物信息学来表征 RBPs,并进行湿实验室验证研究。对 IPF 患者组织的批量 RNA 测序数据进行数据挖掘,确定 Quaking(QKI)为显著下调的 RBP。通过对 IPF 患者数据的单细胞 RNA 测序分析,确认了细胞类型特异性表达。我们系统地分析了 QKI 周围的分子相互作用网络及其与人类肺成纤维细胞中 microRNAs(miRs)的功能相互作用,并发现了一个新的调节 miR-506-QKI 轴,有助于 IPF 的发病机制。通过应用 miR 和肺生物学模型系统的内部实验验证了计算结果。这项研究支持了对由 miR-506-QKI 轴调节的 IPF 的内在分子机制的理解。最初应用于人类肺部疾病,此处提出的综合计算数据挖掘方法可以适应其他疾病实体,强调了其在 RBP 研究中的实际相关性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8eb7/8203802/9bfc60b20a02/41598_2021_89531_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8eb7/8203802/dd1f2c8620ca/41598_2021_89531_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8eb7/8203802/334c57d7954f/41598_2021_89531_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8eb7/8203802/88ac227ad746/41598_2021_89531_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8eb7/8203802/9bfc60b20a02/41598_2021_89531_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8eb7/8203802/dd1f2c8620ca/41598_2021_89531_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8eb7/8203802/334c57d7954f/41598_2021_89531_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8eb7/8203802/88ac227ad746/41598_2021_89531_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8eb7/8203802/9bfc60b20a02/41598_2021_89531_Fig4_HTML.jpg

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