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Comprehensive bioinformatics identifies key microRNA players in ATG7-deficient lung fibroblasts

Please always quote using this URN: urn:nbn:de:bvb:20-opus-285181
  • Background: Deficient autophagy has been recently implicated as a driver of pulmonary fibrosis, yet bioinformatics approaches to study this cellular process are lacking. Autophagy-related 5 and 7 (ATG5/ATG7) are critical elements of macro-autophagy. However, an alternative ATG5/ATG7-independent macro-autophagy pathway was recently discovered, its regulation being unknown. Using a bioinformatics proteome profiling analysis of ATG7-deficient human fibroblasts, we aimed to identify key microRNA (miR) regulators in autophagy. Method: We haveBackground: Deficient autophagy has been recently implicated as a driver of pulmonary fibrosis, yet bioinformatics approaches to study this cellular process are lacking. Autophagy-related 5 and 7 (ATG5/ATG7) are critical elements of macro-autophagy. However, an alternative ATG5/ATG7-independent macro-autophagy pathway was recently discovered, its regulation being unknown. Using a bioinformatics proteome profiling analysis of ATG7-deficient human fibroblasts, we aimed to identify key microRNA (miR) regulators in autophagy. Method: We have generated ATG7-knockout MRC-5 fibroblasts and performed mass spectrometry to generate a large-scale proteomics dataset. We further quantified the interactions between various proteins combining bioinformatics molecular network reconstruction and functional enrichment analysis. The predicted key regulatory miRs were validated via quantitative polymerase chain reaction. Results: The functional enrichment analysis of the 26 deregulated proteins showed decreased cellular trafficking, increased mitophagy and senescence as the major overarching processes in ATG7-deficient lung fibroblasts. The 26 proteins reconstitute a protein interactome of 46 nodes and miR-regulated interactome of 834 nodes. The miR network shows three functional cluster modules around miR-16-5p, miR-17-5p and let-7a-5p related to multiple deregulated proteins. Confirming these results in a biological setting, serially passaged wild-type and autophagy-deficient fibroblasts displayed senescence-dependent expression profiles of miR-16-5p and miR-17-5p. Conclusions: We have developed a bioinformatics proteome profiling approach that successfully identifies biologically relevant miR regulators from a proteomics dataset of the ATG-7-deficient milieu in lung fibroblasts, and thus may be used to elucidate key molecular players in complex fibrotic pathological processes. The approach is not limited to a specific cell-type and disease, thus highlighting its high relevance in proteome and non-coding RNA research.show moreshow less

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Metadaten
Author: Stevan D. Stojanović, Maximilian Fuchs, Jan Fiedler, Ke Xiao, Anna Meinecke, Annette Just, Andreas Pich, Thomas Thum, Meik Kunz
URN:urn:nbn:de:bvb:20-opus-285181
Document Type:Journal article
Faculties:Fakultät für Biologie / Theodor-Boveri-Institut für Biowissenschaften
Language:English
Parent Title (English):International Journal of Molecular Sciences
ISSN:1422-0067
Year of Completion:2020
Volume:21
Issue:11
Article Number:4126
Source:International Journal of Molecular Sciences (2020) 21:11, 4126. https://doi.org/10.3390/ijms21114126
DOI:https://doi.org/10.3390/ijms21114126
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie
6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Tag:autophagy; bioinformatics; functional network analysis; lung fibrosis; miR; proteomics; senescence
Release Date:2023/06/13
Date of first Publication:2020/06/09
Licence (German):License LogoCC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International