Comprehensive Bioinformatics Identifies Key microRNA Players in ATG7-Deficient Lung Fibroblasts

Int J Mol Sci. 2020 Jun 9;21(11):4126. doi: 10.3390/ijms21114126.

Abstract

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 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 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.

Keywords: autophagy; bioinformatics; functional network analysis; lung fibrosis; miR; proteomics; senescence.

MeSH terms

  • Autophagosomes / genetics
  • Autophagosomes / physiology
  • Autophagy
  • Autophagy-Related Protein 5 / metabolism
  • Autophagy-Related Protein 7 / genetics*
  • Autophagy-Related Protein 7 / metabolism
  • Cells, Cultured
  • Cellular Senescence
  • Computational Biology
  • Endothelial Cells / metabolism
  • Fibroblasts / pathology
  • Fibroblasts / physiology*
  • Gene Knockout Techniques
  • Humans
  • MicroRNAs / genetics*
  • Microtubule-Associated Proteins / metabolism

Substances

  • ATG5 protein, human
  • Autophagy-Related Protein 5
  • MAP1LC3B protein, human
  • MicroRNAs
  • Microtubule-Associated Proteins
  • ATG7 protein, human
  • Autophagy-Related Protein 7