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  • Identification of transcriptional regulatory network associated with response of host epithelial cells to SARS-CoV-2 #MMPMID34907210
  • Su C; Rousseau S; Emad A
  • Sci Rep 2021[Dec]; 11 (1): 23928 PMID34907210show ga
  • Identification of transcriptional regulatory mechanisms and signaling networks involved in the response of host cells to infection by SARS-CoV-2 is a powerful approach that provides a systems biology view of gene expression programs involved in COVID-19 and may enable the identification of novel therapeutic targets and strategies to mitigate the impact of this disease. In this study, our goal was to identify a transcriptional regulatory network that is associated with gene expression changes between samples infected by SARS-CoV-2 and those that are infected by other respiratory viruses to narrow the results on those enriched or specific to SARS-CoV-2. We combined a series of recently developed computational tools to identify transcriptional regulatory mechanisms involved in the response of epithelial cells to infection by SARS-CoV-2, and particularly regulatory mechanisms that are specific to this virus when compared to other viruses. In addition, using network-guided analyses, we identified kinases associated with this network. The results identified pathways associated with regulation of inflammation (MAPK14) and immunity (BTK, MBX) that may contribute to exacerbate organ damage linked with complications of COVID-19. The regulatory network identified herein reflects a combination of known hits and novel candidate pathways supporting the novel computational pipeline presented herein to quickly narrow down promising avenues of investigation when facing an emerging and novel disease such as COVID-19.
  • |A549 Cells[MESH]
  • |COVID-19/*genetics[MESH]
  • |Cell Line[MESH]
  • |Epithelial Cells/chemistry/cytology/virology[MESH]
  • |Gene Expression Profiling/*methods[MESH]
  • |Gene Expression Regulation[MESH]
  • |Humans[MESH]
  • |Models, Biological[MESH]
  • |SARS-CoV-2/*pathogenicity[MESH]
  • |Sequence Analysis, RNA/*methods[MESH]
  • |Systems Biology[MESH]

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  • suck abstract from ncbi

    23928 1.11 2021