TY - JOUR
T1 - Severe acute respiratory syndrome coronavirus (Sars-cov)-2 infection induces dysregulation of immunity
T2 - In silico gene expression analysis
AU - Wu, Yen Hung
AU - Yeh, I. Jeng
AU - Phan, Nam Nhut
AU - Yen, Meng Chi
AU - Liu, Hsin Liang
AU - Wang, Chih Yang
AU - Hsu, Hui Ping
N1 - Publisher Copyright:
© The author(s).
PY - 2021
Y1 - 2021
N2 - Highly pathogenic coronaviruses (CoVs) induce acute respiratory distress syndrome, and the severe acute respiratory syndrome coronavirus (SARS-CoV)-2 has caused a pandemic since late 2019. The diversity of clinical manifestations after SARS-CoV-2 infection results in great challenges to diagnose CoV disease 2019 (COVID-19). There is a growing body of published research on this topic; however, effective medications are still undergoing a long process of being assessed. In the search for potential genetic targets for this infection, we applied a holistic bioinformatics approach to study alterations of gene signatures between SARS-CoV-2-infected cells and mock-infected controls. Two different kinds of lung epithelial cells, A549 with angiotensin-converting enzyme 2 (ACE2) overexpression and normal human bronchial epithelial (NHBE) cells, were infected with SARS-CoV-2. We performed bioinformatics analyses of RNA-sequencing in this study. Through a Venn diagram, Database for Annotation, Visualization and Integrated Discovery, Gene Ontology, Ingenuity Pathway Analysis, and Gene Set Enrichment Analysis, the pathways and networks were constructed from commonly upregulated genes in SARS-CoV-2-infected lung epithelial cells. Genes associated with immune-related pathways, responses of host cells after intracellular infection, steroid hormone biosynthesis, receptor signaling, and the complement system were enriched. Dysregulation of the immune system and malfunction of interferon contribute to a failure to kill SARS-CoV-2 and exacerbate respiratory distress in severely ill patients. Current findings from this study provide a comprehensive investigation of SARS-CoV-2 infection using high-throughput technology.
AB - Highly pathogenic coronaviruses (CoVs) induce acute respiratory distress syndrome, and the severe acute respiratory syndrome coronavirus (SARS-CoV)-2 has caused a pandemic since late 2019. The diversity of clinical manifestations after SARS-CoV-2 infection results in great challenges to diagnose CoV disease 2019 (COVID-19). There is a growing body of published research on this topic; however, effective medications are still undergoing a long process of being assessed. In the search for potential genetic targets for this infection, we applied a holistic bioinformatics approach to study alterations of gene signatures between SARS-CoV-2-infected cells and mock-infected controls. Two different kinds of lung epithelial cells, A549 with angiotensin-converting enzyme 2 (ACE2) overexpression and normal human bronchial epithelial (NHBE) cells, were infected with SARS-CoV-2. We performed bioinformatics analyses of RNA-sequencing in this study. Through a Venn diagram, Database for Annotation, Visualization and Integrated Discovery, Gene Ontology, Ingenuity Pathway Analysis, and Gene Set Enrichment Analysis, the pathways and networks were constructed from commonly upregulated genes in SARS-CoV-2-infected lung epithelial cells. Genes associated with immune-related pathways, responses of host cells after intracellular infection, steroid hormone biosynthesis, receptor signaling, and the complement system were enriched. Dysregulation of the immune system and malfunction of interferon contribute to a failure to kill SARS-CoV-2 and exacerbate respiratory distress in severely ill patients. Current findings from this study provide a comprehensive investigation of SARS-CoV-2 infection using high-throughput technology.
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U2 - 10.7150/ijms.52256
DO - 10.7150/ijms.52256
M3 - Article
C2 - 33526974
AN - SCOPUS:85099835314
SN - 1449-1907
VL - 18
SP - 1143
EP - 1152
JO - International Journal of Medical Sciences
JF - International Journal of Medical Sciences
IS - 5
ER -