Stability of SARS-CoV-2-Encoded Proteins and Their Antibody Levels Correlate with Interleukin 6 in COVID-19 Patients.
mSystems
; 7(3): e0005822, 2022 06 28.
Article
en En
| MEDLINE
| ID: mdl-35582921
The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), has become a severe global public health crisis. Therefore, understanding the molecular details of SARS-CoV-2 will be critical for fighting the virus's spread and preventing future pandemics. In this study, we globally profiled the stability of SARS-CoV-2-encoded proteins, studied their degradation pathways, and determined their correlation with the antibody responses in patient plasma. We identified 18 proteins with unstable half-lives and 6 relatively stable proteins with longer half-lives. The labile SARS-CoV-2 proteins were degraded mainly by the ubiquitin-proteasome pathway. We also observed a significant correlation between antibody levels and protein half-lives, which indicated that a stable antigen of SARS-CoV-2 could be more effective for eliciting antibody responses. In addition, levels of antiviral antibodies targeting NSP10 were found to be negatively correlated with systemic levels of interleukin 6 (IL-6) in patients. These findings may facilitate the development of novel therapeutic or diagnostic approaches. IMPORTANCE SARS-CoV-2, the etiological cause of COVID-19, carries 29 genes in its genome. However, our knowledge of the viral proteins in biological and biochemical aspects is limited. In this study, we globally profiled the stability of the viral proteins in living lung epithelial cells. Importantly, the labile SARS-CoV-2-encoded proteins were mainly degraded through the ubiquitin-proteasome pathway. Stable proteins, including spike and nucleocapsid, of SARS-CoV-2 were more effective in eliciting antibody production. The levels of antiviral antibodies targeting NSP10 were negatively correlated with systemic levels of IL-6 in COVID-19 patients.
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1
Base de datos:
MEDLINE
Asunto principal:
COVID-19
Tipo de estudio:
Prognostic_studies
Idioma:
En
Revista:
MSystems
Año:
2022
Tipo del documento:
Article