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Cell culture model system utilizing engineered A549 cells to express high levels of ACE2 and TMPRSS2 for investigating SARS-CoV-2 infection and antivirals
Preprint
em Inglês
| bioRxiv
| ID: ppbiorxiv-474593
ABSTRACT
Novel pathogenic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to pose an imminent global threat since its initial outbreak in December 2019. A simple in vitro model system using cell lines highly susceptible to SARS-CoV-2 infection are critical to facilitate the study of the virus cycle and to discover effective antivirals against the virus. Human lung alveolar A549 cells are regarded as a useful and valuable model for respiratory virus infection. However, SARS-CoV-2 uses the ACE2 as receptor for viral entry and the TMPRSS2 to prime the Spike protein, both of which are negligibly expressed in A549 cells. Here, we report the generation of a robust human lung epithelial cell-based model by transducing ACE2 and TMPRSS2 into A549 cells and show that the ACE2 enriched A549ACE2/TMPRSS2 cells (ACE2plus) and its single-cell-derived subclone (ACE2plusC3) are highly susceptible to SARS-CoV-2 infection. These engineered ACE2plus showed higher ACE2 and TMPRSS2 mRNA expression levels than currently used Calu3 and commercial A549ACE2/TMPRSS2 cells. ACE2 and TMPRSS2 proteins were also highly and ubiquitously expressed in ACE2plusC3 cells. Additionally, antiviral drugs like Camostat mesylate, EIDD-1931, and Remdesivir strongly inhibited SARS-CoV-2 replication. Notably, multinucleated syncytia, a clinical feature commonly observed in severe COVID-19 patients was induced in ACE2plusC3 cells either by virus infection or by overexpressing the Spike proteins of different variants of SARS-CoV-2. Syncytial process was effectively blocked by the furin protease inhibitor, Decanoyl-RVKR-CMK. Taken together, we have developed a robust human A549 lung epithelial cell-based model that can be applied to probe SARS-CoV-2 replication and to facilitate the discovery of SARS-CoV-2 inhibitors.
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Texto completo:
Disponível
Coleções:
Preprints
Base de dados:
bioRxiv
Tipo de estudo:
Estudo prognóstico
Idioma:
Inglês
Ano de publicação:
2022
Tipo de documento:
Preprint