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A C57BL/6 Mouse model of SARS-CoV-2 infection recapitulates age- and sex-based differences in human COVID-19 disease and recovery (preprint)
researchsquare; 2022.
Preprint
in English
| PREPRINT-RESEARCHSQUARE | ID: ppzbmed-10.21203.rs.3.rs-2194450.v1
ABSTRACT
We present a comprehensive analysis of SARS-CoV-2 infection and recovery in wild type C57BL/6 mice, demonstrating that this is an ideal model of infection and recovery that accurately phenocopies acute human disease arising from the ancestral SARS-CoV-2. Disease severity and infection kinetics are age- and sex-dependent, as has been reported for humans, with older mice and males in particular exhibiting decreased viral clearance and increased mortality. We identified key parallels with human pathology, including intense virus positivity in bronchial epithelial cells, wide-spread alveolar involvement, recruitment of immune cells to the infected lungs, and acute bronchial epithelial cell death. Moreover, older animals experienced increased virus persistence, delayed dispersal of immune cells into lung parenchyma, and morphologic evidence of tissue damage and inflammation. Parallel analysis of SCID mice revealed that the adaptive immune response was not required for recovery from COVID disease symptoms nor early phase clearance of virus but was required for efficient clearance of virus at later stages of infection. Finally, transcriptional analyses indicated that induction and duration of key innate immune gene programs may explain differences in age-dependent disease severity. Importantly, these data demonstrate that SARS-CoV-2-mediated disease in C57BL/6 mice accurately phenocopies human disease across ages and establishes a platform for future therapeutic and genetic screens for not just SARS-CoV-2 but also novel coronaviruses that have yet to emerge.
Full text:
Available
Collection:
Preprints
Database:
PREPRINT-RESEARCHSQUARE
Main subject:
Adenocarcinoma, Bronchiolo-Alveolar
/
COVID-19
/
Inflammation
/
Lung Diseases
Language:
English
Year:
2022
Document Type:
Preprint
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