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Comparative infectivity and pathogenesis of emerging SARS-CoV-2 variants in Syrian hamsters (preprint)
biorxiv; 2021.
Preprint in English | bioRxiv | ID: ppzbmed-10.1101.2021.02.26.433062
ABSTRACT
Within one year after its emergence, more than 108 million people contracted SARS-CoV-2 and almost 2.4 million succumbed to COVID-19. New SARS-CoV-2 variants of concern (VoC) are emerging all over the world, with the threat of being more readily transmitted, being more virulent, or escaping naturally acquired and vaccine-induced immunity. At least three major prototypic VoC have been identified, i.e. the UK (B.1.1.7), South African (B.1.351) and Brazilian (B.1.1.28.1), variants. These are replacing formerly dominant strains and sparking new COVID-19 epidemics and new spikes in excess mortality. We studied the effect of infection with prototypic VoC from both B.1.1.7 and B.1.351 lineages in Syrian golden hamsters to assess their relative infectivity and pathogenicity in direct comparison to two basal SARS-CoV-2 strains isolated in early 2020. A very efficient infection of the lower respiratory tract of hamsters by these VoC is observed. In line with clinical evidence from patients infected with these VoC, no major differences in disease outcome were observed as compared to the original strains as was quantified by (i) histological scoring, (ii) micro-computed tomography, and (iii) analysis of the expression profiles of selected antiviral and pro-inflammatory cytokine genes. Noteworthy however, in hamsters infected with VoC B.1.1.7, a particularly strong elevation of proinflammatory cytokines was detected. Overall, we established relevant preclinical infection models that will be pivotal to assess the efficacy of current and future vaccine(s) (candidates) as well as therapeutics (small molecules and antibodies) against two important SARS-CoV-2 VoC.
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Full text: Available Collection: Preprints Database: bioRxiv Main subject: COVID-19 Language: English Year: 2021 Document Type: Preprint

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Full text: Available Collection: Preprints Database: bioRxiv Main subject: COVID-19 Language: English Year: 2021 Document Type: Preprint