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Modelling the viral dynamics of the SARS-CoV-2 Delta and Omicron variants in different cell types
We use viral kinetic models fitted to viral load data from in vitro studies to explain why the SARS-CoV-2 Omicron variant replicates faster than the Delta variant in nasal cells, but slower than Delta in lung cells, which could explain Omicron's higher transmission potential and lower severity....
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10410224/ https://www.ncbi.nlm.nih.gov/pubmed/37553993 http://dx.doi.org/10.1098/rsif.2023.0187 |
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author | McCormack, Clare P. Yan, Ada W. C. Brown, Jonathan C. Sukhova, Ksenia Peacock, Thomas P. Barclay, Wendy S. Dorigatti, Ilaria |
author_facet | McCormack, Clare P. Yan, Ada W. C. Brown, Jonathan C. Sukhova, Ksenia Peacock, Thomas P. Barclay, Wendy S. Dorigatti, Ilaria |
author_sort | McCormack, Clare P. |
collection | PubMed |
description | We use viral kinetic models fitted to viral load data from in vitro studies to explain why the SARS-CoV-2 Omicron variant replicates faster than the Delta variant in nasal cells, but slower than Delta in lung cells, which could explain Omicron's higher transmission potential and lower severity. We find that in both nasal and lung cells, viral infectivity is higher for Omicron but the virus production rate is higher for Delta, with an estimated approximately 200-fold increase in infectivity and 100-fold decrease in virus production when comparing Omicron with Delta in nasal cells. However, the differences are unequal between cell types, and ultimately lead to the basic reproduction number and growth rate being higher for Omicron in nasal cells, and higher for Delta in lung cells. In nasal cells, Omicron alone can enter via a TMPRSS2-independent pathway, but it is primarily increased efficiency of TMPRSS2-dependent entry which accounts for Omicron's increased activity. This work paves the way for using within-host mathematical models to understand the transmission potential and severity of future variants. |
format | Online Article Text |
id | pubmed-10410224 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | The Royal Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-104102242023-08-10 Modelling the viral dynamics of the SARS-CoV-2 Delta and Omicron variants in different cell types McCormack, Clare P. Yan, Ada W. C. Brown, Jonathan C. Sukhova, Ksenia Peacock, Thomas P. Barclay, Wendy S. Dorigatti, Ilaria J R Soc Interface Life Sciences–Mathematics interface We use viral kinetic models fitted to viral load data from in vitro studies to explain why the SARS-CoV-2 Omicron variant replicates faster than the Delta variant in nasal cells, but slower than Delta in lung cells, which could explain Omicron's higher transmission potential and lower severity. We find that in both nasal and lung cells, viral infectivity is higher for Omicron but the virus production rate is higher for Delta, with an estimated approximately 200-fold increase in infectivity and 100-fold decrease in virus production when comparing Omicron with Delta in nasal cells. However, the differences are unequal between cell types, and ultimately lead to the basic reproduction number and growth rate being higher for Omicron in nasal cells, and higher for Delta in lung cells. In nasal cells, Omicron alone can enter via a TMPRSS2-independent pathway, but it is primarily increased efficiency of TMPRSS2-dependent entry which accounts for Omicron's increased activity. This work paves the way for using within-host mathematical models to understand the transmission potential and severity of future variants. The Royal Society 2023-08-09 /pmc/articles/PMC10410224/ /pubmed/37553993 http://dx.doi.org/10.1098/rsif.2023.0187 Text en © 2023 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited. |
spellingShingle | Life Sciences–Mathematics interface McCormack, Clare P. Yan, Ada W. C. Brown, Jonathan C. Sukhova, Ksenia Peacock, Thomas P. Barclay, Wendy S. Dorigatti, Ilaria Modelling the viral dynamics of the SARS-CoV-2 Delta and Omicron variants in different cell types |
title | Modelling the viral dynamics of the SARS-CoV-2 Delta and Omicron variants in different cell types |
title_full | Modelling the viral dynamics of the SARS-CoV-2 Delta and Omicron variants in different cell types |
title_fullStr | Modelling the viral dynamics of the SARS-CoV-2 Delta and Omicron variants in different cell types |
title_full_unstemmed | Modelling the viral dynamics of the SARS-CoV-2 Delta and Omicron variants in different cell types |
title_short | Modelling the viral dynamics of the SARS-CoV-2 Delta and Omicron variants in different cell types |
title_sort | modelling the viral dynamics of the sars-cov-2 delta and omicron variants in different cell types |
topic | Life Sciences–Mathematics interface |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10410224/ https://www.ncbi.nlm.nih.gov/pubmed/37553993 http://dx.doi.org/10.1098/rsif.2023.0187 |
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