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Regional and temporal coordinated mutation patterns in SARS-CoV-2 spike protein revealed by a clustering and network analysis
SARS-CoV-2 has steadily mutated during its spread to > 300 million people throughout the world. The WHO has designated strains with certain mutations, “variants of concern” (VOC), as they may have higher infectivity and/or resist neutralization by antibodies in sera of vaccinated individuals and...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8782831/ https://www.ncbi.nlm.nih.gov/pubmed/35064154 http://dx.doi.org/10.1038/s41598-022-04950-4 |
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author | Negi, Surendra S. Schein, Catherine H. Braun, Werner |
author_facet | Negi, Surendra S. Schein, Catherine H. Braun, Werner |
author_sort | Negi, Surendra S. |
collection | PubMed |
description | SARS-CoV-2 has steadily mutated during its spread to > 300 million people throughout the world. The WHO has designated strains with certain mutations, “variants of concern” (VOC), as they may have higher infectivity and/or resist neutralization by antibodies in sera of vaccinated individuals and convalescent patients. Methods to detect regionally emerging VOC are needed to guide treatment and vaccine design. Cluster and network analysis was applied to over 1.2 million sequences of the SARS-CoV-2 spike protein from 36 countries in the GISAID database. While some mutations rapidly spread throughout the world, regionally specific groups of variants were identified. Strains circulating in each country contained different sets of high frequency mutations, many of which were known VOCs. Mutations within clusters increased in frequency simultaneously. Low frequency, but highly correlated mutations detected by the method could signal emerging VOCs, especially if they occur at higher frequency in other regions. An automated version of our method to find high frequency mutations in a set of SARS-COV-2 spike sequences is available online at http://curie.utmb.edu/SAR.html. |
format | Online Article Text |
id | pubmed-8782831 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-87828312022-01-24 Regional and temporal coordinated mutation patterns in SARS-CoV-2 spike protein revealed by a clustering and network analysis Negi, Surendra S. Schein, Catherine H. Braun, Werner Sci Rep Article SARS-CoV-2 has steadily mutated during its spread to > 300 million people throughout the world. The WHO has designated strains with certain mutations, “variants of concern” (VOC), as they may have higher infectivity and/or resist neutralization by antibodies in sera of vaccinated individuals and convalescent patients. Methods to detect regionally emerging VOC are needed to guide treatment and vaccine design. Cluster and network analysis was applied to over 1.2 million sequences of the SARS-CoV-2 spike protein from 36 countries in the GISAID database. While some mutations rapidly spread throughout the world, regionally specific groups of variants were identified. Strains circulating in each country contained different sets of high frequency mutations, many of which were known VOCs. Mutations within clusters increased in frequency simultaneously. Low frequency, but highly correlated mutations detected by the method could signal emerging VOCs, especially if they occur at higher frequency in other regions. An automated version of our method to find high frequency mutations in a set of SARS-COV-2 spike sequences is available online at http://curie.utmb.edu/SAR.html. Nature Publishing Group UK 2022-01-21 /pmc/articles/PMC8782831/ /pubmed/35064154 http://dx.doi.org/10.1038/s41598-022-04950-4 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Negi, Surendra S. Schein, Catherine H. Braun, Werner Regional and temporal coordinated mutation patterns in SARS-CoV-2 spike protein revealed by a clustering and network analysis |
title | Regional and temporal coordinated mutation patterns in SARS-CoV-2 spike protein revealed by a clustering and network analysis |
title_full | Regional and temporal coordinated mutation patterns in SARS-CoV-2 spike protein revealed by a clustering and network analysis |
title_fullStr | Regional and temporal coordinated mutation patterns in SARS-CoV-2 spike protein revealed by a clustering and network analysis |
title_full_unstemmed | Regional and temporal coordinated mutation patterns in SARS-CoV-2 spike protein revealed by a clustering and network analysis |
title_short | Regional and temporal coordinated mutation patterns in SARS-CoV-2 spike protein revealed by a clustering and network analysis |
title_sort | regional and temporal coordinated mutation patterns in sars-cov-2 spike protein revealed by a clustering and network analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8782831/ https://www.ncbi.nlm.nih.gov/pubmed/35064154 http://dx.doi.org/10.1038/s41598-022-04950-4 |
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