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Integrating genotypes and phenotypes improves long-term forecasts of seasonal influenza A/H3N2 evolution
Seasonal influenza virus A/H3N2 is a major cause of death globally. Vaccination remains the most effective preventative. Rapid mutation of hemagglutinin allows viruses to escape adaptive immunity. This antigenic drift necessitates regular vaccine updates. Effective vaccine strains need to represent...
Autores principales: | , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7553778/ https://www.ncbi.nlm.nih.gov/pubmed/32876050 http://dx.doi.org/10.7554/eLife.60067 |
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author | Huddleston, John Barnes, John R Rowe, Thomas Xu, Xiyan Kondor, Rebecca Wentworth, David E Whittaker, Lynne Ermetal, Burcu Daniels, Rodney Stuart McCauley, John W Fujisaki, Seiichiro Nakamura, Kazuya Kishida, Noriko Watanabe, Shinji Hasegawa, Hideki Barr, Ian Subbarao, Kanta Barrat-Charlaix, Pierre Neher, Richard A Bedford, Trevor |
author_facet | Huddleston, John Barnes, John R Rowe, Thomas Xu, Xiyan Kondor, Rebecca Wentworth, David E Whittaker, Lynne Ermetal, Burcu Daniels, Rodney Stuart McCauley, John W Fujisaki, Seiichiro Nakamura, Kazuya Kishida, Noriko Watanabe, Shinji Hasegawa, Hideki Barr, Ian Subbarao, Kanta Barrat-Charlaix, Pierre Neher, Richard A Bedford, Trevor |
author_sort | Huddleston, John |
collection | PubMed |
description | Seasonal influenza virus A/H3N2 is a major cause of death globally. Vaccination remains the most effective preventative. Rapid mutation of hemagglutinin allows viruses to escape adaptive immunity. This antigenic drift necessitates regular vaccine updates. Effective vaccine strains need to represent H3N2 populations circulating one year after strain selection. Experts select strains based on experimental measurements of antigenic drift and predictions made by models from hemagglutinin sequences. We developed a novel influenza forecasting framework that integrates phenotypic measures of antigenic drift and functional constraint with previously published sequence-only fitness estimates. Forecasts informed by phenotypic measures of antigenic drift consistently outperformed previous sequence-only estimates, while sequence-only estimates of functional constraint surpassed more comprehensive experimentally-informed estimates. Importantly, the best models integrated estimates of both functional constraint and either antigenic drift phenotypes or recent population growth. |
format | Online Article Text |
id | pubmed-7553778 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-75537782020-10-14 Integrating genotypes and phenotypes improves long-term forecasts of seasonal influenza A/H3N2 evolution Huddleston, John Barnes, John R Rowe, Thomas Xu, Xiyan Kondor, Rebecca Wentworth, David E Whittaker, Lynne Ermetal, Burcu Daniels, Rodney Stuart McCauley, John W Fujisaki, Seiichiro Nakamura, Kazuya Kishida, Noriko Watanabe, Shinji Hasegawa, Hideki Barr, Ian Subbarao, Kanta Barrat-Charlaix, Pierre Neher, Richard A Bedford, Trevor eLife Evolutionary Biology Seasonal influenza virus A/H3N2 is a major cause of death globally. Vaccination remains the most effective preventative. Rapid mutation of hemagglutinin allows viruses to escape adaptive immunity. This antigenic drift necessitates regular vaccine updates. Effective vaccine strains need to represent H3N2 populations circulating one year after strain selection. Experts select strains based on experimental measurements of antigenic drift and predictions made by models from hemagglutinin sequences. We developed a novel influenza forecasting framework that integrates phenotypic measures of antigenic drift and functional constraint with previously published sequence-only fitness estimates. Forecasts informed by phenotypic measures of antigenic drift consistently outperformed previous sequence-only estimates, while sequence-only estimates of functional constraint surpassed more comprehensive experimentally-informed estimates. Importantly, the best models integrated estimates of both functional constraint and either antigenic drift phenotypes or recent population growth. eLife Sciences Publications, Ltd 2020-09-02 /pmc/articles/PMC7553778/ /pubmed/32876050 http://dx.doi.org/10.7554/eLife.60067 Text en http://creativecommons.org/publicdomain/zero/1.0/ http://creativecommons.org/publicdomain/zero/1.0/This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication (http://creativecommons.org/publicdomain/zero/1.0/) . |
spellingShingle | Evolutionary Biology Huddleston, John Barnes, John R Rowe, Thomas Xu, Xiyan Kondor, Rebecca Wentworth, David E Whittaker, Lynne Ermetal, Burcu Daniels, Rodney Stuart McCauley, John W Fujisaki, Seiichiro Nakamura, Kazuya Kishida, Noriko Watanabe, Shinji Hasegawa, Hideki Barr, Ian Subbarao, Kanta Barrat-Charlaix, Pierre Neher, Richard A Bedford, Trevor Integrating genotypes and phenotypes improves long-term forecasts of seasonal influenza A/H3N2 evolution |
title | Integrating genotypes and phenotypes improves long-term forecasts of seasonal influenza A/H3N2 evolution |
title_full | Integrating genotypes and phenotypes improves long-term forecasts of seasonal influenza A/H3N2 evolution |
title_fullStr | Integrating genotypes and phenotypes improves long-term forecasts of seasonal influenza A/H3N2 evolution |
title_full_unstemmed | Integrating genotypes and phenotypes improves long-term forecasts of seasonal influenza A/H3N2 evolution |
title_short | Integrating genotypes and phenotypes improves long-term forecasts of seasonal influenza A/H3N2 evolution |
title_sort | integrating genotypes and phenotypes improves long-term forecasts of seasonal influenza a/h3n2 evolution |
topic | Evolutionary Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7553778/ https://www.ncbi.nlm.nih.gov/pubmed/32876050 http://dx.doi.org/10.7554/eLife.60067 |
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