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Implementing sequence-based antigenic distance calculation into immunological shape space model
BACKGROUND: In 2009, a novel influenza vaccine was distributed worldwide to combat the H1N1 influenza “swine flu” pandemic. However, antibodies induced by the vaccine display differences in their specificity and cross-reactivity dependent on pre-existing immunity. Here, we present a computational mo...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7303933/ https://www.ncbi.nlm.nih.gov/pubmed/32560624 http://dx.doi.org/10.1186/s12859-020-03594-3 |
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author | Anderson, Christopher S. Sangster, Mark Y. Yang, Hongmei Mariani, Thomas J. Chaudhury, Sidhartha Topham, David J. |
author_facet | Anderson, Christopher S. Sangster, Mark Y. Yang, Hongmei Mariani, Thomas J. Chaudhury, Sidhartha Topham, David J. |
author_sort | Anderson, Christopher S. |
collection | PubMed |
description | BACKGROUND: In 2009, a novel influenza vaccine was distributed worldwide to combat the H1N1 influenza “swine flu” pandemic. However, antibodies induced by the vaccine display differences in their specificity and cross-reactivity dependent on pre-existing immunity. Here, we present a computational model that can capture the effect of pre-existing immunity on influenza vaccine responses. The model predicts the region of the virus hemagglutinin (HA) protein targeted by antibodies after vaccination as well as the level of cross-reactivity induced by the vaccine. We tested our model by simulating a scenario similar to the 2009 pandemic vaccine and compared the results to antibody binding data obtained from human subjects vaccinated with the monovalent 2009 H1N1 influenza vaccine. RESULTS: We found that both specificity and cross-reactivity of the antibodies induced by the 2009 H1N1 influenza HA protein were affected by the viral strain the individual was originally exposed. Specifically, the level of antigenic relatedness between the original exposure HA antigen and the 2009 HA protein affected antigenic-site immunodominance. Moreover, antibody cross-reactivity was increased when the individual’s pre-existing immunity was specific to an HA protein antigenically distinct from the 2009 pandemic strain. Comparison of simulation data with antibody binding data from human serum samples demonstrated qualitative and quantitative similarities between the model and real-life immune responses to the 2009 vaccine. CONCLUSION: We provide a novel method to evaluate expected outcomes in antibody specificity and cross-reactivity after influenza vaccination in individuals with different influenza HA antigen exposure histories. The model produced similar outcomes as what has been previously reported in humans after receiving the 2009 influenza pandemic vaccine. Our results suggest that differences in cross-reactivity after influenza vaccination should be expected in individuals with different exposure histories. |
format | Online Article Text |
id | pubmed-7303933 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-73039332020-06-19 Implementing sequence-based antigenic distance calculation into immunological shape space model Anderson, Christopher S. Sangster, Mark Y. Yang, Hongmei Mariani, Thomas J. Chaudhury, Sidhartha Topham, David J. BMC Bioinformatics Research Article BACKGROUND: In 2009, a novel influenza vaccine was distributed worldwide to combat the H1N1 influenza “swine flu” pandemic. However, antibodies induced by the vaccine display differences in their specificity and cross-reactivity dependent on pre-existing immunity. Here, we present a computational model that can capture the effect of pre-existing immunity on influenza vaccine responses. The model predicts the region of the virus hemagglutinin (HA) protein targeted by antibodies after vaccination as well as the level of cross-reactivity induced by the vaccine. We tested our model by simulating a scenario similar to the 2009 pandemic vaccine and compared the results to antibody binding data obtained from human subjects vaccinated with the monovalent 2009 H1N1 influenza vaccine. RESULTS: We found that both specificity and cross-reactivity of the antibodies induced by the 2009 H1N1 influenza HA protein were affected by the viral strain the individual was originally exposed. Specifically, the level of antigenic relatedness between the original exposure HA antigen and the 2009 HA protein affected antigenic-site immunodominance. Moreover, antibody cross-reactivity was increased when the individual’s pre-existing immunity was specific to an HA protein antigenically distinct from the 2009 pandemic strain. Comparison of simulation data with antibody binding data from human serum samples demonstrated qualitative and quantitative similarities between the model and real-life immune responses to the 2009 vaccine. CONCLUSION: We provide a novel method to evaluate expected outcomes in antibody specificity and cross-reactivity after influenza vaccination in individuals with different influenza HA antigen exposure histories. The model produced similar outcomes as what has been previously reported in humans after receiving the 2009 influenza pandemic vaccine. Our results suggest that differences in cross-reactivity after influenza vaccination should be expected in individuals with different exposure histories. BioMed Central 2020-06-19 /pmc/articles/PMC7303933/ /pubmed/32560624 http://dx.doi.org/10.1186/s12859-020-03594-3 Text en © The Author(s) 2020 Open AccessThis 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/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Anderson, Christopher S. Sangster, Mark Y. Yang, Hongmei Mariani, Thomas J. Chaudhury, Sidhartha Topham, David J. Implementing sequence-based antigenic distance calculation into immunological shape space model |
title | Implementing sequence-based antigenic distance calculation into immunological shape space model |
title_full | Implementing sequence-based antigenic distance calculation into immunological shape space model |
title_fullStr | Implementing sequence-based antigenic distance calculation into immunological shape space model |
title_full_unstemmed | Implementing sequence-based antigenic distance calculation into immunological shape space model |
title_short | Implementing sequence-based antigenic distance calculation into immunological shape space model |
title_sort | implementing sequence-based antigenic distance calculation into immunological shape space model |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7303933/ https://www.ncbi.nlm.nih.gov/pubmed/32560624 http://dx.doi.org/10.1186/s12859-020-03594-3 |
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