Predicting Antigenic Variants of Influenza A/H3N2 Viruses

Current inactivated influenza vaccines provide protection when vaccine antigens and circulating viruses share a high degree of similarity in hemagglutinin protein. Five antigenic sites in the hemagglutinin protein have been proposed, and 131 amino acid positions have been identified in the five anti...

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Main Authors: Min-Shi Lee, Jack Si-En Chen
Format: Article
Language:English
Published: Centers for Disease Control and Prevention 2004-08-01
Series:Emerging Infectious Diseases
Subjects:
Online Access:https://wwwnc.cdc.gov/eid/article/10/8/04-0107_article
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spelling doaj-9bf6595ec826444aba4cc133a1c0c4d02020-11-25T01:58:09ZengCenters for Disease Control and PreventionEmerging Infectious Diseases1080-60401080-60592004-08-011081385139010.3201/eid1008.040107Predicting Antigenic Variants of Influenza A/H3N2 VirusesMin-Shi LeeJack Si-En ChenCurrent inactivated influenza vaccines provide protection when vaccine antigens and circulating viruses share a high degree of similarity in hemagglutinin protein. Five antigenic sites in the hemagglutinin protein have been proposed, and 131 amino acid positions have been identified in the five antigenic sites. In addition, 20, 18, and 32 amino acid positions in the hemagglutinin protein have been identified as mouse monoclonal antibody–binding sites, positively selected codons, and substantially diverse codons, respectively. We investigated these amino acid positions for predicting antigenic variants of influenza A/H3N2 viruses in ferrets. Results indicate that the model based on the number of amino acid changes in the five antigenic sites is best for predicting antigenic variants (agreement = 83%). The methods described in this study could be applied to predict vaccine-induced cross-reactive antibody responses in humans, which may further improve the selection of vaccine strains.https://wwwnc.cdc.gov/eid/article/10/8/04-0107_articleinfluenzaantigenicityvaccine strainhemagglutininprediction modelantigenic variants
collection DOAJ
language English
format Article
sources DOAJ
author Min-Shi Lee
Jack Si-En Chen
spellingShingle Min-Shi Lee
Jack Si-En Chen
Predicting Antigenic Variants of Influenza A/H3N2 Viruses
Emerging Infectious Diseases
influenza
antigenicity
vaccine strain
hemagglutinin
prediction model
antigenic variants
author_facet Min-Shi Lee
Jack Si-En Chen
author_sort Min-Shi Lee
title Predicting Antigenic Variants of Influenza A/H3N2 Viruses
title_short Predicting Antigenic Variants of Influenza A/H3N2 Viruses
title_full Predicting Antigenic Variants of Influenza A/H3N2 Viruses
title_fullStr Predicting Antigenic Variants of Influenza A/H3N2 Viruses
title_full_unstemmed Predicting Antigenic Variants of Influenza A/H3N2 Viruses
title_sort predicting antigenic variants of influenza a/h3n2 viruses
publisher Centers for Disease Control and Prevention
series Emerging Infectious Diseases
issn 1080-6040
1080-6059
publishDate 2004-08-01
description Current inactivated influenza vaccines provide protection when vaccine antigens and circulating viruses share a high degree of similarity in hemagglutinin protein. Five antigenic sites in the hemagglutinin protein have been proposed, and 131 amino acid positions have been identified in the five antigenic sites. In addition, 20, 18, and 32 amino acid positions in the hemagglutinin protein have been identified as mouse monoclonal antibody–binding sites, positively selected codons, and substantially diverse codons, respectively. We investigated these amino acid positions for predicting antigenic variants of influenza A/H3N2 viruses in ferrets. Results indicate that the model based on the number of amino acid changes in the five antigenic sites is best for predicting antigenic variants (agreement = 83%). The methods described in this study could be applied to predict vaccine-induced cross-reactive antibody responses in humans, which may further improve the selection of vaccine strains.
topic influenza
antigenicity
vaccine strain
hemagglutinin
prediction model
antigenic variants
url https://wwwnc.cdc.gov/eid/article/10/8/04-0107_article
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