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H1N1 influenza virus epitopes classified by monoclonal antibodies
Epitopes serve an important role in influenza infection. It may be useful to screen universal influenza virus vaccines, analyzing the epitopes of multiple subtypes of the hemagglutinin (HA) protein. A total of 40 monoclonal antibodies (mAbs) previously obtained from flu virus HA antigens (developmen...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
D.A. Spandidos
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6122413/ https://www.ncbi.nlm.nih.gov/pubmed/30186431 http://dx.doi.org/10.3892/etm.2018.6429 |
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author | Guo, Chunyan Zhang, Haixiang Xie, Xin Liu, Yang Sun, Lijun Li, Huijin Yu, Pengbo Hu, Hanyu Sun, Jingying Li, Yuan Feng, Qing Zhao, Xiangrong Liang, Daoyan Wang, Zhen Hu, Jun |
author_facet | Guo, Chunyan Zhang, Haixiang Xie, Xin Liu, Yang Sun, Lijun Li, Huijin Yu, Pengbo Hu, Hanyu Sun, Jingying Li, Yuan Feng, Qing Zhao, Xiangrong Liang, Daoyan Wang, Zhen Hu, Jun |
author_sort | Guo, Chunyan |
collection | PubMed |
description | Epitopes serve an important role in influenza infection. It may be useful to screen universal influenza virus vaccines, analyzing the epitopes of multiple subtypes of the hemagglutinin (HA) protein. A total of 40 monoclonal antibodies (mAbs) previously obtained from flu virus HA antigens (development and characterization of 40 mAbs generated using H1N1 influenza virus split vaccines were previously published) were used to detect and classify mAbs into distinct flu virus sub-categories using the ELISA method. Following this, the common continuous amino acid sequences were identified by multiple sequence alignment analysis with the GenBank database and DNAMAN software, for use in predicting the epitopes of the HA protein. Synthesized peptides of these common sequences were prepared, and used to verify and determine the predicted linear epitopes through localization and distribution analyses. With these methods, nine HA linear epitopes distributed among different strains of influenza virus were identified, which included three from influenza A, four from 2009 H1N1 and seasonal influenza, and two from H1. The present study showed that considering a combination of the antigen-antibody reaction specificity, variation in the influenza virus HA protein and linear epitopes may present a useful approach for designing effective multi-epitope vaccines. Furthermore, the study aimed to clarify the cause and pathogenic mechanism of influenza virus HA-induced flu, and presents a novel idea for identifying the epitopes of other pathogenic microorganisms. |
format | Online Article Text |
id | pubmed-6122413 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
spelling | pubmed-61224132018-09-05 H1N1 influenza virus epitopes classified by monoclonal antibodies Guo, Chunyan Zhang, Haixiang Xie, Xin Liu, Yang Sun, Lijun Li, Huijin Yu, Pengbo Hu, Hanyu Sun, Jingying Li, Yuan Feng, Qing Zhao, Xiangrong Liang, Daoyan Wang, Zhen Hu, Jun Exp Ther Med Articles Epitopes serve an important role in influenza infection. It may be useful to screen universal influenza virus vaccines, analyzing the epitopes of multiple subtypes of the hemagglutinin (HA) protein. A total of 40 monoclonal antibodies (mAbs) previously obtained from flu virus HA antigens (development and characterization of 40 mAbs generated using H1N1 influenza virus split vaccines were previously published) were used to detect and classify mAbs into distinct flu virus sub-categories using the ELISA method. Following this, the common continuous amino acid sequences were identified by multiple sequence alignment analysis with the GenBank database and DNAMAN software, for use in predicting the epitopes of the HA protein. Synthesized peptides of these common sequences were prepared, and used to verify and determine the predicted linear epitopes through localization and distribution analyses. With these methods, nine HA linear epitopes distributed among different strains of influenza virus were identified, which included three from influenza A, four from 2009 H1N1 and seasonal influenza, and two from H1. The present study showed that considering a combination of the antigen-antibody reaction specificity, variation in the influenza virus HA protein and linear epitopes may present a useful approach for designing effective multi-epitope vaccines. Furthermore, the study aimed to clarify the cause and pathogenic mechanism of influenza virus HA-induced flu, and presents a novel idea for identifying the epitopes of other pathogenic microorganisms. D.A. Spandidos 2018-09 2018-07-09 /pmc/articles/PMC6122413/ /pubmed/30186431 http://dx.doi.org/10.3892/etm.2018.6429 Text en Copyright: © Guo et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. |
spellingShingle | Articles Guo, Chunyan Zhang, Haixiang Xie, Xin Liu, Yang Sun, Lijun Li, Huijin Yu, Pengbo Hu, Hanyu Sun, Jingying Li, Yuan Feng, Qing Zhao, Xiangrong Liang, Daoyan Wang, Zhen Hu, Jun H1N1 influenza virus epitopes classified by monoclonal antibodies |
title | H1N1 influenza virus epitopes classified by monoclonal antibodies |
title_full | H1N1 influenza virus epitopes classified by monoclonal antibodies |
title_fullStr | H1N1 influenza virus epitopes classified by monoclonal antibodies |
title_full_unstemmed | H1N1 influenza virus epitopes classified by monoclonal antibodies |
title_short | H1N1 influenza virus epitopes classified by monoclonal antibodies |
title_sort | h1n1 influenza virus epitopes classified by monoclonal antibodies |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6122413/ https://www.ncbi.nlm.nih.gov/pubmed/30186431 http://dx.doi.org/10.3892/etm.2018.6429 |
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