Analysis of antigenically important residues in human influenza A virus in terms of B-cell epitopes.

Abstract

In this paper we undertake an analysis of the antigenicity of influenza A virus hemagglutinin. We developed a novel computational approach to the identification of antigenically active regions and showed that the amino acid substitutions between successive predominant seasonal strains form clusters that are consistent, in terms of both their location and their size, with the properties of B-cell epitopes in general and with those epitopes that have been identified experimentally in influenza A virus hemagglutinin to date. Such an interpretation provides a biologically plausible framework for an understanding of the location of antigenically important substitutions that is more specific than the canonical "antigenic site" model and provides an effective basis for deriving models that predict antigenic escape in the H3N2 subtype. Our results support recent indications that antibodies binding to the "stalk" region of hemagglutinin are found in the human population and exert evolutionary pressure on the virus. Our computational approach provides a possible method for identifying antigenic escape through evolution in this region, which in some cases will not be identified by the hemagglutinin inhibition assay.

• Authors: William D Lees, David S Moss, Adrian J Shepherd
• Journal: Journal of virology (J Virol) Vol. 85 Issue 17 Pg. 8548-55 (Sep 2011) ISSN: 1098-5514 [Electronic] United States
• PMID: 21680505 (Publication Type: Journal Article)

Chemical References

• Antigens, Viral
• Epitopes, B-Lymphocyte
• Hemagglutinin Glycoproteins, Influenza Virus

Topics

• Amino Acid Substitution (genetics)
• Antigens, Viral (genetics, immunology)
• Computational Biology (methods)
• Epitopes, B-Lymphocyte (genetics, immunology)
• Hemagglutinin Glycoproteins, Influenza Virus (genetics, immunology)
• Humans
• Immune Evasion
• Influenza A Virus, H1N1 Subtype (genetics, immunology)
• Influenza A Virus, H3N2 Subtype (genetics, immunology)
• Models, Molecular
• Mutation, Missense