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Identifying the genetic basis of antigenic change in influenza A(H1N1)
William T. Harvey, Victoria Gregory, Donald J. Benton, James P. J. Hall, Rodney S. Daniels, Trevor Bedford, Daniel T. Haydon, Alan J. Hay, John W. McCauley, Richard Reeve
(Submitted on 16 Apr 2014)
Determining phenotype from genetic data is a fundamental challenge for virus research. Identification of emerging antigenic variants among circulating influenza viruses is critical to the vaccine virus selection process, with effectiveness maximized when vaccine constituents are antigenically matched to circulating viruses. Generally, antigenic similarity of viruses is assessed by the haemagglutination inhibition (HI) assay. We present models that define key antigenic determinants by identifying substitutions that significantly affect antigenic phenotype assessed using HI assay. Sequences of 506 haemagglutinin (HA) proteins from seasonal influenza A(H1N1) isolates and reference viruses, spanning over a decade, with complementary HI data and a crystallographic structure were analysed. We identified substitutions at fifteen surface-exposed positions as causing changes in antigenic phenotype of HA. At four positions the antigenic impact of substitutions was apparent at multiple points in the phylogeny, while eleven further sites were resolved by identifying branches containing antigenicity-changing events and determining the substitutions responsible by ancestral state reconstruction. Reverse genetics was used to demonstrate the causal effect on antigenicity of a subset of substitutions including one instance where multiple contemporaneous substitutions made a definitive identification impossible $\textit{in silico}$. This technique quantifies the impact of specific amino acid substitutions allowing us to make predictions of antigenic distance, increasing the value of new genetic sequence data for monitoring antigenic drift and phenotypic evolution. It demonstrates the generality of an approach originally developed for foot-and-mouth disease virus that could be extended to other established and emerging influenza virus subtypes as well as other antigenically variable pathogens.
Subjects: Populations and Evolution (q-bio.PE); Quantitative Methods (q-bio.QM)
Cite as: arXiv:1404.4197 [q-bio.PE]
(or arXiv:1404.4197v1 [q-bio.PE] for this version)
http://arxiv.org/abs/1404.4197
William T. Harvey, Victoria Gregory, Donald J. Benton, James P. J. Hall, Rodney S. Daniels, Trevor Bedford, Daniel T. Haydon, Alan J. Hay, John W. McCauley, Richard Reeve
(Submitted on 16 Apr 2014)
Determining phenotype from genetic data is a fundamental challenge for virus research. Identification of emerging antigenic variants among circulating influenza viruses is critical to the vaccine virus selection process, with effectiveness maximized when vaccine constituents are antigenically matched to circulating viruses. Generally, antigenic similarity of viruses is assessed by the haemagglutination inhibition (HI) assay. We present models that define key antigenic determinants by identifying substitutions that significantly affect antigenic phenotype assessed using HI assay. Sequences of 506 haemagglutinin (HA) proteins from seasonal influenza A(H1N1) isolates and reference viruses, spanning over a decade, with complementary HI data and a crystallographic structure were analysed. We identified substitutions at fifteen surface-exposed positions as causing changes in antigenic phenotype of HA. At four positions the antigenic impact of substitutions was apparent at multiple points in the phylogeny, while eleven further sites were resolved by identifying branches containing antigenicity-changing events and determining the substitutions responsible by ancestral state reconstruction. Reverse genetics was used to demonstrate the causal effect on antigenicity of a subset of substitutions including one instance where multiple contemporaneous substitutions made a definitive identification impossible $\textit{in silico}$. This technique quantifies the impact of specific amino acid substitutions allowing us to make predictions of antigenic distance, increasing the value of new genetic sequence data for monitoring antigenic drift and phenotypic evolution. It demonstrates the generality of an approach originally developed for foot-and-mouth disease virus that could be extended to other established and emerging influenza virus subtypes as well as other antigenically variable pathogens.
Subjects: Populations and Evolution (q-bio.PE); Quantitative Methods (q-bio.QM)
Cite as: arXiv:1404.4197 [q-bio.PE]
(or arXiv:1404.4197v1 [q-bio.PE] for this version)
http://arxiv.org/abs/1404.4197