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Cluster-transition determining sites underlying the antigenic evolution of seasonal influenza viruses

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  • Cluster-transition determining sites underlying the antigenic evolution of seasonal influenza viruses

    Mol Biol Evol. 2019 Mar 9. pii: msz050. doi: 10.1093/molbev/msz050. [Epub ahead of print]
    Cluster-transition determining sites underlying the antigenic evolution of seasonal influenza viruses.

    Quan L1,2, Ji C1, Ding X1, Peng Y3, Liu M4, Sun J1, Jiang T1, Wu A1.
    Author information

    Abstract

    Seasonal influenza viruses undergo frequent mutations on their surface hemagglutinin (HA) proteins to escape the host immune response. In these mutations, a few key amino acid sites are associated with significant antigenic cluster transitions. To recognize the cluster-transition determining sites of seasonal influenza A/H3N2 and A/H1N1 viruses systematically and quickly, we developed a computational model named RECDS to evaluate the contribution of a specific amino acid site on the HA protein in the whole history of antigenic evolution. In RECDS, we ranked all of the HA sites by calculating the contribution scores derived from the forest of gradient boosting classifiers trained by various sequence-based and structure-based features. With the RECDS model, we found out that the sites determining influenza antigenicity were mostly around the receptor-binding domain both for the influenza A/H3N2 and A/H1N1 viruses. Specifically, half of the cluster-transition determining sites of the influenza A/H1N1 virus were located in the vestigial esterase domain and basic path area on the HA, which indicated that the differential driving force of the antigenic evolution of the A/H1N1 virus refers to the A/H3N2 virus. Beyond that, the footprints of substitutions responsible for antigenic evolution were inferred according to the phylogenetic trees for the cluster-transition determining sites. The monitoring of genetic variation occurring at these cluster-transition determining sites in circulating influenza viruses on a large scale will potentially reduce current assay workloads in influenza surveillance and the selection of new influenza vaccine strains.
    The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.


    PMID: 30851115 DOI: 10.1093/molbev/msz050
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