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Structures and functions linked to genome-wide adaptation of human influenza A viruses

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  • Structures and functions linked to genome-wide adaptation of human influenza A viruses

    Sci Rep. 2019 Apr 18;9(1):6267. doi: 10.1038/s41598-019-42614-y.
    Structures and functions linked to genome-wide adaptation of human influenza A viruses.

    Klingen TR1, Loers J1, Stanelle-Bertram S2, Gabriel G2,3, McHardy AC4,5.
    Author information

    Abstract

    Human influenza A viruses elicit short-term respiratory infections with considerable mortality and morbidity. While H3N2 viruses circulate for more than 50 years, the recent introduction of pH1N1 viruses presents an excellent opportunity for a comparative analysis of the genome-wide evolutionary forces acting on both subtypes. Here, we inferred patches of sites relevant for adaptation, i.e. being under positive selection, on eleven viral protein structures, from all available data since 1968 and correlated these with known functional properties. Overall, pH1N1 have more patches than H3N2 viruses, especially in the viral polymerase complex, while antigenic evolution is more apparent for H3N2 viruses. In both subtypes, NS1 has the highest patch and patch site frequency, indicating that NS1-mediated viral attenuation of host inflammatory responses is a continuously intensifying process, elevated even in the longtime-circulating subtype H3N2. We confirmed the resistance-causing effects of two pH1N1 changes against oseltamivir in NA activity assays, demonstrating the value of the resource for discovering functionally relevant changes. Our results represent an atlas of protein regions and sites with links to host adaptation, antiviral drug resistance and immune evasion for both subtypes for further study.


    PMID: 31000776 DOI: 10.1038/s41598-019-42614-y
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  • #2
    14 pages pdf : https://www.nature.com/articles/s41598-019-42614-y.pdf
    no numbers to compare evolution,mutations afaics

    > Overall, pH1N1 have more patches than H3N2

    what's a patch ?

    Data Availability The PatchDetection software, figures and tables from
    this manuscript, and all related data used in this publication
    are fully available under the Apache License 2.0 at
    Contribute to hzi-bifo/PatchDetection development by creating an account on GitHub.


    we identified clusters (patches) of sites under positive selection on the protein
    structure based on dN/dS values and protein structure models.
    A widely used method determines the rates of non-synonymous to synonymous changes
    (dN/dS ratio) in a phylogeny 13,31. A significant excess of dN to dS, or dN/dS> 1,
    provides evidence for positive selection, assuming that synonymous changes are neutral.

    85. Klingen, T. R., Loers, J. & McHardy, A. C. PatchDetection data, https://doi.org/10.5281/zenodo.1475963 (2018)
    22. Tusche, C., Steinbruck, L. & McHardy, A. C. Detecting patches of protein sites of influenza A viruses under
    positive selection. Mol Biol Evol 29 , 2063?2071, https://doi.org/10.1093/molbev/mss095 (2012)
    23. Kratsch, C., Klingen, T. R., Mumken, L., Steinbruck, L. & McHardy, A. C. Determination of
    antigenicity-altering patches on the major surface protein of human influenza A/H3N2 viruses.
    Virus Evol 2 , vev025, https://doi.org/10.1093/ve/vev025 (2016)

    I'm interested in expert panflu damage estimates
    my current links: http://bit.ly/hFI7H ILI-charts: http://bit.ly/CcRgT

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