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A complex epistatic network limits the mutational reversibility in the influenza hemagglutinin receptor-binding site

Author

Listed:
  • Nicholas C. Wu

    (The Scripps Research Institute)

  • Andrew J. Thompson

    (The Scripps Research Institute)

  • Jia Xie

    (The Scripps Research Institute)

  • Chih-Wei Lin

    (The Scripps Research Institute)

  • Corwin M. Nycholat

    (The Scripps Research Institute)

  • Xueyong Zhu

    (The Scripps Research Institute)

  • Richard A. Lerner

    (The Scripps Research Institute
    The Scripps Research Institute)

  • James C. Paulson

    (The Scripps Research Institute
    The Scripps Research Institute)

  • Ian A. Wilson

    (The Scripps Research Institute
    The Scripps Research Institute)

Abstract

The hemagglutinin (HA) receptor-binding site (RBS) in human influenza A viruses is critical for attachment to host cells, which imposes a functional constraint on its natural evolution. On the other hand, being part of the major antigenic sites, the HA RBS of human H3N2 viruses needs to constantly mutate to evade the immune system. From large-scale mutagenesis experiments, we here show that several of the natural RBS substitutions become integrated into an extensive epistatic network that prevents substitution reversion. X-ray structural analysis reveals the mechanistic consequences as well as changes in the mode of receptor binding. Further studies are necessary to elucidate whether such entrenchment limits future options for immune escape or adversely affect long-term viral fitness.

Suggested Citation

  • Nicholas C. Wu & Andrew J. Thompson & Jia Xie & Chih-Wei Lin & Corwin M. Nycholat & Xueyong Zhu & Richard A. Lerner & James C. Paulson & Ian A. Wilson, 2018. "A complex epistatic network limits the mutational reversibility in the influenza hemagglutinin receptor-binding site," Nature Communications, Nature, vol. 9(1), pages 1-13, December.
    • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-03663-5
    DOI: 10.1038/s41467-018-03663-5
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    Cited by:

    1. Luca Unione & Augustinus N. A. Ammerlaan & Gerlof P. Bosman & Elif Uslu & Ruonan Liang & Frederik Broszeit & Roosmarijn Woude & Yanyan Liu & Shengzhou Ma & Lin Liu & Marcos Gómez-Redondo & Iris A. Ber, 2024. "Probing altered receptor specificities of antigenically drifting human H3N2 viruses by chemoenzymatic synthesis, NMR, and modeling," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    2. Syed Awais W. Shah & Daniel P. Palomar & Ian Barr & Leo L. M. Poon & Ahmed Abdul Quadeer & Matthew R. McKay, 2024. "Seasonal antigenic prediction of influenza A H3N2 using machine learning," Nature Communications, Nature, vol. 15(1), pages 1-12, December.

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