Article | Published:

A predictive fitness model for influenza

Nature volume 507, pages 5761 (06 March 2014) | Download Citation

Abstract

The seasonal human influenza A/H3N2 virus undergoes rapid evolution, which produces significant year-to-year sequence turnover in the population of circulating strains. Adaptive mutations respond to human immune challenge and occur primarily in antigenic epitopes, the antibody-binding domains of the viral surface protein haemagglutinin. Here we develop a fitness model for haemagglutinin that predicts the evolution of the viral population from one year to the next. Two factors are shown to determine the fitness of a strain: adaptive epitope changes and deleterious mutations outside the epitopes. We infer both fitness components for the strains circulating in a given year, using population-genetic data of all previous strains. From fitness and frequency of each strain, we predict the frequency of its descendent strains in the following year. This fitness model maps the adaptive history of influenza A and suggests a principled method for vaccine selection. Our results call for a more comprehensive epidemiology of influenza and other fast-evolving pathogens that integrates antigenic phenotypes with other viral functions coupled by genetic linkage.

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Acknowledgements

We acknowledge discussions with B. D. Greenbaum, B. Grenfell, C. Illingworth, A. Levine, J. W. McCauley, V. Mustonen, S. Pompei and R. Rabadan. This work has been partially supported by Deutsche Forschungsgemeinschaft grant SFB 680 and by German Federal Ministry of Education and Research grant 0315893-Sybacol. Part of this work was performed at the Kavli Institute of Theoretical Physics (Santa Barbara), which has been supported by National Science Foundation grant PHY05-51164.

Author information

Affiliations

  1. Institute for Theoretical Physics, University of Cologne, Zülpicher Strasse 77, 50937 Köln, Germany

    • Marta Łuksza
    •  & Michael Lässig
  2. Biological Sciences, Columbia University, 607D Fairchild Center, New York, New York 10027, USA

    • Marta Łuksza

Authors

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Contributions

Both authors designed research, developed methods, analysed data, interpreted results and wrote the paper.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Michael Lässig.

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Supplementary information

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  1. 1.

    Supplementary Data

    This file contains the GenBank and Gisaid accession numbers of the influenza strains used in the study.

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DOI

https://doi.org/10.1038/nature13087

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