Abstract

Influenza A virus is characterized by high genetic diversity1,2,3. However, most of what is known about influenza evolution has come from consensus sequences sampled at the epidemiological scale4 that only represent the dominant virus lineage within each infected host. Less is known about the extent of within-host virus diversity and what proportion of this diversity is transmitted between individuals5. To characterize virus variants that achieve sustainable transmission in new hosts, we examined within-host virus genetic diversity in household donor-recipient pairs from the first wave of the 2009 H1N1 pandemic when seasonal H3N2 was co-circulating. Although the same variants were found in multiple members of the community, the relative frequencies of variants fluctuated, with patterns of genetic variation more similar within than between households. We estimated the effective population size of influenza A virus across donor-recipient pairs to be approximately 100–200 contributing members, which enabled the transmission of multiple lineages, including antigenic variants.

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Acknowledgements

T.S. was a predoctoral trainee supported by US National Institutes of Health T32 training grant T32 EB009403 as part of the HHMI-NIBIB Interfaces Initiative. This research was supported with a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (project T11-705/14N) (L.L.M.P., Y.G., J.S.M.P. and B.J.C.), federal funds from the National Institute of Allergy and Infectious Diseases, US National Institutes of Health, US Department of Health and Human Services, under contract numbers HHS-N272201400006C (L.L.M.P., Y.G. and J.S.M.P.), HHS-N266200700005C (B.J.C.) and HHS-N272200900007C (E.G., X.L., R.A.H., T.B.S. and D.E.W.), the National Institute of General Medical Science, US National Institutes of Health, under award numbers U54 GM088491 (E.G., R.R. and J.V.D.) and U54 GM088558 (B.J.C.), and National Health and Medical Research Council of Australia Fellowship AF30 (E.C.H.). The data for this manuscript were generated and prepared while D.E.W. was employed at the J. Craig Venter Institute. The opinions expressed in this article are the authors' own and do not reflect the views of the Centers for Disease Control and Prevention, the US Department of Health and Human Services or the US government.

Author information

Author notes

    • Matthew B Rogers
    •  & David E Wentworth

    Present addresses: Children's Hospital of Pittsburgh, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA (M.B.R.) and Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA (D.E.W.).

    • Leo L M Poon
    •  & Timothy Song

    These authors contributed equally to this work.

    • Benjamin J Cowling
    •  & Elodie Ghedin

    These authors jointly supervised this work.

Affiliations

  1. Public Health Laboratory Sciences, School of Public Health, The University of Hong Kong, Hong Kong, China.

    • Leo L M Poon
    • , Yi Guan
    •  & Joseph S M Peiris
  2. Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.

    • Timothy Song
    •  & Matthew B Rogers
  3. Center for Genomics and Systems Biology, Department of Biology, New York University, New York, New York, USA.

    • Timothy Song
    • , Bin Zhou
    • , Alan Twaddle
    •  & Elodie Ghedin
  4. School of Computer Sciences, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA.

    • Roni Rosenfeld
  5. J. Craig Venter Institute, Rockville, Maryland, USA.

    • Xudong Lin
    • , Rebecca A Halpin
    • , Timothy B Stockwell
    •  & David E Wentworth
  6. Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

    • Robert Sebra
  7. Pittsburgh Supercomputer Center, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA.

    • Jay V DePasse
  8. Marie Bashir Institute for Infectious Diseases and Biosecurity, Charles Perkins Centre, School of Biological Sciences, The University of Sydney, Sydney, New South Wales, Australia.

    • Edward C Holmes
  9. Sydney Medical School, The University of Sydney, Sydney, New South Wales, Australia.

    • Edward C Holmes
  10. Tisch Cancer Institute, Departments of Medicine, Hematology and Medical Oncology, and Pathology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

    • Benjamin Greenbaum
  11. Epidemiology and Biostatistics, School of Public Health, The University of Hong Kong, Hong Kong, China.

    • Benjamin J Cowling
  12. College of Global Public Health, New York University, New York, New York, USA.

    • Elodie Ghedin

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Contributions

All the authors read and approved the manuscript. L.L.M.P. and E.G. conceived and designed the experiments, supervised research, performed analyses and wrote the manuscript. T.S. analyzed the deep sequence data, performed the variant codon and clustering analyses, and wrote the manuscript. B.G. and R.R. supervised research on the inoculum size estimates and wrote the manuscript. X.L., R.A.H., D.E.W., B.Z. and R.S. performed the sample preparation and sequencing. T.B.S., A.T. and J.V.D. performed the bioinformatic analyses. M.B.R. performed phylogenetic analyses. E.C.H. performed phylogenetic analyses and wrote the manuscript. Y.G. and J.S.M.P. conceived and designed the experiments. B.J.C. conceived and designed the experiments and supervised research.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Benjamin J Cowling or Elodie Ghedin.

Supplementary information

PDF files

  1. 1.

    Supplementary Text and Figures

    Supplementary Figures 1–5.

Excel files

  1. 1.

    Supplementary Table 1

    Pearson's correlation between quantitative viral loads (qPCR) and variant counts in nasopharyngeal swabs.

  2. 2.

    Supplementary Table 2

    Variant counts (>3%) for each segment and evidence of mixed infections.

  3. 3.

    Supplementary Table 3

    Haplotype reconstruction from SMRT PacBio sequencing: H1N1/2009 pair 681_V1(0) and 681_V3(2).

  4. 4.

    Supplementary Table 4

    Haplotype reconstruction from SMRT PacBio sequencing: H1N1/2009 pair 742_V1(0) and 742_V3(3).

  5. 5.

    Supplementary Table 5

    Haplotype reconstruction from SMRT PacBio sequencing: H1N1/2009 pair 779_V1(0) and 779_V2(1).

  6. 6.

    Supplementary Table 6

    Haplotype reconstruction from SMRT PacBio sequencing: H3N2 pair 720_V1(0) and 720_V2(1).

  7. 7.

    Supplementary Table 7

    Haplotype reconstruction from SMRT PacBio sequencing: H3N2 pair 734_V1(0) and 734_V3(2).

  8. 8.

    Supplementary Table 8

    Haplotype reconstruction from SMRT PacBio sequencing: H3N2 pair 763_V1(0) and 763_V2(3).

  9. 9.

    Supplementary Table 9

    Number of mapped reads and average coverage for each sample analyzed.

  10. 10.

    Supplementary Table 10

    Wright-Fisher parameter values.

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DOI

https://doi.org/10.1038/ng.3479

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