Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Letter
  • Published:

Quantifying influenza virus diversity and transmission in humans

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.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Maximum-likelihood phylogenies of concatenated coding regions for H3N2.
Figure 2: Comparison of HA minor variant frequencies across households.
Figure 3: Box plots of L1-norm pairwise genetic distance within and across households.
Figure 4: Reconstruction of potential transmission pathways of H1N1/2009 and H3N2 outbreaks.
Figure 5: Box plots comparing frequencies for shared variants within and across households.
Figure 6: Probability of variant transmission as a function of the relative frequency of the minor variant.

Similar content being viewed by others

Accession codes

Primary accessions

Sequence Read Archive

Referenced accessions

NCBI Reference Sequence

References

  1. Bush, R.M., Fitch, W.M., Bender, C.A. & Cox, N.J. Positive selection on the H3 hemagglutinin gene of human influenza virus A. Mol. Biol. Evol. 16, 1457–1465 (1999).

    Article  CAS  Google Scholar 

  2. Drake, J.W. Rates of spontaneous mutation among RNA viruses. Proc. Natl. Acad. Sci. USA 90, 4171–4175 (1993).

    Article  CAS  Google Scholar 

  3. Drake, J.W. & Holland, J.J. Mutation rates among RNA viruses. Proc. Natl. Acad. Sci. USA 96, 13910–13913 (1999).

    Article  CAS  Google Scholar 

  4. Viboud, C., Nelson, M.I., Tan, Y. & Holmes, E.C. Contrasting the epidemiological and evolutionary dynamics of influenza spatial transmission. Phil. Trans. R. Soc. Lond. B 368, 20120199 (2013).

    Article  Google Scholar 

  5. Fordyce, S.L. et al. Genetic diversity among pandemic 2009 influenza viruses isolated from a transmission chain. Virol. J. 10, 116 (2013).

    Article  Google Scholar 

  6. Poon, L.L. et al. Viral genetic sequence variations in pandemic H1N1/2009 and seasonal H3N2 influenza viruses within an individual, a household and a community. J. Clin. Virol. 52, 146–150 (2011).

    Article  CAS  Google Scholar 

  7. Cowling, B.J. et al. Comparative epidemiology of pandemic and seasonal influenza A in households. N. Engl. J. Med. 362, 2175–2184 (2010).

    Article  CAS  Google Scholar 

  8. Ghedin, E. et al. Unseasonal transmission of H3N2 influenza A virus during the swine-origin H1N1 pandemic. J. Virol. 84, 5715–5718 (2010).

    Article  CAS  Google Scholar 

  9. Lee, N., Chan, P.K., Lam, W.Y., Szeto, C.C. & Hui, D.S. Co-infection with pandemic H1N1 and seasonal H3N2 influenza viruses. Ann. Intern. Med. 152, 618–619 (2010).

    Article  Google Scholar 

  10. Jombart, T., Eggo, R.M., Dodd, P.J. & Balloux, F. Reconstructing disease outbreaks from genetic data: a graph approach. Heredity (Edinb.) 106, 383–390 (2011).

    Article  CAS  Google Scholar 

  11. Hughes, J. et al. Transmission of equine influenza virus during an outbreak is characterized by frequent mixed infections and loose transmission bottlenecks. PLoS Pathog. 8, e1003081 (2012).

    Article  CAS  Google Scholar 

  12. Emmett, K.J., Lee, A., Khiabanian, H. & Rabadan, R. High-resolution genomic surveillance of 2014 ebolavirus using shared subclonal variants. PLoS Curr. http://dx.doi.org/10.1371/currents.outbreaks.c7fd7946ba606c982668a96bcba43c90 (9 February 2015).

  13. Combe, M., Garijo, R., Geller, R., Cuevas, J.M. & Sanjuán, R. Single-cell analysis of RNA virus infection identifies multiple genetically diverse viral genomes within single infectious units. Cell Host Microbe 18, 424–432 (2015).

    Article  CAS  Google Scholar 

  14. Westgeest, K.B. et al. Genomewide analysis of reassortment and evolution of human influenza A(H3N2) viruses circulating between 1968 and 2011. J. Virol. 88, 2844–2857 (2014).

    Article  Google Scholar 

  15. Varble, A. et al. Influenza A virus transmission bottlenecks are defined by infection route and recipient host. Cell Host Microbe 16, 691–700 (2014).

    Article  CAS  Google Scholar 

  16. Xu, R. et al. Structural basis of preexisting immunity to the 2009 H1N1 pandemic influenza virus. Science 328, 357–360 (2010).

    Article  CAS  Google Scholar 

  17. Kitikoon, P. et al. Pathogenicity and transmission in pigs of the novel A(H3N2)v influenza virus isolated from humans and characterization of swine H3N2 viruses isolated in 2010–2011. J. Virol. 86, 6804–6814 (2012).

    Article  CAS  Google Scholar 

  18. Tharakaraman, K. et al. Antigenically intact hemagglutinin in circulating avian and swine influenza viruses and potential for H3N2 pandemic. Sci. Rep. 3, 1822 (2013).

    Article  Google Scholar 

  19. Cong, Y. et al. Reassortant between human-like H3N2 and avian H5 subtype influenza A viruses in pigs: a potential public health risk. PLoS One 5, e12591 (2010).

    Article  Google Scholar 

  20. Zhou, B. et al. Single-reaction genomic amplification accelerates sequencing and vaccine production for classical and Swine origin human influenza a viruses. J. Virol. 83, 10309–10313 (2009).

    Article  CAS  Google Scholar 

  21. Djikeng, A. et al. Viral genome sequencing by random priming methods. BMC Genomics 9, 5 (2008).

    Article  Google Scholar 

  22. Stamatakis, A., Hoover, P. & Rougemont, J. A rapid bootstrap algorithm for the RAxML Web servers. Syst. Biol. 57, 758–771 (2008).

    Article  Google Scholar 

  23. Nakamura, K. et al. Sequence-specific error profile of Illumina sequencers. Nucleic Acids Res. 39, e90 (2011).

    Article  CAS  Google Scholar 

  24. Charlesworth, B. Fundamental concepts in genetics: effective population size and patterns of molecular evolution and variation. Nat. Rev. Genet. 10, 195–205 (2009).

    Article  CAS  Google Scholar 

  25. Chaisson, M.J. & Tesler, G. Mapping single molecule sequencing reads using basic local alignment with successive refinement (BLASR): application and theory. BMC Bioinformatics 13, 238 (2012).

    Article  CAS  Google Scholar 

  26. Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).

    Article  Google Scholar 

Download references

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

Authors and Affiliations

Authors

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.

Corresponding authors

Correspondence to Benjamin J Cowling or Elodie Ghedin.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–5. (PDF 5543 kb)

Supplementary Table 1

Pearson's correlation between quantitative viral loads (qPCR) and variant counts in nasopharyngeal swabs. (XLSX 14 kb)

Supplementary Table 2

Variant counts (>3%) for each segment and evidence of mixed infections. (XLSX 61 kb)

Supplementary Table 3

Haplotype reconstruction from SMRT PacBio sequencing: H1N1/2009 pair 681_V1(0) and 681_V3(2). (XLSX 64 kb)

Supplementary Table 4

Haplotype reconstruction from SMRT PacBio sequencing: H1N1/2009 pair 742_V1(0) and 742_V3(3). (XLSX 60 kb)

Supplementary Table 5

Haplotype reconstruction from SMRT PacBio sequencing: H1N1/2009 pair 779_V1(0) and 779_V2(1). (XLSX 67 kb)

Supplementary Table 6

Haplotype reconstruction from SMRT PacBio sequencing: H3N2 pair 720_V1(0) and 720_V2(1). (XLSX 106 kb)

Supplementary Table 7

Haplotype reconstruction from SMRT PacBio sequencing: H3N2 pair 734_V1(0) and 734_V3(2). (XLSX 83 kb)

Supplementary Table 8

Haplotype reconstruction from SMRT PacBio sequencing: H3N2 pair 763_V1(0) and 763_V2(3). (XLSX 91 kb)

Supplementary Table 9

Number of mapped reads and average coverage for each sample analyzed. (XLSX 15 kb)

Supplementary Table 10

Wright-Fisher parameter values. (XLSX 67 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Poon, L., Song, T., Rosenfeld, R. et al. Quantifying influenza virus diversity and transmission in humans. Nat Genet 48, 195–200 (2016). https://doi.org/10.1038/ng.3479

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

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

This article is cited by

Search

Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research