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Whole genome sequencing identifies influenza A H3N2 transmission and offers superior resolution to classical typing methods

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Abstract

Objectives

Influenza with its annual epidemic waves is a major cause of morbidity and mortality worldwide. However, only little whole genome data are available regarding the molecular epidemiology promoting our understanding of viral spread in human populations.

Methods

We implemented a RT-PCR strategy starting from patient material to generate influenza A whole genome sequences for molecular epidemiological surveillance. Samples were obtained within the Bavarian Influenza Sentinel. The complete influenza virus genome was amplified by a one-tube multiplex RT-PCR and sequenced on an Illumina MiSeq.

Results

We report whole genomic sequences for 50 influenza A H3N2 viruses, which was the predominating virus in the season 2014/15, directly from patient specimens. The dataset included random samples from Bavaria (Germany) throughout the influenza season and samples from three suspected transmission clusters. We identified the outbreak samples based on sequence identity. Whole genome sequencing (WGS) was superior in resolution compared to analysis of single segments or partial segment analysis. Additionally, we detected manifestation of substantial amounts of viral quasispecies in several patients, carrying mutations varying from the dominant virus in each patient.

Conclusion

Our rapid whole genome sequencing approach for influenza A virus shows that WGS can effectively be used to detect and understand outbreaks in large communities. Additionally, the genomic data provide in-depth details about the circulating virus within one season.

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Acknowledgements

We would like to thank Christine Hartberger and Marina Fischer for excellent technical assistance as well as Sabine Meinel for support and critical discussion of the manuscript.

Funding

The work was supported by the Bavarian State Ministry of Health and Care (Project 13-30). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Author information

Authors and Affiliations

  1. Bavarian Health and Food Safety Authority, Veterinärstraße 2, 85764, Oberschleißheim, Germany

    Dominik M. Meinel, Susanne Heinzinger, Ute Eberle, Nikolaus Ackermann, Katharina Schönberger & Andreas Sing

Authors
  1. Dominik M. Meinel
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  2. Susanne Heinzinger
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  3. Ute Eberle
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  4. Nikolaus Ackermann
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  5. Katharina Schönberger
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  6. Andreas Sing
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Contributions

DMM designed and carried out experiments, performed data analysis and wrote manuscript. SH, UE, KS, NA carried out sample collection and selection. AS performed data analysis and wrote manuscript.

Corresponding author

Correspondence to Andreas Sing.

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Conflict of interests

The authors declare no conflict of interests.

Ethical approval

No ethical approval was required for this study, as samples were collected as part of public health outbreak investigations based on the German Infection Protection Act.

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Meinel, D.M., Heinzinger, S., Eberle, U. et al. Whole genome sequencing identifies influenza A H3N2 transmission and offers superior resolution to classical typing methods. Infection 46, 69–76 (2018). https://doi.org/10.1007/s15010-017-1091-3

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  • DOI: https://doi.org/10.1007/s15010-017-1091-3

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