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Visualizing real-time influenza virus infection, transmission and protection in ferrets

Author

Listed:
  • Erik A. Karlsson

    (St Jude Children’s Research Hospital)

  • Victoria A. Meliopoulos

    (St Jude Children’s Research Hospital)

  • Chandra Savage

    (Animal Resource Center, St Jude Children’s Research Hospital)

  • Brandi Livingston

    (Animal Resource Center, St Jude Children’s Research Hospital)

  • Andrew Mehle

    (University of Wisconsin-Madison)

  • Stacey Schultz-Cherry

    (St Jude Children’s Research Hospital)

Abstract

Influenza transmission efficiency in ferrets is vital for risk-assessment studies. However, the inability to monitor viral infection and transmission dynamics in real time only provides a glimpse into transmissibility. Here we exploit a replication-competent influenza reporter virus to investigate dynamics of infection/transmission in ferrets. Bioluminescent imaging of ferrets infected with A/California/04/2009 H1N1 virus (CA/09) encoding NanoLuc (NLuc) luciferase provides the first real-time snapshot of influenza infection/transmission. Luminescence in the respiratory tract and in less well-characterized extra-pulmonary sites is observed, and imaging identifies infections in animals that would have otherwise been missed by traditional methods. Finally, the reporter virus significantly increases the speed and sensitivity of virological and serological assays. Thus, bioluminescent imaging of influenza infections rapidly determines intra-host dissemination, inter-host transmission and viral load, revealing infection dynamics and pandemic potential of the virus. These results have important implications for antiviral drug susceptibility, vaccine efficacy, transmissibility and pathogenicity studies.

Suggested Citation

  • Erik A. Karlsson & Victoria A. Meliopoulos & Chandra Savage & Brandi Livingston & Andrew Mehle & Stacey Schultz-Cherry, 2015. "Visualizing real-time influenza virus infection, transmission and protection in ferrets," Nature Communications, Nature, vol. 6(1), pages 1-10, May.
    • Handle: RePEc:nat:natcom:v:6:y:2015:i:1:d:10.1038_ncomms7378
    DOI: 10.1038/ncomms7378
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    Cited by:

    1. Arenas, Abbiana R. & Thackar, Neil B. & Haskell, Evan C., 2017. "The logistic growth model as an approximating model for viral load measurements of influenza A virus," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 133(C), pages 206-222.

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