SYMP 21-3 - Understanding strain competition mediated by immunity in influenza virus

Thursday, August 10, 2017: 2:30 PM
Portland Blrm 253, Oregon Convention Center
Trevor Bedford, Fred Hutchinson Cancer Research Institute, Seattle, WA
Background/Question/Methods

Owing to rapid mutation, the evolution of the influenza virus occurs on a human timescale; rather than being forced to infer past evolutionary events, we can observe them in near real-time. While individuals develop long-lasting immunity to particular influenza strains after infection, antigenic mutations to the influenza virus genome result in proteins that are recognized to a lesser degree by the human immune system, leaving individuals susceptible to future infection. Mutations are only transiently advantageous; the virus population must keep evolving antigenically to stay ahead of developing human immunity. Viruses compete with one another through the imprint of immunity they leave in the human population. This creates dynamical feedbacks and selective pressure for "antigenically novel" viruses. Owing to rapid antigenic evolution, the World Health Organization (WHO) issues twice-yearly recommendations for influenza vaccine strain choice. In the Northern Hemisphere, the February recommendation is used in the following winter's vaccine, and thus vaccine choice amounts to forecasting the makeup of the viral population ~10 months in advance.
We believe a more complete understanding of strain competition would aid in such forecasting of future strain dynamics.

Results/Conclusions

We apply phylodynamic methods using both forward-simulation approaches and phylogenetic inference to understand patterns of strain turnover across influenza lineages. We find evidence of rare advantageous mutants in H3N2 influenza and rapid success when mutants do appear. Influenza H1N1 and influenza B show fewer adaptive mutations and consequently more co-circulating viral diversity. Rapid and deterministic patterns of strain growth and decline are used a litmus test for identifying neutral vs adaptive dynamics.