Stochastic processes constrain the within and between host evolution of influenza virus
Abstract
The evolutionary dynamics of influenza virus ultimately derive from processes that take place within and between infected individuals. Here we define influenza virus dynamics in human hosts through sequencing of 249 specimens from 200 individuals collected over 6290 person-seasons of observation. Because these viruses were collected from individuals in a prospective community-based cohort, they are broadly representative of natural infections with seasonal viruses. Consistent with a neutral model of evolution, sequence data from 49 serially sampled individuals illustrated the dynamic turnover of synonymous and nonsynonymous single nucleotide variants and provided little evidence for positive selection of antigenic variants. We also identified 43 genetically-validated transmission pairs in this cohort. Maximum likelihood optimization of multiple transmission models estimated an effective transmission bottleneck of 1-2 genomes. Our data suggest that positive selection is inefficient at the level of the individual host and that stochastic processes dominate the host-level evolution of influenza viruses.
Data availability
All data generated or analyzed during this study are included in the manuscript and supporting files. Source data files have been provided. All sequence reads have been deposited to NCBI's BioProject under accession number PRJNA412631.
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Whole genome sequencing of Influenza isolates from a prospective household cohortPublicly available at the NCBI BioProject (accession no: PRJNA412631).
Article and author information
Author details
Funding
Doris Duke Charitable Foundation (CSDA 2013105)
- Adam S Lauring
National Institute of Allergy and Infectious Diseases (R01 AI118886)
- Adam S Lauring
National Institute of General Medical Sciences (T32 GM007544)
- John T McCrone
Centers for Disease Control and Prevention (U01 IP00474)
- Arnold S Monto
National Institute of Allergy and Infectious Diseases (K08 AI119182)
- Robert J Woods
National Institute of Allergy and Infectious Diseases (R01 AI097150)
- Arnold S Monto
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Human subjects: This study was approved by the Institutional Review Board of the University of Michigan Medical School. Adults provided written informed consent for participation for themselves and their children; children 7-17 years provided oral assent.
Copyright
© 2018, McCrone et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Further reading
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- Computational and Systems Biology
- Evolutionary Biology
As pathogens spread in a population of hosts, immunity is built up, and the pool of susceptible individuals are depleted. This generates selective pressure, to which many human RNA viruses, such as influenza virus or SARS-CoV-2, respond with rapid antigenic evolution and frequent emergence of immune evasive variants. However, the host’s immune systems adapt, and older immune responses wane, such that escape variants only enjoy a growth advantage for a limited time. If variant growth dynamics and reshaping of host-immunity operate on comparable time scales, viral adaptation is determined by eco-evolutionary interactions that are not captured by models of rapid evolution in a fixed environment. Here, we use a Susceptible/Infected model to describe the interaction between an evolving viral population in a dynamic but immunologically diverse host population. We show that depending on strain cross-immunity, heterogeneity of the host population, and durability of immune responses, escape variants initially grow exponentially, but lose their growth advantage before reaching high frequencies. Their subsequent dynamics follows an anomalous random walk determined by future escape variants and results in variant trajectories that are unpredictable. This model can explain the apparent contradiction between the clearly adaptive nature of antigenic evolution and the quasi-neutral dynamics of high-frequency variants observed for influenza viruses.
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