Stochastic processes dominate the within and between host evolution of influenza virus

Abstract

The global evolutionary dynamics of influenza virus ultimately derive from processes that take place within and between infected individuals. Here we define the dynamics of influenza A virus populations in human hosts through next generation sequencing of 249 specimens from 200 individuals collected over 6290 person-seasons of observation. Because these viruses were collected over 5 seasons from individuals in a prospective community-based cohort, they are broadly representative of natural human infections with seasonal viruses. We used viral sequence data from 35 serially sampled individuals to estimate a within host effective population size of 30-70 and an in vivo mutation rate of 4x10-5 per nucleotide per cellular infectious cycle. These estimates are consistent across several models and robust to the models' underlying assumptions. We also identified 43 epidemiologically linked and genetically validated transmission pairs. Maximum likelihood optimization of multiple transmission models estimates an effective transmission bottleneck of 1-2 distinct genomes. Our data suggest that positive selection of novel viral variants is inefficient at the level of the individual host and that genetic drift and other stochastic processes dominate the within and between host evolution of influenza A viruses.