Influenza Virus Evolution Within and Between Human Hosts

Abstract

Rapid adaptive evolution significantly contributes to the size and severity of seasonal influenza epidemics. While influenza evolution has been well defined at the global scale, these dynamics ultimately derive from processes that take place within and between infected individuals. The dynamics of influenza evolution within and between individual hosts are poorly understood.

In my thesis, I have applied an empirically-validated, next-generation sequencing approach to over 300 patient-derived samples from two vaccinated cohorts to define influenza evolution within and between naturally infected individuals. I compared influenza diversity between vaccinated and unvaccinated individuals enrolled in the FLUVACS study, the last randomized, placebo-controlled trial of influenza vaccine efficacy. Phylogenetic analysis of consensus hemagglutinin and neuraminidase sequences showed no stratification by pre-season HAI and NAI titer, respectively. Additionally, within-host diversity did not significantly vary with day of sampling, vaccination status, or pre-season antibody titer. Contrary to what has been suggested in experimental systems, these data indicate that seasonal influenza vaccination has little impact on intrahost diversity in natural infections and that vaccine-induced immunity may be only a minor contributor to antigenic drift at local scales.

In the second study, I used quantitative models to define influenza virus dynamics in individuals enrolled in a prospective, community-based cohort. Sequence data from 35 serially sampled individuals suggested that within-host populations are dynamic and not shaped by antigenic selection. Classical population genetic models showed these dynamics were consistent with a within-host effective population size of 30-70 and an in vivo mutation rate of 4 × 10^{−5} per nucleotide. Additionally, I characterized the between-host effective transmission bottleneck in 43 epidemiologically linked and genetically-validated transmission pairs. Maximum likelihood optimization of multiple transmission models estimated an effective transmission bottleneck of 1-2 genomes.

These data suggest that contrary to the global dynamics, positive selection is inefficient at the level of the individual host. Genetic drift and other stochastic processes likely dominate the host-level evolution of influenza viruses.