32nd International Dynamics & Evolution of Human Viruses

VIRAL POPULATION SIZE IMPACTS EVOLUTIONARY DYNAMICS IN SHIV-INFECTED RHESUS MACAQUES

Not scheduled

20m

Abbaye de Royaumont, Asnières-sur-Oise, France

Oral Within-host dynamics & adaptation

Speaker

Mr Michael P. Hogarty (University of Pennsylvania)

Description

BACKGROUND: Modelling HIV evolution can illuminate mechanisms of viral persistence and predict resistance to antiretroviral therapies. However, current models do not take into account viral population size. Here, we examine in a large cohort of simian-human immunodeficiency virus (SHIV) infected rhesus macaques the relationship between viral population size and rates of virus diversification and divergence. We make the surprising finding that at clinically-relevant virus load titers, the numbers of productively infected cells are low enough to limit rates of virus escape from immune or antiretroviral selection pressures.
METHODS: We analyzed over 13,000 viral envelope (Env) gene sequences from 64 SHIV-infected rhesus macaques from at least three timepoints per individual spanning one year of untreated infection. For each macaque, we aligned these nucleotide sequences to the reference Env, created rooted phylogenetic trees, and measured diversity and divergence as a function of plasma viral load. We then correlated these data with viral phylogenies and applied a simple stead-state model of infection to estimate the per nucleotide mutation sampling rate as a function plasma virus load and number of productively-infected cells.
RESULTS: Mutations accumulated linearly within each macaque but at different rates with a range of ~0.003 to 0.05 mutations per site per year. These rates of divergence significantly correlated with viral load as did rates of diversification. Corresponding phylogenetic analyses identified clusters of highly related sequences within single timepoints, and their frequency was inversely correlated with setpoint viral loads. The steady-state model of infection predicts that only 60-900 productively-infected cells contributed to a setpoint viral load of 10³ vRNA copies/mL, which corresponds to a mutation sampling rate of 0.0016 to 0.011 mutations per site per day.
CONCLUSIONS: The findings show that viral load and therefore population size dramatically impact the rate of viral evolution and the sampling frequency of escape mutations.