Determining the role of selection on the evolution of HIV-1 at the within- and between-host scales

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SummaryHIV-1 is an RNA virus with short generation times, high mutation rates and a chronic period of infection, providing the ideal conditions for rapid adaptive evolution. Evolutionary dynamics are shaped by selection on two levels: within-host adaptation, such as selection of variants that evade host-specific immune responses, and between-host adaptation. Past research has found evolutionary rates are five times faster within a host than between hosts, however there is evidence that suggests the rates of divergence are approximately equivalent. A proposed explanation of this finding is that segregating sites are "toggling" between states during infection. Possible mechanisms include temporal changes in selection pressures and synonymous slightly deleterious mutations hitch-hiking to high frequency due to genetic linkage, and then falling in frequency as a result of recombination or reversion.This project will use phylogenetic analysis of HIV-1 sequencing data and methods from population genetics to determine the sites toggling between states and to build a data-driven understanding of the selection process that shape evolution at both levels. The effect of selection pressures on phylogenetic inferences is currently largely unknown, and a key objective of this work will be to develop phylodynamic models that incorporate the evolutionary complexities, such as selection and recombination, that are typically unaccounted for or are included without reference to real biological findings.Aims and objectives:1. Develop a mutation-selection balance model that explains the evolution of virulence by purifying selection.2. Determine the selection processes that results in within-host toggling: longitudinal sequencing data will be analysed to identify sites under selection and the most likely mechanisms that result in toggling at segregating sites.3. Incorporate toggling at within and between-host levels into evolutionary and phylodynamic models: questions that will be addressed include whether individual and population-level rates are sensitive to the measurement timescale, and how does sampling frequency alter the effect of toggling on phylogenetic inferences, such as time to most recent common ancestor.Novelty:The major contribution of this DPhil will be the linking of biological mechanisms, selection pressures and evolutionary and epidemiological outcomes at the within and between-host levels. The development of effective vaccines and treatments depend upon our understanding of how the virus is transmitted between hosts with different immunological backgrounds and consequently evolves and adapts within the host over many years, and this is heavily influenced by the different selection processes that are the focus of this research. Moreover, more sophisticated phylodynamic models will improve the inferences made on the timing of new outbreaks and consequently the implementation of public health interventions.Alignment of EPSRC strategies and research areasThis project falls within the EPSRC healthcare technologies research area and will in part utilise already published deep-sequenced datasets, as well as long-read longitudinal sequencing data for hundreds of individuals and transmission pairs that will be available within 6-12 months.