If HIV-1 infection is left untreated the viral load of chronically infected individuals can be around 100,000 copies per millilitre of blood. This rapidly reproducing virus within an individual is in stark contrast to the exceptionally low chance of infection, with around 1 in every 10,000 exposures leading to infection, with most new infections initiated by 1-5 founder variants (Talbert-Slagle et al. 2014). Despite the effort dedicated to the study of HIV acquisition, we lack a quantitative framework in which to understand this apparent discordance between the rampant viral dynamics within a patient and the poorly transmitting pathogen within a population. Understanding why transmission of HIV-1 from one partner occurs and why this transmitting virus is able to initiate chronic infection in the recipient partner will be key to unraveling this conundrum.

There are known risk factors associated with transmitting or acquiring HIV, the exact mechanisms underlying these risk factors and thus the relative role of each partner in determining transmission risk are not well elucidated. Understanding the mechanisms underlying the role of the transmitting partner and the recipient partner in both infection acquisition and disease progression will likely help quantify the dynamics of HIV acquisition and harmonize the discordance between the high viral load and low transmission probability and founder strain multiplicity.

This project will disentangle the role of the transmitting partner and the recipient partner in infection acquisition and their roles in the subsequent disease progression in the recipient partner. Specifically, on sexual exposure to HIV-1, which factors - both of the transmitter and of the recipient - dictate whether infection occurs, how many variants found infection and how disease progresses in the newly infected partner? By understanding the determinants of both infection acquisition and disease progression, we will be able to develop more effective strategies to control and treat HIV.

With an increasingly rich data source of next-generation sequence data available, we are now able to build a picture of infection dynamics through infection. These data provide a window into the events taking place at the onset of infection, around the time of when a group of 'founder strains' initiate infection (Keele et al. 2008). This PhD project will use existing and newly generated next-generation sequence data to understand estimates of the number and type of these founder strains (Romero-Severson et al. 2016). Then, using phylogenetic, mathematical or statistical approaches, the student will evaluate how the number and type of these founder strains impacts disease progression.

It is anticipated that this PhD project would use quantitative skills to approach this scientific problem from three angles. One, by evaluating whether different methodologies to calculate the number of founder strains provide consistent results. Founder strains are genetically homogeneous lineages of viruses that go on to successfully replicate within the host during its infection. Both the nature and number of founder strains holds important information on an individual's risk of infection and their ultimate prognosis (Janes et al. 2015), but estimating the number of founder strains is usually time-consuming and computationally intensive. Accurately using data on the number of founder strains will depend on confidently relying on these previous estimates. Second, by developing a mathematical model to harmonize these data on the number of founder strains with the risk of transmission by route and by stage of infection. It is anticipated that the mathematical modelling undertaken by the student will be data-driven from diverse sources such as phylogenetic analysis, epidemiology and vaccine trials and could involve statistical model fitting methodology. Three, by extending the mathematical model to incorporate the role of founder strains on disease progression and viral load. A suitable candidate would be one interested in using or developing their quantitative skills in the area of infectious disease and genetics/sequencing.