During human immunodeficiency virus 1 (HIV-1) infection, the viral population is in constant battle with the host immune system. The cytotoxic T-lymphocyte (CTL) response, a branch of the adaptive immune response, is implicated in viral control and can drive viral evolution in the infected host population. Endogenous viral peptides, or ‘epitopes’, are presented to CTLs by human leukocyte antigen (HLA) class I molecules on the surface of infected cells where they may be identified as non-self. Mutations in or proximal to a viral epitope can result in ‘escape’ from CTLs targeting that epitope. The repertoire of epitopes which may be presented is dependent upon host class I HLA types. As such, reversion may occur after transmission due to changes in viral fitness and selection in the context of a new HLA background. Thus, parameters describing the dynamics of CTL escape and reversion are key to understanding how CTL responses within individuals relate to HIV-1 sequence evolution in the infected host population. Escape and reversion can be studied directly using biological assays and longitudinal viral sequence data, or indirectly by considering viral sequences across multiple hosts. Indirect approaches include tree based methods which detect associations between host HLA and viral sequence but do not estimate rates of escape and reversion, and ordinary differential equation (ODE) models which estimate these rates but do not consider the dependency structure inherent in viral sequence data. We introduce two models which estimate escape and reversion rates whilst accounting for the shared ancestry of viral sequence data. For our first model, we lay out an integrated Bayesian approach which combines genealogical inference and an existing epidemiological model to inform escape and reversion rate estimates. Using this model, we find evidence for correlation between escape rate estimates across widely separated geographical regions. We also observe a non-linear negative correlation between in vitro replicative capacity and escape rate. Both findings suggest that epistasis does not play a strong role in the escape process. Although our first model worked well, it had some key limitations which we address in our second method. Notably, by making a series of approximations, we are able account for recombination and analyse very large datasets which would be computationally infeasible under the first model. We verify our second approach through extensive simulations, and use the method to estimate both drug and HLA associated selection along portions of the HIV-1 genome. We test the results of the model using existing knowledge, and determine a collection of putative selected sites which warrant further investigation. Finally, we find evidence to support the notion that the CTL response played a role in HIV-1 subtype diversification.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:640038 |
Date | January 2014 |
Creators | Palmer, Duncan |
Contributors | McVean, Gilean; McLean, Angela |
Publisher | University of Oxford |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | http://ora.ox.ac.uk/objects/uuid:1cd57b15-485d-4f5a-8a1c-7702a355c597 |
Page generated in 0.0014 seconds