Intrahost HIV population dynamics in CNS and other tissues

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DESCRIPTION (provided by applicant): HIV creates complex genetic populations within a host, and remains latent in a variety of cell types and tissues under antiretroviral therapy, representing a barrier to therapeutic cure. Yet little is known about the relative sizes of latent viral reservoirs in different tissues such as the central nervous system (CNS), and even less about exchange between viral subpopulations in different tissues over time. Deep sequencing technologies allow extensive sampling of these populations. Previous studies have been hampered by limited sampling of viral diversity in the CNS and because they studied only single or occasionally multiple, sparse time points. Designing workable viral eradication strategies will require a characterizing the CNS viral reservoir and its population dynamics with higher resolution. To address these gaps in knowledge, we will apply recently developed techniques, digital PCR (dPCR) and ultra deep sequencing (UDS), to quantify tissue reservoir size and the dynamics of viral subpopulations in archived, longitudinal samples of cerebrospinal fluid cells and supernatant and peripheral blood mononuclear cells and plasma. Here we will evaluate viral subpopulation interactions occurring after antiretroviral treatment interruption, which provides a substantial perturbation of steady state viral and cellular dynamics to anchor the observations. We will apply phylogenetic methods to viral population sequences from CNS and blood over time to assess population dynamics. The study sample comprises a unique, densely serially sampled group of 10 HIV+ subjects undergoing antiretroviral (ART) treatment interruption or viral rebound in the face of continued ART. The project will generate approximately 1.2 million viral sequences. These will be analyzed to delineate how the CNS viral reservoir interacts dynamically with other viral subpopulations and contributes to viral diversification and pathogenicity. The project also will measure the size of CNS viral reservoirs. After de-identification of human subjects, viral sequences will be posted as appropriate on public scientific data resource utilities and software generated for this project will be made publicly available.