Single cell transcriptomics of HIV persistence and latency

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Summary Antiretroviral therapy (ART) in HIV-1 infection suppresses viral replication, preserves and improves the CD4+ T cell count and prevents disease progression. However, treatment with ART is not curative, and interruption of therapy consistently unleashes viral relapse. The persistence of a viral reservoir following ART is the major obstacle to an HIV cure. Proposed “shock and kill” strategies to activate and eliminate the HIV reservoir are currently not informed by a knowledge of the T cell states or lineages that support latency. One of the greatest challenges in latency research is to distinguish latent cells from non-latent cells, which is inherently difficult to do without perturbing the latent state of the cells. With current approaches, cellular activation is required to enumerate latent cells, which disrupts the very state that we would like to study. To overcome this major roadblock to latency studies, we have developed an HIV-induced lineage tracing model (HILT) in humanized mouse that irreversibly genetically marks infected cells. When combined with single cell RNA sequencing (scRNAseq) approaches in HIV-infected, ART-treated animals, the result is an emerging genomic resolution view of transcriptional states associated with HIV infection and latency. Preliminary studies presented here begin to provide an unprecedented, single cell genomic classification of HIV-infected CD4 T cell lineages and states during acute infection and during early antiretroviral treatment. In this proposal, we explore single cell multi-omics of persistently infected human CD4 T cells in humanized mice and examine how it responds to oligoclonal TCR activation versus homeostatic proliferation. The systems biology of T cells will be used to dissect latent reservoirs in novel small animal models for HIV to understand how a reservoir is generated and maintained in distinct cell states. Genomic analysis may be used to identify drugs or biologic interventions that can push cells towards active HIV expression and are independent of cellular activation state. These could be used to develop cure strategies aimed at enhancing expression and the progressive decay of the latent reservoir. We hypothesize that a single cell multi-omics approach will elucidate developmentally diverse T cell lineages and transcriptional states that harbor HIV reservoirs, and that each cluster may display unique gene programs associated with HIV persistence. Reversing the expression of factors associated with HIV persistence may reactivate the reservoir. Single cell multi-omics may unveil new targeted strategies to purge HIV from different T cell states. The proposed study leverages a team with expertise in HIV immunopathogenesis, humanized mice, single cell genomics, to deeply phenotype human T cell reservoirs in novel small animal models.