Tracing and Controlling Fates of Single Host Cells during HIV Infection

About This Grant

Project Summary/Abstract Human Immunodeficiency Virus 1 (HIV-1) infection outcome is variable between single host cells, even within clonal populations. Host factors are variably expressed and can promote susceptibility to infection and latency, a state wherein a copy of the virus remains in the host genome, posing a serious therapeutic challenge. Yet, no lasting solutions to these problems exist to date because we lack a comprehensive knowledge of the drivers of host cell state to distinct infection fates. Targeting the source of single cell variability in HIV-1 infection may provide strategies for its prevention, treatment, and cure. My proposed work will investigate how certain cell states permit HIV-1 infection and latency—two major roadblocks to lasting cures. Here, I propose to 1) nominate host cell state drivers of HIV-1 susceptibility, and 2) redefine HIV-1 infection at the single-cell level using a new viral isoform capture method. Toward this end, I will develop preVIEU, a multimodal framework combining DNA barcoding, single-cell profiling, viral mRNA isoform capture, and computation. To determine the extent HIV-1 infection fate is predestined by cell state, I will barcode primary CD4+ T cells and track if “twin” sibling cells share the same fate upon HIV-1 challenge. To then reveal what specific state predetermines a cell to either active or latent infection, I will profile cells using CITE-seq—combined single cell transcriptomic and protein abundance measurement—and link one sibling’s initial state before viral exposure to the other sibling’s infection fate via their shared barcode. I will experimentally validate that these states drive a specific fate, and screen for proteins and pathways underpinning these states to identify factors controlling infection outcomes. To better understand infection dynamics within single cells, I will develop the viral isoform capture component of preVIEU that I will then apply to study cell-, cell type-, and tissue-specific infection states in SIV-infected, ART-suppressed macaque samples. Lastly, I will monitor latency reversal in single cells to determine synergistic drug treatments to improve the targeting of the latent reservoir. Overall, I will develop generalizable frameworks to infer host cell infection state-to-fate mappings at unprecedented resolution to further our understanding of HIV-1 infection dynamics and pave the way for precise disease control strategies.