Quantitative Analysis of Cellular Signaling in Viral Latency

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DESCRIPTION (provided by applicant): Latent HIV is the most significant barrier to complete eradication of HIV from a patient. However, the molecular basis of latency remains unknown. Using a retroviral model of the HIV-1 Tat-mediated positive feedback loop, the laboratories of Profs. Schaffer (sponsor) and Arkin (co-sponsor) showed that clonal populations of infected Jurkat cells with a single viral integration can either rapidly initiate viral gene expression or exhibit long periods of low gene expression analogous to a latent infection. We hypothesize that these long stochastic transcriptional and translational delays could maintain the virus in an inactive state long enough for the host T cell to convert to a memory T cell and thereby solidify the virus into a latent state, a fundamentally new hypothesis for how HIV latency is established. I am using experimental and computational techniques to probe how NF-kB, a key transcriptional regulator of the HIV LTR promoter, influences stochastic gene expression and latency. My central hypotheses are 1) that fluctuations in the interaction of NF-kB at the HIV LTR in single T cells alters the basal transcription rate and leads to the activation or latency decision; and 2) that with an appropriate strength and duration of NF-kB activation, it is possible to purge the latent pool without toxicity. These hypotheses will be tested through a set of experiments organized into two specific aims. In Specific Aim I, I will determine if cell-to-cell heterogeneity in NF-kB interactions at the HIV LTR promoter contributes to stochasticity in HIV gene expression. To do this, I will collect quantitative data using molecular biology techniques to perturb NF-kB LTR binding and nuclear concentrations in infected Jurkat cells, and then use these data to computationally simulate the HIV latency decision. In Specific Aim II, I will use this computational model of NF-kB-dependent HIV gene expression to design therapeutic anti-latency strategies, and then experimentally test efficacy. This blend of molecular virology and computational biology promises to make progress in designing therapies for a major biomedical problem. PUBLIC HEALTH RELEVANCE: Latent HIV, a pool of replication-competent virus that "hides" in host cells, is the significant barrier curing HIV-infected patients, however, scientists still do not know how latency is established. I am building a mathematical model to investigate how HIV can lead to active infection in some cells and latent infection in other cells. I will then use this model to help design anti-latency drug strategies to purge latent infections from a cell population.