Characterization and assessment of telomerase transduced primary CD4+ T-cells as a model to study HIV latency.

Award amount: 50,000.00

Although significant strides have been made in controlling viral pathogenicity via. Anti-Retroviral Therapy (ART), a major barrier to curing HIV-1 infection is the transcriptionally silent, latent proviral reservoir that resides within HIV infected individuals. These stable yet extremely rare (~1 in 1 million cells) viral reservoirs are primarily thought to be harbored in quiescent, homeo-statically proliferating, resting memory CD4+ T-cells. As such, it is essential to have an in-depth understanding of the molecular mechanisms by which viral latency is established and maintained; a task currently hindered due to latent primary T-cell models having limited lifespan ex vivo. Therefore, the generation of in vitro long-lasting primary T-cell models that faithfully recapitulates in vivo characteristics of resting memory T-cells would be vastly beneficial in the road towards eliminating latently infected T-cells. In the current study, we aim to determine the potential of telomerase reverse transcriptase (hTERT) transduced primary CD4+ T-cells (hTERT+CD4+T-cells) as a model to establish and study HIV latency. As, ectopic expression of hTERT in CD8+ T-cells has shown to induce cell immortalization and maintain primary cell characteristics, Aim 1 will be focused on fully characterizing hTERT+CD4+T-cells, and further investigate whether the hTERT over-expression causes significant perturbations towards T-cell phenotype and function (naïve vs. effector vs. memory). In Aim 2, we will assess the potential for establishing hTERT+CD4+T-cells as a primary T-cell model for studying T-cell latency and subsequently compare hTERT+CD4+T-cells infected with HIV to previously established primary T-cell models of HIV latency. We aim to carry out the assays over the course of 2022 and wherein rigorous statistical analyses will be applied as necessary for the individual experimental design, with appropriate technical and biological replicates employed to ensure data generated is sustainable and broadly generalizable.