Combination antiretroviral therapy (ART) can suppress HIV replication and lead to decreased mortality in HIV-infected individuals. However, ART does not eliminate the latent HIV reservoir, so effective viral suppression requires lifelong ART administration. Therefore, developing a way to eliminate or achieve ART-free control of the reservoir is a top research priority. One challenge to accomplishing this is that we still have limited understanding of the phenotypic and functional properties of the latently-infected cells that persist in people living with HIV. One challenge to characterizing in vivo latently-infected cells is the inability to directly phenotype these cells, due to the lack of a universal biomarker distinguishing them from uninfected cells. As a result, the only way to directly phenotype latent cells has been to stimulate a bulk population of patient-derived cells ex vivo in order to induce expression of viral proteins by the latent cells. Although this allows identification and therefore phenotyping of the reactivated cells by FACS, the measured phenotypes are different from the original phenotypes of the latently-infected cells since ex vivo stimulation alters gene expression. Here, by applying a pseudotime-based bioinformatics approach called PP-SLIDE on paired sets of unstimulated and stimulated patient cells deep-phenotyped by high-dimensional single-cell analytical approaches (CyTOF, single-cell RNAseq), we infer the phenotypes of latently-infected cells in their original pre-stimulation state, and use this approach to chart the in vivo latent reservoir.
In Aim 1, we will use PP-SLIDE on CyTOF-phenotyped cells to compare the latently-infected cells present in the blood and tissues of clinically-matched men and women.
In Aim 2, we will characterize the extent to which markers identified in Aim 1, as well as markers identified from an unbiased approach implementing PP-SLIDE on cells analyzed by single-cell RNAseq, enrich for reservoir cells harboring HIV with genetically-intact replication-competent HIV, for these are the cells that are likely the most important to control or eliminate for ART-free viral control.
In Aim 3, we will characterize the mechanisms that allow the latently-infected cells to persist, focusing on the role of antigen- and homeostasis-driven clonal expansion of CD4+ T cells. By combining cutting-edge single-cell analysis tools with high-dimensional data analysis methods to map the ?atlas? of in vivo latent cells, our studies will provide an unprecedented definition of the features of reservoir cells that persist, reveal whether any reservoir cell traits associate with anatomy (blood vs. tissues) or biological sex (men vs. women), and inform on the mechanisms driving reservoir maintenance. This knowledge that will be important for designing targeted methods to achieve a universal HIV cure.
While effective at suppressing HIV replication, current antiretroviral treatments fail to eliminate latent HIV, leaving a small but persistent HIV ?reservoir? that can produce virus when infected individuals stop their treatment. We propose to characterize and compare the cells that harbor latent HIV in the blood and tissues of HIV-infected men and women. By defining the features that distinguish these reservoir cells from uninfected cells and characterizing the molecular mechanisms that stably maintain these cells for long periods of time, we can design targeted interventions to specifically suppress or even eliminate these cells to achieve HIV cure.
