Abstract
A major barrier to finding a cure for human immunodeficiency virus type-I (HIV-1) infection is the existence and persistence of the HIV-1 latent reservoir. Although the size of the reservoir is shown to be extremely stable under effective antiretroviral therapy, multiple lines of evidence suggest that the reservoir is composed of dynamic and heterogeneous subpopulations. Quantifying the dynamics of these subpopulations and the processes that maintain the latent reservoir is crucial to the development of effective strategies to eliminate this reservoir. Here, we constructed a mathematical model to consider four latently infected subpopulations, according to their ability to proliferate and the type of virus they are infected. Our model explains a wide range of clinical observations, including variable estimates of the reservoir half-life and dynamical turnover of cytotoxic T lymphocyte (CTL) escape viruses in the reservoir. It suggests that very early treatment leads to a reservoir that is small in size and is composed of less stable latently infected cells (compared to the reservoir in chronically infected individuals). The shorter half-lives estimated from individuals treated during acute infection is likely driven by cells that are less prone to proliferate; in contrast, the remarkably consistent estimate of the long half-lives in individuals who are treated during chronic infection are driven by fast proliferating cells that are likely to be infected by CTL escape mutants. Our model shed light on the dynamics of the reservoir in the absence and presence of antiretroviral therapy. More broadly, it can be used to estimate the turnover rates of subpopulations of the reservoir as well as to design and evaluate the impact of various therapeutic interventions to purge the HIV-1 reservoir.
Author summary Human immunodeficiency virus (HIV) infects tens of millions of people globally and causes approximately a million death each year. Current treatment for HIV infection suppresses viral load but does not eradicates the virus. A major barrier to cure HIV infection is the existence and persistence of populations of cells that are latently infected by HIV, i.e. the HIV latent reservoir. Understanding and quantifying the kinetics of the reservoir is therefore critical for developing and evaluating effective therapies to purge the reservoir. Recent studies suggested that this reservoir is heterogenous in their population dynamics; yet most previous mathematical models consider this reservoir as a homogenous population. Here we developed a model explicitly tracking the heterogenous subpopulations of the reservoir. We show that this model explains a wide range of clinical observations, and then demonstrate its utility to make quantitative predictions about varies interventions that aim to restrict or reduce the size of the reservoir.
