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Background: The primary hurdle to curing HIV is due to the establishment of a reservoir early in infection. In an effort to find new treatment strategies, we and others have focused on understanding the selection pressures exerted on the reservoir by studying how proviral sequences change over time. Methods: To gain insights into the dynamics of the HIV reservoir we analyzed longitudinal near full-length sequences from 7 people living with HIV between 1 and 20 years following the initiation of antiretroviral treatment. We used this data to employ Bayesian mixed effects models to characterize the decay of the reservoir using single-phase and multiphasic decay models based on near full-length sequencing. In addition, we developed a machine-learning approach utilizing logistic regression to identify elements within the HIV genome most associated with proviral decay and persistence. By systematically analyzing proviruses that are deleted for a specific element, we gain insights into their role in reservoir contraction and expansion. Results: Our analyses indicate that biphasic decay models of intact reservoir dynamics were better than single-phase models with a stronger statistical fit. Based on the biphasic decay pattern of the intact reservoir, we estimated the half-lives of the first and second phases of decay to be 18.2 (17.3 to 19.2, 95%CI) and 433 (227 to 6400, 95%CI) months, respectively. In contrast, the dynamics of defective proviruses differed favoring neither model definitively, with an estimated half-life of 87.3 (78.1 to 98.8, 95% CI) months during the first phase of the biphasic model. Machine-learning analysis of HIV genomes at the nucleotide level revealed that the presence of the splice donor site D1 was the principal genomic element associated with contraction. This role of D1 was then validated in an in vitro system. Using the same approach, we additionally found supporting evidence that HIV nef may confer a protective advantage for latently infected T cells while tat was associated with clonal expansion. Conclusions: The nature of intact reservoir decay suggests that the long-lived HIV reservoir contains at least 2 distinct compartments. The first compartment decays faster than the second compartment. Our machine-learning analysis of HIV proviral sequences reveals specific genomic elements are associated with contraction while others are associated with persistence and expansion. Together, these opposing forces shape the reservoir over time.

Historically, naive cells have been considered inconsequential to HIV persistence. Here, we compared the contributions of naive and memory cells to the reservoirs of individuals with a spectrum of reservoir sizes and variable immunological control. We performed proviral sequencing of approximately 6000 proviruses from cellular subsets of 5 elite controllers (ECs) off antiretroviral therapy (ART) and 5 chronic progressors (CPs) on ART. The levels of naive infection were barely detectable in ECs and approximately 300-fold lower compared with those in CPs. Moreover, the ratio of infected naive to memory cells was significantly lower in ECs. Overall, the naive infection level increased as reservoir size increased, such that naive cells were a major contributor to the intact reservoir of CPs, whose reservoirs were generally very diverse. In contrast, the reservoirs of ECs were dominated by proviral clones. Critically, the fraction of proviral clones increased with cell differentiation, with naive infection predicting reservoir diversity. Longitudinal sequencing revealed that the reservoir of ECs was less dynamic compared with that of CPs. Naive cells play a critical role in HIV persistence. Their infection level predicts reservoir size and diversity. Moreover, the diminishing diversity of the reservoir as cellular subsets mature suggests that naive T cells repopulate the memory compartment and that direct infection of naive T cells occurs in vivo.

How HIV reservoirs are shaped over time on antiviral therapy is poorly understood. Here, the authors analyze the dynamics of the HIV reservoir by longitudinal proviral sequencing revealing that HIV reservoir expression can contribute to its clearance and paradoxically even to its persistence.

Despite the efficacy of antiretroviral therapy (ART), HIV persists in a latent form and remains a hurdle to eradication. CD4+ T lymphocytes harbor the majority of the HIV reservoir, but the role of individual subsets remains unclear. CD4+ T cells were sorted into central, transitional, effector memory, and naive T cells. We measured HIV DNA and performed proviral sequencing of more than 1900 proviruses in 2 subjects at 2 and 9 years after ART initiation to estimate the contribution of each subset to the reservoir. Although our study was limited to 2 subjects, we obtained comparable findings with publicly available sequences. While the HIV integration levels were lower in naive compared with memory T cells, naive cells were a major contributor to the intact proviral reservoir. Notably, proviral sequences isolated from naive cells appeared to be unique, while those retrieved from effector memory cells were mainly clonal. The number of clones increased as cells differentiated from a naive to an effector memory phenotype, suggesting naive cells repopulate the effector memory reservoir as previously shown for central memory cells. Naive T cells contribute substantially to the intact HIV reservoir and represent a significant hurdle for HIV eradication.