Simulating within host human immunodeficiency virus 1 genome evolution in the persistent reservoir

QuickFit: A High-Throughput RT-qPCR-Based Assay to Quantify Viral Growth and Fitness In Vitro

Quantifying viral growth rates is key to understanding evolutionary dynamics and the potential for mutants to escape antiviral drugs. Defining evolutionary escape paths and their impact on viral fitness allows for the development of drugs that are resistant to escape. In the case of HIV, combination antiretroviral therapy can successfully prevent or treat infection, but it relies on strict adherence to prevent escape. Here, we present a method termed QuickFit that enables the quantification of viral fitness by employing large numbers of parallel viral cultures to measure growth rates accurately. QuickFit consistently recapitulated HIV growth measurements obtained by traditional approaches, but with significantly higher throughput and lower rates of error. This method represents a promising tool for rapid and consistent evaluation of viral fitness.

HIV reservoirs are dominated by genetically younger and clonally enriched proviruses

IMPORTANCE

Characterizing the human immunodeficiency virus (HIV) reservoir that endures despite antiretroviral therapy (ART) is critical to cure efforts. We observed that the oldest proviruses persisting during ART were exclusively defective, while intact proviruses (and rebound HIV) dated to nearer ART initiation. This helps explain why studies that sampled sub-genomic proviruses on-ART (which are largely defective) routinely found sequences dating to early infection, whereas those that sampled replication-competent HIV found almost none. Together with our findings that intact proviruses were more likely to be clonal, and that on-ART low-level/isolated viremia originated from proviruses of varying ages (including possibly defective ones), our observations indicate that (i) on-ART and rebound viremia can have distinct within-host origins, (ii) intact proviruses have shorter lifespans than grossly defective ones and thus depend more heavily on clonal expansion for persistence, and (iii) an HIV reservoir predominantly "dating" to near ART initiation will be substantially adapted to within-host pressures, complicating immune-based cure strategies.

Inferring Human Immunodeficiency Virus 1 Proviral Integration Dates With Bayesian Inference

Human immunodeficiency virus 1 (HIV) proviruses archived in the persistent reservoir currently pose the greatest obstacle to HIV cure due to their evasion of combined antiretroviral therapy and ability to reseed HIV infection. Understanding the dynamics of the HIV persistent reservoir is imperative for discovering a durable HIV cure. Here, we explore Bayesian methods using the software BEAST2 to estimate HIV proviral integration dates. We started with within-host longitudinal HIV sequences collected prior to therapy, along with sequences collected from the persistent reservoir during suppressive therapy. We built a BEAST2 model to estimate integration dates of proviral sequences collected during suppressive therapy, implementing a tip date random walker to adjust the sequence tip dates and a latency-specific prior to inform the dates. To validate our method, we implemented it on both simulated and empirical data sets. Consistent with previous studies, we found that proviral integration dates were spread throughout active infection. Path sampling to select an alternative prior for date estimation in place of the latency-specific prior produced unrealistic results in one empirical data set, whereas on another data set, the latency-specific prior was selected as best fitting. Our Bayesian method outperforms current date estimation techniques with a root mean squared error of 0.89 years on simulated data relative to 1.23-1.89 years with previously developed methods. Bayesian methods offer an adaptable framework for inferring proviral integration dates.

HIV reservoirs are dominated by genetically younger and clonally enriched proviruses

In order to cure HIV, we need to better understand the within-host evolutionary origins of the small reservoir of genome-intact proviruses that persists within infected cells during antiretroviral therapy (ART). Most prior studies on reservoir evolutionary dynamics however did not discriminate genome-intact proviruses from the vast background of defective ones. We reconstructed within-host pre-ART HIV evolutionary histories in six individuals and leveraged this information to infer the ages of intact and defective proviruses sampled after an average >9 years on ART, along with the ages of rebound and low-level/isolated viremia occurring during this time. We observed that the longest-lived proviruses persisting on ART were exclusively defective, usually due to large deletions. In contrast, intact proviruses and rebound HIV exclusively dated to the years immediately preceding ART. These observations are consistent with genome-intact proviruses having shorter lifespans, likely due to the cumulative risk of elimination following viral reactivation and protein production. Consistent with this, intact proviruses (and those with packaging signal defects) were three times more likely to be genetically identical compared to other proviral types, highlighting clonal expansion as particularly important in ensuring their survival. By contrast, low-level/isolated viremia sequences were genetically heterogeneous and sometimes ancestral, where viremia may have originated from defective proviruses. Results reveal that the HIV reservoir is dominated by clonally-enriched and genetically younger sequences that date to the untreated infection period when viral populations had been under within-host selection pressures for the longest duration. Knowledge of these qualities may help focus strategies for reservoir elimination.

HIV Proviral Burden, Genetic Diversity, and Dynamics in Viremic Controllers Who Subsequently Initiated Suppressive Antiretroviral Therapy

Curing HIV will require eliminating the reservoir of integrated, replication-competent proviruses that persist despite antiretroviral therapy (ART). Understanding the burden, genetic diversity, and longevity of persisting proviruses in diverse individuals with HIV is critical to this goal, but these characteristics remain understudied in some groups. Among them are viremic controllers—individuals who naturally suppress HIV to low levels but for whom therapy is nevertheless recommended. We reconstructed within-host HIV evolutionary histories from longitudinal single-genome amplified viral sequences in four viremic controllers who eventually initiated ART and used this information to characterize the age and diversity of proviruses persisting on therapy. We further leveraged these within-host proviral age distributions to estimate rates of proviral turnover prior to ART. This is an important yet understudied metric, since pre-ART proviral turnover dictates reservoir composition at ART initiation (and thereafter), which is when curative interventions, once developed, would be administered. Despite natural viremic control, all participants displayed significant within-host HIV evolution pretherapy, where overall on-ART proviral burden and diversity broadly reflected the extent of viral replication and diversity pre-ART. Consistent with recent studies of noncontrollers, the proviral pools of two participants were skewed toward sequences that integrated near ART initiation, suggesting dynamic proviral turnover during untreated infection. In contrast, proviruses recovered from the other two participants dated to time points that were more evenly spread throughout infection, suggesting slow or negligible proviral decay following deposition. HIV cure strategies will need to overcome within-host proviral diversity, even in individuals who naturally controlled HIV replication before therapy.