CD8+ lymphocyte control of SIV infection during antiretroviral therapy

Antiviral capacity of the early CD8 T-cell response is predictive of natural control of SIV infection: Learning in vivo dynamics using ex vivo data

While most individuals suffer progressive disease following HIV infection, a small fraction spontaneously controls the infection. Although CD8 T-cells have been implicated in this natural control, their mechanistic roles are yet to be established. Here, we combined mathematical modeling and analysis of previously published data from 16 SIV-infected macaques, of which 12 were natural controllers, to elucidate the role of CD8 T-cells in natural control. For each macaque, we considered, in addition to the canonical in vivo plasma viral load and SIV DNA data, longitudinal ex vivo measurements of the virus suppressive capacity of CD8 T-cells. Available mathematical models do not allow analysis of such combined in vivo-ex vivo datasets. We explicitly modeled the ex vivo assay, derived analytical approximations that link the ex vivo measurements with the in vivo effector function of CD8-T cells, and integrated them with an in vivo model of virus dynamics, thus developing a new learning framework that enabled the analysis. Our model fit the data well and estimated the recruitment rate and/or maximal killing rate of CD8 T-cells to be up to 2-fold higher in controllers than non-controllers (p = 0.013). Importantly, the cumulative suppressive capacity of CD8 T-cells over the first 4-6 weeks of infection was associated with virus control (Spearman's ρ = -0.51; p = 0.05). Thus, our analysis identified the early cumulative suppressive capacity of CD8 T-cells as a predictor of natural control. Furthermore, simulating a large virtual population, our model quantified the minimum capacity of this early CD8 T-cell response necessary for long-term control. Our study presents new, quantitative insights into the role of CD8 T-cells in the natural control of HIV infection and has implications for remission strategies.

Modelling HIV-1 control and remission

Remarkable advances are being made in developing interventions for eliciting long-term remission of HIV-1 infection. The success of these interventions will obviate the need for lifelong antiretroviral therapy, the current standard-of-care, and benefit the millions living today with HIV-1. Mathematical modelling has made significant contributions to these efforts. It has helped elucidate the possible mechanistic origins of natural and post-treatment control, deduced potential pathways of the loss of such control, quantified the effects of interventions, and developed frameworks for their rational optimization. Yet, several important questions remain, posing challenges to the translation of these promising interventions. Here, we survey the recent advances in the mathematical modelling of HIV-1 control and remission, highlight their contributions, and discuss potential avenues for future developments.

Understanding early HIV-1 rebound dynamics following antiretroviral therapy interruption: The importance of effector cell expansion

Most people living with HIV-1 experience rapid viral rebound once antiretroviral therapy is interrupted; however, a small fraction remain in viral remission for an extended duration. Understanding the factors that determine whether viral rebound is likely after treatment interruption can enable the development of optimal treatment regimens and therapeutic interventions to potentially achieve a functional cure for HIV-1. We built upon the theoretical framework proposed by Conway and Perelson to construct dynamic models of virus-immune interactions to study factors that influence viral rebound dynamics. We evaluated these models using viral load data from 24 individuals following antiretroviral therapy interruption. The best-performing model accurately captures the heterogeneity of viral dynamics and highlights the importance of the effector cell expansion rate. Our results show that post-treatment controllers and non-controllers can be distinguished based on the effector cell expansion rate in our models. Furthermore, these results demonstrate the potential of using dynamic models incorporating an effector cell response to understand early viral rebound dynamics post-antiretroviral therapy interruption.

Making a Monkey out of Human Immunodeficiency Virus/Simian Immunodeficiency Virus Pathogenesis: Immune Cell Depletion Experiments as a Tool to Understand the Immune Correlates of Protection and Pathogenicity in HIV Infection

Understanding the underlying mechanisms of HIV pathogenesis is critical for designing successful HIV vaccines and cure strategies. However, achieving this goal is complicated by the virus's direct interactions with immune cells, the induction of persistent reservoirs in the immune system cells, and multiple strategies developed by the virus for immune evasion. Meanwhile, HIV and SIV infections induce a pandysfunction of the immune cell populations, making it difficult to untangle the various concurrent mechanisms of HIV pathogenesis. Over the years, one of the most successful approaches for dissecting the immune correlates of protection in HIV/SIV infection has been the in vivo depletion of various immune cell populations and assessment of the impact of these depletions on the outcome of infection in non-human primate models. Here, we present a detailed analysis of the strategies and results of manipulating SIV pathogenesis through in vivo depletions of key immune cells populations. Although each of these methods has its limitations, they have all contributed to our understanding of key pathogenic pathways in HIV/SIV infection.

Modeling dynamics of acute HIV infection incorporating density-dependent cell death and multiplicity of infection

Understanding the dynamics of acute HIV infection can offer valuable insights into the early stages of viral behavior, potentially helping uncover various aspects of HIV pathogenesis. The standard viral dynamics model explains HIV viral dynamics during acute infection reasonably well. However, the model makes simplifying assumptions, neglecting some aspects of HIV infection. For instance, in the standard model, target cells are infected by a single HIV virion. Yet, cellular multiplicity of infection (MOI) may have considerable effects in pathogenesis and viral evolution. Further, when using the standard model, we take constant infected cell death rates, simplifying the dynamic immune responses. Here, we use four models-1) the standard viral dynamics model, 2) an alternate model incorporating cellular MOI, 3) a model assuming density-dependent death rate of infected cells and 4) a model combining (2) and (3)-to investigate acute infection dynamics in 43 people living with HIV very early after HIV exposure. We find that all models qualitatively describe the data, but none of the tested models is by itself the best to capture different kinds of heterogeneity. Instead, different models describe differing features of the dynamics more accurately. For example, while the standard viral dynamics model may be the most parsimonious across study participants by the corrected Akaike Information Criterion (AICc), we find that viral peaks are better explained by a model allowing for cellular MOI, using a linear regression analysis as analyzed by R2. These results suggest that heterogeneity in within-host viral dynamics cannot be captured by a single model. Depending on the specific aspect of interest, a corresponding model should be employed.

Understanding early HIV-1 rebound dynamics following antiretroviral therapy interruption: The importance of effector cell expansion

Most people living with HIV-1 experience rapid viral rebound once antiretroviral therapy is interrupted; however, a small fraction remain in viral remission for an extended duration. Understanding the factors that determine whether viral rebound is likely after treatment interruption can enable the development of optimal treatment regimens and therapeutic interventions to potentially achieve a functional cure for HIV-1. We built upon the theoretical framework proposed by Conway and Perelson to construct dynamic models of virus-immune interactions to study factors that influence viral rebound dynamics. We evaluated these models using viral load data from 24 individuals following antiretroviral therapy interruption. The best-performing model accurately captures the heterogeneity of viral dynamics and highlights the importance of the effector cell expansion rate. Our results show that post-treatment controllers and non-controllers can be distinguished based on the effector cell expansion rate in our models. Furthermore, these results demonstrate the potential of using dynamic models incorporating an effector cell response to understand early viral rebound dynamics post-antiretroviral therapy interruption.

Modeling resistance to the broadly neutralizing antibody PGT121 in people living with HIV-1

PGT121 is a broadly neutralizing antibody in clinical development for the treatment and prevention of HIV-1 infection via passive administration. PGT121 targets the HIV-1 V3-glycan and demonstrated potent antiviral activity in a phase I clinical trial. Resistance to PGT121 monotherapy rapidly occurred in the majority of participants in this trial with the sampled rebound viruses being entirely resistant to PGT121 mediated neutralization. However, two individuals experienced long-term ART-free viral suppression following antibody infusion and retained sensitivity to PGT121 upon viral rebound. Here, we develop mathematical models of the HIV-1 dynamics during this phase I clinical trial. We utilize these models to understand the dynamics leading to PGT121 resistance and to identify the mechanisms driving the observed long-term viral control. Our modeling highlights the importance of the relative fitness difference between PGT121 sensitive and resistant subpopulations prior to treatment. Specifically, by fitting our models to data, we identify the treatment-induced competitive advantage of previously existing or newly generated resistant population as a primary driver of resistance. Finally, our modeling emphasizes the high neutralization ability of PGT121 in both participants who exhibited long-term viral control.

CD8+ T cells control SIV infection using both cytolytic effects and non-cytolytic suppression of virus production

Whether CD8+ T lymphocytes control human immunodeficiency virus infection by cytopathic or non-cytopathic mechanisms is not fully understood. Multiple studies highlighted non-cytopathic effects, but one hypothesis is that cytopathic effects of CD8+ T cells occur before viral production. Here, to examine the role of CD8+ T cells prior to virus production, we treated SIVmac251-infected macaques with an integrase inhibitor combined with a CD8-depleting antibody, or with either reagent alone. We analyzed the ensuing viral dynamics using a mathematical model that included infected cells pre- and post- viral DNA integration to compare different immune effector mechanisms. Macaques receiving the integrase inhibitor alone experienced greater viral load decays, reaching lower nadirs on treatment, than those treated also with the CD8-depleting antibody. Models including CD8+ cell-mediated reduction of viral production (non-cytolytic) were found to best explain the viral profiles across all macaques, in addition an effect in killing infected cells pre-integration (cytolytic) was supported in some of the best models. Our results suggest that CD8+ T cells have both a cytolytic effect on infected cells before viral integration, and a direct, non-cytolytic effect by suppressing viral production.

Evolution during primary HIV infection does not require adaptive immune selection

Modern HIV research depends crucially on both viral sequencing and population measurements. To directly link mechanistic biological processes and evolutionary dynamics during HIV infection, we developed multiple within-host phylodynamic models of HIV primary infection for comparative validation against viral load and evolutionary dynamics data. The optimal model of primary infection required no positive selection, suggesting that the host adaptive immune system reduces viral load but surprisingly does not drive observed viral evolution. Rather, the fitness (infectivity) of mutant variants is drawn from an exponential distribution in which most variants are slightly less infectious than their parents (nearly neutral evolution). This distribution was not largely different from either in vivo fitness distributions recorded beyond primary infection or in vitro distributions that are observed without adaptive immunity, suggesting the intrinsic viral fitness distribution may drive evolution. Simulated phylogenetic trees also agree with independent data and illuminate how phylogenetic inference must consider viral and immune-cell population dynamics to gain accurate mechanistic insights.

Immune-viral dynamics modeling for SARS-CoV-2 drug development

Coronavirus disease 2019 (COVID-19) global pandemic is caused by severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) viral infection, which can lead to pneumonia, lung injury, and death in susceptible populations. Understanding viral dynamics of SARS-CoV-2 is critical for development of effective treatments. An Immune-Viral Dynamics Model (IVDM) is developed to describe SARS-CoV-2 viral dynamics and COVID-19 disease progression. A dataset of 60 individual patients with COVID-19 with clinical viral load (VL) and reported disease severity were assembled from literature. Viral infection and replication mechanisms of SARS-CoV-2, viral-induced cell death, and time-dependent immune response are incorporated in the model to describe the dynamics of viruses and immune response. Disease severity are tested as a covariate to model parameters. The IVDM was fitted to the data and parameters were estimated using the nonlinear mixed-effect model. The model can adequately describe individual viral dynamics profiles, with disease severity identified as a covariate on infected cell death rate. The modeling suggested that it takes about 32.6 days to reach 50% of maximum cell-based immunity. Simulations based on virtual populations suggested a typical mild case reaches VL limit of detection (LOD) by 13 days with no treatment, a moderate case by 17 days, and a severe case by 41 days. Simulations were used to explore hypothetical treatments with different initiation time, disease severity, and drug effects to demonstrate the usefulness of such modeling in informing decisions. Overall, the IVDM modeling and simulation platform enables simulations for viral dynamics and treatment efficacy and can be used to aid in clinical pharmacokinetic/pharmacodynamic (PK/PD) and dose-efficacy response analysis for COVID-19 drug development.

Mechanistic Modeling of a Novel Oncolytic Virus, V937, to Describe Viral Kinetic and Dynamic Processes Following Intratumoral and Intravenous Administration

V937 is an investigational novel oncolytic non-genetically modified Kuykendall strain of Coxsackievirus A21 which is in clinical development for the treatment of advanced solid tumor malignancies. V937 infects and lyses tumor cells expressing the intercellular adhesion molecule I (ICAM-I) receptor. We integrated in vitro and in vivo data from six different preclinical studies to build a mechanistic model that allowed a quantitative analysis of the biological processes of V937 viral kinetics and dynamics, viral distribution to tumor, and anti-tumor response elicited by V937 in human xenograft models in immunodeficient mice following intratumoral and intravenous administration. Estimates of viral infection and replication which were calculated from in vitro experiments were successfully used to describe the tumor response in vivo under various experimental conditions. Despite the predicted high clearance rate of V937 in systemic circulation (t_1/2 = 4.3 min), high viral replication was observed in immunodeficient mice which resulted in tumor shrinkage with both intratumoral and intravenous administration. The described framework represents a step towards the quantitative characterization of viral distribution, replication, and oncolytic effect of a novel oncolytic virus following intratumoral and intravenous administrations in the absence of an immune response. This model may further be expanded to integrate the role of the immune system on viral and tumor dynamics to support the clinical development of oncolytic viruses.

Mechanistic basis of post-treatment control of SIV after anti-α4β7 antibody therapy

Treating macaques with an anti-α4β7 antibody under the umbrella of combination antiretroviral therapy (cART) during early SIV infection can lead to viral remission, with viral loads maintained at < 50 SIV RNA copies/ml after removal of all treatment in a subset of animals. Depletion of CD8⁺ lymphocytes in controllers resulted in transient recrudescence of viremia, suggesting that the combination of cART and anti-α4β7 antibody treatment led to a state where ongoing immune responses kept the virus undetectable in the absence of treatment. A previous mathematical model of HIV infection and cART incorporates immune effector cell responses and exhibits the property of two different viral load set-points. While the lower set-point could correspond to the attainment of long-term viral remission, attaining the higher set-point may be the result of viral rebound. Here we expand that model to include possible mechanisms of action of an anti-α4β7 antibody operating in these treated animals. We show that the model can fit the longitudinal viral load data from both IgG control and anti-α4β7 antibody treated macaques, suggesting explanations for the viral control associated with cART and an anti-α4β7 antibody treatment. This effective perturbation to the virus-host interaction can also explain observations in other nonhuman primate experiments in which cART and immunotherapy have led to post-treatment control or resetting of the viral load set-point. Interestingly, because the viral kinetics in the various treated animals differed—some animals exhibited large fluctuations in viral load after cART cessation—the model suggests that anti-α4β7 treatment could act by different primary mechanisms in different animals and still lead to post-treatment viral control. This outcome is nonetheless in accordance with a model with two stable viral load set-points, in which therapy can perturb the system from one set-point to a lower one through different biological mechanisms.

Some macaques treated with an anti-α4β7 monoclonal antibody along with antiretroviral therapy during the early stages of simian immunodeficiency virus infection had their viral load become undetectable (below 50 SIV RNA copies/ml) after all treatment was stopped, whereas animals not given the antibody all had their viral loads rebound to high levels. Using a mathematical model, we examined four potential ways in which the antibody could have altered the balance between viral growth and immune control to maintain an undetectable viral load. We show that a shift to controlled infection can occur through multiple biologically reasonable mechanisms of action of the anti-α4β7 antibody.

The CD8+ T Cell Noncytotoxic Antiviral Responses

The CD8+ T cell noncytotoxic antiviral response (CNAR) was discovered during studies of asymptomatic HIV-infected subjects more than 30 years ago. In contrast to CD8+ T cell cytotoxic lymphocyte (CTL) activity, CNAR suppresses HIV replication without target cell killing. This activity has characteristics of innate immunity: it acts on all retroviruses and thus is neither epitope specific nor HLA restricted. The HIV-associated CNAR does not affect other virus families. It is mediated, at least in part, by a CD8+ T cell antiviral factor (CAF) that blocks HIV transcription. A variety of assays used to measure CNAR/CAF and the effects on other retrovirus infections are described. Notably, CD8+ T cell noncytotoxic antiviral responses have now been observed with other virus families but are mediated by different cytokines. Characterizing the protein structure of CAF has been challenging despite many biologic, immunologic, and molecular studies. It represents a low-abundance protein that may be identified by future next-generation sequencing approaches. Since CNAR/CAF is a natural noncytotoxic activity, it could provide promising strategies for HIV/AIDS therapy, cure, and prevention.

IL-21 and IFNα therapy rescues terminally differentiated NK cells and limits SIV reservoir in ART-treated macaques

Unlike HIV infection, which progresses to AIDS absent suppressive anti-retroviral therapy, nonpathogenic infections in natural hosts, such African green monkeys, are characterized by a lack of gut microbial translocation and robust secondary lymphoid natural killer cell responses resulting in an absence of chronic inflammation and limited SIV dissemination in lymph node B-cell follicles. Here we report, using the pathogenic model of antiretroviral therapy-treated, SIV-infected rhesus macaques that sequential interleukin-21 and interferon alpha therapy generate terminally differentiated blood natural killer cells (NKG2a/clowCD16+) with potent human leukocyte antigen-E-restricted activity in response to SIV envelope peptides. This is in contrast to control macaques, where less differentiated, interferon gamma-producing natural killer cells predominate. The frequency and activity of terminally differentiated NKG2a/clowCD16+ natural killer cells correlates with a reduction of replication-competent SIV in lymph node during antiretroviral therapy and time to viral rebound following analytical treatment interruption. These data demonstrate that African green monkey-like natural killer cell differentiation profiles can be rescued in rhesus macaques to promote viral clearance in tissues.

CD8+ T cells fail to limit SIV reactivation following ART withdrawal until after viral amplification

To define the contribution of CD8+ T cell responses to control of SIV reactivation during and following antiretroviral therapy (ART), we determined the effect of long-term CD8+ T cell depletion using a rhesusized anti-CD8β monoclonal antibody on barcoded SIVmac239 dynamics on stable ART and after ART cessation in rhesus macaques (RMs). Among the RMs with full CD8+ T cell depletion in both blood and tissue, there were no significant differences in the frequency of viral blips in plasma, the number of SIV RNA+ cells and the average number of RNA copies/infected cell in tissue, and levels of cell-associated SIV RNA and DNA in blood and tissue relative to control-treated RMs during ART. Upon ART cessation, both CD8+ T cell-depleted and control RMs rebounded in fewer than 12 days, with no difference in the time to viral rebound or in either the number or growth rate of rebounding SIVmac239M barcode clonotypes. However, effectively CD8+ T cell-depleted RMs showed a stable, approximately 2-log increase in post-ART plasma viremia relative to controls. These results indicate that while potent antiviral CD8+ T cell responses can develop during ART-suppressed SIV infection, these responses effectively intercept post-ART SIV rebound only after systemic viral replication, too late to limit reactivation frequency or the early spread of reactivating SIV reservoirs.

Role of NKG2a/c+CD8+ T cells in pathogenic versus non-pathogenic SIV infections

Some viruses have established an equilibrium with their host. African green monkeys (AGM) display persistent high viral replication in the blood and intestine during Simian immunodeficiency virus (SIV) infection but resolve systemic inflammation after acute infection and lack intestinal immune or tissue damage during chronic infection. We show that NKG2_a/c⁺CD8⁺ T cells increase in the blood and intestine of AGM in response to SIVagm infection in contrast to SIVmac infection in macaques, the latter modeling HIV infection. NKG2_a/c⁺CD8⁺ T cells were not expanded in lymph nodes, and CXCR5⁺NKG2_a/c⁺CD8⁺ T cell frequencies further decreased after SIV infection. Genome-wide transcriptome analysis of NKG2_a/c⁺CD8⁺ T cells from AGM revealed the expression of NK cell receptors, and of molecules with cytotoxic effector, gut homing, and immunoregulatory and gut barrier function, including CD73. NKG2_a/c⁺CD8⁺ T cells correlated negatively with IL-23 in the intestine during SIVmac infection. The data suggest a potential regulatory role of NKG2_a/c⁺CD8⁺ T cells in intestinal inflammation during SIV/HIV infections.

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Molecular determination of NKG2a/c⁺CD8⁺ T cells in two species of nonhuman primates

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Tissue distribution of NKG2a/c⁺CD8⁺ T cell is profoundly sculpted by SIV infections

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Intestinal NKG2a/c⁺CD8⁺ T cells correlated negatively with IL-23 in SIV infection

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NKG2a/c⁺CD8⁺ T cells might play a protective gut barrier function in HIV/SIV infection

Development of a quantitative relationship between CAR-affinity, antigen abundance, tumor cell depletion and CAR-T cell expansion using a multiscale systems PK-PD model

The development of mechanism-based, multiscale pharmacokinetic–pharmacodynamic (PK-PD) models for chimeric antigen receptor (CAR)-T cells is needed to enable investigation of in vitro and in vivo correlation of CAR-T cell responses and to facilitate preclinical-to-clinical translation. Toward this goal, we first developed a cell-level in vitro PD model that quantitatively characterized CAR-T cell-induced target cell depletion, CAR-T cell expansion and cytokine release. The model accounted for key drug-specific (CAR-affinity, CAR-densities) and system-specific (antigen densities, E:T ratios) variables and was able to characterize comprehensive in vitro datasets from multiple affinity variants of anti-EGFR and anti-HER2 CAR-T cells. Next, a physiologically based PK (PBPK) model was developed to simultaneously characterize the biodistribution of untransduced T-cells, anti-EGFR CAR-T and anti-CD19 CAR-T cells in xenograft -mouse models. The proposed model accounted for the engagement of CAR-T cells with tumor cells at the site of action. Finally, an integrated PBPK-PD relationship was established to simultaneously characterize expansion of CAR-T cells and tumor growth inhibition (TGI) in xenograft mouse model, using datasets from anti-BCMA, anti-HER2, anti-CD19 and anti-EGFR CAR-T cells. Model simulations provided potential mechanistic insights toward the commonly observed multiphasic PK profile (i.e., rapid distribution, expansion, contraction and persistence) of CAR-T cells in the clinic. Model simulations suggested that CAR-T cells may have a steep dose-exposure relationship, and the apparent Cmax upon CAR-T cell expansion in blood may be more sensitive to patient tumor-burden than CAR-T dose levels. Global sensitivity analysis described the effect of other drug-specific parameters toward CAR-T cell expansion and TGI. The proposed modeling framework will be further examined with the clinical PK and PD data, and the learnings can be used to inform design and development of future CAR-T therapies.

Models of SIV rebound after treatment interruption that involve multiple reactivation events

In order to assess the efficacy of novel HIV-1 treatments leading to a functional cure, the time to viral rebound is frequently used as a surrogate endpoint. The longer the time to viral rebound, the more efficacious the therapy. In support of such an approach, mathematical models serve as a connection between the size of the latent reservoir and the time to HIV-1 rebound after treatment interruption. The simplest of such models assumes that a single successful latent cell reactivation event leads to observable viremia after a period of exponential viral growth. Here we consider a generalization developed by Pinkevych et al. and Hill et al. of this simple model in which multiple reactivation events can occur, each contributing to the exponential growth of the viral load. We formalize and improve the previous derivation of the dynamics predicted by this model, and use the model to estimate relevant biological parameters from SIV rebound data. We confirm a previously described effect of very early antiretroviral therapy (ART) initiation on the rate of recrudescence and the viral load growth rate after treatment interruption. We find that every day ART initiation is delayed results in a 39% increase in the recrudescence rate (95% credible interval: [18%, 62%]), and a 11% decrease of the viral growth rate (95% credible interval: [4%, 20%]). We show that when viral rebound occurs early relative to the viral load doubling time, a model with multiple successful reactivation events fits the data better than a model with only a single successful reactivation event.

Role of Dendritic Cells in Exposing Latent HIV-1 for the Kill

The development of effective yet nontoxic strategies to target the latent human immunodeficiency virus-1 (HIV-1) reservoir in antiretroviral therapy (ART)-suppressed individuals poses a critical barrier to a functional cure. The ‘kick and kill’ approach to HIV eradication entails proviral reactivation during ART, coupled with generation of cytotoxic T lymphocytes (CTLs) or other immune effectors equipped to eliminate exposed infected cells. Pharmacological latency reversal agents (LRAs) that have produced modest reductions in the latent reservoir ex vivo have not impacted levels of proviral DNA in HIV-infected individuals. An optimal cure strategy incorporates methods that facilitate sufficient antigen exposure on reactivated cells following the induction of proviral gene expression, as well as the elimination of infected targets by either polyfunctional HIV-specific CTLs or other immune-based strategies. Although conventional dendritic cells (DCs) have been used extensively for the purpose of inducing antigen-specific CTL responses in HIV-1 clinical trials, their immunotherapeutic potential as cellular LRAs has been largely ignored. In this review, we discuss the challenges associated with current HIV-1 eradication strategies, as well as the unharnessed potential of ex vivo-programmed DCs for both the ‘kick and kill’ of latent HIV-1.

Specific Activation In Vivo of HIV-1 by a Bromodomain Inhibitor from Monocytic Cells in Humanized Mice under Antiretroviral Therapy

Combination antiretroviral therapy (cART) effectively suppresses HIV-1 replication and enables HIV‑infected individuals to live long, productive lives. However, the persistence of HIV-1 reservoirs of both T and myeloid cells with latent or low-replicating HIV-1 in patients under cART makes HIV-1 infection an incurable disease. Recent studies have focused on the development of strategies to activate and purge these reservoirs. Bromodomain and extraterminal domain proteins (BETs) are epigenetic readers involved in modulating gene expression. Several bromodomain inhibitors (BETi) are reported to activate viral transcription in vitro in HIV-1 latency cell lines in a P-TEFb (CDK9/cyclin T1)-dependent manner. Little is known about BETi efficacy in activating HIV-1 reservoir cells under cART in vivo Here we report that a BETi (I-BET151) efficiently activated HIV-1 reservoirs under effective cART in humanized mice in vivo Interestingly, I-BET151 during suppressive cART in vivo activated HIV-1 gene expression only in monocytic cells and not in CD4⁺ T cells. We further demonstrate that BETi preferentially enhanced HIV-1 gene expression in monocytic cells rather than in T cells and that whereas CDK9 was involved in activating HIV-1 by I-BET151 in both monocytic and T cells, CDK2 enhanced HIV-1 transcription in monocytic cells but inhibited it in T cells. Our findings reveal a role for CDK2 in differential modulation of HIV-1 gene expression in myeloid cells and in T cells and provide a novel strategy to reactivate monocytic reservoirs with BETi during cART.IMPORTANCE Bromodomain inhibitors have been reported to activate HIV-1 transcription in vitro, but their effect on activation of HIV-1 reservoirs during cART in vivo is unclear. We found that BETi (I-BET151) treatment reactivated HIV-1 gene expression in humanized mice during suppressive cART. Interestingly, I-BET151 preferentially reactivated HIV-1 gene expression in monocytic cells, but not in CD4 T cells, in cART-treated mice. Furthermore, I-BET151 significantly increased HIV-1 transcription in monocytic cells, but not in HIV-1-infected CD4 T cells, via CDK2-dependent mechanisms. Our findings suggest that BETi can preferentially activate monocytic HIV-1 reservoir cells and that a combination of reservoir activation agents targeting different cell types and pathways is needed to achieve reactivation of different HIV-1 reservoir cells during cART.

Cat and Mouse: HIV Transcription in Latency, Immune Evasion and Cure/Remission Strategies

There is broad scientific and societal consensus that finding a cure for HIV infection must be pursued. The major barrier to achieving a cure for HIV/AIDS is the capacity of the HIV virus to avoid both immune surveillance and current antiretroviral therapy (ART) by rapidly establishing latently infected cell populations, termed latent reservoirs. Here, we provide an overview of the rapidly evolving field of HIV cure/remission research, highlighting recent progress and ongoing challenges in the understanding of HIV reservoirs, the role of HIV transcription in latency and immune evasion. We review the major approaches towards a cure that are currently being explored and further argue that small molecules that inhibit HIV transcription, and therefore uncouple HIV gene expression from signals sent by the host immune response, might be a particularly promising approach to attain a cure or remission. We emphasize that a better understanding of the game of "cat and mouse" between the host immune system and the HIV virus is a crucial knowledge gap to be filled in both cure and vaccine research.

Towards multiscale modeling of the CD8+ T cell response to viral infections

The CD8⁺ T cell response is critical to the control of viral infections. Yet, defining the CD8⁺ T cell response to viral infections quantitatively has been a challenge. Following antigen recognition, which triggers an intracellular signaling cascade, CD8⁺ T cells can differentiate into effector cells, which proliferate rapidly and destroy infected cells. When the infection is cleared, they leave behind memory cells for quick recall following a second challenge. If the infection persists, the cells may become exhausted, retaining minimal control of the infection while preventing severe immunopathology. These activation, proliferation and differentiation processes as well as the mounting of the effector response are intrinsically multiscale and collective phenomena. Remarkable experimental advances in the recent years, especially at the single cell level, have enabled a quantitative characterization of several underlying processes. Simultaneously, sophisticated mathematical models have begun to be constructed that describe these multiscale phenomena, bringing us closer to a comprehensive description of the CD8⁺ T cell response to viral infections. Here, we review the advances made and summarize the challenges and opportunities ahead. This article is categorized under: Analytical and Computational Methods > Computational Methods Biological Mechanisms > Cell Fates Biological Mechanisms > Cell Signaling Models of Systems Properties and Processes > Mechanistic Models.

Probabilistic control of HIV latency and transactivation by the Tat gene circuit

The reservoir of HIV latently infected cells is the major obstacle for eradication of HIV infection. The "shock-and-kill" strategy proposed earlier aims to reduce the reservoir by activating cells out of latency. While the intracellular HIV Tat gene circuit is known to play important roles in controlling latency and its transactivation in HIV-infected cells, the detailed control mechanisms are not well understood. Here we study the mechanism of probabilistic control of the latent and the transactivated cell phenotypes of HIV-infected cells. We reconstructed the probability landscape, which is the probability distribution of the Tat gene circuit states, by directly computing the exact solution of the underlying chemical master equation. Results show that the Tat circuit exhibits a clear bimodal probability landscape (i.e., there are two distinct probability peaks, one associated with the latent cell phenotype and the other with the transactivated cell phenotype). We explore potential modifications to reactions in the Tat gene circuit for more effective transactivation of latent cells (i.e., the shock-and-kill strategy). Our results suggest that enhancing Tat acetylation can dramatically increase Tat and viral production, while increasing the Tat-transactivation response binding affinity can transactivate latent cells more rapidly than other manipulations. Our results further explored the "block and lock" strategy toward a functional cure for HIV. Overall, our study demonstrates a general approach toward discovery of effective therapeutic strategies and druggable targets by examining control mechanisms of cell phenotype switching via exactly computed probability landscapes of reaction networks.