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

Plasma lipidomic alterations during pathogenic SIV infection with and without antiretroviral therapy

Introduction

Lipid profiles change in human immunodeficiency virus (HIV) infection and correlate with inflammation. Lipidomic alterations are impacted by multiple non-HIV-related behavioral risk factors; thus, use of animal models in which these behavioral factors are controlled may inform on the specific lipid changes induced by simian immunodeficiency virus (SIV) infection and/or antiretroviral therapy (ART).

Methods

Using ultrahigh Performance Liquid Chromatography-Tandem Mass Spectroscopy, we assessed and compared (ANOVA) longitudinal lipid changes in naïve and ART-treated SIV-infected pigtailed macaques (PTMs). Key parameters of infection (IL-6, TNFa, D-dimer, CRP and CD4+ T cell counts) were correlated (Spearman) with lipid concentrations at critical time points of infection and treatment.

Results

Sphingomyelins (SM) and lactosylceramides (LCER) increased during acute infection, returning to baseline during chronic infection; Hexosylceramides (HCER) increased throughout infection, being normalized with prolonged ART; Phosphatidylinositols (PI) and lysophosphatidylcholines (LPC) decreased with SIV infection and did not return to normal with ART; Phosphatidylethanolamines (PE), lysophosphatidylethanolamines (LPE) and phosphatidylcholines (PC) were unchanged by SIV infection, yet significantly decreased throughout ART. Specific lipid species (SLS) were also substantially modified by SIV and/or ART in most lipid classes. In conclusion, using a metabolically controlled model, we identified specific lipidomics signatures of SIV infection and/or ART, some of which were similar to people living with HIV (PWH). Many SLS were identical to those involved in development of organ dysfunctions encountered in virally suppressed individuals. Lipid changes also correlated with markers of disease progression, inflammation and coagulation.

Discussion

Our data suggest that lipidomic profile alterations contribute to residual systemic inflammation and comorbidities seen in HIV/SIV infections and therefore may be used as biomarkers of SIV/HIV comorbidities. Further exploration into the benefits of interventions targeting dyslipidemia is needed for the prevention HIV-related comorbidities.

Advances in the mathematical modeling of posttreatment control of HIV-1

PURPOSE OF REVIEW

Several new intervention strategies have shown significant improvements over antiretroviral therapy (ART) in eliciting lasting posttreatment control (PTC) of HIV-1. Advances in mathematical modelling have offered mechanistic insights into PTC and the workings of these interventions. We review these advances.

RECENT FINDINGS

Broadly neutralizing antibody (bNAb)-based therapies have shown large increases over ART in the frequency and the duration of PTC elicited. Early viral dynamics models of PTC with ART have been advanced to elucidate the underlying mechanisms, including the role of CD8+ T cells. These models characterize PTC as an alternative set-point, with low viral load, and predict routes to achieving it. Large-scale omic datasets have offered new insights into viral and host factors associated with PTC. Correspondingly, new classes of models, including those using learning techniques, have helped exploit these datasets and deduce causal links underlying the associations. Models have also offered insights into therapies that either target the proviral reservoir, modulate immune responses, or both, assessing their translatability.

SUMMARY

Advances in mathematical modeling have helped better characterize PTC, elucidated and quantified mechanisms with which interventions elicit it, and informed translational efforts.

Memory stem CD8+T cells in HIV/Mtb mono- and co-infection: characteristics, implications, and clinical significance

Human immunodeficiency Virus (HIV) and Mycobacterium tuberculosis (Mtb) co-infection presents a significant public health challenge worldwide. Comprehensive assessment of the immune response in HIV/Mtb co-infection is complex and challenging. CD8+T cells play a pivotal role in the adaptive immune response to both HIV and Mtb. The differentiation of CD8+T cells follow a hierarchical pattern, with varying degrees of exhaustion throughout the process. Memory stem T cells (TSCM cells) is at the apex of the memory T lymphocyte system, which has recently emerged as a promising target in immunotherapy. In this context, we discuss the alterations of CD8+TSCM cells in HIV/Mtb mono- and co-infection, their implications and clinical significance, and potential for improving immunotherapy.

Trade-off between the antiviral and vaccinal effects of antibody therapy in the humoral response to HIV

Antibody therapy for HIV-1 infection exerts two broad effects: a drug-like, antiviral effect, which rapidly lowers the viral load, and a vaccinal effect, which may control the viral load long-term by improving the immune response. Here, we elucidate a trade-off between these two effects as they pertain to the humoral response, which may compromise antibody therapy aimed at eliciting long-term HIV-1 remission. We developed a multi-scale computational model that combined within-host viral dynamics and stochastic simulations of the germinal centre (GC) reaction, enabling simultaneous quantification of the antiviral and vaccinal effects of antibody therapy. The model predicted that increasing antibody dosage or antibody-antigen affinity increased immune complex formation and enhanced GC output. Beyond a point, however, a strong antiviral effect reduced antigen levels substantially, extinguishing GCs and limiting the humoral response. We found signatures of this trade-off in clinical studies. Accounting for the trade-off could be important in optimizing antibody therapy for HIV-1 remission.

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.

Spatial technologies to evaluate the HIV-1 reservoir and its microenvironment in the lymph node

The presence of the HIV-1 reservoir, a group of immune cells that contain intact, integrated, and replication-competent proviruses, is a major challenge to cure HIV-1. HIV-1 reservoir cells are largely unaffected by the cytopathic effects of viruses, antiviral immune responses, or antiretroviral therapy (ART). The HIV-1 reservoir is seeded early during HIV-1 infection and augmented during active viral replication. CD4+ T cells are the primary target for HIV-1 infection, and recent studies suggest that memory T follicular helper cells within the lymph node, more precisely in the B cell follicle, harbor integrated provirus, which contribute to viral rebound upon ART discontinuation. The B cell follicle, more specifically the germinal center, possesses a unique environment because of its distinct property of being partly immune privileged, potentially allowing HIV-1-infected cells within the lymph nodes to be protected from CD8+ T cells. This modified immune response in the germinal center of the follicle is potentially explained by the exclusion of CD8+ T cells and the presence of T regulatory cells at the junction of the follicle and extrafollicular region. The proviral makeup of HIV-1-infected cells is similar in lymph nodes and blood, suggesting trafficking between these compartments. Little is known about the cell-to-cell interactions, microenvironment of HIV-1-infected cells in the follicle, and trafficking between the lymph node follicle and other body compartments. Applying a spatiotemporal approach that integrates genomics, transcriptomics, and proteomics to investigate the HIV-1 reservoir and its neighboring cells in the lymph node has promising potential for informing HIV-1 cure efforts.

Follicular Immune Landscaping Reveals a Distinct Profile of FOXP3hiCD4hi T Cells in Treated Compared to Untreated HIV

Follicular helper CD4hi T cells (TFH) are a major cellular pool for the maintenance of the HIV reservoir. Therefore, the delineation of the follicular (F)/germinal center (GC) immune landscape will significantly advance our understanding of HIV pathogenesis. We have applied multiplex confocal imaging, in combination with the relevant computational tools, to investigate F/GC in situ immune dynamics in viremic (vir-HIV), antiretroviral-treated (cART HIV) People Living With HIV (PLWH) and compare them to reactive, non-infected controls. Lymph nodes (LNs) from viremic and cART PLWH could be further grouped based on their TFH cell densities in high-TFH and low-TFH subgroups. These subgroups were also characterized by different in situ distributions of PD1hi TFH cells. Furthermore, a significant accumulation of follicular FOXP3hiCD4hi T cells, which were characterized by a low scattering in situ distribution profile and strongly correlated with the cell density of CD8hi T cells, was found in the cART-HIV low-TFH group. An inverse correlation between plasma viral load and LN GrzBhiCD8hi T and CD16hiCD15lo cells was found. Our data reveal the complex GC immune landscaping in HIV infection and suggest that follicular FOXP3hiCD4hi T cells could be negative regulators of TFH cell prevalence in cART-HIV.

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.

Comparative analysis of within-host dynamics of acute infection and viral rebound dynamics in postnatally SHIV-infected ART-treated infant rhesus macaques

Viral dynamics of acute HIV infection and HIV rebound following suspension of antiretroviral therapy may be qualitatively similar but must differ given, for one, development of adaptive immune responses. Understanding the differences of acute HIV infection and viral rebound dynamics in pediatric populations may provide insights into the mechanisms of viral control with potential implications for vaccine design and the development of effective targeted therapeutics for infants and children. Mathematical models have been a crucial tool to elucidate the complex processes driving viral infections within the host. Traditionally, acute HIV infection has been modeled with a standard model of viral dynamics initially developed to explore viral decay during treatment, while viral rebound has necessitated extensions of that standard model to incorporate explicit immune responses. Previous efforts to fit these models to viral load data have underscored differences between the two infection stages, such as increased viral clearance rate and increased death rate of infected cells during rebound. However, these findings have been predicated on viral load measurements from disparate adult individuals. In this study, we aim to bridge this gap, in infants, by comparing the dynamics of acute infection and viral rebound within the same individuals by leveraging an infant nonhuman primate Simian/Human Immunodeficiency Virus (SHIV) infection model. Ten infant Rhesus macaques (RMs) orally challenged with SHIV.C.CH505 375H dCT and given ART at 8 weeks post-infection. These infants were then monitored for up to 60 months post-infection with serial viral load and immune measurements. We use the HIV standard viral dynamics model fitted to viral load measurements in a nonlinear mixed effects framework. We find that the primary difference between acute infection and rebound is the increased death rate of infected cells during rebound. We use these findings to generate hypotheses on the effects of adaptive immune responses. We leverage these findings to formulate hypotheses to elucidate the observed results and provide arguments to support the notion that delayed viral rebound is characterized by a stronger CD8+ T cell response.

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.

Incorporating Intracellular Processes in Virus Dynamics Models

In-host models have been essential for understanding the dynamics of virus infection inside an infected individual. When used together with biological data, they provide insight into viral life cycle, intracellular and cellular virus-host interactions, and the role, efficacy, and mode of action of therapeutics. In this review, we present the standard model of virus dynamics and highlight situations where added model complexity accounting for intracellular processes is needed. We present several examples from acute and chronic viral infections where such inclusion in explicit and implicit manner has led to improvement in parameter estimates, unification of conclusions, guidance for targeted therapeutics, and crossover among model systems. We also discuss trade-offs between model realism and predictive power and highlight the need of increased data collection at finer scale of resolution to better validate complex models.

Antibody-mediated depletion of select leukocyte subsets in blood and tissue of nonhuman primates

Understanding the immunological control of pathogens requires a detailed evaluation of the mechanistic contributions of individual cell types within the immune system. While knockout mouse models that lack certain cell types have been used to help define the role of those cells, the biological and physiological characteristics of mice do not necessarily recapitulate that of a human. To overcome some of these differences, studies often look towards nonhuman primates (NHPs) due to their close phylogenetic relationship to humans. To evaluate the immunological role of select cell types, the NHP model provides distinct advantages since NHP more closely mirror the disease manifestations and immunological characteristics of humans. However, many of the experimental manipulations routinely used in mice (e.g., gene knock-out) cannot be used with the NHP model. As an alternative, the in vivo infusion of monoclonal antibodies that target surface proteins on specific cells to either functionally inhibit or deplete cells can be a useful tool. Such depleting antibodies have been used in NHP studies to address immunological mechanisms of action. In these studies, the extent of depletion has generally been reported for blood, but not thoroughly assessed in tissues. Here, we evaluated four depleting regimens that primarily target T cells in NHP: anti-CD4, anti-CD8α, anti-CD8β, and immunotoxin-conjugated anti-CD3. We evaluated these treatments in healthy unvaccinated and IV BCG-vaccinated NHP to measure the extent that vaccine-elicited T cells - which may be activated, increased in number, or resident in specific tissues - are depleted compared to resting populations in unvaccinated NHPs. We report quantitative measurements of in vivo depletion at multiple tissue sites providing insight into the range of cell types depleted by a given mAb. While we found substantial depletion of target cell types in blood and tissue of many animals, residual cells remained, often residing within tissue. Notably, we find that animal-to-animal variation is substantial and consequently studies that use these reagents should be powered accordingly.