Modeling HIV persistence, the latent reservoir, and viral blips

Mathematical analysis of an HIV latent infection model including both virus-to-cell infection and cell-to-cell transmission

HIV can infect cells via virus-to-cell infection or cell-to-cell viral transmission. These two infection modes may occur in a synergistic way and facilitate viral spread within an infected individual. In this paper, we developed an HIV latent infection model including both modes of transmission and time delays between viral entry and integration or viral production. We analysed the model by defining the basic reproductive number, showing the existence, positivity and boundedness of the solution, and proving the local and global stability of the infection-free and infected steady states. Numerical simulations have been performed to illustrate the theoretical results and evaluate the effects of time delays and fractions of infection leading to latency on the virus dynamics. The estimates of the relative contributions to the HIV latent reservoir and the virus population from the two modes of transmission have also been provided.

Pyroptosis, superinfection, and the maintenance of the latent reservoir in HIV-1 infection

A long-lived reservoir of latently infected T cells prevents antiretroviral therapy from eliminating HIV-1 infection. Furthering our understanding of the dynamics of latency generation and maintenance is therefore vital to improve treatment outcome. Using mathematical models and experiments, we suggest that the death of latently infected cells brought about by pyroptosis, or to a lesser extent by superinfection, might be key mechanisms to account for the size and composition of the latent reservoir. Pyroptosis is a form of cell death that occurs in a resting (and thus latently infected) T cell when a productively infected cell attempts cell-to-cell transmission of virus. Superinfection of latently infected cells by productive virus could similarly remove those cells through active virus replication and resulting cytopathicity. The mathematical models presented can explain a number of previously published clinical observations including latent reservoir size and the relationships to viral load in acute HIV infection, measurements of the latent reservoir in chronic infection, and the replacement of wild-type virus by CTL escape mutants within the latent reservoir. Basic virus dynamics models of latency that do not take into account pyroptosis, superinfection, or other potential complexities cannot account for the data.

An HIV model with age-structured latently infected cells

HIV latency remains a major obstacle to viral elimination. The activation rate of latently infected cells may depend on the age of latent infection. In this paper, we develop a model of HIV infection including age-structured latently infected cells. We mathematically analyse the model and use numerical simulations with different activation functions to show that the model can explain the persistence of low-level viremia and the latent reservoir stability in patients on therapy. Sensitivity tests suggest that the model is robust to the changes of most parameters but is sensitive to the relative magnitude of the net generation rate and the long-term activation rate of latently infected cells. To reduce the sensitivity, we extend the model to include homeostatic proliferation of latently infected cells. The new model is robust in reproducing the long-term dynamics of the virus and latently infected cells observed in patients receiving prolonged combination therapy.

Analysis of HIV models with two time delays

Time delays can affect the dynamics of HIV infection predicted by mathematical models. In this paper, we studied two mathematical models each with two time delays. In the first model with HIV latency, one delay is the time between viral entry into a cell and the establishment of HIV latency, and the other delay is the time between cell infection and viral production. We defined the basic reproductive number and showed the local and global stability of the steady states. Numerical simulations were performed to evaluate the influence of time delays on the dynamics. In the second model with HIV immune response, one delay is the time between cell infection and viral production, and the other delay is the time needed for the adaptive immune response to emerge to control viral replication. With two positive delays, we obtained the stability crossing curves for the model, which were shown to be a series of open-ended curves.

HIV-1 persistent viremia is frequently followed by episodes of low-level viremia

After the start of antiretroviral therapy (ART), plasma HIV-RNA levels should fall below the limit of detection (LOD) within 24 weeks. Hence, the prolonged decline of HIV-RNA after ART initiation is defined as persistent viremia (PV). In this retrospective study, we analyzed factors associated with PV. Next-generation sequencing of viral RNA/DNA was performed to study viral evolution and the emergence of drug-resistance mutations in HIV-infected patients with PV (n = 20). In addition, HIV-DNA species, immunological parameters, and clinical data of the patients were analyzed. We found that the possible causes for PV were divers, and both virologic and host parameters of this particular cohort were heterogeneous. We identified viruses with therapy-associated DRMs in six patients (30%); two of these were detected as minority variants. Five patients had sub-optimal drug levels (25%) and the baseline plasma viral loads were relatively high. Strikingly, we observed that >40% of the PV patients finally reaching HIV levels below the LOD later on showed up with episodes of low-level viremia (LLV). However, the amount of PBMC derived HIV-DNA species was not correlated with the likelihood of LLV after PV. According to our data, we conclude that drug-resistant viruses, sub-optimal drug level, and high baseline viral loads might be probable reasons for the prolonged RNA decline only in a sub-set of patients. In the absence of emerging DRMs and/or compliance issues, the clinical implications of PV remain unclear; however, PV appears to be a risk factor for episodes of LLV.

Influence of raltegravir intensification on viral load and 2-LTR dynamics in HIV patients on suppressive antiretroviral therapy

Antiretroviral therapy can suppress HIV-1 plasma viral load to below the detection limit but cannot eradicate the virus. Whether residual ongoing viral replication persists during suppressive therapy remains unclear. A few clinical studies showed that treatment intensification with an additional drug led to a lower viral load or an increase in 2-LTR (long terminal repeat), a marker for ongoing viral replication. However, some other studies found no change in the viral load and 2-LTR. In this paper, we developed multi-stage models to evaluate the influence of treatment intensification with the integrase inhibitor raltegravir on viral load and 2-LTR dynamics in HIV patients under suppressive therapy. We analyzed one model and obtained the local and global stability of the steady states. The model and its variation predict that raltegravir intensification induces a very minor decrease in the viral load and a minor increase in 2-LTR. We also compared modeling prediction with the 2-LTR data in a raltegravir intensification study. To achieve the 2-LTR increase observed in some patients, the level of viral replication needs to be substantially high, which is inconsistent with the sustained viral suppression in patients during treatment intensification. These modeling results, together with the theoretical estimate of the upper bound of the 2-LTR increase, suggest that treatment intensification with raltegravir has a minor effect on the plasma viremia and 2-LTR in patients under suppressive therapy. Other treatment strategies have to be developed for the cure or functional control of the infection.

Modelling and Simulation of the Dynamics of the Antigen-Specific T Cell Response Using Variable Structure Control Theory

Experimental and mathematical studies in immunology have revealed that the dynamics of the programmed T cell response to vigorous infection can be conveniently modelled using a sigmoidal or a discontinuous immune response function. This paper hypothesizes strong synergies between this existing work and the dynamical behaviour of engineering systems with a variable structure control (VSC) law. These findings motivate the interpretation of the immune system as a variable structure control system. It is shown that dynamical properties as well as conditions to analytically assess the transition from health to disease can be developed for the specific T cell response from the theory of variable structure control. In particular, it is shown that the robustness properties of the specific T cell response as observed in experiments can be explained analytically using a VSC perspective. Further, the predictive capacity of the VSC framework to determine the T cell help required to overcome chronic Lymphocytic Choriomeningitis Virus (LCMV) infection is demonstrated. The findings demonstrate that studying the immune system using variable structure control theory provides a new framework for evaluating immunological dynamics and experimental observations. A modelling and simulation tool results with predictive capacity to determine how to modify the immune response to achieve healthy outcomes which may have application in drug development and vaccine design.

Stochastic modelling of the eradication of the HIV-1 infection by stimulation of latently infected cells in patients under highly active anti-retroviral therapy

HIV-1 infected patients are effectively treated with highly active anti-retroviral therapy (HAART). Whilst HAART is successful in keeping the disease at bay with average levels of viral load well below the detection threshold of standard clinical assays, it fails to completely eradicate the infection, which persists due to the emergence of a latent reservoir with a half-life time of years and is immune to HAART. This implies that life-long administration of HAART is, at the moment, necessary for HIV-1-infected patients, which is prone to drug resistance and cumulative side effects as well as imposing a considerable financial burden on developing countries, those more afflicted by HIV, and public health systems. The development of therapies which specifically aim at the removal of this latent reservoir has become a focus of much research. A proposal for such therapy consists of elevating the rate of activation of the latently infected cells: by transferring cells from the latently infected reservoir to the active infected compartment, more cells are exposed to the anti-retroviral drugs thus increasing their effectiveness. In this paper, we present a stochastic model of the dynamics of the HIV-1 infection and study the effect of the rate of latently infected cell activation on the average extinction time of the infection. By analysing the model by means of an asymptotic approximation using the semi-classical quasi steady state approximation (QSS), we ascertain that this therapy reduces the average life-time of the infection by many orders of magnitudes. We test the accuracy of our asymptotic results by means of direct simulation of the stochastic process using a hybrid multi-scale Monte Carlo scheme.

Metabolic profiling during HIV-1 and HIV-2 infection of primary human monocyte-derived macrophages

We evaluated cellular metabolism profiles of HIV-1 and HIV-2 infected primary human monocyte-derived macrophages (MDMs). First, HIV-2 GL-AN displays faster production kinetics and greater amounts of virus as compared to HIV-1s: YU-2, 89.6 and JR-CSF. Second, quantitative LC-MS/MS metabolomics analysis demonstrates very similar metabolic profiles in glycolysis and TCA cycle metabolic intermediates between HIV-1 and HIV-2 infected macrophages, with a few notable exceptions. The most striking metabolic change in MDMs infected with HIV-2 relative to HIV-1-infected MDMs was the increased levels of quinolinate, a metabolite in the tryptophan catabolism pathway that has been linked to HIV/AIDS pathogenesis. Third, both HIV-1 and HIV-2 infected MDMs showed elevated levels of ribose-5-phosphate, a key metabolic component in nucleotide biosynthesis. Finally, HIV-2 infected MDMs display increased dNTP concentrations as predicted by Vpx-mediated SAMHD1 degradation. Collectively, these data show differential metabolic changes during HIV-1 and HIV-2 infection of macrophages.

EPICE-HIV: An Epidemiologic Cost-Effectiveness Model for HIV Treatment

The goal of this research was to establish a new and innovative framework for cost-effectiveness modeling of HIV-1 treatment, simultaneously considering both clinical and epidemiological outcomes. EPICE-HIV is a multi-paradigm model based on a within-host micro-simulation model for the disease progression of HIV-1 infected individuals and an agent-based sexual contact network (SCN) model for the transmission of HIV-1 infection. It includes HIV-1 viral dynamics, CD4⁺ T cell infection rates, and pharmacokinetics/pharmacodynamics modeling. Disease progression of HIV-1 infected individuals is driven by the interdependent changes in CD4⁺ T cell count, changes in plasma HIV-1 RNA, accumulation of resistance mutations and adherence to treatment. The two parts of the model are joined through a per-sexual-act and viral load dependent probability of disease transmission in HIV-discordant couples. Internal validity of the disease progression part of the model is assessed and external validity is demonstrated in comparison to the outcomes observed in the STaR randomized controlled clinical trial. We found that overall adherence to treatment and the resulting pattern of treatment interruptions are key drivers of HIV-1 treatment outcomes. Our model, though largely independent of efficacy data from RCT, was accurate in producing 96-week outcomes, qualitatively and quantitatively comparable to the ones observed in the STaR trial. We demonstrate that multi-paradigm micro-simulation modeling is a promising tool to generate evidence about optimal policy strategies in HIV-1 treatment, including treatment efficacy, HIV-1 transmission, and cost-effectiveness analysis.

Dynamics of an HIV Model with Multiple Infection Stages and Treatment with Different Drug Classes

Highly active antiretroviral therapy can effectively control HIV replication in infected individuals. Some clinical and modeling studies suggested that viral decay dynamics may depend on the inhibited stages of the viral replication cycle. In this paper, we develop a general mathematical model incorporating multiple infection stages and various drug classes that can interfere with specific stages of the viral life cycle. We derive the basic reproductive number and obtain the global stability results of steady states. Using several simple cases of the general model, we study the effect of various drug classes on the dynamics of HIV decay. When drugs are assumed to be 100% effective, drugs acting later in the viral life cycle lead to a faster or more rapid decay in viremia. This is consistent with some patient and experimental data, and also agrees with previous modeling results. When drugs are not 100% effective, the viral decay dynamics are more complicated. Without a second population of long-lived infected cells, the viral load decline can have two phases if drugs act at an intermediate stage of the viral replication cycle. The slopes of viral load decline depend on the drug effectiveness, the death rate of infected cells at different stages, and the transition rate of infected cells from one to the next stage. With a second population of long-lived infected cells, the viral load decline can have three distinct phases, consistent with the observation in patients receiving antiretroviral therapy containing the integrase inhibitor raltegravir. We also fit modeling prediction to patient data under efavirenz (a nonnucleoside reverse-transcriptase inhibitor) and raltegravir treatment. The first-phase viral load decline under raltegravir therapy is longer than that under efavirenz, resulting in a lower viral load at initiation of the second-phase decline in patients taking raltegravir. This explains why patients taking a raltegravir-based therapy were faster to achieve viral suppression than those taking an efavirenz-based therapy. Taken together, this work provides a quantitative and systematic comparison of the effect of different drug classes on HIV decay dynamics and can explain the viral load decline in HIV patients treated with raltegravir-containing regimens.

Modeling the Slow CD4+ T Cell Decline in HIV-Infected Individuals

The progressive loss of CD4+ T cell population is the hallmark of HIV-1 infection but the mechanism underlying the slow T cell decline remains unclear. Some recent studies suggested that pyroptosis, a form of programmed cell death triggered during abortive HIV infection, is associated with the release of inflammatory cytokines, which can attract more CD4+ T cells to be infected. In this paper, we developed mathematical models to study whether this mechanism can explain the time scale of CD4+ T cell decline during HIV infection. Simulations of the models showed that cytokine induced T cell movement can explain the very slow decline of CD4+ T cells within untreated patients. The long-term CD4+ T cell dynamics predicted by the models were shown to be consistent with available data from patients in Rio de Janeiro, Brazil. Highly active antiretroviral therapy has the potential to restore the CD4+ T cell population but CD4+ response depends on the effectiveness of the therapy, when the therapy is initiated, and whether there are drug sanctuary sites. The model also showed that chronic inflammation induced by pyroptosis may facilitate persistence of the HIV latent reservoir by promoting homeostatic proliferation of memory CD4+ cells. These results improve our understanding of the long-term T cell dynamics in HIV-1 infection, and support that new treatment strategies, such as the use of caspase-1 inhibitors that inhibit pyroptosis, may maintain the CD4+ T cell population and reduce the latent reservoir size.

The CD4+ T cell population within HIV-infected individuals declines slowly as disease progresses. When CD4+ cells drop to below 200 cells/ul, the infection is usually considered to enter the late stage, i.e., acquired immune deficiency syndrome (AIDS). CD4+ T cell depletion can take many years but the biological events underlying such slow decline are not well understood. Some studies showed that the majority of infected T cells in lymph nodes die by pyroptosis, a form of programmed cell death, which can release inflammatory signals attracting more CD4+ T cells to be infected. We developed mathematical models to describe this process and explored whether they can generate the long-term CD4+ T cell decline. We showed that pyroptosis induced cell movement can explain the slow time scale of CD4+ T cell depletion and that pyroptosis may also contribute to the persistence of latently infected cells, which represent a major obstacle to HIV eradication. The modeling prediction agrees with patient data in Rio de Janeiro, Brazil. These results suggest that a combination of current treatment regimens and caspase-1 inhibitor that can inhibit pyroptosis might provide a new way to maintain the CD4+ T cell population and eradicate the HIV latent reservoir.

Recombination Enhances HIV-1 Envelope Diversity by Facilitating the Survival of Latent Genomic Fragments in the Plasma Virus Population

HIV-1 is subject to immune pressure exerted by the host, giving variants that escape the immune response an advantage. Virus released from activated latent cells competes against variants that have continually evolved and adapted to host immune pressure. Nevertheless, there is increasing evidence that virus displaying a signal of latency survives in patient plasma despite having reduced fitness due to long-term immune memory. We investigated the survival of virus with latent envelope genomic fragments by simulating within-host HIV-1 sequence evolution and the cycling of viral lineages in and out of the latent reservoir. Our model incorporates a detailed mutation process including nucleotide substitution, recombination, latent reservoir dynamics, diversifying selection pressure driven by the immune response, and purifying selection pressure asserted by deleterious mutations. We evaluated the ability of our model to capture sequence evolution in vivo by comparing our simulated sequences to HIV-1 envelope sequence data from 16 HIV-infected untreated patients. Empirical sequence divergence and diversity measures were qualitatively and quantitatively similar to those of our simulated HIV-1 populations, suggesting that our model invokes realistic trends of HIV-1 genetic evolution. Moreover, reconstructed phylogenies of simulated and patient HIV-1 populations showed similar topological structures. Our simulation results suggest that recombination is a key mechanism facilitating the persistence of virus with latent envelope genomic fragments in the productively infected cell population. Recombination increased the survival probability of latent virus forms approximately 13-fold. Prevalence of virus with latent fragments in productively infected cells was observed in only 2% of simulations when we ignored recombination, while the proportion increased to 27% of simulations when we allowed recombination. We also found that the selection pressures exerted by different fitness landscapes influenced the shape of phylogenies, diversity trends, and survival of virus with latent genomic fragments. Our model predicts that the persistence of latent genomic fragments from multiple different ancestral origins increases sequence diversity in plasma for reasonable fitness landscapes.

Increasing evidence suggests that HIV-1 released from activated latent cells survives in productively infected cells in patient plasma despite competition against better adapted virus variants that have evolved in response to the host immune pressure. Long-term survival requires that latent virus forms adapt to the host immune response so that they are not outcompeted. We simulated the dynamics of HIV-1 envelope sequence evolution in response to host immune pressure to investigate how virus from activated latent cells can survive despite having reduced fitness compared to the more evolved virus variants in patient plasma. The evolutionary trends of our simulated virus populations followed closely those observed in HIV-1 sequence data from 16 patients. Our simulation results suggest that recombination facilitates the survival of genomic fragments originating from virus activated from latent cells. Our model further predicts that sequence diversity increases with the number of latent genomic fragments from different origins that persist in plasma.

Didehydro-Cortistatin A: a new player in HIV-therapy?

Antiretroviral therapy can effectively suppress HIV-1 infection but is ineffective against integrated proviruses. A latent viral reservoir composed of latently infected CD4(+)T cells persists under suppressive therapy, and infected individuals must remain indefinitely on antiretroviral therapy to prevent viral reactivation and propagation. Despite therapy, some degree of low-level ongoing replication is detected and transient viral reactivation may replenish the latent reservoir. An analog of the natural compound, Cortistatin A, blocks HIV-1 transcription by specifically targeting the viral transactivator, Tat. Treatment of latently infected cells with this Tat inhibitor promotes a state of deep-latency from which HIV reactivation capacity is greatly diminished. Here we discuss the use of Tat inhibitors to limit the latent reservoir to achieve a functional cure.

Modeling the Effects of Vorinostat In Vivo Reveals both Transient and Delayed HIV Transcriptional Activation and Minimal Killing of Latently Infected Cells

Recent efforts to cure human immunodeficiency virus type-1 (HIV-1) infection have focused on developing latency reversing agents as a first step to eradicate the latent reservoir. The histone deacetylase inhibitor, vorinostat, has been shown to activate HIV RNA transcription in CD4+ T-cells and alter host cell gene transcription in HIV-infected individuals on antiretroviral therapy. In order to understand how latently infected cells respond dynamically to vorinostat treatment and determine the impact of vorinostat on reservoir size in vivo, we have constructed viral dynamic models of latency that incorporate vorinostat treatment. We fitted these models to data collected from a recent clinical trial in which vorinostat was administered daily for 14 days to HIV-infected individuals on suppressive ART. The results show that HIV transcription is increased transiently during the first few hours or days of treatment and that there is a delay before a sustained increase of HIV transcription, whose duration varies among study participants and may depend on the long term impact of vorinostat on host gene expression. Parameter estimation suggests that in latently infected cells, HIV transcription induced by vorinostat occurs at lower levels than in productively infected cells. Furthermore, the estimated loss rate of transcriptionally induced cells remains close to baseline in most study participants, suggesting vorinostat treatment does not induce latently infected cell killing and thus reduce the latent reservoir in vivo.

Combination antiretroviral therapy (cART) for HIV infection must be taken for life due to the existence of long lived latently infected cells. Recent efforts have focused on developing latency reversing agents to eliminate latently infected cells by activating HIV production. In this work, we assess the impact of a latency reversing agent, vorinostat, by fitting dynamic models to data from a clinical trial. Results show that vorinostat treatment induces HIV transcription transiently and that the sustained induction of HIV transcription may depend on the temporal impact of vorinostat on host gene expression. Our results also suggest that vorinostat treatment is not sufficient to induce killing of latently infected cells in a majority of HIV-infected individuals on cART.

Transient detectable viremia and the risk of viral rebound in patients from the Swiss HIV Cohort Study

BACKGROUND

Temporary increases in plasma HIV RNA ('blips') are common in HIV patients on combination antiretroviral therapy (cART). Blips above 500 copies/mL have been associated with subsequent viral rebound. It is not clear if this relationship still holds when measurements are made using newer more sensitive assays.

METHODS

We selected antiretroviral-naive patients that then recorded one or more episodes of viral suppression on cART with HIV RNA measurements made using more sensitive assays (lower limit of detection below 50 copies/ml). We estimated the association in these episodes between blip magnitude and the time to viral rebound.

RESULTS

Four thousand ninety-four patients recorded a first episode of viral suppression on cART using more sensitive assays; 1672 patients recorded at least one subsequent suppression episode. Most suppression episodes (87 %) were recorded with TaqMan version 1 or 2 assays. Of the 2035 blips recorded, 84 %, 12 % and 4 % were of low (50-199 copies/mL), medium (200-499 copies/mL) and high (500-999 copies/mL) magnitude respectively. The risk of viral rebound increased as blip magnitude increased with hazard ratios of 1.20 (95 % CI 0.89-1.61), 1.42 (95 % CI 0.96-2.19) and 1.93 (95 % CI 1.24-3.01) for low, medium and high magnitude blips respectively; an increase of hazard ratio 1.09 (95 % CI 1.03 to 1.15) per 100 copies/mL of HIV RNA.

CONCLUSIONS

With the more sensitive assays now commonly used for monitoring patients, blips above 200 copies/mL are increasingly likely to lead to viral rebound and should prompt a discussion about adherence.

A multi-scale mathematical modeling framework to investigate anti-viral therapeutic opportunities in targeting HIV-1 accessory proteins

Human immunodeficiency virus-1 (HIV-1) employs accessory proteins to evade innate immune responses by neutralizing the anti-viral activity of host restriction factors. Apolipoprotein B mRNA-editing enzyme 3G (APOBEC3G, A3G) and bone marrow stromal cell antigen 2 (BST2) are host resistance factors that potentially inhibit HIV-1 infection. BST2 reduces viral production by tethering budding HIV-1 particles to virus producing cells, while A3G inhibits the reverse transcription (RT) process and induces viral genome hypermutation through cytidine deamination, generating fewer replication competent progeny virus. Two HIV-1 proteins counter these cellular restriction factors: Vpu, which reduces surface BST2, and Vif, which degrades cellular A3G. The contest between these host and viral proteins influences whether HIV-1 infection is established and progresses towards AIDS. In this work, we present an age-structured multi-scale viral dynamics model of in vivo HIV-1 infection. We integrated the intracellular dynamics of anti-viral activity of the host factors and their neutralization by HIV-1 accessory proteins into the virus/cell population dynamics model. We calculate the basic reproductive ratio (Ro) as a function of host-viral protein interaction coefficients, and numerically simulated the multi-scale model to understand HIV-1 dynamics following host factor-induced perturbations. We found that reducing the influence of Vpu triggers a drop in Ro, revealing the impact of BST2 on viral infection control. Reducing Vif׳s effect reveals the restrictive efficacy of A3G in blocking RT and in inducing lethal hypermutations, however, neither of these factors alone is sufficient to fully restrict HIV-1 infection. Interestingly, our model further predicts that BST2 and A3G function synergistically, and delineates their relative contribution in limiting HIV-1 infection and disease progression. We provide a robust modeling framework for devising novel combination therapies that target HIV-1 accessory proteins and boost antiviral activity of host factors.

An evolutionary role for HIV latency in enhancing viral transmission

HIV latency is the chief obstacle to eradicating HIV but is widely believed to be an evolutionary accident providing no lentiviral fitness advantage. However, findings of latency being "hardwired" into HIV's gene-regulatory circuitry appear inconsistent with latency being an evolutionary accident, given HIV's rapid mutation rate. Here, we propose that latency is an evolutionary "bet-hedging" strategy whose frequency has been optimized to maximize lentiviral transmission by reducing viral extinction during mucosal infections. The model quantitatively fits the available patient data, matches observations of high-frequency latency establishment in cell culture and primates, and generates two counterintuitive but testable predictions. The first prediction is that conventional CD8-depletion experiments in SIV-infected macaques increase latent cells more than viremia. The second prediction is that strains engineered to have higher replicative fitness—via reduced latency—will exhibit lower infectivity in animal-model mucosal inoculations. Therapeutically, the theory predicts treatment approaches that may substantially enhance "activate-and-kill" HIV-cure strategies.

Post-treatment control of HIV infection

Antiretroviral therapy (ART) for HIV is not a cure. However, recent studies suggest that ART, initiated early during primary infection, may induce post-treatment control (PTC) of HIV infection with HIV RNA maintained at <50 copies per mL. We investigate the hypothesis that ART initiated early during primary infection permits PTC by limiting the size of the latent reservoir, which, if small enough at treatment termination, may allow the adaptive immune response to prevent viral rebound (VR) and control infection. We use a mathematical model of within host HIV dynamics to capture interactions among target cells, productively infected cells, latently infected cells, virus, and cytotoxic T lymphocytes (CTLs). Analysis of our model reveals a range in CTL response strengths where a patient may show either VR or PTC, depending on the size of the latent reservoir at treatment termination. Below this range, patients will always rebound, whereas above this range, patients are predicted to behave like elite controllers. Using data on latent reservoir sizes in patients treated during primary infection, we also predict population-level VR times for noncontrollers consistent with observations.

Immuno-modulatory strategies for reduction of HIV reservoir cells

Antiretroviral therapy is able to suppress the viral load to below the detection limit, but it is not able to eradicate HIV reservoirs. Thus, there is a critical need for a novel treatment to eradicate (or reduce) the reservoir in order to eliminate the need for a lifelong adherence to antiretroviral therapy, which is expensive and potentially toxic. In this paper, we investigate the possible pharmacological strategies or combinations of strategies that may be beneficial to reduce or possibly eradicate the latent reservoir. We do this via studies with a validated mathematical model, where the parameter values are obtained with newly acquired clinical data for HIV patients. Our findings indicate that the strategy of reactivating the reservoir combined with enhancement of the killing rate of HIV-specific CD8+ T cells is able to eradicate the reservoir. In addition, our analysis shows that a targeted suppression of the immune system is also a possible strategy to eradicate the reservoir.

Stochastic modelling of viral blips in HIV-1-infected patients: effects of inhomogeneous density fluctuations

We propose a stochastic model of HIV-1 infection dynamics under HAART in order to analyse the origin and dynamics of the so-called viral blips, i.e. episodes of transient viremia that occur in the phase of where the disease remains in a latent state during which the viral load raises above the detection limit of standard clinical assays. Based on prior work in the subject, we consider an infection model in which latently infected cell compartment sustains a residual (latent) infection over long periods of time. Unlike previous models, we include the effects of inhomogeneities in cell and virus concentration in the blood stream. We further consider the effect of burst virion production. By comparing with the experimental results obtained during a study in which intensive sampling was carried out on HIV-1-infected patients undergoing HAART over a long period of time, we conclude that our model supports the hypothesis that viral blips are consistent with random fluctuations around the average viral load. We further observe that agreement between our simulation results and the blip statistics obtained in the aforementioned study improves when burst virion production is considered. We also study the effect of sample manipulation artifacts on the results produced by our model, in particular, that of the post-extraction handling time, i.e. the time elapsed between sample extraction and actual test. Our results support the notion that the statistics of viral blips can be critically affected by such artifacts.

HIV reservoir dynamics in the face of highly active antiretroviral therapy

Upon discontinuation of highly active antiretroviral therapy (HAART), human immunodeficiency virus (HIV)-infected individuals experience a brisk rebound in blood plasma viremia due to the exodus of HIV from various body reservoirs. Assessment of HIV dynamics during HAART and following treatment discontinuation is essential to better understand HIV persistence. Here we will first provide a brief overview of the molecular mechanisms involved in HIV reservoir formation and persistence. After a summary of HAART-mediated HIV decay within peripheral blood, we discuss findings from clinical studies examining the effects of HAART initiation and interruption on HIV reservoir dynamics in major anatomical compartments, including lymph nodes and spleen, gut associated lymphoid tissue, reproductive organs, the central nervous system, and the lungs. Features contributing to these reservoirs as distinct compartments, including anatomical features, the presence of drug transporters, and the effect of co-infection, are also discussed.

Mathematical modeling of multi-drugs therapy: a challenge for determining the optimal combinations of antiviral drugs

In the current era of antiviral drug therapy, combining multiple drugs is a primary approach for improving antiviral effects, reducing the doses of individual drugs, relieving the side effects of strong antiviral drugs, and preventing the emergence of drug-resistant viruses. Although a variety of new drugs have been developed for HIV, HCV and influenza virus, the optimal combinations of multiple drugs are incompletely understood. To optimize the benefits of multi-drugs combinations, we must investigate the interactions between the combined drugs and their target viruses. Mathematical models of viral infection dynamics provide an ideal tool for this purpose. Additionally, whether drug combinations computed by these models are synergistic can be assessed by two prominent drug combination theories, Loewe additivity and Bliss independence. By combining the mathematical modeling of virus dynamics with drug combination theories, we could show the principles by which drug combinations yield a synergistic effect. Here, we describe the theoretical aspects of multi-drugs therapy and discuss their application to antiviral research.

HIV-1 transcriptional regulation in the central nervous system and implications for HIV cure research

Human immunodeficiency virus type-1 (HIV-1) invades the central nervous system (CNS) during acute infection which can result in HIV-associated neurocognitive disorders in up to 50% of patients, even in the presence of combination antiretroviral therapy (cART). Within the CNS, productive HIV-1 infection occurs in the perivascular macrophages and microglia. Astrocytes also become infected, although their infection is restricted and does not give rise to new viral particles. The major barrier to the elimination of HIV-1 is the establishment of viral reservoirs in different anatomical sites throughout the body and viral persistence during long-term treatment with cART. While the predominant viral reservoir is believed to be resting CD4(+) T cells in the blood, other anatomical compartments including the CNS, gut-associated lymphoid tissue, bone marrow, and genital tract can also harbour persistently infected cellular reservoirs of HIV-1. Viral latency is predominantly responsible for HIV-1 persistence and is most likely governed at the transcriptional level. Current clinical trials are testing transcriptional activators, in the background of cART, in an attempt to purge these viral reservoirs and reverse viral latency. These strategies aim to activate viral transcription in cells constituting the viral reservoir, so they can be recognised and cleared by the immune system, while new rounds of infection are blocked by co-administration of cART. The CNS has several unique characteristics that may result in differences in viral transcription and in the way latency is established. These include CNS-specific cell types, different transcription factors, altered immune surveillance, and reduced antiretroviral drug bioavailability. A comprehensive understanding of viral transcription and latency in the CNS is required in order to determine treatment outcomes when using transcriptional activators within the CNS.

Stochastic population switch may explain the latent reservoir stability and intermittent viral blips in HIV patients on suppressive therapy

Highly active antiretroviral therapy can suppress plasma viral loads of HIV-1 infected individuals to below the detection limit of standard clinical assays. However, low-level viremia still persists. Many patients also have transient viral load measurements above the detection limit (the so-called "viral blips"). The latent reservoir consisting of latently infected CD4+ T cells represents a major obstacle to HIV-1 eradication. These cells can be activated to produce virions but the size of the latent reservoir is relatively stable. The mechanisms underlying low viral load persistence, emergence of intermittent viral blips and stability of the latent reservoir are not well understood. Cellular and viral transcription factors play an important role in the establishment and maintenance of HIV-1 latency. Infected cells with intermediate transcriptional activities may either revert to a latent state or become highly activated and produce virions due to intracellular perturbations. Here we develop a mathematical model that includes such stochastic population switch. We demonstrate that the model can generate a stable latent reservoir, intermittent viral blips, as well as low-level viremia persistence. Latently infected cells with intermediate transcription activities may maintain their size through a high level of homeostatic proliferation, while cells with low transcriptional activities are likely to be maintained through the reversion from cells with intermediate transcription activities. Simulations also suggest that treatment intensification or activation therapy may not help to eradicate the latent reservoir. Blocking the proliferation of latently infected cells might be a good strategy. These results provide more insights into the long-term dynamics of virus and latently infected cells in HIV patients on suppressive therapy and may help to develop novel treatment strategies.

Computational study to determine when to initiate and alternate therapy in HIV infection

HIV is a widespread viral infection without cure. Drug treatment has transformed HIV disease into a treatable long-term infection. However, the appearance of mutations within the viral genome reduces the susceptibility of HIV to drugs. Therefore, a key goal is to extend the time until patients exhibit resistance to all existing drugs. Current HIV treatment guidelines seem poorly supported as practitioners have not achieved a consensus on the optimal time to initiate and to switch antiretroviral treatments. We contribute to this discussion with predictions derived from a mathematical model of HIV dynamics. Our results indicate that early therapy initiation (within 2 years postinfection) is critical to delay AIDS progression. For patients who have not received any therapy during the first 3 years postinfection, switch in response to virological failure may outperform proactive switching strategies. In case that proactive switching is opted, the switching time between therapies should not be larger than 100 days. Further clinical trials are needed to either confirm or falsify these predictions.

Dynamics analysis and simulation of a modified HIV infection model with a saturated infection rate

This paper studies a modified human immunodeficiency virus (HIV) infection differential equation model with a saturated infection rate. It is proved that if the basic virus reproductive number R 0 of the model is less than one, then the infection-free equilibrium point of the model is globally asymptotically stable; if R 0 of the model is more than one, then the endemic infection equilibrium point of the model is globally asymptotically stable. Based on the clinical data from HIV drug resistance database of Stanford University, using the proposed model simulates the dynamics of the two groups of patients' anti-HIV infection treatment. The numerical simulation results are in agreement with the evolutions of the patients' HIV RNA levels. It can be assumed that if an HIV infected individual's basic virus reproductive number R 0 < 1 then this person will recover automatically; if an antiretroviral therapy makes an HIV infected individual's R 0 < 1, this person will be cured eventually; if an antiretroviral therapy fails to suppress an HIV infected individual's HIV RNA load to be of unpredictable level, the time that the patient's HIV RNA level has achieved the minimum value may be the starting time that drug resistance has appeared.

Human systems immunology: hypothesis-based modeling and unbiased data-driven approaches

Systems immunology is an emerging paradigm that aims at a more systematic and quantitative understanding of the immune system. Two major approaches have been utilized to date in this field: unbiased data-driven modeling to comprehensively identify molecular and cellular components of a system and their interactions; and hypothesis-based quantitative modeling to understand the operating principles of a system by extracting a minimal set of variables and rules underlying them. In this review, we describe applications of the two approaches to the study of viral infections and autoimmune diseases in humans, and discuss possible ways by which these two approaches can synergize when applied to human immunology.

Reactivation of latent HIV-1 in central memory CD4⁺ T cells through TLR-1/2 stimulation

BACKGROUND

Toll-like receptors (TLRs) are crucial for recognition of pathogen-associated molecular patterns by cells of the innate immune system. TLRs are present and functional in CD4⁺ T cells. Memory CD4⁺ T cells, predominantly central memory cells (TCM), constitute the main reservoir of latent HIV-1. However, how TLR ligands affect the quiescence of latent HIV within central memory CD4⁺ T cells has not been studied.

RESULTS

We evaluated the ability of a broad panel of TLR agonists to reactivate latent HIV-1. The TLR-1/2 agonist Pam3CSK4 leads to viral reactivation of quiescent HIV in a model of latency based on cultured TCM and in resting CD4⁺ T cells isolated from aviremic patients. In addition, we investigated the signaling pathway associated with Pam3CSK4 involved in HIV-1 reactivation. We show that the transcription factors NFκB, NFAT and AP-1 cooperate to induce viral reactivation downstream of TLR-1/2 stimulation. Furthermore, increasing levels of cyclin T1 is not required for TLR-mediated viral reactivation, but induction of viral expression requires activated pTEFb. Finally, Pam3CSK4 reactivates latent HIV-1 in the absence of T cell activation or proliferation, in contrast to antigen stimulation.

CONCLUSIONS

Our findings suggest that the signaling through TLR-1/2 pathway via Pam3CSK4 or other reagents should be explored as an anti-latency strategy either alone or in combination with other anti-latency drugs.

Vaccine and immunotherapeutic interventions

PURPOSE OF REVIEW

As we enter the fourth decade in HIV epidemic, advances in understanding HIV pathogenesis and development of potent and safer antiretroviral drugs have been spectacular. More than 30 antiviral drugs have been registered and the impact of combination antiviral therapy on morbidity and mortality has been dramatic. However, despite long-term virus suppression, HIV invariably rebounds after interruption of therapy. Long-term antiviral therapy does not cure HIV infection nor does it induce restoration/development of virus-specific immune responses capable of controlling HIV replication. Therefore, development of immune-based interventions is needed to restore effective defenses that can lead to HIV functional cure and ultimately eradication.

RECENT FINDINGS

Therapeutic vaccination and immune interventions that generate de-novo or that boost preexisting HIV-specific T-cell responses are being investigated as a potential means to achieve a 'functional HIV cure'. One major hurdle in the quest of an HIV cure is control and elimination of the HIV latent reservoir. Several immune interventions that target the latent reservoir have been tried in recent years. In parallel, several therapeutic vaccination strategies have been developed and tested in early clinical studies. Recent encouraging studies show for the first time that vaccination can have an impact on HIV load.

SUMMARY

This review summarizes the main immune interventions evaluated over the last years. Ways to improve them, as well as challenges in monitoring/evaluating effects of such strategies, are being discussed. In addition, clinical efficacy and potential clinical benefits of immunotherapeutic interventions are particularly difficult to measure. This review highlights current assays used and their shortcoming.

Quantification of viral infection dynamics in animal experiments

Analyzing the time-course of several viral infections using mathematical models based on experimental data can provide important quantitative insights regarding infection dynamics. Over the past decade, the importance and significance of mathematical modeling has been gaining recognition among virologists. In the near future, many animal models of human-specific infections and experimental data from high-throughput techniques will become available. This will provide us with the opportunity to develop new quantitative approaches, combining experimental and mathematical analyses. In this paper, we review the various quantitative analyses of viral infections and discuss their possible applications.

Modeling the within-host dynamics of HIV infection

The new field of viral dynamics, based on within-host modeling of viral infections, began with models of human immunodeficiency virus (HIV), but now includes many viral infections. Here we review developments in HIV modeling, emphasizing quantitative findings about HIV biology uncovered by studying acute infection, the response to drug therapy and the rate of generation of HIV variants that escape immune responses. We show how modeling has revealed many dynamical features of HIV infection and how it may provide insight into the ultimate cure for this infection.

Mathematical models of viral latency

While viral latency remains one of the biggest challenges for successful antiviral therapy, it has also inspired mathematical modelers to develop dynamical system approaches with the aim of predicting the impact of drug efficacy on disease progression and the persistence of latent viral reservoirs. In this review we present several differential equation models and assess their relative success in giving advice to the working clinician and their predictive power for inferring long term viral eradication from short term abatement. Many models predict that there is a considerable likelihood of viral rebound due to continuous reseeding of latent reservoirs. Most mathematical models of HIV latency suffer from being reductionist by ignoring the growing variety of different cell types harboring latent virus, the considerable intercellular delay involved in reactivation, and host-related epigenetic modifications which may alter considerably the dynamical system of immune cell populations.

Modeling antiretroviral drug responses for HIV-1 infected patients using differential equation models

We review mathematical modeling and related statistical issues of HIV dynamics primarily in response to antiretroviral drug therapy in this article. We start from a basic model of virus infection and then review a number of more advanced models with consideration of pharmacokinetic factors, adherence and drug resistance. Specifically, we illustrate how mathematical models can be developed and parameterized to understand the effects of long-term treatment and different treatment strategies on disease progression. In addition, we discuss a variety of parameter estimation methods for differential equation models that are applicable to either within- or between-host viral dynamics.

Pathogenesis and treatment of HIV infection: the cellular, the immune system and the neuroendocrine systems perspective

Infections with HIV represent a great challenge for the development of strategies for an effective cure. The spectrum of diseases associated with HIV ranges from opportunistic infections and cancers to systemic physiological disorders like encephalopathy and neurocognitive impairment. A major progress in controlling HIV infection has been achieved by highly active antiretroviral therapy (HAART). However, HAART does neither eliminate the virus reservoirs in form of latently infected cells nor does it completely reconstitute immune reactivity and physiological status. Furthermore, the failure of the STEP vaccine trial and the only marginal efficacies of the RV144 trial together suggest that the causal relationships between the complex sets of viral and immunological processes that contribute to protection or disease pathogenesis are still poorly understood. Here, we provide an up-to-date overview of HIV-host interactions at the cellular, the immune system and the neuroendocrine systems level. Only by integrating this multi-level knowledge one will be able to handle the systems complexity and develop new methodologies of analysis and prediction for a functional restoration of the immune system and the health of the infected host.

Models of contrasting strategies of rhinovirus immune manipulation

Rhinoviruses, consisting of well over one hundred serotypes that cause a plurality of common colds, are completely cleared by the host immune system after causing minimal cell death, but often without inducing long-term immune memory. We develop mathematical models of two kinds of rhinoviruses, the major group and minor group, that use different receptors to enter target cells. Roughly the 90 serotypes in the major group bind to ICAM-1, a molecule that is upregulated on antigen-presenting cells, and alter the timing, location and type of the immune response. The 12 members of the minor group do not so modulate the response. Our model predicts similar virus dynamics for the major and minor groups but with quite different underlying mechanisms. Over a range of key parameters that quantify immune manipulation, disease outcomes lie within a triangle in the plane describing damage and memory, of which the major and minor group form two corners. This model of infection by a highly adapted and low virulence virus provides a starting point for understanding the development of asthma and other pathologies.

Analysis of intracellular human immunodeficiency virus (HIV)-1 drug resistance mutations in multi-failed HIV-1-infected patients treated with a salvage regimen: 72-week follow-up

The human immunodeficiency virus (HIV) mutational archive of proviral DNA was monitored during a 72-week follow-up in 20 multidrug-experienced HIV-1-infected patients treated with a darunavir/ritonavir-based salvage therapy. At the beginning of the study, all patients harboured a number of intracellular drug resistance-associated mutations (RAMs) in peripheral blood mononuclear cells. In some patients, a significant fluctuation in the number of RAMs was observed during the observation period. However, all patients, notwithstanding the presence or the fluctuation of intracellular RAMs, showed a persistently undetectable viraemia. The data suggest that the archived resistant viral variants change during suppressive therapy, but that the variants are unable to re-emerge and to affect virological response.

An increasing proportion of monotypic HIV-1 DNA sequences during antiretroviral treatment suggests proliferation of HIV-infected cells

Understanding how HIV-1 persists during effective antiretroviral therapy (ART) should inform strategies to cure HIV-1 infection. We hypothesize that proliferation of HIV-1-infected cells contributes to persistence of HIV-1 infection during suppressive ART. This predicts that identical or monotypic HIV-1 DNA sequences will increase over time during ART. We analyzed 1,656 env and pol sequences generated following single-genome amplification from the blood and sputum of six individuals during long-term suppressive ART. The median proportion of monotypic sequences increased from 25.0% prior to ART to 43.2% after a median of 9.8 years of suppressive ART. The proportion of monotypic sequences was estimated to increase 3.3% per year (95% confidence interval, 2.3 to 4.4%; P < 0.001). Drug resistance mutations were not more common in the monotypic sequences, arguing against viral replication during times with lower antiretroviral concentrations. Bioinformatic analysis found equivalent genetic distances of monotypic and nonmonotypic sequences from the predicted founder virus sequence, suggesting that the relative increase in monotypic variants over time is not due to selective survival of cells with viruses from the time of acute infection or from just prior to ART initiation. Furthermore, while the total HIV-1 DNA load decreased during ART, the calculated concentration of monotypic sequences was stable in children, despite growth over nearly a decade of observation, consistent with proliferation of infected CD4(+) T cells and slower decay of monotypic sequences. Our findings suggest that proliferation of cells with proviruses is a likely mechanism of HIV-1 DNA persistence, which should be considered when designing strategies to eradicate HIV-1 infection.

Excitability in the host-pathogen interactions of HIV infection and emergence of viral load blips

HIV viral blips are characterized by intermittent episodes of detectable low-level viraemia which return spontaneously to an undetectable level in patients with full suppression of viraemia (<50 copies/ml). The precise mechanisms responsible for viraemia blips and their clinical significance are not known. In this work, we analyze HIV blips using a mathematical model describing basic host-pathogen interactions, in particular regulatory processes involving CD4+, CD8+ T-cells and the virus. We show that under adequate conditions, this interaction system can be excitable and small perturbations of the system by external stimuli can generate robust viral load (VL) blips of regular or irregular frequency and peak amplitudes. Importantly, our analysis showed that direct perturbations of the viral load (by latent reservoirs or opportunistic diseases for example) more efficiently trigger VL blips on contrary to direct perturbations of the immune system, in particular the levels of uninfected CD4+ and cytotoxic CD8+ T-cells. This feature is shown to rely on specific stability properties in this interaction system. Our analysis moreover suggests that blips should be of low clinical significance since any other VL or immune system perturbations could trigger transient viraemia under adequate excitability conditions.

Human immunodeficiency virus (HIV) latency: the major hurdle in HIV eradication

Failure of highly active antiretroviral therapy to eradicate the human immunodeficiency virus (HIV), even in patients who suppress the virus to undetectable levels for many years, underscores the problems associated with fighting this infection. The existence of persistent infection in certain cellular and anatomical reservoirs appears to be the major hurdle in HIV eradication. The development of therapeutic interventions that eliminate or limit the latent viral pools or prevent the reemergence of the viruses from producing cells will therefore be required to enhance the effectiveness of current antiretroviral strategies. To achieve this goal, there is a pressing need to understand HIV latency at the molecular level to design novel and improved therapies to either eradicate HIV or find a functional cure in which patients could maintain a manageable viral pool without AIDS in the absence of antiretroviral therapy. The integrated proviral genome remains transcriptionally silent for a long period in certain subsets of T cells. This ability to infect cells latently helps HIV to establish a persistent infection despite strong humoral and cellular immune responses against the viral proteins. The main purpose of this report is to provide a general overview of the HIV latency. We will describe the hurdles being faced in eradicating latent HIV proviruses. We will also briefly discuss the ongoing strategies aimed toward curing HIV infection.

Prolonged tenofovir treatment of macaques infected with K65R reverse transcriptase mutants of SIV results in the development of antiviral immune responses that control virus replication after drug withdrawal

BACKGROUND

We reported previously that while prolonged tenofovir monotherapy of macaques infected with virulent simian immunodeficiency virus (SIV) resulted invariably in the emergence of viral mutants with reduced in vitro drug susceptibility and a K65R mutation in reverse transcriptase, some animals controlled virus replication for years. Transient CD8+ cell depletion or short-term tenofovir interruption within 1 to 5 years of treatment demonstrated that a combination of CD8+ cell-mediated immune responses and continued tenofovir therapy was required for sustained suppression of viremia. We report here follow-up data on 5 such animals that received tenofovir for 8 to 14 years.

RESULTS

Although one animal had a gradual increase in viremia from 3 years onwards, the other 4 tenofovir-treated animals maintained undetectable viremia with occasional viral blips (≤ 300 RNA copies/ml plasma). When tenofovir was withdrawn after 8 to 10 years from three animals with undetectable viremia, the pattern of occasional episodes of low viremia (≤ 3600 RNA/ml plasma) continued throughout the 10-month follow-up period. These animals had low virus levels in lymphoid tissues, and evidence of multiple SIV-specific immune responses.

CONCLUSION

Under certain conditions (i.e., prolonged antiviral therapy initiated early after infection; viral mutants with reduced drug susceptibility) a virus-host balance characterized by strong immunologic control of virus replication can be achieved. Although further research is needed to translate these findings into clinical applications, these observations provide hope for a functional cure of HIV infection via immunotherapeutic strategies that boost antiviral immunity and reduce the need for continuous antiretroviral therapy.

HIV model parameter estimates from interruption trial data including drug efficacy and reservoir dynamics

Mathematical models based on ordinary differential equations (ODE) have had significant impact on understanding HIV disease dynamics and optimizing patient treatment. A model that characterizes the essential disease dynamics can be used for prediction only if the model parameters are identifiable from clinical data. Most previous parameter identification studies for HIV have used sparsely sampled data from the decay phase following the introduction of therapy. In this paper, model parameters are identified from frequently sampled viral-load data taken from ten patients enrolled in the previously published AutoVac HAART interruption study, providing between 69 and 114 viral load measurements from 3-5 phases of viral decay and rebound for each patient. This dataset is considerably larger than those used in previously published parameter estimation studies. Furthermore, the measurements come from two separate experimental conditions, which allows for the direct estimation of drug efficacy and reservoir contribution rates, two parameters that cannot be identified from decay-phase data alone. A Markov-Chain Monte-Carlo method is used to estimate the model parameter values, with initial estimates obtained using nonlinear least-squares methods. The posterior distributions of the parameter estimates are reported and compared for all patients.

Hyperthermia stimulates HIV-1 replication

HIV-infected individuals may experience fever episodes. Fever is an elevation of the body temperature accompanied by inflammation. It is usually beneficial for the host through enhancement of immunological defenses. In cultures, transient non-physiological heat shock (42–45°C) and Heat Shock Proteins (HSPs) modulate HIV-1 replication, through poorly defined mechanisms. The effect of physiological hyperthermia (38–40°C) on HIV-1 infection has not been extensively investigated. Here, we show that culturing primary CD4+ T lymphocytes and cell lines at a fever-like temperature (39.5°C) increased the efficiency of HIV-1 replication by 2 to 7 fold. Hyperthermia did not facilitate viral entry nor reverse transcription, but increased Tat transactivation of the LTR viral promoter. Hyperthermia also boosted HIV-1 reactivation in a model of latently-infected cells. By imaging HIV-1 transcription, we further show that Hsp90 co-localized with actively transcribing provirus, and this phenomenon was enhanced at 39.5°C. The Hsp90 inhibitor 17-AAG abrogated the increase of HIV-1 replication in hyperthermic cells. Altogether, our results indicate that fever may directly stimulate HIV-1 replication, in a process involving Hsp90 and facilitation of Tat-mediated LTR activity.

Fever is a complex reaction triggered in response to pathogen infection. It induces diverse effects on the human body and especially on the immune system. The functions of immune cells are positively affected by fever, helping them to fight infection. Fever consists in a physiological elevation of temperature and in inflammation. While the role of inflammatory molecules on HIV-1 replication has been widely studied, little is known about the direct effect of temperature on viral replication. Here, we report that hyperthermia (39.5°C) boosts HIV-1 replication in CD4+ T cells. In single-cycle infection experiments, hyperthermia increased HIV-1 infection up to 7-fold. This effect was mediated in part by an increased activation of the HIV-1 promoter by the viral protein Tat. Our results also indicate that hyperthermia may help HIV-1 to reactivate from latency. We also show that the Heat Shock Protein Hsp90, which levels are increased at 39.5°C, mediates in a large part the positive effect of hyperthermia on HIV-1 infection. Our work suggests that in HIV-1-infected patients, fever episodes may facilitate viral replication.

Impact of latently infected cells on strain archiving within HIV hosts

Latently infected cells are a barrier to HIV eradication on therapy due to long half-lives of between 6 and 44 months. The mechanism behind this long term maintenance is unclear although bystander proliferation and asymmetric division have both been put forward for consideration in mathematical models. The latently infected cell reservoir seems to act as an archive for strains of HIV no longer dominant in the blood, such as wild-type virus when the individual is on therapy. This is particularly significant when patients wish to come off medication and wild-type virus re-emerges. We use a two target cell model capable of producing low-level viral load on therapy and include latent cells and two strains of virus, wild-type and drug resistant, to investigate the impact of two possible mechanisms of latent cell reservoir maintenance on strain archiving. We find that although short term (less than a year) archiving of viral strains is possible in a model with no mechanism for reservoir maintenance, both bystander proliferation and asymmetric division of latent cells allow archiving to occur over much longer timescales (2 or more years). We suggest that regardless of the mechanism involved, latent cell reservoir maintenance allows strain archiving to occur. We interpret our results for clinical consideration.

Spontaneous clearance of viral infections by mesoscopic fluctuations

Spontaneous disease extinction can occur due to a rare stochastic fluctuation. We explore this process, both numerically and theoretically, in two minimal models of stochastic viral infection dynamics. We propose a method that reduces the complexity in models of viral infections so that the remaining dynamics can be studied by previously developed techniques for analyzing epidemiological models. Using this technique, we obtain an expression for the infection clearance time as a function of kinetic parameters. We apply our theoretical results to study stochastic infection clearance for specific stages of HIV and HCV dynamics. Our results show that the typical time for stochastic clearance of a viral infection increases exponentially with the size of the population, but infection still can be cleared spontaneously within a reasonable time interval in a certain population of cells. We also show that the clearance time is exponentially sensitive to the viral decay rate and viral infectivity but only linearly dependent on the lifetime of an infected cell. This suggests that if standard drug therapy fails to clear an infection then intensifying therapy by adding a drug that reduces the rate of cell infection rather than immune modulators that hasten infected cell death may be more useful in ultimately clearing remaining pockets of infection.

The clinical interpretation of viral blips in HIV patients receiving antiviral treatment: are we ready to infer poor adherence?

OBJECTIVES

Viral blips may be an indication of poor adherence to antiretroviral treatment. This article studies how the variations of the definitions of viral blips and that of the choice of sampling frame in studies investigating viral blips may contribute to the uncertainty of the associations between viral blips and possible causes.

DESIGN

Mathematical modeling study allows us to study the impact of different sampling frames and different definitions of blips upon study results that are usually not feasible in clinical settings.

METHODS

Using a previously published mathematical model, scenarios of different drug adherence levels and viral blips, with different sampling frames, were modeled.

RESULTS

In the case of viral blips as a result of nonadherence to combinational antiretroviral therapy, rather than calculating the incidence of blips directly from the number of blips observed in a given period of time, it is better to report the proportion of observations in a given period of time that are ≥50 copies per milliliter. Therefore, as the denominator, the number of observations in a given period of time is important. However, the proportion of blips is not very informative on the drug adherence level.

CONCLUSIONS

We should standardize definitions of viral blips and the choice of sampling frame and to report the proportion of observations of a given sampling frame in a given period of time that are ≥50 copies per milliliter, so that comparable data can be generated across different populations.

Piecewise HIV virus dynamic model with CD4(+) T cell count-guided therapy: I

The strategies of structured treatment interruptions (STIs) of antiretroviral therapies have been proposed for clinical management of HIV infected patients, but clinical studies on STIs failed to achieve a consistent conclusion for this strategy. To evaluate the STI strategies, in particular, CD4(+) T cell count-guided STIs, and explain these controversial conclusions from different clinical studies, in this paper we propose to use piecewise HIV virus dynamic models to quantitatively explore the STI strategies and investigate their dynamic behaviors. Our analysis results indicate that CD4(+) T cell counts can be maintained above a safe level using the STI with a single threshold or a threshold window. Numerical simulations show that the CD4(+) T cell counts either fluctuate or approach a stable level for a patient, depending on the prescribed upper or lower threshold values. In particular, the CD4(+) T cell counts can be stabilized at a desired level if the threshold policy control is applied. The durations of drug-on and drug-off are very sensitive to the prescribed upper or lower threshold levels, which possibly explains why the on-off strategy with fixed schedule or an STI strategy with frequent switches are associated with the high rate of failure. Our findings suggest that it is critical to carefully choose the thresholds of CD4(+) T cell count and individualize the STIs for each individual patient based on initial CD4(+) T cell counts.

Immediate antiviral therapy appears to restrict resting CD4+ cell HIV-1 infection without accelerating the decay of latent infection

HIV type 1 (HIV-1) persists within resting CD4(+) T cells despite antiretroviral therapy (ART). To better understand the kinetics by which resting cell infection (RCI) is established, we developed a mathematical model that accurately predicts (r = 0.65, P = 2.5 × 10(-4)) the initial frequency of RCI measured about 1 year postinfection, based on the time of ART initiation and the dynamic changes in viremia and CD4(+) T cells. In the largest cohort of patients treated during acute seronegative HIV infection (AHI) in whom RCI has been stringently quantified, we found that early ART reduced the generation of latently infected cells. Although RCI declined after the first year of ART in most acutely infected patients, there was a striking absence of decline when initial RCI frequency was less than 0.5 per million. Notably, low-level viremia was observed more frequently as RCI increased. Together these observations suggest that (i) the degree of RCI is directly related to the availability of CD4(+) T cells susceptible to HIV, whether viremia is controlled by the immune response and/or ART; and (ii) that two pools of infected resting CD4(+) T cells exist, namely, less stable cells, observable in patients in whom viremia is not well controlled in early infection, and extremely stable cells that are established despite early ART. These findings reinforce and extend the concept that new approaches will be needed to eradicate HIV infection, and, in particular, highlight the need to target the extremely small but universal, long-lived latent reservoir.