Elsevier

Journal of Theoretical Biology

Volume 260, Issue 2, 21 September 2009, Pages 308-331
Journal of Theoretical Biology

Review
Modeling HIV persistence, the latent reservoir, and viral blips

https://doi.org/10.1016/j.jtbi.2009.06.011Get rights and content

Abstract

HIV-1 eradication from infected individuals has not been achieved with the prolonged use of highly active antiretroviral therapy (HAART). The cellular reservoir for HIV-1 in resting memory CD4+ T cells remains a major obstacle to viral elimination. The reservoir does not decay significantly over long periods of time but is able to release replication-competent HIV-1 upon cell activation. Residual ongoing viral replication may likely occur in many patients because low levels of virus can be detected in plasma by sensitive assays and transient episodes of viremia, or HIV-1 blips, are often observed in patients even with successful viral suppression for many years. Here we review our current knowledge of the factors contributing to viral persistence, the latent reservoir, and blips, and mathematical models developed to explore them and their relationships. We show how mathematical modeling has helped improve our understanding of HIV-1 dynamics in patients on HAART and of the quantitative events underlying HIV-1 latency, reservoir stability, low-level viremic persistence, and emergence of intermittent viral blips. We also discuss treatment implications related to these studies.

Introduction

The advent of potent combination antiretroviral therapy has resulted in a substantial reduction in the incidence of HIV-1-related morbidity and mortality (Murphy et al., 2001). Highly active antiretroviral therapy (HAART) based on the administration of at least three different drugs from two or more classes (e.g., two nucleoside reverse transcriptase inhibitors, NRTI, combined with either a protease inhibitor or a non-nucleoside reverse transcriptase inhibitor, NNRTI) has proved extremely effective in suppressing the plasma viral load1 of most HIV-1-infected patients to below the limit of viral detection (e.g., 50 RNA copies/mL) of standard assays (Collier et al., 1996) (Fig. 1). Since viral replication is directly linked to CD4+ T cell2 depletion, viral evolution and disease progression (Mellors et al., 1996), the viral decline in the presence of combination therapy has profound clinical significance.

Over the past decades, many mathematical models, both deterministic and stochastic, have been developed to study HIV-1 infection and drug treatment. Many of these models, and particularly those developed before the mid-1990s, focused on the decline of CD4+ T cells (Perelson and Nelson, 1999), partially due to lack of accurate methods that could measure the number of virus particles in blood. The development of rapid and sensitive polymerase chain reaction (PCR)-based methods that can quantify genomic viral RNA molecules (each virus particle contains two RNA molecules) has proven to be significant in understanding HIV-1 viral load and facilitated the study of the host–pathogen interaction in HIV-1 infection by modeling. Seminal experimental studies by Ho et al. (1995), Wei et al. (1995) and modeling results by Perelson et al. (1996) suggested that both free virus and productively infected cells have rapid turnover. It was estimated that more than 1010 virions are produced every day in an untreated patient with chronic HIV-1 infection (Perelson et al., 1996). These results clarified that HIV-1 is not a “slow” virus and that it can replicate rapidly. The observation that HIV viral loads assume a relatively constant level in patients during chronic infection, due to a balance between rapid viral production and rapid viral clearance, allowed one to calculate viral production rates from the rate of viral clearance observed during potent antiretroviral therapy. More importantly, these results suggested that drug resistant mutations are very common in the viral genome because of the large HIV-1 turnover rate, and that the failure of antiretroviral drugs, when used as monotherapy, is an inevitable consequence of the rapid HIV-1 replication. In this article, we will start with a review of a few basic models used to study viral infection and estimate parameters that govern viral production and clearance. We show how mathematical models combined with experimental results revealed a number of different time scales, from hours to days to weeks to months, and biological processes underlying them during HIV-1 infection. These results have made significant contributions to our understanding of HIV-1 dynamics and drug therapy.

Eradication of HIV-1 from infected individuals is the ultimate goal of antiretroviral therapeutic interventions. However, this possibility seems unlikely at present despite the great deal of progress that has been made in developing potent antiretroviral drugs and in understanding the molecular biology of HIV-1 replication (see reviews in Blankson et al., 2002, Ho, 1998, Marsden and Zack, 2009, Pierson et al., 2000, Richman et al., 2009, Simon and Ho, 2003, Stevenson, 2003). Although HAART has proved extremely effective in reducing the viral load in HIV-infected patients to below 50 RNA copies/mL (Collier et al., 1996, Staszewski et al., 1999), the detection limit of current standard assays, a low level of viremia can be detected in plasma by more sensitive assays even after years of treatment (Dornadula et al., 1999, Palmer et al., 2003, Palmer et al., 2008). Moreover, a number of patients experience transient episodes of detectable viremia, or blips, even when the viral load has been suppressed to below the limit of detection for many years (Greub et al., 2002, Havlir et al., 2001, Mira et al., 2002, Sklar et al., 2002). These phenomena indicate that residual ongoing viral replication3 is very likely to continue in many patients on HAART.

HIV-1 can establish a state of latent infection in resting memory CD4+ T cells4 (Chun et al., 1997a, Chun et al., 1995). These latently infected cells are capable of escaping from viral cytopathic effects5 and host immune mechanisms due to very low levels of HIV-1 messenger RNA (mRNA) and proteins they express (Hermankova et al., 2003, Lassen et al., 2004). Because of the nature of memory CD4+ T cells (Sprent and Surh, 2002), they remain in the resting state in the presence of potent combination therapy for a very long period of time (Chun et al., 1997b, Finzi et al., 1997, Wong et al., 1997). However, they can produce new virus when stimulated by relevant antigen (Chun et al., 1998b). Thus, a viral rebound seems inevitable when therapy is withdrawn.

Determining the decay rate of the latent reservoir6 remains an important issue since it is directly related to the possibility and the time needed for the antiretroviral regimens currently in use to cure the infection. Estimates of the half-life7 of the latent reservoir are quite divergent, ranging from about 6 months (Chun et al., 2007, Ramratnam et al., 2000, Zhang et al., 1999a) to 44 months (Finzi et al., 1999, Siliciano et al., 2003). Therefore, combination treatment over as long as 73 years might be required for eradication of the latent reservoir (Finzi et al., 1999). Considering drug toxicities and medical tolerance, emergence of drug resistance, and treatment cost, such a lifetime therapy may not be reasonable for HIV-infected patients. Devising efficient strategies to accelerate the decay of the latent reservoir is a prerequisite for viral eradication (Richman et al., 2009).

We will review our current understanding of the factors that contribute to viral persistence, the latent reservoir persistence and viral blips. We discuss recent models proposed to study virus dynamics in patients on potent combination treatment and to explore possible mechanisms underlying low-level viral persistence, stability of the latent reservoir, and occurrence of intermittent viral blips. These models offer a quantitative investigation of the influence of ongoing viral replication on the viral load dynamics and the latent reservoir decay characteristics observed in HAART-treated patients. Finally, we discuss related treatment implications for clinical practice.

Section snippets

Multiphasic viral decay

Quantitative analysis of HIV-1 replication in vivo has made significant contributions to our understanding of AIDS pathogenesis and antiretroviral treatment (reviewed in Finzi and Siliciano, 1998, Perelson, 2002). After a few months of HIV-1 infection, the plasma virus usually attains a viral set-point,8 ranging from 102 to 107copies/mL (Piatak et al., 1993) in different patients, that

Low-level viremic persistence

Although potent combination therapy can suppress the viral loads in many patients to below the detection limit of present assays, 50 RNA copies/mL, this does not imply that virus production has been completely stopped by the therapy. On the contrary, in many patients with suppressed plasma viral levels for a prolonged time, a low level of viremia can still be detected by more sensitive assays that can quantify HIV-1 RNA down to one or a few copies/mL (Dornadula et al., 1999, Palmer et al., 2003,

Latent reservoir

Because latently infected CD4+ cells can rekindle productive viral infection when treatment is withdrawn and because they have a very slow decay rate in the majority of patients on HAART (Finzi et al., 1997, Ramratnam et al., 2000, Siliciano et al., 2003, Zhang et al., 1999a), the latent reservoir has been considered as a major obstacle to viral eradication (see reviews in Blankson et al., 2002, Chun and Fauci, 1999).

Intermittent viral blips

Although many infected individuals exhibit sustained low-level viremia on HAART, a number of them have occasional viral load measurements above the detection limit. Such transient episodes of detectable viremia are called “blips” (Fig. 1). Since viral blips are relatively rare events, neither their occurrence timing, frequency, duration, amplitude nor their etiology is well known. With more extensive sampling viral blips are more likely to be identified in the majority of patients at some time.

Treatment implications

Low-level persistent viremia, a stable latent reservoir, and intermittent viral blips observed in infected individuals on potent combination treatment all suggest that current HAART regimens are unable to eradicate HIV-1 from patients. Studies of the dynamics, mechanisms and relationships between them could have important treatment implications.

Concluding remarks

Mathematical modeling, in conjunction with experimental data, has yielded quantitative results that have greatly improved our understanding of AIDS pathogenesis and facilitated the management of patients with HIV-1 infection. Since HIV-1 takes about 10 years, on average, to progress from initial infection to full-blown AIDS, its replication was thought to be a slow process. A simple model used to interpret clinical data from Phase I/II drug trials showed that virus is produced and cleared

Acknowledgments

Portions of this work were performed under the auspices of the U.S. Department of Energy under contract DE-AC52-06NA25396. This work was supported by NIH Grants AI028433-18 and RR06555-17. We thank three reviewers for their constructive comments and suggestions that improved this manuscript.

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