What do mathematical models tell us about killing rates during HIV-1 infection?

Gadhamsetty, Saikrishna; Beltman, Joost B.; Boer, Rob J. de

doi:10.1016/j.imlet.2015.07.009

Cited by 19 publications

(20 citation statements)

References 63 publications

(139 reference statements)

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“…Soon after detection, numbers of latently infected cells agreed with previous measurements [35,36] both in magnitude (a total of approximately 100 infected cells per million CD4+ T cells) and in relative proportions of replication competent provirus (approximately 1 in 100 latently infected cells). The relative timing and magnitude of the adaptive immune response coarsely matched experimental observations: our modeled adaptive immune compartment rose several orders of magnitude within 2 weeks following first positive viral load; further, by viral set-point the adaptive immunity has saturated and the infected cell death due to adaptive immunity was comparable to the infected cell death due to cytopathic effects [37][38][39]-as calculated using the ratio of κE/(κE+ δ I ).…”

Section: A Deterministic Mathematical Model Of Primary Hiv Infection supporting

confidence: 63%

Mathematical modeling to reveal breakthrough mechanisms in the HIV Antibody Mediated Prevention (AMP) trials

et al. 2020

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The ongoing Antibody Mediated Prevention (AMP) trials will uncover whether passive infusion of the broadly neutralizing antibody (bNAb) VRC01 can protect against HIV acquisition. Previous statistical simulations indicate these trials may be partially protective. In that case, it will be crucial to identify the mechanism of breakthrough infections. To that end, we developed a mathematical modeling framework to simulate the AMP trials and infer the breakthrough mechanisms using measurable trial outcomes. This framework combines viral dynamics with antibody pharmacokinetics and pharmacodynamics, and will be generally applicable to forthcoming bNAb prevention trials. We fit our model to human viral load data (RV217). Then, we incorporated VRC01 neutralization using serum pharmacokinetics (HVTN 104) and in vitro pharmacodynamics (LANL CATNAP database). We systematically explored trial outcomes by reducing in vivo potency and varying the distribution of sensitivity to VRC01 in circulating strains. We found trial outcomes could be used in a clinical trial regression model (CTRM) to reveal whether partially protective trials were caused by large fractions of VRC01-resistant (IC50>50 μg/mL) circulating strains or rather a global reduction in VRC01 potency against all strains. The former mechanism suggests the need to enhance neutralizing antibody breadth; the latter suggests the need to enhance VRC01 delivery and/or in vivo binding. We will apply the clinical trial regression model to data from the completed trials to help optimize future approaches for passive delivery of anti-HIV neutralizing antibodies. PLOS Computational Biology | https://doi.org/10.1371/journal.pcbi.

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Section: A Deterministic Mathematical Model Of Primary Hiv Infection supporting

confidence: 63%

Mathematical modeling to reveal breakthrough mechanisms in the HIV Antibody Mediated Prevention (AMP) trials

et al. 2020

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“…During this early phase (sometimes called an eclipse phase), infected cells do not produce virus and die at rate δ 1 . After integration, infected cells are able to produce new virus and die at rate δ 2 . The effect of RAL is included in the model by reducing the integration rate k by a factor (1 − ω ), where ω is the efficacy of RAL .…”

Section: Treatment With Integrase Inhibitors and Cd8+ Cell Depletionmentioning

confidence: 99%

“…After integration, infected cells are able to produce new virus and die at rate δ 2 . 64,72,[89][90][91] The effect of RAL is F I G U R E 5 Schematic of a viral dynamics model with multiple stages of infected cells. Target cells, T, become infected but do not produce virus during the early parts of the viral lifecycle (I 1 ), and infected cells only becomes productive (I 2 ) after some time (~1/k) included in the model by reducing the integration rate k by a factor…”

Section: Dynamics Of Viral Load Under Integrase Inhibitor Therapymentioning

confidence: 99%

The dynamics of simian immunodeficiency virus after depletion of CD8+ cells

Cardozo

Apetrei

Pandrea

et al. 2018

Immunological Reviews

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Human immunodeficiency virus infection is still one of the most important causes of morbidity and mortality in the world, with a disproportionate human and economic burden especially in poorer countries. Despite many years of intense research, an aspect that still is not well understood is what (immune) mechanisms control the viral load during the prolonged asymptomatic stage of infection. Because CD8+ T cells have been implicated in this control by multiple lines of evidence, there has been a focus on understanding the potential mechanisms of action of this immune effector population. One type of experiment used to this end has been depleting these cells with monoclonal antibodies in the simian immunodeficiency virus-macaque model and then studying the effect of that depletion on the viral dynamics. Here we review what these experiments have told us. We emphasize modeling studies to interpret the changes in viral load observed in these experiments, including discussion of alternative models, assumptions and interpretations, as well as potential future experiments.

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“…Mathematical modeling of CTL activity during HIV infection is consistent with lytic control by CTL, and predicts that most productively infected cells are killed by CTL ( 10 , 49 ). Apart from their positive effects of controlling viral spread, CTL have been shown to cause tissue damage in viral infections, such as in viral myocarditis ( 50 ) and viral hepatitis.…”

Section: Discussionmentioning

confidence: 75%

Killing of Latently HIV-Infected CD4 T Cells by Autologous CD8 T Cells Is Modulated by Nef

et al. 2018

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The role of HIV-specific CD8 T cell activity in the course of HIV infection and the way it affects the virus that resides in the latent reservoir resting memory cells is debated. The PBMC of HIV-infected patients contain HIV-specific CD8 T cells and their potential targets, CD4 T cells latently infected by HIV. CD4 T cells and CD8 T cells procured from PBMC of HIV-infected patients were co-incubated and analyzed: Formation of CD8 T cells and HIV-infected CD4 T cell conjugates and apoptosis of these CD4 T cells were observed by fluorescence microscopy with in situ PCR of HIV LTR DNA. Furthermore, conjugation of CD8 T cells with CD4 T cells and apoptosis of CD4 T cells was observed and quantified by imaging flow cytometry using anti-human activated caspase 3 antibody and TUNEL assay. The conjugation activity and apoptosis were found to be much higher in patients with acute HIV infection or AIDS compared to patients in chronic infection on antiretroviral therapy (ART) or not. Patients on ART had low grade conjugation and apoptosis of isolated CD69, CD25, and HLA-DR-negative CD4 T cells (latent reservoir cells) by CD8 T cells. Using in situ PCR The latent reservoir CD4 T cells were shown to contain most of the HIV DNA. We demonstrate in HIV-infected patients, that CD8 T cells conjugate with and kill HIV-infected CD4 T cells, including HIV-infected resting memory CD4 T cells, throughout the course of HIV infection. We propose that in HIV-infected patients CD4 T cell annihilation is caused in part by ongoing activity of HIV-specific CD8 T cells. HIV Nef protein interacts with ASK 1 and inhibits its pro-apoptotic death signaling by Fas/FasL, thus protecting HIV-infected cells from CD8 T cells killing. A peptide that interrupts Nef-ASK1 interaction that had been delivered into CD4 T cells procured from patients on ART resulted in the increase of their apoptosis inflicted by autologous CD8 T cells. We suggest that elimination of the HIV-infected latent reservoir CD4 T cells can be achieved by Nef inhibition.

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What do mathematical models tell us about killing rates during HIV-1 infection?

Cited by 19 publications

References 63 publications

Mathematical modeling to reveal breakthrough mechanisms in the HIV Antibody Mediated Prevention (AMP) trials

Mathematical modeling to reveal breakthrough mechanisms in the HIV Antibody Mediated Prevention (AMP) trials

The dynamics of simian immunodeficiency virus after depletion of CD8+ cells

Killing of Latently HIV-Infected CD4 T Cells by Autologous CD8 T Cells Is Modulated by Nef

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