Treatment interruption to boost specific HIV immunity in acute infection

A new efficient approach to fit stochastic models on the basis of high-throughput experimental data using a model of IRF7 gene expression as case study

Background

Mathematical models are used to gain an integrative understanding of biochemical processes and networks. Commonly the models are based on deterministic ordinary differential equations. When molecular counts are low, stochastic formalisms like Monte Carlo simulations are more appropriate and well established. However, compared to the wealth of computational methods used to fit and analyze deterministic models, there is only little available to quantify the exactness of the fit of stochastic models compared to experimental data or to analyze different aspects of the modeling results.

Results

Here, we developed a method to fit stochastic simulations to experimental high-throughput data, meaning data that exhibits distributions. The method uses a comparison of the probability density functions that are computed based on Monte Carlo simulations and the experimental data. Multiple parameter values are iteratively evaluated using optimization routines. The method improves its performance by selecting parameters values after comparing the similitude between the deterministic stability of the system and the modes in the experimental data distribution. As a case study we fitted a model of the IRF7 gene expression circuit to time-course experimental data obtained by flow cytometry. IRF7 shows bimodal dynamics upon IFN stimulation. This dynamics occurs due to the switching between active and basal states of the IRF7 promoter. However, the exact molecular mechanisms responsible for the bimodality of IRF7 is not fully understood.

Conclusions

Our results allow us to conclude that the activation of the IRF7 promoter by the combination of IRF7 and ISGF3 is sufficient to explain the observed bimodal dynamics.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-017-0406-4) contains supplementary material, which is available to authorized users.

Clustered epitopes within a new poly-epitopic HIV-1 DNA vaccine shows immunogenicity in BALB/c mice

Despite a huge number of studies towards vaccine development against human immunodeficiency virus-1, no effective vaccine has been approved yet. Thus, new vaccines should be provided with new formulations. Herein, a new DNA vaccine candidate encoding conserved and immunogenic epitopes from HIV-1 antigens of tat, pol, gag and env is designed and constructed. After bioinformatics analyses to find the best epitopes and their tandem, nucleotide sequence corresponding to the designed multiepitope was synthesized and cloned into pcDNA3.1+ vector. Expression of pcDNA3.1-tat/pol/gag/env plasmid was evaluated in HEK293T cells by RT-PCR and western-blotting. Seven groups of BALB/c mice were intramuscularly immunized three times either with 50, 100, 200 µg of plasmid in 2-week intervals or with similar doses of insert-free plasmid. Two weeks after the last injection, proliferation of T cells and secretion of IL4 and IFN-γ cytokines were evaluated using Brdu and ELISA methods, respectively. Results showed the proper expression of the plasmid in protein and mRNA levels. Moreover, the designed multiepitope plasmid was capable of induction of both proliferation responses as well as IFN-γ and IL-4 cytokine production in a considerable level compared to the control groups. Overall, our primary data warranted further detailed studies on the potency of this vaccine.

High-dimensional immunomonitoring models of HIV-1-specific CD8 T-cell responses accurately identify subjects achieving spontaneous viral control

The development of immunomonitoring models to determine HIV-1 vaccine efficacy is a major challenge. Studies suggest that HIV-1–specific CD8 T cells play a critical role in subjects achieving spontaneous viral control (HIV-1 controllers) and that they will be important in immune interventions. However, no single CD8 T-cell function is uniquely associated with controller status and the heterogeneity of responses targeting different epitopes further complicates the discovery of determinants of protective immunity. In the present study, we describe immunomonitoring models integrating multiple functions of epitope-specific CD8 T cells that distinguish controllers from subjects with treated or untreated progressive infection. Models integrating higher numbers of variables and trained with the least absolute shrinkage and selection operator (LASSO) variant of logistic regression and 10-fold cross-validation produce “diagnostic tests” that display an excellent capacity to delineate subject categories. The test accuracy reaches 75% area under the receiving operating characteristic curve in cohorts matched for prevalence of protective alleles. Linear mixed-effects model analyses show that the proliferative capacity, cytokine production, and kinetics of cytokine secretion are associated with HIV-1 control. Although proliferative capacity is the strongest single discriminant, integrated modeling of different dimensions of data leverages individual associations. This strategy may have important applications in predictive model development and immune monitoring of HIV-1 vaccine trials.

KEY POINTS

Immune monitoring models integrating multiple functions of HIV-1-specific CD8 T cells distinguish controllers from subjects with progressive HIV-1 infection. This strategy may have important applications in predictive model development and immune monitoring of HIV-1 vaccine trials.

Alterations in brain metabolism during the first year of HIV infection

Migration of both uninfected and infected monocytes into the brain during acute HIV infection likely initiates metabolic changes that can be observed with magnetic resonance spectroscopy (MRS). Herein, we measured changes in brain metabolism during the first year of HIV infection and examined the relationship of these metabolite levels to CD16+ monocyte populations measured in the blood. MRS was performed on nine HIV+ subjects identified during acute HIV infection and nine seronegative control subjects. HIV+ subjects were examined within 90 days of an indeterminate Western blot, then again 2 and 6 months later, during early infection. Blood samples were collected for plasma viral RNA and monocyte subset quantification. HIV+ subjects were identified with acute viral ailment and did not display severe cognitive deficits such as dementia or minor cognitive motor disorder. Changes in lipid membrane metabolism (choline levels) in the frontal cortex and white matter were observed during the initial year of HIV infection. Greater numbers of CD16+ monocytes were associated with lower N-acetylaspartate levels and higher choline levels in the brain. These results suggest that HIV infection induces metabolic changes in the brain early during infection and that these changes may be related to monocyte dynamics in the periphery.

Immunological analysis of treatment interruption after early highly active antiretroviral therapy

We longitudinally evaluated HIV-specific T-cell immunity after discontinuation of highly active antiretroviral therapy (HAART). After treatment interruption (TI), some individuals could maintain a low plasma viral load (<15,000 copies/mL), whereas others could not (>50,000 copies/mL). Before HAART was initiated, plasma viral load was similar. After TI, the numbers of CD8(+) T cells increased more in individuals without viral control, whereas individuals maintaining a low viral load showed a more pronounced increase in HIV-specific CD8(+) T-cell numbers. No differences were seen in the number or percentage of cytokine-producing HIV-1-specific CD4(+) T cells, or in proliferative capacity of T cells. Four weeks after TI, the magnitude of the total HIV-1-specific CD8(+) T-cell response (IFN-γ(+) and/or IL-2(+) and/or CD107a(+)) was significantly higher in individuals maintaining viral control. Degranulation contributed more to the overall CD8(+) T-cell response than cytokine production. Whether increased T-cell functionality is a cause or consequence of low viral load remains to be elucidated.