Immune activation, CD4+ T cell counts, and viremia exhibit oscillatory patterns over time in patients with highly resistant HIV infection

The rates of immunologic and clinical progression are lower in patients with drug-resistant HIV compared to wild-type HIV. This difference is not fully explained by viral load. It has been argued that reductions in T cell activation and/or viral fitness might result in preserved target cells and an altered relationship between the level of viremia and the rate of CD4+ T cell loss. We tested this hypothesis over time in a cohort of patients with highly resistant HIV. Fifty-four antiretroviral-treated patients with multi-drug resistant HIV and detectable plasma HIV RNA were followed longitudinally. CD4+ T cell counts and HIV RNA levels were measured every 4 weeks and T cell activation (CD38/HLA-DR) was measured every 16 weeks. We found that the levels of CD4+ T cell activation over time were a strong independent predictor of CD4+ T cell counts while CD8+ T cell activation was more strongly associated with viremia. Using spectral analysis, we found strong evidence for oscillatory (or cyclic) behavior in CD4+ T cell counts, HIV RNA levels, and T cell activation. Each of the cell populations exhibited an oscillatory behavior with similar frequencies. Collectively, these data suggest that there may be a mechanistic link between T cell activation, CD4+ T cell counts, and viremia and lends support for the hypothesis of altered predator-prey dynamics as a possible explanation of the stability of CD4+ T cell counts in the presence of sustained multi-drug resistant viremia.     

Modeling HIV quasispecies evolutionary dynamics

Background

During the HIV infection several quasispecies of the virus arise, which are able to use different coreceptors, in particular the CCR5 and CXCR4 coreceptors (R5 and X4 phenotypes, respectively). The switch in coreceptor usage has been correlated with a faster progression of the disease to the AIDS phase. As several pharmaceutical companies are starting large phase III trials for R5 and X4 drugs, models are needed to predict the co-evolutionary and competitive dynamics of virus strains.

Results

We present a model of HIV early infection which describes the dynamics of R5 quasispecies and a model of HIV late infection which describes the R5 to X4 switch. We report the following findings: after superinfection (multiple infections at different times) or coinfection (simultaneous infection by different strains), quasispecies dynamics has time scales of several months and becomes even slower at low number of CD4+ T cells. Phylogenetic inference of chemokine receptors suggests that viral mutational pathway may generate a large variety of R5 variants able to interact with chemokine receptors different from CXCR4. The decrease of CD4+ T cells, during AIDS late stage, can be described taking into account the X4-related Tumor Necrosis Factor dynamics.

Conclusion

The results of this study bridge the gap between the within-patient and the inter-patients (i.e. world-wide) evolutionary processes during HIV infection and may represent a framework relevant for modeling vaccination and therapy.

     

A preliminary analysis of the balance between Th1 and Th2 cells after CD34+ cell-selected autologous PBSC transplantation

BACKGROUND: CD34+ cell-selected autologous PBSC transplantation (CD34+ APBSCT) is a procedure used for the treatment of patients with malignant disease that is intended to eliminate residual tumor cells from autologous grafts. However, frequent infectious complications after CD34+ APBSCT can occur. A delay of recovery of the absolute number of CD4+ T cells after transplantation was reported to be one disadvantageous factor. As data on T-cell function after CD34+ APBSCT are scanty, we analyzed changes in T-helper cell 1 (Th1) and T-helper cell 2 (Th2) after CD34+ APBSCT to evaluate immune reconstitution. METHODS: Twelve patients underwent APBSCT (CD34+APBSCT group, n=4, and unselected APBSCT, n=8). Peripheral blood (PB) samples were obtained at 2, 4, 8, 12 and 16 weeks after the transplantation. The dynamics of the Th1 and Th2 were analyzed at a single-cell level, using flow cytometry. RESULTS: In the CD34+ APBSCT group, not only the absolute count of CD4+ T cells but also the proportion of Th1 cells in CD4+ T cells and the ratio of Th1 to Th2 after transplantation were significantly decreased at 2 and 4 weeks after transplantation compared with findings in the unselected APBSCT group. DISCUSSION: We suggest that higher rates of infectious complications after CD34+ APBSCT may be due to the inability of residual T cells from the CD34+ cell selection to generate mature T cells that function adequately against infection. Although further study would be required, our preliminary data provide some information on the immune reconstitution after CD34+ APBSCT and differentiation of T lymphocytes into Th1 and Th2 in vivo.     

Vaccination-induced noncytolytic effects in the acute phase of SHIV infection

Many studies have shown that vaccines inducing CD8+ T cell responses can reduce viral loads and preserve CD4+ T cell numbers in monkey models of HIV infection. The mechanism of viral control by the vaccine-induced CD8+ T cells is usually assumed to be cytolysis of infected cells. However, in addition to cytolysis of infected cells, CD8+ T cells secrete a range of soluble factors that suppress viral replication. We have studied the dynamics of virus and CD4+ T cells in a successful vaccination-challenge model of SHIV infection. We find that better viral control in the acute phase of infection is associated with slower decay of peak viral load. Comparing viral and CD4+ T cell dynamics in acute infection, we find that a cytolytic mode of viral control with direct killing of infected cells is inconsistent with the observed trends. On the other hand, comparison of the predicted effects of noncytolytic CD8+ effector function with the experimental data shows that non-cytolytic control provides a better explanation of the experimental results. Our analysis suggests that vaccine-induced CD8+ T cells control SHIV infection by non-cytolytic means.     

Modeling regulation mechanisms in the immune system

We develop a mathematical framework for modeling regulatory mechanisms in the immune system. The model describes dynamics of key components of the immune network within two compartments: lymph node and tissue. We demonstrate using numerical simulations that our system can eliminate virus-infected cells, which are characterized by a tendency to increase without control (in absence of an immune response), while tolerating normal cells, which are characterized by a tendency to approach a stable equilibrium population. We experiment with different combinations of T cell reactivities that lead to effective systems and conclude that slightly self-reactive T cells can exist within the immune system and are controlled by regulatory cells. We observe that CD8+ T cell dynamics has two phases. In the first phase, CD8+ cells remain sequestered within the lymph node during a period of proliferation. In the second phase, the CD8+ population emigrates to the tissue and destroys its target population. We also conclude that a self-tolerant system must have a mechanism of central tolerance to ensure that self-reactive T cells are not too self-reactive. Furthermore, the effectiveness of a system depends on a balance between the reactivities of the effector and regulatory T cell populations, where the effectors are slightly more reactive than the regulatory cells.     

Dynamics of CD4+ T cells in HIV-1 infection

Mathematical modeling is becoming established in the immunologist's toolbox as a method to gain insight into the dynamics of the immune response and its components. No more so than in the case of the study of human immunodeficiency virus (HIV) infection, where earlier work on the viral dynamics brought significant advances in our understanding of HIV replication and evolution. Here, I review different areas of the study of the dynamics of CD4+ T cells in the setting of HIV, where modeling played important and diverse roles in helping us understand CD4+ T-cell homeostasis and the effect of HIV infection. As the experimental techniques become more accurate and quantitative, modeling should play a more important part in both experimental design and data analysis.     

Application of linear system analysis to the horizontal vestibulo-ocular reflex of the alert rhesus monkey using pseudorandom binary sequence and single frequency sinusoidal stimulation

Horizontal eye movements of the alert rhesus monkey resulting from both pseudorandom binary sequence (PRBS) and single frequency sinusoidal rotational stimulation were analyzed using a PDP 11/40 computer in order to generate gain, phase, and coherence estimates at discrete frequencies between 0.008 and 1.28 Hz. A computer simulation of vestibular induced eye movements was used to validate our analysis procedures and to determine the effects of digital noise. Frequency domain transfer functions derived from gain and phase estimates revealed that the responses to PRBS stimulation and to single frequency sinusoids were not appreciably different. PRBS testing was accomplished in approximately one third the time required for sinusoidal testing and yielded highly reproducible data. We conclude that PRBS stimulation is a reliable and efficient method for assessing linear system parameters of the horizontal vestibulo-ocular reflex. PRBS testing may be particularly and advantageous in studies of vestibulo-oculomotor plasticity in which rapid assessment of alterations in system dynamics is essential.     

A novel index of functional connectivity: phase lag based on Wilcoxon signed rank test

Phase synchronization has been an effective measurement of functional connectivity, detecting similar dynamics over time among distinct brain regions. However, traditional phase synchronization-based functional connectivity indices have been proved to have some drawbacks. For example, the phase locking value (PLV) index is sensitive to volume conduction, while the phase lag index (PLI) and the weighted phase lag index (wPLI) are easily affected by noise perturbations. In addition, thresholds need to be applied to these indices to obtain the binary adjacency matrix that determines the connections. However, the selection of the thresholds is generally arbitrary. To address these issues, in this paper we propose a novel index of functional connectivity, named the phase lag based on the Wilcoxon signed-rank test (PLWT). Specifically, it characterizes the functional connectivity based on the phase lag with a weighting procedure to reduce the influence of volume conduction and noise. Besides, it automatically identifies the important connections without relying on thresholds, by taking advantage of the framework of the Wilcoxon signed-rank test. The performance of the proposed PLWT index is evaluated on simulated electroencephalograph (EEG) datasets, as well as on two resting-state EEG datasets. The experimental results on the simulated EEG data show that the PLWT index is robust to volume conduction and noise. Furthermore, the brain functional networks derived by PLWT on the real EEG data exhibit a reasonable scale-free characteristic and high test–retest (TRT) reliability of graph measures. We believe that the proposed PLWT index provides a useful and reliable tool to identify the underlying neural interactions, while effectively diminishing the influence of volume conduction and noise.     

Slow Noise in the Period of a Biological Oscillator Underlies Gradual Trends and Abrupt Transitions in Phasic Relationships in Hybrid Neural Networks

In order to study the ability of coupled neural oscillators to synchronize in the presence of intrinsic as opposed to synaptic noise, we constructed hybrid circuits consisting of one biological and one computational model neuron with reciprocal synaptic inhibition using the dynamic clamp. Uncoupled, both neurons fired periodic trains of action potentials. Most coupled circuits exhibited qualitative changes between one-to-one phase-locking with fairly constant phasic relationships and phase slipping with a constant progression in the phasic relationships across cycles. The phase resetting curve (PRC) and intrinsic periods were measured for both neurons, and used to construct a map of the firing intervals for both the coupled and externally forced (PRC measurement) conditions. For the coupled network, a stable fixed point of the map predicted phase locking, and its absence produced phase slipping. Repetitive application of the map was used to calibrate different noise models to simultaneously fit the noise level in the measurement of the PRC and the dynamics of the hybrid circuit experiments. Only a noise model that added history-dependent variability to the intrinsic period could fit both data sets with the same parameter values, as well as capture bifurcations in the fixed points of the map that cause switching between slipping and locking. We conclude that the biological neurons in our study have slowly-fluctuating stochastic dynamics that confer history dependence on the period. Theoretical results to date on the behavior of ensembles of noisy biological oscillators may require re-evaluation to account for transitions induced by slow noise dynamics.     

Different rates of CD4+ and CD8+ T-cell proliferation in interleukin-2-treated human immunodeficiency virus-positive subjects

BACKGROUND: Interleukin-2 (IL-2) has been used successfully to increase CD4 cell counts in patients who are human immunodeficiency virus (HIV) positive. The mechanisms involved in this phenomenon are unknown. We hypothesized that a differential proliferation rate of CD4+ compared with CD8+ lymphocytes could be related to the increase of CD4 counts and of CD4/CD8 ratios that occur in HIV+ patients during IL-2 treatment. METHODS: We enrolled in our study 14 HIV+ patients treated with IL-2 or with highly active antiretroviral therapy (HAART) during a 96-week observation period. Using flow cytometry, we measured longitudinally the expression of the Ki67 antigen in peripheral blood CD4+ and CD8+ lymphocyte subsets. RESULTS: Compared with HAART alone, IL-2 produced a rapid increase of Ki67+ proliferating CD4 cells and a concomitant increase of the CD4/CD8 ratios, whereas the corresponding CD8 proliferation increased slightly. On the contrary, HAART alone was effective in suppressing equally both CD4 and CD8 proliferation. CONCLUSIONS: Our results suggest a selective activity of IL-2 on CD4 T-cell proliferation; on the contrary, CD8-specific proliferation is affected minimally during treatment. This information may offer the potential to plan correctly immune activating regimens.     

Dynamics of CD8+ T cell responses during acute and chronic lymphocytic choriomeningitis virus infection

Infection of mice with lymphocytic choriomeningitis virus (LCMV) is frequently used to study the underlying principles of viral infections and immune responses. We fit a mathematical model to recently published data characterizing Ag-specific CD8+ T cell responses during acute (Armstrong) and chronic (clone 13) LCMV infection. This allows us to analyze the differences in the dynamics of CD8+ T cell responses against different types of LCMV infections. For the four CD8+ T cell responses studied, we find that, compared with the responses against acute infection, responses against chronic infection are generally characterized by an earlier peak and a faster contraction phase thereafter. Furthermore, the model allows us to give a new interpretation of the effect of thymectomy on the dynamics of CD8+ T cell responses during chronic LCMV infection: a smaller number of naive precursor cells is sufficient to account for the observed differences in the responses in thymectomized mice. Finally, we compare data characterizing LCMV-specific CD8+ T cell responses from different laboratories. Although the data were derived from the same experimental model, we find quantitative differences that can be solved by introducing a scaling factor. Also, we find kinetic differences that are at least partly due to the infrequent measurements of CD8+ T cells in the different laboratories.     

High level of surface CD4 prevents stable human immunodeficiency virus infection of T-cell transfectants.

CD4 is the principal receptor for the human immunodeficiency virus (HIV). We have isolated and studied CD4-expressing tumor cell clones made by expressing CD4 in the T-cell tumor line HSB. Two clones, one designated HSBCD4, a clone expressing low levels of CD4, and the other, HSB10xCD4, a high-expresser CD4+ clone, were studied for their ability to bind and replicate HIV. In contrast to many other CD4+ cells that down-modulate CD4 following HIV infection, the HSB10xCD4 clones continued to express high levels of surface CD4 following infection with HIV. Unlike infection of HSBCD4 or many other human CD4+ cells, HIV infection of HSB10xCD4 clone was short lived: p24 antigen, provirus, or coculturable virus was present for less than 14 days following infection with several strains of HIV-1 or with HIV-2. When infection was initiated by transfection of proviral DNA, high and low CD4 expressers initially produced p24 antigen at approximately the same level. However, high CD4 expressers produced coculturable virus only during the first few days following transfection, whereas low CD4 expressers transfected with HIV continued to produce virus beyond 6 weeks. Monoclonal antibody-mediated down-modulation of CD4 surface expression on HSB10xCD4 clones permitted these formerly HIV-resistant cells to become persistently infected with HIV. Thus, high concentrations of CD4 on the surface of an HIV-infected cell prevent persistent HIV infection of CD4+ cells.     

High viral burden and rapid CD4+ cell depletion in human immunodeficiency virus type 1-infected SCID-hu mice suggest direct viral killing of thymocytes in vivo.

The mechanism of CD4+ cell loss in lymphoid organs is unknown. In this study, human immunodeficiency virus (HIV) infection of human fetal thymus/liver implants in severe combined immunodeficient mice was used to investigate the mechanism of HIV-induced depletion of CD4-bearing cells in vivo. The implants were assessed for depletion of CD4+ thymocytes, apoptosis, and viral burden. We detected two phases of CD4 cell depletion, an initial rapid phase and a more gradual later phase. Compared to mock-infected implants, HIV-infected implants did not demonstrate detectable increases in the levels of apoptosis while severe depletion of CD4-bearing cells was ongoing. During peak loss of CD4+ cells, high viral burden was observed, suggesting that loss of CD4+ cells in this in vivo system is due to direct killing of infected thymocytes. Increased levels of apoptosis were observed during the later phase of thymocyte depletion; however, these apoptotic cells lacked CD4. This finding suggests that a second indirect mechanism may be responsible for the destruction of CD4- CD8+ thymocytes in vivo. Taken together, these results suggest that CD4+ and CD4- cells may die by different mechanism(s).     

Analysis of Ter-Ter enzyme kinetic mechanisms by computer simulation of isotope exchange at chemical equilibrium: development and application of ISOTER, a personal-computer-based program

A convenient, personal-computer-based program has been developed that allows simulation of isotopic exchange kinetics at chemical equilibrium catalyzed by a three reactant-three product (TerTer) enzyme system: A + B + C integral of P + Q + R. This program, ISOTER, utilizes a rapid algebraic method to calculate the exchange rate between any reactant-product pair as a function of the substrate concentration and avoids altogether the necessity of deriving an explicit (but cumbersome and impractical) equation for exchange rate. ISOTER was used to generate model saturation patterns for 16 different TerTer kinetic mechanisms, varying different combinations of reactant-product pairs in constant ratio at equilibrium: [all substrates], [A, P], [B, Q], and [C, R], while holding the nonvaried components constant. These model studies indicate that virtually every one of these mechanisms can be distinguished from the others. In addition, ISOTER has been used to fit multiple sets of experimental data for Escherichia coli glutamine synthetase, which produced a set of rate constants consistent with the previously proposed "preferred order random" kinetic mechanism.     

Simian-Human Immunodeficiency Infection – Is the Course Set in the Acute Phase?

Identifying early predictors of infection outcome is important for the clinical management of HIV infection, and both viral load and CD4+ T cell level have been found to be useful predictors of subsequent disease progression. Very high viral load or extensively depleted CD4+ T cells in the acute phase often result in failure of immune control, and a fast progression to AIDS. It is usually assumed that extensive loss of CD4+ T cells in the acute phase of HIV infection prevents the establishment of robust T cell help required for virus control in the chronic phase. We tested this hypothesis using viral load and CD4+ T cell number of SHIV-infected rhesus macaques. In acute infection, the lowest level of CD4+ T cells was a good predictor of later survival; animals having less than 3.3% of baseline CD4+ T cells progressed to severe disease, while animals with more than 3.3% of baseline CD4+ T cells experienced CD4+ T cell recovery. However, it is unclear if the disease progression was caused by early depletion, or was simply a result of a higher susceptibility of an animal to infection. We derived a simple relationship between the expected number of CD4+ T cells in the acute and chronic phases for a constant level of host susceptibility or resistance. We found that in most cases, the depletion of CD4+ T cells in chronic infection was consistent with the prediction from the acute CD4+ T cell loss. However, the animals with less than 3.3% of baseline CD4 T cells in the acute phase were approximately 20% more depleted late in the infection than expected based on constant level of virus control. This suggests that severe acute CD4 depletion indeed impairs the immune response.     

Linear modes of gene expression determined by independent component analysis

MOTIVATION: The expression of genes is controlled by specific combinations of cellular variables. We applied Independent Component Analysis (ICA) to gene expression data, deriving a linear model based on hidden variables, which we term 'expression modes'. The expression of each gene is a linear function of the expression modes, where, according to the ICA model, the linear influences of different modes show a minimal statistical dependence, and their distributions deviate sharply from the normal distribution. RESULTS: Studying cell cycle-related gene expression in yeast, we found that the dominant expression modes could be related to distinct biological functions, such as phases of the cell cycle or the mating response. Analysis of human lymphocytes revealed modes that were related to characteristic differences between cell types. With both data sets, the linear influences of the dominant modes showed distributions with large tails, indicating the existence of specifically up- and downregulated target genes. The expression modes and their influences can be used to visualize the samples and genes in low-dimensional spaces. A projection to expression modes helps to highlight particular biological functions, to reduce noise, and to compress the data in a biologically sensible way.     

Joint Inference on HIV Viral Dynamics and Immune Suppression in Presence of Measurement Errors

Summary : In an attempt to provide a tool to assess antiretroviral therapy and to monitor disease progression, this article studies association of human immunodeficiency virus (HIV) viral suppression and immune restoration. The data from a recent acquired immune deficiency syndrome (AIDS) study are used for illustration. We jointly model HIV viral dynamics and time to decrease in CD4/CD8 ratio in the presence of CD4 process with measurement errors, and estimate the model parameters simultaneously via a method based on a Laplace approximation and the commonly used Monte Carlo EM algorithm. The approaches and many of the points presented apply generally.