Dynamics of co-infection with M. Tuberculosis and HIV-1

Systems biology approaches to investigate the role of granulomas in TB-HIV coinfection

The risk of active tuberculosis disease is 15-21 times higher in those coinfected with human immunodeficiency virus-1 (HIV) compared to tuberculosis alone, and tuberculosis is the leading cause of death in HIV+ individuals. Mechanisms driving synergy between Mycobacterium tuberculosis (Mtb) and HIV during coinfection include: disruption of cytokine balances, impairment of innate and adaptive immune cell functionality, and Mtb-induced increase in HIV viral loads. Tuberculosis granulomas are the interface of host-pathogen interactions. Thus, granuloma-based research elucidating the role and relative impact of coinfection mechanisms within Mtb granulomas could inform cohesive treatments that target both pathogens simultaneously. We review known interactions between Mtb and HIV, and discuss how the structure, function and development of the granuloma microenvironment create a positive feedback loop favoring pathogen expansion and interaction. We also identify key outstanding questions and highlight how coupling computational modeling with in vitro and in vivo efforts could accelerate Mtb-HIV coinfection discoveries.

An investigation of tuberculosis progression revealing the role of macrophages apoptosis via sensitivity and bifurcation analysis

Mycobacterium tuberculosis infection features various disease outcomes: clearance, latency, active disease, and latent tuberculosis infection (LTBI) reactivation. Identifying the decisive factors for disease outcomes and progression is crucial to elucidate the macrophages-tuberculosis interaction and provide insights into therapeutic strategies. To achieve this goal, we first model the disease progression as a dynamical shift among different disease outcomes, which are characterized by various steady states of bacterial concentration. The causal mechanisms of steady-state transitions can be the occurrence of transcritical and saddle-node bifurcations, which are induced by slowly changing parameters. Transcritical bifurcation, occurring when the basic reproduction number equals to one, determines whether the infection clears or spreads. Saddle-node bifurcation is the key mechanism to create and destroy steady states. Based on these two steady-state transition mechanisms, we carry out two sample-based sensitivity analyses on transcritical bifurcation conditions and saddle-node bifurcation conditions. The sensitivity analysis results suggest that the macrophage apoptosis rate is the most significant factor affecting the transition in disease outcomes. This result agrees with the discovery that the programmed cell death (apoptosis) plays a unique role in the complex microorganism-host interplay. Sensitivity analysis narrows down the parameters of interest, but cannot answer how these parameters influence the model outcomes. To do this, we employ bifurcation analysis and numerical simulation to unfold various disease outcomes induced by the variation of macrophage apoptosis rate. Our findings support the hypothesis that the regulation mechanism of macrophage apoptosis affects the host immunity against tuberculosis infection and tuberculosis virulence. Moreover, our mathematical results suggest that new treatments and/or vaccines that regulate macrophage apoptosis in combination with weakening bacillary viability and/or promoting adaptive immunity could have therapeutic value.

Mathematical model for the growth of Mycobacterium tuberculosis in the granuloma

In this work we formulate a model for the population dynamics of Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis (TB). Our main interest is to assess the impact of the competition among bacteria on the infection prevalence. For this end, we assume that Mtb population has two types of growth. The first one is due to bacteria produced in the interior of each infected macrophage, and it is assumed that is proportional to the number of infected macrophages. The second one is of logistic type due to the competition among free bacteria released by the same infected macrophages. The qualitative analysis and numerical results suggests the existence of forward, backward and S-shaped bifurcations when the associated reproduction number R0 of the Mtb is less unity. In addition, qualitative analysis of the model shows that there may be up to three bacteria-present equilibria, two locally asymptotically stable, and one unstable.

Optimal control of intervention strategies in malaria–tuberculosis co-infection with relapse

A model which incorporates some of the basic epidemiological features of the co-dynamics of malaria and tuberculosis (TB) is formulated and the effectiveness of current intervention strategies of these two diseases is analyzed. The malaria-only and TB-only models are considered first. Global stability disease-free steady states of the two sub-models does not hold due to the co-existence of stable disease-free with stable endemic equilibria, a phenomenon known as backward bifurcation. The dynamics of the dual malaria–TB model with intervention strategies are also analyzed. Numerical simulations of the malaria–TB model are carried out to determine whether the two diseases can co-exist. Lastly, sensitivity analysis on key parameters that drive the disease dynamics is performed in order to identify their relative importance to disease transmission.

A review of computational and mathematical modeling contributions to our understanding of Mycobacterium tuberculosis within-host infection and treatment

Tuberculosis (TB) is an ancient and deadly disease characterized by complex host-pathogen dynamics playing out over multiple time and length scales and physiological compartments. Computational modeling can be used to integrate various types of experimental data and suggest new hypotheses, mechanisms, and therapeutic approaches to TB. Here, we offer a first-time comprehensive review of work on within-host TB models that describe the immune response of the host to infection, including the formation of lung granulomas. The models include systems of ordinary and partial differential equations and agent-based models as well as hybrid and multi-scale models that are combinations of these. Many aspects of M. tuberculosis infection, including host dynamics in the lung (typical site of infection for TB), granuloma formation, roles of cytokine and chemokine dynamics, and bacterial nutrient availability have been explored. Finally, we survey applications of these within-host models to TB therapy and prevention and suggest future directions to impact this global disease.

Mathematical epidemiology: Past, present, and future

We give a brief outline of some of the important aspects of the development of mathematical epidemiology.

Systems Medicine and Infection

By using a systems-based approach, mathematical and computational techniques can be used to develop models that describe the important mechanisms involved in infectious diseases. An iterative approach to model development allows new discoveries to continually improve the model and ultimately increase the accuracy of predictions.SIR models are used to describe epidemics, predicting the extent and spread of disease. Genome-wide genotyping and sequencing technologies can be used to identify the biological mechanisms behind diseases. These tools help to build strategies for disease prevention and treatment, an example being the recent outbreak of Ebola in West Africa where these techniques were deployed.HIV is a complex disease where much is still to be learned about the virus and the best effective treatment. With basic mathematical modeling techniques, significant discoveries have been made over the last 20 years. With recent technological advances, the computational resources now available, and interdisciplinary cooperation, further breakthroughs are inevitable.In TB, modeling has traditionally been empirical in nature, with clinical data providing the fuel for this top-down approach. Recently, projects have begun to use data derived from laboratory experiments and clinical trials to create mathematical models that describe the mechanisms responsible for the disease.A systems medicine approach to infection modeling helps identify important biological questions that then direct future experiments, the results of which improve the model in an iterative cycle. This means that data from several model systems can be integrated and synthesized to explore complex biological systems.

Extremely high HIV-1 viral load in a patient with undiagnosed clinical indicator disease for HIV infection

We report a case of a new diagnosis of HIV with an extremely high viral load presenting with HIV encephalopathy, in a 54-year-old woman who had been treated with 2 years of extended high-dose immunosuppressant therapy for a recalcitrant pruritic rash before diagnosis.

A double age-structured model of the co-infection of tuberculosis and HIV

After decades on the decline, it is believed that the emergence of HIV is responsible for an increase in the tuberculosis prevalence. The leading infectious disease in the world, tuberculosis is also the leading cause of death among HIV-positive individuals. Each disease progresses through several stages. The current model suggests modeling these stages through a time-since-infection tracking transmission rate function, which, when considering co-infection, introduces a double-age structure in the PDE system. The basic and invasion reproduction numbers for each disease are calculated and the basic ones established as threshold for the disease progression. Numerical results confirm the calculations and a simple treatment scenario suggests the importance of time-since-infection when introducing disease control and treatment in the model.

How can mathematical models advance tuberculosis control in high HIV prevalence settings?

Existing approaches to tuberculosis (TB) control have been no more than partially successful in areas with high human immunodeficiency virus (HIV) prevalence. In the context of increasingly constrained resources, mathematical modelling can augment understanding and support policy for implementing those strategies that are most likely to bring public health and economic benefits. In this paper, we present an overview of past and recent contributions of TB modelling in this key area, and suggest a way forward through a modelling research agenda that supports a more effective response to the TB-HIV epidemic, based on expert discussions at a meeting convened by the TB Modelling and Analysis Consortium. The research agenda identified high-priority areas for future modelling efforts, including 1) the difficult diagnosis and high mortality of TB-HIV; 2) the high risk of disease progression; 3) TB health systems in high HIV prevalence settings; 4) uncertainty in the natural progression of TB-HIV; and 5) combined interventions for TB-HIV. Efficient and rapid progress towards completion of this modelling agenda will require co-ordination between the modelling community and key stakeholders, including advocates, health policy makers, donors and national or regional finance officials. A continuing dialogue will ensure that new results are effectively communicated and new policy-relevant questions are addressed swiftly.

Global stability of an epidemic model for HIV–TB co-infection with infection-age

A nonlinear mathematical HIV–TB model with infection-age is proposed in this paper. The basic reproduction numbers according to HIV and TB are respectively determined whether one of the diseases dies out or persists. The local and global stability of the disease-free and dominated equilibria are discussed by employing integral semigroup theory and Lyapunov functionals. The persistence of the system is also obtained by the persistence theories of the systems. The simulation illustrates the theoretical results.

Optimal control of a two-strain tuberculosis-HIV/AIDS co-infection model

Tuberculosis is a bacterial disease caused by Mycobacterium tuberculosis (TB). The risk for TB infection greatly increases with HIV infection; TB disease occurs in 7-10% of patients with HIV infection each year, increasing the potential for transmission of drug-resistant Mycobacterium tuberculosis strains. In this paper a deterministic model is presented and studied for the transmission of TB-HIV/AIDS co-infection. Optimal control theory is then applied to investigate optimal strategies for controlling the spread of the disease using treatment of infected individuals with TB as the system control variables. Various combination strategies were examined so as to investigate the impact of the controls on the spread of the disease. And incremental cost-effectiveness ratio (ICER) was used to investigate the cost effectiveness of all the control strategies. Our results show that the implementation of the combination strategy involving the prevention of treatment failure in drug-sensitive TB infectious individuals and the treatment of individuals with drug-resistant TB is the most cost-effective control strategy. Similar results were obtained with different objective functionals involving the minimization of the number of individuals with drug-sensitive TB-only and drug-resistant TB-only with the efforts involved in applying the control.

Modeling TB-HIV Syndemic and Treatment

Tuberculosis (TB) and human immunodeficiency virus (HIV) can be considered a deadly human syndemic. In this paper, we formulate a model for TB and HIV transmission dynamics. The model considers both TB and acquired immune deficiency syndrome (AIDS) treatment for individuals with only one of the two infectious diseases or both. The basic reproduction number and equilibrium points are determined and stability is analyzed. Through simulations, we show that TB treatment for individuals with only TB infection reduces the number of individuals that become coinfected with TB and HIV/AIDS and reduces the diseases (TB and AIDS) induced deaths. Analogously, the treatment of individuals with only AIDS also reduces the number of coinfected individuals. Further, TB treatment for coinfected individuals in the active and latent stage of TB disease implies a decrease of the number of individuals that passes from HIV-positive to AIDS.

On the interactions of sensitive and resistant Mycobacterium tuberculosis to antibiotics

In this work we propose a system of non linear ordinary differential equations for the dynamics of Mycobacterium tuberculosis (Mtb) within the host, in order to study the role of macrophages, T cells and antibiotics in the control of sensitive and resistant Mtb. Conditions for the persistence of sensitive and resistant bacteria are given in terms of the secondary infections produced by bacteria and macrophages, the immune response, and the antibiotic treatment. Model analysis predicts backward bifurcations for certain values of the parameters. In this case, the dynamics is characterized by the coexistence of two infection states with low and high bacteria load, respectively.

Changing risk behaviours and the HIV epidemic: a mathematical analysis in the context of treatment as prevention

Background

Expanding access to highly active antiretroviral therapy (HAART) has become an important approach to HIV prevention in recent years. Previous studies suggest that concomitant changes in risk behaviours may either help or hinder programs that use a Treatment as Prevention strategy.

Analysis

We consider HIV-related risk behaviour as a social contagion in a deterministic compartmental model, which treats risk behaviour and HIV infection as linked processes, where acquiring risk behaviour is a prerequisite for contracting HIV. The equilibrium behaviour of the model is analysed to determine epidemic outcomes under conditions of expanding HAART coverage along with risk behaviours that change with HAART coverage. We determined the potential impact of changes in risk behaviour on the outcomes of Treatment as Prevention strategies. Model results show that HIV incidence and prevalence decline only above threshold levels of HAART coverage, which depends strongly on risk behaviour parameter values. Expanding HAART coverage with simultaneous reduction in risk behaviour act synergistically to accelerate the drop in HIV incidence and prevalence. Above the thresholds, additional HAART coverage is always sufficient to reverse the impact of HAART optimism on incidence and prevalence. Applying the model to an HIV epidemic in Vancouver, Canada, showed no evidence of HAART optimism in that setting.

Conclusions

Our results suggest that Treatment as Prevention has significant potential for controlling the HIV epidemic once HAART coverage reaches a threshold. Furthermore, expanding HAART coverage combined with interventions targeting risk behaviours amplify the preventive impact, potentially driving the HIV epidemic to elimination.

The roles of immune memory and aging in protective immunity and endogenous reactivation of tuberculosis

Finding more effective vaccines against tuberculosis (TB) and improved preventive treatments against endogenous reactivation of latent TB is strategic to block transmission and reach the WHO goal of eliminating TB by 2050. Key related open questions in TB research include: i) what are the determinants of a strong memory response upon primary infection? ii) what is the role of cytokines towards protective memory response against a secondary infection? iii) what are the mechanisms responsible for the increased risk of reactivation in elderly individuals? To address these questions, we explored a computational model of the immune response to Mycobacterium tuberculosis including a mathematical description of immunosenescence and the generation and maintenance of immune memory. Sensitivity analysis techniques, together with extensive model characterization and in silico experiments, were applied to identify key mechanisms controlling TB reactivation and immunological memory. Key findings of this study are summarized by the following model predictions: i) increased strength and duration of memory protection is associated with higher levels of Tumor Necrosis Factor- (TNF) during primary infection; ii) production of TNF, but not of interferon-, by memory T cells during secondary infection is a major determinant of effective protection; iii) impaired recruitment of CD4+ T cells may promote reactivation of latent TB infections in aging hosts. This study is a first attempt to consider the immune dynamics of a persistent infection throughout the lifetime of the host, taking into account immunosenescence and memory. While the model is TB specific, the results are applicable to other persistent bacterial infections and can aid in the development, evaluation and refinement of TB treatment and/or vaccine protocols.

Modelling HIV and MTB co-infection including combined treatment strategies

A new host-pathogen model is described that simulates HIV-MTB co-infection and treatment, with the objective of testing treatment strategies. The model includes CD4+ and CD8+ T cells, resting and activated macrophages, HIV and Mycobacterium tuberculosis (MTB). For TB presentation at various stages of HIV disease in a co-infected individual, combined treatment strategies were tested with different relative timings of treatment for each infection. The stages were early HIV disease, late HIV disease and AIDS. The main strategies were TB treatment followed by anti-retroviral therapy (ART) after delays of 15 days, 2 months and 6 months. ART followed by TB treatment was an additional strategy that was tested. Treatment was simulated with and without drug interaction. Simulation results were that TB treatment first followed by ART after a stage-dependent delay has the best outcome. During early HIV disease a 6 month delay is acceptable. During late HIV disease, a 2 month delay is best. During AIDS it is better to start ART after 15 days. However, drug interaction works against the benefits of early ART. These results agree with expert reviews and clinical trials.

Mathematical models of the epidemiology and control of drug-resistant TB

Recent reports of extensively drug-resistant TB in South Africa have renewed concerns that antibiotic resistance may undermine progress in TB control. We review three major questions for which mathematical models elucidate the epidemiology and control of drug-resistant TB. How is multiple drug-resistant Mycobacterium tuberculosis selected for in individuals exposed to combination chemotherapy? What factors determine the prevalence of drug-resistant TB? Which interventions to prevent the spread of drug-resistant TB are effective and feasible? Models offer insight into the acquisition and amplification of drug resistance, reveal the importance of distinguishing the intrinsic and extrinsic determinants of the reproductive capacity of drug-resistant M. tuberculosis, and demonstrate the cost effectiveness of interventions for drug-resistant TB. These models also highlight knowledge gaps for which new research will improve our ability to project trends of drug resistance and develop more effective policies for its control.

Assessing the impact of feline immunodeficiency virus and bovine tuberculosis co-infection in African lions

Bovine tuberculosis (BTB), caused by Mycobacterium bovis, is a disease that was introduced relatively recently into the Kruger National Park (KNP) lion population. Feline immunodeficiency virus (FIV(ple)) is thought to have been endemic in lions for a much longer time. In humans, co-infection between Mycobacterium tuberculosis and human immunodeficiency virus increases disease burden. If BTB were to reach high levels of prevalence in lions, and if similar worsening effects would exist between FIV(ple) and BTB as for their human equivalents, this could pose a lion conservation problem. We collected data on lions in KNP from 1993 to 2008 for spatio-temporal analysis of both FIV(ple) and BTB, and to assess whether a similar relationship between the two diseases exists in lions. We found that BTB prevalence in the south was higher than in the north (72 versus 19% over the total study period) and increased over time in the northern part of the KNP (0-41%). No significant spatio-temporal differences were seen for FIV(ple) in the study period, in agreement with the presumed endemic state of the infection. Both infections affected haematology and blood chemistry values, FIV(ple) in a more pronounced way than BTB. The effect of co-infection on these values, however, was always less than additive. Though a large proportion (31%) of the lions was co-infected with FIV(ple) and M. bovis, there was no evidence for a synergistic relation as in their human counterparts. Whether this results from different immunopathogeneses remains to be determined.

Epidemiological models of Mycobacterium tuberculosis complex infections

The resurgence of tuberculosis in the 1990s and the emergence of drug-resistant tuberculosis in the first decade of the 21st century increased the importance of epidemiological models for the disease. Due to slow progression of tuberculosis, the transmission dynamics and its long-term effects can often be better observed and predicted using simulations of epidemiological models. This study provides a review of earlier study on modeling different aspects of tuberculosis dynamics. The models simulate tuberculosis transmission dynamics, treatment, drug resistance, control strategies for increasing compliance to treatment, HIV/TB co-infection, and patient groups. The models are based on various mathematical systems, such as systems of ordinary differential equations, simulation models, and Markov Chain Monte Carlo methods. The inferences from the models are justified by case studies and statistical analysis of TB patient datasets.

IN-VIVOMATHEMATICAL STUDY OF CO-INFECTION DYNAMICS OF HIV-1 ANDMYCOBACTERIUM TUBERCULOSIS

Human Immunodeficiency Virus type-1 (HIV-1) fuels the pathogenesis of Mycobacterium tuberculosis (Mtb) in humans. We develop a mathematical model in an attempt to understand the immune mechanisms that are involved during the co-infection of Mtb and HIV-1. Our study reveals that infection of an Mtb infected individual with HIV-1 results in fast development of active TB. The mathematical model analysis and simulations show that Mtb infection is linked to HIV infection through macrophages and CD4+ T cells. The study shows that depletion of macrophages and CD4+ T cells by HIV-1 worsens the picture of Mtb infection and in-turn Mtb infection affects the progression of HIV-1 infection since it is also capable of inducing rapid replication of HIV. Our analytical and numerical simulations show that macrophages are a potential reservoir of HIV particles during HIV-1 infection. Co-infection simulations reveal that co-infection exacerbates more the pathogen that caused the first infection. Simulations also show that co-infection disease progression patterns converge to a similar trend after a considerable time interval irrespective of which pathogen first caused infection and the second pathogen that caused co-infection. This work suggests directions for further studies and potential treatment strategies.

MATHEMATICAL MODELING OF CHEMOTHERAPY OF HUMAN TB INFECTION

This work assesses the impact of the first line drug regimen on active disease control under the stipulated time of tuberculosis (TB) treatment. In an effort to understand why a robust immune response mechanism sometimes fails to completely control TB infection, we first developed a model that captures the human immune response mechanisms to Mycobacterium tuberculosis (Mtb) infection. We then extended the model to include drug therapy. The drug therapy model is used to assess the potency of the recommended six-month TB drug chemotherapy in infected individuals. The efficacy of each drug was explored and observations show that low drug efficacy values result in extension of treatment period. The numerical results confirm typical clinical disease progression patterns noticed in individuals under TB therapy. The drug model simulations and analysis show that administration of the recommended first line three-drug regimen normally cures the TB infection. Using the model, we established that only Isoniazid monotherapy drug treatment, and any combination therapy of two drugs including Isoniazid are potent enough to resolve the TB infection.

THE ROLE OF DENDRITIC CELLS AND OTHER IMMUNE MECHANISMS DURING HUMAN INFECTION WITHMYCOBACTERIUM TUBERCULOSIS

Human immune response mechanisms are crucial in the control of Mycobacterium tuberculosis (Mtb) infection. Understanding the human immune mechanisms and Mtb dynamics will assist in understanding the occurrence of different clinical outcomes experienced by individuals infected with Mtb. This work elaborates the role of dendritic cells (DCs) and other immune mechanisms in Mtb infection. We develop a model to predict disease progression scenarios, that is latency or active disease. Model analysis shows that occurrence of active disease is much attributed to the Mtb pathogen's ability to persist outside the intracellular environment and that strong immune response results in latent TB while relatively weak immune response result in active tuberculosis (TB). Our numerical results show that DCs recruitment, antigen (Ag) uptake and maturation affect the priming of the immune response and T cells levels at the site of infection. This study shows the crucial link between the innate immune mechanisms and the adaptive immune mechanisms. It also suggests directions for further basic studies and potential new treatment strategies.

Host immune responses that promote initial HIV spread

The host inflammatory response to HIV invasion is a necessary component of the innate antiviral activity that vaccines and early interventions seek to exploit/enhance. However, the response is dependent on CD4+ T-helper cell 1 (Th1) recruitment and activation. It is this very recruitment of HIV-susceptible target cells that is associated with the initial viral proliferation. Hence, global enhancement of the inflammatory response by T-cells and dendritic cells will likely feed viral propagation. Mucosal entry sites contain inherent pathways, in the form of natural regulatory T-cells (nTreg), that globally dampen the inflammatory response. We created a model of this inflammatory response to virus as well as inherent nTreg-mediated regulation of Th1 recruitment and activation. With simulations using this model we sought to address the net effect of nTreg activation and its specific functions as well as identify mechanisms of the natural inflammatory response that are best targeted to inhibit viral spread without compromising initial antiviral activity. Simulation results provide multiple insights that are relevant to developing intervention strategies that seek to exploit natural immune processes: (i) induction of the regulatory response through nTreg activation expedites viral proliferation due to viral production by nTreg itself and not to reduced Natural Killer (NK) cell activity; (ii) at the same time, induction of the inflammation response through either DC activation or Th1 activation expedites viral proliferation; (iii) within the inflammatory pathway, the NK response is an effective controller of viral proliferation while DC-mediated stimulation of T-cells is a significant driver of viral proliferation; and (iv) nTreg-mediated DC deactivation plays a significant role in slowing viral proliferation by inhibiting T-cell stimulation, making this function an aide to the antiviral immune response.

Rule-based modelling of iron homeostasis in tuberculosis

To establish itself within the host system, Mycobacterium tuberculosis (Mtb) has formulated various means of attacking the host system. One such crucial strategy is the exploitation of the iron resources of the host system. Obtaining and maintaining the required concentration of iron becomes a matter of contest between the host and the pathogen, both trying to achieve this through complex molecular networks. The extent of complexity makes it important to obtain a systems perspective of the interplay between the host and the pathogen with respect to iron homeostasis. We have reconstructed a systems model comprising 92 components and 85 protein-protein or protein-metabolite interactions, which have been captured as a set of 194 rules. Apart from the interactions, these rules also account for protein synthesis and decay, RBC circulation and bacterial production and death rates. We have used a rule-based modelling approach, Kappa, to simulate the system separately under infection and non-infection conditions. Various perturbations including knock-outs and dual perturbation were also carried out to monitor the behavioral change of important proteins and metabolites. From this, key components as well as the required controlling factors in the model that are critical for maintaining iron homeostasis were identified. The model is able to re-establish the importance of iron-dependent regulator (ideR) in Mtb and transferrin (Tf) in the host. Perturbations, where iron storage is increased, appear to enhance nutritional immunity and the analysis indicates how they can be harmful for the host. Instead, decreasing the rate of iron uptake by Tf may prove to be helpful. Simulation and perturbation studies help in identifying Tf as a possible drug target. Regulating the mycobactin (myB) concentration was also identified as a possible strategy to control bacterial growth. The simulations thus provide significant insight into iron homeostasis and also for identifying possible drug targets for tuberculosis.

Effect of treating co-infections on HIV-1 viral load: a systematic review

Co-infections contribute to HIV-related pathogenesis and often increase viral load in HIV-infected people. We did a systematic review to assess the effect of treating key co-infections on plasma HIV-1-RNA concentrations in low-income countries. We identified 18 eligible studies for review: two on tuberculosis, two on malaria, six on helminths, and eight on sexually transmitted infections, excluding untreatable or non-pathogenic infections. Standardised mean plasma viral load decreased after the treatment of co-infecting pathogens in all 18 studies. The standardised mean HIV viral-load difference ranged from -0.04 log(10) copies per mL (95% CI -0.24 to 0.16) after syphilis treatment to -3.47 log(10) copies per mL (95% CI -3.78 to -3.16) after tuberculosis treatment. Of 14 studies with variance data available, 12 reported significant HIV viral-load differences before and after treatment. Although many of the viral-load reductions were 1.0 log(10) copies per mL or less, even small changes in plasma HIV-RNA concentrations have been shown to slow HIV progression and could translate into population-level benefits in lowering HIV transmission risk.

Tuberculosis incidence and risk factors among patients living with HIV/AIDS in public health service institutions in Brasilia, Federal District

In order to estimate the incidence of and risk factors for developing tuberculosis, the clinical charts of a retrospective cohort of 281 HIV-positive adults, who were notified to the AIDS Program of the Health Department of Brasilia in 1998, were reviewed in 2003. All the patients were treatment-naive regarding antiretroviral therapy at the time of inclusion in the cohort. Twenty-nine patients were identified as having tuberculosis at the start of the study. Thirteen incident tuberculosis cases were identified during the 60 months of follow-up, with an incidence density rate of 1.24/100 person-years. Tuberculosis incidence was highest among patients with baseline CD4+ T-lymphocyte counts < or = 200 cells/microl who were not using antiretroviral therapy (incidence = 5.47; 95% CI = 2.73 to 10.94). Multivariate analysis showed that baseline CD4+ T-lymphocyte counts < or = 200 cells/microl (adjusted hazard ratio [AHR] = 5.09; 95% CI = 1.27 to 20.37; p = 0.02) and non-use of antiretroviral therapy (AHR = 12.17; 95% CI = 2.6 to 56.90; p = 0.001) were independently associated with increased risk of tuberculosis.

A perturbation-based estimate algorithm for parameters of coupled ordinary differential equations, applications from chemical reactions to metabolic dynamics

Conversion of complex phenomena in medicine, pharmaceutical and systems biology fields to a system of ordinary differential equations (ODEs) and identification of parameters from experimental data and theoretical model equations can be treated as a computational engine to arrive at the best solution for chemical reactions, biochemical metabolic and intracellular pathways. Particularly, to gain insight into the pathophysiology of diabetes's metabolism in our current clinical studies, glucose kinetics and insulin secretion can be assessed by the ODE model. Parameter estimation is usually performed by minimizing a cost function which quantifies the difference between theoretical model predictions and experimental measurements. This paper explores how the numerical method and iteration program are developed to search ODE's parameters using the perturbation method, instead of the Gauss-Newton or Levenberg-Marquardt method. Several interesting applications, including Lotka-Volterra chemical reaction system, Lorenz chaos, dynamics of tetracycline hydrochloride concentration, and Bergman's Minimal Model for glucose kinetics are illustrated.

Tracking the dynamics of pathogen interactions: Modeling ecological and immune-mediated processes in a two-pathogen single-host system

Traditionally, epidemiological studies have focused on understanding the dynamics of a single pathogen, assuming no interactions with other pathogens. Recently, a large body of work has begun to explore the effects of immune-mediated interactions, arising from cross-immunity and antibody-dependent enhancement, between related pathogen strains. In addition, ecological processes such as a temporary period of convalescence and pathogen-induced mortality have led to the concept of ecological interference between unrelated diseases. There remains, however, the need for a systematic study of both immunological and ecological processes within a single framework. In this paper, we develop a general two-pathogen single-host model of pathogen interactions that simultaneously incorporates these mechanisms. We are then able to mechanistically explore how immunoecological processes mediate interactions between diseases for a pool of susceptible individuals. We show that the precise nature of the interaction can induce either competitive or cooperative associations between pathogens. Understanding the dynamic implications of multi-pathogen associations has potentially important public health consequences. Such a framework may be especially helpful in disentangling the effects of partially cross-immunizing infections that affect populations with a pre-disposition towards immunosuppression such as children and the elderly.

The dynamical implications of disease interference: correlations and coexistence

Ecological interference between unrelated diseases, caused by the temporary or permanent removal of individuals susceptible to one disease following infection with another, might be an important mechanism underlying epidemics. In this paper, we explore the potential dynamic consequences of interference by analyzing a two-disease model. By studying the stability domain of the model's equilibria, we find that the stable region of the two-disease endemic state becomes increasingly smaller as the strength of interference (largely determined by the disease-induced mortality) increases. When seasonal changes are included in the transmission rates, the bifurcation structure of the model's periodic cycles reveals that when the two diseases have similar mean transmission rates, multiple attractors in which the two diseases are strongly correlated can coexist, and that when the two diseases have very different mean transmission rates, the one with higher mean transmission rate may determine the dynamics of the system, with the other infection mimicking the behavior. We conclude that ecological interference can have important effects on the dynamical pattern of interacting diseases, the extent of which is determined by the epidemiological features of the diseases, their mean transmission rates in particular.

p38 MAPK-dependent and YY1-mediated chemokine receptors CCR5 and CXCR4 up-regulation in U937 cell line infected by Mycobacterium tuberculosis or Actinobacillus actinomycetemcomitans

We have found previously that the chemokine receptors CCR5 and CXCR4, which are the coreceptors of HIV, are up-regulated in human macrophage cell line U937 infected by Mycobacterium tuberculosis (MTB). This suggests another possibility to explain the co-infection of MTB and HIV. In order to detect the up-regulation of CCR5 and CXCR4 as a unique phenomenon of MTB infection or a ubiquitous phenomenon of pathogenic bacteria, we investigated the expression changes of these two chemokine receptors in macrophages attacked by another bacterium Actinobacillus actinomycetemcomitans (AA) (from mRNA level and protein level). To reveal the molecular mechanism of these expression changes, p38 MAPK special inhibitor SB203580 was used and the expression of CCR5 and CXCR4 negative regulator YY1 transfactor was analyzed. Finally, we conclude that the up-regulation of CCR5 and CXCR4 can at least partially contribute to the down-regulation of transfactor YY1 which is p38 MAPK pathway-dependent and this up-regulation has little relationship with MTB and HIV co-infection.

Immunoadjuvant prednisolone therapy for HIV-associated tuberculosis: a phase 2 clinical trial in Uganda

Background. Human immunodeficiency virus (HIV)-infected patients with tuberculosis (TB) respond to effective antituberculous therapy, but their prognosis remains poor. Mounting evidence from clinical studies supports the concept of copathogenesis in which immune activation that is triggered by TB and mediated by cytokines stimulates viral replication and worsens HIV infection, especially when immune function is preserved.Methods. We performed a phase 2, randomized, double-blind, placebo-controlled clinical trial in Kampala, Uganda, to determine whether immunoadjuvant prednisolone therapy in HIV-infected patients with TB who have CD4(+) T cell counts >/=200 cells/ mu L is safe and effective at increasing CD4(+) T cell counts.Results. Short-term prednisolone therapy reduced levels of immune activation and tended to produce higher CD4(+) T cell counts. Although prednisolone therapy was associated with a more rapid clearance of Mycobacterium tuberculosis from the sputum, it was also associated with a transient increase in HIV RNA levels, which receded when prednisolone therapy was discontinued. The intervention worsened underlying hypertension and caused fluid retention and hyperglycemia.Conclusion. The benefits of prednisolone therapy on immune activation and CD4(+) T cell counts do not outweigh the risks of adverse events in HIV-infected patients with TB and preserved immune function.

A model for the study of Helicobacter pylori interaction with human gastric acid secretion

We present a comprehensive mathematical model describing Helicobacter pylori interaction with the human gastric acid secretion system. We use the model to explore host and bacterial conditions that allow persistent infection to develop and be maintained. Our results show that upon colonization, there is a transient period (day 1-20 post-infection) prior to the establishment of persistence. During this period, changes to host gastric physiology occur including elevations in positive effectors of acid secretion (such as gastrin and histamine). This is promoted by reduced somatostatin levels, an inhibitor of acid release. We suggest that these changes comprise compensatory mechanisms aimed at restoring acid to pre-infection levels. We also show that ammonia produced by bacteria sufficiently buffers acid promoting bacteria survival and growth.

The human immune response to Mycobacterium tuberculosis in lung and lymph node

A key issue for the study of tuberculosis is to understand why individuals infected with Mycobacterium tuberculosis (Mtb) experience different clinical outcomes. To better understand the dynamics of Mtb infection and immunity, we have previously developed a temporal mathematical model that qualitatively and quantitatively characterizes the cellular and cytokine control network during infection. In this work we extend that model to a two compartmental model to capture the important processes of cellular activation and priming that occur between the lung and the nearest draining lymph node. We are able to reproduce typical disease progression scenarios including primary infection, latency or clearance. Then we use the model to predict key processes determining these different disease trajectories (i.e. identify bifurcation parameters), suggesting directions for further basic science study and potential new treatment strategies.

On treatment of tuberculosis in heterogeneous populations

Global eradication of tuberculosis (TB) is an international agenda. Thus understanding effects of treatment of TB in different settings is crucial. In previous work, we introduced the framework for a mathematical model of epidemic TB in demographically distinct, heterogeneous populations. Simulations showed the importance of genetic susceptibility in determining endemic prevalence levels. In the work presented here, we include treatment and investigate different strategies for treatment of latent and active TB disease in heterogeneous populations. We illustrate how the presence of a genetically susceptible subpopulation dramatically alters effects of treatment in the same way a core population does in the setting of sexually transmitted diseases. In addition, we evaluate treatment strategies that focus specifically on this subpopulation, and our results indicate that genetically susceptible subpopulations should be accounted for when designing treatment strategies to achieve the greatest reduction in disease prevalence.

Immune response and virus population composition: HIV as a case study

Based on the current understanding of the immune response, we present what we believe to be a new model of intrahost virus dynamics. The model takes into account the relationship between virus replication rate and the level of antigen displayed by infected cells, and shows how the cell-directed immune response controls both virus load and virus replication rate. In contrast to conventional wisdom, it shows that the predominant virus variant does not necessarily have the highest replication rate. A strong immune response produces a selective advantage for latent viruses, whereas a deteriorating immune response invites in viruses of higher replication rates. The model is analysed in light of the well-studied HIV/AIDS disease progression, and shows how a wide range of major, seemingly unrelated issues in the study of HIV may be accounted for in a simple and unified manner.

A model to predict cell-mediated immune regulatory mechanisms during human infection with Mycobacterium tuberculosis

A key issue for the study of tuberculosis infection (TB) is to understand why individuals infected with Mycobacterium tuberculosis experience different clinical outcomes. Elaborating the immune mechanisms that determine whether an infected individual will suffer active TB or latent infection can aid in developing treatment and prevention strategies. To better understand the dynamics of M. tuberculosis infection and immunity, we have developed a virtual human model that qualitatively and quantitatively characterizes the cellular and cytokine control network operational during TB infection. Using this model, we identify key regulatory elements in the host response. In particular, factors affecting cell functions, such as macrophage activation and bactericidal capabilities, and effector T cell functions such as cytotoxicity and cytokine production can each be determinative. The model indicates, however, that even if latency is achieved, it may come at the expense of tissue damage if the response is not properly regulated. A balance in Th1 and Th2 immune responses governed by IFN-gamma, IL-10, and IL-4 facilitate this down-regulation. These results are further explored through virtual deletion and depletion experiments.

Glucocorticoids suppress human immunodeficiency virus type-1 long terminal repeat activity in a cell type-specific, glucocorticoid receptor-mediated fashion: direct protective effects at variance with clinical phenomenology

Glucocorticoid administration and/or excess secretion have been associated with increased Human Immunodeficiency Virus Type-1 (HIV-1) replication and AIDS progression. The HIV-1 long terminal repeat (LTR) promoter contains glucocorticoid-responsive element (GRE)-like sequences that could mediate a positive effect of glucocorticoids on HIV-1. In addition, we recently demonstrated that the HIV-1 accessory protein Vpr is a potent coactivator of the glucocorticoid receptor, which, like the host coactivator p300, potentiates the effect of glucocorticoids on GRE-containing, glucocorticoid-responsive genes. Such an effect may increase the sensitivity of several host target tissues to glucocorticoids by several fold, and may, thus, contribute to a positive effect of glucocorticoids on the HIV-1-LTR in infected host cells. In this study, we determined the direct effect of glucocorticoids on HIV-1-LTR by examining the ability of dexamethasone to modulate the activity of this promoter coupled to the luciferase reporter gene in human cell lines. Dexamethasone markedly inhibited Tat-stimulated, p300- or Vpr-enhanced luciferase activities in a cell-type specific, dose-dependent, and glucocorticoid receptor-mediated fashion. This effect of dexamethasone was not potentiated by Vpr, was antagonized by the glucocorticoid receptor antagonist RU 486 and required the DNA-binding domain of the receptor. These data suggest that the inhibitory effect of glucocorticoids on the HIV-1-LTR may be exerted via non-GRE-dependent inhibition of the strongly positive host transcription factor NF-kappaB, which interacts with the DNA- and ligand-binding domains of the receptor. Alternatively, it is also possible that dexamethasone-activated glucocorticoid receptor competes with other transcription factors for their binding sites on the promoter region or squelches transcription factors shared by HIV-1-LTR and glucocorticoid-responsive promoters. We conclude that glucocorticoids suppress, rather than stimulate, the HIV-1 promoter, thus acting, protectively for the host. Their apparent negative clinical association with AIDS is most likely due to immunosuppression of the host.