Tuberculosis research: going forward with a powerful "translational systems biology" approach

A brief overview of mathematical modeling of the within-host dynamics of Mycobacterium tuberculosis

Tuberculosis (TB), a disease caused by bacteria Mycobacterium tuberculosis (Mtb), remains one of the major infectious diseases of humans with 10 million TB cases and 1.5 million deaths due to TB worldwide yearly. Upon exposure of a new host to Mtb, bacteria typically infect one local site in the lung, but over time, Mtb disseminates in the lung and in some cases to extrapulmonary sites. The contribution of various host components such as immune cells to Mtb dynamics in the lung, its dissemination in the lung and outside of the lung, remains incompletely understood. Here we overview different types of mathematical models used to gain insights in within-host dynamics of Mtb; these include models based on ordinary or partial differential equations (ODEs and PDEs), stochastic simulation models based on ODEs, agent-based models (ABMs), and hybrid models (ODE-based models linked to ABMs). We illustrate results from several of such models and identify areas for future resesarch.

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.

Mycobacterial virulence: impact on immunogenicity and vaccine research

The borderline between virulence and efficacy in live attenuated vaccine strains is often blurred and this is also the case for the Bacillus Calmette–Guérin (BCG), the only currently licensed anti-tuberculosis vaccine used on a large, global scale, which was obtained almost 100 years ago. While BCG is more than 99% identical at the genome level to Mycobacterium tuberculosis, the causative pathogen of human tuberculosis, some important differences in virulence factors cause naturally irreversible attenuation and safety of this vaccine in the immunocompetent host. Some of these virulence factors are involved in persistence capacities of the vaccine strains and also represent strong immunogens, responsible for inducing different host signaling pathways, which have to be taken into consideration for the development of revised and new vaccine strains. Here we discuss a number of selected mycobacterial features in relation to their biological functions and potential impact on virulence and vaccine efficacy.

Tuberculosis: Current Status, Diagnosis, Treatment and Development of Novel Vaccines

Tuberculosis (TB) is an infectious disease that mainly affects the lungs and spreads to other organs of the body through the haematogenous route. It is one of the ten major causes of mortality worldwide. India has the highest incidence of new- and multidrug-resistant (MDR) - TB cases in the world. Bacille Calmette-Guerin (BCG) is the vaccine commonly available against TB. BCG does offer some protection against serious forms of TB in childhood but its protective effect wanes with age. Many new innovative strategies are being trailed for the development of effective and potent vaccines like mucosal- and epitope-based vaccines, which may replace BCG or boost BCG responses. The use of nanotechnology for diagnosis and treatment of TB is also in the pipeline along with many other vaccines, which are under clinical trials. Further, in-silico models were developed for finding new drug targets and designing drugs against Mycobacterium tuberculosis (Mtb). These models offer the benefit of computational experiments which are easy, inexpensive and give quick results. This review will focus on the available treatments and new approaches to develop potent vaccines for the treatment of TB.

Immunosenescence: A systems-level overview of immune cell biology and strategies for improving vaccine responses

Immunosenescence contributes to a decreased capacity of the immune system to respond effectively to infections or vaccines in the elderly. The full extent of the biological changes that lead to immunosenescence are unknown, but numerous cell types involved in innate and adaptive immunity exhibit altered phenotypes and function as a result of aging. These manifestations of immunosenescence at the cellular level are mediated by dysregulation at the genetic level, and changes throughout the immune system are, in turn, propagated by numerous cellular interactions. Environmental factors, such as nutrition, also exert significant influence on the immune system during aging. While the mechanisms that govern the onset of immunosenescence are complex, systems biology approaches allow for the identification of individual contributions from each component within the system as a whole. Although there is still much to learn regarding immunosenescence, systems-level studies of vaccine responses have been highly informative and will guide the development of new vaccine candidates, novel adjuvant formulations, and immunotherapeutic drugs to improve vaccine responses among the aging population.

Systems approach to tuberculosis vaccine development

Tuberculosis is both highly prevalent across the world and eludes our attempts to control it. The current bacillus Calmette-Guérin vaccine has unreliable protection against adult pulmonary tuberculosis. As a result, tuberculosis vaccine development has been an ongoing area of research for several decades. Only recently have research efforts resulted in the development of several vaccine candidates that are further along in clinical trials. The majority of the barriers surrounding tuberculosis vaccine development are related to the lack of defined biomarkers for tuberculosis protective immunity and the lack of understanding of the complex interactions between the host and pathogen in the human immune system. As a result, testing various antigens discovered through molecular biology techniques have been only with surrogates of protection and do not accurately predict protective immunity. This review will address new discoveries in latency antigens and new next-generation candidate vaccines that promise the possibility of sterile eradication. Also discussed are the potentially important roles of systems biology and vaccinomics in shortening development of an efficacious tuberculosis vaccine through utilization of high-throughput technology, computer modelling and integrative approaches.

A physiologically based pharmacokinetic model of rifampin in mice

One problem associated with regimen-based development of antituberculosis (anti-TB) drugs is the difficulty of a systematic and thorough in vivo evaluation of the large number of possible regimens that arise from consideration of multiple drugs tested together. A mathematical model capable of simulating the pharmacokinetics and pharmacodynamics of experimental combination chemotherapy of TB offers a way to mitigate this problem by extending the use of available data to investigate regimens that are not initially tested. In order to increase the available mathematical tools needed to support such a model for preclinical anti-TB drug development, we constructed a preliminary whole-body physiologically based pharmacokinetic (PBPK) model of rifampin in mice, using data from the literature. Interindividual variability was approximated using Monte Carlo (MC) simulation with assigned probability distributions for the model parameters. An MC sensitivity analysis was also performed to determine correlations between model parameters and plasma concentration to inform future model development. Model predictions for rifampin concentrations in plasma, liver, kidneys, and lungs, following oral administration, were generally in agreement with published experimental data from multiple studies. Sensitive model parameters included those descriptive of oral absorption, total clearance, and partitioning of rifampin between blood and muscle. This PBPK model can serve as a starting point for the integration of rifampin pharmacokinetics in mice into a larger mathematical framework, including the immune response to Mycobacterium tuberculosis infection, and pharmacokinetic models for other anti-TB drugs.

Systems biology of fungal infection

Elucidation of pathogenicity mechanisms of the most important human-pathogenic fungi, Aspergillus fumigatus and Candida albicans, has gained great interest in the light of the steadily increasing number of cases of invasive fungal infections. A key feature of these infections is the interaction of the different fungal morphotypes with epithelial and immune effector cells in the human host. Because of the high level of complexity, it is necessary to describe and understand invasive fungal infection by taking a systems biological approach, i.e., by a comprehensive quantitative analysis of the non-linear and selective interactions of a large number of functionally diverse, and frequently multifunctional, sets of elements, e.g., genes, proteins, metabolites, which produce coherent and emergent behaviors in time and space. The recent advances in systems biology will now make it possible to uncover the structure and dynamics of molecular and cellular cause-effect relationships within these pathogenic interactions. We review current efforts to integrate omics and image-based data of host-pathogen interactions into network and spatio-temporal models. The modeling will help to elucidate pathogenicity mechanisms and to identify diagnostic biomarkers and potential drug targets for therapy and could thus pave the way for novel intervention strategies based on novel antifungal drugs and cell therapy.

Computational databases, pathway and cheminformatics tools for tuberculosis drug discovery

We are witnessing the growing menace of both increasing cases of drug-sensitive and drug-resistant Mycobacterium tuberculosis strains and the challenge to produce the first new tuberculosis (TB) drug in well over 40 years. The TB community, having invested in extensive high-throughput screening efforts, is faced with the question of how to optimally leverage these data to move from a hit to a lead to a clinical candidate and potentially, a new drug. Complementing this approach, yet conducted on a much smaller scale, cheminformatic techniques have been leveraged and are examined in this review. We suggest that these computational approaches should be optimally integrated within a workflow with experimental approaches to accelerate TB drug discovery.