Differential risk of tuberculosis reactivation among anti-TNF therapies is due to drug binding kinetics and permeability

A novel C-4-modified isotetrone acts as a potent bio-enhancer to augment the activities of anti-tuberculosis drugs against Mycobacterium tuberculosis

Mycobacterium tuberculosis is a deadly pathogen that claims millions of lives every year. Current research focuses on finding new anti-tuberculosis drugs that are safe and effective, with lesser side effects and toxicity. One important approach is to identify bio-enhancers that can improve the effectiveness of anti-tuberculosis drugs, resulting in reduced doses and shortened treatment times. The present study investigates the use of C-4 modified isotetrones as bio-enhancers. A series of studies suggest an isotetrone, labeled as C11, inhibits growth, improves MIC, MBC and enhances the killing of M. tuberculosis H37Rv strain when used in combination with the first line and injectable anti-TB drugs in a dose-dependent manner. The combination of C11 and rifampicin also reduces the generation of spontaneous mutants against rifampicin and reaches a mutation prevention concentration (MPC) with moderate rifampicin concentrations. The identified compounds are effective against the MDR strain of M. tuberculosis and non-cytotoxic in HepG2 cells. We find that C11 induces the generation of reactive oxygen species (ROS) inside macrophages and within bacteria, resulting in better efficacy.

Characterizing the immune response to Mycobacterium tuberculosis: a comprehensive narrative review and implications in disease relapse

Introduction

Tuberculosis remains the leading cause of death from infectious diseases among adults worldwide. To date, an overarching review of the immune response to Mtb in humans has not been fully elucidated, with innate immunity remaining poorly understood due to historic focus on adaptive immunity. Specifically, there is a major gap concerning the contribution of the immune system to overall bacterial clearance, particularly residual bacteria. This review aims to describe the time course of interactions between the host immune system and Mtb, from the start of the infection to the development of the adaptive response. Concordantly, we aim to crystallize the pathogenic effects and immunoevasive mechanisms of Mtb. The translational value of animal data is also discussed.

Methods

The literature search was conducted in the PubMed, ScienceDirect, and Google Scholar databases, which included reported research from 1990 until 2024. A total of 190 publications were selected and screened, of which 108 were used for abstraction and 86 were used for data extraction. Graphical summaries were created using the narrative information (i.e., recruitment, recognition, and response) to generate clear visual representations of the immune response at the cellular and molecular levels.

Results

The key cellular players included airway epithelial cells, alveolar epithelial cells, neutrophils, natural killer cells, macrophages, dendritic cells, T cells, and granulomatous lesions; the prominent molecular players included IFN-γ, TNF-α, and IL-10. The paper also sheds light on the immune response to residual bacteria and applications of the data.

Discussion

We provide a comprehensive characterization of the key immune players that are implicated in pulmonary tuberculosis, in line with the organs or compartments in which mycobacteria reside, offering a broad vignette of the immune response to Mtb and how it responds to residual bacteria. Ultimately, the data presented could provide immunological insights to help establish optimized criteria for identifying efficacious treatment regimens and durations for relapse prevention in the modeling and simulation space and wider fields.

Successful rescue TNF-α blocking for Mycobacterium genavense - Related immune reconstitution inflammatory syndrome: A case report

Immune reconstitution inflammatory syndrome (IRIS) has been reported in immunocompromised patients with disseminated Mycobacterium genavense. Management relies on high-dose corticosteroids. We describe two cases of late-onset corticosteroid-refractory IRIS related to disseminated infection in a HIV-positive patient and a renal transplant patient who had a favorable outcome with a monoclonal TNF-α blocker.

A framework for multi-scale intervention modeling: virtual cohorts, virtual clinical trials, and model-to-model comparisons

Computational models of disease progression have been constructed for a myriad of pathologies. Typically, the conceptual implementation for pathology-related in-silico intervention studies has been ad-hoc and similar in design to experimental studies. We introduce a multi-scale interventional design (MID) framework toward two key goals: tracking of disease dynamics from within-body to patient to population scale; and tracking impact(s) of interventions across these same spatial scales. Our MID framework prioritizes investigation of impact on individual patients within virtual pre-clinical trials, instead of replicating the design of experimental studies. We apply a MID framework to develop, organize, and analyze a cohort of virtual patients for the study of tuberculosis (TB) as an example disease. For this study, we use HostSim: our next-generation whole patient-scale computational model of individuals infected with Mycobacterium tuberculosis. HostSim captures infection within lungs by tracking multiple granulomas, together with dynamics occurring with blood and lymph node compartments, the compartments involved during pulmonary TB. We extend HostSim to include a simple drug intervention as an example of our approach and use our MID framework to quantify the impact of treatment at cellular and tissue (granuloma), patient (lungs, lymph nodes and blood), and population scales. Sensitivity analyses allow us to determine which features of virtual patients are the strongest predictors of intervention efficacy across scales. These insights allow us to identify patient-heterogeneous mechanisms that drive outcomes across scales.

A secreted form of chorismate mutase (Rv1885c) in Mycobacterium bovis BCG contributes to pathogenesis by inhibiting mitochondria-mediated apoptotic cell death of macrophages

BACKGROUND

Mycobacterium tuberculosis is the causative agent of tuberculosis (TB), and its pathogenicity is associated with its ability to evade the host defense system. The secretory form of the chorismate mutase of M. tuberculosis (TBCM, encoded by Rv1885c) is assumed to play a key role in the pathogenesis of TB; however, the mechanism remains unknown.

METHODS

A tbcm deletion mutant (B∆tbcm) was generated by targeted gene knockout in BCG to investigate the pathogenic role of TBCM in mice or macrophages. We compared the pathogenesis of B∆tbcm and wild-type BCG in vivo by measuring the bacterial clearance rate and the degree of apoptosis. Promotion of the intrinsic apoptotic pathway was evaluated in infected bone marrow-derived macrophages (BMDMs) by measuring apoptotic cell death, loss of mitochondrial membrane potential and translocation of pore-forming proteins. Immunocytochemistry, western blotting and real-time PCR were also performed to assess the related protein expression levels after infection. Furthermore, these findings were validated by complementation of tbcm in BCG.

RESULTS

Deletion of the tbcm gene in BCG leads to reduced pathogenesis in a mouse model, compared to wild type BCG, by promoting apoptotic cell death and bacterial clearance. Based on these findings, we found that intrinsic apoptosis and mitochondrial impairment were promoted in B∆tbcm-infected BMDMs. B∆tbcm down-regulates the expression of Bcl-2, which leads to mitochondrial outer membrane permeabilization (MOMP), culminating in cytochrome c release from mitochondria. Consistent with this, transcriptome profiling also indicated that B∆tbcm infection is more closely related to altered mitochondrial-related gene expression than wild-type BCG infection, suggesting an inhibitory role of TBCM in mitochondrial dysfunction. Moreover, genetic complementation of B∆tbcm (C∆tbcm) restored its capacity to inhibit mitochondria-mediated apoptotic cell death.

CONCLUSIONS

Our findings demonstrate the contribution of TBCM to bacterial survival, inhibiting intrinsic apoptotic cell death of macrophages as a virulence factor of M. tuberculosis complex (MTBC) strains, which could be a potential target for the development of TB therapy.

Development and Analysis of Multiscale Models for Tuberculosis: From Molecules to Populations

Although infectious disease dynamics are often analyzed at the macro-scale, increasing numbers of drug-resistant infections highlight the importance of within-host modeling that simultaneously solves across multiple scales to effectively respond to epidemics. We review multiscale modeling approaches for complex, interconnected biological systems and discuss critical steps involved in building, analyzing, and applying such models within the discipline of model credibility. We also present our two tools: CaliPro, for calibrating multiscale models (MSMs) to datasets, and tunable resolution, for fine- and coarse-graining sub-models while retaining insights. We include as an example our work simulating infection with Mycobacterium tuberculosis to demonstrate modeling choices and how predictions are made to generate new insights and test interventions. We discuss some of the current challenges of incorporating novel datasets, rigorously training computational biologists, and increasing the reach of MSMs. We also offer several promising future research directions of incorporating within-host dynamics into applications ranging from combinatorial treatment to epidemic response.

Tumor Necrosis Factor: What Is in a Name?

Tumor Necrosis Factor was one of the first cytokines described in the literature as a soluble mediator of cytotoxicity to tumors. Over the years, more extensive research that tried to employ Tumor Necrosis Factor in cancer treatments showed nevertheless that it mainly functioned as a proinflammatory cytokine. However, this did not stop the search for the holy grail of cancer research: A cytokine that could act as a one-stop treatment for solid tumors and lymphomas. This review will summarize the long experimental history of Tumor Necrosis Factor that caused the initial observations of a tumor necrotizing cytokine that could serve as a potential cancer treatment and discuss the current state of research into this side of the activities of Tumor Necrosis Factor.

Effector memory CD4+ T cells induce damaging innate inflammation and autoimmune pathology by engaging CD40 and TNFR on myeloid cells

Cytokine storm and sterile inflammation are common features of T cell-mediated autoimmune diseases and T cell-targeted cancer immunotherapies. Although blocking individual cytokines can mitigate some pathology, the upstream mechanisms governing overabundant innate inflammatory cytokine production remain unknown. Here, we have identified a critical signaling node that is engaged by effector memory T cells (T_EM) to mobilize a broad proinflammatory program in the innate immune system. Cognate interactions between T_EM and myeloid cells led to induction of an inflammatory transcriptional profile that was reminiscent, yet entirely independent, of classical pattern recognition receptor (PRR) activation. This PRR-independent "de novo" inflammation was driven by preexisting T_EM engagement of both CD40 and tumor necrosis factor receptor (TNFR) on myeloid cells. Cytokine toxicity and autoimmune pathology could be completely rescued by ablating these pathways genetically or pharmacologically in multiple models of T cell-driven inflammation, indicating that T_EM instruction of the innate immune system is a primary driver of associated immunopathology. Thus, we have identified a previously unknown trigger of cytokine storm and autoimmune pathology that is amenable to therapeutic interventions.

Leishmaniasis in the United States: Emerging Issues in a Region of Low Endemicity

Leishmaniasis, a chronic and persistent intracellular protozoal infection caused by many different species within the genus Leishmania, is an unfamiliar disease to most North American providers. Clinical presentations may include asymptomatic and symptomatic visceral leishmaniasis (so-called Kala-azar), as well as cutaneous or mucosal disease. Although cutaneous leishmaniasis (caused by Leishmania mexicana in the United States) is endemic in some southwest states, other causes for concern include reactivation of imported visceral leishmaniasis remotely in time from the initial infection, and the possible long-term complications of chronic inflammation from asymptomatic infection. Climate change, the identification of competent vectors and reservoirs, a highly mobile populace, significant population groups with proven exposure history, HIV, and widespread use of immunosuppressive medications and organ transplant all create the potential for increased frequency of leishmaniasis in the U.S. Together, these factors could contribute to leishmaniasis emerging as a health threat in the U.S., including the possibility of sustained autochthonous spread of newly introduced visceral disease. We summarize recent data examining the epidemiology and major risk factors for acquisition of cutaneous and visceral leishmaniasis, with a special focus on implications for the United States, as well as discuss key emerging issues affecting the management of visceral leishmaniasis.

TAM receptors and their ligand-mediated activation: Role in atherosclerosis

TAM family tyrosine kinase receptors including Tyro3, Axl, and MerTK are the key efferocytosis receptors presenting on antigen-presenting cell that mediate the clearance of apoptotic cells. They are thought to regulate inflammatory diseases by modulating inflammatory response and efferocytosis. Recent studies have revealed novel roles of TAM receptors in the biosynthesis of specialized pro-resolving mediators (SPMs) and inflammation resolution. In this chapter, we discuss the central roles of TAM signaling in atherosclerosis focusing on their regulation in efferocytosis and inflammation resolution and highlight the unique therapeutic potential of SPMs in blocking the progression of atherosclerosis.

Susceptibility to Intracellular Infections: Contributions of TNF to Immune Defense

An interesting puzzle is the fact that an infection of a tumor necrosis factor α (TNF)-deficient host with pathogens such as bacteria or parasites that reside intracellularly inevitably ends fatally. Is this due to one specific role of TNF in the immune defense or are different functions responsible for this outcome? In this review we provide an update of the functions of TNF in the defense against the intracellular pathogens Listeria monocytogenes, Mycobacterium tuberculosis, and Leishmania major. Furthermore, we discuss the role of TNF in the generation of proinflammatory macrophages in mouse models of infection and summarize briefly the potential consequences of anti-TNF treatment for infectious diseases.

TNF-α antagonists differentially induce TGF-β1-dependent resuscitation of dormant-like Mycobacterium tuberculosis

TNF-α- as well as non-TNF-α-targeting biologics are prescribed to treat a variety of immune-mediated inflammatory disorders. The well-documented risk of tuberculosis progression associated with anti-TNF-α treatment highlighted the central role of TNF-α for the maintenance of protective immunity, although the rate of tuberculosis detected among patients varies with the nature of the drug. Using a human, in-vitro granuloma model, we reproduce the increased reactivation rate of tuberculosis following exposure to Adalimumab compared to Etanercept, two TNF-α-neutralizing biologics. We show that Adalimumab, because of its bivalence, specifically induces TGF-β1-dependent Mycobacterium tuberculosis (Mtb) resuscitation which can be prevented by concomitant TGF-β1 neutralization. Moreover, our data suggest an additional role of lymphotoxin-α–neutralized by Etanercept but not Adalimumab–in the control of latent tuberculosis infection. Furthermore, we show that, while Secukinumab, an anti-IL-17A antibody, does not revert Mtb dormancy, the anti-IL-12-p40 antibody Ustekinumab and the recombinant IL-1RA Anakinra promote Mtb resuscitation, in line with the importance of these pathways in tuberculosis immunity.

Mycobacterium tuberculosis (Mtb) is the world’s leading infectious killer. Multi-cellular immune structures called granulomas may constitute a latent form of Mtb infection and a potential reservoir for future cases. Post-marketing surveillance data suggested that Mtb protective immunity is unequally impacted by different TNF-α-targeting drugs used to treat inflammatory disorders. We used an in-vitro granuloma model to reproduce these clinical observations and gain mechanistic insights and, in addition, to assess the risk of tuberculosis reactivation associated with the use of other immunomodulatory drugs. These results may inspire pharmacologists to design future drug-development strategies of biologics in particular, while immunologists and microbiologists will find a relevant experimental approach to disentangle the complex interactions involved in Mtb protective immunity and immunopathogenesis.

The impact of the interleukin 12/23 inhibitor ustekinumab on the risk of infections in patients with psoriatic arthritis

Introduction: Psoriatic arthritis (PsA) is characterized by chronic inflammation mediated by pro-inflammatory cytokines, with clinical features resulting from dysfunctional integrated signaling pathways affecting different constituents of the immune system. Increased understanding of the processes responsible for enthesitis, synovial inflammation, joint erosion, and new bone formation during PsA has led to development of biologic therapies targeting these cytokines. There is an increased risk of opportunistic infections in patients with PsA, and this risk is increased further with targeted biologic therapy.Areas covered: This paper reviews the role of the interleukin (IL)-12, IL-23 and IL-17 axis in the pathogenesis of PsA. The data suggest that ustekinumab is associated with a low risk of infections in patients with PsA, including tuberculosis or hepatitis reactivation. No live vaccines can be safely administered; ustekinumab is contraindicated/cannot be given with live vaccines. However, long-term treatment with ustekinumab does not impair the immune response to these vaccines when administered after an appropriate interval.Expert opinion: Ustekinumab is associated with a low risk of serious and opportunistic infections. More research is needed to confirm these findings specifically in patients with PsA, and comparative studies are needed to investigate the relative risk of infection with different biologics.

Practical Guidelines for Managing Patients With Psoriasis on Biologics: An Update

The paradigm for treating inflammatory diseases has shifted dramatically in the past 10 to 20 years with the discovery of targeted therapeutics or "biologic" agents. Patients with rheumatoid arthritis, inflammatory bowel disease, psoriatic arthritis, and psoriasis, among others, are reaping the benefits of decades of bench to bedside research, allowing them to live more productive lives with less side effects than traditional systemic therapies. Despite these advances, many physicians unfamiliar with biologics are left to care for the basic needs of these patients and may be unaware of the multisystem comorbidities associated with psoriasis and the screening, monitoring, and other special considerations required of biologics patients. This can be overwhelming to primary care physicians and inadvertently expose patients to undue risks. The aim of this review is to provide a practical approach for all health care providers caring for patients with psoriasis being treated with biologics to facilitate communication with their treating dermatologist and ultimately provide patients with more comprehensive care.

Dynamic balance of pro- and anti-inflammatory signals controls disease and limits pathology

Immune responses to pathogens are complex and not well understood in many diseases, and this is especially true for infections by persistent pathogens. One mechanism that allows for long-term control of infection while also preventing an over-zealous inflammatory response from causing extensive tissue damage is for the immune system to balance pro- and anti-inflammatory cells and signals. This balance is dynamic and the immune system responds to cues from both host and pathogen, maintaining a steady state across multiple scales through continuous feedback. Identifying the signals, cells, cytokines, and other immune response factors that mediate this balance over time has been difficult using traditional research strategies. Computational modeling studies based on data from traditional systems can identify how this balance contributes to immunity. Here we provide evidence from both experimental and mathematical/computational studies to support the concept of a dynamic balance operating during persistent and other infection scenarios. We focus mainly on tuberculosis, currently the leading cause of death due to infectious disease in the world, and also provide evidence for other infections. A better understanding of the dynamically balanced immune response can help shape treatment strategies that utilize both drugs and host-directed therapies.

Low Levels of T Cell Exhaustion in Tuberculous Lung Granulomas

The hallmarks of pulmonary Mycobacterium tuberculosis infection are lung granulomas. These organized structures are composed of host immune cells whose purpose is to contain or clear infection, creating a complex hub of immune and bacterial cell activity, as well as limiting pathology in the lungs. Yet, given cellular activity and the potential for frequent interactions between host immune cells and M. tuberculosis-infected cells, we observed a surprisingly low quantity of cytokine-producing T cells (<10% of granuloma T cells) in our recent study of M. tuberculosis infection within nonhuman primate (NHP) granulomas. Various mechanisms could limit T cell function, and one hypothesis is T cell exhaustion. T cell exhaustion is proposed to result from continual antigen stimulation, inducing them to enter a state characterized by low cytokine production, low proliferation, and expression of a series of inhibitory receptors, the most common being PD-1, LAG-3, and CTLA-4. In this work, we characterized the expression of inhibitory receptors on T cells and the functionality of these cells in tuberculosis (TB) lung granulomas. We then used these experimental data to calibrate and inform an agent-based computational model that captures environmental, cellular, and bacterial dynamics within granulomas in lungs during M. tuberculosis infection. Together, the results of the modeling and the experimental work suggest that T cell exhaustion alone is not responsible for the low quantity of M. tuberculosis-responsive T cells observed within TB granulomas and that the lack of exhaustion is likely an intrinsic property of granuloma structure.

Role of Interstitial Fluid Turnover on Target Suppression by Therapeutic Biologics Using a Minimal Physiologically Based Pharmacokinetic Model

For therapeutic biologics against soluble ligands, the magnitude and duration of target suppression affect their therapeutic efficacy. Many factors have been evaluated in relation to target suppression but the interstitial fluid turnover rate in target tissues has not been considered. Inspired by the fact that etanercept exerts limited efficacy in Crohn's disease despite its high efficacy in rheumatoid arthritis, we developed a minimal physiologically based pharmacokinetic model to investigate the role of the tissue fluid turnover rate on soluble target suppression and assessed the interrelationships between binding constants and tissue fluid turnover. Interstitial fluid turnover rates in target tissues were found to strongly influence target binding kinetics. For tissues with low fluid turnover, stable binders (low k_off) exhibit greater target suppression, but efficacy is often restricted by accumulation of the drug-target complex. For tissues with high fluid turnover, fast binders (high k_on) are generally favored, but a plateau effect is present for antibodies with low dissociation rates (k_off). Etanercept is often regarded as a fast tumor necrosis factor-α (TNF-α) binder (high k_on) despite comparable binding affinity (K_D, k_off/k_on) with adalimumab and infliximab. Crohn's disease largely involves the colon, a tissue with relatively slower fluid turnover than arthritis-associated joint synovium; this may explain why etanercept exerts poor TNF-α suppressive effect in Crohn's disease. This study highlights the importance of tissue interstitial fluid turnover in evaluation of therapeutic antibodies bound to soluble antigens.

The role of non-resolving inflammation in atherosclerosis

Non-resolving inflammation drives the development of clinically dangerous atherosclerotic lesions by promoting sustained plaque inflammation, large necrotic cores, thin fibrous caps, and thrombosis. Resolution of inflammation is not merely a passive return to homeostasis, but rather an active process mediated by specific molecules, including fatty acid-derived specialized pro-resolving mediators (SPMs). In advanced atherosclerosis, there is an imbalance between levels of SPMs and proinflammatory lipid mediators, which results in sustained leukocyte influx into lesions, inflammatory macrophage polarization, and impaired efferocytosis. In animal models of advanced atherosclerosis, restoration of SPMs limits plaque progression by suppressing inflammation, enhancing efferocytosis, and promoting an increase in collagen cap thickness. This Review discusses the roles of non-resolving inflammation in atherosclerosis and highlights the unique therapeutic potential of SPMs in blocking the progression of clinically dangerous plaques.

Biologic-Induced Infections in Inflammatory Bowel Disease: The TNF-α Antagonists

Objective: To review the mechanism and association of infectious risk among the tumor-necrosis factor α (TNF-α) antagonists used in inflammatory bowel disease. Data Sources: A PubMed literature search was performed using the following search terms: infliximab, adalimumab, certolizumab, golimumab, inflammatory bowel disease, crohn’s, ulcerative colitis, adverse effects, adverse events, safety, and infection. Study Selection and Data Extraction: Meta-analyses and cohort studies with outcomes pertaining to quantitative infectious risk were reviewed. Case reports and case series describing association between TNF-α inhibitors and infection were also reviewed. Data Synthesis: A total of 7 recent meta-analyses of randomized trials demonstrate inconclusive association of infection with TNF-α antagonists. Registry data suggest that medications carry an independent risk of opportunistic infections. Risk factors for infection include older age, malnutrition, diabetes, and possibly combination therapy. Reported infections vary widely but include intracellular and granulomatous bacteria, viruses, and fungi. Conclusion: TNF-α antagonists are associated with an increased risk of opportunistic infection, although this risk has not been demonstrated conclusively in randomized controlled trials. Knowledge of concomitant risk factors, mechanism of infectious risk, and available treatment options can improve patient care in the clinical setting.

Deletion of TGF-β1 Increases Bacterial Clearance by Cytotoxic T Cells in a Tuberculosis Granuloma Model

Mycobacterium tuberculosis is the pathogenic bacterium that causes tuberculosis (TB), one of the most lethal infectious diseases in the world. The only vaccine against TB is minimally protective, and multi-drug resistant TB necessitates new therapeutics to treat infection. Developing new therapies requires a better understanding of the complex host immune response to infection, including dissecting the processes leading to formation of granulomas, the dense cellular lesions associated with TB. In this work, we pair experimental and computational modeling studies to explore cytokine regulation in the context of TB. We use our next-generation hybrid multi-scale model of granuloma formation (GranSim) to capture molecular, cellular, and tissue scale dynamics of granuloma formation. We identify TGF-β1 as a major inhibitor of cytotoxic T-cell effector function in granulomas. Deletion of TGF-β1 from the system results in improved bacterial clearance and lesion sterilization. We also identify a novel dichotomous regulation of cytotoxic T cells and macrophages by TGF-β1 and IL-10, respectively. These findings suggest that increasing cytotoxic T-cell effector functions may increase bacterial clearance in granulomas and highlight potential new therapeutic targets for treating TB.

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.

Quantitative computational models of molecular self-assembly in systems biology

Molecular self-assembly is the dominant form of chemical reaction in living systems, yet efforts at systems biology modeling are only beginning to appreciate the need for and challenges to accurate quantitative modeling of self-assembly. Self-assembly reactions are essential to nearly every important process in cell and molecular biology and handling them is thus a necessary step in building comprehensive models of complex cellular systems. They present exceptional challenges, however, to standard methods for simulating complex systems. While the general systems biology world is just beginning to deal with these challenges, there is an extensive literature dealing with them for more specialized self-assembly modeling. This review will examine the challenges of self-assembly modeling, nascent efforts to deal with these challenges in the systems modeling community, and some of the solutions offered in prior work on self-assembly specifically. The review concludes with some consideration of the likely role of self-assembly in the future of complex biological system models more generally.

Facing the challenges of multiscale modelling of bacterial and fungal pathogen-host interactions

Recent and rapidly evolving progress on high-throughput measurement techniques and computational performance has led to the emergence of new disciplines, such as systems medicine and translational systems biology. At the core of these disciplines lies the desire to produce multiscale models: mathematical models that integrate multiple scales of biological organization, ranging from molecular, cellular and tissue models to organ, whole-organism and population scale models. Using such models, hypotheses can systematically be tested. In this review, we present state-of-the-art multiscale modelling of bacterial and fungal infections, considering both the pathogen and host as well as their interaction. Multiscale modelling of the interactions of bacteria, especially Mycobacterium tuberculosis, with the human host is quite advanced. In contrast, models for fungal infections are still in their infancy, in particular regarding infections with the most important human pathogenic fungi, Candida albicans and Aspergillus fumigatus. We reflect on the current availability of computational approaches for multiscale modelling of host-pathogen interactions and point out current challenges. Finally, we provide an outlook for future requirements of multiscale modelling.

Biologic Agents and Tuberculosis

Treatment with biologic agents, in particular tumor necrosis factor alpha (TNF-α) inhibitors, is associated with an increased risk of tuberculosis (TB), and screening and treatment for latent TB infection (LTBI) in patients undergoing such treatment is therefore indicated. The risk of TB associated with different biologics varies significantly, with the highest relative risks, 29.3 and 18.6, associated with adalimumab and infliximab, respectively. The risk of TB with newer TNF-α inhibitors and other biologics appears to be lower. Performance of LTBI screening tests is affected by immune-mediated inflammatory diseases and immunosuppressive therapy in patients due to commence TNF-α inhibitor treatment. Interferon gamma release assays (IGRAs) have a higher specificity than the tuberculin skin test (TST) in patients with Bacillus Calmette–Guérin (BCG) vaccination and have probably a better sensitivity than TST in immunosuppressed patients. LTBI screening programs prior to commencement of anti-TNF-α treatment significantly reduce the incidence of TB, but the optimal screening algorithm, in particular the question of whether a combination of IGRA and TST or a single test only should be used, is a matter of ongoing debate. Use of TST in combination with IGRA is justified to increase sensitivity. Repeat testing for LTBI should be limited to patients at increased risk of TB. If TB develops during anti-TNF-α treatment, it is more likely to be disseminated and extrapulmonary than are other TB cases. Discontinuation of anti-TNF-α treatment in patients diagnosed with TB is associated with an increased risk of immune reconstitution inflammatory syndrome, which is probably best managed by reintroduction of anti-TNF-α treatment.

A Multi-Compartment Hybrid Computational Model Predicts Key Roles for Dendritic Cells in Tuberculosis Infection

Tuberculosis (TB) is a world-wide health problem with approximately 2 billion people infected with Mycobacterium tuberculosis (Mtb, the causative bacterium of TB). The pathologic hallmark of Mtb infection in humans and Non-Human Primates (NHPs) is the formation of spherical structures, primarily in lungs, called granulomas. Infection occurs after inhalation of bacteria into lungs, where resident antigen-presenting cells (APCs), take up bacteria and initiate the immune response to Mtb infection. APCs traffic from the site of infection (lung) to lung-draining lymph nodes (LNs) where they prime T cells to recognize Mtb. These T cells, circulating back through blood, migrate back to lungs to perform their immune effector functions. We have previously developed a hybrid agent-based model (ABM, labeled GranSim) describing in silico immune cell, bacterial (Mtb) and molecular behaviors during tuberculosis infection and recently linked that model to operate across three physiological compartments: lung (infection site where granulomas form), lung draining lymph node (LN, site of generation of adaptive immunity) and blood (a measurable compartment). Granuloma formation and function is captured by a spatio-temporal model (i.e., ABM), while LN and blood compartments represent temporal dynamics of the whole body in response to infection and are captured with ordinary differential equations (ODEs). In order to have a more mechanistic representation of APC trafficking from the lung to the lymph node, and to better capture antigen presentation in a draining LN, this current study incorporates the role of dendritic cells (DCs) in a computational fashion into GranSim.

Cytokines and Chemokines in Mycobacterium tuberculosis Infection

Chemokines and cytokines are critical for initiating and coordinating the organized and sequential recruitment and activation of cells into Mycobacterium tuberculosis-infected lungs. Correct mononuclear cellular recruitment and localization are essential to ensure control of bacterial growth without the development of diffuse and damaging granulocytic inflammation. An important block to our understanding of TB pathogenesis lies in dissecting the critical aspects of the cytokine/chemokine interplay in light of the conditional role these molecules play throughout infection and disease development. Much of the data highlighted in this review appears at first glance to be contradictory, but it is the balance between the cytokines and chemokines that is critical, and the "goldilocks" (not too much and not too little) phenomenon is paramount in any discussion of the role of these molecules in TB. Determination of how the key chemokines/cytokines and their receptors are balanced and how the loss of that balance can promote disease is vital to understanding TB pathogenesis and to identifying novel therapies for effective eradication of this disease.

Computational immuno-biology for organ transplantation and regenerative medicine

Organ transplantation and regenerative medicine are adopted platforms that provide replacement tissues and organs from natural or engineered sources. Acceptance, tolerance and rejection depend greatly on the proper control of the immune response against graft antigens, motivating the development of immunological and genetical therapies that prevent organ failure. They rely on a complete, or partial, understanding of the immune system. Ultimately, they are innovative technologies that ensure permanent graft tolerance and indefinite graft survival through the modulation of the immune system. Computational immunology has arisen as a tool towards a mechanistic understanding of the biological and physicochemical processes surrounding an immune response. It comprehends theoretical and computational frameworks that simulate immuno-biological systems. The challenge is centered on the multi-scale character of the immune system that spans from atomistic scales, during peptide-epitope and protein interactions, to macroscopic scales, for lymph transport and organ-organ reactions. In this paper, we discuss, from an engineering perspective, the biological processes that are involved during the immune response of organ transplantation. Previous computational efforts, including their characteristics and visible limitations, are described. Finally, future perspectives and challenges are listed to motivate further developments.

Multiscale Model of Mycobacterium tuberculosis Infection Maps Metabolite and Gene Perturbations to Granuloma Sterilization Predictions

Granulomas are a hallmark of tuberculosis. Inside granulomas, the pathogen Mycobacterium tuberculosis may enter a metabolically inactive state that is less susceptible to antibiotics. Understanding M. tuberculosis metabolism within granulomas could contribute to reducing the lengthy treatment required for tuberculosis and provide additional targets for new drugs. Two key adaptations of M. tuberculosis are a nonreplicating phenotype and accumulation of lipid inclusions in response to hypoxic conditions. To explore how these adaptations influence granuloma-scale outcomes in vivo, we present a multiscale in silico model of granuloma formation in tuberculosis. The model comprises host immunity, M. tuberculosis metabolism, M. tuberculosis growth adaptation to hypoxia, and nutrient diffusion. We calibrated our model to in vivo data from nonhuman primates and rabbits and apply the model to predict M. tuberculosis population dynamics and heterogeneity within granulomas. We found that bacterial populations are highly dynamic throughout infection in response to changing oxygen levels and host immunity pressures. Our results indicate that a nonreplicating phenotype, but not lipid inclusion formation, is important for long-term M. tuberculosis survival in granulomas. We used virtual M. tuberculosis knockouts to predict the impact of both metabolic enzyme inhibitors and metabolic pathways exploited to overcome inhibition. Results indicate that knockouts whose growth rates are below ∼66% of the wild-type growth rate in a culture medium featuring lipid as the only carbon source are unable to sustain infections in granulomas. By mapping metabolite- and gene-scale perturbations to granuloma-scale outcomes and predicting mechanisms of sterilization, our method provides a powerful tool for hypothesis testing and guiding experimental searches for novel antituberculosis interventions.

Immunotherapy for tuberculosis: future prospects

Tuberculosis (TB) is still a major global health problem. A third of the world’s population is infected with Mycobacterium tuberculosis. Only ~10% of infected individuals develop TB but there are 9 million TB cases with 1.5 million deaths annually. The standard prophylactic treatment regimens for latent TB infection take 3–9 months, and new cases of TB require at least 6 months of treatment with multiple drugs. The management of latent TB infection and TB has become more challenging because of the spread of multidrug-resistant and extremely drug-resistant TB. Intensified efforts to find new TB drugs and immunotherapies are needed. Immunotherapies could modulate the immune system in patients with latent TB infection or active disease, enabling better control of M. tuberculosis replication. This review describes several types of potential immunotherapies with a focus on those which have been tested in humans.

Computational Identification of Mechanistic Factors That Determine the Timing and Intensity of the Inflammatory Response

Timely resolution of inflammation is critical for the restoration of homeostasis in injured or infected tissue. Chronic inflammation is often characterized by a persistent increase in the concentrations of inflammatory cells and molecular mediators, whose distinct amount and timing characteristics offer an opportunity to identify effective therapeutic regulatory targets. Here, we used our recently developed computational model of local inflammation to identify potential targets for molecular interventions and to investigate the effects of individual and combined inhibition of such targets. This was accomplished via the development and application of computational strategies involving the simulation and analysis of thousands of inflammatory scenarios. We found that modulation of macrophage influx and efflux is an effective potential strategy to regulate the amount of inflammatory cells and molecular mediators in both normal and chronic inflammatory scenarios. We identified three molecular mediators − tumor necrosis factor-α (TNF-α), transforming growth factor-β (TGF-β), and the chemokine CXCL8 − as potential molecular targets whose individual or combined inhibition may robustly regulate both the amount and timing properties of the kinetic trajectories for neutrophils and macrophages in chronic inflammation. Modulation of macrophage flux, as well as of the abundance of TNF-α, TGF-β, and CXCL8, may improve the resolution of chronic inflammation.

A recent approach to quantitatively characterize the timing and intensity of the inflammatory response relies on the use of four quantities termed inflammation indices. The values of the inflammation indices may reflect the differences between normal and pathological inflammation, and may be used to gauge the effects of therapeutic interventions aimed to control inflammation. Yet, the specific inflammatory mechanisms that can be targeted to selectively control these indices remain unknown. Here, we developed and applied a computational strategy to identify potential target mechanisms to regulate such indices. We used our recently developed model of local inflammation to simulate thousands of inflammatory scenarios. We then subjected the corresponding inflammation index values to sensitivity and correlation analysis. We found that the inflammation indices may be significantly influenced by the macrophage influx and efflux rates, as well as by the degradation rates of three specific molecular mediators. These results suggested that the indices can be effectively regulated by individual or combined inhibition of those molecular mediators, which we confirmed by computational experiments. Taken together, our results highlight possible targets of therapeutic intervention that can be used to control both the timing and the intensity of the inflammatory response.

In silico evaluation and exploration of antibiotic tuberculosis treatment regimens

Background

Improvement in tuberculosis treatment regimens requires selection of antibiotics and dosing schedules from a large design space of possibilities. Incomplete knowledge of antibiotic and host immune dynamics in tuberculosis granulomas impacts clinical trial design and success, and variations among clinical trials hamper side-by-side comparison of regimens. Our objective is to systematically evaluate the efficacy of isoniazid and rifampin regimens, and identify modifications to these antibiotics that improve treatment outcomes.

Results

We pair a spatio-temporal computational model of host immunity with pharmacokinetic and pharmacodynamic data on isoniazid and rifampin. The model is calibrated to plasma pharmacokinetic and granuloma bacterial load data from non-human primate models of tuberculosis and to tissue and granuloma measurements of isoniazid and rifampin in rabbit granulomas. We predict the efficacy of regimens containing different doses and frequencies of isoniazid and rifampin. We predict impacts of pharmacokinetic/pharmacodynamic modifications on antibiotic efficacy. We demonstrate that suboptimal antibiotic concentrations within granulomas lead to poor performance of intermittent regimens compared to daily regimens. Improvements from dose and frequency changes are limited by inherent antibiotic properties, and we propose that changes in intracellular accumulation ratios and antimicrobial activity would lead to the most significant improvements in treatment outcomes. Results suggest that an increased risk of drug resistance in fully intermittent as compared to daily regimens arises from higher bacterial population levels early during treatment.

Conclusions

Our systems pharmacology approach complements efforts to accelerate tuberculosis therapeutic development.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-015-0221-8) contains supplementary material, which is available to authorized users.

Latent tuberculosis infection detection and active tuberculosis prevention in patients receiving anti-TNF therapy: an Italian nationwide survey

AIMS

Primary: to investigate Italian rheumatology practice regarding latent tubercular infection (LTBI) detection and tuberculosis (TB) prevention in patients requiring anti-tumor necrosis factor (anti-TNF) therapy. Secondary: to assess the overall number of TB cases over 10 years and their distribution by drug.

METHODS

An anonymous, 24 multiple-response questionnaire was completed by 393/449 (87.5%) rheumatologists prescribing anti-TNF therapy. Six questions provided setting information, and 18 the compliance with recommendations and the recorded TB cases.

RESULTS

The Italian recommendations were used by 323 (82%) and other sets by 60 (15%). TB specialists were always consulted by 81 (21%) and occasionally by 73 (19%). LTBI screening was made using chest radiograph (CR) by 5%, tuburculin skin test (TST) by 5.3%, CR + TST by 35.6%, interferon-gamma release assay (IGRA) by 7.4%, CR + IGRAs by 26% and CR + TST + IGRA by 20.6%. Isoniazid was initiated in the presence of positivity of TST by 97 (24.7%), TST + IGRA by 101 (25.7%) and IGRA by 195 (49.6%). Anti-TNF starting delay was 1 month in 63.1% of the cases, 3 months in 27.7%, concomitantly in 5.6%. Overall, 317 TB reactivation cases occurred in 39 353 patients, with an incidence rate of 80.5 cases/100 000/year (10 times higher than in the Italian general population). TB occurred during TB prophylaxis in 192 (60.6%). TB cases incidence rate divided by drug was: etanercept (ETN) 51 (16%), 28/100 000/year, adalimumab (ADA) 98 (31%), 89/100 000/year, infliximab (IFX) 137 (43.2%), 211/100 000/year, with a significantly lower frequency in the ETN group compared to ADA and IFX groups (χ(2)  = P < 0.001).

CONCLUSION

Italian rheumatologists are highly aware of anti-TNF-related TB risk with variable LTBI screening and TB prevention strategies. TB outcome was significantly lower in the ETN group.

Control of Mycobacterial Infections in Mice Expressing Human Tumor Necrosis Factor (TNF) but Not Mouse TNF

Tumor necrosis factor (TNF) is an important cytokine for host defense against pathogens but is also associated with the development of human immunopathologies. TNF blockade effectively ameliorates many chronic inflammatory conditions but compromises host immunity to tuberculosis. The search for novel, more specific human TNF blockers requires the development of a reliable animal model. We used a novel mouse model with complete replacement of the mouse TNF gene by its human ortholog (human TNF [huTNF] knock-in [KI] mice) to determine resistance to Mycobacterium bovis BCG and M. tuberculosis infections and to investigate whether TNF inhibitors in clinical use reduce host immunity. Our results show that macrophages from huTNF KI mice responded to BCG and lipopolysaccharide similarly to wild-type macrophages by NF-κB activation and cytokine production. While TNF-deficient mice rapidly succumbed to mycobacterial infection, huTNF KI mice survived, controlling the bacterial burden and activating bactericidal mechanisms. Administration of TNF-neutralizing biologics disrupted the control of mycobacterial infection in huTNF KI mice, leading to an increased bacterial burden and hyperinflammation. Thus, our findings demonstrate that human TNF can functionally replace murine TNF in vivo, providing mycobacterial resistance that could be compromised by TNF neutralization. This new animal model will be helpful for the testing of specific biologics neutralizing human TNF.

Exploring the potential of adjunct therapy in tuberculosis

A critical unmet need for treatment of drug-resistant tuberculosis (TB) is to find novel therapies that are efficacious, safe, and shorten the duration of treatment. Drug discovery approaches for TB primarily target essential genes of the pathogen Mycobacterium tuberculosis (Mtb) but novel strategies such as host-directed therapies and nonmicrobicidal targets are necessary to bring about a paradigm shift in treatment. Drugs targeting the host pathways and nonmicrobicidal proteins can be used only in conjunction with existing drugs as adjunct therapies. Significantly, host-directed adjunct therapies have the potential to decrease duration of treatment, as they are less prone to drug resistance, target the immune responses, and act via novel mechanism of action. Recent advances in targeting host-pathogen interactions have implicated pathways such as eicosanoid regulation and angiogenesis. Furthermore, several approved drugs such as metformin and verapamil have been identified that appear suitable for repurposing for the treatment of TB. These findings and the challenges in the area of host- and/or pathogen-directed adjunct therapies and their implications for TB therapy are discussed.

A population model capturing dynamics of tuberculosis granulomas predicts host infection outcomes

Granulomas play a centric role in tuberculosis (TB) infection progression. Multiple granulomas usually develop within a single host. These granulomas are not synchronized in size or bacteria load, and will follow different trajectories over time. How the fate of individual granulomas influence overall infection outcome at host scale is not understood, although computational models have been developed to predict single granuloma behavior. Here we present a within-host population model that tracks granulomas in two key organs during Mycobacteria tuberculosis (Mtb) infection: lung and lymph nodes (LN). We capture various time courses of TB progression, including latency and reactivation. The model predicts that there is no steady state; rather it is a continuous process of progressing to active disease over differing time periods. This is consistent with recently posed ideas suggesting that latent TB exists as a spectrum of states and not a single state. The model also predicts a dual role for granuloma development in LNs during Mtb infection: in early phases of infection granulomas suppress infection by providing additional antigens to the site of immune priming; however, this induces a more rapid reactivation at later stages by disrupting immune responses. We identify mechanisms that strongly correlate with better host-level outcomes, including elimination of uncontained lung granulomas by inducing low levels of lung tissue damage and inhibition of bacteria dissemination within the lung.

A multi-scale approach to designing therapeutics for tuberculosis

Approximately one third of the world's population is infected with Mycobacterium tuberculosis. Limited information about how the immune system fights M. tuberculosis and what constitutes protection from the bacteria impact our ability to develop effective therapies for tuberculosis. We present an in vivo systems biology approach that integrates data from multiple model systems and over multiple length and time scales into a comprehensive multi-scale and multi-compartment view of the in vivo immune response to M. tuberculosis. We describe computational models that can be used to study (a) immunomodulation with the cytokines tumor necrosis factor and interleukin 10, (b) oral and inhaled antibiotics, and

Systems Pharmacology Approach Toward the Design of Inhaled Formulations of Rifampicin and Isoniazid for Treatment of Tuberculosis

Conventional oral therapies for the treatment of tuberculosis are limited by poor antibiotic distribution in granulomas, which contributes to lengthy treatment regimens and inadequate bacterial sterilization. Inhaled formulations are a promising strategy to increase antibiotic efficacy and reduce dose frequency. We develop a multiscale computational approach that accounts for simultaneous dynamics of a lung granuloma, carrier release kinetics, pharmacokinetics, and pharmacodynamics. Using this computational platform, we predict that a rationally designed inhaled formulation of isoniazid given at a significantly reduced dose frequency has better sterilizing capabilities and reduced toxicity than the current oral regimen. Furthermore, we predict that inhaled formulations of rifampicin require unrealistic carrier antibiotic loadings that lead to early toxicity concerns. Lastly, we predict that targeting carriers to macrophages has limited effects on treatment efficacy. Our platform can be extended to account for additional antibiotics and provides a new tool for rapidly prototyping the efficacy of inhaled formulations.

Strategies for efficient numerical implementation of hybrid multi-scale agent-based models to describe biological systems

Biologically related processes operate across multiple spatiotemporal scales. For computational modeling methodologies to mimic this biological complexity, individual scale models must be linked in ways that allow for dynamic exchange of information across scales. A powerful methodology is to combine a discrete modeling approach, agent-based models (ABMs), with continuum models to form hybrid models. Hybrid multi-scale ABMs have been used to simulate emergent responses of biological systems. Here, we review two aspects of hybrid multi-scale ABMs: linking individual scale models and efficiently solving the resulting model. We discuss the computational choices associated with aspects of linking individual scale models while simultaneously maintaining model tractability. We demonstrate implementations of existing numerical methods in the context of hybrid multi-scale ABMs. Using an example model describing Mycobacterium tuberculosis infection, we show relative computational speeds of various combinations of numerical methods. Efficient linking and solution of hybrid multi-scale ABMs is key to model portability, modularity, and their use in understanding biological phenomena at a systems level.

Pharmaceutical aspects of anti-inflammatory TNF-blocking drugs

Tumor necrosis factor (TNF) is a key regulator of inflammatory processes in several immune-mediated inflammatory diseases such as rheumatoid arthritis, ankylosing spondylitis, Crohn's disease, ulcerative colitis, psoriasis and psoriatic arthritis. Inactivating TNF has been found to be a plausible approach in treating these conditions. Two major strategies have been adopted by scientists to inactivate TNF: one is to use monoclonal antibodies (mAbs) that bind to TNF, and the other is to use fusion proteins that bind to TNF, both inactivate TNF and help to prevent TNF-mediated inflammatory processes. Monoclonal antibodies (mAbs) are biological products that selectively bind to specific antigen molecules, and fusion proteins are soluble receptors that bind to TNF. These types of drugs are generally known as biologics and there has been an explosion in the development and testing of biologics since the 1994 US approval and launch of abciximab, a mAb that binds to GPIIb/IIIa on platelets. Anti-TNF drugs that are currently approved by FDA for treating inflammatory conditions include adalimumab, certolizumab pegol, golimumab, infliximab and etanercept. Since these agents are complex protein molecules, the pharmacodynamics and pharmacokinetics of these drugs are different from small-molecule anti-inflammatory agents. This review focuses on the pharmaceutical aspects of these drugs such as mechanism of action, adverse effects, pharmacokinetics and drug interactions. An effort was also taken to compare the pharmacodynamics and pharmacokinetic properties of these drugs, with the available data at this time.

Inhibition of 4-1BBL-regulated TLR response in macrophages ameliorates endotoxin-induced sepsis in mice

Activation of Toll-like receptor (TLR) signaling rapidly induces the expression of inflammatory genes, which is persistent for a defined period of time. However, uncontrolled and excessive inflammation may lead to the development of diseases. 4-1BB ligand (4-1BBL) plays an essential role in sustaining the expression of inflammatory cytokines by interacting with TLRs during macrophage activation. Here, we show that inhibition of 4-1BBL signaling reduced the inflammatory responses in macrophages and ameliorated endotoxin-induced sepsis in mice. A 4-1BB-Fc fusion protein significantly reduced TNF production in macrophages by blocking the oligomerization of TLR4 and 4-1BBL. Administration of 4-1BB-Fc suppressed LPS-induced sepsis by reducing TNF production, and the coadministration of anti-TNF and 4-1BB-Fc provided better protection against LPS-induced sepsis. Taken together, these observations suggest that inhibition of the TLR/4-1BBL complex formation may be highly efficient in protecting against continued inflammation, and that 4-1BB-Fc could be a potential therapeutic target for the treatment of inflammatory diseases.

Computer simulations of the mouse spermatogenic cycle

The spermatogenic cycle describes the periodic development of germ cells in the testicular tissue. The temporal-spatial dynamics of the cycle highlight the unique, complex, and interdependent interaction between germ and somatic cells, and are the key to continual sperm production. Although understanding the spermatogenic cycle has important clinical relevance for male fertility and contraception, there are a number of experimental obstacles. For example, the lengthy process cannot be visualized through dynamic imaging, and the precise action of germ cells that leads to the emergence of testicular morphology remains uncharacterized. Here, we report an agent-based model that simulates the mouse spermatogenic cycle on a cross-section of the seminiferous tubule over a time scale of hours to years, while considering feedback regulation, mitotic and meiotic division, differentiation, apoptosis, and movement. The computer model is able to elaborate the germ cell dynamics in a time-lapse movie format, allowing us to trace individual cells as they change state and location. More importantly, the model provides mechanistic understanding of the fundamentals of male fertility, namely how testicular morphology and sperm production are achieved. By manipulating cellular behaviors either individually or collectively in silico, the model predicts causal events for the altered arrangement of germ cells upon genetic or environmental perturbations. This in silico platform can serve as an interactive tool to perform long-term simulation and to identify optimal approaches for infertility treatment and contraceptive development.

A computational tool integrating host immunity with antibiotic dynamics to study tuberculosis treatment

While active tuberculosis (TB) is a treatable disease, many complex factors prevent its global elimination. Part of the difficulty in developing optimal therapies is the large design space of antibiotic doses, regimens and combinations. Computational models that capture the spatial and temporal dynamics of antibiotics at the site of infection can aid in reducing the design space of costly and time-consuming animal pre-clinical and human clinical trials. The site of infection in TB is the granuloma, a collection of immune cells and bacteria that form in the lung, and new data suggest that penetration of drugs throughout granulomas is problematic. Here we integrate our computational model of granuloma formation and function with models for plasma pharmacokinetics, lung tissue pharmacokinetics and pharmacodynamics for two first line anti-TB antibiotics. The integrated model is calibrated to animal data. We make four predictions. First, antibiotics are frequently below effective concentrations inside granulomas, leading to bacterial growth between doses and contributing to the long treatment periods required for TB. Second, antibiotic concentration gradients form within granulomas, with lower concentrations toward their centers. Third, during antibiotic treatment, bacterial subpopulations are similar for INH and RIF treatment: mostly intracellular with extracellular bacteria located in areas non-permissive for replication (hypoxic areas), presenting a slowly increasing target population over time. Finally, we find that on an individual granuloma basis, pre-treatment infection severity (including bacterial burden, host cell activation and host cell death) is predictive of treatment outcome.