Oxygen Modulates the Effectiveness of Granuloma Mediated Host Response to Mycobacterium tuberculosis: A Multiscale Computational Biology Approach

Sepsis-Induced Endothelial Dysfunction: Permeability and Regulated Cell Death

Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection. Endothelial cells (ECs) are an important cell type typically affected in sepsis, resulting in compromised barrier function and various forms of regulated cell death (RCD). However, the precise mechanisms underlying sepsis-induced EC damage remain unclear. This review summarizes the recent research progress on factors and mechanisms that may affect the permeability and RCD of ECs under septic conditions, including glycocalyx, damage-associated molecular patterns, and various forms of RCD in ECs, such as apoptosis, pyroptosis, ferroptosis, and autophagy. This review offers important insights into the underlying mechanisms of endothelial dysfunction in sepsis, aiming to contribute to developing small-molecule targeted clinical therapies.

Coupling In silico and In vitro Mechanistic Models to Define Vitamin D3 Immunomodulation of IL-12 and Nitric Oxide in Mycobacterium tuberculosis Infection

Tuberculosis, caused by Mycobacterium tuberculosis (Mtb), is a highly infectious disease mainly affecting the lungs. Macrophages are key phagocytic immune cells and the preferred hosts for intracellular bacteria growth. Macrophages are also important sites of vitamin D3 synthesis, with vitamin D3 deficiency associated with increased risk of developing active TB. There is great interest in vitamin D3 as adjunctive therapy due to its immunomodulatory and antimicrobial properties, particularly the effect on proinflammatory effectors like bactericidal nitric oxide (NO). NO production requires inducible nitric oxide synthase expression, which is regulated by IFN-γ, a pro-inflammatory cytokine upregulated by IL-12. Vitamin D3 serves an important host protective function to regulate NO production to a level that is sufficient to restrict Mtb growth while avoiding uncontrolled inflammation. While previous in vitro studies have shown that vitamin D3 modulates NO levels and IL-12, in an infection dose-dependent manner, to date, there are no computational models that capture the mechanisms by which vitamin D3 regulates NO production during high and low Mtb infection. Using an integrative systems biology approach, we define key signaling pathways involved in vitamin D3 immunometabolism and determine the impact of vitamin D3 sufficiency/deficiency given infection dosage. Data from multiple computational models and in vitro infection studies are integrated into a mechanistic model, and simulation results compared to in vitro IL-12 and NO concentrations from our in vitro models of infection. Concurrence between our in-silico and in vitro models demonstrates the feasibility of NO modulation in a vitamin D3 and infection level dependent manner.

In silico agent-based modeling approach to characterize multiple in vitro tuberculosis infection models

In vitro models of Mycobacterium tuberculosis (Mtb) infection are a valuable tool for examining host-pathogen interactions and screening drugs. With the development of more complex in vitro models, there is a need for tools to help analyze and integrate data from these models. To this end, we introduce an agent-based model (ABM) representation of the interactions between immune cells and bacteria in an in vitro setting. This in silico model was used to simulate both traditional and spheroid cell culture models by changing the movement rules and initial spatial layout of the cells in accordance with the respective in vitro models. The traditional and spheroid simulations were calibrated to published experimental data in a paired manner, by using the same parameters in both simulations. Within the calibrated simulations, heterogeneous outputs are seen for bacterial count and T cell infiltration into the macrophage core of the spheroid. The simulations also predict that equivalent numbers of activated macrophages do not necessarily result in similar bacterial reductions; that host immune responses can control bacterial growth in both spheroid structure dependent and independent manners; that STAT1 activation is the limiting step in macrophage activation in spheroids; and that drug screening and macrophage activation studies could have different outcomes depending on the in vitro culture used. Future model iterations will be guided by the limitations of the current model, specifically which parts of the output space were harder to reach. This ABM can be used to represent more in vitro Mtb infection models due to its flexible structure, thereby accelerating in vitro discoveries.

Mathematical model of oxygen, nutrient, and drug transport in tuberculosis granulomas

Physiological abnormalities in pulmonary granulomas-pathological hallmarks of tuberculosis (TB)-compromise the transport of oxygen, nutrients, and drugs. In prior studies, we demonstrated mathematically and experimentally that hypoxia and necrosis emerge in the granuloma microenvironment (GME) as a direct result of limited oxygen availability. Building on our initial model of avascular oxygen diffusion, here we explore additional aspects of oxygen transport, including the roles of granuloma vasculature, transcapillary transport, plasma dilution, and interstitial convection, followed by cellular metabolism. Approximate analytical solutions are provided for oxygen and glucose concentration, interstitial fluid velocity, interstitial fluid pressure, and the thickness of the convective zone. These predictions are in agreement with prior experimental results from rabbit TB granulomas and from rat carcinoma models, which share similar transport limitations. Additional drug delivery predictions for anti-TB-agents (rifampicin and clofazimine) strikingly match recent spatially-resolved experimental results from a mouse model of TB. Finally, an approach to improve molecular transport in granulomas by modulating interstitial hydraulic conductivity is tested in silico.

Concomitant immunity to M. tuberculosis infection

Some persistent infections provide a level of immunity that protects against reinfection with the same pathogen, a process referred to as concomitant immunity. To explore the phenomenon of concomitant immunity during Mycobacterium tuberculosis infection, we utilized HostSim, a previously published virtual host model of the immune response following Mtb infection. By simulating reinfection scenarios and comparing with data from non-human primate studies, we propose a hypothesis that the durability of a concomitant immune response against Mtb is intrinsically tied to levels of tissue resident memory T cells (Trms) during primary infection, with a secondary but important role for circulating Mtb-specific T cells. Further, we compare HostSim reinfection experiments to observational TB studies from the pre-antibiotic era to predict that the upper bound of the lifespan of resident memory T cells in human lung tissue is likely 2-3 years. To the authors' knowledge, this is the first estimate of resident memory T-cell lifespan in humans. Our findings are a first step towards demonstrating the important role of Trms in preventing disease and suggest that the induction of lung Trms is likely critical for vaccine success.

Engineering multicellular living systems-a Keystone Symposia report

The ability to engineer complex multicellular systems has enormous potential to inform our understanding of biological processes and disease and alter the drug development process. Engineering living systems to emulate natural processes or to incorporate new functions relies on a detailed understanding of the biochemical, mechanical, and other cues between cells and between cells and their environment that result in the coordinated action of multicellular systems. On April 3-6, 2022, experts in the field met at the Keystone symposium "Engineering Multicellular Living Systems" to discuss recent advances in understanding how cells cooperate within a multicellular system, as well as recent efforts to engineer systems like organ-on-a-chip models, biological robots, and organoids. Given the similarities and common themes, this meeting was held in conjunction with the symposium "Organoids as Tools for Fundamental Discovery and Translation".

Phenotypic adaptation of Mycobacterium tuberculosis to host-associated stressors that induce persister formation

Mycobacterium tuberculosis exhibits a remarkable ability to interfere with the host antimicrobial response. The pathogen exploits elaborate strategies to cope with diverse host-induced stressors by modulating its metabolism and physiological state to prolong survival and promote persistence in host tissues. Elucidating the adaptive strategies that M. tuberculosis employs during infection to enhance persistence is crucial to understanding how varying physiological states may differentially drive disease progression for effective management of these populations. To improve our understanding of the phenotypic adaptation of M. tuberculosis, we review the adaptive strategies employed by M. tuberculosis to sense and coordinate a physiological response following exposure to various host-associated stressors. We further highlight the use of animal models that can be exploited to replicate and investigate different aspects of the human response to infection, to elucidate the impact of the host environment and bacterial adaptive strategies contributing to the recalcitrance of infection.

Coxiella burnetii Affects HIF1α Accumulation and HIF1α Target Gene Expression

HIF1α is an important transcription factor regulating not only cellular responses to hypoxia, but also anti-infective defense responses. We recently showed that HIF1α hampers replication of the obligate intracellular pathogen Coxiella burnetii which causes the zoonotic disease Q fever. Prior to development of chronic Q fever, it is assumed that the bacteria enter a persistent state. As HIF1α and/or hypoxia might be involved in the induction of C. burnetii persistence, we analyzed the role of HIF1α and hypoxia in the interaction of macrophages with C. burnetii to understand how the bacteria manipulate HIF1α stability and activity. We demonstrate that a C. burnetii-infection initially induces HIF1α stabilization, which decreases then over the course of an infection. This reduction depends on bacterial viability and a functional type IV secretion system (T4SS). While neither the responsible T4SS effector protein(s) nor the molecular mechanism leading to this partial HIF1α destabilization have been identified, our results demonstrate that C. burnetii influences the expression of HIF1α target genes in multiple ways. Therefore, a C. burnetii infection promotes HIF1α-mediated upregulation of several metabolic target genes; affects apoptosis-regulators towards a more pro-apoptotic signature; and under hypoxic conditions, shifts the ratio of the inflammatory genes analyzed towards a pro-inflammatory profile. Taken together, C. burnetii modulates HIF1α in a still elusive manner and alters the expression of multiple HIF1α target genes.

Targeting endogenous gaseous signaling molecules as novel host-directed therapies against tuberculosis infection

Tuberculosis (TB) is a chronic pulmonary disease caused by Mycobacterium tuberculosis which is a major cause of morbidity and mortality worldwide. Due to the complexity of disease and its continuous global spread, there is an urgent need to improvise the strategies for prevention, diagnosis, and treatment. The current anti-TB regimen lasts for months and warrants strict compliance to clear infection and to minimize the risk of development of multi drug-resistant tuberculosis. This underscores the need to have new and improved therapeutics for TB treatment. Several studies have highlighted the unique ability of Mycobacterium tuberculosis to exploit host factors to support its survival inside the intracellular environment. One of the key players to mycobacterial disease susceptibility and infection are endogenous gases such as oxygen, nitric oxide, carbon monoxide and hydrogen sulfide. Nitric oxide and carbon monoxide as the physiological gaseous messengers are considered important to the outcome of Mycobacterium tuberculosis infection. The role of hydrogen sulfide in human tuberculosis is yet not fully elucidated, but this gas has been shown to play a significant role in bacterial respiration, growth and pathogenesis. This review will focus on the host factors majorly endogenous gaseous signaling molecules which contributes to Mycobacterium tuberculosis survival inside the intracellular environment and highlight the potential therapeutic targets.

Survival of hypoxia-induced dormancy is not a common feature of all strains of the Mycobacterium tuberculosis complex

While persistence in a dormant state is crucial for the life cycle of Mycobacterium tuberculosis, no investigation regarding dormancy survival of different strains across different lineages was performed so far. We analyzed responses to oxygen starvation and recovery in terms of growth, metabolism, and transcription. All different strains belonging to the Euro-American lineage (L4) showed similar survival and resuscitation characteristics. Different clinical isolates from the Beijing (L2), East African-Indian (L3), and Delhi/Central Asian (L1) lineage did not survive oxygen starvation. We show that dormancy survival is lineage-dependent. Recovery from O₂ starvation was only observed in strains belonging to the Euro-American (L4) lineage but not in strains belonging to different lineages (L1, L2, L3). Thus, resuscitation from dormancy after oxygen starvation is not a general feature of all M. tuberculosis strains as thought before. Our findings are of key importance to understand infection dynamics of non-Euro-American vs Euro-American strains and to develop drugs targeting the dormant state.

Development of New Tuberculosis Drugs: Translation to Regimen Composition for Drug-Sensitive and Multidrug-Resistant Tuberculosis

Tuberculosis (TB) kills more people than any other infectious disease. Challenges for developing better treatments include the complex pathology due to within-host immune dynamics, interpatient variability in disease severity and drug pharmacokinetics-pharmacodynamics (PK-PD), and the growing emergence of resistance. Model-informed drug development using quantitative and translational pharmacology has become increasingly recognized as a method capable of drug prioritization and regimen optimization to efficiently progress compounds through TB drug development phases. In this review, we examine translational models and tools, including plasma PK scaling, site-of-disease lesion PK, host-immune and bacteria interplay, combination PK-PD models of multidrug regimens, resistance formation, and integration of data across nonclinical and clinical phases.We propose a workflow that integrates these tools with computational platforms to identify drug combinations that have the potential to accelerate sterilization, reduce relapse rates, and limit the emergence of resistance.

Modelling the effects of environmental heterogeneity within the lung on the tuberculosis life-cycle

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In silico model of TB in the lung incorporating environmental heterogeneity.

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Preferential conditions at the apex of lung localise post-primary disease there.

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Analysis of the key influences driving disease at different regions of the lung.

Progress in shortening the duration of tuberculosis (TB) treatment is hampered by the lack of a predictive model that accurately reflects the diverse environment within the lung. This is important as TB has been shown to produce distinct localisations to different areas of the lung during different disease stages, with the environmental heterogeneity within the lung of factors such as air ventilation, blood perfusion and oxygen tension believed to contribute to the apical localisation witnessed during the post-primary form of the disease.

Building upon our previous model of environmental lung heterogeneity, we present a networked metapopulation model that simulates TB across the whole lung, incorporating these notions of environmental heterogeneity across the whole TB life-cycle to show how different stages of the disease are influenced by different environmental and immunological factors. The alveolar tissue in the lung is divided into distinct patches, with each patch representing a portion of the total tissue and containing environmental attributes that reflect the internal conditions at that location. We include populations of bacteria and immune cells in various states, and events are included which determine how the members of the model interact with each other and the environment. By allowing some of these events to be dependent on environmental attributes, we create a set of heterogeneous dynamics, whereby the location of the tissue within the lung determines the disease pathological events that occur there.

Our results show that the environmental heterogeneity within the lung is a plausible driving force behind the apical localisation during post-primary disease. After initial infection, bacterial levels will grow in the initial infection location at the base of the lung until an adaptive immune response is initiated. During this period, bacteria are able to disseminate and create new lesions throughout the lung. During the latent stage, the lesions that are situated towards the apex are the largest in size, and once a post-primary immune-suppressing event occurs, it is the uppermost lesions that reach the highest levels of bacterial proliferation. Our sensitivity analysis also shows that it is the differential in blood perfusion, causing reduced immune activity towards the apex, which has the biggest influence of disease outputs.

Mechanisms controlling bacterial infection in myeloid cells under hypoxic conditions

Various factors of the tissue microenvironment such as the oxygen concentration influence the host-pathogen interaction. During the past decade, hypoxia-driven signaling via hypoxia-inducible factors (HIF) has emerged as an important factor that affects both the pathogen and the host. In this chapter, we will review the current knowledge of this complex interplay, with a particular emphasis given to the impact of hypoxia and HIF on the inflammatory and antimicrobial activity of myeloid cells, the bacterial responses to hypoxia and the containment of bacterial infections under oxygen-limited conditions. We will also summarize how low oxygen concentrations influence the metabolism of neutrophils, macrophages and dendritic cells. Finally, we will discuss the consequences of hypoxia and HIFα activation for the invading pathogen, with a focus on Pseudomonas aeruginosa, Mycobacterium tuberculosis, Coxiella burnetii, Salmonella enterica and Staphylococcus aureus. This includes a description of the mechanisms and microbial factors, which the pathogens use to sense and react to hypoxic conditions.

A computational model tracks whole-lung Mycobacterium tuberculosis infection and predicts factors that inhibit dissemination

Mycobacterium tuberculosis (Mtb), the causative infectious agent of tuberculosis (TB), kills more individuals per year than any other infectious agent. Granulomas, the hallmark of Mtb infection, are complex structures that form in lungs, composed of immune cells surrounding bacteria, infected cells, and a caseous necrotic core. While granulomas serve to physically contain and immunologically restrain bacteria growth, some granulomas are unable to control Mtb growth, leading to bacteria and infected cells leaving the granuloma and disseminating, either resulting in additional granuloma formation (local or non-local) or spread to airways or lymph nodes. Dissemination is associated with development of active TB. It is challenging to experimentally address specific mechanisms driving dissemination from TB lung granulomas. Herein, we develop a novel hybrid multi-scale computational model, MultiGran, that tracks Mtb infection within multiple granulomas in an entire lung. MultiGran follows cells, cytokines, and bacterial populations within each lung granuloma throughout the course of infection and is calibrated to multiple non-human primate (NHP) cellular, granuloma, and whole-lung datasets. We show that MultiGran can recapitulate patterns of in vivo local and non-local dissemination, predict likelihood of dissemination, and predict a crucial role for multifunctional CD8+ T cells and macrophage dynamics for preventing dissemination.

Tuberculosis (TB) is caused by infection with Mycobacterium tuberculosis (Mtb) and kills 3 people per minute worldwide. Granulomas, spherical structures composed of immune cells surrounding bacteria, are the hallmark of Mtb infection and sometimes fail to contain the bacteria and disseminate, leading to further granuloma growth within the lung environment. To date, the mechanisms that determine granuloma dissemination events have not been characterized. We present a computational multi-scale model of granuloma formation and dissemination within primate lungs. Our computational model is calibrated to multiple experimental datasets across the cellular, granuloma, and whole-lung scales of non-human primates. We match to both individual granuloma and granuloma-population datasets, predict likelihood of dissemination events, and predict a critical role for multifunctional CD8+ T cells and macrophage-bacteria interactions to prevent infection dissemination.

Modelling the dynamics of tuberculosis lesions in a virtual lung: Role of the bronchial tree in endogenous reinfection

Tuberculosis (TB) is an infectious disease that still causes more than 1.5 million deaths annually. The World Health Organization estimates that around 30% of the world's population is latently infected. However, the mechanisms responsible for 10% of this reserve (i.e., of the latently infected population) developing an active disease are not fully understood, yet. The dynamic hypothesis suggests that endogenous reinfection has an important role in maintaining latent infection. In order to examine this hypothesis for falsifiability, an agent-based model of growth, merging, and proliferation of TB lesions was implemented in a computational bronchial tree, built with an iterative algorithm for the generation of bronchial bifurcations and tubes applied inside a virtual 3D pulmonary surface. The computational model was fed and parameterized with computed tomography (CT) experimental data from 5 latently infected minipigs. First, we used CT images to reconstruct the virtual pulmonary surfaces where bronchial trees are built. Then, CT data about TB lesion' size and location to each minipig were used in the parameterization process. The model's outcome provides spatial and size distributions of TB lesions that successfully reproduced experimental data, thus reinforcing the role of the bronchial tree as the spatial structure triggering endogenous reinfection. A sensitivity analysis of the model shows that the final number of lesions is strongly related with the endogenous reinfection frequency and maximum growth rate of the lesions, while their mean diameter mainly depends on the spatial spreading of new lesions and the maximum radius. Finally, the model was used as an in silico experimental platform to explore the transition from latent infection to active disease, identifying two main triggering factors: a high inflammatory response and the combination of a moderate inflammatory response with a small breathing amplitude.

In Vitro Granuloma Models of Tuberculosis: Potential and Challenges

Despite intensive research efforts, several fundamental disease processes for tuberculosis (TB) remain poorly understood. A central enigma is that host immunity is necessary to control disease yet promotes transmission by causing lung immunopathology. Our inability to distinguish these processes makes it challenging to design rational novel interventions. Elucidating basic immune mechanisms likely requires both in vivo and in vitro analyses, since Mycobacterium tuberculosis is a highly specialized human pathogen. The classic immune response is the TB granuloma organized in three dimensions within extracellular matrix. Several groups are developing cell culture granuloma models. In January 2018, NIAID convened a workshop, entitled "3-D Human in vitro TB Granuloma Model" to advance the field. Here, we summarize the arguments for developing advanced TB cell culture models and critically review those currently available. We discuss how integrating complementary approaches, specifically organoids and mathematical modeling, can maximize progress, and conclude by discussing future challenges and opportunities.

Cryptococcus neoformans resists to drastic conditions by switching to viable but non-culturable cell phenotype

Metabolically quiescent pathogens can persist in a viable non-replicating state for months or even years. For certain infectious diseases, such as tuberculosis, cryptococcosis, histoplasmosis, latent infection is a corollary of this dormant state, which has the risk for reactivation and clinical disease. During murine cryptococcosis and macrophage uptake, stress and host immunity induce Cryptococcus neoformans heterogeneity with the generation of a sub-population of yeasts that manifests a phenotype compatible with dormancy (low stress response, latency of growth). In this subpopulation, mitochondrial transcriptional activity is regulated and this phenotype has been considered as a hallmark of quiescence in stem cells. Based on these findings, we worked to reproduce this phenotype in vitro and then standardize the experimental conditions to consistently generate this dormancy in C. neoformans. We found that incubation of stationary phase yeasts (STAT) in nutriment limited conditions and hypoxia for 8 days (8D-HYPOx) was able to produced cells that mimic the phenotype obtained in vivo. In these conditions, mortality and/or apoptosis occurred in less than 5% of the yeasts compared to 30-40% of apoptotic or dead yeasts upon incubation in normoxia (8D-NORMOx). Yeasts in 8D-HYPOx harbored a lower stress response, delayed growth and less that 1% of culturability on agar plates, suggesting that these yeasts are viable but non culturable cells (VBNC). These VBNC were able to reactivate in the presence of pantothenic acid, a vitamin that is known to be involved in quorum sensing and a precursor of acetyl-CoA. Global metabolism of 8D-HYPOx cells showed some specific requirements and was globally shut down compared to 8D-NORMOx and STAT conditions. Mitochondrial analyses showed that the mitochondrial mass increased with mitochondria mostly depolarized in 8D-HYPOx compared to 8D-NORMox, with increased expression of mitochondrial genes. Proteomic and transcriptomic analyses of 8D-HYPOx revealed that the number of secreted proteins and transcripts detected also decreased compared to 8D-NORMOx and STAT, and the proteome, secretome and transcriptome harbored specific profiles that are engaged as soon as four days of incubation. Importantly, acetyl-CoA and the fatty acid pathway involving mitochondria are required for the generation and viability maintenance of VBNC. Altogether, these data show that we were able to generate for the first time VBNC phenotype in C. neoformans. This VBNC state is associated with a specific metabolism that should be further studied to understand dormancy/quiescence in this yeast.

Submuscular gluteal abcess: An unusual presentation of rare sacral tuberculosis

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Gluteal abscess and sacral tuberculosis are rare entities in spine tuberculosis, as to our knowledge; this is the second case report about it.

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MRI has a great role to describe anatomical pathophysiology of the abscess dissemination from sacral tuberculosis.

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Sacral tuberculosis should be made as the main differential diagnosis for atypical sacral lesion that occurs with submuscular gluteal abscess.

Introduction

Both gluteal abscess and sacral tuberculosis are rare entities in spinal tuberculosis cases. Even in endemic country, this atypical presentation may be the cause of delayed diagnosis and treatment.

Presentation of case

A 51-year-old woman was admitted with painless massive lump on both of her thighs that have been enlarging for the past 6 months. She had a history of previous tuberculosis treatment. From the MRI examination submuscular gluteal abscess, which was an extension of the sacral tuberculosis, were found. Open debridement and biopsy were performed, which confirmed the suspicion of tuberculosis. Oral anti tuberculosis drugs were administered after. There was no recurrence and complication at the final follow up.

Discussion

Cold abscess formation is common in spine tuberculosis however the formation of gluteal abscess as the extension of sacral tuberculosis is rare. Although MRI's specificity in determining the underlying cause is poor, it has a great role not only determining the location and size of the lesion, but also to describe anatomical pathophysiology of the abscess dissemination from sacral tuberculosis.

Conclusion

Despite the limitation of the study and the rarity of this case, tuberculosis should be made as the main differential diagnosis for atypical sacral lesion that occurs with submuscular gluteal abscess.

A Multiscale Agent-Based Model for the Investigation of E. coli K12 Metabolic Response During Biofilm Formation

Bacterial biofilm formation is an organized collective response to biochemical cues that enables bacterial colonies to persist and withstand environmental insults. We developed a multiscale agent-based model that characterizes the intracellular, extracellular, and cellular scale interactions that modulate Escherichia coli MG1655 biofilm formation. Each bacterium's intracellular response and cellular state were represented as an outcome of interactions with the environment and neighboring bacteria. In the intracellular model, environment-driven gene expression and metabolism were captured using statistical regression and Michaelis-Menten kinetics, respectively. In the cellular model, growth, death, and type IV pili- and flagella-dependent movement were based on the bacteria's intracellular state. We implemented the extracellular model as a three-dimensional diffusion model used to describe glucose, oxygen, and autoinducer 2 gradients within the biofilm and bulk fluid. We validated the model by comparing simulation results to empirical quantitative biofilm profiles, gene expression, and metabolic concentrations. Using the model, we characterized and compared the temporal metabolic and gene expression profiles of sessile versus planktonic bacterial populations during biofilm formation and investigated correlations between gene expression and biofilm-associated metabolites and cellular scale phenotypes. Based on our in silico studies, planktonic bacteria had higher metabolite concentrations in the glycolysis and citric acid cycle pathways, with higher gene expression levels in flagella and lipopolysaccharide-associated genes. Conversely, sessile bacteria had higher metabolite concentrations in the autoinducer 2 pathway, with type IV pili, autoinducer 2 export, and cellular respiration genes upregulated in comparison with planktonic bacteria. Having demonstrated results consistent with in vitro static culture biofilm systems, our model enables examination of molecular phenomena within biofilms that are experimentally inaccessible and provides a framework for future exploration of how hypothesized molecular mechanisms impact bulk community behavior.

Screening and identification of potential protein biomarkers for evaluating the efficacy of intensive therapy in pulmonary tuberculosis

This research aimed to discover potential biomarkers for evaluating the therapeutic efficacy of intensive therapy in pulmonary tuberculosis (TB). Protein profiles in 2-months intensively treated TB patients, untreated TB patients, and healthy controls were investigated with iTRAQ-2DLC-MS/MS technique. 71 differential proteins were identified in 2-months intensively treated TB patients. Significant differences in complement component C7 (CO7), apolipoprotein A-IV (APOA4), apolipoprotein C-II (APOC2), and angiotensinogen (ANGT) were found by ELISA validation. CO7 and ANGT were also found significantly different in sputum negative patients, compared with sputum positive patients after intensive treatment. Clinical analysis showed that after 2-months intensive treatment several indicators were significantly changed, and the one-year cure rate of sputum negative patients were significantly higher than sputum positive patients. Diagnostic models consisting of APOC2, CO7 and APOA4 were established to distinguish intensively treated TB patients from untreated TB patients and healthy controls with the AUC value of 0.910 and 0.935. Meanwhile, ANGT and CO7 were combined to identify sputum negative and sputum positive TB patients after intensive treatment with 89.36% sensitivity, 71.43% specificity, and the AUC value of 0.853. The results showed that APOC2, CO7, APOA4, and ANGT may be potential biomarkers for evaluating the efficacy of intensive anti-TB therapy.

Modelling the effects of bacterial cell state and spatial location on tuberculosis treatment: Insights from a hybrid multiscale cellular automaton model

If improvements are to be made in tuberculosis (TB) treatment, an increased understanding of disease in the lung is needed. Studies have shown that bacteria in a less metabolically active state, associated with the presence of lipid bodies, are less susceptible to antibiotics, and recent results have highlighted the disparity in concentration of different compounds into lesions. Treatment success therefore depends critically on the responses of the individual bacteria that constitute the infection. We propose a hybrid, individual-based approach that analyses spatio-temporal dynamics at the cellular level, linking the behaviour of individual bacteria and host cells with the macroscopic behaviour of the microenvironment. The individual elements (bacteria, macrophages and T cells) are modelled using cellular automaton (CA) rules, and the evolution of oxygen, drugs and chemokine dynamics are incorporated in order to study the effects of the microenvironment in the pathological lesion. We allow bacteria to switch states depending on oxygen concentration, which affects how they respond to treatment. This is the first multiscale model of its type to consider both oxygen-driven phenotypic switching of the Mycobacterium tuberculosis and antibiotic treatment. Using this model, we investigate the role of bacterial cell state and of initial bacterial location on treatment outcome. We demonstrate that when bacteria are located further away from blood vessels, less favourable outcomes are more likely, i.e. longer time before infection is contained/cleared, treatment failure or later relapse. We also show that in cases where bacteria remain at the end of simulations, the organisms tend to be slower-growing and are often located within granulomas, surrounded by caseous material.

Killing Mycobacterium tuberculosis In Vitro: What Model Systems Can Teach Us

Tuberculosis is one of the most successful human diseases in our history due in large part to the multitude of virulence factors exhibited by the causative agent, Mycobacterium tuberculosis. Understanding the pathogenic nuances of this organism in the context of its human host is an ongoing topic of study facilitated by isolating cells from model organisms such as mice and non-human primates. However, M. tuberculosis is an obligate intracellular human pathogen, and disease progression and outcome in these model systems can differ from that of human disease. Current in vitro models of infection include primary macrophages and macrophage-like immortalized cell lines as well as the induced pluripotent stem cell-derived cell types. This article will discuss these in vitro model systems in general, what we have learned so far about utilizing them to answer questions about pathogenesis, the potential role of other cell types in innate control of M. tuberculosis infection, and the development of new coculture systems with multiple cell types. As we continue to expand current in vitro systems and institute new ones, the knowledge gained will improve our understanding of not only tuberculosis but all infectious diseases.

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.

IL-2 sensitivity and exogenous IL-2 concentration gradient tune the productive contact duration of CD8(+) T cell-APC: a multiscale modeling study

Background

The CD8⁺ T cell immune response fights acute infections by intracellular pathogens and, by generating an immune memory, enables immune responses against secondary infections. Activation of the CD8⁺ T cell immune response involves a succession of molecular events leading to modifications of CD8⁺ T cell population. To understand the endogenous and exogenous mechanisms controlling the activation of CD8⁺ T cells and to investigate the influence of early molecular events on the long-term cell population behavior, we developed a multiscale computational model. It integrates three levels of description: a Cellular Potts model describing the individual behavior of CD8⁺ T cells, a system of ordinary differential equations describing a decision-making molecular regulatory network at the intracellular level, and a partial differential equation describing the diffusion of IL-2 in the extracellular environment.

Results

We first calibrated the model parameters based on in vivo data and showed the model’s ability to reproduce early dynamics of CD8⁺ T cells in murine lymph nodes after influenza infection, both at the cell population and intracellular levels. We then showed the model’s ability to reproduce the proliferative responses of CD5^hi and CD5^lo CD8⁺ T cells to exogenous IL-2 under a weak TCR stimulation. This stressed the role of short-lasting molecular events and the relevance of explicitly describing both intracellular and cellular scale dynamics. Our results suggest that the productive contact duration of CD8⁺ T cell-APC is influenced by the sensitivity of individual CD8⁺ T cells to the activation signal and by the IL-2 concentration in the extracellular environment.

Conclusions

The multiscale nature of our model allows the reproduction and explanation of some acquired characteristics and functions of CD8⁺ T cells, and of their responses to multiple stimulation conditions, that would not be accessible in a classical description of cell population dynamics that would not consider intracellular dynamics.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-016-0323-y) contains supplementary material, which is available to authorized users.