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2.
PLoS Comput Biol ; 16(12): e1008520, 2020 12.
Article in English | MEDLINE | ID: mdl-33370784

ABSTRACT

Mycobacterium tuberculosis (Mtb) infection causes tuberculosis (TB), a disease characterized by development of granulomas. Granulomas consist of activated immune cells that cluster together to limit bacterial growth and restrict dissemination. Control of the TB epidemic has been limited by lengthy drug regimens, antibiotic resistance, and lack of a robustly efficacious vaccine. Fibrosis commonly occurs during treatment and is associated with both positive and negative disease outcomes in TB but little is known about the processes that initiate fibrosis in granulomas. Human and nonhuman primate granulomas undergoing fibrosis can have spindle-shaped macrophages with fibroblast-like morphologies suggesting a relationship between macrophages, fibroblasts, and granuloma fibrosis. This relationship has been difficult to investigate because of the limited availability of human pathology samples, the time scale involved in human TB, and overlap between fibroblast and myeloid cell markers in tissues. To better understand the origins of fibrosis in TB, we used a computational model of TB granuloma biology to identify factors that drive fibrosis over the course of local disease progression. We validated the model with granulomas from nonhuman primates to delineate myeloid cells and lung-resident fibroblasts. Our results suggest that peripheral granuloma fibrosis, which is commonly observed, can arise through macrophage-to-myofibroblast transformation (MMT). Further, we hypothesize that MMT is induced in M1 macrophages through a sequential combination of inflammatory and anti-inflammatory signaling in granuloma macrophages. We predict that MMT may be a mechanism underlying granuloma-associated fibrosis and warrants further investigation into myeloid cells as drivers of fibrotic disease.


Subject(s)
Granuloma/pathology , Macrophages/pathology , Myofibroblasts/pathology , Systems Biology , Tuberculosis/pathology , Fibrosis , Humans , Mycobacterium tuberculosis/immunology , STAT1 Transcription Factor/metabolism , STAT3 Transcription Factor/metabolism
3.
Front Immunol ; 11: 613638, 2020.
Article in English | MEDLINE | ID: mdl-33552077

ABSTRACT

Tuberculosis (TB) is a worldwide health problem; successful interventions such as vaccines and treatment require a 2better understanding of the immune response to infection with Mycobacterium tuberculosis (Mtb). In many infectious diseases, pathogen-specific T cells that are recruited to infection sites are highly responsive and clear infection. Yet in the case of infection with Mtb, most individuals are unable to clear infection leading to either an asymptomatically controlled latent infection (the majority) or active disease (roughly 5%-10% of infections). The hallmark of Mtb infection is the recruitment of immune cells to lungs leading to development of multiple lung granulomas. Non-human primate models of TB indicate that on average <10% of T cells within granulomas are Mtb-responsive in terms of cytokine production. The reason for this reduced responsiveness is unknown and it may be at the core of why humans typically are unable to clear Mtb infection. There are a number of hypotheses as to why this reduced responsiveness may occur, including T cell exhaustion, direct downregulation of antigen presentation by Mtb within infected macrophages, the spatial organization of the granuloma itself, and/or recruitment of non-Mtb-specific T cells to lungs. We use a systems biology approach pairing data and modeling to dissect three of these hypotheses. We find that the structural organization of granulomas as well as recruitment of non-specific T cells likely contribute to reduced responsiveness.


Subject(s)
Granuloma, Respiratory Tract/immunology , Macrophages/immunology , Mycobacterium tuberculosis/immunology , T-Lymphocytes/immunology , Tuberculosis, Pulmonary/immunology , Animals , Cytokines/immunology , Granuloma, Respiratory Tract/microbiology , Lung/immunology , Lung/microbiology , Macaca fascicularis , Macrophages/microbiology , Primates , Tuberculosis, Pulmonary/microbiology
4.
J Theor Biol ; 367: 166-179, 2015 Feb 21.
Article in English | MEDLINE | ID: mdl-25497475

ABSTRACT

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.


Subject(s)
Anti-Bacterial Agents/therapeutic use , Computer Simulation , Immunity/drug effects , Tuberculosis/drug therapy , Tuberculosis/immunology , Animals , Anti-Bacterial Agents/pharmacokinetics , Anti-Bacterial Agents/pharmacology , Antitubercular Agents/pharmacokinetics , Antitubercular Agents/pharmacology , Antitubercular Agents/therapeutic use , Calibration , Disease Models, Animal , Dose-Response Relationship, Drug , Granuloma/immunology , Granuloma/pathology , Humans , Isoniazid/pharmacokinetics , Isoniazid/therapeutic use , Mice , Models, Biological , Mycobacterium tuberculosis/drug effects , Mycobacterium tuberculosis/growth & development , Primates , Rifampin/pharmacokinetics , Rifampin/therapeutic use , Time Factors , Treatment Outcome , Tuberculosis/microbiology , Tuberculosis/pathology
5.
Ambio ; 36(8): 657-60, 2007 Dec.
Article in English | MEDLINE | ID: mdl-18240681

ABSTRACT

Using Christmas Bird Count data, we analyze the annual spatio-temporal abundances of six passerine species in the upper Great Plains, US (1960-1990). This study provides new insight into how global warming could cause separation of species within present-day communities. We find that winter relative abundances of similarly-sized songbirds are differentially affected by ambient winter temperature. As such, average annual winter temperature fluctuations (i.e., severity of winter) are significantly (P < 0.05) correlated with the relative abundances of three species while the other three are not. Our conditional probability-of-occurrence analysis indicates that the abundances of the three temperature-associated species declined markedly below -4 degrees C while the abundances of the other three species fluctuated little from 8 degrees C to -16 degrees C. We conclude that even in colder climates i) the winter distributions of some, but not all, songbirds are directly or indirectly limited by temperature; and ii) these birds have dynamic abundances that can quickly respond to temperature changes.


Subject(s)
Greenhouse Effect , Songbirds , Animals , Population Density , Population Dynamics , Seasons , Temperature , United States
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