ArticlePloS one2013
Multi-scale modeling predicts a balance of tumor necrosis factor-α and interleukin-10 controls the granuloma environment during Mycobacterium tuberculosis infection.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 88 papers.
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Who cites it
88 citing papers in PubMed, 123 citations in OpenAlex.
- The Synergistic Effects of the Glutathione Precursor, NAC and First-Line Antibiotics in the Granulomatous Response AgainstFrontiers in immunology · 2018Trial
- A Comparison of Mechanisms Driving Lesion Outcomes During Lung Tumor and Tuberculosis Granuloma Formation.Bulletin of mathematical biology · 2026Article
- The eight pillars of within-host tuberculosis modelling.Frontiers in immunology · 2026Review
- Age-related severity of nontuberculous mycobacterial lung disease is mediated by aberrant macrophage responses and lung microbial dysbiosis.The Journal of infection · 2025Article
- Partially-functional exhausted CD8+ T cells can contribute to short-term viral suppression: a computational prediction for children with perinatal HIV.bioRxiv : the preprint server for biology · 2025Article
- A novel machine-learning based optimization: identifying new treatment regimens for tuberculosis.Numerical algebra, control and optimization · 2025Article
- Rankings of tuberculosis antibiotic treatment regimens are sensitive to spatial scale, detection limit, and initial host bacterial burden.Journal of theoretical biology · 2025Article
- Timing matters in macrophage/CD4+ T cell interactions: an agent-based model comparingmSystems · 2025Article
- Review
- GEODE: anFrontiers in pharmacology · 2025Article
- A brief overview of mathematical modeling of the within-host dynamics of Mycobacterium tuberculosis.Frontiers in applied mathematics and statistics · 2024Article
- In silico agent-based modeling approach to characterize multiple in vitro tuberculosis infection models.PloS one · 2024Article
- Optimizing tuberculosis treatment efficacy: Comparing the standard regimen with Moxifloxacin-containing regimens.PLoS computational biology · 2023Article
- A computational modeling approach for predicting multicell spheroid patterns based on signaling-induced differential adhesion.PLoS computational biology · 2022Article
- A global method for fast simulations of molecular dynamics in multiscale agent-based models of biological tissues.iScience · 2022Article
- QSPcc reduces bottlenecks in computational model simulations.Communications biology · 2021Article
- To Sobol or not to Sobol? The effects of sampling schemes in systems biology applications.Mathematical biosciences · 2021Article
- A multi-scale pipeline linking drug transcriptomics with pharmacokinetics predicts in vivo interactions of tuberculosis drugs.Scientific reports · 2021Article
- Article
- Development of New Tuberculosis Drugs: Translation to Regimen Composition for Drug-Sensitive and Multidrug-Resistant Tuberculosis.Annual review of pharmacology and toxicology · 2021Review
28 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Interleukin-10 (IL-10) and tumor necrosis factor-α (TNF-α) are key anti- and pro-inflammatory mediators elicited during the host immune response to Mycobacterium tuberculosis (Mtb). Understanding the opposing effects of these mediators is difficult due to the complexity of processes acting across different spatial (molecular, cellular, and tissue) and temporal (seconds to years) scales. We take an in silico approach and use multi-scale agent based modeling of the immune response to Mtb, including molecular scale details for both TNF-α and IL-10. Our model predicts that IL-10 is necessary to modulate macrophage activation levels and to prevent host-induced tissue damage in a granuloma, an aggregate of cells that forms in response to Mtb. We show that TNF-α and IL-10 parameters related to synthesis, signaling, and spatial distribution processes control concentrations of TNF-α and IL-10 in a granuloma and determine infection outcome in the long-term. We devise an overall measure of granuloma function based on three metrics - total bacterial load, macrophage activation levels, and apoptosis of resting macrophages - and use this metric to demonstrate a balance of TNF-α and IL-10 concentrations is essential to Mtb infection control, within a single granuloma, with minimal host-induced tissue damage. Our findings suggest that a balance of TNF-α and IL-10 defines a granuloma environment that may be beneficial for both host and pathogen, but perturbing the balance could be used as a novel therapeutic strategy to modulate infection outcomes.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.