ArticlePLoS computational biology2020
A computational model tracks whole-lung Mycobacterium tuberculosis infection and predicts factors that inhibit dissemination.
Article in PLoS computational biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed, 32 citations in OpenAlex.
- Immortal genome assumption significantly underestimates replication and death rates ofMicrobiology spectrum · 2026Article
- Immortal genome assumption significantly underestimates replication and death rates ofbioRxiv : the preprint server for biology · 2026Article
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- Bacterial zinc metalloproteases as facilitators of pathogenic success: a review.Archives of microbiology · 2026Review
- The eight pillars of within-host tuberculosis modelling.Frontiers in immunology · 2026Review
- Tuberculosis: An Ongoing Global Threat.Advances in experimental medicine and biology · 2026Review
- Rankings of tuberculosis antibiotic treatment regimens are sensitive to spatial scale, detection limit, and initial host bacterial burden.Journal of theoretical biology · 2025Article
- Enhanced Glycosylation Caused by Overexpression of Rv1002c in a Recombinant BCG Promotes Immune Response and Protects againstVaccines · 2024Article
- Decoding immune kinetics: unveiling secrets using custom-built mathematical models.Nature methods · 2024Article
- A systematic efficacy analysis of tuberculosis treatment with BPaL-containing regimens using a multiscale modeling approach.CPT: pharmacometrics & systems pharmacology · 2024Article
- A brief overview of mathematical modeling of the within-host dynamics of Mycobacterium tuberculosis.Frontiers in applied mathematics and statistics · 2024Article
- Optimizing tuberculosis treatment efficacy: Comparing the standard regimen with Moxifloxacin-containing regimens.PLoS computational biology · 2023Article
- The spatial dynamics of immune response upon virus infection through hybrid dynamical computational model.Frontiers in immunology · 2023Article
- Investigating the comorbidity of COPD and tuberculosis, a computational study.Frontiers in systems biology · 2023Article
- A virtual host model of Mycobacterium tuberculosis infection identifies early immune events as predictive of infection outcomes.Journal of theoretical biology · 2022Article
- A multi-approach and multi-scale platform to model CD4+ T cells responding to infections.PLoS computational biology · 2021Article
- To Sobol or not to Sobol? The effects of sampling schemes in systems biology applications.Mathematical biosciences · 2021Article
- The knowns and unknowns of latent Mycobacterium tuberculosis infection.The Journal of clinical investigation · 2021Review
- Article
- Neutrophil Dynamics AffectFrontiers in immunology · 2021Article
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
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.
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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.