ArticlemBio2015
Characterization of host and microbial determinants in individuals with latent tuberculosis infection using a human granuloma model.
Article in mBio, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 87 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
87 citing papers in PubMed, 1 synthesis or guideline pooled it, 124 citations in OpenAlex.
- Pooled it
- Article
- Biodetection of Mycobacterium tuberculosis: nano-biosensors in detection; from principles to recent progresses.Journal of biological engineering · 2026Review
- Methodology for a freshly engineered or cryo-preserved 3D tuberculoma bioplatform for studying tuberculosis biology and high-content screening of therapeutics.Frontiers in immunology · 2026Article
- Exploring the Protein Landscape of Dormant Mycobacterium tuberculosis Through In Vitro Functional Studies.Advances in experimental medicine and biology · 2026Review
- Whole Blood vs Serum-Derived Exosomes for Host and Pathogen-Specific Tuberculosis Biomarker Identification: RNA-Seq-Based Machine-Learning Approach.Biochemical genetics · 2025Article
- Article
- Methods for Evaluating the Effects of 2D and 3D Culture Environment on Macrophage Response to Mycobacterium Infection.Microorganisms · 2025Article
- Human alveolar macrophage response to Mycobacterium tuberculosis: immune characteristics underlying large inter-individual variability.Communications biology · 2025Article
- Article
- Timing matters in macrophage/CD4+ T cell interactions: an agent-based model comparingmSystems · 2025Article
- Plasma Immune Biomarkers Predictive of Progression to Active Tuberculosis in Household Contacts of Patients With Tuberculosis.The Journal of infectious diseases · 2025Article
- Model systems to studyFrontiers in cellular and infection microbiology · 2025Review
- Experimental dissection of tuberculosis protective immunity: a human perspective.Frontiers in cellular and infection microbiology · 2025Review
- Efficacy and Possible Mechanism(s) of Action of Gallium Tetraphenylporphyrin Nanoparticles against HIV-TB Coinfection in anACS infectious diseases · 2024Article
- Clinical significance of pleural fluid lactate dehydrogenase/adenosine deaminase ratio in the diagnosis of tuberculous pleural effusion.BMC pulmonary medicine · 2024Article
- Tuberculosis Vaccines and T Cell Immune Memory.Vaccines · 2024Review
- Review
- Combination of MCL-1 and BCL-2 inhibitors is a promising approach for a host-directed therapy for tuberculosis.Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie · 2023Article
- Functionalizing Dendrimers for Targeted Delivery of Bioactive Molecules to Macrophages: A Potential Treatment forPharmaceuticals (Basel, Switzerland) · 2023Review
27 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
unlabelledGranulomas sit at the center of tuberculosis (TB) immunopathogenesis. Progress in biomarkers and treatment specific to the human granuloma environment is hindered by the lack of a relevant and tractable infection model that better accounts for the complexity of the host immune response as well as pathogen counterresponses that subvert host immunity in granulomas. Here we developed and characterized an in vitro granuloma model derived from human peripheral blood mononuclear cells (PBMCs) and autologous serum. Importantly, we interrogated this model for its ability to discriminate between host and bacterial determinants in individuals with and without latent TB infection (LTBI). By the use of this model, we provide the first evidence that granuloma formation, bacterial survival, lymphocyte proliferation, pro- and anti-inflammatory cytokines, and lipid body accumulation are significantly altered in LTBI individuals. Moreover, we show a specific transcriptional signature of Mycobacterium tuberculosis associated with survival within human granuloma structures depending on the host immune status. Our report provides fundamentally new information on how the human host immune status and bacterial transcriptional signature may dictate early granuloma formation and outcome and provides evidence for the validity of the granuloma model and its potential applications. IMPORTANCE: In 2012, approximately 1.3 million people died from tuberculosis (TB), the highest rate for any single bacterial pathogen. The long-term control of TB requires a better understanding of Mycobacterium tuberculosis pathogenesis in appropriate research models. Granulomas represent the characteristic host tissue response to TB, controlling the bacilli while concentrating the immune response to a limited area. However, complete eradication of bacteria does not occur, since M. tuberculosis has its own strategies to adapt and persist. Thus, the M. tuberculosis-containing granuloma represents a unique environment for dictating both the host immune response and the bacterial response. Here we developed and characterized an in vitro granuloma model derived from blood cells of individuals with latent TB infection that more accurately defines the human immune response and metabolic profiles of M. tuberculosis within this uniquely regulated immune environment. This model may also prove beneficial for understanding other granulomatous diseases.
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What OpenQuestion holds
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.