4.7 Article

Characterization of Host and Microbial Determinants in Individuals with Latent Tuberculosis Infection Using a Human Granuloma Model

Journal

MBIO
Volume 6, Issue 1, Pages -

Publisher

AMER SOC MICROBIOLOGY
DOI: 10.1128/mBio.02537-14

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Funding

  1. NCATS NIH HHS [UL1 TR001070] Funding Source: Medline
  2. NIAID NIH HHS [T32 AI070117] Funding Source: Medline
  3. NIGMS NIH HHS [R25 GM089571] Funding Source: Medline
  4. NATIONAL CENTER FOR ADVANCING TRANSLATIONAL SCIENCES [UL1TR001070] Funding Source: NIH RePORTER
  5. NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES [T32AI070117] Funding Source: NIH RePORTER
  6. NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES [R25GM089571] Funding Source: NIH RePORTER

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Granulomas 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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