| Literature DB >> 31729564 |
Osagie A Eribo1, Nelita du Plessis1, Mumin Ozturk2,3, Reto Guler2,3, Gerhard Walzl1, Novel N Chegou4.
Abstract
Although tuberculosis (TB) is a curable disease, it remains the foremost cause of death from a single pathogen. Globally, approximately 1.6 million people died of TB in 2017. Many predisposing factors related to host immunity, genetics and the environment have been linked to TB. However, recent evidence suggests a relationship between dysbiosis in the gut microbiome and TB disease development. The underlying mechanism(s) whereby dysbiosis in the gut microbiota may impact the different stages in TB disease progression, are, however, not fully explained. In the wake of recently emerging literature, the gut microbiome could represent a potential modifiable host factor to improve TB immunity and treatment response. Herein, we summarize early data detailing (1) possible association between gut microbiome dysbiosis and TB (2) the potential for the use of microbiota biosignatures to discriminate active TB disease from healthy individuals (3) the adverse effect of protracted anti-TB antibiotics treatment on gut microbiota balance, and possible link to increased susceptibility to Mycobacterium tuberculosis re-infection or TB recrudescence following successful cure. We also discuss immune pathways whereby the gut microbiome could impact TB disease and serve as target for clinical manipulation.Entities:
Keywords: Gut commensal; Immune response; Microbial imbalance; Microbiome biosignatures; Mycobacterium tuberculosis; Tuberculosis therapy
Mesh:
Substances:
Year: 2019 PMID: 31729564 PMCID: PMC7162824 DOI: 10.1007/s00018-019-03370-4
Source DB: PubMed Journal: Cell Mol Life Sci ISSN: 1420-682X Impact factor: 9.261
Summary of recent studies on gut microbiome and tuberculosis
| Authors | Study location | Study type | Study description | Main differences in microbiota between groups | Immune correlates/effect | Ref |
|---|---|---|---|---|---|---|
| Hu et al. (2019) | China | Human | A total of 46 TB cases and 61 controls. Patients were newly diagnosed with pulmonary TB and anti-TB drug naïve. | 1. SCFA producers enriched in control cohorts compared to TB cases 2. Three microbiota signatures comprising | [ | |
| Khan et al. (2019) | Canada | Animal | Experimental animals were pretreated with INH/PYZ or RIF followed by H37Rv infection. Control animals were antibiotics untreated but infected with H37Rv. 4-5 mice per group | 1. Significant difference in 2. RIF depleted Firmicutes population and increased | INH/PYZ treatment dampened alveolar macrophage spare respiratory capacity, basal respiration and ATP production. Reduced IL-1β, TNF-α and MHCII. Increased macrophage permissiveness and mouse susceptibility to | [ |
| Hu et al. (2019) | China | Human | A total of 61 TB cases, 10 LTBI and 13 healthy controls. TB cases were divided into 28 active TB, 13 and 10 TB patients on 1- and 2-weeks anti-TB therapy, respectively, and 10 cured TB patients | 1. Minor changes during 2. Decreased | [ | |
| Dumas et al. (2018) | France | Animal | Treatment of mice with broad-spectrum antibiotics, infection with | No change in neutrophils, macrophages, dendritic cells, IFN-γ, TNF-α and IL-1β in antibiotics-treated animals. Decrease in MAIT cells and IL17A in treated animals and increased | [ | |
| Luo et al. (2017) | China | Human | 37 TB patients and 20 healthy controls. TB patients were divided into NTB (new diagnose with TB and less than I week anti-TB treatment) and RTB (previously treated and cured prior to becoming culture-positive) | 1. 2. Depleted | Both | [ |
| Wipperman et al. (2017) | Haiti | Human | Cohorts of 19 TB patients on treatment, 19 patients treated and cured of TB and 75 controls. 3 TB patients were on treatment for more than 6 months. Controls were divided into 50 IGRA positive and 25 IGRA negative (LTBI) | 1. 2. | [ |
SCFA Short chain fatty acid, FT faecal transplant, INH Isoniazid, RIF Rifampicin, PYZ pyrazinamide, LTBI Latent tuberculosis infection, IGRA interferon gamma release assay, IFN-γ interferon gamma, TNF-α tumor necrosis factor-alpha, Th T helper, IL interleukin, MAIT mucosal associated invariant T, MHCII Major histocompatibility complex II, AUC Area under curve
Fig. 1Model for gut microbiome and metabolite regulation of cytokine responses during tuberculosis disease. Heterogeneity and balance in gut microbiota and metabolites provide different signals that educate the immune system. Exposure to M.tb infection triggers gut–lung homing of pro- and anti-inflammatory T lymphocytes. Homeostatic cytokine lung environment is maintained. Macrophages clear infection or contain pathogen within granulomas in people shown as No TB disease. By contrast, factors such as antibiotics use, HIV infection and diabetes alter microbiota balance leading to defective/skewed T lymphocytes activation. M.tb infectious challenge in this state triggers over-abundance of a T lymphocyte subsets upon gut–lung homing. Macrophage response is impaired. Defective T and B cell cooperation results in poor control of infection, promotes infection of adjacent lung tissues and progression to active TB disease