| Literature DB >> 30228238 |
Sivaranjani Namasivayam1, Alan Sher2, Michael S Glickman3,4, Matthew F Wipperman5,6.
Abstract
Tuberculosis (TB) is an ancient infectious disease of humans that has been extensively studied both clinically and experimentally. Although susceptibility to Mycobacterium tuberculosis infection is clearly influenced by factors such as nutrition, immune status, and both mycobacterial and host genetics, the variable pathogenesis of TB in infected individuals remains poorly understood. During the past two decades, it has become clear that the microbiota-the trillion organisms that reside at mucosal surfaces within and on the body-can exert a major influence on disease outcome through its effects on host innate and adaptive immune function and metabolism. This new recognition of the potentially pleiotropic participation of the microbiome in immune responses has raised the possibility that the microbiota may influence M. tuberculosis infection and/or disease. Similarly, treatment of TB may alter the healthy steady-state composition and function of the microbiome, possibly affecting treatment outcome in addition to other host physiological parameters. Herein, we review emerging evidence for how the microbiota may influence the transition points in the life cycle of TB infection, including (i) resistance to initial infection, (ii) initial infection to latent tuberculosis (LTBI), (iii) LTBI to reactivated disease, and (iv) treatment to cure. A major goal of this review is to frame questions to guide future scientific and clinical studies in this largely unexplored but increasingly important area of TB research.Entities:
Keywords: antibiotics; microbiome; tuberculosis
Mesh:
Substances:
Year: 2018 PMID: 30228238 PMCID: PMC6143735 DOI: 10.1128/mBio.01420-18
Source DB: PubMed Journal: MBio Impact factor: 7.867
FIG 1Putative interactions between the intestinal and/or lung microbiome and the host that could influence the outcome of M. tuberculosis (Mtb) infection and treatment. The potential intersection points between microbiome, TB infection, and antibiotic treatment are multifold. (Point 1) Previous studies have demonstrated that specific clades of organisms (e.g., Prevotella) produce short-chain fatty acids like butyrate and propionate (44) that could set tissue-specific immune responsiveness in the lung. (Point 2) The immune state dictated in part by the interaction of the lung microbiota and innate cells such as alveolar macrophages could shape the outcome of the initial encounter of TB with the host. (Point 3) Additionally, the intestinal microbiome and its metabolites, through their previously described role in setting systemic immune tone and/or the production of antimicrobial products, may influence TB susceptibility in a related but trans fashion. (Point 4) Finally, the effects of M. tuberculosis infection and/or its treatment with antibiotics on the microbiota could influence the outcome of TB therapy and cure as well as other physiological functions.
Summary of antituberculosis treatment-induced alterations in the microbiota
| Antibiotic(s) | Effect on intestinal microbiota | Reference |
|---|---|---|
| HRZ (mice) | Decreases in | |
| Post-HRZ (mice) | Decrease in | |
| HRZE (humans) | Decrease in | |
| HRZE (humans) | Decrease in | |
| Post-HRZE (humans) | Decrease in | |
| H alone | Alterations in | |
| R alone | Decrease in diversity and a number of | |
| Z alone | Alterations in |
Abbreviations: H, isoniazid; R, rifampin; Z, pyrazinamide; E, ethambutol.
FIG 2Cladograms depicting the parallel effects of TB antibiotic treatment on the intestinal microbiomes of mice and humans. Two recent studies reported the effects of antituberculosis therapy, HRZ(E), on the gut flora of mice (57) and humans (81). A combined comparison of data from naive/healthy mice/humans versus mice administered HRZ or humans taking HRZE is shown based on published (57, 81) as well as additional unpublished data. In both host species, in comparison to corresponding healthy untreated controls, members of the order Clostridiales were depleted following treatment, whereas certain taxa of the order Erysipelotrichales and phylum Actinobacteria were enriched. Cladograms were generated using Metacoder (92).