期刊
ELIFE
卷 7, 期 -, 页码 -出版社
ELIFE SCIENCES PUBLICATIONS LTD
DOI: 10.7554/eLife.30916
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资金
- National Institutes of Health [P41 GM103504]
- Defense Advanced Research Projects Agency [HR0011-15-C-0094]
- Human Frontier Science Program [RGP00055/2015]
- Takeda Science Foundation
- National Institute of General Medical Sciences [5R01 GM106303]
- Japan Agency for Medical Research and Development
- National Institute of Allergy and Infectious Diseases [R15-AI112985-01A1]
- National Science Foundation [1458347]
- Core Research for Evolutional Science and Technology
- Brigham and Women's Hospital
- Div Of Biological Infrastructure
- Direct For Biological Sciences [1458347] Funding Source: National Science Foundation
Manipulation of the gut microbiota holds great promise for the treatment of diseases. However, a major challenge is the identification of therapeutically potent microbial consortia that colonize the host effectively while maximizing immunologic outcome. Here, we propose a novel workflow to select optimal immune-inducing consortia from microbiome compositicon and immune effectors measurements. Using published and newly generated microbial and regulatory T-cell (T-reg) data from germ-free mice, we estimate the contributions of twelve Clostridia strains with known immune-modulating effect to T-reg induction. Combining this with a longitudinal data-constrained ecological model, we predict the ability of every attainable and ecologically stable subconsortium in promoting T-reg activation and rank them by the T-reg Induction Score (TrIS). Experimental validation of selected consortia indicates a strong and statistically significant correlation between predicted TrIS and measured T-reg. We argue that computational indexes, such as the TrIS, are valuable tools for the systematic selection of immune-modulating bacteriotherapeutics.
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