Computer-guided design of optimal microbial consortia for immune system modulation

Richard R. Stein, Takeshi Tanoue, Rose L. Szabady, Shakti K. Bhattarai, Bernat Olle, Jason M. Norman, Wataru Suda, Kenshiro Oshima, Masahira Hattori, Georg K. Gerber, Chris Sander, Kenya Honda, Vanni Bucci

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

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 (Treg) data from germ-free mice, we estimate the contributions of twelve Clostridia strains with known immune-modulating effect to Treg induction. Combining this with a longitudinal data-constrained ecological model, we predict the ability of every attainable and ecologically stable subconsortium in promoting Treg activation and rank them by the Treg Induction Score (TrIS). Experimental validation of selected consortia indicates a strong and statistically significant correlation between predicted TrIS and measured Treg. We argue that computational indexes, such as the TrIS, are valuable tools for the systematic selection of immune-modulating bacteriotherapeutics.

Original languageEnglish
Article numbere30916
JournaleLife
Volume7
DOIs
Publication statusPublished - 2018 Apr 17
Externally publishedYes

Fingerprint

Microbial Consortia
Clostridium
T-cells
Workflow
Immune system
Microbiota
Regulatory T-Lymphocytes
Immune System
Chemical activation
Modulation
Gastrointestinal Microbiome

ASJC Scopus subject areas

  • Neuroscience(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)

Cite this

Stein, R. R., Tanoue, T., Szabady, R. L., Bhattarai, S. K., Olle, B., Norman, J. M., ... Bucci, V. (2018). Computer-guided design of optimal microbial consortia for immune system modulation. eLife, 7, [e30916]. https://doi.org/10.7554/eLife.30916

Computer-guided design of optimal microbial consortia for immune system modulation. / Stein, Richard R.; Tanoue, Takeshi; Szabady, Rose L.; Bhattarai, Shakti K.; Olle, Bernat; Norman, Jason M.; Suda, Wataru; Oshima, Kenshiro; Hattori, Masahira; Gerber, Georg K.; Sander, Chris; Honda, Kenya; Bucci, Vanni.

In: eLife, Vol. 7, e30916, 17.04.2018.

Research output: Contribution to journalArticle

Stein, RR, Tanoue, T, Szabady, RL, Bhattarai, SK, Olle, B, Norman, JM, Suda, W, Oshima, K, Hattori, M, Gerber, GK, Sander, C, Honda, K & Bucci, V 2018, 'Computer-guided design of optimal microbial consortia for immune system modulation' eLife, vol. 7, e30916. https://doi.org/10.7554/eLife.30916
Stein RR, Tanoue T, Szabady RL, Bhattarai SK, Olle B, Norman JM et al. Computer-guided design of optimal microbial consortia for immune system modulation. eLife. 2018 Apr 17;7. e30916. https://doi.org/10.7554/eLife.30916
Stein, Richard R. ; Tanoue, Takeshi ; Szabady, Rose L. ; Bhattarai, Shakti K. ; Olle, Bernat ; Norman, Jason M. ; Suda, Wataru ; Oshima, Kenshiro ; Hattori, Masahira ; Gerber, Georg K. ; Sander, Chris ; Honda, Kenya ; Bucci, Vanni. / Computer-guided design of optimal microbial consortia for immune system modulation. In: eLife. 2018 ; Vol. 7.
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