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Treg induction by a rationally selected mixture of Clostridia strains from the human microbiota

Nature volume 500, pages 232–236 (2013)Cite this article

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Abstract

Manipulation of the gut microbiota holds great promise for the treatment of inflammatory and allergic diseases1,2. Although numerous probiotic microorganisms have been identified3, there remains a compelling need to discover organisms that elicit more robust therapeutic responses, are compatible with the host, and can affect a specific arm of the host immune system in a well-controlled, physiological manner. Here we use a rational approach to isolate CD4+FOXP3+ regulatory T (Treg)-cell-inducing bacterial strains from the human indigenous microbiota. Starting with a healthy human faecal sample, a sequence of selection steps was applied to obtain mice colonized with human microbiota enriched in Treg-cell-inducing species. From these mice, we isolated and selected 17 strains of bacteria on the basis of their high potency in enhancing Treg cell abundance and inducing important anti-inflammatory molecules—including interleukin-10 (IL-) and inducible T-cell co-stimulator (ICOS)—in Treg cells upon inoculation into germ-free mice. Genome sequencing revealed that the 17 strains fall within clusters IV, XIVa and XVIII of Clostridia, which lack prominent toxins and virulence factors. The 17 strains act as a community to provide bacterial antigens and a TGF-β-rich environment to help expansion and differentiation of Treg cells. Oral administration of the combination of 17 strains to adult mice attenuated disease in models of colitis and allergic diarrhoea. Use of the isolated strains may allow for tailored therapeutic manipulation of human immune disorders.

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Figure 1: Treg cell accumulation in germ-free mice induced by inoculation with human microbiota.
Figure 2: Assessment of microbiota composition and isolation of Treg-cell-inducing strains.
Figure 3: Characterization of 17 Treg-cell-inducing strains.
Figure 4: Treatment with 17-mix suppresses experimental colitis models.

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Acknowledgements

This work was supported by JSPS NEXT program, Grant in Aid for Scientific Research on Innovative Areas ‘Genome Science’ from the Ministry of Education, Culture, Sports, Science and Technology of Japan (No.221S0002), the global COE project of ‘Genome Information Big Bang’ and the Waksman Foundation of Japan Inc. We thank M. Suyama, K. Furuya, C. Yoshino, H. Inaba, E. Iioka, Y. Takayama, M. Kiuchi, Y. Hattori, N. Fukuda and A. Nakano for technical assistance, and P. D. Burrows for review of the manuscript.

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Author notes

  1. Koji Atarashi, Takeshi Tanoue and Kenshiro Oshima: These authors contributed equally to this work.

Authors and Affiliations

  1. RIKEN Center for Integrative Medical Sciences (IMS-RCAI), 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan,

    Koji Atarashi, Takeshi Tanoue, Yuji Nagano, Shinji Fukuda, Seiko Narushima, Koji Hase, Hiroshi Ohno & Kenya Honda

  2. Department of Immunology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan,

    Koji Atarashi, Takeshi Tanoue, Yuji Nagano, Tadatsugu Taniguchi & Kenya Honda

  3. PRESTO, Japan Science and Technology Agency, 4-1-8 Honcho Kawaguchi, Saitama 332-0012, Japan,

    Koji Atarashi & Koji Hase

  4. CREST, Japan Science and Technology Agency, 4-1-8 Honcho Kawaguchi, Saitama 332-0012, Japan,

    Kenshiro Oshima, Hidetoshi Morita & Kenya Honda

  5. Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8561, Japan,

    Kenshiro Oshima, Wataru Suda, Sangwan Kim & Masahira Hattori

  6. Experimental Immunology, Immunology Frontier Research Center, Osaka University, 3-1 Yamadaoka, Suita, Osaka 565-0871, Japan,

    Hiroyoshi Nishikawa, Takuro Saito & Shimon Sakaguchi

  7. Institute for Advanced Biosciences, Keio University, 246-2 Mizukami, Tsuruoka, Yamagata 997-0052, Japan,

    Shinji Fukuda

  8. Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Avenue des Hauts-Fourneaux, 7, Esch-sur-Alzette, L-4362, Luxembourg,

    Joëlle V. Fritz & Paul Wilmes

  9. Department of Molecular Preventive Medicine, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan,

    Satoshi Ueha & Kouji Matsushima

  10. PureTech Ventures, 500 Boylston Street, Suite 1600, Boston, Massachusetts 02116, USA,

    Bernat Olle

  11. School of Veterinary Medicine, Azabu University, 1-17-71 Fuchinobe, Sagamihara, Kanagawa 252-5201, Japan,

    Hidetoshi Morita

Authors
  1. Koji Atarashi
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Contributions

K.Ho. planned experiments, analysed data and wrote the paper together with B.O. and M.H.; K.A. and T.Tano. performed immunological analyses and bacterial cultures together with Y.N., S.N. and H.M.; W.S., K.O., S.K. and M.H. performed bacterial sequence analyses; K.M. and S.U. provided essential materials; H.N., T.S. and S.S. supervised the Treg cell suppression assay; S.F., K.Ha., H.O., T.Tani., J.V.F. and P.W. were involved in data discussions.

Corresponding authors

Correspondence to Masahira Hattori or Kenya Honda.

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Competing interests

B.O. is an employee of PureTech Ventures.

Additional information

All genome sequence data are deposited in DDBJ BioProject ID PRJDB521-543.

Supplementary information

Supplementary Figures

This file contains Supplementary Figures 1-17. (PDF 1797 kb)

Supplementary Table 1

This file contains meta 16S rRNA gene analysis for the series of gnotobiotic mice. The numbers of detected reads, the closest species, and % similarities with the closest species for each OTU in each exGF mouse are shown. (XLSX 32 kb)

Supplementary Table 2

This file contains putative toxins and virulence factors found in 17 strains. BLASTP search of gene products predicted from genomes was performed using virulence factor databases (VFDB and MvirDB) with the e-value cut off of 1.0e-10, the identity >30% and the length coverage >60%. Note that several strains possess genes encoding putative hyaluronidase, sialidase, fibronectin-binding proteins, and flagella-related proteins but with low similarity to genes of pathogenic Clostridia species, and most of these genes are also encoded by other commensal Clostridia species. (XLSX 72 kb)

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Atarashi, K., Tanoue, T., Oshima, K. et al. Treg induction by a rationally selected mixture of Clostridia strains from the human microbiota. Nature 500, 232–236 (2013). https://doi.org/10.1038/nature12331

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