Treg induction by a rationally selected mixture of Clostridia strains from the human microbiota (original) (raw)

Accession codes

Accessions

DDBJ/GenBank/EMBL

References

  1. Round, J. L. & Mazmanian, S. K. The gut microbiota shapes intestinal immune responses during health and disease. Nature Rev. Immunol. 9, 313–323 (2009)
    Article CAS Google Scholar
  2. Honda, K. & Littman, D. R. The microbiome in infectious disease and inflammation. Annu. Rev. Immunol. 30, 759–795 (2012)
    Article CAS Google Scholar
  3. O’Toole, P. W. & Cooney, J. C. Probiotic bacteria influence the composition and function of the intestinal microbiota. Interdiscip. Perspect. Infect. Dis. 2008, 175285 (2008)
    PubMed PubMed Central Google Scholar
  4. Atarashi, K. et al. Induction of colonic regulatory T cells by indigenous Clostridium species. Science 331, 337–341 (2011)
    Article ADS CAS Google Scholar
  5. Geuking, M. B. et al. Intestinal bacterial colonization induces mutualistic regulatory T cell responses. Immunity 34, 794–806 (2011)
    Article CAS Google Scholar
  6. Russell, S. L. et al. Early life antibiotic-driven changes in microbiota enhance susceptibility to allergic asthma. EMBO Rep. 13, 440–447 (2012)
    Article CAS Google Scholar
  7. Round, J. L. & Mazmanian, S. K. Inducible Foxp3+ regulatory T-cell development by a commensal bacterium of the intestinal microbiota. Proc. Natl Acad. Sci. USA 107, 12204–12209 (2010)
    Article ADS CAS Google Scholar
  8. Chung, H. et al. Gut immune maturation depends on colonization with a host-specific microbiota. Cell 149, 1578–1593 (2012)
    Article CAS Google Scholar
  9. Sokol, H. et al. Faecalibacterium prausnitzii is an anti-inflammatory commensal bacterium identified by gut microbiota analysis of Crohn disease patients. Proc. Natl Acad. Sci. USA 105, 16731–16736 (2008)
    Article ADS CAS Google Scholar
  10. Thornton, A. M. et al. Expression of Helios, an Ikaros transcription factor family member, differentiates thymic-derived from peripherally induced Foxp3+ T regulatory cells. J. Immunol. 184, 3433–3441 (2010)
    Article CAS Google Scholar
  11. Rubtsov, Y. P. et al. Regulatory T cell-derived interleukin-10 limits inflammation at environmental interfaces. Immunity 28, 546–558 (2008)
    Article CAS Google Scholar
  12. Wing, K. et al. CTLA-4 control over Foxp3+ regulatory T cell function. Science 322, 271–275 (2008)
    Article ADS CAS Google Scholar
  13. Zheng, Y. et al. Regulatory T-cell suppressor program co-opts transcription factor IRF4 to control TH2 responses. Nature 458, 351–356 (2009)
    Article ADS CAS Google Scholar
  14. Maslowski, K. M. & Mackay, C. R. Diet, gut microbiota and immune responses. Nature Immunol. 12, 5–9 (2011)
    Article CAS Google Scholar
  15. Lathrop, S. K. et al. Peripheral education of the immune system by colonic commensal microbiota. Nature 478, 250–254 (2011)
    Article ADS CAS Google Scholar
  16. Cebula, A. et al. Thymus-derived regulatory T cells contribute to tolerance to commensal microbiota. Nature 497, 258–262 (2013)
    Article ADS CAS Google Scholar
  17. Collins, M. D. et al. The phylogeny of the genus Clostridium: proposal of five new genera and eleven new species combinations. Int. J. Syst. Bacteriol. 44, 812–826 (1994)
    Article CAS Google Scholar
  18. Qin, J. et al. A human gut microbial gene catalogue established by metagenomic sequencing. Nature 464, 59–65 (2010)
    Article CAS Google Scholar
  19. Kweon, M. N., Yamamoto, M., Kajiki, M., Takahashi, I. & Kiyono, H. Systemically derived large intestinal CD4+ Th2 cells play a central role in STAT6-mediated allergic diarrhea. J. Clin. Invest. 106, 199–206 (2000)
    Article CAS Google Scholar
  20. Strober, W., Fuss, I. J. & Blumberg, R. S. The immunology of mucosal models of inflammation. Annu. Rev. Immunol. 20, 495–549 (2002)
    Article CAS Google Scholar
  21. Lawley, T. D. et al. Targeted restoration of the intestinal microbiota with a simple, defined bacteriotherapy resolves relapsing Clostridium difficile disease in mice. PLoS Pathog. 8, e1002995 (2012)
    Article CAS Google Scholar
  22. Frank, D. N. et al. Molecular-phylogenetic characterization of microbial community imbalances in human inflammatory bowel diseases. Proc. Natl Acad. Sci. USA 104, 13780–13785 (2007)
    Article ADS CAS Google Scholar
  23. Manichanh, C. et al. Reduced diversity of faecal microbiota in Crohn’s disease revealed by a metagenomic approach. Gut 55, 205–211 (2006)
    Article CAS Google Scholar
  24. Candela, M. et al. Unbalance of intestinal microbiota in atopic children. BMC Microbiol. 12, 95 (2012)
    Article CAS Google Scholar
  25. Morita, H. et al. An improved isolation method for metagenomic analysis of the microbial flora of the human intestine. Microbes Environ. 22, 214–222 (2007)
    Article Google Scholar
  26. Kim, S. W. et al. Robustness of gut microbiota of healthy adults in response to probiotic intervention revealed by high-throughput pyrosequencing. DNA Res. 20, 241–253 (2013)
    Article CAS Google Scholar
  27. Noguchi, H., Taniguchi, T. & Itoh, T. MetaGeneAnnotator: detecting species-specific patterns of ribosomal binding site for precise gene prediction in anonymous prokaryotic and phage genomes. DNA Res. 15, 387–396 (2008)
    Article CAS Google Scholar
  28. Jolley, K. A. et al. Ribosomal multilocus sequence typing: universal characterization of bacteria from domain to strain. Microbiology 158, 1005–1015 (2012)
    Article CAS Google Scholar

Download references

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.

Author information

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
    You can also search for this author inPubMed Google Scholar
  2. Takeshi Tanoue
    You can also search for this author inPubMed Google Scholar
  3. Kenshiro Oshima
    You can also search for this author inPubMed Google Scholar
  4. Wataru Suda
    You can also search for this author inPubMed Google Scholar
  5. Yuji Nagano
    You can also search for this author inPubMed Google Scholar
  6. Hiroyoshi Nishikawa
    You can also search for this author inPubMed Google Scholar
  7. Shinji Fukuda
    You can also search for this author inPubMed Google Scholar
  8. Takuro Saito
    You can also search for this author inPubMed Google Scholar
  9. Seiko Narushima
    You can also search for this author inPubMed Google Scholar
  10. Koji Hase
    You can also search for this author inPubMed Google Scholar
  11. Sangwan Kim
    You can also search for this author inPubMed Google Scholar
  12. Joëlle V. Fritz
    You can also search for this author inPubMed Google Scholar
  13. Paul Wilmes
    You can also search for this author inPubMed Google Scholar
  14. Satoshi Ueha
    You can also search for this author inPubMed Google Scholar
  15. Kouji Matsushima
    You can also search for this author inPubMed Google Scholar
  16. Hiroshi Ohno
    You can also search for this author inPubMed Google Scholar
  17. Bernat Olle
    You can also search for this author inPubMed Google Scholar
  18. Shimon Sakaguchi
    You can also search for this author inPubMed Google Scholar
  19. Tadatsugu Taniguchi
    You can also search for this author inPubMed Google Scholar
  20. Hidetoshi Morita
    You can also search for this author inPubMed Google Scholar
  21. Masahira Hattori
    You can also search for this author inPubMed Google Scholar
  22. Kenya Honda
    You can also search for this author inPubMed Google Scholar

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 toMasahira Hattori or Kenya Honda.

Ethics declarations

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)

PowerPoint slides

Rights and permissions

About this article

Cite this article

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

Download citation