Letter | Published:

Precision microbiome reconstitution restores bile acid mediated resistance to Clostridium difficile

Nature volume 517, pages 205208 (08 January 2015) | Download Citation

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Abstract

The gastrointestinal tracts of mammals are colonized by hundreds of microbial species that contribute to health, including colonization resistance against intestinal pathogens1. Many antibiotics destroy intestinal microbial communities and increase susceptibility to intestinal pathogens2. Among these, Clostridium difficile, a major cause of antibiotic-induced diarrhoea, greatly increases morbidity and mortality in hospitalized patients3. Which intestinal bacteria provide resistance to C. difficile infection and their in vivo inhibitory mechanisms remain unclear. Here we correlate loss of specific bacterial taxa with development of infection, by treating mice with different antibiotics that result in distinct microbiota changes and lead to varied susceptibility to C. difficile. Mathematical modelling augmented by analyses of the microbiota of hospitalized patients identifies resistance-associated bacteria common to mice and humans. Using these platforms, we determine that Clostridium scindens, a bile acid 7α-dehydroxylating intestinal bacterium, is associated with resistance to C. difficile infection and, upon administration, enhances resistance to infection in a secondary bile acid dependent fashion. Using a workflow involving mouse models, clinical studies, metagenomic analyses, and mathematical modelling, we identify a probiotic candidate that corrects a clinically relevant microbiome deficiency. These findings have implications for the rational design of targeted antimicrobials as well as microbiome-based diagnostics and therapeutics for individuals at risk of C. difficile infection.

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Change history

  • 07 January 2015

    A minor change was made to the author list.

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Sequence Read Archive

Data deposits

Study sequence data are deposited in the National Center for Biotechnology Information Sequence Read Archive under accession number SRP045811.

References

  1. 1.

    & Microbiota-mediated colonization resistance against intestinal pathogens. Nature Rev. Immunol. 13, 790–801 (2013)

  2. 2.

    et al. Profound alterations of intestinal microbiota following a single dose of clindamycin results in sustained susceptibility to Clostridium difficile-induced colitis. Infect. Immun. 80, 62–73 (2012)

  3. 3.

    , & Clostridium difficile infection: new developments in epidemiology and pathogenesis. Nature Rev. Microbiol. 7, 526–536 (2009)

  4. 4.

    et al. Duodenal infusion of donor feces for recurrent Clostridium difficile. N. Engl. J. Med. 368, 407–415 (2013)

  5. 5.

    et al. Insights into secondary metabolism from a global analysis of prokaryotic biosynthetic gene clusters. Cell 158, 412–421 (2014)

  6. 6.

    et al. Decreased diversity of the fecal microbiome in recurrent Clostridium difficile-associated diarrhea. J. Infect. Dis. 197, 435–438 (2008)

  7. 7.

    & UniFrac: a new phylogenetic method for comparing microbial communities. Appl. Environ. Microbiol. 71, 8228–8235 (2005)

  8. 8.

    et al. Intestinal domination and the risk of bacteremia in patients undergoing allogeneic hematopoietic stem cell transplantation. Clin. Infect. Dis. 55, 905–914 (2012)

  9. 9.

    et al. Early Clostridium difficile infection during allogeneic hematopoietic stem cell transplantation. PLoS ONE 9, e90158 (2014)

  10. 10.

    et al. Ecological modeling from time-series inference: insight into dynamics and stability of intestinal microbiota. PLOS Comput. Biol. 9, e1003388 (2013)

  11. 11.

    Efficiency of various bile salt preparations for stimulation of Clostridium difficile spore germination. J. Clin. Microbiol. 18, 1017–1019 (1983)

  12. 12.

    & Bile salts and glycine as cogerminants for Clostridium difficile spores. J. Bacteriol. 190, 2505–2512 (2008)

  13. 13.

    , , , & Clostridium scindens baiCD and baiH genes encode stereo-specific 7α/7β-hydroxy-3-oxo-Δ4-cholenoic acid oxidoreductases. Biochim. Biophys. Acta 1781, 16–25 (2008)

  14. 14.

    , & Bile salt biotransformations by human intestinal bacteria. J. Lipid Res. 47, 241–259 (2006)

  15. 15.

    et al. Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nature Biotechnol. 31, 814–821 (2013)

  16. 16.

    , & Bile acid sequestrants: more than simple resins. Curr. Opin. Lipidol. 23, 43–55 (2012)

  17. 17.

    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)

  18. 18.

    & A genomic update on clostridial phylogeny: Gram-negative spore formers and other misplaced clostridia. Environ. Microbiol. 15, 2631–2641 (2013)

  19. 19.

    , , & Assignment of Eubacterium sp. VPI 12708 and related strains with high bile acid 7α-dehydroxylating activity to Clostridium scindens and proposal of Clostridium hylemonae sp. nov., isolated from human faeces. Int. J. Syst. Evol. Microbiol. 50, 971–978 (2000)

  20. 20.

    & Identification and characterization of a bile acid 7α-dehydroxylation operon in Clostridium sp. strain TO-931, a highly active 7α-dehydroxylating strain isolated from human feces. Appl. Environ. Microbiol. 66, 1107–1113 (2000)

  21. 21.

    et al. Microbiota transplantation restores normal fecal bile acid composition in recurrent Clostridium difficile infection. Am. J. Physiol. Gastrointest. Liver Physiol. 306, G310–G319 (2014)

  22. 22.

    , , , & Bile acids as carcinogens in human gastrointestinal cancers. Mutat. Res. 589, 47–65 (2005)

  23. 23.

    et al. Microbiota-liberated host sugars facilitate post-antibiotic expansion of enteric pathogens. Nature 502, 96–99 (2013)

  24. 24.

    , , , & Critical role for MyD88-mediated neutrophil recruitment during Clostridium difficile colitis. Infect. Immun. 80, 2989–2996 (2012)

  25. 25.

    , , & Toll-like receptor 5 stimulation protects mice from acute Clostridium difficile colitis. Infect. Immun. 79, 1498–1503 (2011)

  26. 26.

    et al. Thuricin CD, a posttranslationally modified bacteriocin with a narrow spectrum of activity against Clostridium difficile. Proc. Natl Acad. Sci. USA 107, 9352–9357 (2010)

  27. 27.

    et al. A mouse model of Clostridium difficile-associated disease. Gastroenterology 135, 1984–1992 (2008)

  28. 28.

    , , & Metabolism of bile salts in mice influences spore germination in Clostridium difficile. PLoS ONE 5, e8740 (2010)

  29. 29.

    et al. Vancomycin-resistant Enterococcus domination of intestinal microbiota is enabled by antibiotic treatment in mice and precedes bloodstream invasion in humans. J. Clin. Invest. 120, 4332–4341 (2010)

  30. 30.

    , , , & Development and application of a polymerase chain reaction assay for the detection and enumeration of bile acid 7α-dehydroxylating bacteria in human feces. Clin. Chim. Acta 331, 127–134 (2003)

  31. 31.

    et al. Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J. 6, 1621–1624 (2012)

  32. 32.

    et al. Intestinal microbiota containing Barnesiella cures vancomycin-resistant Enterococcus faecium colonization. Infect. Immun. 81, 965–973 (2013)

  33. 33.

    et al. Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl. Environ. Microbiol. 75, 7537–7541 (2009)

  34. 34.

    , , , & UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27, 2194–2200 (2011)

  35. 35.

    , & Clearcut: a fast implementation of relaxed neighbor joining. Bioinformatics 22, 2823–2824 (2006)

  36. 36.

    et al. QIIME allows analysis of high-throughput community sequencing data. Nature Methods 7, 335–336 (2010)

  37. 37.

    Building phylogenetic trees from molecular data with MEGA. Mol. Biol. Evol. 30, 1229–1235 (2013)

  38. 38.

    Human Microbiome Project Consortium Structure. Function and diversity of the healthy human microbiome. Nature 486, 207–214 (2012)

  39. 39.

    , & RAPSearch2: a fast and memory-efficient protein similarity search tool for next-generation sequencing data. Bioinformatics 28, 125–126 (2012)

  40. 40.

    Statistical Power Analysis for the Behavioral Sciences (Routledge, 1988)

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Acknowledgements

E.G.P. received funding from US National Institutes of Health (NIH) grants RO1 AI42135 and AI95706, and from the Tow Foundation. J.B.X. received funding from the NIH Office of the Director (DP2OD008440), NCI (U54 CA148967), and from a seed grant from the Lucille Castori Center for Microbes, Inflammation, and Cancer. C.G.B. was supported by a Medical Scientist Training Program grant from the National Institute of General Medical Sciences of the NIH (award number T32GM07739, awarded to the Weill Cornell/Rockefeller/Sloan-Kettering Tri-Institutional MD-PhD Program).

Author information

Affiliations

  1. Infectious Diseases Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York 10065, USA

    • Charlie G. Buffie
    • , Peter T. McKenney
    • , Melissa Kinnebrew
    • , Ying Taur
    •  & Eric G. Pamer
  2. Lucille Castori Center for Microbes, Inflammation and Cancer, Memorial Sloan Kettering Cancer Center, New York, New York 10065, USA

    • Charlie G. Buffie
    • , Peter T. McKenney
    • , Lilan Ling
    • , Asia Gobourne
    • , Daniel No
    • , Melissa Kinnebrew
    • , Eric Littmann
    • , Ying Taur
    • , Nora C. Toussaint
    • , Joao B. Xavier
    •  & Eric G. Pamer
  3. Computational Biology Program, Sloan-Kettering Institute, New York, New York 10065, USA

    • Vanni Bucci
    • , Richard R. Stein
    • , Chris Sander
    • , Nora C. Toussaint
    •  & Joao B. Xavier
  4. Department of Biology, University of Massachusetts Dartmouth, North Dartmouth, Massachusetts 02747, USA

    • Vanni Bucci
  5. Donald B. and Catherine C. Marron Cancer Metabolism Center, Sloan-Kettering Institute, New York, New York 10065, USA

    • Hui Liu
    •  & Justin R. Cross
  6. Genomics Core Laboratory, Sloan-Kettering Institute, New York, New York 10065, USA

    • Agnes Viale
  7. Bone Marrow Transplant Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York 10065, USA

    • Marcel R. M. van den Brink
    •  & Robert R. Jenq
  8. Immunology Program, Sloan-Kettering Institute, New York, New York 10065, USA

    • Marcel R. M. van den Brink
    •  & Eric G. Pamer

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Contributions

C.G.B. and E.G.P. designed the experiments and wrote the manuscript with input from co-authors. C.G.B. performed animal experiments and most analyses. V.B., R.R.S., J.B.X., C.S. and C.G.B. performed microbiota time-series inference modelling and analysis. P.T.M. and C.G.B designed and performed ex vivo experiments. L.L., A.G., A.V. D.N. and M.K. performed 16S amplicon quantification and multiparallel sequencing (454, MiSeq) and contributed to data analysis. M.R.M.v.d.B., R.R.J., Y.T., E.L., C.G.B. and E.G.P. assessed clinical parameters and supervised patient cohort analysis. N.C.T. and C.G.B. performed metagenomic shotgun sequencing analysis. J.R.C. and H.L. developed the metabolomics analysis platform and performed quantification of bile acid species.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Eric G. Pamer.

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DOI

https://doi.org/10.1038/nature13828

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