Precision microbiome reconstitution restores bile acid mediated resistance to Clostridium difficile

doi:10.1038/nature13828

. 2015 Jan 8;517(7533):205-8.

doi: 10.1038/nature13828. Epub 2014 Oct 22.

Precision microbiome reconstitution restores bile acid mediated resistance to Clostridium difficile

Charlie G Buffie¹, Vanni Bucci², Richard R Stein³, Peter T McKenney¹, Lilan Ling⁴, Asia Gobourne⁴, Daniel No⁴, Hui Liu⁵, Melissa Kinnebrew¹, Agnes Viale⁶, Eric Littmann⁴, Marcel R M van den Brink⁷, Robert R Jenq⁸, Ying Taur¹, Chris Sander³, Justin R Cross⁵, Nora C Toussaint⁹, Joao B Xavier⁹, Eric G Pamer¹⁰

Affiliations

¹ 1] Infectious Diseases Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York 10065, USA [2] Lucille Castori Center for Microbes, Inflammation and Cancer, Memorial Sloan Kettering Cancer Center, New York, New York 10065, USA.
² 1] Computational Biology Program, Sloan-Kettering Institute, New York, New York 10065, USA [2] Department of Biology, University of Massachusetts Dartmouth, North Dartmouth, Massachusetts 02747, USA.
³ Computational Biology Program, Sloan-Kettering Institute, New York, New York 10065, USA.
⁴ Lucille Castori Center for Microbes, Inflammation and Cancer, Memorial Sloan Kettering Cancer Center, New York, New York 10065, USA.
⁵ Donald B. and Catherine C. Marron Cancer Metabolism Center, Sloan-Kettering Institute, New York, New York 10065, USA.
⁶ Genomics Core Laboratory, Sloan-Kettering Institute, New York, New York 10065, USA.
⁷ 1] Bone Marrow Transplant Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York 10065, USA [2] Immunology Program, Sloan-Kettering Institute, New York, New York 10065, USA.
⁸ Bone Marrow Transplant Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York 10065, USA.
⁹ 1] Lucille Castori Center for Microbes, Inflammation and Cancer, Memorial Sloan Kettering Cancer Center, New York, New York 10065, USA [2] Computational Biology Program, Sloan-Kettering Institute, New York, New York 10065, USA.
¹⁰ 1] Infectious Diseases Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York 10065, USA [2] Lucille Castori Center for Microbes, Inflammation and Cancer, Memorial Sloan Kettering Cancer Center, New York, New York 10065, USA [3] Immunology Program, Sloan-Kettering Institute, New York, New York 10065, USA.

PMID: 25337874
PMCID: PMC4354891
DOI: 10.1038/nature13828

Precision microbiome reconstitution restores bile acid mediated resistance to Clostridium difficile

Charlie G Buffie et al. Nature. 2015.

. 2015 Jan 8;517(7533):205-8.

doi: 10.1038/nature13828. Epub 2014 Oct 22.

Authors

Affiliations

¹ 1] Infectious Diseases Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York 10065, USA [2] Lucille Castori Center for Microbes, Inflammation and Cancer, Memorial Sloan Kettering Cancer Center, New York, New York 10065, USA.
² 1] Computational Biology Program, Sloan-Kettering Institute, New York, New York 10065, USA [2] Department of Biology, University of Massachusetts Dartmouth, North Dartmouth, Massachusetts 02747, USA.
³ Computational Biology Program, Sloan-Kettering Institute, New York, New York 10065, USA.
⁴ Lucille Castori Center for Microbes, Inflammation and Cancer, Memorial Sloan Kettering Cancer Center, New York, New York 10065, USA.
⁵ Donald B. and Catherine C. Marron Cancer Metabolism Center, Sloan-Kettering Institute, New York, New York 10065, USA.
⁶ Genomics Core Laboratory, Sloan-Kettering Institute, New York, New York 10065, USA.
⁷ 1] Bone Marrow Transplant Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York 10065, USA [2] Immunology Program, Sloan-Kettering Institute, New York, New York 10065, USA.
⁸ Bone Marrow Transplant Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York 10065, USA.
⁹ 1] Lucille Castori Center for Microbes, Inflammation and Cancer, Memorial Sloan Kettering Cancer Center, New York, New York 10065, USA [2] Computational Biology Program, Sloan-Kettering Institute, New York, New York 10065, USA.
¹⁰ 1] Infectious Diseases Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York 10065, USA [2] Lucille Castori Center for Microbes, Inflammation and Cancer, Memorial Sloan Kettering Cancer Center, New York, New York 10065, USA [3] Immunology Program, Sloan-Kettering Institute, New York, New York 10065, USA.

PMID: 25337874
PMCID: PMC4354891
DOI: 10.1038/nature13828

Abstract

The gastrointestinal tracts of mammals are colonized by hundreds of microbial species that contribute to health, including colonization resistance against intestinal pathogens. Many antibiotics destroy intestinal microbial communities and increase susceptibility to intestinal pathogens. Among these, Clostridium difficile, a major cause of antibiotic-induced diarrhoea, greatly increases morbidity and mortality in hospitalized patients. 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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Figures

**Extended Data Figure 1. Dynamics of intestinal microbiota structure and *C. difficile* susceptibility following antibiotic exposure**
Strategy for determining *C. difficile* susceptibility duration post-antibiotic exposure (n=3 separately-housed mouse colonies per antibiotic arm) and relating infection resistance to microbiota structure (a). Intestinal bacterial density of animals before and after antibiotic exposure (b). Results were representative of two independent experiments. Center values (mean), error bars (s.e.m.) (b). Relative abundance of bacterial OTUs (≥97% sequence identity, >0.01% relative abundance) sorted by class (red) and corresponding *C. difficile* susceptibility (blue) among antibiotic-exposed mice (n=68) allowed to recover for variable time intervals prior to *C. difficile* infection challenge (c). Results were representative of two independent experiments. ND (not detectable).

**Extended Data Figure 2. Allo-HSCT patient timelines and *C. difficile* infection status transitions**
Transitions between *C. difficile* (*tcdB*-positive) colonization status in patients receiving allogeneic hematopoietic stem cell transplantation, as measured by *C. difficile* 16S rRNA abundance during the period of hospitalization (light gray bars). Timepoints when *C. difficile* colonization was determined to be positive (red diamonds) and negative (blue diamonds), and when *C. difficile* infection was clinically diagnosed (black dots) and metronidazole was administered (dark gray bars), are displayed relative to the time of transplant per patient.

Extended Data Figure 3. Identification of bacteria conserved across human and murine intestinal microbiota predicted to inhibit *C. difficile*
Identification of bacterial OTUs abundant in mice (n=68) and humans (n=24) (a) that account for a minority of OTU membership (b) but the majority of the structure of the intestinal microbiota of both host species following antibiotic exposure (b). Subnetworks of abundant OTUs predicted inhibit (blue) or positively associate with (red) *C. difficile* in murine (c) and human (d) intestinal microbiota.

**Extended Data Figure 4. Phylogenetic distribution of resistance-associated intestinal bacteria and isolates selected for adoptive transfer**
The maximum likelihood phylogenetic tree (Kimura model, bootstrap of 100 replicates) was constructed using the MEGA 6.06 package from representative sequences of intestinal bacteria associated with resistance to *C. difficile* infection (blue), including cultured representatives subsequently used in adoptive transfer experiments (bold). The tree was rooted using intestinal bacteria associated with susceptibility to infection (red) as an out-group.

Extended Data Figure 5. Adoptive transfer and engraftment of four-bacteria consortium or *C. scindens* ameliorates intestinal *C. difficile* cytotoxin load and acute *C. difficile*-associated weight loss
*C. difficile* toxin load in antibiotic-exposed animals receiving adoptive transfers 24 hours after *C. difficile* infection challenge (a). Animals weights 48 hours after infection challenge (b) and *C. difficile* CFU 24 hours after infection challenge (c). Engraftment of bacterial isolates in the intestinal microbiota of antibiotic-exposed animals two days following adoptive transfer of *B. intestihominis*, *P. capillosus*, *B. hansenii*, and/or *C. scindens* (d). Intestinal bacterial density (feces) from antibiotic-exposed mice administered suspensions containing 4 bacteria, *C. scindens*, or vehicle (PBS) as measured by quantitative RT-PCR of 16S rRNA genes (e). ****P<0.0001, ***P<0.001, **P<0.01, *P<0.05; Mann-Whitney (two-tailed) (a,**b,d,e**), Kruskal-Wallis with Dunn correction (c) (n=6–10 per group). Center values (mean), error bars (s.e.m.). Results were representative of at least two independent experiments. Numbers under group columns in (a) denote the number of mice with detectable engraftment of the given bacterium (out of 10 possible separately-housed animals per group) (d).

**Extended Data Figure 6. Adoptive transfer of consortia or *C. scindens* restores *baiCD* and secondary bile acid biosynthesis gene family abundance**
PCR-based detection of the 7α-HSDH-encoding *baiCD* gene in bacterial isolates, intestinal microbiomes (feces) of animals prior to antibiotic exposure, and intestinal microbiomes (feces) of animals that, following antibiotic exposure, remained *C. difficile*-susceptible or recovered resistance to infection spontaneously or following adoptive transfer of bacterial isolates (a). Reconstituted abundance of the secondary bile acid biosynthesis gene family, as predicted by PICRUSt, in antibiotic-exposed animals receiving adoptive transfers (n=10 per group) (b). ***P<0.001, *P<0.05, ns (not significant); Mann-Whitney (two-tailed) (b). Center values (mean), error bars (s.e.m.).

**Extended Data Figure 7. Impacts of bacteria adoptive transfers on intestinal abundance of bile acids**
Intestinal abundance of the secondary bile acids lithochoate (LCA) (a), ursodeoxycholate (UDCA) (b), and primary bile acids (**c-f**) in mice following antibiotic exposure and adoptive transfer of bacteria indicated. ****P<0.0001, *P<0.05, ns (not significant), Kruskal-Wallis test with Dunn’s correction. Center values (mean), error bars (s.e.m.).

**Extended Data Figure 8. *C. difficile* growth inhibition by secondary bile acids and intestinal content from antibiotic-naive animals**
Addition of the secondary bile acids deoxycholate (DCA) (a) or lithochoate (LCA) (b) to culture media inhibits *C. difficile*. Bile acid-dependent inhibition of *C. difficile* enumerated by recovery of CFU after inoculation of vegetative *C. difficile* into cell-free (c) or whole (d) intestinal content harvested from C57BL/6J mice (n=5–6 per group), with or without pre-incubation with cholestyramine. **P<0.01, Mann-Whitney (two-tailed) (c,d).

**Figure 1. Different antibiotics induce distinct changes to *C. difficile* infection resistance and intestinal microbiota composition**
Susceptibility to *C. difficile* infection following clindamycin (a), ampicillin (b), or enrofloxacin (c). Correlation of *C. difficile* CFU and toxin in cecal content following infection (d). Intestinal microbiota composition at timepoints indicated (e,f,g). Each stacked bar represents the mean microbiota composition of three separately-housed animals. ****P<0.0001. Center values (mean), error bars (s.e.m.) (a, b, c).

**Figure 2. Native intestinal bacterial species conserved across murine and human microbiota are predicted to inhibit *C. difficile* infection**
Intestinal microbiota alpha diversity (a) and Beta diversity (weighted UniFrac distances) (b) of antibiotic-naïve (n=15) and antibiotic-exposed animals susceptible (n=21) or resistant (n=47) to *C. difficile* infection. Correlation of individual bacterial OTUs with susceptibility to *C. difficile* infection (c). Colonization (*C. difficile*-negative to -positive) and clearance (*C. difficile*-positive to –negative) events among *C. difficile*-diagnosed and carrier patients included in microbiota time-series inference modeling (d). Bacterial species with strong *C. difficile* interactions in human and murine microbiota models (e) that exist in a conserved subnetwork predicted to inhibit (blue) or positively associate (red) with *C. difficile* (f). ***P<0.001. In (c), P<0.0005 (“any biodiversity”, n=68) or P<0.05 (“Low biodiversity”, Shannon≤1 (n=16 animals). Center values (mean), error bars (s.e.m.).

**Figure 3. Adoptive transfer of resistance-associated intestinal bacteria following antibiotic exposure increases resistance to *C. difficile* infection**
Intestinal burden of *C. difficile* CFU (a) and toxin (b) 24 hours after *C. difficile* infection of antibiotic-exposed animals receiving adoptive transfers. Weight loss (c) and mortality (d) of animals post-infection. Correlation of adoptively-transferred bacteria engraftment with *C. difficile* susceptibility, (e) and microbiota biodiversity (f) pre-infection. ****P<0.0001, **P<0.01, *P<0.05, ns (not significant). Mean (f)), error bars (range (a), s.e.m. (f)).

**Figure 4. *C. scindens*-mediated *C. difficile* inhibition is associated with secondary bile acid synthesis and dependent on bile endogenous to intestinal content**
Relative abundance of secondary bile species (a) and biosynthesis gene abundance predicted by PICRUSt (b) in intestinal content from antibiotic-exposed *C. difficile* susceptible (n=21), resistant (n=47), and pre-antibiotic (n=15) animals. Correlation of *C. difficile* susceptibility with secondary bile acid biosynthesis gene family abundance in intestinal content (n=6) quantified using shotgun sequencing (c). Intestinal abundance of deoxycholic acid (DCA) following adoptive transfer of bacteria (n=10 per group) (d). Correlation of *C. scindens* engraftment with DCA abundance and *baiCD* status in intestinal content of antibiotic-exposed, adoptively transferred animals (n=30) (e). Bile acid-dependent *C. scindens*-mediated inhibition of *C. difficile* quantified *ex vivo* (n=6 per group) (f). ****P<0.0001, ***P<0.001, **P<0.01, *P<0.05. Gylceroltransferase F51, endogenous reference gene (c). Shaded region around mean ‘pre-antibiotic (abx)’ DCA abundance (s.d.) (e).

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Comment in

Infection: microbiota reconstitution for resistance to Clostridium difficile infection--fight fire with fire?
Ray K. Ray K. Nat Rev Gastroenterol Hepatol. 2015 Jan;12(1):4. doi: 10.1038/nrgastro.2014.194. Epub 2014 Nov 11. Nat Rev Gastroenterol Hepatol. 2015. PMID: 25385229 No abstract available.
Microbial bile acid metabolic clusters: the bouncers at the bar.
Sorg JA. Sorg JA. Cell Host Microbe. 2014 Nov 12;16(5):551-2. doi: 10.1016/j.chom.2014.10.015. Epub 2014 Nov 12. Cell Host Microbe. 2014. PMID: 25525784 Free PMC article.
Dysfunctional families: Clostridium scindens and secondary bile acids inhibit the growth of Clostridium difficile.
Greathouse KL, Harris CC, Bultman SJ. Greathouse KL, et al. Cell Metab. 2015 Jan 6;21(1):9-10. doi: 10.1016/j.cmet.2014.12.016. Cell Metab. 2015. PMID: 25565200 Free PMC article.
Systematic discovery of probiotics.
Forster SC, Lawley TD. Forster SC, et al. Nat Biotechnol. 2015 Jan;33(1):47-9. doi: 10.1038/nbt.3111. Nat Biotechnol. 2015. PMID: 25574637 No abstract available.

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References

1. Buffie CG, Pamer EG. Microbiota-mediated colonization resistance against intestinal pathogens. Nat Rev Immunol. 2013;13:790–801. - PMC - PubMed
1. Buffie CG, Jarchum I, Equinda M, Lipuma L, et al. Profound alterations of intestinal microbiota following a single dose of clindamycin results in sustained susceptibility to Clostridium difficile-induced colitis. Infect Immun. 2012;80:62–73. - PMC - PubMed
1. Rupnik M, Wilcox MH, Gerding DN. Clostridium difficile infection: new developments in epidemiology and pathogenesis. Nat Rev Microbiol. 2009;7:526–536. - PubMed
1. van Nood E, Vrieze A, Nieuwdorp M, Fuentes S, et al. Duodenal infusion of donor feces for recurrent Clostridium difficile. N Engl J Med. 2013;368:407–415. - PubMed
1. Cimermancic P, Medema MH, Claesen J, Kurita K, et al. Insights into secondary metabolism from a global analysis of prokaryotic biosynthetic gene clusters. Cell. 2014;158:412–421. - PMC - PubMed

Supplementary references (Methods)

1. Chen X, Katchar K, Goldsmith JD, Nanthakumar N, et al. A mouse model of Clostridium difficile-associated disease. Gastroenterology. 2008;135:1984–1992. - PubMed
1. Giel JL, Sorg JA, Sonenshein AL, Zhu J. Metabolism of bile salts in mice influences spore germination in Clostridium difficile. PLoS One. 2010;5:e8740. - PMC - PubMed
1. Ubeda C, Taur Y, Jenq RR, Equinda MJ, 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. 2010;120:4332–4341. - PMC - PubMed
1. Wells JE, Williams KB, Whitehead TR, Heuman DM, Hylemon PB. Development and application of a polymerase chain reaction assay for the detection and enumeration of bile acid 7α-dehydroxylating bacteria in human feces. Clinica Chimica Acta. 2003;331:127–134. - PubMed
1. Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, et al. Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J. 2012;6:1621–1624. - PMC - PubMed

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[1] Buffie CG, Pamer EG. Microbiota-mediated colonization resistance against intestinal pathogens. Nat Rev Immunol. 2013;13:790–801. - PMC - PubMed

[2] Buffie CG, Pamer EG. Microbiota-mediated colonization resistance against intestinal pathogens. Nat Rev Immunol. 2013;13:790–801. - PMC - PubMed

[3] Buffie CG, Jarchum I, Equinda M, Lipuma L, et al. Profound alterations of intestinal microbiota following a single dose of clindamycin results in sustained susceptibility to Clostridium difficile-induced colitis. Infect Immun. 2012;80:62–73. - PMC - PubMed

[4] Buffie CG, Jarchum I, Equinda M, Lipuma L, et al. Profound alterations of intestinal microbiota following a single dose of clindamycin results in sustained susceptibility to Clostridium difficile-induced colitis. Infect Immun. 2012;80:62–73. - PMC - PubMed

[5] Rupnik M, Wilcox MH, Gerding DN. Clostridium difficile infection: new developments in epidemiology and pathogenesis. Nat Rev Microbiol. 2009;7:526–536. - PubMed

[6] Rupnik M, Wilcox MH, Gerding DN. Clostridium difficile infection: new developments in epidemiology and pathogenesis. Nat Rev Microbiol. 2009;7:526–536. - PubMed

[7] van Nood E, Vrieze A, Nieuwdorp M, Fuentes S, et al. Duodenal infusion of donor feces for recurrent Clostridium difficile. N Engl J Med. 2013;368:407–415. - PubMed

[8] van Nood E, Vrieze A, Nieuwdorp M, Fuentes S, et al. Duodenal infusion of donor feces for recurrent Clostridium difficile. N Engl J Med. 2013;368:407–415. - PubMed

[9] Cimermancic P, Medema MH, Claesen J, Kurita K, et al. Insights into secondary metabolism from a global analysis of prokaryotic biosynthetic gene clusters. Cell. 2014;158:412–421. - PMC - PubMed

[10] Cimermancic P, Medema MH, Claesen J, Kurita K, et al. Insights into secondary metabolism from a global analysis of prokaryotic biosynthetic gene clusters. Cell. 2014;158:412–421. - PMC - PubMed

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Precision microbiome reconstitution restores bile acid mediated resistance to Clostridium difficile

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Precision microbiome reconstitution restores bile acid mediated resistance to Clostridium difficile

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