Microbiome-wide association studies have established that numerous diseases are associated with changes in the microbiota1,2. These studies typically generate a long list of commensals implicated as biomarkers of disease, with no clear relevance to disease pathogenesis1,2,3,4,5. If the field is to move beyond correlations and begin to address causation, an effective system is needed for refining this catalogue of differentially abundant microbes and to allow subsequent mechanistic studies1,4. Here we demonstrate that triangulation of microbe–phenotype relationships is an effective method for reducing the noise inherent in microbiota studies and enabling identification of causal microbes. We found that gnotobiotic mice harbouring different microbial communities exhibited differential survival in a colitis model. Co-housing of these mice generated animals that had hybrid microbiotas and displayed intermediate susceptibility to colitis. Mapping of microbe–phenotype relationships in parental mouse strains and in mice with hybrid microbiotas identified the bacterial family Lachnospiraceae as a correlate for protection from disease. Using directed microbial culture techniques, we discovered Clostridium immunis, a previously unknown bacterial species from this family, that—when administered to colitis-prone mice—protected them against colitis-associated death. To demonstrate the generalizability of our approach, we used it to identify several commensal organisms that induce intestinal expression of an antimicrobial peptide. Thus, we have used microbe–phenotype triangulation to move beyond the standard correlative microbiome study and identify causal microbes for two completely distinct phenotypes. Identification of disease-modulating commensals by microbe–phenotype triangulation may be more broadly applicable to human microbiome studies.
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Lynch, S. V. & Pedersen, O. The human intestinal microbiome in health and disease. N. Engl. J. Med. 375, 2369–2379 (2016)
Surana, N. K. & Kasper, D. L. Deciphering the tête-à-tête between the microbiota and the immune system. J. Clin. Invest. 124, 4197–4203 (2014)
Sze, M. A. & Schloss, P. D. Looking for a signal in the noise: revisiting obesity and the microbiome. MBio 7, e01018–16 (2016)
Gilbert, J. A. et al. Microbiome-wide association studies link dynamic microbial consortia to disease. Nature 535, 94–103 (2016)
Gevers, D. et al. The treatment-naive microbiome in new-onset Crohn’s disease. Cell Host Microbe 15, 382–392 (2014)
Atarashi, K. et al. Treg induction by a rationally selected mixture of Clostridia strains from the human microbiota. Nature 500, 232–236 (2013)
Blanton, L. V. et al. Gut bacteria that prevent growth impairments transmitted by microbiota from malnourished children. Science 351, aad3311 (2016)
Ivanov, I. I. et al. Induction of intestinal Th17 cells by segmented filamentous bacteria. Cell 139, 485–498 (2009)
Kau, A. L. et al. Functional characterization of IgA-targeted bacterial taxa from undernourished Malawian children that produce diet-dependent enteropathy. Sci. Transl. Med. 7, 276ra24 (2015)
Mazmanian, S. K., Round, J. L. & Kasper, D. L. A microbial symbiosis factor prevents intestinal inflammatory disease. Nature 453, 620–625 (2008)
Palm, N. W. et al. Immunoglobulin A coating identifies colitogenic bacteria in inflammatory bowel disease. Cell 158, 1000–1010 (2014)
Chung, H. et al. Gut immune maturation depends on colonization with a host-specific microbiota. Cell 149, 1578–1593 (2012)
Baumgart, M. et al. Culture independent analysis of ileal mucosa reveals a selective increase in invasive Escherichia coli of novel phylogeny relative to depletion of Clostridiales in Crohn’s disease involving the ileum. ISME J. 1, 403–418 (2007)
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)
Kang, S. et al. Dysbiosis of fecal microbiota in Crohn’s disease patients as revealed by a custom phylogenetic microarray. Inflamm. Bowel Dis. 16, 2034–2042 (2010)
Vaishnava, S. et al. The antibacterial lectin RegIIIγ promotes the spatial segregation of microbiota and host in the intestine. Science 334, 255–258 (2011)
Cash, H. L., Whitham, C. V., Behrendt, C. L. & Hooper, L. V. Symbiotic bacteria direct expression of an intestinal bactericidal lectin. Science 313, 1126–1130 (2006)
Geva-Zatorsky, N. et al. Mining the human gut microbiota for immunomodulatory organisms. Cell 168, 928–943 (2017)
Falkow, S. Molecular Koch’s postulates applied to microbial pathogenicity. Rev. Infect. Dis. 10 (Suppl. 2), S274–S276 (1988)
Fredricks, D. N. & Relman, D. A. Sequence-based identification of microbial pathogens: a reconsideration of Koch’s postulates. Clin. Microbiol. Rev. 9, 18–33 (1996)
Koch, R. Untersuchungen über Bakterien: V. Die Ätiologie der Milzbrand-Krankheit, begründet auf die Entwicklungsgeschicte des Bacillus anthracis. Cohns Beitr. Biol. Pflanz. 2, 277–310 (1876)
Wirtz, S., Neufert, C., Weigmann, B. & Neurath, M. F. Chemically induced mouse models of intestinal inflammation. Nat. Protocols 2, 541–546 (2007)
Caporaso, J. G. et al. Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J. 6, 1621–1624 (2012)
Caporaso, J. G. et al. QIIME allows analysis of high-throughput community sequencing data. Nat. Methods 7, 335–336 (2010)
McDonald, D. et al. An improved Greengenes taxonomy with explicit ranks for ecological and evolutionary analyses of bacteria and archaea. ISME J. 6, 610–618 (2012)
Vázquez-Baeza, Y., Pirrung, M., Gonzalez, A. & Knight, R. EMPeror: a tool for visualizing high-throughput microbial community data. Gigascience 2, 16 (2013)
Segata, N. et al. Metagenomic biomarker discovery and explanation. Genome Biol. 12, R60 (2011)
Kaneuchi, C., Watanabe, K., Terada, A., Benno, Y. & Mitsuoka, T. Taxonomic study of Bacteroides clostridiiformis subsp. clostridiiformis (Burri and Ankersmit) Holdeman and Moore and of related organisms: proposal of Clostridium clostridiiformis (Burri and Ankersmit) comb. nov. and Clostridium symbiosum (Stevens) comb. nov. Int. J. Syst. Evol. Microbiol. 26, 195–204 (1976)
Zankari, E. et al. Identification of acquired antimicrobial resistance genes. J. Antimicrob. Chemother. 67, 2640–2644 (2012)
Joensen, K. G. et al. Real-time whole-genome sequencing for routine typing, surveillance, and outbreak detection of verotoxigenic Escherichia coli. J. Clin. Microbiol. 52, 1501–1510 (2014)
Cosentino, S., Voldby Larsen, M., Møller Aarestrup, F. & Lund, O. PathogenFinder—distinguishing friend from foe using bacterial whole genome sequence data. PLoS ONE 8, e77302 (2013)
We thank C. Couter for technical assistance; S. Edwards, J. Ramos, and T. Sherpa for assistance with gnotobiotic mice; R. Bronson for review of histology; J. McCoy for editorial assistance; and members of the Kasper laboratory for discussions. Support for this work was provided by a Career Development Award from Boston Children’s Hospital (N.K.S.) and National Institutes of Health grants K08 AI108690 (N.K.S.) and U19 AI109764 (N.K.S. and D.L.K.).
N.K.S. and D.L.K. are inventors on patent application numbers 17/38680, 62/581372 and 62/523330 submitted by Harvard University that cover the therapeutic use of C. immunis.
Reviewer Information Nature thanks J. Faith, M. Lathrop, A. Macpherson and the other anonymous reviewer(s) for their contribution to the peer review of this work.
Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data figures and tables
Linear discriminant analysis effect size was used to identify differentially abundant taxa in the faecal microbiota of various mice. Taxa coloured red and green were more abundant in that particular group of mice. Taxa coloured yellow did not statistically differ in abundance between groups. Each ring of the cladogram represents a different taxonomic level, starting with kingdom in the centre and ending with genus in the outer ring. a, Comparison of HMb and MMb. b, Comparison of MMb and SPF. c, Comparison of MMb and MMbHMb-1d. d, Comparison of HMb and HMbMMb-1d. The family Lachnospiraceae is indicated by the symbols c4 (a), a6 (b), a1 (c), and a9 (d).
Extended Data Figure 2 Several taxa that are differentially present in HMb and MMb mice do not augment colitis severity.
a, Survival of MMb mice (n = 2 mice) and MMb mice orally receiving P. clara (n = 4 mice) or B. uniformis (n = 4 mice) and subjected to DSS-induced colitis. b, Survival of HMb mice (n = 2 mice) and HMb mice orally receiving L. reuteri (n = 4), R. gnavus (n = 4 mice), or SFB (n = 4 mice) and subjected to DSS-induced colitis.
Extended Data Figure 3 Culture of MMb faeces on semi-selective medium does not enrich for Lachnospiraceae.
The relative abundance of bacterial families present in MMb faeces before (left) and after (right) culture is shown.
Weighted principal components analysis of the faecal microbiota of MMb mice before and after gavage with MMb cx or HMb cx is shown. The arrow indicates an MMb mouse that received HMb cx but died after being challenged with DSS.
Extended Data Figure 5 The HMb cx bacterial consortium is sufficient to protect mice from colitis-associated death.
The survival of germ-free mice orally receiving HMb cx (n = 10 mice) and subjected to DSS-induced colitis is shown.
Extended Data Figure 6 Several taxa that are present in MMb mice and absent in HMb mice do not induce Reg3γ expression.
qPCR analysis of ileal Reg3γ expression in HMb mice receiving no organisms (n = 4 mice) and in HMb mice receiving orally administered A. stercoricanis (n = 4 mice), M. intestinale (n = 4 mice), or L. vaginalis (n = 4 mice). Reg3γ expression was normalized to germ-free mice (n = 3 mice). Individual (dots) and mean (bars) values are shown.
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Surana, N., Kasper, D. Moving beyond microbiome-wide associations to causal microbe identification. Nature 552, 244–247 (2017). https://doi.org/10.1038/nature25019
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