Abstract
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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Change history
17 January 2018
Please see accompanying Erratum (http://doi.org/10.1038/nature25471). In Fig. 2c, the labels for the green, blue and red lines were corrected from: ‘MMb’, ‘MMbHMb−1d’ and ‘MMbHMb−3d’ to ‘HMb’, ‘HMbMMb−1d’ and ‘HMbMMb−3d’, respectively.
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Acknowledgements
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.).
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N.K.S. conceived the study, designed and performed experiments, and analysed all data. D.L.K. supervised all aspects of the project. N.K.S. and D.L.K. wrote the paper.
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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.
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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.
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Extended data figures and tables
Extended Data Figure 1 Individual MWAS reveal a large number of differentially abundant taxa.
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.
Extended Data Figure 4 MMb mice given MMb cx and MMb mice given HMb cx have distinct microbiotas.
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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DOI: https://doi.org/10.1038/nature25019
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