TY - JOUR
T1 - Identifying gut microbe-host phenotype relationships using combinatorial communities in gnotobiotic mice
AU - Faith, Jeremiah J.
AU - Ahern, Philip P.
AU - Ridaura, Vanessa K.
AU - Cheng, Jiye
AU - Gordon, Jeffrey I.
PY - 2014/1/22
Y1 - 2014/1/22
N2 - Identifying a scalable, unbiased method for discovering which members of the human gut microbiota influence specific physiologic, metabolic, and immunologic phenotypes remains a challenge. We describe a method in which a clonally arrayed collection of cultured, sequenced bacteria was generated from one of several human fecal microbiota samples found to transmit a particular phenotype to recipient germ-free mice. Ninety-four bacterial consortia of diverse size, randomly drawn from the culture collection, were introduced into germ-free animals. We identified an unanticipated range of bacterial strains that promoted accumulation of colonic regulatory T cells (Tregs) and expansion of Nrp1lo/- peripheral Tregs, as well as strains that modulated mouse adiposity and cecal metabolite concentrations, using feature selection algorithms and follow-up monocolonizations. This combinatorial approach enables a systems-level understanding of microbial contributions to human biology.
AB - Identifying a scalable, unbiased method for discovering which members of the human gut microbiota influence specific physiologic, metabolic, and immunologic phenotypes remains a challenge. We describe a method in which a clonally arrayed collection of cultured, sequenced bacteria was generated from one of several human fecal microbiota samples found to transmit a particular phenotype to recipient germ-free mice. Ninety-four bacterial consortia of diverse size, randomly drawn from the culture collection, were introduced into germ-free animals. We identified an unanticipated range of bacterial strains that promoted accumulation of colonic regulatory T cells (Tregs) and expansion of Nrp1lo/- peripheral Tregs, as well as strains that modulated mouse adiposity and cecal metabolite concentrations, using feature selection algorithms and follow-up monocolonizations. This combinatorial approach enables a systems-level understanding of microbial contributions to human biology.
UR - http://www.scopus.com/inward/record.url?scp=84893370250&partnerID=8YFLogxK
U2 - 10.1126/scitranslmed.3008051
DO - 10.1126/scitranslmed.3008051
M3 - Article
C2 - 24452263
AN - SCOPUS:84893370250
SN - 1946-6234
VL - 6
JO - Science Translational Medicine
JF - Science Translational Medicine
IS - 220
M1 - 220ra11
ER -