Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO 63108, USA.
Sci Transl Med. 2014 Jan 22;6(220):220ra11. doi: 10.1126/scitranslmed.3008051.
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 (T(regs)) and expansion of Nrp1(lo/-) peripheral T(regs), 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.
确定一种可扩展、无偏倚的方法来发现哪些人类肠道微生物群成员会影响特定的生理、代谢和免疫表型仍然是一个挑战。我们描述了一种方法，该方法从几个被发现可将特定表型传递给受体无菌小鼠的人类粪便微生物群样本之一中，生成了一组经克隆排列的培养、测序细菌。从培养物中随机抽取的 94 种不同大小的细菌联合体被引入无菌动物体内。我们使用特征选择算法和后续的单定植，鉴定出了一系列出乎意料的细菌菌株，这些菌株可促进结肠调节性 T 细胞（Tregs）的积累和 Nrp1（lo/-）外周 Tregs 的扩增，以及调节小鼠肥胖和盲肠代谢物浓度的菌株。这种组合方法能够实现对微生物对人类生物学贡献的系统水平理解。
