Microbiome-wide association studies have established that numerous diseases are associated with changes in the microbiota. These studies typically generate a long list of commensals implicated as biomarkers of disease, with no clear relevance to disease pathogenesis. 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 studies. 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.

中文翻译：

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超越微生物组范围的关联到因果微生物识别

全微生物组关联研究已经确定，许多疾病都与微生物群的变化有关。这些研究通常会产生一长串作为疾病生物标志物的共生体，与疾病发病机制没有明确的相关性。如果该领域要超越相关性并开始解决因果关系，则需要一个有效的系统来完善这一差异丰富的微生物目录，并允许进行后续的机制研究。在这里，我们证明微生物-表型关系的三角测量是一种有效的方法，可以减少微生物群研究中固有的噪音，并能够识别致病微生物。我们发现具有不同微生物群落的无菌小鼠在结肠炎模型中表现出不同的存活率。这些小鼠的共同饲养产生了具有混合微生物群并表现出对结肠炎的中等易感性的动物。亲本小鼠品系和具有杂交微生物群的小鼠中微生物-表型关系的图谱确定细菌家族毛螺菌科是预防疾病的关联物。使用定向微生物培养技术，我们发现了免疫梭菌（Clostridium immunis），这是一种以前未知的来自该家族的细菌物种，当给予易患结肠炎的小鼠时，可以保护它们免受结肠炎相关的死亡。为了证明我们的方法的普遍性，我们用它来识别几种诱导抗菌肽肠道表达的共生生物。因此，我们使用微生物-表型三角测量超越了标准的相关微生物组研究，并确定了两种完全不同的表型的致病微生物。通过微生物-表型三角测量鉴定调节疾病的共生体可能更广泛地适用于人类微生物组研究。