Moving beyond microbiome-wide associations to causal microbe identification.
Moving beyond microbiome-wide associations to causal microbe identification.
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DOI：
10.1038/nature25019
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发表时间：
2017-12-14
期刊：
影响因子：
64.8
通讯作者：
Kasper DL
中科院分区：
文献类型：
--
作者：
Surana NK;Kasper DL
全微生物组的关联研究已经确定，许多疾病与微生物区系的变化有关。这些研究通常会产生一长串共生现象，作为疾病的生物标记物，与疾病发病机制没有明确的相关性。如果这个领域要超越相关性，开始解决因果关系，就需要一个有效的系统来提炼这种差异丰富的微生物目录，并允许随后的机制研究。在这里，我们证明了微生物-表型关系的三角测量是一种有效的方法，可以减少微生物区系研究中固有的噪音，并能够识别致病微生物。我们发现，在结肠炎模型中，拥有不同微生物群落的诺生菌小鼠表现出不同的存活率。这些小鼠的共居产生了具有混合微生物群并表现出结肠炎中等易感性的动物。在亲代小鼠品系和具有杂交微生物群的小鼠中绘制的微生物-表型关系图确定了细菌科Lachnospiraceae与疾病保护相关。使用定向微生物培养技术，我们发现了免疫梭菌，这是一种以前未知的细菌物种，当给与结肠炎易感小鼠时，它能保护它们免受结肠炎相关死亡的影响。为了证明我们的方法的普适性，我们使用它来鉴定几种诱导抗菌肽在肠道中表达的共生生物。因此，我们使用微生物-表型三角测量法超越了标准的相关微生物组研究，并确定了两种完全不同表型的致病微生物。通过微生物-表型三角法鉴定疾病调节共生体可能更广泛地适用于人类微生物组研究。
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 catalog of differentially abundant microbes and allow for subsequent mechanistic studies. Herein, 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 harboring 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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影响因子：
3.7
作者：
Cosentino S;Voldby Larsen M;Møller Aarestrup F;Lund O
通讯作者：
Lund O
DOI：
10.1038/ismej.2012.8
发表时间：
2012-08
期刊：
The ISME journal
影响因子：
--
作者：
通讯作者：
--
影响因子：
14.8
作者：
Wirtz, Stefan;Neufert, Clemens;Neurath, Markus F.
通讯作者：
Neurath, Markus F.
影响因子：
9.4
作者：
Joensen, Katrine Grimstrup;Scheutz, Flemming;Aarestrup, Frank M.
通讯作者：
Aarestrup, Frank M.
影响因子：
64.5
作者：
Chung H;Pamp SJ;Hill JA;Surana NK;Edelman SM;Troy EB;Reading NC;Villablanca EJ;Wang S;Mora JR;Umesaki Y;Mathis D;Benoist C;Relman DA;Kasper DL
通讯作者：
Kasper DL