Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.
Howard Hughes Medical Institute, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.
PLoS Biol. 2018 Feb 20;16(2):e2003962. doi: 10.1371/journal.pbio.2003962. eCollection 2018 Feb.
Specific members of complex microbiota can influence host phenotypes, depending on both the abiotic environment and the presence of other microorganisms. Therefore, it is challenging to define bacterial combinations that have predictable host phenotypic outputs. We demonstrate that plant-bacterium binary-association assays inform the design of small synthetic communities with predictable phenotypes in the host. Specifically, we constructed synthetic communities that modified phosphate accumulation in the shoot and induced phosphate starvation-responsive genes in a predictable fashion. We found that bacterial colonization of the plant is not a predictor of the plant phenotypes we analyzed. Finally, we demonstrated that characterizing a subset of all possible bacterial synthetic communities is sufficient to predict the outcome of untested bacterial consortia. Our results demonstrate that it is possible to infer causal relationships between microbiota membership and host phenotypes and to use these inferences to rationally design novel communities.
特定的复杂微生物群落成员可以根据非生物环境和其他微生物的存在来影响宿主表型。因此，定义具有可预测宿主表型输出的细菌组合是具有挑战性的。我们证明植物-细菌二元关联测定可以为具有可预测表型的小型合成群落的设计提供信息。具体来说，我们构建了可以以可预测的方式修饰植物地上部磷积累并诱导磷饥饿响应基因的合成群落。我们发现，细菌对植物的定殖并不是我们分析的植物表型的预测因子。最后，我们证明了对所有可能的细菌合成群落的子集进行特征描述足以预测未经测试的细菌共生体的结果。我们的研究结果表明，推断微生物群成员与宿主表型之间的因果关系是可能的，并且可以利用这些推断来合理地设计新型群落。
