In naturally occurring microbial systems, species rarely exist in isolation. There is strong ecological evidence for a positive relationship between species diversity and the functional output of communities. The pervasiveness of these communities in nature highlights that there may be advantages for engineered strains to exist in cocultures as well. Building synthetic microbial communities allows us to create distributed systems that mitigates issues often found in engineering a monoculture, especially when functional complexity is increasing. Here, we demonstrate a methodology for designing robust synthetic communities that use quorum sensing to control amensal bacteriocin interactions in a chemostat environment. We explore model spaces for two and three strain systems, using Bayesian methods to perform model selection, and identify the most robust candidates for producing stable steady state communities. Our findings highlight important interaction motifs that provide stability, and identify requirements for selecting genetic parts and tuning the community composition.

中文翻译：

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合成微生物群落的自动化设计

在自然发生的微生物系统中，物种很少单独存在。有强有力的生态学证据表明物种多样性与社区功能输出之间存在正相关关系。这些社区在自然界中的普遍性表明，在共同培养中也存在工程菌株的优势。建立合成微生物群落使我们能够创建分布式系统，以减轻在设计单一栽培时经常遇到的问题，尤其是在功能复杂性不断提高的情况下。在这里，我们演示了一种用于设计强大的合成社区的方法，该群体使用群体感应来控制恒化细菌环境中的闭经细菌素相互作用。我们使用贝叶斯方法探索两个和三个应变系统的模型空间，以进行模型选择，并确定产生稳定的稳态社区的最有力的候选人。我们的发现突出了重要的相互作用基序，这些基序提供了稳定性，并确定了选择遗传部分和调整群落组成的要求。