Automated design of synthetic microbial communities

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.在天然存在的微生物系统中，物种极少单独存活。已有充分的生态学证据表明，物种多样性与群落功能产出之间存在正相关关系。这类群落在自然界中的广泛分布提示，工程菌株以共培养形式存在或许也具备相应优势。构建合成微生物群落，可使我们搭建分布式系统，从而缓解单一菌株工程化中常出现的问题，尤其是在功能复杂度不断提升的场景下。本研究展示了一种设计稳健合成群落的方法，该方法利用群体感应（quorum sensing）来调控恒化器环境中的偏害型细菌素相互作用。我们针对双菌株和三菌株系统探索了模型空间，采用贝叶斯方法开展模型选择，并筛选出可形成稳定稳态群落的最优候选群落。本研究结果揭示了赋予群落稳定性的关键相互作用基序，并明确了筛选遗传元件以及调控群落组成的相关要求。