Department of Biosystems Science and Engineering (D-BSSE), ETH Zürich, Mattenstrasse 26, 4058, Basel, Switzerland.
Nat Commun. 2022 Aug 16;13(1):4808. doi: 10.1038/s41467-022-32392-z.
Communities of microbes play important roles in natural environments and hold great potential for deploying division-of-labor strategies in synthetic biology and bioproduction. However, the difficulty of controlling the composition of microbial consortia over time hinders their optimal use in many applications. Here, we present a fully automated, high-throughput platform that combines real-time measurements and computer-controlled optogenetic modulation of bacterial growth to implement precise and robust compositional control of a two-strain E. coli community. In addition, we develop a general framework for dynamic modeling of synthetic genetic circuits in the physiological context of E. coli and use a host-aware model to determine the optimal control parameters of our closed-loop compositional control system. Our platform succeeds in stabilizing the strain ratio of multiple parallel co-cultures at arbitrary levels and in changing these targets over time, opening the door for the implementation of dynamic compositional programs in synthetic bacterial communities.
微生物群落在自然环境中发挥着重要作用,并且在合成生物学和生物生产中具有很大的潜力来部署分工策略。然而,随着时间的推移控制微生物群落组成的难度阻碍了它们在许多应用中的最佳使用。在这里,我们提出了一个完全自动化、高通量的平台,它结合了实时测量和计算机控制的细菌生长光遗传学调节,以实现对两株大肠杆菌群落的精确和稳健的组成控制。此外,我们开发了一个用于大肠杆菌生理环境下合成遗传电路的动态建模的通用框架,并使用宿主感知模型来确定我们的闭环组成控制系统的最佳控制参数。我们的平台成功地将多个平行共培养物的菌株比例稳定在任意水平,并随时间改变这些目标,为在合成细菌群落中实现动态组成程序打开了大门。