A bioreactor-based architecture for in vivo model-based and sim-to-real learning control of microbial consortium composition
Sara Maria Brancato, Davide Salzano, Davide Fiore, Francesco De Lellis, Giovanni Russo, Mario di Bernardo
与生物生产单栽培相比,微生物联合体具有显著的生物技术优势。 然而,由于缺乏可扩展的架构来确保人口之间的稳定共存,工业部署受到阻碍。 现有的策略依赖于基因修饰,这些修饰会强加代谢负荷或环境变化,从而降低产量。 我们提出了一个多功能的控制架构,以调节双应变联体的密度和组成,而无需基因工程或剧烈的环境变化。 我们基于生物反应器的控制架构包括一个混合室,其中两种菌株都是共同培养的,并且有一个储存库,维持生长较慢的菌株。 对于两院,我们开发基于模型和sim-to-real学习控制器。 然后,控制架构在双菌株的大肠杆菌联盟上进行体内验证,实现对联合体密度和成分的精确和稳健调节,包括跟踪时间变化参考和从扰动中恢复。
Microbial consortia offer significant biotechnological advantages over monocultures for bioproduction. However, industrial deployment is hampered by the lack of scalable architectures to ensure stable coexistence between populations. Existing strategies rely on genetic modifications, which impose metabolic load, or environmental changes, which can reduce production. We present a versatile control architecture to regulate density and composition of a two-strain consortium without genetic engineer...