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Living organisms employ endogenous negative feedback loops to maintain homeostasis despite environmental fluctuations. A pressing open challenge in Synthetic Biology is to design and implement synthetic circuits to control host cells' behavior, in order to regulate and maintain desired conditions. To cope with the high degree of circuit complexity required to accomplish this task and the intrinsic modularity of classical control schemes, we suggest the implementation of synthetic endogenous feedback loops across more than one cell population. The distribution of the sensing, computation, and actuation functions required to achieve regulation across different cell populations within a consortium allows the genetic engineering in a particular cell to be reduced, increases the robustness, and makes it possible to reuse the synthesized modules for different control applications. Here, we analyze, in-silico, the design of a synthetic feedback controller implemented across two cell populations in a consortium. We study the effects of distributing the various functions required to build a control system across two populations, prove the robustness and modularity of the strategy described, and provide a computational proof-of-concept of its feasibility.

In-Silico Analysis and Implementation of a Multicellular Feedback Control Strategy in a Synthetic Bacterial Consortium