Multicellular Feedback Control Strategies in Synthetic Microbial Consortia: From Embedded to Distributed Control

TL;DR

This paper reviews recent advances in multicellular feedback control in synthetic microbial consortia, emphasizing distributed control strategies, theoretical frameworks, experimental demonstrations, and future challenges for real-world applications.

Contribution

It provides a comprehensive survey of control architectures, modeling approaches, and experimental implementations of multicellular feedback systems in synthetic biology.

Findings

Distributed control reduces metabolic burden.

Enhances robustness to environmental uncertainty.

Enables modular and scalable control architectures.

Abstract

Living organisms rely on endogenous feedback mechanisms to maintain homeostasis in the presence of uncertainty and environmental fluctuations. An emerging challenge at the interface of control systems engineering and synthetic biology is the design of reliable feedback strategies to regulate cellular behavior and collective biological functions. In this article, we review recent advances in multicellular feedback control, where sensing, computation, and actuation are distributed across different cell populations within synthetic microbial consortia, giving rise to biological multiagent control systems governed by molecular communication. From a control-theoretic perspective, these consortia can be interpreted as distributed biomolecular control systems, where coordination among populations replace embedded regulation. We survey theoretical frameworks, control architectures, and modeling approaches, ranging from aggregate population-level dynamics to spatially aware agent-based simulations, and discuss experimental demonstrations in engineered \textit{Escherichia coli} consortia. We highlight how distributing control functions across populations can reduce metabolic burden, mitigate retroactivity, improve robustness to uncertainty, and enable modular reuse of control components. Beyond regulation of gene expression, we discuss the emerging problem of population composition control, where coordination among growing and competing cell populations becomes an integral part of the control objective. Finally, we outline key open challenges that must be addressed before multicellular control strategies can be deployed in real-world applications such as biomanufacturing, environmental remediation, and therapeutic systems. These challenges span modeling and simulation, experimental platform development, coordination and composition control, and long-term evolutionary stability.