Manipulation of cellular motility using a target signal can facilitate the development of biosensors or microbe-powered biorobots. Here, we engineered signal-dependent motility in Escherichia coli via the transcriptional control of a key motility gene. Without manipulating chemotaxis, signal-dependent switching of motility, either on or off, led to population-level directional movement of cells up or down a signal gradient. We developed a mathematical model that captures the behaviour of the cells, enables identification of key parameters controlling system behaviour, and facilitates predictive-design of motility-based pattern formation. We demonstrated that motility of the receiver strains could be controlled by a sender strain generating a signal gradient. The modular quorum sensing-dependent architecture for interfacing different senders with receivers enabled a broad range of systems-level behaviours. The directional control of motility, especially combined with the potential to incorporate tuneable sensors and more complex sensing-logic, may lead to tools for novel biosensing and targeted-delivery applications.

Summary form only given. Our goal here was to develop an Escherichia coli based sensing and actuation system. Here we divided the genetic circuitry required for actuation and sensing into two strains of E. coli and linked the two strains via a cell-cell communication signal. We targeted a quorum-sensing (QS) signaling molecule to control the motility response of our actuator strain. We demonstrated that the actuator cells showed signaling molecule dependent motility. Further, we developed a mathematical model that describes our engineered actuator system to provide insight into the key parameters controlling behavior of the system. As a model sensing system, we built an isopropyl β-D-1-thiogalactopyranoside (IPTG) sensor in E. coli. The sensor was designed to produce the QS signaling molecule in response to IPTG. We then demonstrated that the actuator cells respond to signaling molecule produced by this sensor strain. The sensing and actuation system engineered here can be used to build synthetic networks where motility is tightly regulated and controlled by cell-cell communication.

Microbial fatty acid-derived fuels have emerged as promising alternatives to petroleum-based transportation fuels. Here we report a modular engineering approach that systematically removed metabolic pathway bottlenecks and led to significant titre improvements in a multi-gene fatty acid metabolic pathway. On the basis of central pathway architecture, E. coli fatty acid biosynthesis was re-cast into three modules: the upstream acetyl coenzyme A formation module; the intermediary acetyl-CoA activation module; and the downstream fatty acid synthase module. Combinatorial optimization of transcriptional levels of these three modules led to the identification of conditions that balance the supply of acetyl-CoA and consumption of malonyl-CoA/ACP. Refining protein translation efficiency by customizing ribosome binding sites for both the upstream acetyl coenzyme A formation and fatty acid synthase modules enabled further production improvement. Fed-batch cultivation of the engineered strain resulted in a final fatty acid production of 8.6 g l−1. The modular engineering strategies demonstrate a generalized approach to engineering cell factories for valuable metabolites production. Microbial fatty acid-derived fuels represent promising alternatives to the traditionally used fossil fuels. Koffas and colleagues report that E. colicentral metabolism can be modified to produce large quantities of fatty acids through a modular pathway engineering strategy.