Collaborative Research: DMS/NIGMS2: Spatiotemporal dynamics of intercellular signaling in growing cellular populations

Engineered multicellular bacterial systems have a wide range of potential applications, including gut microbiome maintenance, cancer therapy, environmental remediation, and engineered living materials that can sense and respond to local conditions. However, such bacterial systems are difficult to design due to our lack of a mechanistic understanding of how cells within a bacterial colony interact and communicate across time and space. This work will address this issue by studying simplified engineered bacterial systems and formulating novel mathematical frameworks that will allow engineers to better predict colony behavior. More broadly, this research will expose undergraduates, graduate students, and postdoctoral researchers to cutting edge synthetic biology research and train them to enter the growing biotechnology industrial sector. Additionally, the findings will be incorporated into undergraduate and graduate classes. Synthetic biologists have long strived to create engineered multicellular systems with unicellular bacteria for industrial and biomedical applications. Towards this goal, the PIs will use a combination of experimental and theoretical synthetic biology to develop mathematical modeling techniques that describe the spatiotemporal dynamics of intercellular signaling in spatially extended bacterial systems. In previous work, the PIs have developed numerous spatially extended synthetic bacterial systems and methods for monitoring intercellular signaling, gene expression, and cellular growth within them. The PIs will use these techniques in a series of increasingly complex experiments to determine how mathematical models need to be altered to better reproduce and predict the spatiotemporal dynamics of spatially extended synthetic multicellular systems. Overall, this research will lead to more accurate mathematical models that will enable us to better design large-scale, complex synthetic systems capable of coordinating their spatiotemporal gene expression patterns. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.