CAREER: Programmable synthetic microbial consortia for complex multicellular functions

University Of Massachusetts Amherst, Amherst MA

Investigators

Abstract

Engineered mixed cell populations have potential application in biomanufacturing, cell-based therapies, and diagnostics. Bacterial metabolism is a highly reactive network, and different reactions occur at different times. They are turned on and off by signals generated internally and externally. In this way the cell can make effective decisions regarding the flow of carbon sources and other materials through specific reaction pathways. Attempts to engineer cell populations have not achieved comparable control. This project will focus on developing a protocol for the design of control systems for mixtures of microbes. The protocol will guide the construction of genetic components that can help implement the control system. These components will be evaluated in a variety of organisms. A core objective of this project is to educate and mentor a diverse future workforce. Programs for K-12 STEM education and to broaden research opportunities for underrepresented groups will be developed and implemented. Similar to naturally-occurring dynamic pathway expression, computational dynamic metabolic modeling predicts optimized bioproduction by discrete metabolic states and temporal enzyme activation. This has not been achievable within bioproduction microbial consortia. The goal of the proposed research is to establish a generalizable platform for the automated design of bacterial consortia. Users will be able to dynamically control metabolism and specify coordinated multicellular responses to user-defined temporal signals. This project will develop genetic circuit components and a circuit design algorithm for partitioning sequential logic circuits within engineered bacterial communities, and identify design principles for biological sequential logic programming in synthetic microbial consortia. The proposed research will produce circuit components that are compatible with automated design algorithms and physical plasmids for bacterial intercellular signaling. This will enable researchers to utilize off-the-shelf parts for a priori design of multicellular genetic circuits that implement temporal transcription control in microbial consortia. 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.