(590e) Programming Multicellular Genetic Circuits and Sequential Logic in Synthetic Microbial Consortia | AIChE

(590e) Programming Multicellular Genetic Circuits and Sequential Logic in Synthetic Microbial Consortia


Andrews, L. B., University of Massachusetts Amherst
For biomanufacturing, engineered microbial consortia are a useful strategy to produce biomolecules with high productivities by tailoring each microbial strain to perform a subset of the biocatalytic steps and utilizing dynamic enzyme expression. Moreover, engineered consortia could be utilized in a variety of settings, including for therapeutic purposes, and offer the potential to perform complex metabolic and regulatory functions that exceed those of an individual strain. Dynamic regulation and programmable responses to specified cues within consortia are of great interest to implement these functions robustly. To achieve dynamic control for a user-defined application, designable genetic circuits can be employed. While robust and scalable algorithms to design genetic circuits in single cells have been developed, similar algorithms to design consortia-level genetic circuits has lagged behind.

In this work, we present a platform for the design of multicellular genetic circuits. We developed a new set of characterized genetic parts for intercellular communication using quorum sensing components. We tested the incorporation of these cell-cell communication modules and extending the signal matching algorithm for the predictive design of multicellular genetic circuits within engineered consortia. A library of cell-cell communication modules was developed that includes 5 quorum sensors, 5 corresponding signal synthases, and 3 quorum quenching enzymes for autonomous and reversible communication within consortia. Through further engineering, the crosstalk within the sensor library was largely reduced. Quorum quenching enzyme activity and substrate specificity were characterized for the set of cell-cell signals. Quorum quenching enzyme HacB could be utilized to turn off communication selectively due to its substrate specificity. To validate the design algorithm for multicellular genetic circuits, we constructed consortia comprising two- or three-strains that contain partitioned sequential logic circuits that contain memory and would be useful in diagnostic contexts. Complex combinational logic circuits that could not be implemented in single cell due to the lack of genetic components and metabolic burden were also constructed in consortia. The three-input majority off genetic circuits constructed in 2-strain consortia had a larger dynamical range comparing to genetic circuits constructed in single cells.