Reverse engineering of bacterial regulatory networks

Daniel Lobo, Department of Biological Sciences, UMBC
Madhavi Avadhani, Department of Biological Sciences, UMBC
Mikhail Plungis, Department of Biological Sciences, UMBC
Caroline Larkin, Department of Biological Sciences, UMBC
Mark Ebeid, Department of Biological Sciences, UMBC

Cellvibrio bacteria utilize glucose and cellobiose in differing manners. We are using automated methods to discover the regulatory network of several genes involved in metabolizing these carbohydrates.

This study uses a computer model of cells to show how chemical signals and physical forces work together to control and keep the shape of tissues stable. The model tracks how cells grow, divide, and die in response to signal molecules that spread between cells and to the mechanical stress they feel from their neighbors. The results suggest that a feedback loop between these signals and tissue mechanics is needed for tissues to reliably reach and keep a target shape. The project also shows that self-organized signal patterns, like Turing-type systems, can guide tissue growth so that stable shapes form and can regrow after damage. Overall, the work gives a clear framework for studying how linked chemical and mechanical feedback can explain stable body and organ shapes during development and regeneration.