The goal of this research is to determine how collections of cells, for example, a colony of bacterial cells forming a biofilm, coordinate their behaviors to accomplish goals that are impossible for isolated single cells alone. In particular, the project examines how cellular collectives cooperate to better sense the environment in an effort to determine the spatial location of important resources needed for survival. Computational and experimental methods are integrated in investigations that examine the genetic interactions involved in collective cell sensing. These investigations are used to produce models that advance the understanding of the nature of the cellular interactions. The models are then validated with experimental data. A better understanding of how cells cooperate will inform methods for the construction of synthetic multicellular systems that could be applied to biomanufacturing, environmental remediation or tissue formation for regenerative medicine. In addition to the scientific advances, this project provides societal benefits through curriculum development, the training of students ranging from middle-schoolers to postdoctoral researchers, and the public dissemination of science through mass media.
A combination of mathematical modeling and experimental synthetic biology is used to overcome the challenges associated with studying native cell signaling pathways and provide more precise control over genetic and network components. Hypotheses are generated through analytically tractable mathematical models. The resulting predictions are tested on multicellular colonies with realistic, multi-scale agent-based computer models. Next, synthetic gene circuits that contain the proper inter- and intracellular regulatory mechanisms are constructed in Escherichia coli. These gene circuits are then examined experimentally for their collective phenotypes. Finally, the research team fits the mathematical models to the resulting data and validates their predictions on separate sets of experiments. This award was co-funded by the Systems and Synthetic Biology Program in the Division of Molecular and Cellular Biosciences and the Mathematical Biology Program in the Division of Mathematical Sciences.
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.
