An experimental-computational platform for investigating microbial interactions and dynamics in communities with two codependent species

Microbial interactions are critical for governing community behavior and structure in natural environments. Examination of microbial interactions in the lab involves growth under ideal conditions in batch culture; conditions that occur in nature are, however, characterized by disequilibrium. Of particular interest is the role that system variables play in shaping cell-to-cell interactions and organization at ultrafine spatial scales. We seek to use experiments and agent-based modeling to help discover mechanisms relevant to microbial dynamics and interactions in the environment. Currently, we are using an agent-based model to simulate microbial growth, dynamics and interactions that occur on a microwell-array device developed in our lab. Bacterial cells growing in the microwells of this platform can be studied with high-throughput and high-content image analyses using brightfield and fluorescence microscopy. The agent-based model is written in the language Netlogo, which in turn is "plugged into" a computational framework that allows submitting many calculations in parallel for different initial parameters; visualizing the outcomes in an interactive phase-like diagram; and searching, with a genetic algorithm, for the parameters that lead to the most optimal simulation outcome.