Microbes are social organisms that are most commonly found forming complex ecological communities. Every species in a community is typically represented by large numbers of cells which may also differ in their individual behaviors. A fascinating fact is that the individual behavior of a microbial cell often depends on what the other cells in their vicinity are doing; much like animals do, microbes implement social strategies. Not having a central nervous system to help them make decisions, bacteria adopt these social strategies as alternative phenotypes, encoded in their DNA sequences and governed by biochemical and gene regulatory circuits. Evolutionary changes in these “decision-making circuits” will therefore affect ecological interactions between species and are an essential component of microbial communities.
At the Rowland, the Sanchez Lab was interested in shedding some light into this rather complex system, and understanding the relationship between the evolution of microbial behavior and microbial ecology. For instance, they asked questions such as: How is the social behavior of microbes encoded in their DNA? How does the behavior of individuals from one species affect the behavior of other species in the community? Can we describe these interactions quantitatively? How does the structure of microbial communities affect the evolution of social traits? Can we quantitatively map complex microbial interaction networks and predict their community dynamics? In order to tackle these questions, the Sanchez Lab used a combination of biophysical tools (in order to grow large numbers of cultures in parallel and help us determine the frequencies of different species in these communities), mathematical and computational modeling (to help us generate quantitative hypotheses and understand our data) and systems and synthetic biology (in order to engineer cells with pre-determined social behaviors and to assemble communities in vitro).