Microorganisms live in complex communities and interact either through secreting soluble molecules or by delivering effectors in a contact dependent manner. Microbial interactions range from cooperative to competitive. Contact-dependent growth inhibition (CDI), discovered in Escherichia coli EC93, is becoming increasingly studied, as this mode of interaction seems to be widespread among proteobacteria. CDI is mediated by cdiBAI genes which encode for a two-partner secretion system; i.e. CdiB is an outer membrane protein that transports CdiA to the surface of the cell. CdiA can interact with a specific receptor on a target cell and deliver a toxin localized in its C-terminal domain to the target cell. CdiI is a small immunity protein that neutralizes the toxic effect of CdiA toxin. Recently, evidence from our research group has shown that E. coli EC93 harbours two cdi loci. The first cdi locus has been extensively studied but the role of second locus remained unknown. In this study we wanted to elucidate the activity and the role of second E. coli EC93 cdi locus in intra-strain bacterial interactions. Bacterial competitions of E. coli EC93 wild type versus E. coli EC93 targets that had deletions for one or both cdi loci showed that the second locus is indeed active in inhibiting the targets, albeit to a lesser extent than the first. The toxic activity of the second cdi-locus was neutralized specifically by the second immunity protein. The expression of both these systems is higher under carbon starvation conditions than in nutrient rich conditions. Unfortunately, we could not elucidate the mechanism of toxicity for the second cdi locus toxin. Taken together, our results show that E. coli EC93 actively uses both of its cdi loci during bacterial interactions and that these systems are more active during stressful conditions.

Thesis advisor: Babak Momeni / Microbial communities are complex networks comprised of multiple species that are facilitating and inhibiting one another (as well as themselves). Currently, we lack an understanding of what mechanisms drive coexistence within these communities. We aimed to remedy this by studying the dynamics of coexisting communities, focusing on the complexity of their interaction networks, the impact of spatial dynamics, and the interplay of facilitating and inhibiting interactions. These limitations in our understanding prevent the furtherment of designing intentional communities for bioremediation, maintenance of healthy microbiota, and other functional communities. To better understand these microbial dynamics, we chose to address the problem from two fronts: computational modeling and exploring dynamics of cocultures. Through our 1-D model, spatial structure fostering more coexistence – especially when facilitation is present. For the coexistence assays, we determined that contact-dependent growth inhibition is a density dependent mechanism, and the use of a Tn-Seq mutant library to predict species interactions is possible, but needs further optimization to reconcile density dependent effects of interactions. / Thesis (MS) — Boston College, 2021. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Biology.