Abstract

Microbial species exhibit a wide repertoire of phenotypic responses to their surroundings, be it stresses posed by their environment, or signals from their bacterial community. Despite advances in computer vision, reporting such phenotypic responses is often done in a qualitative manner. In the course of my work I developed a user-friendly software tool to address the lack of a standardized, quantitative method to measure microbial phenotypes macroscopically. This freely available software, called Iris, can quantify a wide range of microbial phenotypes at the colony level and in a high-throughput fashion. Iris is already used by several research groups, and I present some of its diverse applications and potential for hypothesis generation. One such application is the quantification of the impact of each gene on the cell envelope permeability in E. coli. The Gram-negative bacterial cell envelope forms a barrier against antimicrobial drugs, drastically limiting the list of treatments effective against these organisms. To expand our knowledge on how this multi-layered is built and perturbed, we developed a rapid screening method to detect mutants with envelope defects. By screening a systematic gene deletion mutant collection in E. coli across 4 conditions, we identified a number of mutants with defects in envelope assembly. Among those were genes known to be involved in envelope biogenesis, as well as 102 genes of unknown function. In the course of my work I built upon and improved this screening approach, to acquire quantitative membrane permeability measurements that can be used for high- throughput chemical genomics approaches. Gram-negative bacterial envelope is both a permeability barrier, and a structural barrier. The structural component mainly consists of the rigid peptidoglycan (PG) sacculus, which gives the cells the ability to withstand both turgor pressure and environmental insults. Although biosynthesis of PG is central to bacteria and a target of β-lactam antibiotics, its regulation remains largely elusive. Recently, a number of regulators of PG biosynthesis have been identified, and shown to have coevolved with domains in PG synthases. With the aim of uncovering potential regulatory connections, I developed a computational approach to explore the coevolution of domains in proteins involved in cell wall biosynthesis and remodeling with other proteins in the cell. The method correctly identified existing regulatory interactions, and is readily applied to species across the bacterial kingdom.