Stochastic gene expression in bacteria: effects of regulatory RNAs on population profiles

• Applicant: Dr. Bork Berghoff
• Subject Area: Metabolism, Biochemistry and Genetics of Microorganisms
• Term: from 2012 to 2016
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 229046453

Organisms display adequate expression patterns of their genetic equipment in order to adapt to their environment. Especially, unicellular organisms need to ultimately react to their environment for survival. In this context, single regulatory factors control complex cellular programs, which in turn significantly determine phenotypes. Populations of genetically identical cells frequently develop into subpopulation with distinct phenotypes based on stochastic events. Stochastic gene expression also triggers heterogeneity in bacterial populations. Emerging subpopulations are either in the ON- or the OFF-state for distinct cellular programs leading to bistable expression patterns and, correspondingly, different phenotypes/behaviors. This can be seen at many bacterial traits, as e.g. sporulation and competence. So far, little is known about the roles of sRNAs, acting at the post-transcriptional level, as determinant factors for ON/OFF switches. To address this question I will use two relevant model systems in E. coli: persister formation and biofilm development. Both processes exhibit a considerable influence on antibiotic resistance and are therefore of major relevance. It is known that the growth-arresting toxin TisB, that is controlled by the sRNA IstR-1, increases the frequency of persisters. In biofilm development, the major regulator of curli and cellulose synthesis, CsgD, is controlled by at least two sRNAs (OmrA and OmrB). Expression of target proteins (TisB and CsgD), tagged with fluorescent proteins, will be analyzed in different sRNA backgrounds (deletion/overexpression). Stochastic switching of subpopulations and their ratios will be investigated by FACS analysis, and high-end microscopy in microfluidics devices will report on effects in growing cells at single-cell level in real time. Phenotypic tests complement this analysis. Switching phenotypes underly many important bacterial traits. My project will provide roles and mechanisms for the impact of sRNAs to bistability and stochasticity in general.

• DFG Programme: Research Fellowships
• International Connection: Sweden
• Host: Professor Dr. Gerhart Wagner