Competition by ColicinE2 release in Escherichia coli

• Applicant: Privatdozentin Dr. Madeleine Opitz
• Subject Area: Biophysics ; Statistical Physics, Nonlinear Dynamics, Complex Systems, Soft and Fluid Matter, Biological Physics
• Term: from 2018 to 2020
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 396470437

Microbial interactions like cooperation and competition govern ecosystem dynamics influencing ecosystem composition, maintenance of diversity and the microbiota-host relationship. Despite the detailed knowledge of individual interaction mechanisms and community compositions as obtained by large-scale sequencing, a fundamental problem in microbial ecology is the need for predictive model systems that combine experimental and theoretical efforts to explain how ecosystems dynamics emerge from interactions between single cells. Here, we will use the well-studied ColicinE2 bacterial model system of Escherichia coli to investigate bacterial competition by toxin release, both experimentally and theoretically. Thereby, we aim to understand what factors, both deterministic and stochastic, determine competition outcome and consequently community composition. In particular, we will study two different strategies that toxin producing bacteria can use in principle to increase their competitive effect: (i) heterogeneous toxin production and (ii) the creation of a delay between toxin production and release to prevent premature release of ineffective toxin concentrations. We will monitor the bacterial interaction dynamics in range expansion experiments from the near single cell level up to the development of macroscopic bacterial colonies and correlate competition outcome to the initial conditions. Analyzing the competition of the toxin producing strain with bacteria sensitive and resistant towards the toxin in the presence of different external stress levels, we aim to understand how robust and effective the above described strategies are, and which of these two strategies is the most effective to ensure dominance of the toxin producing strain. Taken together, this study will provide a deeper understanding on how stochastic and deterministic factors control bacterial competition by toxin release.

• DFG Programme: Research Grants