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Competition by ColicinE2 release in Escherichia coli

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
 
Final Report Year 2020

Final Report Abstract

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, using the well-studied ColicinE2 bacterial model system of Escherichia coli we investigated bacterial competition by toxin release, both experimentally and theoretically. Monitoring the bacterial interaction dynamics in range expansion experiments from the near single cell level up to the development of macroscopic bacterial colonies, we show that both deterministic and stochastic factors determine competition outcome and consequently community composition. In particular, we studied two different strategies that toxin-producing bacteria can use in principle to increase their competitive success: (i) heterogeneous toxin production and (ii) the creation of a delay between toxin production and release to prevent premature release of ineffective toxin concentrations. Investigating toxin expression dynamics, we showed that a late toxin release results in a high amount of toxin that is released into the environment. However, both factors, the time-point of toxin release as well as the amount of toxin released are affecting the competition of the toxin-producing strain with a strain sensitive towards the toxin. Furthermore, we were able to show that the environmental condition, in particular the main carbon source, alters toxin expression dynamics and therefore greatly affects the bacterial competition. Taken together, this study provided a deeper understanding on how stochastic and deterministic factors control bacterial competition by toxin release.

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