Published in

The Royal Society, Open Biology, 11(10), 2020

DOI: 10.1098/rsob.200206

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Modelling population dynamics in a unicellular social organism community using a minimal model and evolutionary game theory

Journal article published in 2020 by Ravindra Garde ORCID, Jan Ewald ORCID, Ákos T. Kovács ORCID, Stefan Schuster ORCID
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Most unicellular organisms live in communities and express different phenotypes. Many efforts have been made to study the population dynamics of such complex communities of cells, coexisting as well-coordinated units. Minimal models based on ordinary differential equations are powerful tools that can help us understand complex phenomena. They represent an appropriate compromise between complexity and tractability; they allow a profound and comprehensive analysis, which is still easy to understand. Evolutionary game theory is another powerful tool that can help us understand the costs and benefits of the decision a particular cell of a unicellular social organism takes when faced with the challenges of the biotic and abiotic environment. This work is a binocular view at the population dynamics of such a community through the objectives of minimal modelling and evolutionary game theory. We test the behaviour of the community of a unicellular social organism at three levels of antibiotic stress. Even in the absence of the antibiotic, spikes in the fraction of resistant cells can be observed indicating the importance of bet hedging. At moderate level of antibiotic stress, we witness cyclic dynamics reminiscent of the renowned rock–paper–scissors game. At a very high level, the resistant type of strategy is the most favourable.