Journal article
Modelling population dynamics in a unicellular social organism community using a minimal model and evolutionary game theory
Friedrich Schiller University Jena1
Department of Biotechnology and Biomedicine, Technical University of Denmark2
Section for Microbial and Chemical Ecology, Department of Biotechnology and Biomedicine, Technical University of Denmark3
Center for Microbial Secondary Metabolites, Centers, Technical University of Denmark4
Bacterial Interactions and Evolution, Section for Microbial and Chemical Ecology, Department of Biotechnology and Biomedicine, Technical University of Denmark5
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.
Language: | English |
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Publisher: | The Royal Society |
Year: | 2020 |
Pages: | 200206 |
ISBN: | 2811119353 , 2811119361 , 9782811119355 and 9782811119362 |
ISSN: | 20462441 |
Types: | Journal article |
DOI: | 10.1098/rsob.200206 |
ORCIDs: | Kovács, Ákos T. , 0000-0002-7765-8666 , 0000-0002-9415-2317 and 0000-0003-2828-9355 |