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

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.

SEEK ID: https://funginet.hki-jena.de/publications/173

PubMed ID: 33142084

Projects: B1

Publication type: Not specified

Journal: Open Biol

Citation: Open Biol. 2020 Nov;10(11):200206. doi: 10.1098/rsob.200206. Epub 2020 Nov 4.

Date Published: 3rd Nov 2020

Registered Mode: Not specified

Authors: R. Garde, J. Ewald, A. T. Kovacs, S. Schuster

help Submitter
Activity

Views: 1362

Created: 18th Feb 2021 at 09:44

Last updated: 17th Jan 2024 at 10:24

help Tags

This item has not yet been tagged.

help Attributions

None

Powered by
(v.1.13.4)
Copyright © 2008 - 2023 The University of Manchester and HITS gGmbH