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  Which games are growing bacterial populations playing?

Li, X.-Y., Pietschke, C., Fraune, S., Altrock, P. M., Bosch, T. C. G., & Traulsen, A. (2015). Which games are growing bacterial populations playing? Interface: Journal of the Royal Society, 12(108): 20150121. doi:10.1098/rsif.2015.0121.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0027-A947-4 Version Permalink: http://hdl.handle.net/11858/00-001M-0000-0027-A948-2
Genre: Journal Article

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 Creators:
Li, Xiang-Yi1, Author              
Pietschke, Cleo, Author
Fraune, Sebastian, Author
Altrock, Philipp M., Author
Bosch, Thomas C. G., Author
Traulsen, Arne1, Author              
Affiliations:
1Department Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Max Planck Society, ou_1445641              

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Free keywords: bacterial interactions; frequency-dependent selection; Lotka–Volterra equations; nonlinear dynamics; population dynamics
 Abstract: Microbial communities display complex population dynamics, both in frequency and absolute density. Evolutionary game theory provides a natural approach to analyse and model this complexity by studying the detailed interactions among players, including competition and conflict, cooperation and coexistence. Classic evolutionary game theory models typically assume constant population size, which often does not hold for microbial populations. Here, we explicitly take into account population growth with frequencydependent growth parameters, as observed in our experimental system. We study the in vitro population dynamics of the two commensal bacteria (Curvibacter sp. (AEP1.3) and Duganella sp. (C1.2)) that synergistically protect the metazoan host Hydra vulgaris (AEP) from fungal infection. The frequencydependent, nonlinear growth rates observed in our experiments indicate that the interactions among bacteria in co-culture are beyond the simple case of direct competition or, equivalently, pairwise games. This is in agreement with the synergistic effect of anti-fungal activity observed in vivo. Our analysis provides new insight into the minimal degree of complexity needed to appropriately understand and predict coexistence or extinction events in this kind of microbial community dynamics. Our approach extends the understanding of microbial communities and points to novel experiments.

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Language(s): eng - English
 Dates: 2015-05-202015-02-112015-06-17
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: DOI: 10.1098/rsif.2015.0121
 Degree: -

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Title: Interface : Journal of the Royal Society
  Other : J. R. Soc. Interface
Source Genre: Journal
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Publ. Info: London : Royal Society
Pages: 10 S. Volume / Issue: 12 (108) Sequence Number: 20150121 Start / End Page: - Identifier: ISSN: 1742-5689
CoNE: /journals/resource/1000000000018840_1