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  Memory shapes microbial populations

Gokhale, C. S., Giaimo, S., & Remigi, P. (2020). Memory shapes microbial populations. bioRxiv. doi:10.1101/2020.11.05.370106.

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Gokhale, Chaitanya S.1, Autor           
Giaimo, Stefano2, Autor           
Remigi, Philippe, Autor
Affiliations:
1Research Group Theoretical Models of Eco-Evolutionary Dynamics, Department Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Max Planck Society, ou_2355692              
2Department Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Max Planck Society, ou_1445641              

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 Zusammenfassung: Correct decision making is fundamental for all living organisms to thrive under environmental changes. The patterns of environmental variation and the quality of available information define the most favourable strategy among multiple options, including sensing and reacting to environmental cues or randomly adopting a phenotypic state. Memory –} a phenomenon often associated with, but not restricted to, higher multicellular organisms {– can help when temporal correlations exist. How does memory manifest itself in unicellular organisms? Through a combination of deterministic modelling and stochastic simulations, we describe the population-wide fitness consequences of phenotypic memory in microbial populations. Moving beyond binary switching models, our work highlights the need to consider a broader range of switching behaviours when describing microbial adaptive strategies. We show that multiple cellular states capture the empirical observations of lag time distributions, overshoots, and ultimately the phenomenon of phenotypic heterogeneity. We emphasise the implications of our work in understanding antibiotic tolerance, and, in general, survival under fluctuating environments.Competing Interest StatementThe authors have declared no competing interest.

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Sprache(n): eng - English
 Datum: 2020-11-052020
 Publikationsstatus: Erschienen
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 Art der Begutachtung: Keine Begutachtung
 Identifikatoren: DOI: 10.1101/2020.11.05.370106
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Titel: bioRxiv
Genre der Quelle: Zeitschrift
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