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Stable leaders pave the way for cooperation under time-dependent exploration rates.

ABSTRACT: The exploration of different behaviours is part of the adaptation repertoire of individuals to new environments. Here, we explore how the evolution of cooperative behaviour is affected by the interplay between exploration dynamics and social learning, in particular when individuals engage on prisoner's dilemma along the edges of a social network. We show that when the population undergoes a transition from strong to weak exploration rates a decline in the overall levels of cooperation is observed. However, if the rate of decay is lower in highly connected individuals (Leaders) than for the less connected individuals (Followers) then the population is able to achieve higher levels of cooperation. Finally, we show that minor differences in selection intensities (the degree of determinism in social learning) and individual exploration rates, can translate into major differences in the observed collective dynamics.

SUBMITTER: Pinheiro FL

PROVIDER: S-EPMC8074787 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Stable leaders pave the way for cooperation under time-dependent exploration rates.

Pinheiro Flávio L FL Pacheco Jorge M JM Santos Francisco C FC

Royal Society open science 20210203 2

The exploration of different behaviours is part of the adaptation repertoire of individuals to new environments. Here, we explore how the evolution of cooperative behaviour is affected by the interplay between exploration dynamics and social learning, in particular when individuals engage on prisoner's dilemma along the edges of a social network. We show that when the population undergoes a transition from strong to weak exploration rates a decline in the overall levels of cooperation is observe ...[more]

PMID: 33972841

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Project description:UNLABELLED:Swarming bacteria are challenged by the need to invade hostile environments. Swarms of the flagellated bacterium Paenibacillus vortex can collectively transport other microorganisms. Here we show that P. vortex can invade toxic environments by carrying antibiotic-degrading bacteria; this transport is mediated by a specialized, phenotypic subpopulation utilizing a process not dependent on cargo motility. Swarms of beta-lactam antibiotic (BLA)-sensitive P. vortex used beta-lactamase-producing, resistant, cargo bacteria to detoxify BLAs in their path. In the presence of BLAs, both transporter and cargo bacteria gained from this temporary cooperation; there was a positive correlation between BLA resistance and dispersal. P. vortex transported only the most beneficial antibiotic-resistant cargo (including environmental and clinical isolates) in a sustained way. P. vortex displayed a bet-hedging strategy that promoted the colonization of nontoxic niches by P. vortex alone; when detoxifying cargo bacteria were not needed, they were lost. This work has relevance for the dispersal of antibiotic-resistant microorganisms and for strategies for asymmetric cooperation with agricultural and medical implications. IMPORTANCE:Antibiotic resistance is a major health threat. We show a novel mechanism for the local spread of antibiotic resistance. This involves interactions between different bacteria: one species provides an enzyme that detoxifies the antibiotic (a sessile cargo bacterium carrying a resistance gene), while the other (Paenibacillus vortex) moves itself and transports the cargo. P. vortex used a bet-hedging strategy, colonizing new environments alone when the cargo added no benefit, but cooperating when the cargo was needed. This work is of interest in an evolutionary context and sheds light on fundamental questions, such as how environmental antibiotic resistance may lead to clinical resistance and also microbial social organization, as well as the costs, benefits, and risks of dispersal in the environment.

Dataset Information

Stable leaders pave the way for cooperation under time-dependent exploration rates.

Publications

Stable leaders pave the way for cooperation under time-dependent exploration rates.

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