English

Coupled environmental and demographic fluctuations shape the evolution of cooperative antimicrobial resistance

Populations and Evolution 2023-11-16 v2 Statistical Mechanics Adaptation and Self-Organizing Systems Biological Physics

Abstract

There is a pressing need to better understand how microbial populations respond to antimicrobial drugs, and to find mechanisms to possibly eradicate antimicrobial-resistant cells. The inactivation of antimicrobials by resistant microbes can often be viewed as a cooperative behavior leading to the coexistence of resistant and sensitive cells in large populations and static environments. This picture is however greatly altered by the fluctuations arising in volatile environments, in which microbial communities commonly evolve. Here, we study the eco-evolutionary dynamics of a population consisting of an antimicrobial resistant strain and microbes sensitive to antimicrobial drugs in a time-fluctuating environment, modeled by a carrying capacity randomly switching between states of abundance and scarcity. We assume that antimicrobial resistance is a shared public good when the number of resistant cells exceeds a certain threshold. Eco-evolutionary dynamics is thus characterised by demographic noise (birth and death events) coupled to environmental fluctuations which can cause population bottlenecks. By combining analytical and computational means, we determine the environmental conditions for the long-lived coexistence and fixation of both strains, and characterise a fluctuation-driven antimicrobial resistance eradication mechanism, where resistant microbes experience bottlenecks leading to extinction. We also discuss the possible applications of our findings to laboratory-controlled experiments.

Keywords

Cite

@article{arxiv.2307.06326,
  title  = {Coupled environmental and demographic fluctuations shape the evolution of cooperative antimicrobial resistance},
  author = {Lluís Hernández-Navarro and Matthew Asker and Alastair M. Rucklidge and Mauro Mobilia},
  journal= {arXiv preprint arXiv:2307.06326},
  year   = {2023}
}

Comments

21+7 pages, 4+1 figures. The revised version includes minor corrections to the original manuscript. Simulation data and codes for all figures are electronically available from the University of Leeds Data Repository. DOI: https://doi.org/10.5518/1360