Authors: Lluís Hernández-Navarro, Kenneth Distefano, Uwe C. Täuber, and Mauro Mobilia.
Paper published in PLOS Computational Biology: PLoS Comput Biol 22 (3): e1013997 (2026).
You can find the preprint on bioRxiv and arXiv. Supplementary data, codes, and movies are available on https://doi.org/10.17605/OSF.IO/EPB28.
See below for a brief description of the manuscript with a few illustrative figures. The full abstract is attached at the end.
1) Antimicrobial resistance (AMR) is a global threat and combating its spread is of paramount importance. AMR often results from resistant microbes sharing protection against drugs, and microbial communities generally evolve in volatile environments and spatial structures. This has a critical impact on AMR that has been understudied due to its complexity. Here we study a mixed population model of drug-sensitive and drug-resistant microbes on a surface (2D grid of demes). Microbes are exposed to an antimicrobial drug, undergo random births and deaths, and can migrate across the surface, while the environment switches back and forth between different levels of resources.
2) Sensitive and resistant microbes coexist for a long time in environments with constant nutrient levels. However, this picture changes dramatically when the environmental level of resources switches neither too rarely nor too often. Microbes then undergo consecutive population bottlenecks that cause random local extinctions of the resistant strain. Fast microbial migration rescues AMR, whereas strong environmental changes help eradicate AMR across the surface (see supplementary movie 3 on https://osf.io/xf2kp).
3) For these `intermediate-switching’ environments, we demonstrate that slow but nonzero cellular migration speeds up the clearance of AMR (see supplementary movies 1 and 2 on https://osf.io/jwpu2 and https://osf.io/w5qac). Through simulations and mathematical analysis, we determine the environmental conditions and cellular migration speeds that are optimal to eradicate AMR. These findings pave the way to innovative treatment options to prevent the spread of AMR in clinical and other applications.
Abstract:
Antimicrobial resistance (AMR) is a global threat and combating its spread is of paramount importance. AMR often results from a cooperative behaviour with shared drug protection. Microbial communities generally evolve in volatile, spatially structured settings. Migration, space, fluctuations, and environmental variability all have a significant impact on the development and
proliferation of AMR. While drug resistance is enhanced by migration in static conditions, this changes in time-fluctuating spatially structured environments. Here, we consider a two-dimensional metapopulation consisting of demes in which drug-resistant and sensitive cells evolve in a time-changing environment. This contains a toxin against which protection can be shared (cooperative AMR). Cells migrate between demes and connect them. When the environment and the deme composition vary on the same timescale, strong population bottlenecks cause fluctuation-driven extinction events, countered by migration. We investigate the influence of migration and environmental variability on the AMR eco-evolutionary dynamics by asking at what migration rate fluctuations can help clear resistance and what are the near-optimal environmental conditions ensuring the quasi-certain eradication of resistance in the shortest possible time. By combining analytical and computational tools, we answer these questions by determining when the resistant strain goes extinct across the entire metapopulation. While dispersal generally promotes strain coexistence, here we show that slow-but-nonzero migration can speed up and enhance resistance clearance, and determine the near-optimal conditions for this phenomenon. We discuss the impact of our findings on laboratory-controlled experiments and outline their generalisation to lattices of any spatial dimension.