Bacterial motility can govern the dynamics of antibiotic resistance evolution

被引:6
|
作者
Piskovsky, Vit [1 ,2 ]
Oliveira, Nuno M. [1 ,3 ]
机构
[1] Univ Cambridge, Dept App Math & Theoret Phys, Ctr Math Sci, Wilberforce Rd, Cambridge CB3 0WA, England
[2] Univ Oxford, Math Inst, Woodstock Rd, Oxford OX2 6GG, England
[3] Univ Cambridge, Dept Vet Med, Madingley Rd, Cambridge CB3 0ES, England
基金
英国生物技术与生命科学研究理事会;
关键词
EXACT STOCHASTIC SIMULATION; SWARMING MOTILITY; ADAPTATION; CHEMOTAXIS; DIVERGENCE; EMERGENCE; EXCHANGE; LIMITS;
D O I
10.1038/s41467-023-41196-8
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Spatial heterogeneity in antibiotic concentrations is thought to accelerate the evolution of antibiotic resistance, but current theory and experiments have overlooked the effect of cell motility on bacterial adaptation. Here, we study bacterial evolution in antibiotic landscapes with a quantitative model where bacteria evolve under the stochastic processes of proliferation, death, mutation and migration. Numerical and analytical results show that cell motility can both accelerate and decelerate bacterial adaptation by affecting the degree of genotypic mixing and ecological competition. Moreover, we find that for sufficiently high rates, cell motility can limit bacterial survival, and we derive conditions for all these regimes. Similar patterns are observed in more complex scenarios, namely where bacteria can bias their motion in chemical gradients (chemotaxis) or switch between motility phenotypes either stochastically or in a density-dependent manner. Overall, our work reveals limits to bacterial adaptation in antibiotic landscapes that are set by cell motility. In nature, bacteria experience gradients of antibiotics, but we know little about how such heterogeneity affects bacterial adaptation. Piskovsky and Oliveira develop quantitative models of bacterial adaptation in antibiotic landscapes and find that bacterial motility can govern the spatiotemporal dynamics of antibiotic resistance evolution.
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页数:12
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