Department of Biophysics, University of Michigan, Ann Arbor, United States.
Department of Physics, University of Michigan, Ann Arbor, United States.
Elife. 2020 Mar 24;9:e52813. doi: 10.7554/eLife.52813.
The molecular underpinnings of antibiotic resistance are increasingly understood, but less is known about how these molecular events influence microbial dynamics on the population scale. Here, we show that the dynamics of communities exposed to antibiotics can be surprisingly rich, revealing scenarios where increasing population size or delaying drug exposure can promote population collapse. Specifically, we demonstrate how density-dependent feedback loops couple population growth and antibiotic efficacy when communities include drug-resistant subpopulations, leading to a wide range of behavior, including population survival, collapse, or one of two qualitatively distinct bistable behaviors where survival is favored in either small or large populations. These dynamics reflect competing density-dependent effects of different subpopulations, with growth of drug-sensitive cells increasing but growth of drug-resistant cells decreasing effective drug inhibition. Finally, we demonstrate how populations receiving immediate drug influx may sometimes thrive, while identical populations exposed to delayed drug influx collapse.
抗生素耐药性的分子基础越来越被理解,但关于这些分子事件如何影响群体尺度上的微生物动态知之甚少。在这里,我们表明,暴露于抗生素的群落的动态可能出人意料地丰富,揭示了种群规模增加或延迟药物暴露可以促进种群崩溃的情况。具体来说,我们展示了当群落包含耐药亚群时,种群增长和抗生素功效如何通过密度依赖的反馈环耦合,导致广泛的行为,包括种群生存、崩溃或两种定性不同的双稳态行为,其中生存在小或大种群中更有利。这些动态反映了不同亚群的竞争密度依赖性效应,药物敏感细胞的生长增加,但药物耐药细胞的生长减少了有效药物抑制。最后,我们展示了如何使立即接受药物流入的种群有时可能茁壮成长,而暴露于延迟药物流入的相同种群则崩溃。