Antibiotic-induced population fluctuations and stochastic clearance of bacteria.
Antibiotic-induced population fluctuations and stochastic clearance of bacteria.
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作者：
Coates J;Park BR;Le D;Şimşek E;Chaudhry W;Kim M
有效使用抗生素以最大限度地减少治疗失败仍然是一个挑战。有必要更好地了解细菌群体对抗生素的反应。先前对大量细菌群体的研究建立了药效学的确定性框架。在这里，为了描述种群灭绝的动态特征，我们证明了用抗生素消灭细菌的随机性。已知能杀死细菌（杀菌）的抗生素会引起种群波动。因此，在高抗生素浓度下，细菌清除的动态是异质的。在低浓度下，清除仍然以非零概率发生。我们的概率模型很好地捕捉到了人口波动的这些惊人结果。我们的模型进一步提出了一种通过增加灭绝概率来促进根除的策略。我们通过实验测试了对抗生素敏感和临床分离的耐药细菌的这一预测。这一新知识暴露了我们预测细菌根除能力的根本局限性。此外，它还证明了使用以前被认为无效的抗生素浓度来消灭细菌的潜力。
Effective antibiotic use that minimizes treatment failures remains a challenge. A better understanding of how bacterial populations respond to antibiotics is necessary. Previous studies of large bacterial populations established the deterministic framework of pharmacodynamics. Here, characterizing the dynamics of population extinction, we demonstrated the stochastic nature of eradicating bacteria with antibiotics. Antibiotics known to kill bacteria (bactericidal) induced population fluctuations. Thus, at high antibiotic concentrations, the dynamics of bacterial clearance were heterogeneous. At low concentrations, clearance still occurred with a non-zero probability. These striking outcomes of population fluctuations were well captured by our probabilistic model. Our model further suggested a strategy to facilitate eradication by increasing extinction probability. We experimentally tested this prediction for antibiotic-susceptible and clinically-isolated resistant bacteria. This new knowledge exposes fundamental limits in our ability to predict bacterial eradication. Additionally, it demonstrates the potential of using antibiotic concentrations that were previously deemed inefficacious to eradicate bacteria.