Principles of bacteriostatic and bactericidal antibiotics at subinhibitory concentrations

亚抑制浓度下抑菌和杀菌抗生素的原理

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Abstract

Subinhibitory antibiotic exposures are common in clinical and environmental contexts, yet their effects on bacterial growth dynamics remain incompletely understood. We studied the temporal response of Escherichia coli to a panel of bactericidal ("cidal") and bacteriostatic ("static") antibiotics at sub-minimum inhibitory concentrations (sub-MIC). We uncover a sharp dynamical distinction between the two classes. Bacteriostatic antibiotics reduce the initial growth rate in a dose-dependent manner, similar to a nutrient starvation response. In contrast, bactericidal antibiotics do not alter initial growth rates-cells continue to grow as fast as untreated cells-until an abrupt slowdown in growth rate. The onset of the slowdown occurs earlier with increasing concentration, suggesting a damage accumulation mechanism leading to a lethal threshold. Cidals also show a steeper concentration-response curve. We propose that bacteria respond to cidal antibiotics with a "grow-fast-then-crash" strategy that is adaptive for transient lethal threats, whereas static antibiotics trigger stress adaptation and slower growth. While clinical outcomes of statics and cidals are similar at full inhibitory concentrations, these sub-MIC dynamical signatures could influence treatment outcomes. Our findings offer a dynamic framework for antibiotic classification and raise new questions about how bacteria respond to sublethal antibiotic stress.IMPORTANCEUnderstanding how antibiotics influence bacterial growth dynamics at subinhibitory concentrations is crucial for interpreting treatment outcomes. Traditional classifications into bacteriostatic and bactericidal agents rely on endpoint measurements that obscure temporal behaviors critical to bacterial physiology and survival. By analyzing high-resolution growth trajectories of Escherichia coli exposed to 15 antibiotics, our study reveals that bacteriostatics and bactericidals differ fundamentally not only in their outcomes but in their dynamic modes of action. These insights challenge static minimal inhibitory concentration/minimal bactericidal concentration definitions and offer a new, time-resolved framework for antibiotic classification-one that captures the kinetics of damage and response. Our findings have implications for clinical treatment strategies and for understanding how bacteria survive in sublethal antibiotic environments.

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