Antibiotic treatment in vitro of phenotypically tolerant bacterial populations

Abstract

Objectives: Most pharmacodynamic models used for design of treatment regimens are based on time-kill data obtained with normal cells in the susceptible state without taking into account the killing kinetics of the antibiotic-tolerant cells in the population. We compared the microbiological efficacy of six antibiotics against tolerant cells and by mathematical modelling explored the potential clinical implications of tolerance. Methods: Tolerant cells were obtained by filtration of bacterial cultures of Escherichia coli MG1655 after antibiotic exposure. Killing kinetics of the tolerant cells was compared with that of exponentially growing naive cells. To examine the nutrient dependency of the reversion from the tolerant state to the susceptible state, tolerant cells were re-suspended in Luria-Bertani and PBS and re-exposed to antibiotics. A mathematical model was used to explore the clinical implications of antibiotic tolerance. Results: Streptomycin was the most efficient drug against tolerant cells. Ciprofloxacin and ampicillin had intermediate activity against tolerant cells while rifampicin, tetracycline and erythromycin had poor activity against tolerant cells. No correlation could be established between the microbiological efficacies against susceptible and tolerant cells. Reversion from tolerance to susceptibility was dependent on the presence of nutrients and growth. Computer simulations demonstrated that the efficacy of antibiotics against tolerant cell populations has a large influence on treatment outcome. Conclusions: The in vitro killing kinetics of tolerant cells is antibiotic-dependent and different from that of cells in the susceptible state. This difference in efficacy could have an influence on treatment outcome and tolerance should therefore be studied further in vivo. © The Author 2006. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved.