Simultaneous pharmacodynamic analysis of the lag and bactericidal phases exhibited by beta-lactams against Escherichia coli.

Antibiotic-bacterium interactions are complex in nature. In many cases, bacterial killing does not commence immediately after the addition of an antibiotic, and a lag period is observed. Antibiotic permeation and/or the intermediate steps that exist between antibiotic-receptor binding and expression of cell death are two major possible causes for such lag period. This study was primarily designed to determine the relationship, if any, between antibiotic concentrations and the lag periods by a modeling approach. Short-term time-kill studies were conducted for amoxicillin, ampicillin, penicillin-G, oxacillin, and dicloxacillin against Escherichia coli. In conjunction with the use of a saturable rate model to describe the concentration-dependent killing process, a first-order induction (initiation) rate constant was used to characterize the delay in bacterial killing during the lag period. For all of the beta-lactams tested, parameters describing the bactericidal effect suggest that amoxicillin and ampicillin were much more potent than oxacillin and dicloxacillin. The induction rate constant estimates for both ampicillin and amoxicillin were found to relate linearly to concentrations. Nevertheless, these induction rate constant estimates were lower for penicillin-G, oxacillin, and dicloxacillin and increased nonlinearly with concentrations until an apparent plateau was observed. These findings support the hypothesis that the permeation process is potentially a rate-limiting step for the rapid bactericidal beta-lactams such as ampicillin and amoxicillin. However, as suggested by previous observations of the various morphological changes induced by beta-lactams, the contribution of the steps following antibiotic-receptor complex formation to the lag period might be significant for the less bactericidal antibiotics such as oxacillin and dicloxacillin. Findings from the present modeling approach can potentially be used to guide future bench experimentation.