  Bacterial growth environment strongly influences the efficacy of antibiotic
treatment, with slow growth often being associated with decreased
susceptibility. Yet in many cases the connection between antibiotic
susceptibility and pathogen physiology remains unclear. We show that for
ribosome-targeting antibiotics acting on Escherichia coli, a complex interplay
exists between physiology and antibiotic action; for some antibiotics within
this class faster growth indeed increases susceptibility, but for other
antibiotics the opposite is true. Remarkably, these observations can be
explained by a simple mathematical model that combines drug transport and
binding with physiological constraints. Our model reveals that growth-dependent
susceptibility is controlled by a single parameter characterizing the
`reversibility' of antibiotic transport and binding. This parameter provides a
spectrum-classification of antibiotic growth-dependent efficacy that appears to
correspond at its extremes to existing binary classification schemes. In these
limits the model predicts universal, parameter-free limiting forms for growth
inhibition curves. The model also leads to non-trivial predictions for the drug
susceptibility of a translation-mutant strain of E. coli, which we verify
experimentally. Drug action and bacterial metabolism are mechanistically
complex; nevertheless this study illustrates how coarse-grained models can be
used to integrate pathogen physiology into drug design and treatment
strategies.
