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Robust, linear correlations between growth rates and β-lactam–mediated lysis rates

A. J. Lee,Shangying Wang,Hannah R. Meredith,Bihan Zhuang,Zhuojun Dai,L. You

Published 2018 in Proceedings of the National Academy of Sciences of the United States of America

ABSTRACT

Significance How fast bacteria grow influences the efficacy of β-lactams, one of the most commonly used classes of antibiotics. However, the quantitative nature of this correlation is not well established. With precise measurements and analyses enabled by experimental automation, we found a robust relationship between growth and lysis rates that is generally applicable to diverse pairs of β-lactams and bacteria. That is, the growth rate of population serves as a reliable predictor for the lysis rate in response to a β-lactam. This quantitative correlation lays the foundation for predicting bacterial population dynamics during β-lactam treatments. This predictive capability is critical for designing effective antibiotic dosing protocols, in addressing the rising antibiotic resistance crisis. It is widely acknowledged that faster-growing bacteria are killed faster by β-lactam antibiotics. This notion serves as the foundation for the concept of bacterial persistence: dormant bacterial cells that do not grow are phenotypically tolerant against β-lactam treatment. Such correlation has often been invoked in the mathematical modeling of bacterial responses to antibiotics. Due to the lack of thorough quantification, however, it is unclear whether and to what extent the bacterial growth rate can predict the lysis rate upon β-lactam treatment under diverse conditions. Enabled by experimental automation, here we measured >1,000 growth/killing curves for eight combinations of antibiotics and bacterial species and strains, including clinical isolates of bacterial pathogens. We found that the lysis rate of a bacterial population linearly depends on the instantaneous growth rate of the population, regardless of how the latter is modulated. We further demonstrate that this predictive power at the population level can be explained by accounting for bacterial responses to the antibiotic treatment by single cells. This linear dependence of the lysis rate on the growth rate represents a dynamic signature associated with each bacterium–antibiotic pair and serves as the quantitative foundation for designing combination antibiotic therapy and predicting the population-structure change in a population with mixed phenotypes.

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