Quantitative biology of survival under antibiotic treatments.

The mathematical formulation for the dynamics of growth reduction and/or killing under antibiotic treatments has a long history. Even before the extensive use of antibiotics, attempts to model the killing dynamics of biocides were made [1]. Here, we review relatively simple quantitative formulations of the two main modes of survival under antibiotics, resistance and tolerance, as well as their heterogeneity in bacterial populations. We focus on the two main types of heterogeneity that have been described: heteroresistance and antibiotic persistence, each linked to the variation in a different parameter of the antibiotic response dynamics. Finally, we review the effects on survival of combining resistance and tolerance mutations as well as on the mode and tempo of evolution under antibiotic treatments.

Epistasis between antibiotic tolerance, persistence, and resistance mutations.

Understanding the evolution of microorganisms under antibiotic treatments is a burning issue. Typically, several resistance mutations can accumulate under antibiotic treatment, and the way in which resistance mutations interact, i.e., epistasis, has been extensively studied. We recently showed that the evolution of antibiotic resistance in Escherichia coli is facilitated by the early appearance of tolerance mutations. In contrast to resistance, which reduces the effectiveness of the drug concentration, tolerance increases resilience to antibiotic treatment duration in a nonspecific way, for example when bacteria transiently arrest their growth. Both result in increased survival under antibiotics, but the interaction between resistance and tolerance mutations has not been studied. Here, we extend our analysis to include the evolution of a different type of tolerance and a different antibiotic class and measure experimentally the epistasis between tolerance and resistance mutations. We derive the expected model for the effect of tolerance and resistance mutations on the dynamics of survival under antibiotic treatment. We find that the interaction between resistance and tolerance mutations is synergistic in strains evolved under intermittent antibiotic treatment. We extend our analysis to mutations that result in antibiotic persistence, i.e., to tolerance that is conferred only on a subpopulation of cells. We show that even when this population heterogeneity is included in our analysis, a synergistic interaction between antibiotic persistence and resistance mutations remains. We expect our general framework for the epistasis in killing conditions to be relevant for other systems as well, such as bacteria exposed to phages or cancer cells under treatment.

An Experimental Framework for Quantifying Bacterial Tolerance.

Antibiotic tolerance and persistence are often associated with treatment failure and relapse, yet are poorly characterized. In distinction from resistance, which is measured using the minimum inhibitory concentration metric, tolerance and persistence values are not currently evaluated in the clinical setting, and so are overlooked when a course of treatment is prescribed. In this article, we introduce a metric and an automated experimental framework for measuring tolerance and persistence. The tolerance metric is the minimum duration for killing 99% of the population, MDK99, which can be evaluated by a statistical analysis of measurements performed manually or using a robotic system. We demonstrate the technique on strains of Escherichia coli with various tolerance levels. We hope that this, to our knowledge, new approach will be used, along with the existing minimum inhibitory concentration, as a standard for the in vitro characterization of sensitivity to antimicrobials. Quantification of tolerance and persistence may provide vital information in healthcare, and aid research in the field.

Distinguishing between resistance, tolerance and persistence to antibiotic treatment.

Antibiotic tolerance is associated with the failure of antibiotic treatment and the relapse of many bacterial infections. However, unlike resistance, which is commonly measured using the minimum inhibitory concentration (MIC) metric, tolerance is poorly characterized, owing to the lack of a similar quantitative indicator. This may lead to the misclassification of tolerant strains as resistant, or vice versa, and result in ineffective treatments. In this Opinion article, we describe recent studies of tolerance, resistance and persistence, outlining how a clear and distinct definition for each phenotype can be developed from these findings. We propose a framework for classifying the drug response of bacterial strains according to these definitions that is based on the measurement of the MIC together with a recently defined quantitative indicator of tolerance, the minimum duration for killing (MDK). Finally, we discuss genes that are associated with increased tolerance - the 'tolerome' - as targets for treating tolerant bacterial strains.