A quantitative approach to easily characterize and predict cell death and escape to β-lactam treatments

Abstract

To design appropriate treatments, one must be able to characterize accurately the response of bacteria to antibiotics. When exposed to β-lactam treatments, bacteria can be resistant and/or tolerant, and populations can exhibit resilience. Disentangling these phenomena is challenging and no consolidated understanding has been proposed so far. Because these responses involve processes happening at several levels, including the molecular level (e.g. antibiotic degradation), the cell physiology level (filamentation) and the population level (release of β-lactamases into the environment), quantitative modelling approaches are needed. Here, we propose a model of bacterial response to β-lactam treatments that accounts for bacterial resistance, tolerance, and population resilience. Our model can be calibrated solely based on optical density readouts, can predict the inoculum effect, and leads to a mechanistically relevant classification of bacterial response to treatments that goes beyond the classical susceptible / intermediate / resistant classification. Filamentation-mediated tolerance and collective enzyme-mediated antibiotic degradation are essential model features to explain the complex observed response of cell populations to antibiotic treatments.

An Optogenetic Toolkit for Light-Inducible Antibiotic Resistance

“…Although MIC data is an accurate assessment of cell growth in the presence of antibiotic, beta-lactam antibiotics also cause cell filamentation, which can increase optical density (OD) readings even when cells are not dividing, making bla resistance specifically important to confirm by CFU measurement. 35 However, our results using CFU counts confirm that the optical density measurements also translate to a clear difference in cell survival. 36 Overall, we found that OptoCreVvd2 can be used to precisely induce beta-lactamase resistance and identified concentrations of carbenicillin with robust differences between dark and blue-light activated expression of the bla resistance gene construct (Fig.…”

An optogenetic toolkit for light-inducible antibiotic resistance

“…1d). Although MIC data is an accurate assessment of cell growth in the presence of antibiotic, beta-lactam antibiotics also cause cell filamentation, which can increase optical density (OD) readings even when cells are not dividing, making bla resistance specifically important to confirm by CFU measurement 45 . However, our results using CFU counts confirm that the optical density measurements also translate to a clear difference in cell survival 46 .…”

“…Assay plates for measuring the MIC were prepared by performing serial dilutions of antibiotic in 100 μL M9 minimal media in 96-well plates. Low glucose media was used to reduce growth variability by creating carbon-limiting, rather than nutrient-limiting, growth conditions 45 . Antibiotic concentrations were selected to include values that spanned the MIC levels for the dark and light state cultures in each experiment.…”