Differential Selection for Survival and for Growth in Adaptive Laboratory Evolution Experiments With Benzalkonium...

Biocides are used to control microorganisms across different applications, but emerging resistance may pose risks for those applications. Resistance to biocides has commonly been studied using adaptive laboratory evolution (ALE) experiments with growth at subinhibitory concentrations linked to serial subculturing. It has been shown recently that Escherichia coli adapts to repeated lethal stress imposed by the biocide benzalkonium chloride (BAC) by increased survival (i.e., tolerance) and not by evolving the ability to grow at increased concentrations (i.e., resistance). Here, we investigate the contributions of evolution for tolerance as opposed to resistance for the outcome of ALE experiments with E. coli exposed to BAC. We find that BAC concentrations close to the half maximal effective concentration (EC₅₀, 4.36 μg mL^-1) show initial killing (~40%) before the population resumes growth. This indicates that cells face a two-fold selection pressure: for increased survival and for increased growth. To disentangle the effects of both selection pressures, we conducted two ALE experiments: (i) one with initial killing and continued stress close to the EC₅₀ during growth and (ii) another with initial killing and no stress during growth. Phenotypic characterization of adapted populations showed that growth at higher BAC concentrations was only selected for when BAC was present during growth. Whole genome sequencing revealed distinct differences in mutated genes across treatments. Treatments selecting for survival-only led to mutations in genes for metabolic regulation (cyaA) and cellular structure (flagella fliJ), while treatments selecting for growth and survival led to mutations in genes related to stress response (hslO and tufA). Our results demonstrate that serial subculture ALE experiments with an antimicrobial at subinhibitory concentrations can select for increased growth and survival. This finding has implications for the design of ALE experiments to assess resistance risks of antimicrobials in different scenarios such as disinfection, preservation, and environmental pollution.