Differential selection for survival and for growth in adaptive laboratory evolution experiments with benzalkonium chloride

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 E. 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 solely for survival
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 sub-inhibitory 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.