Evolution under low antibiotic concentrations: a risk for the selection ofPseudomonas aeruginosamultidrug resistant mutants in nature
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Abstract
ABSTRACT BACKGROUND Antibiotic pollution of non-clinical environments might have a relevant impact on human health if resistant pathogens are selected. However, this potential risk is often overlooked, since drug concentrations in nature are usually below their minimal inhibitory concentrations (MICs). Albeit, antibiotic resistant bacteria can be selected even at sub-MIC concentrations, in a range that is dubbed the sub-MIC selective window, which depends on both the antibiotic and the pathogen. OBJECTIVES Determine the sub-MIC selective windows of seven antibiotics of clinical relevance in the opportunistic pathogen Pseudomonas aeruginosa and evaluate the risk for selecting resistant mutants in nature, based on published data about the amount of antimicrobials detected in natural environments. METHODS We conducted evolution experiments of P. aeruginosa PA14 in presence of sub-MIC concentrations of ceftazidime, amikacin, levofloxacin, ciprofloxacin, tetracycline, polymyxin B or imipenem, and measured drug susceptibility of the evolved populations. RESULTS Sub-MIC selective window of quinolones was the largest, and the ones of polymyxin B and imipenem, the narrowest. Clinically relevant multidrug resistant (MDR) mutants (presenting MICs above EUCAST clinical breakpoints) arose within the sub-MIC selective windows of the majority of antibiotics tested, being these phenotypes probably mediated by efflux pumps′ activity. DISCUSSION Our data show that the concentration of antibiotics reported in aquatic ecosystems -colonizable by P. aeruginosa - are, in occasions, higher than the ones able to select MDR mutants. This finding has implications for understanding the role of different ecosystems and conditions in the emergence of antibiotic resistance from a One-Health point of view. Further, it highlights the importance of delineating the sub-MIC selective windows for drugs of clinical value in pathogens with environmental niches, in order to evaluate the health risks due to antibiotic pollution of natural ecosystems and ultimately tackle antibiotic resistance.
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