Intrinsic Antimicrobial Resistance Determinants in the Superbug Pseudomonas aeruginosa

ABSTRACT Antimicrobial-resistant bacteria pose a serious threat in the clinic. This is particularly true for opportunistic patho-gens that possess high intrinsic resistance. Thoughmany studies have focused on understanding the acquisition of bacterial re-sistance upon exposure to antimicrobials, the mechanisms controlling intrinsic resistance are not well understood. In this study, we subjected the model opportunistic superbug Pseudomonas aeruginosa to 14 antimicrobials under highly controlled condi-tions and assessed its response using expression- and fitness-based genomic approaches. Our results reveal that gene expression changes andmutant fitness in response to sub-MIC antimicrobials do not correlate on a genomewide scale, indicating that gene expression is not a good predictor of fitness determinants. In general, fewer fitness determinants were identified for antiseptics and disinfectants than for antibiotics. Analysis of gene expression and fitness data together allowed the prediction of antagonis-tic interactions between antimicrobials and insight into the molecular mechanisms controlling these interactions. IMPORTANCE Infections involving multidrug-resistant pathogens are difficult to treat because the therapeutic options are lim-ited. These infections impose a significant financial burden on infected patients and on health care systems. Despite years of anti-microbial resistance research, we lack a comprehensive understanding of the intrinsic mechanisms controlling antimicrobial resistance. This work uses two fine-scale genomic approaches to identify genetic loci important for antimicrobial resistance of the opportunistic pathogen Pseudomonas aeruginosa. Our results reveal that antibiotics have more resistance determinants than antiseptics/disinfectants and that gene expression upon exposure to antimicrobials is not a good predictor of these resistanc