A large-scale whole-genome comparison shows that experimental evolution in response to antibiotics predicts changes in naturally evolved clinical .

is an opportunistic pathogen that causes a wide range of acute and chronic infections. An increasing number of isolates have mutations that make them antibiotic resistant, making treatment difficult. To identify resistance-associated mutations we experimentally evolved the antibiotic sensitive strain PAO1 to become resistant to three widely used anti-pseudomonal antibiotics, ciprofloxacin, meropenem and tobramycin. Mutants could tolerate up to 2048-fold higher concentrations of antibiotic than strain PAO1. Genome sequences were determined for thirteen mutants for each antibiotic. Each mutant had between 2 and 8 mutations. For each antibiotic at least 8 genes were mutated in multiple mutants, demonstrating the genetic complexity of resistance. For all three antibiotics mutations arose in genes known to be associated with resistance, but also in genes not previously associated with resistance. To determine the clinical relevance of mutations uncovered in this study we analysed the corresponding genes in 558 isolates of from patients with chronic lung disease and in 172 isolates from the general environment. Many genes identified through experimental evolution had predicted function-altering changes in clinical isolates but not in environmental isolates, showing that mutated genes in experimentally evolved bacteria can predict those that undergo mutation during infection. Additionally, large deletions of up to 479kb arose in experimentally evolved meropenem resistant mutants and large deletions were present in 87 of the clinical isolates. These findings significantly advance understanding of antibiotic resistance in and demonstrate the validity of experimental evolution in identifying clinically-relevant resistance-associated mutations.