title: Reverse engineering antibiotic sensitivity in a multidrug-resistant Pseudomonas aeruginosa isolate.
abstract: Antibiotic resistance is a pervasive and growing clinical problem. We describe an evaluation of a reverse engineering approach for identifying cellular mechanisms and genes that could be manipulated to increase antibiotic sensitivity in a resistant Pseudomonas aeruginosa isolate. We began by chemically mutating a broadly resistant isolate of P. aeruginosa and screening for mutants with increased sensitivity to the aminoglycoside amikacin, followed by performing whole-genome transcriptional profiling of the mutant and wild-type strains to characterize the global changes occurring as a result of the mutations. We then performed a series of assays to characterize the mechanisms involved in the increased sensitivity of the mutant strains. We report four primary results: (i) mutations that increase sensitivity occur at a high frequency (10(-2)) relative to the frequency of those that increase resistance (10(-5) to 10(-10)) and occur at a frequency 10(4) higher than the frequency of a single point mutation; (ii) transcriptional profiles were altered in sensitive mutants, resulting in overall expression patterns more similar to those of the sensitive laboratory strain PAO1 than those of the parental resistant strain; (iii) genes found from transcriptional profiling had the more dramatic changes in expression-encoded functions related to cellular membrane permeability and aminoglycoside modification, both of which are known aminoglycoside resistance mechanisms; and finally, (iv) even though we did not identify the specific sites of mutation, several different follow-up MIC assays suggested that the mutations responsible for increased sensitivity differed between sensitive mutants.
authors.affiliation: Department of Chemical and Biological Engineering, University of Colorado, Boulder, CO 80309, USA.
authors.forename: Julie M
authors.initials: JM
authors.lastname: Struble
authors.forename: Ryan T
authors.initials: RT
authors.lastname: Gill
mesh_terms: D000583:Amikacin / Q000494:pharmacology; D000900:Anti-Bacterial Agents / Q000494:pharmacology*; D001426:Bacterial Proteins / Q000235:genetics / Q000378:metabolism; D024901:Drug Resistance, Multiple, Bacterial / Q000235:genetics; D020869:Gene Expression Profiling; D005818:Genetic Engineering / Q000379:methods; D006801:Humans; D008826:Microbial Sensitivity Tests; D009154:Mutation; D011550:Pseudomonas aeruginosa / Q000187:drug effects* / Q000235:genetics; D014158:Transcription, Genetic
chemical_list: D000900:Anti-Bacterial Agents; D001426:Bacterial Proteins; D000583:Amikacin