Abstract
Pseudomonas aeruginosa causes a wide range of infections. Ciprofloxacin is one of the most widely used antibiotics for the treatment of these infections. Antibiotic resistance in P. aeruginosa has made its eradication complicated and commonly leads to treatment failures. The genetic basis of ciprofloxacin resistance in P. aeruginosa is partially understood and a more complete understanding may improve chemotherapeutic regimens for treatment of this pathogen.
The overall aim of this thesis was to identify genes associated with ciprofloxacin resistance. Ciprofloxacin-resistant mutants were obtained from an antibiotic sensitive reference strain, P. aeruginosa PAO1, through experimental evolution, and genomic analysis of mutants was carried out. Mutations were found in gyrA, parC, parE, and nfxB, which are genes previously associated with ciprofloxacin resistance, and in genes not previously known to be associated with resistance such as PA3491, and pil genes. The mutation in gyrA was a key determinant of ciprofloxacin resistance. Mutation in the PA3491 gene was shown to be involved in increasing the ciprofloxacin resistance for the first time and was shown to influence the expression of the mexCD efflux pump genes. To quantify the contribution of mutations to ciprofloxacin resistance, mutations were engineered into the PAO1 genome individually and in multiple combinations, and Minimum Inhibitory Concentration (MIC) testing was carried out. Combinations of multiple mutations led to the high level of resistance. MICs of engineered mutants showed that gene-gene interactions were involved in the development of a high level of ciprofloxacin resistance. This information was used to predict the resistance of 237 clinical isolates through analysis of their genome sequences. 71%, 24%, and 7% clinical isolates had actual MICs equal, greater, and less than the predicted MICs, respectively.
Overall, this study enhanced our understanding of the genetic basis of ciprofloxacin resistance evolution in P. aeruginosa. This study has also shown that gene-gene interactions can play an important role in antibiotic resistance and can be successfully incorporated into models predicting resistance phenotype.