CpxR activates MexAB-OprM efflux pump expression and enhances antibiotic resistance in both laboratory and clinical nalB-type isolates of Pseudomonas aeruginosa

Resistance-Nodulation-Division (RND) efflux pumps are responsible for multidrug resistance in Pseudomonas aeruginosa. In this study, we demonstrate that CpxR, previously identified as a regulator of the cell envelope stress response in Escherichia coli, is directly involved in activation of expression of RND efflux pump MexAB-OprM in P. aeruginosa. A conserved CpxR binding site was identified upstream of the mexA promoter in all genome-sequenced P. aeruginosa strains. CpxR is required to enhance mexAB-oprM expression and drug resistance, in the absence of repressor MexR, in P. aeruginosa strains PA14. As defective mexR is a genetic trait associated with the clinical emergence of nalB-type multidrug resistance in P. aeruginosa during antibiotic treatment, we investigated the involvement of CpxR in regulating multidrug resistance among resistant isolates generated in the laboratory via antibiotic treatment and collected in clinical settings. CpxR is required to activate expression of mexAB-oprM and enhances drug resistance, in the absence or presence of MexR, in ofloxacin-cefsulodin-resistant isolates generated in the laboratory. Furthermore, CpxR was also important in the mexR-defective clinical isolates. The newly identified regulatory linkage between CpxR and the MexAB-OprM efflux pump highlights the presence of a complex regulatory network modulating multidrug resistance in P. aeruginosa.

Analysis of expression quantitative trait loci in D. melanogaster

Expression Quantitative Trait Loci (eQTL) analysis allows for the identification of genetic variation associated with variation in gene expression. It is often unclear however, which of the associated variants are causal, and by what mechanism. Integrating functional genomic data with eQTL data can provide insight into the impact of natural variation in the population, and the nature of the transcriptional machinery itself. In this thesis, I integrate functional genomic data with eQTL data derived from both 5’ CAGE and 3’ TagXseq expression assays, in developing embryos. I first use both datasets to analyse the transcription landscape in embryonic D., melanogaster, and then carry out an analysis of sequence motifs associated with transcription factor binding sites, promoters, and 3’ polyadenylation sites. Finally, I integrate functional genomic data, including these novel sequence motifs, to shed light on the mechanisms of gene expression variation in D.,melanogaster. I am able to demonstrate that some variants effecting gene regulation in Drosophila are found within haplotypes which buffer their effects.