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Pseudomonas aeruginosa is known to undergo genomic changes during chronic lung infections of cystic fibrosis patients. Perhaps the most notable and obvious phenotypic change is the switch to the mucoid phenotype caused by frameshift mutations in the mucA gene leading to the over-production of alginate. In the present work we used the mucoid phenotype as evidence of genetic adaptation to the CF lung and sequenced three mucoid strains and their non-mucoid progenitors along with four well known environmental isolates. A variety of comparative genomics software packages including IslandViewer, PanSeq and CCT were used to analyse the data allowing the determination of the core genome phylogeny and identification of pathogenicity islands. The mucoid strains exhibited significantly decreased virulence in the Galleria mellonella infection assay as well as decreased twitching motility. All three mucoid strains showed evidence of genome shrinkage as part of the host adaptation process, typically involving the loss of genomic islands and phages. In order to determine the relative contributions of individual gene loss, we transduced the relevant mutation from the PA14 non-redundant mutant library into the isogenic non-mucoid progenitor strains using phage ϕPA3. We also applied HPLC-MS metabolomics analysis to the CF isolates grown in artificial sputum medium in order to interpret genomic differences. This metabolomics profiling revealed widespread differences including the observations that mucoid strains had significantly lower surfactant and siderophore levels relative to their non-mucoid progenitor strain. Analysis of over 1400 metabolites using Metaboanalyst 2.0 revealed both strain and phenotype specific clustering. Current analysis is aimed at identifying metabolomic changes that are strain specific versus those that are related to the mucA (and other) mutations. We anticipate that this combination of methods represents a valuable tool for biomarker discovery in the context of chronic P. aeruginosa infections in CF.