Protein functional domain analysis enhances genotype-phenotype associations in comparative genomic studies of .

Introduction: represents a paradigm for studies on antibiotic resistance. Nevertheless, despite the considerable number of genome sequences that have been released in recent years, there is still a paucity of knowledge regarding the genomic determinants of the typical phenotypic traits associated with pulmonary infection.

Methods: The genomes of 40 strains of were sequenced over an 8-year period (2007-2014), isolated from the sputum of a single patient with cystic fibrosis in Trentino, Italy. The same isolates were characterised for a panel of 14 phenotypes, including biofilm formation, antibiotic resistance, secretion of siderophores and virulence factors. The phylogenetic coherence of the measured phenotypes was determined in relation to the tree based on single-nucleotide polymorphisms (SNPs). Subsequently, the semantic framework for comparative functional genomics (SAPP) was employed to investigate the depletion or enrichment of specific protein functional domains within the population in relation to the observed phenotypes.

Results: The majority of our findings regarding phenotypic adaptation over time were consistent with the population structure and followed the evolutionary pathways described in the literature. However, an exact relationship between the presence of genes and specific phenotypes could not be established. The SAPP approach enabled the identification of 189 protein domains that were significantly enriched in antibiotic-resistant strains, as well as 87 domains associated with other phenotypic adaptations. In some cases, the domains were commonly associated with antibiotic resistances, for example, outer membrane efflux pumps and porins. However, we also detected a number of domains with unknown function.

Discussion: Our findings provide a foundation for a more comprehensive understanding of the phenotypic adaptations occurring during microevolution in lung environments and facilitate the identification of new targets for the design of novel antimicrobial agents.