Abstract
Pseudomonas aeruginosa (PA) is an opportunistic pathogen that causes diverse human infections including chronic airway infection in patients with cystic fibrosis (CF). Comparing the genomes of CF and non-CF PA isolates has great potential to identify the genetic basis of pathogenicity. To gain a deeper understanding of PA adaptation in CF airways, we performed a genome-wide association study (GWAS) on 1,001 PA genomes. Genetic variations identified among CF isolates were categorized into (i) alterations in protein-coding regions, either large- or small-scale, and (ii) polymorphic variation in intergenic regions. We introduced each CF-associated genetic alteration into the genome of PAO1, a prototype PA strain, and validated the outcomes experimentally. Loci readily mutated among CF isolates included genes encoding a probable sulfatase, a probable TonB-dependent receptor (PA2332~PA2336), L-cystine transporter (YecS, PA0313), and a probable transcriptional regulator (PA5438). A promoter region of a heme/hemoglobin uptake outer membrane receptor (PhuR, PA4710) was also different between the CF and non-CF isolate groups. Our analysis highlights ways in which the PA genome evolves to survive and persist within the context of chronic CF infection.
Highlights
Pseudomonas aeruginosa (PA) is an ubiquitous gram-negative bacterium that can cause disease in plants and animals [1]
We compared a large set of genomes from clinical PA isolates (CF vs. non-cystic fibrosis (CF)) and identified mutations that occurred differentially in either CF or non-CF isolates using genome-wide association study (GWAS) based on 31-mer counting (Fig 8)
We found no evidence that mutations in LasR or other QS-related proteins were significantly overrepresented in CF or non-CF isolates
Summary
Understanding how human pathogens, such as Pseudomonas aeruginosa (PA), adapt to the host environment during prolonged infections can provide important information for the treatment of disease. We compared the genome sequences of PA isolates from cystic fibrosis (CF) and non-CF patients and identified genetic variation that was significantly associated with CF disease. Our bioinformatics analyses, linked with experimental validation via genetic manipulation and phenotypic investigation of mutants, provides novel insights into the genomic plasticity of PA during chronic CF infection
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