Scientific Reports · 2019 · 102 citations · 49 references
Life SciencesGeneticsMicrobiologyAntimicrobial ResistanceHost-pathogen InteractionsMicrobial PathogenesisAntibiotic ResistanceAntibiotic Resistance MechanismsBacterial PathogenesisBacterial Virulence FactorsCystic FibrosisPulmonary InfectionsAntibiotic Resistance GenesAntibiotic Resistance In Respiratory PathogensCftr Gene MutationsCftr Protein FunctionCommensal InteractionsMucus PhysiologyMucus RetentionPseudomonas Aeruginosa Resistance
Cystic fibrosis (CF) is the most common life-threatening genetic disease among Caucasians. CF patients suffer from chronic lung infections due to the presence of thick mucus, caused by cftr gene dysfunction. The two most commonly found bacteria in the mucus of CF patients are Staphylococcus aureus and Pseudomonas aeruginosa. It is well known that early-infecting P. aeruginosa strains produce anti-staphylococcal compounds and inhibit S. aureus growth. More recently, it has been shown that late-infecting P. aeruginosa strains develop commensal-like/coexistence interaction with S. aureus. The aim of this study was to decipher the impact of P. aeruginosa strains on S. aureus. RNA sequencing analysis showed 77 genes were specifically dysregulated in the context of competition and 140 genes in the context of coexistence in the presence of P. aeruginosa. In coexistence, genes encoding virulence factors and proteins involved in carbohydrates, lipids, nucleotides and amino acids metabolism were downregulated. On the contrary, several transporter family encoding genes were upregulated. In particular, several antibiotic pumps belonging to the Nor family were upregulated: tet38, norA and norC, leading to an increase in antibiotic resistance of S. aureus when exposed to tetracycline and ciprofloxacin and an enhanced internalization rate within epithelial pulmonary cells. This study shows that coexistence with P. aeruginosa affects the S. aureus transcriptome and virulence.
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Trimmomatic: a flexible trimmer for Illumina sequence data
Anthony Bolger, Marc Lohse, Björn Usadel · Bioinformatics · 2014 · 69.7K citations · Full text
HTSeq—a Python framework to work with high-throughput sequencing data
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