Pseudomonas aeruginosa gene expression changes during established biofilm infection in a cystic fibrosis lung model

The opportunistic pathogen <i>Pseudomonas aeruginosa</i> forms biofilm infections in the lungs of people with the genetic condition cystic fibrosis (CF) that can persist for decades. There are numerous <i>P. aeruginosa</i> lifestyle changes associated with chronic biofilm infection that are cued by the CF lung environment. These include a loss of virulence, metabolic changes and increased antimicrobial tolerance. We have investigated <i>P. aeruginosa</i> PA14 biofilm infection over 7 days in an <i>ex vivo</i> pig lung (EVPL) model for CF, previously shown to facilitate formation of a clinically relevant <i>P. aeruginosa</i> biofilm structure with expression of key genes comparable to human infection. We have compared <i>P. aeruginosa</i> gene expression between sequential time points: 24 h, 48 h and 7 days post-infection, and investigated tolerance to polymyxins. Our results demonstrate that the EVPL model can maintain a <i>P. aeruginosa</i> biofilm population, which exhibits increased antibiotic tolerance, for at least 7 days. Differential expression of antimicrobial resistance-associated genes was not observed; however, there was significant upregulation of sulphur metabolism and maintenance of a structured biofilm. Our findings demonstrate that 7 days is a viable time point for studying established, chronic biofilm infection in the EVPL model and provide insight into the accompanying gene expression changes.

Authors

Institutions

Publication Details

Journal
Microbiology
Published
2026-03-05
DOI
https://doi.org/10.1099/mic.0.001678
Primary Topic
Bacterial biofilms and quorum sensing
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Pseudomonas aeruginosa gene expression changes during established biofilm infection in a cystic fibrosis lung model

Ramón Garcia Maset, Niamh E. Harrington, Freya Harrison, Freya Allen
Microbiology
Bacterial biofilms and quorum sensing
article

Pseudomonas aeruginosa gene expression changes during established biofilm infection in a cystic fibrosis lung model

Ramón Garcia Maset, Niamh E. Harrington, Freya Harrison, Freya Allen
article en

Abstract

The opportunistic pathogen <i>Pseudomonas aeruginosa</i> forms biofilm infections in the lungs of people with the genetic condition cystic fibrosis (CF) that can persist for decades. There are numerous <i>P. aeruginosa</i> lifestyle changes associated with chronic biofilm infection that are cued by the CF lung environment. These include a loss of virulence, metabolic changes and increased antimicrobial tolerance. We have investigated <i>P. aeruginosa</i> PA14 biofilm infection over 7 days in an <i>ex vivo</i> pig lung (EVPL) model for CF, previously shown to facilitate formation of a clinically relevant <i>P. aeruginosa</i> biofilm structure with expression of key genes comparable to human infection. We have compared <i>P. aeruginosa</i> gene expression between sequential time points: 24 h, 48 h and 7 days post-infection, and investigated tolerance to polymyxins. Our results demonstrate that the EVPL model can maintain a <i>P. aeruginosa</i> biofilm population, which exhibits increased antibiotic tolerance, for at least 7 days. Differential expression of antimicrobial resistance-associated genes was not observed; however, there was significant upregulation of sulphur metabolism and maintenance of a structured biofilm. Our findings demonstrate that 7 days is a viable time point for studying established, chronic biofilm infection in the EVPL model and provide insight into the accompanying gene expression changes.

MicrobiologyVol. 172(3)
University of Liverpool (GB), Oxford University Press (United Kingdom) (GB), University of Warwick (GB), University of Oxford (GB), Biology of Infection (FR), Science Oxford (GB)
University of Warwick, Medical Research Council, Biotechnology and Biological Sciences Research Council
Good health and well-being
Openalex Percentile: Top 32%
Bacterial biofilms and quorum sensing
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.