tesG expression as a potential clinical biomarker for chronic Pseudomonas aeruginosa pulmonary biofilm infections.
Where this comes from
- Record sourced from PubMed, PMID 40165235.
- Also identified by DOI 10.1186/s12916-025-04009-x and PMC identifier 11959726.
- Licence recorded as CC BY-NC-ND.
- Because redistribution is not established, this page shows the abstract only. Follow the links below for the full text.
Abstract
Pseudomonas aeruginosa infections in the lungs affect millions of children and adults worldwide. To our knowledge, no clinically validated prognostic biomarkers for chronic pulmonary P. aeruginosa infections exist. Therefore, this study aims to identify potential prognostic markers for chronic P. aeruginosa biofilm lung infections. Here, we screened the expression of 11 P. aeruginosa regulatory genes (tesG, algD, lasR, lasA, lasB, pelB, phzF, rhlA, rsmY, rsmZ, and sagS) to identify associations between clinical status and chronic biofilm infection. RNA was extracted from 210 sputum samples from patients (n = 70) with chronic P. aeruginosa lung infections (mean age; 29.3-56.2 years; 33 female). Strong biofilm formation was correlated with prolonged hospital stays (212.2 days vs. 44.4 days) and increased mortality (46.2% (18)). Strong biofilm formation is associated with increased tesG expression (P = 0.001), influencing extended intensive care unit (P = 0.002) or hospitalisation stays (P = 0.001), pneumonia risk (P = 0.006), and mortality (P = 0.001). Notably, tesG expression is linked to the modulation of systemic and sputum inflammatory responses and predicts biofilm biomass. This study provides the first clinical dataset of tesG expression levels as a predictive biomarker for chronic P. aeruginosa pulmonary infections.
Medical subject headings
- Biofilms
- Pseudomonas aeruginosa
- Pseudomonas Infections
- Bacterial Proteins