tesG expression as a potential clinical biomarker for chronic Pseudomonas aeruginosa pulmonary biofilm infections

Abstract

Background: 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. Methods: 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. Results: 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. Conclusions: This study provides the first clinical dataset of tesG expression levels as a predictive biomarker for chronic P. aeruginosa pulmonary infections.