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. 2025 Mar 31;23(1):191.
doi: 10.1186/s12916-025-04009-x.

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

Dhammika Leshan Wannigama  1   2   3   4   5   6   7 , Cameron Hurst  8   9   10   11 , Peter N Monk  12 , Gunter Hartel  13 , William Graham Fox Ditcham  14 , Parichart Hongsing #  15   16 , Phatthranit Phattharapornjaroen  17   18 , Puey Ounjai  19 , Pattama Torvorapanit  20 , Kamonwan Jutivorakool  20 , Sirirat Luk-In  21 , Sumanee Nilgate  22   23 , Ubolrat Rirerm  22   23 , Chanikan Tanasatitchai  22   23   15 , Kazuhiko Miyanaga  24 , Longzhu Cui  24 , Naveen Kumar Devanga Ragupathi  25   26   27 , S M Ali Hosseini Rad  28   29 , Aisha Khatib  30 , Robin James Storer  31 , Hitoshi Ishikawa  32 , Mohan Amarasiri  33 , Somrat Charuluxananan  34 , Asada Leelahavanichkul  22   35 , Talerngsak Kanjanabuch  36   37   38   39 , Paul G Higgins #  40   41 , Jane C Davies  42   43 , Stephen M Stick #  44   45   46 , Anthony Kicic #  44   45   46   47 , Tanittha Chatsuwan  48   49 , Kenji Shibuya  50 , Shuichi Abe #  51   15
Affiliations

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

Dhammika Leshan Wannigama et al. BMC Med. .

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.

Keywords: Pseudomonas aeruginosa; Chronic infections; Chronic respiratory diseases; Clinical biomarker; Pulmonary biofilm; Respiratory infections; TesG expression.

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: The study protocol was approved (IRB No. 414/60) by the Institutional Review Board of the Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand, and was performed in accordance with the ethical standards as established in the 1964 Declaration of Helsinki and its later amendments and comparable ethical standards. For this retrospective, non-interventional study of pseudonymised clinical isolates, the requirement for informed consent from patients was waived by the Institutional Review Board (IRB No. 414/60) of the Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Confocal imaging of sputum from a patient with chronic P. aeruginosa infection a bacteria cells from strong biofilm (bacteria cells staining by PNA FISH probes; green/yellow, Hoechst blue for DNA), b strong biofilm structure only (staining with Wheat Germ Agglutinin (WGA) conjugates Alexa Fluor 488 dye; (pseudo coloured magenta), Hoechst blue for DNA), c bacteria cells from moderate biofilm (bacteria cells staining by PNA FISH probes; green/yellow, Hoechst blue for DNA), and d moderate biofilm structure only (Wheat Germ Agglutinin (WGA) conjugates Alexa Fluor 488 dye (pseudo coloured magenta), Hoechst blue for DNA). Sputum samples for images were obtained from two different patients. Survival analysis of biofilm structure (biomass) in terms of e length of hospitalisation and f length of ICU stay among patients with chronic P. aeruginosa lung infection (n = 70). g Bacterial sputum gene expression level in relation to biofilm biomass among patients with chronic P. aeruginosa lung infection (n = 70)
Fig. 2
Fig. 2
Correlation of bacterial sputum gene expression and inflammatory markers among patients with chronic P. aeruginosa lung infection (n = 70). The strength of correlation is represented by the colour intensity, with darker shades indicating stronger negative correlations
Fig. 3
Fig. 3
Correlation of bacterial sputum gene expression and bacterial virulence factors among patients with chronic P. aeruginosa lung infection (n = 70). The intensity and size of the circles indicate the strength and direction of the correlation, with darker and larger circles representing stronger correlations. c-di-GMP: (bis-(3′–5′)-cyclic diguanosine monophosphate
Fig. 4
Fig. 4
a Relationship of bacterial sputum gene expression in terms of predicting biofilm biomass and b receiver operating characteristic (ROC) curve for lasR, pelB, and tesG sputum expression in terms of predicting biofilm biomass among patients with chronic P. aeruginosa lung infection (n = 70)
See this image and copyright information in PMC

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