Pulmonary metabolic changes in a rabbit model of Pseudomonas aeruginosa pneumonia: insights from metabolomic analysis.

Abstract

Background: The current problem associated with Pseudomonas aeruginosa (PA) pneumonia, which is frequently encountered in clinical settings, is drug resistance. If Pseudomonas aeruginosa pneumonia can be rapidly diagnosed in early stage, the occurrence of drug resistance can be reduced. Therefore, our study aimed to investigate pulmonary metabolic changes associated with PA pneumonia and to identify relevant metabolic biomarkers and key metabolic pathways, providing a reference for rapid diagnosis.

Methods: Eighteen rabbits were randomly assigned to either the PA or normal saline (NS) group. Bronchoalveolar lavage fluid (BALF) was analyzed via untargeted liquid chromatography-mass spectrometry (ULCMS) to identify and analyze differentially abundant metabolites between the groups. Univariate comparisons were performed using Student's t-test, while multivariate patterns were analyzed via principal component analysis (PCA) and orthogonal projections to latent structure-discriminant analysis(OPLS-DA).

Results: Successful modeling was achieved in 17 rabbits (8 PAs, 9 NSs). The most abundant metabolite classes detected in BALF were lipids and lipid-like molecules, organoheterocyclic compounds, and benzenoids. A total of 2,451 differentially abundant metabolites were identified, including 1,205 upregulated and 1,210 downregulated metabolites. Key metabolic pathways such as histidine metabolism, arginine and proline metabolism, nucleotide metabolism, and ABC transporters were upregulated in the PA group, whereas choline metabolism in the cancer pathway was downregulated.

Conclusion: PA pneumonia induces distinctive metabolic alterations in the lungs, highlighting potential biomarkers and pathways that could provide valuable insights for clinical diagnosis and treatment.

Clinical trial number: Not applicable.