Database-assisted global metabolomics has received growing attention due to its capability for unbiased identification of metabolites in various biological samples. Herein, we established a mass spectrometry (MS)-based database-assisted global metabolomics method and investigated metabolic distance between pleural effusion induced by tuberculosis and malignancy, which are difficult to be distinguished due to their similar clinical symptoms. The present method utilized a liquid chromatography (LC) system coupled with high resolution mass spectrometry (MS) working on full scan and data dependent mode for data acquisition. Unbiased identification of metabolites was performed through mass spectral searching and then confirmed by using authentic standards. As a result, a total of 194 endogenous metabolites were identified and 33 metabolites were found to be differentiated between tuberculous and malignant pleural effusions. These metabolites involved in tryptophan catabolism, bile acid biosynthesis, and β-oxidation of fatty acids, provided non-invasive biomarkers for differentiation of the pleural effusion samples with high sensitivity and specificity.
Scopus Subject Areas
- Database-assisted global metabolomics
- Mass spectrometry
- Non-invasive biomarker
- Pleural effusion