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Updated: Jan 10, 2026

Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry UPLC-MS
Published on: March 14, 2013
Expanding Metabolome Coverage in LC-MS/MS Analysis through Hydralazine-Based Multifunctional Derivatization
Zhiye Yan1, Weiwei Tang1, Bin Li1
1State Key Laboratory of Natural Medicines and School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing 210009, China.
Abstract:
Metabolomics is a potent tool used for discovering disease biomarkers and investigating intricate mechanisms of diseases by analyzing metabolite changes in biological systems. However, challenges in metabolite detection have not been fully addressed due to their vast physicochemical diversity and broad concentration range, impacting comprehensive profiling of the metabolome, particularly for certain metabolites with limited detection sensitivity. Therefore, a novel chemical derivatization method based on hydralazine (HZN) was developed for highly sensitive detection of various poorly ionized small metabolites in biological samples using liquid chromatography-tandem mass spectrometry (LC-MS/MS). HZN-based multifunctional derivatization mainly targeted metabolites with carbonyl, carboxyl, and phosphoryl groups, such as free fatty acids, keto-acids, hydroxy acids, bile acids, fatty aldehydes, and phosphoryl compounds. Main parameters affecting the derivatization efficiency were investigated, such as the condensation reagent, and optimal conditions were obtained. The labeling of HZN enabled the generation of characteristic fragment ions through collision-induced dissociation, avoiding the laboriousness of deducing MS/MS fragmentation and facilitating large-scale quantitative analysis. The sensitivities of HZN-derivatized metabolites improved significantly, ranging from 10 to 5000-fold, and the limits of quantitation for derivatized metabolites varied from 5 pM to 100 nM, depending on their structures. Furthermore, alterations of various gut microbiota-derived metabolites in mice fed with a high-fat diet were unraveled using the HZN-based derivatization method, indicating its promising applications in the investigation of disease-related changes in the metabolome.
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