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Untargeted Liquid Chromatography-Mass Spectrometry-Based Metabolomics Analysis of Wheat Grain
Published on: March 13, 2020
Establishment of Liquid Chromatography Retention Index Based on Chemical Labeling for Metabolomic Analysis
Shu-Jian Zheng1, Shi-Jie Liu1, Quan-Fei Zhu1
1Key Laboratory of Analytical Chemistry for Biology and Medicine (Ministry of Education), Department of Chemistry , Wuhan University , Wuhan , Hubei 430072 , P.R. China.
Abstract:
Chemical labeling (CL) in combination with liquid chromatography-mass spectrometry (LC-MS) analysis has been demonstrated to be a promising technology in metabolomic analysis. However, identification of chemically labeled metabolites remains to be challenging. Retention time (RT) is one of the most important parameters for the identification of metabolites, but it could vary greatly in LC-MS analysis. In this work, we developed a chemical labeling-based HPLC retention index (CL-HPLC RI) strategy to facilitate the identification of metabolites. In this CL-HPLC RI strategy, a series of 2-dimethylaminoethylamine (DMED)-labeled fatty acids were used as calibrants to establish RIs for DMED-labeled carboxylated compounds and a series of 4-( N, N-dimethylamino)phenyl isothiocyanate (DMAP)-labeled fatty amines were used as calibrants for DMAP-labeled amine compunds. To calculate the RIs, the whole LC chromatogram was divided into 24 time intervals by 23 DMED-labeled fatty acid standards or 15 time intervals by 14 DMAP-labeled fatty amine standards. Then, we established the RIs of 854 detected DMED-labeled carboxylated metabolites and 1057 DMAP-labeled amine metabolites in fecal samples and demonstrated that RIs were highly reproducible under different elution gradients, columns, and instrument systems. Finally, we applied this strategy to the identification of metabolites in human serum. Using RIs, 267 DMED-labeled carboxylated metabolites and 273 DMAP-labeled amine metabolites in human serum matched well with the fecal metabolome database. Taken together, the developed CL-HPLC RI strategy was demonstrated to be a promising method to facilitate the identification of metabolites in metabolomic analysis.
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