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Updated: Sep 2, 2026

A Strategy for Sensitive, Large Scale Quantitative Metabolomics
Published on: May 27, 2014
A strategy for relative quantification of chiral amines in nontargeted metabolomics via formation of fixed adduct
Yuxuan Li1, Xinxin Kong1, Yihao Liu1
1Department of Pharmaceutical Analysis, College of Pharmacy of Yanbian University, Key Laboratory of Natural Medicines of the Changbai Mountain, Ministry of Education, and Department of General Surgery Yanbian University Hospital, Yanji, Jilin, 133002, China.
Abstract:
Chemical derivatization technology significantly expands the detection scope and enhances the sensitivity of untargeted metabolomics. However, the complex adduct ion formations and diverse ionization patterns of derivatized products present substantial challenges for compound screening and data interpretation. Additionally, understanding the correlations between chiral metabolites and biological systems is essential for uncovering molecular mechanisms underlying physiological processes. To address these challenges, this study developed the (S), (R)-(5-(2-(((1-((N,4-dimethylphenyl) sulfonamido) vinyl) oxy) carbonyl) pyrrolidin-1-yl)-5-oxopentyl) triphenylphosphonium ((S), (R)-TPP-BSA) and d15-(S)-TPP-BSA probes, establishing a relative quantitative non-targeted metabolomics strategy for chiral amine-containing metabolites (RQ-NMCA). RQ-NMCA facilitates the formation of stable [M]+ adduct ions of amine derivatives in mass spectrometry, enabling effective identification and analysis of chiral amine metabolites. By leveraging isotope structures, relative quantitative analysis of amine-containing metabolites between groups is achievable. In serum samples from healthy volunteers (HV) and colorectal cancer (CRC) patients, 38 significant differential amine-containing metabolites were identified, including 15 chiral amines. RQ-NMCA introduces the fixed addition ion concept into chemical labeling non-targeted metabolomics, significantly enhancing ionization efficiency while simplifying the screening and identification processes. Furthermore, the integration of chiral recognition and relative quantification approaches is pivotal for understanding the relationship between chiral amine-containing metabolites and physiological or pathological states. This technology provides a robust platform for chiral non-targeted metabolomics research and will facilitate the identification of novel biomarkers for disease diagnosis.
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