Chemoselective Metabolomics via a Modular Reactivity‐Encoding Platform

Understanding disease-associated metabolic reprogramming requires comprehensive interrogation of the chemically diverse metabolome. However, conventional liquid chromatography-mass spectrometry (LC-MS) workflows analyze metabolites in a largely non-discriminatory manner, resulting in systematic underrepresentation of specific functional and reactivity classes due to heterogeneous ionization efficiencies and matrix interference. Here, we report a chemoselective metabolomics strategy based on a modular reactivity-encoding platform (MREP) that enables functional group-resolved stratification of complex metabolomes. Four orthogonally designed alkyne-tagged probes selectively derivatize carboxyl, carbonyl, amine, and thiol functionalities under compatible conditions. The encoded metabolites are subsequently immobilized via azide-alkyne cycloaddition onto a unified solid-phase capture resin, which simultaneously removes matrix components and installs a diagnostic reporter module. This integrated encoding-capture architecture achieves high reaction orthogonality, near-quantitative conversion, and robust quantitative performance across structurally diverse metabolites. The resulting triazole derivatives exhibit markedly enhanced ionization efficiencies and generate a universal reporter-ion, enabling confident submetabolome classification and reconstruction. Application to serum and liver tissues from mice substantially expands the detectable chemical space, yielding 7 208 features and 1 573 annotated metabolites across four functional group-defined layers. Collectively, this work establishes the MREP framework as a versatile platform for reactivity-resolved interrogation of complex small-molecule systems.

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Journal
Advanced Science
Published
2026-07-17
DOI
https://doi.org/10.1002/advs.76599
Primary Topic
Click Chemistry and Applications
Type
article
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article

Chemoselective Metabolomics via a Modular Reactivity‐Encoding Platform

Jia-Yue Liu, Ru-Jie Yang, Min Ren, Jian‐Bo Wan et al.
Advanced Science
Click Chemistry and Applications
article

Chemoselective Metabolomics via a Modular Reactivity‐Encoding Platform

Jia-Yue Liu, Ru-Jie Yang, Min Ren, Jian‐Bo Wan, Hui Li, Kang-hui Wang, Rui‐Xue Hu, Xin Tao, Cang‐Man Zhang, Zhuo‐Ling Zhong, Jun‐Yi Zhou
article en

Abstract

Understanding disease-associated metabolic reprogramming requires comprehensive interrogation of the chemically diverse metabolome. However, conventional liquid chromatography-mass spectrometry (LC-MS) workflows analyze metabolites in a largely non-discriminatory manner, resulting in systematic underrepresentation of specific functional and reactivity classes due to heterogeneous ionization efficiencies and matrix interference. Here, we report a chemoselective metabolomics strategy based on a modular reactivity-encoding platform (MREP) that enables functional group-resolved stratification of complex metabolomes. Four orthogonally designed alkyne-tagged probes selectively derivatize carboxyl, carbonyl, amine, and thiol functionalities under compatible conditions. The encoded metabolites are subsequently immobilized via azide-alkyne cycloaddition onto a unified solid-phase capture resin, which simultaneously removes matrix components and installs a diagnostic reporter module. This integrated encoding-capture architecture achieves high reaction orthogonality, near-quantitative conversion, and robust quantitative performance across structurally diverse metabolites. The resulting triazole derivatives exhibit markedly enhanced ionization efficiencies and generate a universal reporter-ion, enabling confident submetabolome classification and reconstruction. Application to serum and liver tissues from mice substantially expands the detectable chemical space, yielding 7 208 features and 1 573 annotated metabolites across four functional group-defined layers. Collectively, this work establishes the MREP framework as a versatile platform for reactivity-resolved interrogation of complex small-molecule systems.

Advanced Science
University of Macau (MO), Shanghai University of Traditional Chinese Medicine (CN)
Reduced inequalities
Openalex Percentile: Top 16%
Click Chemistry and Applications
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