#AI reads Urine# Comparative evaluation of comprehensive offline 2D-LC strategies coupled to MS for untargeted metabolomic studies of human urine

The paper focuses on untargeted metabolomic studies of human urine and conducts a comparative evaluation of comprehensive offline two-dimensional liquid chromatography (2D-LC) strategies coupled with mass spectrometry (MS). It first points out that liquid chromatography-mass spectrometry (LC-MS) has high coverage potential in metabolomic research, but a single chromatographic mode is difficult to cover metabolites with a wide polarity range. Then, it selects an offline 2D-LC system that uses the mixed reversed-phase/ion-exchange (RP/IEX) mode as the first dimension (1D) and hydrophilic interaction liquid chromatography (HILIC) as the second dimension (2D), and explores the effects of different fraction treatment methods (dilution, concentration, drying and redissolution, direct transfer) during fraction transfer. Additionally, it compares this system with methods such as direct flow injection (DFI), one-dimensional LC (1D-LC), and serial LC in terms of the number of detectable metabolite features. Finally, it concludes that the offline RP/IEX×HILIC-MS method with direct transfer of 5 μL of untreated fractions performs optimally in terms of feature count, fraction stability, and experimental workload, making it suitable for future metabolomic marker identification studies in human urine.

Anal Bioanal Chem. 2025 Nov 1. doi: 10.1007/s00216-025-06195-2.

Youhe Gao

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For earlier AI Reads Urine articles：

https://www.keaipublishing.com/en/journals/advances-in-biomarker-sciences-and-technology/ai-reads-urine/