化学
仿形(计算机编程)
串联
串联质谱法
新陈代谢
糖酵解
色谱法
质谱法
高分辨率
生物化学
计算机科学
材料科学
遥感
复合材料
地质学
操作系统
作者
Kristian Serafimov,Maria Virginia Giolito,Sébastien Ibanez,Ophélie Renoult,Sarah Srhir,Paula Varon Rugeles,Florine Laloux-Morris,Cyril Corbet,Julien Pierrard,Marc Van den Eynde,Michael Lämmerhofer,Olivier Féron
标识
DOI:10.1101/2025.07.04.663184
摘要
ABSTRACT We present UCL-MetIsoLib, a publicly accessible high-resolution tandem mass spectrometry (HRMS/MS) library developed for HILIC-based, ion-pairing free, isomer-resolved metabolomics using a bioinert UHPLC system and the Acquity Premier BEH Amide column. The platform integrates two complementary methods operating under distinct chromatographic conditions (pH 3.5, ESI+; pH 11.0, ESI−), enabling broad metabolic coverage. A total of 334 metabolites are annotated in the library structure, with thiol derivatization incorporated into the extraction protocol to mitigate redox-driven artifacts. Metabolite identification is supported by 245 authentic reference standards and curated according to MSI Level 1 and Level 2 criteria. Validation followed FDA guidelines for bioanalytical method validation and was performed across five biological matrices—urine, plasma, tissues, cultured cells, and patient-derived colorectal organoids—with a U- 13 C, U- 15 N-labeled Amino Acid Mixture used as an isotope labeled internal standard. The method demonstrated high precision (<15% RSD intra-/inter-day) and recovery (85–115% across all QC levels). To demonstrate biological applicability, UCL-MetIsoLib was applied to a case study comparing healthy and colorectal cancer-derived organoids. The method enabled confident annotation of metabolite isomers, including key glycolytic intermediates such as DHAP and GA3P, as well as sugar phosphates from the glycolysis and pentose phosphate pathways. Metabolic alterations were observed in tumor organoids, including accumulation of nucleotide derivatives and shifts in central carbon metabolism. These findings emphasize the value of isomer-resolved spectral libraries in detecting biologically meaningful differences that are often missed in conventional untargeted metabolomics workflows.
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