Kurilung Alongkorn, Limjiasahapong Suphitcha, Wanichthanarak Kwanjeera, Manokasemsan Weerawan, Kaewnarin Khwanta, Duangkumpha Kassaporn, Manocheewa Siriphan, Tansawat Rossarin, Chaiteerakij Roongruedee, Nookaew Intawat, Sirivatanauksorn Yongyut, Khoomrung Sakda
Siriraj Center of Research Excellence in Metabolomics and Systems Biology (SiCORE-MSB), Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
Comput Struct Biotechnol J. 2025 Jul 10;27:3079-3089. doi: 10.1016/j.csbj.2025.07.009. eCollection 2025.
This study presents the development and validation of a liquid chromatography-quadrupole-time-of-flight mass spectrometry method with data-independent acquisition (LC-QTOF-MS) for targeted quantification, post-targeted screening, and untargeted metabolite profiling. Using MS-based precursor ion quantification, the method demonstrated excellent analytical performance with linearity (² > 0.99), accuracy (84 %-131 %), and precision (1 %-17 % relative standard deviation (RSD)). Although LC-QTOF‑MS sensitivity is at least nine-fold lower than LC-triple quadrupole MS with multiple reaction monitoring, it remains adequate for quantifying urinary metabolites, particularly those that fragment poorly or yield low‑intensity product ions. For post‑targeted screening and untargeted profiling, an in‑house reference library (the Siriraj Metabolomics Data Warehouse, SiMD), comprising 174 curated metabolite standards, was integrated into the workflow to enhance metabolite identification confidence. The official website for SiMD can be accessed at https://si-simd.com/. To demonstrate the method's utility, 11 amino and organic acids were quantified in urine samples from 100 healthy individuals. Four compounds-L-methionine, L-histidine, L-tryptophan, and -ferulic acid-were significantly higher levels in females ( < 0.05), likely reflecting sex-specific physiological or dietary intake differences. Post‑targeted screening identified 29 additional metabolites and assigned them to level 1 (/, RT, isotope pattern, and MS/MS spectra matched to reference standards) based on the Metabolomics Standards Initiative guidelines. Untargeted retrospective profiling revealed level 1 seven metabolites, including ribitol, creatine, glucuronic acid, -ferulic acid, succinic acid, dimethylglycine, and 3-hydroxyphenylacetic acid related to sex variation (VIP > 1.5). In summary, the LC-QTOF-MS method coupled with SiMD provides a robust and comprehensive workflow for metabolomics analysis. It enables reliable target quantification and enhances confidence in metabolite identification while also reducing sample and instrumental demands. These features make it particularly well-suited for clinical metabolomics studies.
本研究介绍了一种采用数据非依赖采集的液相色谱-四极杆-飞行时间质谱法（LC-QTOF-MS）用于靶向定量、靶向后筛选和非靶向代谢物谱分析的方法的开发与验证。该方法采用基于质谱的前体离子定量，展现出优异的分析性能，线性关系良好（R²>0.99），准确度高（84 %-131 %），精密度佳（相对标准偏差（RSD）为1 %-17 %）。尽管LC-QTOF-MS的灵敏度比具有多反应监测功能的LC-三重四极杆质谱至少低九倍，但仍足以对尿液代谢物进行定量，特别是那些裂解不佳或产生低强度产物离子的代谢物。对于靶向后筛选和非靶向谱分析，一个包含174种经整理的代谢物标准品的内部参考库（诗里拉吉代谢组学数据仓库，SiMD）被整合到工作流程中，以提高代谢物鉴定的可信度。SiMD的官方网站可通过https://si-simd.com/访问。为证明该方法的实用性，对100名健康个体尿液样本中的11种氨基酸和有机酸进行了定量。四种化合物——L-甲硫氨酸、L-组氨酸、L-色氨酸和阿魏酸——在女性中的水平显著更高（P<0.05），这可能反映了性别特异性的生理或饮食摄入差异。靶向后筛选鉴定出另外29种代谢物，并根据代谢组学标准倡议指南将它们归类为1级（保留时间、同位素模式和MS/MS光谱与参考标准匹配）。非靶向回顾性谱分析揭示了7种1级代谢物，包括与性别差异相关的核糖醇、肌酸、葡萄糖醛酸、阿魏酸、琥珀酸、二甲基甘氨酸和3-羟基苯乙酸（VIP>1.5）。总之，LC-QTOF-MS方法与SiMD相结合为代谢组学分析提供了一个强大而全面的工作流程。它能够进行可靠的靶向定量，提高代谢物鉴定的可信度，同时还减少了对样品和仪器的需求。这些特性使其特别适合临床代谢组学研究。
