Key Laboratory of Phytochemical R&D of Hunan Province, Key Laboratory of Chemical Biology and Traditional Chinese Medicine Research (Ministry of Education of China), Hunan Normal University, Changsha 410081, China.
College of Chemistry and Chemical Engineering, Central South University, Changsha 410083, China.
J Agric Food Chem. 2020 Sep 16;68(37):10200-10212. doi: 10.1021/acs.jafc.0c03328. Epub 2020 Sep 4.
A new chemical labeling-based LC-MS/MS approach was developed for quantitative profiling of nine canonical bases and deoxynucleosides (dNs) in natural products. Using 2-bromo-1-(4-dimethylamino-phenyl)-ethaone (BrDPE) as the tagging reagent, a previously unexploited -alkylpyrimidine derivative (Nad) was created for one-pot labeling of widescope nucleobases via a flexible bromophilic substitution under mild conditions. The derivatization notably improved the LC-MS detection sensitivity by 31-107 fold, enabling a fast dilute-and-shoot analysis of highly diluted samples. The optimized and validated method demonstrated satisfactory accuracy (87-107%), precision (RSDs < 7.5%), and recovery (89-105%) for matrix-matched standard addition. The method was applied to simultaneously determine all target analytes and four uncanonical analogues and base-modified species in seven traditional health foods, which differ in contents by up to 600-fold for discrimination among samples. Further, the base-labeled Nads exhibit a unique fragmentation signature that could be used for untargeted screening of nucleobase-containing metabolites by simplified LC-MS/MS workflow to improve quality evaluation of natural medicinal products.
建立了一种基于新化学标记的 LC-MS/MS 方法,用于对天然产物中九种典型碱基和脱氧核苷(dNs)进行定量分析。使用 2-溴-1-(4-二甲氨基苯基)乙酮(BrDPE)作为标记试剂,通过温和条件下灵活的亲溴取代反应,为广泛的碱基创建了以前未开发的 -烷基嘧啶衍生物(Nad),用于一锅法标记。衍生化显著提高了 LC-MS 检测灵敏度 31-107 倍,能够对高度稀释的样品进行快速稀释和直接进样分析。优化和验证的方法对于基质匹配标准添加具有令人满意的准确性(87-107%)、精密度(RSDs <7.5%)和回收率(89-105%)。该方法用于同时测定七种传统保健品中的所有目标分析物和四种非典型类似物和碱基修饰的物质,这些物质的含量差异高达 600 倍,可用于区分样品。此外,碱基标记的 Nad 表现出独特的碎裂特征,可用于通过简化的 LC-MS/MS 工作流程对含碱基代谢物进行非靶向筛选,以提高天然药物产品的质量评价。