UPLC-Q-TOF/MS based metabolite profiling and quality marker constituents screening of root, stem and rhizome extracts of Ilex asprella

根茎 代谢物 色谱法 化学成分 茎叶展示 化学 代谢组 次生代谢物 传统医学 高效液相色谱法 内胚层 代谢组学 生物 植物 生物化学 医学 基因
作者
Lulu Wang,Zhechen Fan,Siyi Ma,Shiyu Wu,Chi Ma,Hua‐Wu Zeng,Xi‐Ke Xu,Qing Ma,Ji Ye
出处
期刊:Fitoterapia [Elsevier BV]
卷期号:173: 105832-105832 被引量:8
标识
DOI:10.1016/j.fitote.2024.105832
摘要

The root of Ilex asprella (RIA) is a popular plant resource for treating inflammation-related diseases. The purpose of this study was to identify the secondary metabolites, to compare anti-inflammatory effects and to determine the quality marker components among root, stem and rhizome sections of IA. Chemical fingerprints of stem, root and rhizome of IA was determined by high performance liquid chromatography (HPLC). A reliable method using ultra performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-QTOF/MS) was established for comprehensively determining the chemical constituents of the plants. Anti-inflammatory activities of IA and its ingredients were screened by in vivo mouse ear swelling and in vitro LPS-induced release of NO from RAW264.7 cells experiments. Root, stem and rhizome of IA have shown high similarity in chemical fingerprints. Totally 149 compounds were characterized in IA, including triterpenoids, triterpenoid saponins, phenolic acids and lignans. 44 of them were identified based on co-occurring Mass2Motifs, including 19 unreported ones, whilst 17 were tentatively confirmed by comparison with reference compounds. No significant anti-inflammatory activity difference among root, stem and rhizome parts of IA was found. Ilexsaponin B2, protocatechualdehyde, isochlorogenic acid B and quinic acid, were screened out as quality marker compounds in IA. A sensitive and rapid strategy was established to evaluate the differences on secondary metabolites of different parts of IA for the first time, and this study may contribute to the quality evaluation of medicinal herbs and provide theoretically data support for further analysis of different parts of IA.
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