利用质谱分子网络分析‘龙井43’茶籽皂素

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Profiling of Saponins in ‘Longjing43’Tea Seeds by Molecular Networking

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摘要

茶皂素是一类富集于山茶科植物种子中的齐墩果烷型三萜皂苷，由于其结构种类丰富且差异细微，茶皂素的分析、分离和结构鉴定始终面临较大挑战，难以高效明确茶籽中的皂素组成特征。以‘龙井43’茶树茶籽为试验材料，整合超高效液相色谱串联电喷雾-四极杆-轨道阱高分辨质谱技术、质谱分子网络分析和in silico质谱解析方法，在正离子与负离子模式下分别检测出7种和26种茶皂素。其中，正离子模式下检出成分以三萜苷元及其有机酸酯类化合物为主，而负离子模式下以含有三萜苷元、糖基和有机酸为结构特征的典型茶皂素为主。研究结果表明，上述技术的结合可以显著提升茶皂素的分析效率，且质谱的离子化模式对茶皂素的侦测具有偏向性。本研究为茶籽中茶皂素的定性和定量研究提供了新的技术路径与思路。

Abstract

Theasaponins are a class of oleanane-type triterpenoid saponins enriched in seeds of Theaceae plants. The high structural diversity but tiny structural differences among theasaponins are challenging analysis, isolation and structural identification of them, making it difficult for the industry to efficiently characterize the saponin profiles in tea seeds. In this study, using seeds from tea cultivar ‘Longjing43’as experimental material, ultra-high performance liquid chromatography coupled with electrospray ionization quadrupole-orbitrap high-resolution mass spectrometer (UPLC/ESI-Q-Orbitrap MS), molecular networking, and in silico mass spectrometral data processing were employed. A total of 7 and 26 theasaponins were detected in positive and negative ion modes, respectively. Among these, the compounds detected in the positive ion mode were mainly triterpenoid aglycones and their organic acid esters, whereas those detected in the negative ion mode were primarily typical teasaponins characterized by structures containing triterpene aglycones, glycosyl groups and organic acids. The combination of these techniques significantly enhanced the efficiency of theasaponin analysis and the ionization mode of mass spectrometer exhibited a bias in the detection of teasaponins. This study provided a new technical way and perspective for qualitative and quantitative research on theasaponins.

导出引用

郭亮^{1, 2}, 常娅¹, 孔亚帅¹, 高颖², 凌铁军¹. 利用质谱分子网络分析‘龙井43’茶籽皂素[J]. 茶叶科学. 0

GUO Liang^{1, 2}, CHANG Ya¹, KONG Yashuai¹, GAO Ying², LING Tiejun¹. Profiling of Saponins in ‘Longjing43’Tea Seeds by Molecular Networking[J]. Journal of Tea Science. 0

中图分类号： S571.1 O657.63

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