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Spatial metabolomics method to reveal the differences in chemical composition of raw and honey‐fried Stemona tuberosa Lour. by using UPLC‐Orbitrap Fusion MS and desorption electrospray ionization mass spectrometry imaging

化学 轨道轨道 代谢组学 质谱法 色谱法 电喷雾电离 代谢组 解吸电喷雾电离 化学电离 电离 有机化学 离子
作者
Haixuan Xiong,Shuding Sun,Weiwei Zhang,Di Zhao,Xuefang Liu,Yange Tian,Suxiang Feng
出处
期刊:Phytochemical Analysis [Wiley]
卷期号:36 (1): 166-180
标识
DOI:10.1002/pca.3428
摘要

Abstract Introduction Stemona tuberosa Lour. (ST) is a significant traditional Chinese medicine (TCM) renowned for its antitussive and insecticidal properties. ST is commonly subjected to processing in clinical practice before being utilized as a medicinal substance. Currently, the customary technique for processing ST is honey‐fried. Nevertheless, the specific variations in chemical constituents of ST before and after honey‐fried remain unclear. Objective This work aimed to analyze the variations in chemical constituents of ST before and after honey‐fried and to study the distribution of differential markers in the roots. Methods UPLC‐Orbitrap Fusion MS combined with molecular network analysis was used to analyze the metabolome of ST and honey‐fried ST (HST) and to screen the differential metabolites by multivariate statistical analysis. Spatial metabolomics was applied to study the distribution of differential metabolites by desorption electrospray ionization mass spectrometry imaging (DESI‐MSI). Results The ST and HST exhibited notable disparities, with 56 and 61 chemical constituents found from each, respectively. After processing, the types of alkaloids decreased, and 12 differential metabolites were screened from the common compounds. The notable component variations were epibisdehydro‐tuberostemonine J, neostenine, tuberostemonine, croomine, neotuberostemonine, and so forth. MSI visualized the spatial distribution of differential metabolites. Conclusions Our research provided a rapid and effective visualization method for the identification and spatial distribution of metabolites in ST. Compared with the traditional method, this method offered more convincing data supporting the processing mechanism investigations of Stemona tuberosa from a macroscopic perspective.
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