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基于超高效液相色谱-轨道阱融合质谱和解吸电喷雾电离质谱成像的空间代谢组学方法揭示生百部与蜜百部化学成分的差异

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.

作者信息

Xiong Haixuan, Sun Shuding, Zhang Weiwei, Zhao Di, Liu Xuefang, Tian Yange, Feng Suxiang

机构信息

Henan University of Chinese Medicine, Zhengzhou, China.

Collaborative Innovation Center for Chinese Medicine and Respiratory Diseases Co-constructed by Henan Province and Education Ministry of P. R. China, Zhengzhou, China.

出版信息

Phytochem Anal. 2025 Jan;36(1):166-180. doi: 10.1002/pca.3428. Epub 2024 Jul 28.

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.

摘要

引言

百部是一种重要的传统中药,以其止咳和杀虫特性而闻名。在临床实践中,百部通常在用作药物之前进行炮制。目前,百部的常规炮制方法是蜜炙。然而,蜜炙前后百部化学成分的具体变化尚不清楚。

目的

本研究旨在分析蜜炙前后百部化学成分的变化,并研究差异标志物在根部的分布。

方法

采用超高效液相色谱-轨道阱融合质谱联用分子网络分析方法,对百部和蜜炙百部的代谢组进行分析,并通过多元统计分析筛选差异代谢物。应用空间代谢组学通过解吸电喷雾电离质谱成像(DESI-MSI)研究差异代谢物的分布。

结果

百部和蜜炙百部表现出显著差异,分别鉴定出56种和61种化学成分。炮制后,生物碱种类减少,从共同化合物中筛选出12种差异代谢物。显著的成分变化有表双脱氢百部碱J、新百部碱、百部碱、异百部碱、新异百部碱等。质谱成像可视化了差异代谢物的空间分布。

结论

本研究为百部中代谢物的鉴定和空间分布提供了一种快速有效的可视化方法。与传统方法相比,该方法提供了更有说服力的数据,从宏观角度支持了百部炮制机制的研究。

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