A stepwise strategy integrating metabolomics and pseudotargeted spectrum-effect relationship to elucidate the potential hepatotoxic components in Polygonum multiflorum

被引:10
|
作者
Song, Yunfei [1 ,2 ]
Yang, Jianbo [2 ]
Hu, Xiaowen [2 ]
Gao, Huiyu [2 ]
Wang, Pengfei [2 ]
Wang, Xueting [2 ]
Liu, Yue [1 ]
Cheng, Xianlong [2 ]
Wei, Feng [2 ]
Ma, Shuangcheng [1 ,2 ]
机构
[1] Beijing Univ Chinese Med, Sch Chinese Mat Med, Beijing, Peoples R China
[2] Natl Inst Food & Drug Control, Inst Control Chinese Tradit Med & Ethn Med, Beijing, Peoples R China
基金
中国国家自然科学基金;
关键词
polygonum multiflorum; hepatotoxicity; pseudotargeted spectrum-effect relationship; plant metabolomics; mathematical model; QUALITY-CONTROL MARKERS; DISCOVERY; CANCER; (-)-EPICATECHIN; COMBINATION; MEDICINES; THUNB;
D O I
10.3389/fphar.2022.935336
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
Polygonum multiflorum (PM) Thunb., a typical Chinese herbal medicine with different therapeutic effect in raw and processed forms, has been used worldwide for thousands of years. However, hepatotoxicity caused by PM has raised considerable concern in recent decades. The exploration of toxic components in PM has been a great challenge for a long time. In this study, we developed a stepwise strategy integrating metabolomics and pseudotargeted spectrum-effect relationship to illuminate the potential hepatotoxic components in PM. First, 112 components were tentatively identified using ultraperformance liquid chromatography-quadrupole-time-of-flight-mass spectrometry (UPLC-Q-TOF-MS). Second, based on the theory of toxicity attenuation after processing, we combined the UPLC-Q-TOF-MS method and plant metabolomics to screen out the reduced differential components in PM between raw and processed PM. Third, the proposed pseudotargeted MS of 16 differential components was established and applied to 50 batches of PM for quantitative analysis. Fourth, the hepatocytotoxicity of 50 batches of PM was investigated on two hepatocytes, LO2 and HepG2. Last, three mathematical models, gray relational analysis, orthogonal partial least squares analysis, and back propagation artificial neural network, were established to further identify the key variables affecting hepatotoxicity in PM by combining quantitative spectral information with toxicity to hepatocytes of 50 batches of PM. The results suggested that 16 components may have different degrees of hepatotoxicity, which may lead to hepatotoxicity through synergistic effects. Three components (emodin dianthrones, emodin-8-O-beta-D-glucopyranoside, PM 14-17) were screened to have significant hepatotoxicity and could be used as toxicity markers in PM as well as for further studies on the mechanism of toxicity. Above all, the study established an effective strategy to explore the hepatotoxic material basis in PM but also provides reference information for in-depth investigations on the hepatotoxicity of PM.
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页数:19
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