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非靶向代谢组学分析及“商业同源性”比较诱导的生物标志物验证用于人参五个不同部位的系统化学鉴别

Nontargeted metabolomic analysis and "commercial-homophyletic" comparison-induced biomarkers verification for the systematic chemical differentiation of five different parts of Panax ginseng.

作者信息

Qiu Shi, Yang Wen-Zhi, Yao Chang-Liang, Qiu Zhi-Dong, Shi Xiao-Jian, Zhang Jing-Xian, Hou Jin-Jun, Wang Qiu-Rong, Wu Wan-Ying, Guo De-An

机构信息

Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Laboratory for TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Haike Road 501, Shanghai 201203, China; School of Pharmaceutical Sciences, Changchun University of Chinese Medicine, Boshuo Road 1035, Changchun 130117, China.

Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Laboratory for TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Haike Road 501, Shanghai 201203, China.

出版信息

J Chromatogr A. 2016 Jul 1;1453:78-87. doi: 10.1016/j.chroma.2016.05.051. Epub 2016 May 13.

Abstract

A key segment in authentication of herbal medicines is the establishment of robust biomarkers that embody the intrinsic metabolites difference independent of the growing environment or processing technics. We present a strategy by nontargeted metabolomics and "Commercial-homophyletic" comparison-induced biomarkers verification with new bioinformatic vehicles, to improve the efficiency and reliability in authentication of herbal medicines. The chemical differentiation of five different parts (root, leaf, flower bud, berry, and seed) of Panax ginseng was illustrated as a case study. First, an optimized ultra-performance liquid chromatography/quadrupole time-of-flight-MS(E) (UPLC/QTOF-MS(E)) approach was established for global metabolites profiling. Second, UNIFI™ combined with search of an in-house library was employed to automatically characterize the metabolites. Third, pattern recognition multivariate statistical analysis of the MS(E) data of different parts of commercial and homophyletic samples were separately performed to explore potential biomarkers. Fourth, potential biomarkers deduced from commercial and homophyletic root and leaf samples were cross-compared to infer robust biomarkers. Fifth, discriminating models by artificial neutral network (ANN) were established to identify different parts of P. ginseng. Consequently, 164 compounds were characterized, and 11 robust biomarkers enabling the differentiation among root, leaf, flower bud, and berry, were discovered by removing those structurally unstable and possibly processing-related ones. The ANN models using the robust biomarkers managed to exactly discriminate four different parts and root adulterant with leaf as well. Conclusively, biomarkers verification using homophyletic samples conduces to the discovery of robust biomarkers. The integrated strategy facilitates authentication of herbal medicines in a more efficient and more intelligent manner.

摘要

中药材鉴定的一个关键环节是建立强大的生物标志物,这些生物标志物能够体现出与生长环境或加工工艺无关的内在代谢物差异。我们提出了一种通过非靶向代谢组学和“商业同属植物”比较诱导的生物标志物验证,并借助新的生物信息学工具的策略,以提高中药材鉴定的效率和可靠性。以人参五个不同部位(根、叶、花蕾、浆果和种子)的化学差异为例进行了说明。首先,建立了一种优化的超高效液相色谱/四极杆飞行时间质谱(E)(UPLC/QTOF-MS(E))方法用于全局代谢物谱分析。其次,采用UNIFI™结合内部库搜索来自动表征代谢物。第三,分别对商业样品和同属植物样品不同部位的MS(E)数据进行模式识别多元统计分析,以探索潜在的生物标志物。第四,对从商业样品和同属植物的根和叶样品中推导出来的潜在生物标志物进行交叉比较,以推断出强大的生物标志物。第五,建立人工神经网络(ANN)判别模型来识别不同部位的人参。结果,共鉴定出164种化合物,通过去除那些结构不稳定和可能与加工相关的化合物,发现了11种能够区分根、叶、花蕾和浆果的强大生物标志物。使用这些强大生物标志物的ANN模型成功地准确区分了四个不同部位以及根与叶掺假物。总之,使用同属植物样品进行生物标志物验证有助于发现强大的生物标志物。这种综合策略有助于以更高效、更智能的方式对中药材进行鉴定。

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