Integration of targeted metabolite profiling and sequential optimization method for discovery of chemical marker combination to identify the closely-related plant species
Integration of targeted metabolite profiling and sequential optimization method for discovery of chemical marker combination to identify the closely-related plant species
复制标题
整合靶向代谢物分析和序贯优化方法来发现化学标记组合,以识别密切相关的植物物种
DOI:
10.1016/j.phymed.2019.152829
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发表时间:
2019-08-01
期刊:
影响因子:
7.9
通讯作者:
Yang Hua
中科院分区:
文献类型:
--
作者:
Gao Wen;Liu Ke;Yang Hua
Background: Quality control of herbal medicines based on characteristic components is an important trend. Although the plant metabolomics provide a powerful tool for species classification, the discovered marker is usually limited in practical application. For rapid discovery of efficient marker combination, we proposed a strategy integrating targeted metabolite profiling and sequential optimization method.Methods: This strategy included: (1) directional enrichment and chemical profiling of targeted metabolites by matrix solid phase dispersion (MSPD) combined with liquid chromatography-tandem mass spectrometry (LC-MS/MS). (2) Partial least squares discrimination analysis (PLS-DA)-based sequential screening of efficient marker combination was constructed for various species predictions. Five Lonicera species and their characteristic metabolites, sponins, were taken as a case study.Results: A total of 19 saponins were identified, and 12 major and available saponins were enriched based on MSPD and quantified by LC-MS/MS in 5 Lonicera species flower buds. Followed by 3 runs of PLS-DA-based screening, a combination consisting of macranthoidin B, dipsacoside B and alpha-hederin was discovered as the effective chemical marker for 5 analogous Lonicera flower classification.Conclusion: Our study provides an effective and applicable approach to select the practical marker combination for the assessment of analogical herb medicines.