Literature DB >> 31039532

Integration of targeted metabolite profiling and sequential optimization method for discovery of chemical marker combination to identify the closely-related plant species.

Wen Gao1, Ke Liu2, Rui Wang3, Xin-Guang Liu4, Xiao-Shi Li5, Ping Li6, Hua Yang7.   

Abstract

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 α-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.
Copyright © 2019. Published by Elsevier GmbH.

Entities:  

Keywords:  Chemical markers; Lonicera flower; Partial least squares discrimination analysis; Saponin; Sequential optimization method; Targeted metabolomics

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Year:  2019        PMID: 31039532     DOI: 10.1016/j.phymed.2019.152829

Source DB:  PubMed          Journal:  Phytomedicine        ISSN: 0944-7113            Impact factor:   5.340


  1 in total

1.  From non-targeted to targeted GC-MS metabolomics strategy for identification of TCM preparations containing natural and artificial musk.

Authors:  Meng Ding; Jun-Li Fan; Dong-Fang Huang; Yue Jiang; Meng-Ning Li; Yu-Qing Zheng; Xiao-Ping Yang; Ping Li; Hua Yang
Journal:  Chin Med       Date:  2022-04-01       Impact factor: 5.455

  1 in total

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