ArticleScientific reports2017
Screening Specific Biomarkers of Herbs Using a Metabolomics Approach: A Case Study of Panax ginseng.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Exploring the Metabolic and Transcriptomic Profiles ofFrontiers in plant science · 2025Article
- Transcriptome-Wide Integrated Analysis of thePlants (Basel, Switzerland) · 2023Article
- Identification of Anti-HIV Biomarkers ofFrontiers in pharmacology · 2022Article
- Phytochemical Profiling and Quality Control ofMolecules (Basel, Switzerland) · 2021Article
- Phytochemical analysis ofJournal of ginseng research · 2021Review
- Integrated Strategy FromFrontiers in pharmacology · 2021Article
- Metabolic signatures provide novel insights to Picrorhiza kurroa adaptation along the altitude in Himalayan region.Metabolomics : Official journal of the Metabolomic Society · 2020Article
- Unraveling dynamic metabolomes underlying different maturation stages of berries harvested fromJournal of ginseng research · 2020Article
- UPLC-QTOF/MS-Based Nontargeted Metabolomic Analysis of Mountain- and Garden-Cultivated Ginseng of Different Ages in Northeast China.Molecules (Basel, Switzerland) · 2018Article
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4 authors.
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Abstract
Medicinal herbs belonging to the same genus are always easily confused due to their extremely similar morphology and metabolites. Previously, to differentiate them, inherently specific biomarkers were screened out via intuitive comparison of their metabolite profiles. Unfortunately, the selected biomarkers have worked only partially. Most significant specific biomarkers have been neglected. Herein, a novel method for screening specific biomarkers of medicinal herbs using a metabolomics technique was developed. Firstly, the profiles of a group of easily confused herbs belonging to the same genus were analyzed by ultra-high performance liquid chromatography coupled with high-resolution mass spectrometry to detect all components, including low-response metabolites. Then, all components were compared between the different samples, and specific biomarkers were extracted by the metabolomics techniques of alignment, normalization, defining the sample sets, filtering by frequency and Venn diagram analysis with Mass Profiler Professional (MPP) software. Thirdly, the correlations of these biomarkers were investigated via partial correlational analysis to obtain the most representative specific biomarkers. As an example, selection of specific biomarkers for ginseng (Panax ginseng) was performed, and three specific biomarkers including chikusetsusaponin IVa, ginsenoside Rf and ginsenoside Rc were finally selected and verified as the most representative specific biomarkers of Panax ginseng.
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