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Metabonomics study on the effects of the ginsenoside Rg3 in a β-cyclodextrin-based formulation on tumor-bearing rats by a fully automatic hydrophilic interaction/reversed-phase column-switching HPLC-ESI-MS approach

  • Yuan Wang
  • , Jiangshan Wang
  • , Ming Yao
  • , Xinjie Zhao
  • , Jens Fritsche
  • , Philippe Schmitt-Kopplin
  • , Zongwei Cai
  • , Dafang Wan
  • , Xin Lu
  • , Shengli Yang
  • , Jianren Gu
  • , Hans Ulrich Häring
  • , Erwin D. Schleicher
  • , Rainer Lehmann
  • , Guowang Xu
  • Dalian Institute of Chemical Physics Chinese Academy of Sciences
  • Shanghai Jiao Tong University
  • Immatics Biotechnologies GmbH
  • Helmholtz Zentrum München German Research Center for Environmental Health
  • Hong Kong Baptist University
  • Chinese Academy of Sciences
  • Universitätsklinikum Tübingen

Research output: Contribution to journalArticlepeer-review

77 Scopus citations

Abstract

The goal of this study was the application of a novel, fully automatic column-switching approach in a metabonomics study combining the orthogonal selectivities of hydrophilic interaction chromatography (HILIC) and reversed-phase chromatography. The temporal, pharmacodynamic effects of the ginsenoside Rg3 on the metabonome in urine of healthy and liver-tumor-bearing rats have been investigated. Within a total analysis time of 52 min we detected 5686 polar, and on the second column an additional 1808 apolar, urinary metabolite ions. The administration of a single, high dose of Rg3 in a β-cyclodextrin-based formulation led to a considerable change of the metabolic pattern in cancer rats during 3 days studied. Seventeen biomarker candidates including three apolar metabolites, which were not retained on the HILIC column, were detected. Overall, the results suggest that the developed liquid chromatography-mass spectrometry strategy is a promising tool in metabonomics studies for global analysis of highly complex biosamples. It may not only increase the number of discovered biomarkers but consequently improve the comprehensive information on metabolic changes in a fully automatic manner.

Original languageEnglish
Pages (from-to)4680-4688
Number of pages9
JournalAnalytical Chemistry
Volume80
Issue number12
DOIs
StatePublished - 15 Jun 2008
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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