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LC-MS-based metabonomics analysis.

Xin Lu1, Xinjie Zhao, Changmin Bai

  • 1National Chromatographic R&A Center, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China.

Journal of Chromatography. B, Analytical Technologies in the Biomedical and Life Sciences
|November 7, 2007
PubMed
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Metabonomics uses high-performance liquid chromatography-mass spectrometry (HPLC-MS) for comprehensive metabolite analysis. This review explores HPLC-MS strategies for applications in toxicology, drug development, and clinical diagnosis.

Area of Science:

  • Analytical Chemistry
  • Biochemistry
  • Systems Biology

Background:

  • Metabonomics involves comprehensive, quantitative analysis of metabolites in biological samples.
  • It holds promise for toxicology, drug development, functional genomics, systems biology, and clinical diagnosis.
  • Analyzing complex biological samples presents significant analytical chemistry challenges.

Purpose of the Study:

  • To review the strategies and applications of high-performance liquid chromatography-mass spectrometry (HPLC-MS) in metabonomics.
  • To highlight the utility of HPLC-MS in endogenous metabolite research.
  • To discuss the role of HPLC-MS in biomarker discovery and metabolite structural characterization.

Main Methods:

  • High-performance liquid chromatography-mass spectrometry (HPLC-MS) is a key technology.

Related Experiment Videos

  • HPLC-MS offers wide dynamic range and reproducible quantitative analysis.
  • It is suitable for analyzing biofluids with high molecular complexity.

    • Main Results:

    • HPLC-MS is an established technique for drug metabolite analysis, now expanding to endogenous metabolites.
    • The method provides advantages for analyzing complex biological matrices.
    • Its application ranges from basic research to clinical diagnostics.

    Conclusions:

    • HPLC-MS is a powerful tool for metabonomics.
    • It facilitates advancements in understanding biological systems and disease mechanisms.
    • The technique is crucial for biomarker discovery and metabolite identification.