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Related Experiment Video

Updated: Jul 13, 2025

Untargeted Metabolomics from Biological Sources Using Ultraperformance Liquid Chromatography-High Resolution Mass Spectrometry UPLC-HRMS
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Optimising a urinary extraction method for non-targeted GC-MS metabolomics.

Cara Olivier1, Bianca Allen1, Laneke Luies2

  • 1Human Metabolomics, North-West University, Potchefstroom Campus, Private Bag X6001, Box 269, Potchefstroom, 2520, NW, South Africa.

Scientific Reports
|October 16, 2023
PubMed
Summary
This summary is machine-generated.

This study optimized a direct analysis (DA) method for low-volume urine preparation in non-targeted gas chromatography-mass spectrometry (GC-MS) metabolomics. The DA method offers superior repeatability and broader metabolite coverage compared to organic acid extraction methods.

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Area of Science:

  • Metabolomics
  • Analytical Chemistry
  • Biochemistry

Background:

  • Urine is a valuable biofluid for non-targeted metabolomics, offering insights into cellular processes.
  • Optimizing sample preparation is crucial for comprehensive analysis of diverse metabolites.
  • Gas chromatography-mass spectrometry (GC-MS) is a powerful technique for metabolomic profiling.

Purpose of the Study:

  • To optimize a low-volume urine preparation procedure for non-targeted GC-MS metabolomics.
  • To compare the effectiveness of a direct analysis (DA) approach against organic acid (OA) extraction methods.
  • To enhance metabolite coverage, recovery, and repeatability in urinary metabolomic analysis.

Main Methods:

  • Evaluated five extraction methods: four OA variations and one DA approach.
  • Assessed methods based on repeatability, metabolome coverage, and metabolite recovery.
  • Optimized the DA method with an additional drying step and tested urease pre-treatment.

Main Results:

  • The DA method demonstrated superior repeatability and the highest metabolome coverage (91 unique metabolites).
  • OA methods showed bias towards specific compound classes, resulting in lower recovery and higher undetected compound rates.
  • An additional drying step improved the DA method, while urease pre-treatment offered no benefit.

Conclusions:

  • The optimized DA method provides an improved approach for low-volume urine preparation in non-targeted GC-MS metabolomics.
  • This method enables efficient and comprehensive analysis of urinary metabolites.
  • Findings can advance metabolomics, aiding disease diagnosis and biomarker discovery.