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Updated: Feb 8, 2026

An Integrated Workflow of Identification and Quantification on FDR Control-Based Untargeted Metabolome
Published on: September 20, 2022
Partially 13C-labeled mouse tissue as reference for LC-MS based untargeted metabolomics
Frederik Dethloff1, Christoph Bueschl2, Hermann Heumann3
1Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany.
Partially 13C-labeled mouse material serves as an effective internal standard for untargeted metabolomics. This method accurately quantifies metabolites in human plasma, reducing variability and improving relative quantification.
Area of Science:
- Metabolomics
- Biochemistry
- Analytical Chemistry
Background:
- Stable isotope-labeled standards are crucial for metabolite quantification in untargeted metabolomics.
- Ideal standards mirror the labeled metabolites present in the sample for comprehensive analysis.
Purpose of the Study:
- To evaluate partially 13C-labeled mouse material as an internal standard for relative metabolite quantification in untargeted metabolomics.
- To assess the accuracy and precision of this method for analyzing mouse and human samples.
Main Methods:
- Mice were fed a 13C-labeled diet for 14 days, resulting in partially labeled amino acids (6-75% enrichment).
- MetExtract II software was employed for automated detection of native and labeled metabolite peaks.
- Partially 13C-labeled mouse plasma was used with a correction factor in a dilution series for quantification via liquid chromatography-mass spectrometry.
Main Results:
- Partially 13C-labeled mouse plasma enabled accurate relative quantification of human plasma amino acids.
- The coefficient of variation for relative quantification decreased from 27% (without standard) to 10% (with standard).
Conclusions:
- Partially 13C-labeled mouse material is a viable and effective internal standard for untargeted metabolomics.
- This approach enhances the accuracy of relative metabolite quantification in human samples, with broad applicability expected.
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