Isotopologue ratio normalization for non-targeted metabolomics.

Area of Science:

• Metabolomics
• Analytical Chemistry
• Biochemistry

Background:

• Accurate quantification of metabolites is crucial for reliable metabolomics studies.
• Comparing metabolomics data across different batches and instruments remains a significant challenge.
• Current targeted metabolomics often relies on isotope dilution mass spectrometry for normalization.

Purpose of the Study:

• To develop an automated method for semi-quantifying metabolites using a fully stable isotope-labeled metabolite extract.
• To enable robust comparison of metabolite levels across diverse mass spectrometry platforms, including low-resolution instruments.
• To improve intra- and inter-instrument reproducibility in metabolomics data analysis.

Main Methods:

• Utilized a fully stable isotope-labeled metabolite extract as an internal standard for semi-quantification.
• Employed the non-targeted tracer fate detection algorithm for automated detection of internal standards.
• Applied the ratios of light and heavy metabolite forms for normalization and cross-platform comparison.
• Validated the method using gas chromatography electron impact mass spectrometry (GC-EI-MS).

Main Results:

• The developed method allows for automated semi-quantification of both identified and unidentified compounds.
• Demonstrated superior intra- and inter-instrument reproducibility compared to conventional normalization approaches.
• Showcased the method's effectiveness with low-resolution mass spectrometers, broadening accessibility.
• Successfully used a labeled yeast metabolite extract as a reference for mammalian samples.

Conclusions:

• The presented approach offers a robust and automated solution for semi-quantifying metabolites in metabolomics.
• This method enhances data comparability and reproducibility across different experimental setups and instruments.
• The technique is particularly valuable for laboratories utilizing widely available low-resolution mass spectrometry platforms.
• The use of a universal labeled extract simplifies normalization, even when complete stable isotope labeling of samples is challenging.