Isotope tracing-based metabolite identification for mass spectrometry metabolomics

Area of Science:

• Biomedical research
• Metabolomics
• Analytical chemistry

Background:

• Mass spectrometry-based metabolomics is crucial for biomedicine but struggles with identifying the majority of detected features.
• Current metabolite identification relies heavily on mass spectrometry/mass spectrometry (MS2) fragmentation patterns, which has limitations.

Purpose of the Study:

• To develop and validate an orthogonal approach for identifying endogenous metabolites using mass isotopomer distributions (MIDs).
• To computationally identify novel metabolites by comparing their MIDs to known standards in isotope-labeled samples.

Main Methods:

• Utilized cell material labeled with 20 individual 13C tracers to measure MIDs.
• Developed a computational measure of pairwise distance between metabolite MIDs for identification.
• Applied the MID-based approach to identify unknown peaks in metabolomics data.

Main Results:

• Successfully identified 62% of previously unknown metabolite peaks, including novel compounds.
• MID-based identification proved complementary to MS2 methods, offering insights into metabolic pathways.
• Discovered trimethylglycyl-lysine, a novel amino acid derivative altered in human muscle tissue.

Conclusions:

• MID-based annotation using isotope-labeled reference materials is an effective strategy for identifying novel endogenous metabolites.
• This method significantly extends the capabilities of mass spectrometry-based metabolomics.
• The approach provides complementary information to MS2, aiding in the elucidation of metabolic pathways and discovery of new biomarkers.