Charting the Undiscovered Metabolome with Synthetic Multiplexing

Area of Science:

• Metabolomics
• Biochemistry
• Computational Biology

Background:

• Untargeted metabolomics relies on MS/MS libraries for structural annotation.
• Current libraries cover only a small fraction of public MS/MS spectra, leaving many features unannotated.

Purpose of the Study:

• To address the gap in MS/MS spectral annotation by creating a comprehensive, biologically relevant compound library.
• To improve the identification of known and novel metabolites in complex biological samples.

Main Methods:

• Synthesized over 100,000 compounds using reactions mimicking biochemical transformations.
• Developed computational infrastructure for large-scale MS/MS spectral comparisons across repositories.
• Integrated the novel compound library into existing spectral matching workflows.

Main Results:

• 91% of synthesized compounds were not found in existing databases.
• The new library increased the reference-based match rate by 17.4%.
• Over 60 million new MS/MS matches were generated, raising the global annotation rate to 8.1%.

Conclusions:

• The biologically inspired MS/MS library significantly enhances metabolite identification in untargeted metabolomics.
• This framework expands the detectable biochemical landscape across diverse organisms.
• Facilitates the discovery of novel metabolites, including drug conjugates and co-metabolites.