Enhancing tandem mass spectrometry-based metabolite annotation with online chemical labeling
- Nat Commun. 2025 Jul 26;16(1):6911. doi: 10.1038/s41467-025-61240-z.
- 1. Department of Microbial Bioactive Compounds, Interfaculty Institute of Microbiology and Infection Medicine (IMIT), University of Tübingen, Tübingen, Germany.
- 2. Chair for Bioinformatics, Institute for Computer Science, Friedrich Schiller University Jena, Jena, Germany.
- 3. Bright Giant GmbH, Jena, Germany.
- 4. Department of Computer Science, University of California Riverside, Riverside, CA, USA.
- 5. German Center for Infection Research (DZIF), Partner Site Tübingen, Tübingen, Germany.
- 6. Cluster of Excellence EXC 2124: Controlling Microbes to Fight Infection, University of Tübingen, Tübingen, Germany.
- 7. Department Bioresources for Bioeconomy and Health Research, Leibniz Institute DSMZ - German Collection of Microorganisms and Cell Cultures, Braunschweig, Germany.
- 8. Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Prague, Czech Republic.
- 9. Division of Pharmacognosy, Department of Pharmaceutical Sciences, Faculty of Life Sciences, University of Vienna, Vienna, Austria.
- 10. mzio GmbH, Bremen, Germany.
- 11. Department of Microbial Bioactive Compounds, Interfaculty Institute of Microbiology and Infection Medicine (IMIT), University of Tübingen, Tübingen, Germany. [email protected].
- 12. German Center for Infection Research (DZIF), Partner Site Tübingen, Tübingen, Germany. [email protected].
- 13. Cluster of Excellence EXC 2124: Controlling Microbes to Fight Infection, University of Tübingen, Tübingen, Germany. [email protected].
- 14. Cluster of Excellence EXC 2124: Controlling Microbes to Fight Infection, University of Tübingen, Tübingen, Germany. [email protected].
- 15. Department of Biochemistry, University of California Riverside, Riverside, CA, USA. [email protected].
- # Contributed equally.
Metabolite identification in non-targeted mass spectrometry-based metabolomics remains a major challenge due to limited spectral library coverage and difficulties in predicting metabolite fragmentation patterns. Here, we introduce Multiplexed Chemical Metabolomics (MCheM), which employs orthogonal post-column derivatization reactions integrated into a unified mass spectrometry data framework. MCheM generates orthogonal structural information that substantially improves metabolite annotation through in silico spectrum matching and open-modification searches, offering a powerful new toolbox for the structure elucidation of unknown metabolites at scale.
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