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Researchers expanded the known chemical diversity of carnitines, vital metabolites involved in numerous biological processes. This work provides a comprehensive MS/MS spectral library for identifying and discovering new carnitine structures.

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Area of Science:

  • Metabolomics
  • Biochemistry
  • Analytical Chemistry

Background:

  • Carnitines are essential metabolites formed by conjugating L-carnitine with various molecules.
  • They play critical roles in metabolism, transport, and detoxification.
  • The full chemical diversity of carnitines is not yet completely understood.

Purpose of the Study:

  • To systematically identify and characterize the chemical diversity of acylcarnitines.
  • To create a comprehensive MS/MS spectral library for acylcarnitine discovery.
  • To enable the identification of novel carnitine structures and their roles.

Main Methods:

  • Utilized a pan-repository data mining strategy across multiple metabolomics databases (GNPS/MassIVE, MetaboLights, Metabolomics Workbench).
  • Employed MassQL diagnostic fragment ion filtering on LC-MS/MS data to extract acylcarnitine spectra.
  • Generated a large-scale library of unique MS/MS spectra and atomic compositions.

Main Results:

  • Identified 34,222 unique MS/MS spectra representing 2,857 atomic compositions.
  • Detected over 3.8 million acylcarnitine instances.
  • Enabled the discovery of previously unknown carnitines, including dihydroferulic acid conjugated carnitines.

Conclusions:

  • The developed MS/MS library significantly enhances acylcarnitine annotation and discovery.
  • This resource supports the exploration of carnitines in various biological contexts, including host metabolism, diet, and disease.
  • Further research into this diverse metabolite class is warranted.