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<p>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.</p>

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Enhancing tandem mass spectrometry-based metabolite annotation with online chemical labeling

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年7月26日

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  • Giovanni Andrea Vitale,
  • Shu-Ning Xia,
  • Kai Dührkop,
  • Mohammad Reza Zare Shahneh,
  • Heike Brötz-Oesterhelt,
  • Yvonne Mast,
  • Corinna Brungs,
  • Sebastian Böcker,
  • Robin Schmid,
  • Mingxun Wang,
  • Chambers C. Hughes,
  • Daniel Petras

摘要

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.