4.8 Article

HERMES: a molecular-formula-oriented method to target the metabolome

Journal

NATURE METHODS
Volume 18, Issue 11, Pages 1370-+

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41592-021-01307-z

Keywords

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Funding

  1. Ministerio de Educacion y Formacion Profesional (Spanish Government) [2020-COLAB-00552]
  2. Ministerio de Economia y Competitividad (MINECO) [BFU2014-57466-P]
  3. Spanish Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM), an initiative of Instituto de Investigacion Carlos III (ISCIII)
  4. European Union's Horizon 2020 program (MSCA-ITN-2015) [675610]

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HERMES is a molecular-formula-oriented and peak-detection-free method that uses LC/MS1 information to optimize MS2 acquisition, improving the identification rate and biological specificity of metabolites.
Comprehensive metabolome analyses are essential for biomedical, environmental, and biotechnological research. However, current MS1- and MS2-based acquisition and data analysis strategies in untargeted metabolomics result in low identification rates of metabolites. Here we present HERMES, a molecular-formula-oriented and peak-detection-free method that uses raw LC/MS1 information to optimize MS2 acquisition. Investigating environmental water, Escherichia coli, and human plasma extracts with HERMES, we achieved an increased biological specificity of MS2 scans, leading to improved mass spectral similarity scoring and identification rates when compared with a state-of-the-art data-dependent acquisition (DDA) approach. Thus, HERMES improves sensitivity, selectivity, and annotation of metabolites. HERMES is available as an R package with a user-friendly graphical interface for data analysis and visualization. HERMES is a molecular-formula-oriented and peak-detection-free method that uses LC/MS1 information to optimize MS2 acquisition for LC/MS-based metabolomic analysis.

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