HERMES: a molecular-formula-oriented method to target the metabolome
| Autor: | Andrea M. Brunner, Oscar Yanes, Theodore Alexandrov, Michaela Schwaiger-Haber, Dennis Vughs, Gary J. Patti, Maria Vinaixa, Jordi Capellades, Josep M. Badia, Roger Giné |
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| Rok vydání: | 2021 |
| Předmět: |
Computer science
Computational biology 01 natural sciences Biochemistry Article 03 medical and health sciences Plasma Metabolomics Biological specificity Environmental water Tandem Mass Spectrometry Metabolome Escherichia coli Humans Molecular Biology 030304 developmental biology 0303 health sciences 010401 analytical chemistry Cell Biology Spectral similarity 0104 chemical sciences R package Untargeted metabolomics Human plasma Algorithms Water Pollutants Chemical Biotechnology Chromatography Liquid |
| Zdroj: | Nat Methods |
| ISSN: | 1548-7105 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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