Projects per year
Abstract
The annotation of metabolites detected in LC-MS-based untargeted metabolomics studies routinely applies accurate m/z of the intact metabolite (MS1) as well as chromatographic retention time and MS/MS data. Electrospray ionization and transfer of ions through the mass spectrometer can result in the generation of multiple "features" derived from the same metabolite with different m/z values but the same retention time. The complexity of the different charged and neutral adducts, in-source fragments, and charge states has not been previously and deeply characterized. In this paper, we report the first large-scale characterization using publicly available data sets derived from different research groups, instrument manufacturers, LC assays, sample types, and ion modes. 271 m/z differences relating to different metabolite feature pairs were reported, and 209 were annotated. The results show a wide range of different features being observed with only a core 32 m/z differences reported in >50% of the data sets investigated. There were no patterns reporting specific m/z differences that were observed in relation to ion mode, instrument manufacturer, LC assay type, and mammalian sample type, although some m/z differences were related to study group (mammal, microbe, plant) and mobile phase composition. The results provide the metabolomics community with recommendations of adducts, in-source fragments, and charge states to apply in metabolite annotation workflows.
Original language | English |
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Pages (from-to) | 10935-10942 |
Number of pages | 8 |
Journal | Analytical Chemistry |
Volume | 96 |
Issue number | 27 |
Early online date | 25 Jun 2024 |
DOIs | |
Publication status | Published - 9 Jul 2024 |
Keywords
- Spectrometry, Mass, Electrospray Ionization/methods
- Metabolomics/methods
- Animals
- Chromatography, Liquid
- Humans
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Dive into the research topics of 'Characterization of Electrospray Ionization Complexity in Untargeted Metabolomic Studies'. Together they form a unique fingerprint.Projects
- 2 Finished
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Standardised metabolite annotation workflows for enhanced biological interpretation in metabolomic data repositories
Dunn, W.
Biotechnology & Biological Sciences Research Council
1/04/20 → 31/03/23
Project: Research Councils
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Next generation tools for the annotation of metabolites in global LC-MS metabolomic studies
Dunn, W., He, S., Viant, M. & Weber, R.
Biotechnology & Biological Sciences Research Council
1/10/16 → 31/12/17
Project: Research Councils