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Systematic analysis of in-source modifications of primary metabolites during flow-injection time-of-flight mass spectrometry
Flow-injection mass spectrometry (FI-MS) enables metabolomics studies with a very high sample-throughput. However, FI-MS is prone to in-source modifications of analytes because samples are directly injected into the electrospray ionization source of a mass spectrometer without prior chromatographic...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9902335/ https://www.ncbi.nlm.nih.gov/pubmed/36627043 http://dx.doi.org/10.1016/j.ab.2023.115036 |
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author | Farke, Niklas Schramm, Thorben Verhülsdonk, Andreas Rapp, Johanna Link, Hannes |
author_facet | Farke, Niklas Schramm, Thorben Verhülsdonk, Andreas Rapp, Johanna Link, Hannes |
author_sort | Farke, Niklas |
collection | PubMed |
description | Flow-injection mass spectrometry (FI-MS) enables metabolomics studies with a very high sample-throughput. However, FI-MS is prone to in-source modifications of analytes because samples are directly injected into the electrospray ionization source of a mass spectrometer without prior chromatographic separation. Here, we spiked authentic standards of 160 primary metabolites individually into an Escherichia coli metabolite extract and measured the thus derived 160 spike-in samples by FI-MS. Our results demonstrate that FI-MS can capture a wide range of chemically diverse analytes within 30 s measurement time. However, the data also revealed extensive in-source modifications. Across all 160 spike-in samples, we identified significant increases of 11,013 ion peaks in positive and negative mode combined. To explain these unknown m/z features, we connected them to the m/z feature of the (de-)protonated metabolite using information about mass differences and MS2 spectra. This resulted in networks that explained on average 49 % of all significant features. The networks showed that a single metabolite undergoes compound specific and often sequential in-source modifications like adductions, chemical reactions, and fragmentations. Our results show that FI-MS generates complex MS1 spectra, which leads to an overestimation of significant features, but neutral losses and MS2 spectra explain many of these features. |
format | Online Article Text |
id | pubmed-9902335 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-99023352023-03-01 Systematic analysis of in-source modifications of primary metabolites during flow-injection time-of-flight mass spectrometry Farke, Niklas Schramm, Thorben Verhülsdonk, Andreas Rapp, Johanna Link, Hannes Anal Biochem Article Flow-injection mass spectrometry (FI-MS) enables metabolomics studies with a very high sample-throughput. However, FI-MS is prone to in-source modifications of analytes because samples are directly injected into the electrospray ionization source of a mass spectrometer without prior chromatographic separation. Here, we spiked authentic standards of 160 primary metabolites individually into an Escherichia coli metabolite extract and measured the thus derived 160 spike-in samples by FI-MS. Our results demonstrate that FI-MS can capture a wide range of chemically diverse analytes within 30 s measurement time. However, the data also revealed extensive in-source modifications. Across all 160 spike-in samples, we identified significant increases of 11,013 ion peaks in positive and negative mode combined. To explain these unknown m/z features, we connected them to the m/z feature of the (de-)protonated metabolite using information about mass differences and MS2 spectra. This resulted in networks that explained on average 49 % of all significant features. The networks showed that a single metabolite undergoes compound specific and often sequential in-source modifications like adductions, chemical reactions, and fragmentations. Our results show that FI-MS generates complex MS1 spectra, which leads to an overestimation of significant features, but neutral losses and MS2 spectra explain many of these features. Elsevier 2023-03-01 /pmc/articles/PMC9902335/ /pubmed/36627043 http://dx.doi.org/10.1016/j.ab.2023.115036 Text en © 2023 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Farke, Niklas Schramm, Thorben Verhülsdonk, Andreas Rapp, Johanna Link, Hannes Systematic analysis of in-source modifications of primary metabolites during flow-injection time-of-flight mass spectrometry |
title | Systematic analysis of in-source modifications of primary metabolites during flow-injection time-of-flight mass spectrometry |
title_full | Systematic analysis of in-source modifications of primary metabolites during flow-injection time-of-flight mass spectrometry |
title_fullStr | Systematic analysis of in-source modifications of primary metabolites during flow-injection time-of-flight mass spectrometry |
title_full_unstemmed | Systematic analysis of in-source modifications of primary metabolites during flow-injection time-of-flight mass spectrometry |
title_short | Systematic analysis of in-source modifications of primary metabolites during flow-injection time-of-flight mass spectrometry |
title_sort | systematic analysis of in-source modifications of primary metabolites during flow-injection time-of-flight mass spectrometry |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9902335/ https://www.ncbi.nlm.nih.gov/pubmed/36627043 http://dx.doi.org/10.1016/j.ab.2023.115036 |
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