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Untargeted high-resolution paired mass distance data mining for retrieving general chemical relationships

Untargeted metabolomics analysis captures chemical reactions among small molecules. Common mass spectrometry-based metabolomics workflows first identify the small molecules significantly associated with the outcome of interest, then begin exploring their biochemical relationships to understand biolo...

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Detalles Bibliográficos
Autores principales: Yu, Miao, Petrick, Lauren
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8320691/
https://www.ncbi.nlm.nih.gov/pubmed/34337162
http://dx.doi.org/10.1038/s42004-020-00403-z
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author Yu, Miao
Petrick, Lauren
author_facet Yu, Miao
Petrick, Lauren
author_sort Yu, Miao
collection PubMed
description Untargeted metabolomics analysis captures chemical reactions among small molecules. Common mass spectrometry-based metabolomics workflows first identify the small molecules significantly associated with the outcome of interest, then begin exploring their biochemical relationships to understand biological fate or impact. We suggest an alternative by which general chemical relationships including abiotic reactions can be directly retrieved through untargeted high-resolution paired mass distance (PMD) analysis without a priori knowledge of the identities of participating compounds. PMDs calculated from the mass spectrometry data are linked to chemical reactions obtained via data mining of small molecule and reaction databases, i.e. ‘PMD-based reactomics’. We demonstrate applications of PMD-based reactomics including PMD network analysis, source appointment of unknown compounds, and biomarker reaction discovery as complements to compound discovery analyses used in traditional untargeted workflows. An R implementation of reactomics analysis and the reaction/PMD databases is available as the pmd package.
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spelling pubmed-83206912021-07-29 Untargeted high-resolution paired mass distance data mining for retrieving general chemical relationships Yu, Miao Petrick, Lauren Commun Chem Article Untargeted metabolomics analysis captures chemical reactions among small molecules. Common mass spectrometry-based metabolomics workflows first identify the small molecules significantly associated with the outcome of interest, then begin exploring their biochemical relationships to understand biological fate or impact. We suggest an alternative by which general chemical relationships including abiotic reactions can be directly retrieved through untargeted high-resolution paired mass distance (PMD) analysis without a priori knowledge of the identities of participating compounds. PMDs calculated from the mass spectrometry data are linked to chemical reactions obtained via data mining of small molecule and reaction databases, i.e. ‘PMD-based reactomics’. We demonstrate applications of PMD-based reactomics including PMD network analysis, source appointment of unknown compounds, and biomarker reaction discovery as complements to compound discovery analyses used in traditional untargeted workflows. An R implementation of reactomics analysis and the reaction/PMD databases is available as the pmd package. Nature Publishing Group UK 2020-11-06 /pmc/articles/PMC8320691/ /pubmed/34337162 http://dx.doi.org/10.1038/s42004-020-00403-z Text en © The Author(s) 2020, corrected publication 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Yu, Miao
Petrick, Lauren
Untargeted high-resolution paired mass distance data mining for retrieving general chemical relationships
title Untargeted high-resolution paired mass distance data mining for retrieving general chemical relationships
title_full Untargeted high-resolution paired mass distance data mining for retrieving general chemical relationships
title_fullStr Untargeted high-resolution paired mass distance data mining for retrieving general chemical relationships
title_full_unstemmed Untargeted high-resolution paired mass distance data mining for retrieving general chemical relationships
title_short Untargeted high-resolution paired mass distance data mining for retrieving general chemical relationships
title_sort untargeted high-resolution paired mass distance data mining for retrieving general chemical relationships
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8320691/
https://www.ncbi.nlm.nih.gov/pubmed/34337162
http://dx.doi.org/10.1038/s42004-020-00403-z
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