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Ion mobility collision cross-section atlas for known and unknown metabolite annotation in untargeted metabolomics
The metabolome includes not just known but also unknown metabolites; however, metabolite annotation remains the bottleneck in untargeted metabolomics. Ion mobility – mass spectrometry (IM-MS) has emerged as a promising technology by providing multi-dimensional characterizations of metabolites. Here,...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7455731/ https://www.ncbi.nlm.nih.gov/pubmed/32859911 http://dx.doi.org/10.1038/s41467-020-18171-8 |
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author | Zhou, Zhiwei Luo, Mingdu Chen, Xi Yin, Yandong Xiong, Xin Wang, Ruohong Zhu, Zheng-Jiang |
author_facet | Zhou, Zhiwei Luo, Mingdu Chen, Xi Yin, Yandong Xiong, Xin Wang, Ruohong Zhu, Zheng-Jiang |
author_sort | Zhou, Zhiwei |
collection | PubMed |
description | The metabolome includes not just known but also unknown metabolites; however, metabolite annotation remains the bottleneck in untargeted metabolomics. Ion mobility – mass spectrometry (IM-MS) has emerged as a promising technology by providing multi-dimensional characterizations of metabolites. Here, we curate an ion mobility CCS atlas, namely AllCCS, and develop an integrated strategy for metabolite annotation using known or unknown chemical structures. The AllCCS atlas covers vast chemical structures with >5000 experimental CCS records and ~12 million calculated CCS values for >1.6 million small molecules. We demonstrate the high accuracy and wide applicability of AllCCS with medium relative errors of 0.5–2% for a broad spectrum of small molecules. AllCCS combined with in silico MS/MS spectra facilitates multi-dimensional match and substantially improves the accuracy and coverage of both known and unknown metabolite annotation from biological samples. Together, AllCCS is a versatile resource that enables confident metabolite annotation, revealing comprehensive chemical and metabolic insights towards biological processes. |
format | Online Article Text |
id | pubmed-7455731 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-74557312020-09-04 Ion mobility collision cross-section atlas for known and unknown metabolite annotation in untargeted metabolomics Zhou, Zhiwei Luo, Mingdu Chen, Xi Yin, Yandong Xiong, Xin Wang, Ruohong Zhu, Zheng-Jiang Nat Commun Article The metabolome includes not just known but also unknown metabolites; however, metabolite annotation remains the bottleneck in untargeted metabolomics. Ion mobility – mass spectrometry (IM-MS) has emerged as a promising technology by providing multi-dimensional characterizations of metabolites. Here, we curate an ion mobility CCS atlas, namely AllCCS, and develop an integrated strategy for metabolite annotation using known or unknown chemical structures. The AllCCS atlas covers vast chemical structures with >5000 experimental CCS records and ~12 million calculated CCS values for >1.6 million small molecules. We demonstrate the high accuracy and wide applicability of AllCCS with medium relative errors of 0.5–2% for a broad spectrum of small molecules. AllCCS combined with in silico MS/MS spectra facilitates multi-dimensional match and substantially improves the accuracy and coverage of both known and unknown metabolite annotation from biological samples. Together, AllCCS is a versatile resource that enables confident metabolite annotation, revealing comprehensive chemical and metabolic insights towards biological processes. Nature Publishing Group UK 2020-08-28 /pmc/articles/PMC7455731/ /pubmed/32859911 http://dx.doi.org/10.1038/s41467-020-18171-8 Text en © The Author(s) 2020 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/. |
spellingShingle | Article Zhou, Zhiwei Luo, Mingdu Chen, Xi Yin, Yandong Xiong, Xin Wang, Ruohong Zhu, Zheng-Jiang Ion mobility collision cross-section atlas for known and unknown metabolite annotation in untargeted metabolomics |
title | Ion mobility collision cross-section atlas for known and unknown metabolite annotation in untargeted metabolomics |
title_full | Ion mobility collision cross-section atlas for known and unknown metabolite annotation in untargeted metabolomics |
title_fullStr | Ion mobility collision cross-section atlas for known and unknown metabolite annotation in untargeted metabolomics |
title_full_unstemmed | Ion mobility collision cross-section atlas for known and unknown metabolite annotation in untargeted metabolomics |
title_short | Ion mobility collision cross-section atlas for known and unknown metabolite annotation in untargeted metabolomics |
title_sort | ion mobility collision cross-section atlas for known and unknown metabolite annotation in untargeted metabolomics |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7455731/ https://www.ncbi.nlm.nih.gov/pubmed/32859911 http://dx.doi.org/10.1038/s41467-020-18171-8 |
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