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Data Processing of Product Ion Spectra: Quality Improvement by Averaging Multiple Similar Spectra of Small Molecules

In metabolomics studies using high-resolution mass spectrometry (MS), a set of product ion spectra is comprehensively acquired from observed ions using the data-dependent acquisition (DDA) mode of various tandem MS. However, especially for low-intensity signals, it is sometimes difficult to distingu...

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Autores principales: Matsuda, Fumio, Komori, Shuka, Yamada, Yuki, Hara, Daiki, Okahashi, Nobuyuki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Mass Spectrometry Society of Japan 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9853114/
https://www.ncbi.nlm.nih.gov/pubmed/36713802
http://dx.doi.org/10.5702/massspectrometry.A0106
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author Matsuda, Fumio
Komori, Shuka
Yamada, Yuki
Hara, Daiki
Okahashi, Nobuyuki
author_facet Matsuda, Fumio
Komori, Shuka
Yamada, Yuki
Hara, Daiki
Okahashi, Nobuyuki
author_sort Matsuda, Fumio
collection PubMed
description In metabolomics studies using high-resolution mass spectrometry (MS), a set of product ion spectra is comprehensively acquired from observed ions using the data-dependent acquisition (DDA) mode of various tandem MS. However, especially for low-intensity signals, it is sometimes difficult to distinguish artifact signals from true fragment ions derived from a precursor ion. Inadequate precision in the measured m/z value is also one of the bottlenecks to narrowing down the candidate compositional formula. In this study, we report that averaging multiple product ion spectra can improve m/z precision as well as the reliability of fragment ions that are observed in such spectra. A graph-based method was applied to cluster a set of similar spectra from multiple DDA data files resulting in creating an averaged product-ion spectrum. The error levels for the m/z values declined following the central limit theorem, which allowed us to reduce the number of candidate compositional formulas. The improved reliability and precision of the averaged spectra will contribute to a more efficient annotation of product ion spectral data.
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spelling pubmed-98531142023-01-26 Data Processing of Product Ion Spectra: Quality Improvement by Averaging Multiple Similar Spectra of Small Molecules Matsuda, Fumio Komori, Shuka Yamada, Yuki Hara, Daiki Okahashi, Nobuyuki Mass Spectrom (Tokyo) Original Article In metabolomics studies using high-resolution mass spectrometry (MS), a set of product ion spectra is comprehensively acquired from observed ions using the data-dependent acquisition (DDA) mode of various tandem MS. However, especially for low-intensity signals, it is sometimes difficult to distinguish artifact signals from true fragment ions derived from a precursor ion. Inadequate precision in the measured m/z value is also one of the bottlenecks to narrowing down the candidate compositional formula. In this study, we report that averaging multiple product ion spectra can improve m/z precision as well as the reliability of fragment ions that are observed in such spectra. A graph-based method was applied to cluster a set of similar spectra from multiple DDA data files resulting in creating an averaged product-ion spectrum. The error levels for the m/z values declined following the central limit theorem, which allowed us to reduce the number of candidate compositional formulas. The improved reliability and precision of the averaged spectra will contribute to a more efficient annotation of product ion spectral data. The Mass Spectrometry Society of Japan 2022 2022-12-15 /pmc/articles/PMC9853114/ /pubmed/36713802 http://dx.doi.org/10.5702/massspectrometry.A0106 Text en Copyright © 2022 Fumio Matsuda, Shuka Komori, Yuki Yamada, Daiki Hara, and Nobuyuki Okahashi. https://creativecommons.org/licenses/by/2.5/This is an open-access article distributed under the terms of Creative Commons Attribution Non-Commercial 4.0 International License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Original Article
Matsuda, Fumio
Komori, Shuka
Yamada, Yuki
Hara, Daiki
Okahashi, Nobuyuki
Data Processing of Product Ion Spectra: Quality Improvement by Averaging Multiple Similar Spectra of Small Molecules
title Data Processing of Product Ion Spectra: Quality Improvement by Averaging Multiple Similar Spectra of Small Molecules
title_full Data Processing of Product Ion Spectra: Quality Improvement by Averaging Multiple Similar Spectra of Small Molecules
title_fullStr Data Processing of Product Ion Spectra: Quality Improvement by Averaging Multiple Similar Spectra of Small Molecules
title_full_unstemmed Data Processing of Product Ion Spectra: Quality Improvement by Averaging Multiple Similar Spectra of Small Molecules
title_short Data Processing of Product Ion Spectra: Quality Improvement by Averaging Multiple Similar Spectra of Small Molecules
title_sort data processing of product ion spectra: quality improvement by averaging multiple similar spectra of small molecules
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9853114/
https://www.ncbi.nlm.nih.gov/pubmed/36713802
http://dx.doi.org/10.5702/massspectrometry.A0106
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