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Q-RAI data-independent acquisition for lipidomic quantitative profiling
Untargeted lipidomics has been increasingly adopted for hypothesis generation in a biological context or discovery of disease biomarkers. Most of the current liquid chromatography mass spectrometry (LC–MS) based untargeted methodologies utilize a data dependent acquisition (DDA) approach in pooled s...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10630469/ https://www.ncbi.nlm.nih.gov/pubmed/37935746 http://dx.doi.org/10.1038/s41598-023-46312-8 |
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author | Chang, Jing Kai Teo, Guoshou Pewzner-Jung, Yael Cuthbertson, Daniel J. Futerman, Anthony H. Wenk, Markus R. Choi, Hyungwon Torta, Federico |
author_facet | Chang, Jing Kai Teo, Guoshou Pewzner-Jung, Yael Cuthbertson, Daniel J. Futerman, Anthony H. Wenk, Markus R. Choi, Hyungwon Torta, Federico |
author_sort | Chang, Jing Kai |
collection | PubMed |
description | Untargeted lipidomics has been increasingly adopted for hypothesis generation in a biological context or discovery of disease biomarkers. Most of the current liquid chromatography mass spectrometry (LC–MS) based untargeted methodologies utilize a data dependent acquisition (DDA) approach in pooled samples for identification and MS-only acquisition for semi-quantification in individual samples. In this study, we present for the first time an untargeted lipidomic workflow that makes use of the newly implemented Quadrupole Resolved All-Ions (Q-RAI) acquisition function on the Agilent 6546 quadrupole time-of-flight (Q-TOF) mass spectrometer to acquire MS2 spectra in data independent acquisition (DIA) mode. This is followed by data processing and analysis on MetaboKit, a software enabling DDA-based spectral library construction and extraction of MS1 and MS2 peak areas, for reproducible identification and quantification of lipids in DIA analysis. This workflow was tested on lipid extracts from human plasma and showed quantification at MS1 and MS2 levels comparable to multiple reaction monitoring (MRM) targeted analysis of the same samples. Analysis of serum from Ceramide Synthase 2 (CerS2) null mice using the Q-RAI DIA workflow identified 88 lipid species significantly different between CerS2 null and wild type mice, including well-characterized changes previously associated with this phenotype. Our results show the Q-RAI DIA as a reliable option to perform simultaneous identification and reproducible relative quantification of lipids in exploratory biological studies. |
format | Online Article Text |
id | pubmed-10630469 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-106304692023-11-07 Q-RAI data-independent acquisition for lipidomic quantitative profiling Chang, Jing Kai Teo, Guoshou Pewzner-Jung, Yael Cuthbertson, Daniel J. Futerman, Anthony H. Wenk, Markus R. Choi, Hyungwon Torta, Federico Sci Rep Article Untargeted lipidomics has been increasingly adopted for hypothesis generation in a biological context or discovery of disease biomarkers. Most of the current liquid chromatography mass spectrometry (LC–MS) based untargeted methodologies utilize a data dependent acquisition (DDA) approach in pooled samples for identification and MS-only acquisition for semi-quantification in individual samples. In this study, we present for the first time an untargeted lipidomic workflow that makes use of the newly implemented Quadrupole Resolved All-Ions (Q-RAI) acquisition function on the Agilent 6546 quadrupole time-of-flight (Q-TOF) mass spectrometer to acquire MS2 spectra in data independent acquisition (DIA) mode. This is followed by data processing and analysis on MetaboKit, a software enabling DDA-based spectral library construction and extraction of MS1 and MS2 peak areas, for reproducible identification and quantification of lipids in DIA analysis. This workflow was tested on lipid extracts from human plasma and showed quantification at MS1 and MS2 levels comparable to multiple reaction monitoring (MRM) targeted analysis of the same samples. Analysis of serum from Ceramide Synthase 2 (CerS2) null mice using the Q-RAI DIA workflow identified 88 lipid species significantly different between CerS2 null and wild type mice, including well-characterized changes previously associated with this phenotype. Our results show the Q-RAI DIA as a reliable option to perform simultaneous identification and reproducible relative quantification of lipids in exploratory biological studies. Nature Publishing Group UK 2023-11-07 /pmc/articles/PMC10630469/ /pubmed/37935746 http://dx.doi.org/10.1038/s41598-023-46312-8 Text en © The Author(s) 2023 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Chang, Jing Kai Teo, Guoshou Pewzner-Jung, Yael Cuthbertson, Daniel J. Futerman, Anthony H. Wenk, Markus R. Choi, Hyungwon Torta, Federico Q-RAI data-independent acquisition for lipidomic quantitative profiling |
title | Q-RAI data-independent acquisition for lipidomic quantitative profiling |
title_full | Q-RAI data-independent acquisition for lipidomic quantitative profiling |
title_fullStr | Q-RAI data-independent acquisition for lipidomic quantitative profiling |
title_full_unstemmed | Q-RAI data-independent acquisition for lipidomic quantitative profiling |
title_short | Q-RAI data-independent acquisition for lipidomic quantitative profiling |
title_sort | q-rai data-independent acquisition for lipidomic quantitative profiling |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10630469/ https://www.ncbi.nlm.nih.gov/pubmed/37935746 http://dx.doi.org/10.1038/s41598-023-46312-8 |
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