Q-RAI data-independent acquisition for lipidomic quantitative profiling.

Chang, Jing Kai, Teo, Guoshou, Pewzner-Jung, Yael, Cuthbertson, Daniel J ORCID: 0000-0002-6128-0822, Futerman, Anthony H, Wenk, Markus R, Choi, Hyungwon ORCID: 0000-0002-6687-3088 and Torta, Federico
(2023) Q-RAI data-independent acquisition for lipidomic quantitative profiling. Scientific reports, 13 (1). 19281-.

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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.

Item Type: Article
Uncontrolled Keywords: Animals, Humans, Mice, Ions, Lipids, Chromatography, Liquid, Mass Spectrometry, Lipidomics
Divisions: Faculty of Health and Life Sciences
Faculty of Health and Life Sciences > Institute of Life Courses and Medical Sciences
Depositing User: Symplectic Admin
Date Deposited: 21 Dec 2023 16:50
Last Modified: 21 Dec 2023 16:50
DOI: 10.1038/s41598-023-46312-8
Open Access URL: https://doi.org/10.1038/s41598-023-46312-8
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3177607