Application of a novel mass spectral data acquisition approach to lipidomic analysis of liver extracts from sitaxentan-treated liver-humanized PXB mice.
File(s)SONAR accepted version.docx (2.21 MB)
Accepted version
Author(s)
Type
Journal Article
Abstract
The application of a data-independent acquisition (DIA) method ("SONAR") that employs a rapidly scanning quadrupole is described for the lipidomic analysis of complex biological extracts. Using this approach, the MS acquisition window can be varied between 1 and 25 Da, enabling the isolation of ions prior to their entering the collision cell. By rapidly scanning the resolving quadrupole window over a specified mass range, co-eluting precursor ions are transmitted sequentially into the collision cell, where collision energies are cycled between low and elevated levels to induce fragmentation. This method of data generation provides both precursor and fragment ion information at high specificity, allowing for greater accuracy of compound identification, whether using a database, spectral libraries, or comparison to authentic standards. The value of the approach in simplifying and "de-cluttering" the spectra of co-eluting lipids is shown with examples from lipidomic profiles obtained in investigations of the composition of organic extracts of livers obtained from SCID and chimeric liver-humanized mice administered under various experimental conditions.
Date Issued
2019-11-01
Date Acceptance
2019-09-24
Citation
Journal of Proteome Research, 2019, 18 (11), pp.4055-4064
ISSN
1535-3893
Publisher
American Chemical Society
Start Page
4055
End Page
4064
Journal / Book Title
Journal of Proteome Research
Volume
18
Issue
11
Copyright Statement
© 2019 American Chemical Society. This document is the Accepted Manuscript version of a Published Work that appeared in final form in Journal of Proteome Research, after peer review and technical editing by the publisher. To access the final edited and published work see https://doi.org/10.1021/acs.jproteome.9b00334
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/31550900
Subjects
LC-MS/MS
Q-Tof MS
data-independent acquisition (DIA)
lipidomics
metabolites
sitaxentan
Publication Status
Published
Coverage Spatial
United States
Date Publish Online
2019-09-24