Journal
ANALYTICA CHIMICA ACTA
Volume 972, Issue -, Pages 62-72Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.aca.2017.04.008
Keywords
Parallel reaction monitoring; Targeted lipidomics; Systemic lupus erythematosus; Mass spectrometry
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Funding
- National Natural Science Foundation of China [81430056, 31420103905, 81372491]
- National Key Research and Development Program of China [2016YFA0500302]
- Beijing Natural Science Foundation [7161007]
- Lam Chung Nin Foundation for Systems Biomedicine
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Advances in high-resolution mass spectrometers with faster scanning capabilities and higher sensitivities have expanded these instruments' functionality beyond traditional data-dependent acquisition in targeted metabolomics. Apart from the traditional multiple reaction monitoring strategy, the parallel reaction monitoring (PRM) strategy is also used for targeted metabolomics quantification. The high resolution and mass accuracy of full-scan (MS1) and tandem mass spectrometry (MS/MS) scan result in sufficient selectivity by monitoring all MS/MS fragment ions for each target precursor and simultaneously providing flexibility in assay method construction and post-acquisition data analysis. In this study, using an orthogonal quadrupole-time of flight liquid chromatography-mass spectrometry system (QTOF LC-MS), we investigated the applicability of a large-scale targeted lipidomic assay using scheduled PRM. This method monitored 222 lipids belonging to 15 lipid species in serum. Robustness, reproducibility, and quantitative performance were assessed using chemical standards and serum samples. Finally, we demonstrated the application of this PRM-based targeted metabolomic workflow to systemic lupus erythematosus, a severe autoimmunological disease. Results showed that 63 lipids belonging to 11 lipid species were significantly changed. In summary, at the first time, a robust targeted lipidomic workflow was established using PRM acquisition strategy on a Q-TOF platform, providing another powerful tool for targeted metabolomic analysis. (C) 2017 Elsevier B.V. All rights reserved.
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