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High speed untargeted 4D-lipidomics LC-MS/MS workflows with Parallel Accumulation Serial Fragmentation (PASEF)
EP30382
Poster Title: High speed untargeted 4D-lipidomics LC-MS/MS workflows with Parallel Accumulation Serial Fragmentation (PASEF)
Submitted on 24 Jul 2019
Author(s): Ulrike Schweiger-Hufnagel1, Aiko Barsch1, Sven W. Meyer1
Affiliations: 1Bruker Daltonik GmbH, 28359 Bremen, Germany
Poster Views: 1,081
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Poster Information
Abstract: The search for new and validated biomarkers is of particular interest in clinical areas like oncology1,2 or neurology3. As lipids play an important role in many diseases, the area of lipidomics has become central for clinical research. While there is a more in-depth oriented approach to ID as many lipids as possible, clinically-oriented projects often demand a high-throughput for large sample cohorts. Therefore, a short cycle time per sample is necessary to realize research projects with hundreds or even thousands of samples in a reasonable time frame. In order to keep up with this, the analytical instrumentation needs to deliver a high data quality at high acquisition speeds. This is realized by the PASEF (Parallel Accumulation Serial Frag-mentation) acquisition mode on the timsTOF Pro system.4Summary: The potential of the PASEF acquisition mode to increase the sample throughput was demonstrated. The crucial ability to separate co-eluting isobaric compounds and to identify differences between sample groups was maintained. With this, PASEF is demonstrated to be an optimal acquisition mode for deep profiling applying longer LC gradient times as well as for projects with high turnover needs, e.g. in clinical metabolomics studies. References: (1) Röhrig, F., Schulze, A., Nat. Rev. Cancer 16, 732–749 (2016)
(2) Vriens, K. et al., Nature 566, 403–406 (2019)
(3) Yang, Q., Vijayakumar, A. & Kahn, B. B., Nat. Rev. Mol. Cell Biol. 19, 654–672 (2018)
(4) Meier, F. et al., J. Proteome Res. 14, 5378–5387 (2015)
(5) Shevchenko, A. et al., J. Lipid Res., 49, 1137-1146 (2008)
(6) https://fiehnlab.ucdavis.edu/projects/LipidBlast
(7) Bowden, J. A. et al., J. Lipid Res. 58, 2275–2288 (2017)
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