RESEARCH PAPER Hybrid SWATH/MS and HR-SRM/MS acquisition for phospholipidomics using QUAL/QUANT data processing Michel Raetz 1 & Eva Duchoslav 2 & Ron Bonner 3 & Gérard Hopfgartner 1 Received: 14 April 2019 /Revised: 16 May 2019 /Accepted: 24 May 2019 # Springer-Verlag GmbH Germany, part of Springer Nature 2019 Abstract A hybrid SWATH/MS and HR-SRM/MS acquisition approach using multiple unit mass windows and 100 u precursor selection windows has been developed to interface with a chromatographic lipid class separation. The method allows for the simultaneous monitoring of sum compositions in MS1 and up to 48 lipids in MS2 per lipid class. A total of 240 lipid sum compositions from five phospholipid classes could be monitored in MS2 (HR-SRM/MS) while there was no limitation in the number of analytes in MS1 (HR-SIM/MS). On average, 92 lipid sum compositions and 75 lipid species could be quantified in human plasma samples. The robustness and precision of the workflow has been assessed using technical triplicates of the subject samples. Lipid identification was improved using a combined qualitative and quantitative data processing based on prediction instead of library search. Lipid class specific extracted ion currents of precursors and the corresponding molecular species fragments were extracted based on the information obtained from lipid building blocks and a combinatorial strategy. The SWATH/MS approach with the post-acquisition processing is not limited to the analyzed phospholipid classes and can be applied to other analytes and samples of interest. Keywords Glycerophospholipids . Plasma . HILIC . SWATH . QUAL/QUANT . Data processing Introduction Monitoring lipid quantities and profiles in body fluids and tissues is of great interest as they can potentially be used as biomarkers for cancer [1], cardiovascular diseases [2], or neu- rology [3] and other diseases. As glycerophospholipids (PL) are major representatives within the broad diversity of lipids that have been shown to be affected by different physiological conditions [4], quantitative analytical methods are needed to support the understanding of biological processes. As highlighted by Liebisch et al. and Burla et al. [5, 6], lipidomics data should be reported as absolute chemical amounts, since fold changes do not allow for statements of the dynamic range or the importance of changes from a more holistic point of view and make interlaboratory data assessment difficult. Lipid analysis is challenging due to their structural diversi- ty and the complexity of the lipidome. Lipid Maps, the largest publicly available lipid database, currently consists of 21,408 curated and 21,953 in silico generated structural entries (total of 43,361 entries) from eight different lipid categories (as of 03/06/2019) [7]. Mass spectrometry-based lipidomics ap- proaches are generally conducted on triple quadrupole instru- ments (QqQ) using selected reaction monitoring (SRM) [8–10] or on high-resolution mass spectrometers (HRMS) with precursor quantification [10–12]. Samples are introduced to the MS with or without prior separation the latter often using separations of lipid classes by normal phase (NP) [13], hydrophilic interaction (HILIC) [11, 14, 15], or supercritical fluid chromatography (SFC) [9, 10] and ion mobility driven approaches (DMS [16], FAIMS [17]). In quantitative analy- ses, class separation is preferred to reverse phase chromatog- raphy, as all the lipids of the same class co-elute and undergo the same ion suppression or enhancement [5]. This allows for quantification with a single labeled or odd carbon number Electronic supplementary material The online version of this article (https://doi.org/10.1007/s00216-019-01946-4) contains supplementary material, which is available to authorized users. * Gérard Hopfgartner gerard.hopfgartner@unige.ch 1 Life Sciences Mass Spectrometry, Department of Inorganic and Analytical Chemistry, University of Geneva, 24 Quai Ernest Ansermet, CH-1211 Geneva 4, Switzerland 2 SCIEX, 71 Four Valley Drive, Concord, ON L4K 4V8, Canada 3 Ron Bonner Consulting, Newmarket, ON L3Y 3C7, Canada Analytical and Bioanalytical Chemistry https://doi.org/10.1007/s00216-019-01946-4