Comprehensive MS/MS profiling by UHPLC-ESI-QTOF-MS/MS using SWATH data-independent acquisition for the study of platelet lipidomes in coronary artery disease.

A non-targeted lipidomics workflow based on C8 core-shell particle ultra high-performance liquid chromatography (UHPLC) hyphenated to ESI-QTOF-MS in data-independent acquisition (DIA) mode with sequential window acquisition of all theoretical fragment ion spectra (SWATH) was developed and applied to differential platelet lipidomics profiling of cardiovascular disease patients (stable angina pectoris (n = 10), ST-elevated myocardial infarction (n = 13)) against healthy controls (n = 10). DIA with SWATH generates comprehensive MS and MS/MS data throughout the entire chromatograms and all study samples. Hence, chromatograms can be extracted based on precursors or fragments which provided some benefits in terms of assay specificity in some cases. SWATH acquisition offers flexible experimental design with variable Q1 isolation windows. Liquid chromatography as well as SWATH settings were optimized to cover the lipidome of human platelets. The flexibility of the SWATH experiment design was utilized to implement target SWATH windows with narrow 5 Da Q1 precursor ion selection width (multiple reaction monitoring (MRM)-like SWATH windows) for the detection of low abundant oxidized phospholipids. Data processing was performed with MS-DIAL, and its feasibilities and caveats are discussed by illustrative examples. Thereby, identification of lipids is still a bottleneck in non-targeted lipidomics workflow. MS-DIAL, however, offers automatic identification via spectral matching using an in silico library. In total 1971 molecular features were detected cross the samples of which 611 were identified (total score >70%). The quality of the acquired data was validated with embedded quality control samples (n = 11). 80.3% of all features detected in the QC samples showed a coefficient of variation of below 30%. Multivariate statistics were used to visualize differences in the lipidome of distinct sample groups at a false discovery rate of 5%.

[1]  Stuart M. Allen,et al.  Mapping the Human Platelet Lipidome Reveals Cytosolic Phospholipase A2 as a Regulator of Mitochondrial Bioenergetics during Activation , 2016, Cell metabolism.

[2]  Xianlin Han,et al.  Shotgun lipidomics: electrospray ionization mass spectrometric analysis and quantitation of cellular lipidomes directly from crude extracts of biological samples. , 2005, Mass spectrometry reviews.

[3]  David W. Russell,et al.  LMSD: LIPID MAPS structure database , 2006, Nucleic Acids Res..

[4]  R. Schneiter,et al.  Lipid signalling in disease , 2008, Nature Reviews Molecular Cell Biology.

[5]  Matej Oresic,et al.  Informatics and computational strategies for the study of lipids. , 2008, Molecular bioSystems.

[6]  J. Jaumot,et al.  Lipidomic data analysis: tutorial, practical guidelines and applications. , 2015, Analytica chimica acta.

[7]  Xianlin Han,et al.  Accurate mass searching of individual lipid species candidates from high-resolution mass spectra for shotgun lipidomics. , 2014, Rapid communications in mass spectrometry : RCM.

[8]  C. Coman,et al.  Nano-LC/NSI MS Refines Lipidomics by Enhancing Lipid Coverage, Measurement Sensitivity, and Linear Dynamic Range. , 2018, Analytical chemistry.

[9]  R. Gross,et al.  Diabetes-induced changes in specific lipid molecular species in rat myocardium. , 2000, The Biochemical journal.

[10]  T. Schäffer,et al.  Regulation of oxidized platelet lipidome: implications for coronary artery disease , 2017, European heart journal.

[11]  John D. Storey.  The positive false discovery rate: a Bayesian interpretation and the q-value , 2003 .

[12]  J. Bernhagen,et al.  Macrophage Migration Inhibitory Factor Limits Activation-Induced Apoptosis of Platelets via CXCR7-Dependent Akt Signaling , 2014, Circulation research.

[13]  M. Holčapek,et al.  Retention behavior of lipids in reversed-phase ultrahigh-performance liquid chromatography-electrospray ionization mass spectrometry. , 2016, Journal of chromatography. A.

[14]  Marco Y. Hein,et al.  The Perseus computational platform for comprehensive analysis of (prote)omics data , 2016, Nature Methods.

[15]  Xin Lu,et al.  Optimization of large-scale pseudotargeted metabolomics method based on liquid chromatography-mass spectrometry. , 2016, Journal of chromatography. A.

[16]  Xianlin Han,et al.  Plasmalogen deficiency in early Alzheimer's disease subjects and in animal models: molecular characterization using electrospray ionization mass spectrometry , 2001, Journal of neurochemistry.

[17]  Friedrich Spener,et al.  Editorial: What is lipidomics? , 2003 .

[18]  Juan Antonio Vizcaíno,et al.  Shorthand notation for lipid structures derived from mass spectrometry , 2013, Journal of Lipid Research.

[19]  A. Watson,et al.  Thematic Review Lipidomics: a Global Approach to Lipid Analysis in Biological Systems , 2022 .

[20]  Gavin E Reid,et al.  Analytical Challenges and Recent Advances in Mass Spectrometry Based Lipidomics. , 2018, Analytical chemistry.

[21]  Thomas Kraemer,et al.  Liquid chromatography, in combination with a quadrupole time-of-flight instrument (LC QTOF), with sequential window acquisition of all theoretical fragment-ion spectra (SWATH) acquisition: systematic studies on its use for screenings in clinical and forensic toxicology and comparison with informatio , 2014, Analytical chemistry.

[22]  A. Shevchenko,et al.  Lipidomics: coming to grips with lipid diversity , 2010, Nature Reviews Molecular Cell Biology.

[23]  Joshua D. Knowles,et al.  Procedures for large-scale metabolic profiling of serum and plasma using gas chromatography and liquid chromatography coupled to mass spectrometry , 2011, Nature Protocols.

[24]  M. Orešič,et al.  Bioanalytical techniques in nontargeted clinical lipidomics. , 2016, Bioanalysis.

[25]  Oliver Fiehn,et al.  Toward Merging Untargeted and Targeted Methods in Mass Spectrometry-Based Metabolomics and Lipidomics. , 2016, Analytical chemistry.

[26]  Xianlin Han,et al.  Multi-dimensional mass spectrometry-based shotgun lipidomics and novel strategies for lipidomic analyses. , 2012, Mass spectrometry reviews.

[27]  Ludovic C. Gillet,et al.  Targeted Data Extraction of the MS/MS Spectra Generated by Data-independent Acquisition: A New Concept for Consistent and Accurate Proteome Analysis* , 2012, Molecular & Cellular Proteomics.

[28]  Oliver Fiehn,et al.  Comprehensive analysis of lipids in biological systems by liquid chromatography-mass spectrometry. , 2014, Trends in analytical chemistry : TRAC.

[29]  Masanori Arita,et al.  MS-DIAL: Data Independent MS/MS Deconvolution for Comprehensive Metabolome Analysis , 2015, Nature Methods.

[30]  Guan-Yuan Chen,et al.  Off-line mixed-mode liquid chromatography coupled with reversed phase high performance liquid chromatography-high resolution mass spectrometry to improve coverage in lipidomics analysis. , 2017, Analytica chimica acta.

[31]  Lina Zhou,et al.  Simultaneous metabolomics and lipidomics analysis based on novel heart-cutting two-dimensional liquid chromatography-mass spectrometry. , 2017, Analytica chimica acta.

[32]  Herbert Oberacher,et al.  Applying ‘Sequential Windowed Acquisition of All Theoretical Fragment Ion Mass Spectra’ (SWATH) for systematic toxicological analysis with liquid chromatography-high-resolution tandem mass spectrometry , 2014, Analytical and Bioanalytical Chemistry.

[33]  Kazuki Saito,et al.  Hydrogen Rearrangement Rules: Computational MS/MS Fragmentation and Structure Elucidation Using MS-FINDER Software. , 2016, Analytical chemistry.

[34]  Tuulia Hyötyläinen,et al.  Optimizing the lipidomics workflow for clinical studies—practical considerations , 2015, Analytical and Bioanalytical Chemistry.

[35]  Manfred Hallschmid,et al.  Quantification of steroid hormones in plasma using a surrogate calibrant approach and UHPLC-ESI-QTOF-MS/MS with SWATH-acquisition combined with untargeted profiling. , 2018, Analytica chimica acta.

[36]  M. Orešič,et al.  Lipidomics in biomedical research-practical considerations. , 2017, Biochimica et biophysica acta. Molecular and cell biology of lipids.

[37]  A. Davies,et al.  Untargeted UPLC-MS Profiling Pipeline to Expand Tissue Metabolome Coverage: Application to Cardiovascular Disease , 2015, Analytical chemistry.

[38]  R. G. Salomon.  Structural Identification and Cardiovascular Activities of Oxidized Phospholipids , 2012, Circulation research.

[39]  I. Chernushevich,et al.  An introduction to quadrupole-time-of-flight mass spectrometry. , 2001, Journal of mass spectrometry : JMS.

[40]  Ying Zhang,et al.  The Use of Variable Q1 Isolation Windows Improves Selectivity in LC-SWATH-MS Acquisition. , 2015, Journal of proteome research.

[41]  R. Gross.  The evolution of lipidomics through space and time. , 2017, Biochimica et biophysica acta. Molecular and cell biology of lipids.

[42]  R. Subramanian,et al.  Comparison of information-dependent acquisition, SWATH, and MS(All) techniques in metabolite identification study employing ultrahigh-performance liquid chromatography-quadrupole time-of-flight mass spectrometry. , 2014, Analytical chemistry.

[43]  Birgit Schilling,et al.  Repeatability and reproducibility in proteomic identifications by liquid chromatography-tandem mass spectrometry. , 2010, Journal of proteome research.

[44]  Martin Trötzmüller,et al.  Lipidomics by ultrahigh performance liquid chromatography-high resolution mass spectrometry and its application to complex biological samples. , 2017, Journal of chromatography. B, Analytical technologies in the biomedical and life sciences.

[45]  Gérard Hopfgartner,et al.  High-resolution mass spectrometry for integrated qualitative and quantitative analysis of pharmaceuticals in biological matrices , 2012, Analytical and Bioanalytical Chemistry.

[46]  David Broadhurst,et al.  The importance of experimental design and QC samples in large-scale and MS-driven untargeted metabolomic studies of humans. , 2012, Bioanalysis.

[47]  Canan Has,et al.  Identification of key lipids critical for platelet activation by comprehensive analysis of the platelet lipidome. , 2018, Blood.

[48]  Yu Bai,et al.  Lipid metabolism in mouse embryonic fibroblast cells in response to autophagy induced by nutrient stress. , 2017, Analytica chimica acta.

[49]  Gérard Hopfgartner,et al.  Integrated quantification and identification of aldehydes and ketones in biological samples. , 2014, Analytical chemistry.

[50]  M. Lagarde,et al.  Lipidomics is emerging. , 2003, Biochimica et biophysica acta.

[51]  Evelyn Rampler,et al.  Simultaneous non-polar and polar lipid analysis by on-line combination of HILIC, RP and high resolution MS. , 2018, The Analyst.

[52]  Xianlin Han,et al.  Substantial sulfatide deficiency and ceramide elevation in very early Alzheimer's disease: potential role in disease pathogenesis , 2002, Journal of neurochemistry.

[53]  U. Roessner,et al.  A high-resolution HPLC-QqTOF platform using parallel reaction monitoring for in-depth lipid discovery and rapid profiling. , 2018, Analytica chimica acta.

[54]  Evelyn Rampler,et al.  A Novel Lipidomics Workflow for Improved Human Plasma Identification and Quantification Using RPLC-MSn Methods and Isotope Dilution Strategies. , 2018, Analytical chemistry.

[55]  Oliver Fiehn,et al.  LipidBlast - in-silico tandem mass spectrometry database for lipid identification , 2013, Nature Methods.