Untargeted and Semi-targeted Lipid Analysis of Biological Samples Using Mass Spectrometry-Based Metabolomics
Liquid chromatography coupled to mass spectrometry (LC-MS)-based metabolomics and lipidomics offers invaluable tools to qualitatively and quantitatively study biological systems. Historically, unbiased (or discovery) analysis has been performed independen
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uction Technological developments in mass spectrometers over the past decade have enabled these instruments to rapidly scan through wide mass ranges to profile compounds with largely varying abundances, all while maintaining high mass accuracy and resolving power [1–3]. While tandem in-space instruments such as the triple quadrupole (QqQ) have served as a standard instrument for quantitative analyses due to high sensitivity and specificity [2], recent improvements to the tandem in-time quadrupole-Orbitrap, such as the Q Exactive HF, now achieve scanning up to 18 Hz with a resolving power up to 240,000 (FWHM) at 200 m/z, thus providing enhanced spectral quality and femtogram-level sensitivity over a dynamic concentration range of more than four orders of magnitude [4]. These advancements provide researchers with not only a
Angelo D’Alessandro (ed.), High-Throughput Metabolomics: Methods and Protocols, Methods in Molecular Biology, vol. 1978, https://doi.org/10.1007/978-1-4939-9236-2_8, © Springer Science+Business Media, LLC, part of Springer Nature 2019
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robust tool to study complex samples from a systems-wide perspective [5] but also the opportunity to achieve both a discovery analysis—where data on features within a particular mass range are collected in an unbiased fashion—as well as a quantitative, semi-targeted analysis all within the same analytical run without significant sacrifice of analytical fidelity. Using a stable-isotope dilution (SID) approach, samples are extracted with exogenously added isotopologues of compounds of interest, which, by compensating for extraction efficiency and matrix effects, can then be subsequently used for quantification by peak area comparison [6, 7]. As the data from these runs are acquired in an unbiased fashion (e.g., scanning within a mass range of 90–1250 m/z), data can be interrogated post hoc to provide information on the lipidome at large, in addition to the quantitative information provided by SID, thereby enabling a high-throughput robust method to quantitatively measure systems. This approach thus maintains the hypothesis-generating capabilities of discovery analysis while providing quantitative information that is important for assessing the magnitude of a biological effect and enabling the direct comparison of datasets generated on varying technological platforms [8]. In this chapter, we demonstrate examples of this approach to quantify bile acids and oxylipids, while gathering additional data in a wider mass range capable of detecting species from cholesterol, cholesteryl ester, monoacylglyceride, diacylglyceride, triacylglyceride, sphingomyelin, phosphatidylcholine, phosphatidylethanolamine, phosphatidylserine, phosphatidylinositol, and lysophospholipid compound classes for follow-up discovery analyses. These lipid classes offer important information regarding the energy, inflammatory, and stress status of the system. Produced in the liver, bile acids are involved in complex signaling pathways that link gut microbiota with gast
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