4.5 Article

Enhanced Lipidome Coverage in Shotgun Analyses by using Gas-Phase Fractionation

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SPRINGER
DOI: 10.1007/s13361-016-1446-5

关键词

Shotgun lipidomics; Gas-phase fractionation; Lipids; Hen model; Lipid metabolism; Polarity switching; Q Exactive Plus

资金

  1. National Institutes of Health [R01GM087964]
  2. W. M. Keck foundation
  3. North Carolina State University

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A high resolving power shotgun lipidomics strategy using gas-phase fractionation and data-dependent acquisition (DDA) was applied toward comprehensive characterization of lipids in a hen ovarian tissue in an untargeted fashion. Using this approach, a total of 822 unique lipids across a diverse range of lipid categories and classes were identified based on their MS/MS fragmentation patterns. Classes of glycerophospholipids and glycerolipids, such as glycerophosphocholines (PC), glycerophosphoethanolamines (PE), and triglycerides (TG), are often the most abundant peaks observed in shotgun lipidomics analyses. These ions suppress the signal from low abundance ions and hinder the chances of characterizing low abundant lipids when DDA is used. These issues were circumvented by utilizing gas-phase fractionation, where DDA was performed on narrow m/z ranges instead of a broad m/z range. Employing gas-phase fractionation resulted in an increase in sensitivity by more than an order ofmagnitude in both positive-and negative-ionmodes. Furthermore, the enhanced sensitivity increased the number of lipids identified by a factor of approximate to 4, and facilitated identification of low abundant lipids from classes such as cardiolipins that are often difficult to observe in untargeted shotgun analyses and require sample-specific preparation steps prior to analysis. This method serves as a resource for comprehensive profiling of lipids from many different categories and classes in an untargeted manner, as well as for targeted and quantitative analyses of individual lipids. Furthermore, this comprehensive analysis of the lipidome can serve as a species-and tissue-specific database for confident identification of other MS-based datasets, such as mass spectrometry imaging.

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