LC-MS-based lipidomics

The novel approaches in LC-MS-based lipidomics, such as ultra-high performance LC (UHPLC), combined with high-resolution MS methodologies allow fast and reliable analysis of various classes of lipids (33). The modem instruments, with fast duty cycles, allow acquisition of high and low collision energy data simultaneously to provide both data on precursor ions and fragmentation data for all detectable molecular ions (34). 

D1 (10,17S-docosatriene) from DHA using tandem liquid chromatography-photodiode array-electrospray ionization-tandem mass spectrometry (LC-PDA-ESI-MS-MS)-based lipidomic analysis have been documented in ischemic brain [4] and retinal pigment epithelium [5], This new lipid is called neuroprotectin D1 (1) because of its neuro-protectiveproperties in brain ischemia-reperfusion [4] and in oxidative stress-challenged retinal pigment epithelial cells [5] (2) because of its potent ability to inactivate proapoptotic signaling (see apoptosis, Ch. 35) [5] and (3) because it is the first identified neuroprotective mediator derived from DHA. 

Several new methods were developed including both ELISA and liquid chromatography-tandem mass spectrometry (LC/MS/MS)-based lipidomics for... 

Although many systematic indices (e.g.. Lipid MAPS, Chemical Entries of Biological Interest (ChEBI), lUPAC International Chemical Identifiers (InChl), simplified molecular-input line entry system (SMILES)) were developed to list the chemical compounds, these indices (identifiers) can only be meaningful if the compound is totally identified. However, in practice, lipidomics analysis in many cases can only provide partial identification of lipid molecular structures at the current development of technology. Moreover, different lipidomics approaches provide different levels of stmctural identification of lipid species. Therefore, how to clearly express and report the information about the levels of identification for the structures of lipid species (which can be derived fi om MS analysis) is not only helpful for the readers but also important for bioinformatics and data communication. To this end, the analysis by shotgun lipidomics could be used as a typical example to explain these levels. Similar phenomena also exist in the analysis of lipid species employing LC-MS-based approaches. 

As lipidomic analysis is classified into the LC-MS-based approach and shotgun lipidomics, the requirement for sample preparation is also different. The former is more tolerant with the presence of inorganic ions in lipid extracts than the latter since the pre-column or even the analytical column can get rid of these extraction contaminants. However, the presence of inorganic residues may affect substantially the ionization stability as well as ionization efficiencies of different lipid classes and individual species of a class in shotgun lipidomics. Therefore, minimizing the inorganic residues, particularly eliminating any aqueous phase contamination, becomes crucial. 

For both shotgun lipidomics and LC-MS-based approaches, the dynamic range should be examined in the presence of sample matrices instead of using a pure standard. Under such conditions, the matrix effects (e.g., ion suppression) that become more severe in analysis of minor species (or classes) in the presence of abundant species (or classes) can be eliminated for sample analysis. 

Advanced analytical techniques, particularly mass spectrometry (MS), often combined with liquid chromatography (LC) or gas chromatography (GC), are requisite for lipid analysis and they have played the crucial role in the emergence as well as the progresses of lipidomics. MS is the principal choice for the lipid analysis, particularly using electrospray ionization (ESI) and sometimes also atmospheric pressure chemical ionization or laser-based MS methods for surface analysis. The MS-based techniques are the best choice for lipidomics due to their superior sensitivity and molecular specificity, and because they provide the ability to resolve the extensive compositional and structural diversity of lipids in biological systems. 

Lee et al. [41] developed a method for the quantitative analysis of enantiomers and regioisomers of fatty acids, hydroxy fatty acids, and related substances, including several HETEs and prostaglandins. The method is based on pre-column derivatization to pentafluorobenzyl derivatives and subsequent LC-MS analysis in an organic mobile phase using electron-capture negative-ionization (ECNI). The method is applied to lipidomic profiling, for instance of rat epithehal cells. 

Since data analysis is a complicated and very time-consuming task, attempts have been made to automate this process. Kurvinen et al. have developed an algorithm that allows automated assignment and quantification of TAGs based on MS data [35,36]. A similar algorithm was implemented by Liebisch et al. for determination of PC and SM species from PI spectra [37]. Han and Gross have published a protocol for the analysis of phospholipid and triglyceride molecular species (with acyl chain information) based on a two-dimensional matrix of data produced by multiple MS/MS scans [4]. We have recently developed a method that allows accurate quantitative analysis of lipidomes based on two-dimensional LC-MS data [19]. 

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