Background

Lipids are essential components of energy metabolism that can be disrupted in metabolic diseases. Lipids comprise various classes, each possessing widely different chemical properties, e.g., steroids are much more non-polar than phospholipids. Due to the widely differing properties, it is difficult to have a single method catered to all the different lipids. As a result, different classes of lipids often have dedicated analytical methods, such as various derivatization techniques, columns, and mass spectrometers, which makes it challenging to have an overview of a broad spectrum of lipids in a single analysis (Wu et al., 2020; Zhao et al., 2020). Another issue of lipid analysis pertains to the triglyceride class. With up to three aliphatic chains attached to a glycerol backbone, the task of identifying and quantifying all species is highly challenging and has been extensively discussed, with each technique having its own limitations and advantages (Han and Ye, 2021). Compared to other methods requiring adaptations, such as two-dimensional LC, argentation, or supercritical fluid chromatography, the method described here provides a broad view of various lipid classes using standard methods that can be done in most laboratories with basic training.

In this protocol, we describe one variant of a lipidomics workflow, originally developed by the mass spectrometry company SCIEX, that covers over five classes of lipids (sphingolipids, phospholipids, glycerolipids, cholesteryl esters, and fatty acids) (Figure 1), including a partial identification of a single aliphatic chain within the neutral lipid, triacylglycerol (Ubhi et al., 2016). The workflow uses a variety of lipid standards, including stable isotopes from ceramides, sphingomyelins, cholesteryl esters, phosphatidylcholines, phosphatidylethanolamines, phosphatidylglycerols, phosphatidylinositols, phosphatidylserines, monoacylglycerols, diacylglycerols, and triacylglycerols. The system uses a normal-phased hydrophilic interaction chromatography (HILIC) column, which separates the lipids by classes as opposed to chain length in reverse-phased systems. In total, the multiple reaction monitoring (MRM) method performs a single-point quantitation of over 1,000 lipid species, providing a convenient overview of common and important lipids for studying metabolic diseases. Here, we apply the techniques to studying the lipidome of liver tissue from a mouse model with non-alcoholic steatohepatitis (NASH). These techniques are not limited to studying the liver but can be applied to other tissues, including cell culture.

Figure 1. Key structural features of five broad categories of lipids are included in the lipidomics panel