Quantitative Lipidomics in a Core Lab: Navigating a Slippery Slope to Success

Successful “global” metabolomics comes from a divide and conquer strategy. The lipidome represents one such partition of the metabolome and includes hydrophobic compounds such as phospholipids, neutral lipids, sphingolipids, glycolipids, fatty acids and steroids. Liquid chromatography coupled to electrospray ionization mass spectrometry is a practical way to interrogate the lipidome from cells, tissues, or biological fluids. While sample preparation and data acquisition methods are straight forward, the challenge and bottleneck comes in data analysis and the subsequent task of reducing data to information. We have developed a general approach to profile and quantitate over twenty lipid classes including 14 polar and 8 neutral lipid classes and applied this approach to the study of brain tissue in a murine model of Huntington's disease. Targeted extraction of the LC-MS data using Sieve (Thermo) provided identification using an accurate mass and retention time approach and quantification of the total lipid for each lipid class was achieved via spiking the sample with a non-endogenous synthetic lipid. Broadly, using a 5 ppm tolerance, ∼300 mono-, di-, and triacylated lipids were annotated for the number of carbon atoms and double bonds and were readily differentiated from ether-containing or oxidized lipids with high confidence. However, definitive acyl assignments were elusive as most m/z values are mixtures of 2-6 isobaric compounds. Heterogeneity was measured using tandem mass spectrometry but manual annotation laborious and time consuming. Alternatively, Lipid Search (Thermo) was able to define the fatty acid profiles efficiently, and by exporting and combining the results with MS data extracted from Sieve, a comprehensive dataset resulted for ∼1200 lipids. While we conclude that we have developed a working pipeline for complex lipid analysis, the general question of whether quantitative lipidomics is a tractable and viable venture for a core lab is an open question and over-arching theme.