Lipidomics provides great insights into disease states, but identifying target lipids is not an easy task. The lipidome is highly complex and includes eight major categories of lipids, over 80 major classes, 300 sub-classes and thousands of lipid species.1
High-performance liquid chromatography and tandem mass spectrometry (HPLC MS/MS) methods can identify complex lipids and separate many overlapping isomeric or isobaric molecular ions. Looking to further improve lipid identification, Kiyonami et al. recently demonstrated liquid chromatography separation by comparing a new Acclaim C30 column (Thermo Scientific) with a conventional C18 column.2 The researchers obtained three human serum samples and one human plasma sample from the National Institute of Standards and Technology for study.
The lipid profiling workflow included a Dionex UltiMate 3000 Rapid Separation LC (RSLC) system (Thermo Scientific) with either a traditional C18 column, or a small particle (1.9 µm), 25 cm long Acclaim C30 column. The team extracted serum samples using chloroform, methanol and water as solvents. They also used a Q Exactive HF hybrid quadrupole-Orbitrap mass spectrometer to identify and quantify lipids. To further analyze MS data, the team used LipidSearch Software (Thermo Scientific). In particular, the team used the LipidSearch software to identify the lipid species and align the search results for lipid profiling.
Using this strategy, Kiyonami et al. identified and quantified approximately 1,000 molecular lipid species (including all isomers) with a lower than 15% coefficient of variation. The researchers were able to successfully detect 14 triglyceride (TG) (55:3) isomer peaks using the C30 column, while the C18 column detected only 5 TG (55:3) isomer peaks.
The team repeated the experiment using a bovine heart lipid extract and again identified more lipid species using the C30 column than when using conventional C18 columns. These results reveal a definite advantage with the C30 column over the traditional C18 column.
1. Fahy, E., et al.(2009) “Update of the LIPID MAPS comprehensive classification system for lipids,” Journal of Lipid Research, 50(S9-S14), doi: 10.1194/jlr.R800095-JLR200.
2. Kiyonami, R., et al. (2015) “Large scale lipid profiling of a human serum lipidome using a high resolution accurate mass LC/MS/MS approach,” Thermo Scientific.