LC-MS Lipidomic Analysis
The Metabolomics Core offers three types of lipidomics services, 1) LC-MS based non-targeted lipidomics, 2) LC-MS based targeted lipidomics, and 3) GC-MS based fatty acid methyl ester (FAMES) analysis for any biological matrix.
LC-MS based non-targeted lipidomics
We employ the Agilent 6530 Accurate Mass Q-TOF dual ESI mass spectrometer operating in positive and negative ionization modes coupled with ultra-high performance liquid chromatography (UHPLC) to assay a broad range of lipid classes from any biological matrix. Most often, we examine the lipid differences found between biological samples after perturbation of a given system. While there is no single analytical platform that can fully characterize the highly diverse lipidome, our sample extraction and preparation strategy coupled with reversed-phase HPLC provides a robust tool to assess the lipid content of any biological system. Lipid class coverage includes PC, PE, PG, PI, PS, DAG, TAG, SM, CE, EE, CER, CL, and all related lyso and plasmalogen species. We typically identify >1000 unique lipid species from our untargeted lipidomics platform.
LC-MS based targeted lipidomics
When researchers wish to quantitate specific lipids in a targeted fashion, we employ the Agilent 6490 Triple Quadrupole mass spectrometer and the SCIEX QTRAP 6500 System coupled with UHPLC from any biological matrix. This type of project is often limited to 200 specific lipids from a subset of lipid classes and new assays require method development. We routinely run targeted assays for acylcarnitines and sphingolipids.
GC-MS based fatty acid methyl ester (FAMES) analysis
The metabolomics core utilizes an HP6890 GC-MS interfaced with a flame ionization detector (FID) to analyze FAMEs. Free fatty acids are esterified using acid-catalysis on a variety of biological matrixes.
Biological sample preparation
Sample collection is a vital part of lipid analysis. With the highly sensitive analysis methods available, only a very small amount of source material is needed. Two points should be kept in mind, 1) the small quantity of sample taken should be representative of the entire source material, and 2) just enough material, but not too much, should be sampled for all of the planned analysis. What is enough material? There is no clear answer for this as all source material will vary. Generally, we recommend a minimum of 5 mg of wet tissue, a million of cells, 20 µL of plasma, or 100 µg of protein from a membrane fraction. Too much material would be approximately 20-fold more than the minimum. We also require the researcher to record those values when preparing their samples. With few exceptions, all samples should be flash-frozen, stored under nitrogen if possible and shipped on dry ice. Researchers are free to label their samples as they see fit, although we do recommend a simple labeling scheme that refers back to detailed sample information. If possible, researchers should generate a blank (negative control) sample in their set.
Software and data analysis
LC-MS and tandem MS (MS/MS) data is analyzed using a suite of software packages including Agilent Mass Hunter Qual, Mass Hunter Quant and Profinder. Lipid annotation is provided by our core utilizing existing databases (LipidMaps, METLIN and Lipid Match). Data analysis is conducted using MetaboAnalyst (PCA, volcano plots, heatmaps).
Publications
Simcox, Judith et al. Global Analysis of Plasma Lipids Identifies Liver-Derived Acylcarnitines as a Fuel Source for Brown Fat Thermogenesis, Cell Metabolism, Volume 26, Issue 3, 509 – 522.e6
Email Dr. Alan Maschek for information.