Comprehensive untargeted polar metabolite analysis using solvent switching liquid chromatography tandem mass spectrometry.

Metabolomics analyses enable the examination and identification of endogenous biochemical reaction products, revealing information on the metabolic pathways and processes active within a living cell or organism. Determination of metabolic shifts can provide important information on a treatment or disease. Unlike other omics fields that typically have analytes of the same chemical class with common building blocks, those that fall under the nomenclature of metabolites encompass a wide array of different compounds with very diverse physiochemical properties. Development of a comprehensive metabolomic pipeline therefore can be a troublesome and complicated process for the analyst. Often single liquid chromatography-mass spectrometry methods on unfractionated samples are carried out in order to be time-efficient, however this could potentially produce data with a low number of identifiable metabolites. In the present studies, we developed a comprehensive polar metabolomics pipeline for cell-based metabolomics. SH-SY5Y neuroblastoma cells were selected as the sample matrix for method development since they are one of the most widely used cell lines for human neurotoxicity studies. This was accomplished by investigating and optimising different mass spectrometry source and chromatographic conditions to enhance the signal of polar metabolites. Optimised hydrophilic interaction liquid chromatography (HILIC) based metabolomic methods at different pH values were examined in positive, negative, and polarity switching modes to determine which combination yielded the highest number of confidently identified metabolites. Additionally, the use of sequentially running two methods was also compared to determine the degree of overlap and whether there is merit in running two separate methods on one sample. It was determined that solvent switching between two optimised methods, acidic chromatographic conditions in positive mode and basic chromatographic conditions in negative mode, yielded the highest number of unique identifiable metabolites. This could be run in a single analytical batch due to the large pH range of the column. A quick switch method in-between each method allowed both conditioning the column and preparation of the MS source conditions for the sequential method.