Primary Metabolism and Medium-Chain Fatty Acid Alterations Precede Long-Chain Fatty Acid Changes Impacting Neutral Lipid Metabolism in Response to an Anticancer Lysophosphatidylcholine Analogue in Yeast.

The nonmetabolizable lysophosphatidylcholine (LysoPC) analogue edelfosine is the prototype of a class of compounds being investigated for their potential as selective chemotherapeutic agents. Edelfosine targets membranes, disturbing cellular homeostasis. Is not clear at this point how membrane alterations are communicated between intracellular compartments leading to growth inhibition and eventual cell death. In the present study, a combined metabolomics/lipidomics approach for the unbiased identification of metabolic pathways altered in yeast treated with sublethal concentrations of the LysoPC analogue was employed. Mass spectrometry of polar metabolites, fatty acids, and lipidomic profiling was used to study the effects of edelfosine on yeast metabolism. Amino acid and sugar metabolism, the Krebs cycle, and fatty acid profiles were most disrupted, with polar metabolites and short-medium chain fatty acid changes preceding long and very long-chain fatty acid variations. Initial increases in metabolites such as trehalose, proline, and γ-amino butyric acid with a concomitant decrease in metabolites of the Krebs cycle, citrate and fumarate, are interpreted as a cellular attempt to offset oxidative stress in response to mitochondrial dysfunction induced by the treatment. Notably, alanine, inositol, and myristoleic acid showed a steady increase during the period analyzed (2, 4, and 6 h after treatment). Of importance was the finding that edelfosine induced significant alterations in neutral glycerolipid metabolism resulting in a significant increase in the signaling lipid diacylglycerol.

Evaluation of extraction protocols for simultaneous polar and non-polar yeast metabolite analysis using multivariate projection methods.

Metabolomic and lipidomic approaches aim to measure metabolites or lipids in the cell. Metabolite extraction is a key step in obtaining useful and reliable data for successful metabolite studies. Significant efforts have been made to identify the optimal extraction protocol for various platforms and biological systems, for both polar and non-polar metabolites. Here we report an approach utilizing chemoinformatics for systematic comparison of protocols to extract both from a single sample of the model yeast organism Saccharomyces cerevisiae. Three chloroform/methanol/water partitioning based extraction protocols found in literature were evaluated for their effectiveness at reproducibly extracting both polar and non-polar metabolites. Fatty acid methyl esters and methoxyamine/trimethylsilyl derivatized aqueous compounds were analyzed by gas chromatography mass spectrometry to evaluate non-polar or polar metabolite analysis. The comparative breadth and amount of recovered metabolites was evaluated using multivariate projection methods. This approach identified an optimal protocol consisting of 64 identified polar metabolites from 105 ion hits and 12 fatty acids recovered, and will potentially attenuate the error and variation associated with combining metabolite profiles from different samples for untargeted analysis with both polar and non-polar analytes. It also confirmed the value of using multivariate projection methods to compare established extraction protocols.