Flexibility of a eukaryotic lipidome--insights from yeast lipidomics

Mass spectrometry-based shotgun lipidomics has enabled the quantitative and comprehensive assessment of cellular lipid compositions. The yeast Saccharomyces cerevisiae has proven to be a particularly valuable experimental system for studying lipid-related cellular processes. Here, by applying our sh...

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Bibliographic Details
Published in:PloS one 2012-04, Vol.7 (4), p.e35063-e35063
Main Authors: Klose, Christian, Surma, Michal A, Gerl, Mathias J, Meyenhofer, Felix, Shevchenko, Andrej, Simons, Kai
Format: Article
Language:English
Subjects:
Baking yeast
Biochemistry
Biology
Caenorhabditis elegans
Carbon - metabolism
Cell cycle
Chemistry
Cluster Analysis
E coli
Enzymes
Ergosterol
Escherichia coli
Fatty acids
Flexibility
Genomes
Glycerol
Growth conditions
Lipid Metabolism
Lipids
Lipids - classification
Mass Spectrometry
Mass spectroscopy
Metabolism
Molecular biology
Nematodes
Physiological aspects
Phytosterols
Plasma
Plasmids
Saccharomyces cerevisiae
Saccharomyces cerevisiae - chemistry
Saccharomyces cerevisiae - growth & development
Saccharomyces cerevisiae - metabolism
Sphingolipids
Sterols
Temperature
Triglycerides
Yeast
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Summary:Mass spectrometry-based shotgun lipidomics has enabled the quantitative and comprehensive assessment of cellular lipid compositions. The yeast Saccharomyces cerevisiae has proven to be a particularly valuable experimental system for studying lipid-related cellular processes. Here, by applying our shotgun lipidomics platform, we investigated the influence of a variety of commonly used growth conditions on the yeast lipidome, including glycerophospholipids, triglycerides, ergosterol as well as complex sphingolipids. This extensive dataset allowed for a quantitative description of the intrinsic flexibility of a eukaryotic lipidome, thereby providing new insights into the adjustments of lipid biosynthetic pathways. In addition, we established a baseline for future lipidomic experiments in yeast. Finally, flexibility of lipidomic features is proposed as a new parameter for the description of the physiological state of an organism.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0035063