Stoichiometric network reconstruction and analysis of yeast sphingolipid metabolism incorporating different states of hydroxylation

• Published in: BioSystems 2011-04, Vol.104 (1), p.63-75
• Main Authors: Kavun Ozbayraktar, Fatma Betul, Ulgen, Kutlu O.
• Format: Article
• Language: English
• Subjects: Adenosine Triphosphate - metabolism; Calcium - metabolism; Calcium sensitivity; Calcium-Binding Proteins - genetics; Calcium-Binding Proteins - metabolism; Cancer; Cell Membrane - metabolism; Computational systems biology; Diglycerides - biosynthesis; Drug targeting; Fatty Acids - metabolism; Flux balance analysis; Gene Deletion; Glycosyltransferases - genetics; Glycosyltransferases - metabolism; Hydroxylation; Membrane Proteins - genetics; Membrane Proteins - metabolism; Models, Biological; Phosphatidic Acids - biosynthesis; Phospholipids - metabolism; Saccharomyces cerevisiae; Saccharomyces cerevisiae - genetics; Saccharomyces cerevisiae - metabolism; Saccharomyces cerevisiae Proteins - genetics; Saccharomyces cerevisiae Proteins - metabolism; Sphingolipids - genetics; Sphingolipids - metabolism; Yeast sphingolipid metabolism
• ISSN: 0303-2647; 1872-8324
• DOI: 10.1016/j.biosystems.2011.01.001

The first elaborate metabolic model of Saccharomyces cerevisiae sphingolipid metabolism was reconstructed in silico. The model considers five different states of sphingolipid hydroxylation, rendering it unique among other models. It is aimed to clarify the significance of hydroxylation on sphingolipids and hence to interpret the preferences of the cell between different metabolic pathway branches under different stress conditions. The newly constructed model was validated by single, double and triple gene deletions with experimentally verified phenotypes. Calcium sensitivity and deletion mutations that may suppress calcium sensitivity were examined by CSG1 and CSG2 related deletions. The model enabled the analysis of complex sphingolipid content of the plasma membrane coupled with diacylglycerol and phosphatidic acid biosynthesis and ATP consumption in in silico cell. The flux data belonging to these critically important key metabolites are integrated with the fact of phytoceramide induced cell death to propose novel potential drug targets for cancer therapeutics. In conclusion, we propose that IPT1, GDA1, CSG and AUR1 gene deletions may be novel candidates of drug targets for cancer therapy according to the results of flux balance and variability analyses coupled with robustness analysis.