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Alvarez-Vasquez, F.; Sims, K.J.; Cowart, L.A.; Okamoto, Y.; Voit, E.O.; Hannun, Y.A. (2005) Simulation and validation of modelled sphingolipid metabolism in Saccharomyces cerevisiae. Nature, 433, 425-430. Abstract
A Biochemical Systems Theory approach is used (GMA approximation) to set up a large-scale integrative model (25 dynamic variables) to simulate sphingolipid metabolism. A test of robustness was carried out using sensitivity analysis: the vast majority of the sensitivities were small, indicating attenuation (negative sensitivities) or modest amplification (positive sensitivities) to modest perturbations. But 12.9 % of the logarithmic gains, i.e., the relative sensitivity of the steady-state (concentrations and fluxes) of the systems to independent variables (enzyme activities), were higher than 10 in magnitude, and a few were higher than 100 (a logarithmic gain of +10 indicates that upon a change of +1 % in an independent variable the systems response is +10%). It is always suspicions for the quality of the model when such high values are obtained, but the high logarithmic gains were not found to be randomly distributed through out the model, but were clustered in two groups: to one group the authors attributed a real meaning suggesting a high responsiveness of the sphingolipid pathway to the concentration of the enzymes, while to the other group the authors did not attributed biological relevance and instead suggested it was due to modelling artifacts. Overall the authors considered that the model passed the test of robustness.
Model validation was obtained by comparing simulation results with experimental time courses. Experiments of radioactive incorporation from precursors in the wild-type as well as in mutant strains were performed, and while the agreement was acceptable, the model showed a faster response to perturbations than those observed in experiments. Upon addition of inositol a biphasic response for ceramide concentration (fast decrease and then return to basal levels) was obtained both in simulations and experiments.
After testing the model for robustness and validating it, the authors used the model to make predictions on sphingolipid metabolism. According to the model external palmitate exerts a greater influence on de novo sphingolipid synthesis than endogenous palmitoyl-CoA (i.e., produced from malonyl-CoA). This is a good example of an hypothetical experiment that would be very difficult to perform.
In conclusion, by integrating a large set of quantitative information on sphingolipid metabolism this model can constitute a powerfull tool for a deeper understanding of yeast lipid metabolism. 