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Seminars
Metabolics of Recombant Yeast: Gene Expression, Flux Analysis and a Mathematical Model for Gene Regulation of Metabolism
Professor Juan A. Asenjo
Centre for Biochemical Engineering and Biotechnology
Department of Chemical Engineering and Biotechnology
University of Chile
When: Thursday, March 15, 2007
Time: 2:30 PM to 3:30 PM
Where: 1070 Duncall Hall
Abstract:
Metabolomics provides the tools for detailed analysis of cell metabolism using detailed gene expression data and flux calculations. As a model system we are using a recombinant Saccharomyces cerevisiae that accumulates a very high level of intracellular Superoxide Dismutase (SOD) (ca. 30% of total protein). The results of this study show, for the first time, that it is possible to separate two strains of the same species, the native and the recombinant ones, only on the basis of gene expression data. The ontology of the 4 genes which were under-expressed or over-expressed, in a statistically significant way, in the 3 phases studied (genes CTR3, MUC1, PDR15 and PST1) show that the product is expressed at the plasma membrane level or the cell wall of the yeast. Regarding global gene expression when the 2 strains change from one growth phase to another, a large part of the genetic machinery of both strains is activated when changing from growth on glucose to growth on ethanol. The situation is reversed when passing from growth on ethanol to the stationary phase. The global analysis of the transcription levels of those genes which participate in the central energy metabolic pathways such as glycolysis/gluconeogenesis, TCA cycle and the glyoxylate cycle (genes which have mRNA with long half lives), shows a metabolic burden in the recombinant strain.
A stoichiometric model was built, which included 78 reactions. It allowed calculation of the distribution of metabolic fluxes during diauxic growth on glucose and ethanol. Fermentation profiles and metabolic fluxes were analyzed at different phases of growth for the recombinant strain (P+) and for its wild type (P-). The synthesis of SOD by the strain P+ resulted in a decrease in specific growth rate of 34 and 54 % (on glucose and ethanol respectively) in comparison to the wild type. Both strains exhibited similar flux of glucose consumption and ethanol synthesis but important differences in carbon distribution with biomass/substrate yields and ATP production 50 % lower in P+.
We have developed a continuous mathematical model that simulates gene regulation of the metabolism of both strains. This constitutes a quantitative model to describe the consumption of fermentative and non fermentative carbon sources by yeast, which includes the genetic regulatory network associated. Carbon sources included in this study are glucose (fermentative) and ethanol with glycerol (non fermentative). The metabolic network is modeled with enzymatic reactions and ordinary differential equations, while information of genetic networks is incorporated discretely for each situation. Data of metabolic flux analysis and levels of transcripts were used to fit the model.
The model consists of 44 fluxes, which represent 53 enzymes and 67 genes. Values of rate parameters were calculated for each state. Fluxes found by the model were compared with real ones and 75% accordance was found (admitted error of 20%). A main contribution of this model is to present an easy way to find in vivo rate parameters to model metabolic and genetic networks under different conditions. The behaviour of a recombinant strain growing on glucose, which produces the human protein SOD, was modelled, redefining some rate parameters. 95% accordance (admitted error of 20%) was found in metabolic fluxes. The method is extremely appealing, in contrast with traditional methods of numerical analysis, as it does not require knowledge of every detail of the biochemical reactions.
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