(173c) Comparative Stochastic Analysis of the GAL Switch in Saccharomyces Cerevisiae and Kluyveromyces Lactis: Modeling and Experiments

Both Saccharomyces cerevisiae and Kluyveromyces lactis, which share a common ancestry [1], utilize galactose as an alternate carbon and energy source in the absence of glucose. Galactose metabolism is tightly regulated in these microorganisms, and the uptake of galactose is governed by the Leloir pathway using enzymes produced via the GAL genetic switch. The mechanism of the GAL switch, however, is different in the two organisms. In this contribution, we perform stochastic analysis, through a mix of modeling and experiments, on wild type and mutant strains of S. cerevisiae and K. lactis to quantify the effect of these differences.

In the GAL switch in S. cerevisiae, galactose (an inducer) elicits a sigmoidal switch-like response for the expression of GAL genes. GAL genes are switched on by a transcriptional activator, Gal4p, which is under glucose repression. In a wild type strain, Gal4p itself is regulated by a repressor (Gal80p) and an inducer (Gal3p), both of which are under the control of the GAL switch (autoregulation). The Gal4p synthesis is regulated by a kinase, Mig1p, whose unphosphorylated form enters the nucleus to repress the synthesis of Gal4p. The phosphorylation cycle is tightly controlled by glucose concentration in the cytoplasm. Thus, the levels of glucose determine the fraction of Mig1p available in the nucleus. However, the GAL genetic switch in a mutant yeast strain lacking Gal80p responds only to changes in Gal4p, which is in turn regulated by glucose concentration in the medium.

The GAL switch in K. lactis contains two regulatory genes (LAC9 or KlGAL4 and KlGAL80), a bifunctional gene (KlGAL1) and four structural genes (LAC12, LAC4, KlGAL7 and KlGAL10). KlGal80p is a repressor for KlGal4p. In the presence of lactose/galactose, the enzyme permease Lac12p transports them into the cytoplasm, which activates the protein KlGal1p. This bifunctional protein, having both inducer and galactokinase activity, interacts with KlGal80p, forms a stable complex, and relieves the inhibition of KlGal80p on KlGal4p. KlGAL4 contains an upstream activator sequence in its own promoter for the binding of KlGal4p, resulting in an autoregulatory circuit that causes a significant increase in KlGal4p concentration in the presence of lactose/galactose; this autoregulation is a feature not present in S. cerevisiae.

In previous contributions, we have built and validated a deterministic model for the wild type and mutant strains (lacking Gal80p, as described above) of S. cerevisiae that includes relations for genes with one binding site for Gal4p (such as GAL3 and MEL1) and genes with two binding sites (such as GAL1 andGAL2). The model also includes interactions for Mig1p, which has two binding sites for SUC2 and one binding site for GAL3 and GAL1. The GAL genes are regulated by Gal4p and also through Mig1p. We have also constructed a stochastic model for the mutant strain that lacks Gal80p, and validated it through experiments at the phenotypic level of cell growth. The stochastic analysis provides insight into the effects of the number of binding sites and types of mechanisms on the variability, and ultimately on the hierarchy in the uptake of sugars.

In this contribution, we compare the effect of stochasticity on mutant and wild type strains of K. lactis and S. cerevisiae through simulations, and show through experiments the effect on the phenotypic level of cell growth. Stochastic simulations are performed using methods described in [2, 3]. Mutant studies help us assess the relative effect of various parts of the mechanism (multiple binding sites, multiple feedback, etc.), and studies across the two organisms the possible evolutionary advantage of the differences in the mechanisms. Stochastic analysis points at a hierarchy based on variability, and the variability itself is governed by the specifics of the mechanism. Experiments confirm that this variability is transmitted through the metabolism to the phenotypic level of growth.

References:

1. M. Rubio-Texeira, ?A comparative analysis of the GAL genetic switch between not-so-distant cousins: Saccharomyces cerevisiae versus Kluyveromyces lactis', FEMS Yeast Res., 5, 1115-1128 (2005).

2. D.T. Gillespie, ?Exact stochastic simulation of coupled chemical reactions', J. Phys. Chem., 81(25), 2340-2361 (1977).

3. A. Chatterjee, K. Mayawala, J. S. Edwards, and D. G. Vlachos, ?Time accelerated Monte Carlo simulations of biological networks using the binomial t-leap method', Bioinformatics, 21(9), 2136-2137 (2005).