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Title: Modelling and simulation of amino acid starvation responses in yeast Saccharomyces cerevisiae
Author: You, Tao
ISNI:       0000 0004 2668 3567
Awarding Body: University of Aberdeen
Current Institution: University of Aberdeen
Date of Award: 2009
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Saccharomyces cerevisiae is able to sense and respond to amino acid availability in the environment by reprogramming its gene expression.  Upon starvation for any amino acid, the yeast cell induces the biosynthesis of nearly all amino acids by upregulating the master transcription factor Gcn4, which is primarily controlled at the translational level.  Amino acid consumption is decreased by reducing general mRNA translation activity via GCN2.  The molecular mechanisms that mediate this response are known as the General Control Nonderepressible (GCN) response.  The aim of this thesis was to quantitatively understand the GCN response in S. cerevisiae by constructing a series of mathematical models, both deterministic and stochastic, based on published experimental results. Firstly, a deterministic model of general mRNA translation is described, which elaborates the translation initiation apparatus.  This model was used to predict the effects upon general translation activity of changing the abundance of specific initiation factors in isolation and collectively.  This model was also used to study the robustness of general mRNA translation and the trade-off between robustness and performance of this system. Secondly, a series of probabilistic and stochastic models of GCN4 mRNA translation based on Gillespie algorithm are described.  These probabilistic models successfully explained published results regarding the changes in GCN4 mRNA translation resulting from variation in uORF intercistronic distances.  The subsequent stochastic simulations suggested that histidine codon translation rates contribute significantly to the observed changes in ribosomal loading that occur on the GCN4 mRNA. Finally, a comprehensive deterministic model is described for the entire GCN system, integrating the above models.  This comprehensive model was able to predict the GCN responses to both natural and artificial amino acid starvation.  It successfully reproduced the phenotypes of some GCN2 and GCN4 mutants, and was also used to examine the fragility of GCN system when faced with severe artificial histidine starvation.  These predictions await experimental verification.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Saccharomyces cerevisiae ; Yeast fungi ; Biological systems ; Systems Biology