
Research article

Analysing GCN4 translational control in yeast by stochastic chemical kinetics modelling and simulation

Tao You14, Ian Stansfield2, M Carmen Romano12, Alistair JP Brown2 and George M Coghill13*

Author Affiliations

1 School of Natural and Computing Sciences, University of Aberdeen, Institute of Complex System and Mathematical Biology, Aberdeen, UK

2 School of Medical Sciences, University of Aberdeen, Institute of Medical Sciences, Aberdeen, UK

3 School of Natural and Computing Sciences, University of Aberdeen, Computing Science Department, Aberdeen, UK

4 AstraZeneca, Mereside, Alderley Park, Macclesfield, UK

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BMC Systems Biology 2011, 5:131  doi:10.1186/1752-0509-5-131

Published: 18 August 2011

Abstract

Background

The yeast Saccharomyces cerevisiae responds to amino acid starvation by inducing the transcription factor Gcn4. This is mainly mediated via a translational control mechanism dependent upon the translation initiation eIF2·GTP·Met-tRNAiMet ternary complex, and the four short upstream open reading frames (uORFs) in its 5' mRNA leader. These uORFs act to attenuate GCN4 mRNA translation under normal conditions. During amino acid starvation, levels of ternary complex are reduced. This overcomes the GCN4 translation attenuation effect via a scanning/reinitiation control mechanism dependent upon uORF spacing.

Results

Using published experimental data, we have developed and validated a probabilistic formulation of GCN4 translation using the Chemical Master Equation (Model 1). Model 1 explains GCN4 translation's nonlinear dependency upon uORF placements, and predicts that an as yet unidentified factor, which was proposed to regulate GCN4 translation under some conditions, only has pronounced effects upon GCN4 translation when intercistronic distances are unnaturally short. A simpler Model 2 that does not include this unidentified factor could well represent the regulation of a natural GCN4 mRNA. Using parameter values optimised for this algebraic Model 2, we performed stochastic simulations by Gillespie algorithm to investigate the distribution of ribosomes in different sections of GCN4 mRNA under distinct conditions. Our simulations demonstrated that ribosomal loading in the 5'-untranslated region is mainly determined by the ratio between the rates of 5'-initiation and ribosome scanning, but was not significantly affected by rate of ternary complex binding. Importantly, the translation rate for codons starved of cognate tRNAs is predicted to be the most significant contributor to the changes in ribosomal loading in the coding region under repressing and derepressing conditions.

Conclusions

Our integrated probabilistic Models 1 and 2 explained GCN4 translation and helped to elucidate the role of a yet unidentified factor. The ensuing stochastic simulations evaluated different factors that may impact on the translation of GCN4 mRNA, and integrated translation status with ribosomal density.

Keywords:
mRNA translation; GCN4; Gillespie algorithm; stochastic model
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