Dataset Information

You2010_General_Yeast_mRNA_Translation

ABSTRACT: This the model from the article: A quantitative model for mRNA translation in Saccharomyces cerevisiae. You T, Coghill GM, Brown AJ. Yeast. 2010 Mar 19. epub ahead of print, PMID: 20306461 , doi: 10.1002/yea.1770 Abstract: Messenger RNA (mRNA) translation is an essential step in eukaryotic gene expression that contributes to the regulation of this process. We describe a deterministic model based on ordinary differential equations that describe mRNA translation in Saccharomyces cerevisiae. This model, which was parameterized using published data, was developed to examine the kinetic behaviour of translation initiation factors in response to amino acid availability. The model predicts that the abundance of the eIF1-eIF3-eIF5 complex increases under amino acid starvation conditions, suggesting a possible auxiliary role for these factors in modulating translation initiation in addition to the known mechanisms involving eIF2. Our analyses of the robustness of the mRNA translation model suggest that individual cells within a randomly generated population are sensitive to external perturbations (such as changes in amino acid availability) through Gcn2 signalling. However, the model predicts that individual cells exhibit robustness against internal perturbations (such as changes in the abundance of translation initiation factors and kinetic parameters). Gcn2 appears to enhance this robustness within the system. These findings suggest a trade-off between the robustness and performance of this biological network. The model also predicts that individual cells exhibit considerable heterogeneity with respect to their absolute translation rates, due to random internal perturbations. Therefore, averaging the kinetic behaviour of cell populations probably obscures the dynamic robustness of individual cells. This highlights the importance of single-cell measurements for evaluating network properties. Copyright (c) 2010 John Wiley and Sons, Ltd. This model originates from BioModels Database: A Database of Annotated Published Models. It is copyright (c) 2005-2011 The BioModels.net Team. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information. In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not.. To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.

SUBMITTER: Tao You

PROVIDER: MODEL8459127548 | BioModels | 2005-01-01

REPOSITORIES: BioModels

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Publications

A quantitative model for mRNA translation in Saccharomyces cerevisiae.

You Tao T Coghill George M GM Brown Alistair J P AJ

Yeast (Chichester, England) 20101001 10

Messenger RNA (mRNA) translation is an essential step in eukaryotic gene expression that contributes to the regulation of this process. We describe a deterministic model based on ordinary differential equations that describe mRNA translation in Saccharomyces cerevisiae. This model, which was parameterized using published data, was developed to examine the kinetic behaviour of translation initiation factors in response to amino acid availability. The model predicts that the abundance of the eIF1- ...[more]

PMID: 20306461

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Project description:Firczuk2013 - Eukaryotic mRNA translation machinery This is a model of Saccharomyces cerevisiae mRNA translation which includes the initiation, elongation and termination phases. The model is for 20 condon mRNAs. The building of a multi-factor complex in initiation and also the different processes in elongation and termination are modelled in detail. The model takes into account that ribosomes cover more than one codon of mRNA so that the movement of ribosomes are effectively blocked by other ribosomes several codons downstream. It is assumed that 15 codons are occupied by each ribosome. This blocking effect is considered in reaction R18 in initiation and also reaction R26, the reaction where translocation of ribosomes takes place in elongation. The kinetic functions of these two reactions are based on MacDonald et al. 1968 and Heinrich & Rapaport 1980. All other kinetic functions follow mass-action kinetics. The concentrations of transfer RNA species (Met-tRNA, aa-tRNA and tRNA in the model) are kept constant, while the other species' concentrations can change in the course of the simulation. The model describes the translation of a short mRNA with 20 codons. Therefore, all reactions in the elongation cycle (R22, R23, R25, R26, R28 and R29) and the corresponding species are replicated accordingly to model the species with ribosomes bound at different positions. In summary, the model contains 165 different species and 141 reactions. The value of the 56 rate constant parameters were estimated by fitting the model against a series of experimental data consisting of modulation of the various translation factors (Figures 2, 3 and S3). Overall the parameter estimation was carried out over 212 different data points (steady states). This model is described in the article: An in vivo control map for the eukaryotic mRNA translation machinery Helena Firczuk, Shichina Kannambath, Jürgen Pahle, Amy Claydon, Robert Beynon, John Duncan, Hans Westerhoff, Pedro Mendes and John EG McCarthy Molecular Systems Biology. 9:635 Abstract: Rate control analysis defines the in vivo control map governing yeast protein synthesis and generates an extensively parameterized digital model of the translation pathway. Among other non-intuitive outcomes, translation demonstrates a high degree of functional modularity and comprises a non-stoichiometric combination of proteins manifesting functional convergence on a shared maximal translation rate. In exponentially growing cells, polypeptide elongation (eEF1A, eEF2, and eEF3) exerts the strongest control. The two other strong control points are recruitment of mRNA and tRNAi to the 40S ribosomal subunit (eIF4F and eIF2) and termination (eRF1; Dbp5). In contrast, factors that are found to promote mRNA scanning efficiency on a longer than-average 5′untranslated region (eIF1, eIF1A, Ded1, eIF2B, eIF3, and eIF5) exceed the levels required for maximal control. This is expected to allow the cell to minimize scanning transition times, particularly for longer 5′UTRs. The analysis reveals these and other collective adaptations of control shared across the factors, as well as features that reflect functional modularity and system robustness. Remarkably, gene duplication is implicated in the fine control of cellular protein synthesis. This model is hosted on BioModels Database and identified by: BIOMD0000000457 . To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models . To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Dataset Information

You2010_General_Yeast_mRNA_Translation

Publications

A quantitative model for mRNA translation in Saccharomyces cerevisiae.

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