Distributed control for recruitment, scanning and subunit joining steps of translation initiation

Inbuilt Tendency of the eIF2 Regulatory System to Counteract Uncertainties

Eukaryotic initiation factor 2 (eIF2) plays a fundamental role in the regulation of protein synthesis. Investigations have revealed that the regulation of eIF2 is robust against intrinsic uncertainties and is able to efficiently counteract them. The robustness properties of the eIF2 pathway against intrinsic disturbances is also well known. However the reasons for this ability to counteract stresses is less well understood. In this article, the robustness conferring properties of the eIF2 dependent regulatory system is explored with the help of a mathematical model. The novelty of the work presented in this article lies in articulating the possible reason behind the inbuilt robustness of the highly engineered eIF2 system against intrinsic perturbations. Our investigations reveal that the robust nature of the eIF2 pathway may originate from the existence of an attractive natural sliding surface within the system satisfying reaching and sliding conditions that are well established in the domain of control engineering.

Multisite rate control analysis identifies ribosomal scanning as the sole high-capacity/low-flux-control step in mRNA translation

Control of complex intracellular pathways such as protein synthesis is critical to organism survival, but is poorly understood. Translation of a reading frame in eukaryotic mRNA is preceded by a scanning process in which a subset of translation factors helps guide ribosomes to the start codon. Here, we perform comparative analysis of the control status of this scanning step that sits between recruitment of the small ribosomal subunit to the m⁷GpppG‐capped 5′end of mRNA and of the control exerted by downstream phases of polypeptide initiation, elongation and termination. We have utilized a detailed predictive model as guidance for designing quantitative experimental interrogation of control in the yeast translation initiation pathway. We have built a synthetic orthogonal copper‐responsive regulatory promoter (P_CuR3) that is used here together with the tet07 regulatory system in a novel dual‐site in vivo rate control analysis strategy. Combining this two‐site strategy with calibrated mass spectrometry to determine translation factor abundance values, we have tested model‐based predictions of rate control properties of the in vivo system. We conclude from the results that the components of the translation machinery that promote scanning collectively function as a low‐flux‐control system with a capacity to transfer ribosomes into the core process of polypeptide production that exceeds the respective capacities of the steps of polypeptide initiation, elongation and termination. In contrast, the step immediately prior to scanning, that is, ribosome recruitment via the mRNA 5′ cap‐binding complex, is a high‐flux‐control step.

Deciphering the rules by which dynamics of mRNA secondary structure affect translation efficiency in Saccharomyces cerevisiae

Messenger RNA (mRNA) secondary structure decreases the elongation rate, as ribosomes must unwind every structure they encounter during translation. Therefore, the strength of mRNA secondary structure is assumed to be reduced in highly translated mRNAs. However, previous studies in vitro reported a positive correlation between mRNA folding strength and protein abundance. The counterintuitive finding suggests that mRNA secondary structure affects translation efficiency in an undetermined manner. Here, we analyzed the folding behavior of mRNA during translation and its effect on translation efficiency. We simulated translation process based on a novel computational model, taking into account the interactions among ribosomes, codon usage and mRNA secondary structures. We showed that mRNA secondary structure shortens ribosomal distance through the dynamics of folding strength. Notably, when adjacent ribosomes are close, mRNA secondary structures between them disappear, and codon usage determines the elongation rate. More importantly, our results showed that the combined effect of mRNA secondary structure and codon usage in highly translated mRNAs causes a short ribosomal distance in structural regions, which in turn eliminates the structures during translation, leading to a high elongation rate. Together, these findings reveal how the dynamics of mRNA secondary structure coupling with codon usage affect translation efficiency.

An in vivo control map for the eukaryotic mRNA translation machinery

A new quantitative strategy has generated a comprehensive rate control map for protein synthesis in exponentially growing yeast cells. This analysis reveals the modularity of the system as well as highly non-stoichiometric relationships between components.

A ‘genetic titration' method has generated a map of the in vivo rate control properties of components of the protein synthesis machinery in Saccharomyces cerevisiae and has been used to parameterize a new comprehensive model of the translation pathway.

The translation machinery is found to be a highly modular system in functional terms yet the intracellular concentrations of its components range from a few thousand to one million molecules per cell.

This approach identifies non-intuitive features of the system such as the strongest rate control being exercised by high abundance elongation factors.

The rate control analysis allows us to identify a surprising fine-control function for duplicated translation factor genes.

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 tRNA_i 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.

Mathematical and Computational Modelling of Ribosomal Movement and Protein Synthesis: an overview

Translation or protein synthesis consists of a complex system of chemical reactions, which ultimately result in decoding of the mRNA and the production of a protein. The complexity of this reaction system makes it difficult to quantitatively connect its input parameters (such as translation factor or ribosome concentrations, codon composition of the mRNA, or energy availability) to output parameters (such as protein synthesis rates or ribosome densities on mRNAs). Mathematical and computational models of translation have now been used for nearly five decades to investigate translation, and to shed light on the relationship between the different reactions in the system. This review gives an overview over the principal approaches used in the modelling efforts, and summarises some of the major findings that were made.

A quantitative model for mRNA translation in Saccharomyces cerevisiae

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.

Yeast 18 S rRNA is directly involved in the ribosomal response to stringent AUG selection during translation initiation

In eukaryotes, the 40 S ribosomal subunit serves as the platform of initiation factor assembly, to place itself precisely on the AUG start codon. Structural arrangement of the 18 S rRNA determines the overall shape of the 40 S subunit. Here, we present genetic evaluation of yeast 18 S rRNA function using 10 point mutations altering the polysome profile. All the mutants reduce the abundance of the mutant 40 S, making it limiting for translation initiation. Two of the isolated mutations, G875A, altering the core of the platform domain that binds eIF1 and eIF2, and A1193U, changing the h31 loop located below the P-site tRNA(i)(Met), show phenotypes indicating defective regulation of AUG selection. Evidence is provided that these mutations reduce the interaction with the components of the preinitiation complex, thereby inhibiting its function at different steps. These results indicate that the 18 S rRNA mutations impair the integrity of scanning-competent preinitiation complex, thereby altering the 40 S subunit response to stringent AUG selection. Interestingly, nine of the mutations alter the body/platform domains of 18 S rRNA, potentially affecting the bridges to the 60 S subunit, but they do not change the level of 18 S rRNA intermediates. Based on these results, we also discuss the mechanism of the selective degradation of the mutant 40 S subunits.

Translation initiation factors are not required for Dicistroviridae IRES function in vivo

The cricket paralysis virus (CrPV) intergenic region (IGR) internal ribosome entry site (IRES) uses an unusual mechanism of initiating translation, whereby the IRES occupies the P-site of the ribosome and the initiating tRNA enters the A-site. In vitro experiments have demonstrated that the CrPV IGR IRES is able to bind purified ribosomes and form 80S complexes capable of synthesizing small peptides in the absence of any translation initiation factors. These results suggest that initiation by this IRES is factor-independent. To determine whether the IGR IRES functions in the absence of initiation factors in vivo, we assayed IGR IRES activity in various yeast strains harboring mutations in canonical translation initiation factors. We used a dicistronic reporter assay in yeast to determine whether the CrPV IGR IRES is able to promote translation sufficient to support growth in the presence of various deletions or mutations in translation initiation factors. Using this assay, we have previously shown that the CrPV IGR IRES functions efficiently in yeast when ternary complexes (eIF2*GTP*initiator tRNA(met)) are reduced. Here, we demonstrate that the CrPV IGR IRES activity does not require the eukaryotic initiation factors eIF4G1 or eIF5B, and it is enhanced when eIF2B, the eIF3b subunit of eIF3, or eIF4E are impaired. Taken together, these data support a model in which the CrPV IGR IRES is capable of initiating protein synthesis in the absence of any initiation factors in vivo, and suggests that the CrPV IGR IRES initiates translation by directly recruiting the ribosomal subunits in vivo.

Control of translation initiation: a model-based analysis from limited experimental data

We have built a detailed kinetic model of translation initiation in yeast and have used a novel approach to determine the flux controlling steps based on limited experimental data. An efficient parameter estimation method was adapted in order to fit the most uncertain parameters (rate constants) to in vivo measurements in yeast. However, it was found that there were many other sets of plausible parameter values that also gave a good fit of the model to the data. We therefore used random sampling of this uncertain parameter space to generate a large number of diverse fitted parameter sets. A compact characterization of these parameter sets was provided by considering flux control. In particular, we suggest that the rate of translation initiation is most strongly influenced by one of two reactions: either the guanine nucleotide exchange reaction involving initiation factors eIF2 and eIF2B or the assembly of the multifactor complex from its constituent protein/tRNA containing complexes. It is hoped that the approach presented in this paper will add to our understanding of translation initiation pathway and can be used to identify key system-level properties of other biochemical processes.

A quantitative estimation of the global translational activity in logarithmically growing yeast cells

Background

Translation of messenger mRNAs makes significant contributions to the control of gene expression in all eukaryotes. Because translational control often involves fractional changes in translational activity, good quantitative descriptions of translational activity will be required to achieve a comprehensive understanding of this aspect of biology. Data on translational activity are difficult to generate experimentally under physiological conditions, however, translational activity as a parameter is in principle accessible through published genome-wide datasets.

Results

An examination of the accuracy of genome-wide expression datasets generated for Saccharomyces cerevisiae shows that the available datasets suffer from large random errors within studies as well as systematic shifts in reported values between studies, which make predictions of translational activity at the level of individual genes relatively inaccurate. In contrast, predictions of cell-wide translational activity are possible from such datasets with higher accuracy, and current datasets predict a production rate of about 13,000 proteins per haploid cell per second under fast growth conditions. This prediction is shown to be consistent with independently derived kinetic information on nucleotide exchange reactions that occur during translation, and on the ribosomal content of yeast cells.

Conclusion

This study highlights some of the limitations in published genome-wide expression datasets, but also demonstrates a novel use for such datasets in examining global properties of cells. The global translational activity of yeast cells predicted in this study is a useful benchmark against which biochemical data on individual translation factor activities can be interpreted.