Multi-site 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 (PCuR3) 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

Minimum-noise production of translation factor eIF4G maps to a mechanistically determined optimal rate control window for protein synthesis

Gene expression noise influences organism evolution and fitness. The mechanisms determining the relationship between stochasticity and the functional role of translation machinery components are critical to viability. eIF4G is an essential translation factor that exerts strong control over protein synthesis. We observe an asymmetric, approximately bell-shaped, relationship between the average intracellular abundance of eIF4G and rates of cell population growth and global mRNA translation, with peak rates occurring at normal physiological abundance. This relationship fits a computational model in which eIF4G is at the core of a multi-component– complex assembly pathway. This model also correctly predicts a plateau-like response of translation to super-physiological increases in abundance of the other cap-complex factors, eIF4E and eIF4A. Engineered changes in eIF4G abundance amplify noise, demonstrating that minimum stochasticity coincides with physiological abundance of this factor. Noise is not increased when eIF4E is overproduced. Plasmid-mediated synthesis of eIF4G imposes increased global gene expression stochasticity and reduced viability because the intrinsic noise for this factor influences total cellular gene noise. The naturally evolved eIF4G gene expression noise minimum maps within the optimal activity zone dictated by eIF4G’s mechanistic role. Rate control and noise are therefore interdependent and have co-evolved to share an optimal physiological abundance point

An in vivo control map for the eukaryotic mRNA translation machinery

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

Translational control of gene expression noise and its relationship to ageing in yeast

Gene expression noise influences organism evolution and fitness but is poorly understood. There is increasing evidence that the functional roles of components of the translation machinery influence noise intensity. In addition, modulation of the activities of at least some of these same components affects the replicative lifespan of a broad spectrum of organisms. In a novel comparative approach, we modulate the activities of the translation initiation factors eIFG1 and eIF4G2, both of which are involved in the process of recruiting ribosomal 43S preinitiation complexes to the 5’ end of eukaryotic mRNAs. We show that tagging of the cell wall using a fluorescent dye allows us to follow gene expression noise as different yeast strains progress through successive cycles of replicative ageing. This procedure reveals a relationship between global protein synthesis rate and gene expression noise (cell‐to‐cell heterogeneity), which is accompanied by a parallel correlation between gene expression noise and the replicative age of mother cells. An alternative approach, based on microfluidics, confirms the interdependence between protein synthesis rate, gene expression noise and ageing. We additionally show that it is important to characterize the influence of the design of the microfluidic device on the nutritional state of the cells during such experiments. Analysis of the noise data derived from flow cytometry and fluorescence microscopy measurements indicates that both the intrinsic and the extrinsic noise components increase as a function of ageing