Ribosome recycling induces optimal translation rate at low ribosomal availability

Single-molecule visualization of mRNA circularization during translation

Translation is mediated by precisely orchestrated sequential interactions among translation initiation components, mRNA, and ribosomes. Biochemical, structural, and genetic techniques have revealed the fundamental mechanism that determines what occurs and when, where and in what order. Most mRNAs are circularized via the eIF4E-eIF4G-PABP interaction, which stabilizes mRNAs and enhances translation by recycling ribosomes. However, studies using single-molecule fluorescence imaging have allowed for the visualization of complex data that opposes the traditional "functional circularization" theory. Here, we briefly introduce single-molecule techniques applied to studies on mRNA circularization and describe the results of in vitro and live-cell imaging. Finally, we discuss relevant insights and questions gained from single-molecule research related to translation.

Single polysome analysis of mRNP

Eukaryotic translation is a complex process that involves the interplay of various translation factors to convert genetic information into a specific amino acid chain. According to an elegant model of eukaryotic translation initiation, the 3' poly(A) tail of an mRNA, which is occupied by poly(A)-binding proteins (PABPs), communicates with the 5'-cap bound by eIF4E to enhance translation. Although the circularization of mRNA resulting from the communication is widely understood, it has yet to be directly observed. To explore mRNA circularization in translation, we analyzed the level of colocalization of eIF4E, eIF4G, and PABP on individual mRNAs in polysomal and subpolysomal fractions using single polysome analysis. Our results show that the three tested proteins barely coexist in mRNA in either polysomal or subpolysomal fractions, implying that the closed-loop structure generated by the communication between eIF4E, eIF4G, and PAPB may be transient during translation.

Modeling transport of extended interacting objects with drop-off phenomenon

We study a deterministic framework for important cellular transport phenomena involving a large number of interacting molecules called the excluded flow of extended interacting objects with drop-off effect (EFEIOD). This model incorporates many realistic features of biological transport process including the length of biological “particles” and the fact that they can detach along the biological ‘tracks’. The flow between the consecutive sites is unidirectional and is described by a “soft” simple exclusion principle and by repelling or attracting forces between neighboring particles. We show that the model admits a unique steady-state. Furthermore, if the parameters are periodic with common period T, then the steady-state profile converge to a unique periodic solution of period T. Simulations of the EFEIOD demonstrate several non-trivial effects of the interactions on the system steady-state profile. For example, detachment rates may help in increasing the steady-state flow by alleviating traffic jams that can exist due to several reasons like bottleneck rate or interactive forces between the particles. We also analyze the special case of our model, when there are no forces exerted by neighboring particles, and called it as the ribosome flow model of extended objects with drop-off effect (RFMEOD), and study the sensitivity of its steady-state to variations in the parameters.

Eukaryotic initiation factor 4F promotes a reorientation of eukaryotic initiation factor 3 binding on the 5' and the 3' UTRs of barley yellow dwarf virus mRNA

Viral mRNAs that lack a 5′ m⁷GTP cap and a 3′ poly-A tail rely on structural elements in their untranslated regions (UTRs) to form unique RNA-protein complexes that regulate viral translation. Recent studies of the barley yellow dwarf virus (BYDV) have revealed eukaryotic initiation factor 3 (eIF3) plays a significant role in facilitating communication between its 5′ and 3′ UTRs by binding both UTRs simultaneously. This report uses in vitro translation assays, fluorescence anisotropy binding assays, and selective 2′-hydroxyl acylation analyzed by primer extension (SHAPE) footprinting to identify secondary structures that are selectively interacting with eIF3. SHAPE data also show that eIF3 alters its interaction with BYDV structures when another factor crucial for BYDV translation, eIF4F, is introduced by the 3′ BYDV translational enhancer (BTE). The observed BTE and eIF4F-induced shift of eIF3 position on the 5’ UTR and the translational effects of altering eIF3-binding structures (SLC and SLII) support a new model for BYDV translation initiation that requires the reorientation of eIF3 on BYDV UTRs. This eIF3 function in BYDV translation initiation is both reminiscent of and distinct from eIF3–RNA interactions found in other non-canonically translating mRNAs (e.g. HCV). This characterization of a new role in translation initiation expands the known functionality of eIF3 and may be broadly applicable to other non-canonically translating mRNAs.

Codon usage and protein length-dependent feedback from translation elongation regulates translation initiation and elongation speed

Essential cellular functions require efficient production of many large proteins but synthesis of large proteins encounters many obstacles in cells. Translational control is mostly known to be regulated at the initiation step. Whether translation elongation process can feedback to regulate initiation efficiency is unclear. Codon usage bias, a universal feature of all genomes, plays an important role in determining gene expression levels. Here, we discovered that there is a conserved but codon usage-dependent genome-wide negative correlation between protein abundance and CDS length. The codon usage effects on protein expression and ribosome flux on mRNAs are influenced by CDS length; optimal codon usage preferentially promotes production of large proteins. Translation of mRNAs with long CDS and non-optimal codon usage preferentially induces phosphorylation of initiation factor eIF2α, which inhibits translation initiation efficiency. Deletion of the eIF2α kinase CPC-3 (GCN2 homolog) in Neurospora preferentially up-regulates large proteins encoded by non-optimal codons. Surprisingly, CPC-3 also inhibits translation elongation rate in a codon usage and CDS length-dependent manner, resulting in slow elongation rates for long CDS mRNAs. Together, these results revealed a codon usage and CDS length-dependent feedback mechanism from translation elongation to regulate both translation initiation and elongation kinetics.

Dynamics of ribosomes in mRNA translation under steady- and nonsteady-state conditions

Recent advances in DNA sequencing and fluorescence imaging have made it possible to monitor the dynamics of ribosomes actively engaged in messenger RNA (mRNA) translation. Here, we model these experiments within the inhomogeneous totally asymmetric simple exclusion process (TASEP) using realistic kinetic parameters. In particular, we present analytic expressions to describe the following three cases: (a) translation of a newly transcribed mRNA, (b) translation in the steady state and, specifically, the dynamics of individual (tagged) ribosomes, and (c) runoff translation after inhibition of translation initiation. In cases (b) and (c) we develop an effective medium approximation to describe many-ribosome dynamics in terms of a single tagged ribosome in an effective medium. The predictions are in good agreement with stochastic simulations.

Whole cell biophysical modeling of codon-tRNA competition reveals novel insights related to translation dynamics

The importance of mRNA translation models has been demonstrated across many fields of science and biotechnology. However, a whole cell model with codon resolution and biophysical dynamics is still lacking. We describe a whole cell model of translation for E. coli. The model simulates all major translation components in the cell: ribosomes, mRNAs and tRNAs. It also includes, for the first time, fundamental aspects of translation, such as competition for ribosomes and tRNAs at a codon resolution while considering tRNAs wobble interactions and tRNA recycling. The model uses parameters that are tightly inferred from large scale measurements of translation. Furthermore, we demonstrate a robust modelling approach which relies on state-of-the-art practices of translation modelling and also provides a framework for easy generalizations. This novel approach allows simulation of thousands of mRNAs that undergo translation in the same cell with common resources such as ribosomes and tRNAs in feasible time. Based on this model, we demonstrate, for the first time, the direct importance of competition for resources on translation and its accurate modelling. An effective supply-demand ratio (ESDR) measure, which is related to translation factors such as tRNAs, has been devised and utilized to show superior predictive power in complex scenarios of heterologous gene expression. The devised model is not only more accurate than the existing models, but, more importantly, provides a framework for analyzing complex whole cell translation problems and variables that haven't been explored before, making it important in various biomedical fields.

mRNA translation is a fundamental process in all living organisms and the importance of its modeling has been demonstrated across many fields of science and biotechnology. Specifically, modeling a whole cell context with a high resolution has been a great challenge in the field, making many important problems un-addressable. In this study we devised a novel model, which allows, for the first time, simultaneous simulation of thousands of mRNAs, along with various bio-physical aspects that affect translation (such as codon-resolution dynamics and shared resources pool of both ribosomes and tRNAs). We demonstrated (using experimental data) that this model is more accurate than existing ones, and, more importantly, provides a framework for addressing complex translation problems (such as heterologous expression) at whole cell scale and in reasonable time. We demonstrated the model using E. coli data, but the model can be easily tailored to other organisms as well. Our model addresses an urgent unmet need for biophysically accurate whole cell translation model with resources coupling and has potential applications in many fields, including medicine and biotechnology.

Functional Cyclization of Eukaryotic mRNAs

The closed-loop model of eukaryotic translation states that mRNA is circularized by a chain of the cap-eIF4E-eIF4G-poly(A)-binding protein (PABP)-poly(A) interactions that brings 5' and 3' ends together. This circularization is thought to promote the engagement of terminating ribosomes to a new round of translation at the same mRNA molecule, thus enhancing protein synthesis. Despite the general acceptance and the elegance of the hypothesis, it has never been proved experimentally. Using continuous in situ monitoring of luciferase synthesis in a mammalian in vitro system, we show here that the rate of translation initiation at capped and polyadenylated reporter mRNAs increases after the time required for the first ribosomes to complete mRNA translation. Such acceleration strictly requires the presence of a poly(A)-tail and is abrogated by the addition of poly(A) RNA fragments or m⁷GpppG cap analog to the translation reaction. The optimal functional interaction of mRNA termini requires 5' untranslated region (UTR) and 3' UTR of moderate lengths and provides stronger acceleration, thus a longer poly(A)-tail. Besides, we revealed that the inhibitory effect of the dominant negative R362Q mutant of initiation factor eIF4A diminishes in the course of translation reaction, suggesting a relaxed requirement for ATP. Taken together, our results imply that, upon the functional looping of an mRNA, the recycled ribosomes can be recruited to the start codon of the same mRNA molecule in an eIF4A-independent fashion. This non-canonical closed-loop assisted reinitiation (CLAR) mode provides efficient translation of the functionally circularized mRNAs.

Translational control of gene expression via interacting feedback loops

Translation is a key step in the synthesis of proteins. Accordingly, cells have evolved an intricate array of control mechanisms to regulate this process. By constructing a multicomponent mathematical framework we uncover how translation may be controlled via interacting feedback loops. Our results reveal that this interplay gives rise to a remarkable range of protein synthesis dynamics, including oscillations, step change, and bistability. This suggests that cells may have recourse to a much richer set of control mechanisms than was previously understood.

Power series method for solving TASEP-based models of mRNA translation

We develop a method for solving mathematical models of messenger RNA (mRNA) translation based on the totally asymmetric simple exclusion process (TASEP). Our main goal is to demonstrate that the method is versatile and applicable to realistic models of translation. To this end we consider the TASEP with codon-dependent elongation rates, premature termination due to ribosome drop-off and translation reinitiation due to circularisation of the mRNA. We apply the method to the model organism Saccharomyces cerevisiae under physiological conditions and find an excellent agreement with the results of stochastic simulations. Our findings suggest that the common view on translation as being rate-limited by initiation is oversimplistic. Instead we find theoretical evidence for ribosome interference and also theoretical support for the ramp hypothesis which argues that codons at the beginning of genes have slower elongation rates in order to reduce ribosome density and jamming.

The ribosome, (slow) beating heart of cancer (stem) cell

The ribosome has long been considered as a consistent molecular factory, with a rather passive role in the translation process. Recent findings have shifted this obsolete view, revealing a remarkably complex and multifaceted machinery whose role is to orchestrate spatiotemporal control of gene expression. Ribosome specialization discovery has raised the interesting possibility of the existence of its malignant counterpart, an 'oncogenic' ribosome, which may promote tumor progression. Here we weigh the arguments supporting the existence of an 'oncogenic' ribosome and evaluate its role in cancer evolution. In particular, we provide an analysis and perspective on how the ribosome may play a critical role in the acquisition and maintenance of cancer stem cell phenotype.

Ribosomopathies: There's strength in numbers

Ribosomopathies are a group of human disorders most commonly caused by ribosomal protein haploinsufficiency or defects in ribosome biogenesis. These conditions manifest themselves as physiological defects in specific cell and tissue types. We review current molecular models to explain ribosomopathies and attempt to reconcile the tissue specificity of these disorders with the ubiquitous requirement for ribosomes in all cells. Ribosomopathies as a group are diverse in their origins and clinical manifestations; we use the well-described Diamond-Blackfan anemia (DBA) as a specific example to highlight some common features. We discuss ribosome homeostasis as an overarching principle that governs the sensitivity of specific cells and tissue types to ribosomal protein mutations. Mathematical models and experimental insights rationalize how even subtle shifts in the availability of ribosomes, such as those created by ribosome haploinsufficiency, can drive messenger RNA-specific effects on protein expression. We discuss recently identified roles played by ribosome rescue and recycling factors in regulating ribosome homeostasis.

Gene length as a regulator for ribosome recruitment and protein synthesis: theoretical insights

Protein synthesis rates are determined, at the translational level, by properties of the transcript’s sequence. The efficiency of an mRNA can be tuned by varying the ribosome binding sites controlling the recruitment of the ribosomes, or the codon usage establishing the speed of protein elongation. In this work we propose transcript length as a further key determinant of translation efficiency. Based on a physical model that considers the kinetics of ribosomes advancing on the mRNA and diffusing in its surrounding, as well as mRNA circularisation and ribosome drop-off, we explain how the transcript length may play a central role in establishing ribosome recruitment and the overall translation rate of an mRNA. According to our results, the proximity of the 3′ end to the ribosomal recruitment site of the mRNA could induce a feedback in the translation process that would favour the recycling of ribosomes. We also demonstrate how this process may be involved in shaping the experimental ribosome density-gene length dependence. Finally, we argue that cells could exploit this mechanism to adjust and balance the usage of its ribosomal resources.

Optimal Translation Along a Circular mRNA

The ribosome flow model on a ring (RFMR) is a deterministic model for ribosome flow along a circularized mRNA. We derive a new spectral representation for the optimal steady-state production rate and the corresponding optimal steady-state ribosomal density in the RFMR. This representation has several important advantages. First, it provides a simple and numerically stable algorithm for determining the optimal values even in very long rings. Second, it enables efficient computation of the sensitivity of the optimal production rate to small changes in the transition rates along the mRNA. Third, it implies that the optimal steady-state production rate is a strictly concave function of the transition rates. Maximizing the optimal steady-state production rate with respect to the rates under an affine constraint on the rates thus becomes a convex optimization problem that admits a unique solution. This solution can be determined numerically using highly efficient algorithms. This optimization problem is important, for example, when re-engineering heterologous genes in a host organism. We describe the implications of our results to this and other aspects of translation.

Ribosome reinitiation can explain length-dependent translation of messenger RNA

Models of mRNA translation usually presume that transcripts are linear; upon reaching the end of a transcript each terminating ribosome returns to the cytoplasmic pool before initiating anew on a different transcript. A consequence of linear models is that faster translation of a given mRNA is unlikely to generate more of the encoded protein, particularly at low ribosome availability. Recent evidence indicates that eukaryotic mRNAs are circularized, potentially allowing terminating ribosomes to preferentially reinitiate on the same transcript. Here we model the effect of ribosome reinitiation on translation and show that, at high levels of reinitiation, protein synthesis rates are dominated by the time required to translate a given transcript. Our model provides a simple mechanistic explanation for many previously enigmatic features of eukaryotic translation, including the negative correlation of both ribosome densities and protein abundance on transcript length, the importance of codon usage in determining protein synthesis rates, and the negative correlation between transcript length and both codon adaptation and 5' mRNA folding energies. In contrast to linear models where translation is largely limited by initiation rates, our model reveals that all three stages of translation-initiation, elongation, and termination/reinitiation-determine protein synthesis rates even at low ribosome availability.

Novel mRNA-specific effects of ribosome drop-off on translation rate and polysome profile

The well established phenomenon of ribosome drop-off plays crucial roles in translational accuracy and nutrient starvation responses during protein translation. When cells are under stress conditions, such as amino acid starvation or aminoacyl-tRNA depletion due to a high level of recombinant protein expression, ribosome drop-off can substantially affect the efficiency of protein expression. Here we introduce a mathematical model that describes the effects of ribosome drop-off on the ribosome density along the mRNA and on the concomitant protein synthesis rate. Our results show that ribosome premature termination may lead to non-intuitive ribosome density profiles, such as a ribosome density which increases from the 5' to the 3' end. Importantly, the model predicts that the effects of ribosome drop-off on the translation rate are mRNA-specific, and we quantify their resilience to drop-off, showing that the mRNAs which present ribosome queues are much less affected by ribosome drop-off than those which do not. Moreover, among those mRNAs that do not present ribosome queues, resilience to drop-off correlates positively with the elongation rate, so that sequences using fast codons are expected to be less affected by ribosome drop-off. This result is consistent with a genome-wide analysis of S. cerevisiae, which reveals that under favourable growth conditions mRNAs coding for proteins involved in the translation machinery, known to be highly codon biased and using preferentially fast codons, are highly resilient to ribosome drop-off. Moreover, in physiological conditions, the translation rate of mRNAs coding for regulatory, stress-related proteins, is less resilient to ribosome drop-off. This model therefore allows analysis of variations in the translational efficiency of individual mRNAs by accounting for the full range of known ribosome behaviours, as well as explaining mRNA-specific variations in ribosome density emerging from ribosome profiling studies.

On the Ribosomal Density that Maximizes Protein Translation Rate

During mRNA translation, several ribosomes attach to the same mRNA molecule simultaneously translating it into a protein. This pipelining increases the protein translation rate. A natural and important question is what ribosomal density maximizes the protein translation rate. Using mathematical models of ribosome flow along both a linear and a circular mRNA molecules we prove that typically the steady-state protein translation rate is maximized when the ribosomal density is one half of the maximal possible density. We discuss the implications of our results to endogenous genes under natural cellular conditions and also to synthetic biology.

Predictive biophysical modeling and understanding of the dynamics of mRNA translation and its evolution

mRNA translation is the fundamental process of decoding the information encoded in mRNA molecules by the ribosome for the synthesis of proteins. The centrality of this process in various biomedical disciplines such as cell biology, evolution and biotechnology, encouraged the development of dozens of mathematical and computational models of translation in recent years. These models aimed at capturing various biophysical aspects of the process. The objective of this review is to survey these models, focusing on those based and/or validated on real large-scale genomic data. We consider aspects such as the complexity of the models, the biophysical aspects they regard and the predictions they may provide. Furthermore, we survey the central systems biology discoveries reported on their basis. This review demonstrates the fundamental advantages of employing computational biophysical translation models in general, and discusses the relative advantages of the different approaches and the challenges in the field.

Probabilistic Boolean Network Modelling and Analysis Framework for mRNA Translation

mRNA translation is a complex process involving the progression of ribosomes on the mRNA, resulting in the synthesis of proteins, and is subject to multiple layers of regulation. This process has been modelled using different formalisms, both stochastic and deterministic. Recently, we introduced a Probabilistic Boolean modelling framework for mRNA translation, which possesses the advantage of tools for numerically exact computation of steady state probability distribution, without requiring simulation. Here, we extend this model to incorporate both random sequential and parallel update rules, and demonstrate its effectiveness in various settings, including its flexibility in accommodating additional static and dynamic biological complexities and its role in parameter sensitivity analysis. In these applications, the results from the model analysis match those of TASEP model simulations. Importantly, the proposed modelling framework maintains the stochastic aspects of mRNA translation and provides a way to exactly calculate probability distributions, providing additional tools of analysis in this context. Finally, the proposed modelling methodology provides an alternative approach to the understanding of the mRNA translation process, by bridging the gap between existing approaches, providing new analysis tools, and contributing to a more robust platform for modelling and understanding translation.

ABCE1 is essential for S phase progression in human cells

ABCE1 is a highly conserved protein universally present in eukaryotes and archaea, which is crucial for the viability of different organisms. First identified as RNase L inhibitor, ABCE1 is currently recognized as an essential translation factor involved in several stages of eukaryotic translation and ribosome biogenesis. The nature of vital functions of ABCE1, however, remains unexplained. Here, we study the role of ABCE1 in human cell proliferation and its possible connection to translation. We show that ABCE1 depletion by siRNA results in a decreased rate of cell growth due to accumulation of cells in S phase, which is accompanied by inefficient DNA synthesis and reduced histone mRNA and protein levels. We infer that in addition to the role in general translation, ABCE1 is involved in histone biosynthesis and DNA replication and therefore is essential for normal S phase progression. In addition, we analyze whether ABCE1 is implicated in transcript-specific translation via its association with the eIF3 complex subunits known to control the synthesis of cell proliferation-related proteins. The expression levels of a few such targets regulated by eIF3A, however, were not consistently affected by ABCE1 depletion.

Community control in cellular protein production: consequences for amino acid starvation

Deprivation of essential nutrients can have stark consequences for many processes in a cell. We consider amino acid starvation, which can result in bottlenecks in mRNA translation when ribosomes stall due to lack of resources, i.e. tRNAs charged with the missing amino acid. Recent experiments also show less obvious effects such as increased charging of other (non-starved) tRNA species and selective charging of isoaccepting tRNAs. We present a mechanism which accounts for these observations and shows that production of some proteins can actually increase under starvation. One might assume that such responses could only be a result of sophisticated control pathways, but here we show that these effects can occur naturally due to changes in the supply and demand for different resources, and that control can be accomplished through selective use of rare codons. We develop a model for translation which includes the dynamics of the charging and use of aminoacylated tRNAs, explicitly taking into account the effect of specific codon sequences. This constitutes a new control mechanism in gene regulation which emerges at the community level, i.e. via resources used by all ribosomes.

Optimization of translation profiles enhances protein expression and solubility

mRNA is translated with a non-uniform speed that actively coordinates co-translational folding of protein domains. Using structure-based homology we identified the structural domains in epoxide hydrolases (EHs) and introduced slow-translating codons to delineate the translation of single domains. These changes in translation speed dramatically improved the solubility of two EHs of metagenomic origin in Escherichia coli. Conversely, the importance of transient attenuation for the folding, and consequently solubility, of EH was evidenced with a member of the EH family from Agrobacterium radiobacter, which partitions in the soluble fraction when expressed in E. coli. Synonymous substitutions of codons shaping the slow-transiting regions to fast-translating codons render this protein insoluble. Furthermore, we show that low protein yield can be enhanced by decreasing the free folding energy of the initial 5’-coding region, which can disrupt mRNA secondary structure and enhance ribosomal loading. This study provides direct experimental evidence that mRNA is not a mere messenger for translation of codons into amino acids but bears an additional layer of information for folding, solubility and expression level of the encoded protein. Furthermore, it provides a general frame on how to modulate and fine-tune gene expression of a target protein.

Quantitative studies of mRNA recruitment to the eukaryotic ribosome

The process of peptide bond synthesis by ribosomes is conserved between species, but the initiation step differs greatly between the three kingdoms of life. This is illustrated by the evolution of roughly an order of magnitude more initiation factor mass found in humans compared with bacteria. Eukaryotic initiation of translation is comprised of a number of sub-steps: (i) recruitment of an mRNA and initiator methionyl-tRNA to the 40S ribosomal subunit; (ii) migration of the 40S subunit along the 5' UTR to locate the initiation codon; and (iii) recruitment of the 60S subunit to form the 80S initiation complex. Although the mechanism and regulation of initiation has been studied for decades, many aspects of the pathway remain unclear. In this review, I will focus discussion on what is known about the mechanism of mRNA selection and its recruitment to the 40S subunit. I will summarize how the 43S preinitiation complex (PIC) is formed and stabilized by interactions between its components. I will discuss what is known about the mechanism of mRNA selection by the eukaryotic initiation factor 4F (eIF4F) complex and how the selected mRNA is recruited to the 43S PIC. The regulation of this process by secondary structure located in the 5' UTR of an mRNA will also be discussed. Finally, I present a possible kinetic model with which to explain the process of mRNA selection and recruitment to the eukaryotic ribosome.