Ribosome collisions and translation efficiency: optimization by codon usage and mRNA destabilization

Comprehensive translational profiling and STE AI uncover rapid control of protein biosynthesis during cell stress

Translational control is important in all life, but it remains a challenge to accurately quantify. When ribosomes translate messenger (m)RNA into proteins, they attach to the mRNA in series, forming poly(ribo)somes, and can co-localize. Here, we computationally model new types of co-localized ribosomal complexes on mRNA and identify them using enhanced translation complex profile sequencing (eTCP-seq) based on rapid in vivo crosslinking. We detect long disome footprints outside regions of non-random elongation stalls and show these are linked to translation initiation and protein biosynthesis rates. We subject footprints of disomes and other translation complexes to artificial intelligence (AI) analysis and construct a new, accurate and self-normalized measure of translation, termed stochastic translation efficiency (STE). We then apply STE to investigate rapid changes to mRNA translation in yeast undergoing glucose depletion. Importantly, we show that, well beyond tagging elongation stalls, footprints of co-localized ribosomes provide rich insight into translational mechanisms, polysome dynamics and topology. STE AI ranks cellular mRNAs by absolute translation rates under given conditions, can assist in identifying its control elements and will facilitate the development of next-generation synthetic biology designs and mRNA-based therapeutics.

Codon-optimization in gene therapy: promises, prospects and challenges

Codon optimization has evolved to enhance protein expression efficiency by exploiting the genetic code's redundancy, allowing for multiple codon options for a single amino acid. Initially observed in E. coli, optimal codon usage correlates with high gene expression, which has propelled applications expanding from basic research to biopharmaceuticals and vaccine development. The method is especially valuable for adjusting immune responses in gene therapies and has the potenial to create tissue-specific therapies. However, challenges persist, such as the risk of unintended effects on protein function and the complexity of evaluating optimization effectiveness. Despite these issues, codon optimization is crucial in advancing gene therapeutics. This study provides a comprehensive review of the current metrics for codon-optimization, and its practical usage in research and clinical applications, in the context of gene therapy.

Genes for highly abundant proteins in Escherichia coli avoid 5' codons that promote ribosomal initiation

In many species highly expressed genes (HEGs) over-employ the synonymous codons that match the more abundant iso-acceptor tRNAs. Bacterial transgene codon randomization experiments report, however, that enrichment with such "translationally optimal" codons has little to no effect on the resultant protein level. By contrast, consistent with the view that ribosomal initiation is rate limiting, synonymous codon usage following the 5' ATG greatly influences protein levels, at least in part by modifying RNA stability. For the design of bacterial transgenes, for simple codon based in silico inference of protein levels and for understanding selection on synonymous mutations, it would be valuable to computationally determine initiation optimality (IO) scores for codons for any given species. One attractive approach is to characterize the 5' codon enrichment of HEGs compared with the most lowly expressed genes, just as translational optimality scores of codons have been similarly defined employing the full gene body. Here we determine the viability of this approach employing a unique opportunity: for Escherichia coli there is both the most extensive protein abundance data for native genes and a unique large-scale transgene codon randomization experiment enabling objective definition of the 5' codons that cause, rather than just correlate with, high protein abundance (that we equate with initiation optimality, broadly defined). Surprisingly, the 5' ends of native genes that specify highly abundant proteins avoid such initiation optimal codons. We find that this is probably owing to conflicting selection pressures particular to native HEGs, including selection favouring low initiation rates, this potentially enabling high efficiency of ribosomal usage and low noise. While the classical HEG enrichment approach does not work, rendering simple prediction of native protein abundance from 5' codon content futile, we report evidence that initiation optimality scores derived from the transgene experiment may hold relevance for in silico transgene design for a broad spectrum of bacteria.

Large-scale analysis of mRNA sequences localized near the start and amber codons and their impact on the diversity of mRNA display libraries

Extremely diverse libraries are essential for effectively selecting functional peptides or proteins, and mRNA display technology is a powerful tool for generating such libraries with over 1012-1013 diversity. Particularly, the protein-puromycin linker (PuL)/mRNA complex formation yield is determining for preparing the libraries. However, how mRNA sequences affect the complex formation yield remains unclear. To study the effects of N-terminal and C-terminal coding sequences on the complex formation yield, puromycin-attached mRNAs containing three random codons after the start codon (32768 sequences) or seven random bases next to the amber codon (6480 sequences) were translated. Enrichment scores were calculated by dividing the appearance rate of every sequence in protein-PuL/mRNA complexes by that in total mRNAs. The wide range of enrichment scores (0.09-2.10 for N-terminal and 0.30-4.23 for C-terminal coding sequences) indicated that the N-terminal and C-terminal coding sequences strongly affected the complex formation yield. Using C-terminal GGC-CGA-UAG-U sequences, which resulted in the highest enrichment scores, we constructed highly diverse libraries of monobodies and macrocyclic peptides. The present study provides insights into how mRNA sequences affect the protein/mRNA complex formation yield and will accelerate the identification of functional peptides and proteins involved in various biological processes and having therapeutic applications.

Modelling genetic stability in engineered cell populations

Predicting the evolution of engineered cell populations is a highly sought-after goal in biotechnology. While models of evolutionary dynamics are far from new, their application to synthetic systems is scarce where the vast combination of genetic parts and regulatory elements creates a unique challenge. To address this gap, we here-in present a framework that allows one to connect the DNA design of varied genetic devices with mutation spread in a growing cell population. Users can specify the functional parts of their system and the degree of mutation heterogeneity to explore, after which our model generates host-aware transition dynamics between different mutation phenotypes over time. We show how our framework can be used to generate insightful hypotheses across broad applications, from how a device's components can be tweaked to optimise long-term protein yield and genetic shelf life, to generating new design paradigms for gene regulatory networks that improve their functionality.

Ultradeep characterisation of translational sequence determinants refutes rare-codon hypothesis and unveils quadruplet base pairing of initiator tRNA and transcript

Translation is a key determinant of gene expression and an important biotechnological engineering target. In bacteria, 5'-untranslated region (5'-UTR) and coding sequence (CDS) are well-known mRNA parts controlling translation and thus cellular protein levels. However, the complex interaction of 5'-UTR and CDS has so far only been studied for few sequences leading to non-generalisable and partly contradictory conclusions. Herein, we systematically assess the dynamic translation from over 1.2 million 5'-UTR-CDS pairs in Escherichia coli to investigate their collective effect using a new method for ultradeep sequence-function mapping. This allows us to disentangle and precisely quantify effects of various sequence determinants of translation. We find that 5'-UTR and CDS individually account for 53% and 20% of variance in translation, respectively, and show conclusively that, contrary to a common hypothesis, tRNA abundance does not explain expression changes between CDSs with different synonymous codons. Moreover, the obtained large-scale data provide clear experimental evidence for a base-pairing interaction between initiator tRNA and mRNA beyond the anticodon-codon interaction, an effect that is often masked for individual sequences and therefore inaccessible to low-throughput approaches. Our study highlights the indispensability of ultradeep sequence-function mapping to accurately determine the contribution of parts and phenomena involved in gene regulation.

Autoinduction Expression Modules for Regulating Gene Expression in Bacillus subtilis

Although quorum sensing (QS) promoters that can autonomously activate gene expression have been identified and engineered in Bacillus subtilis, researchers focus on quantifying individual promoters while ignoring the interaction between other genetic regulatory elements. Here, we constructed the autoinduction expression modules consisting of promoters responsive to QS ComQXPA, ribosome binding sites (RBSs), and terminators. Using superfolder green fluorescent protein (sfGFP) as a reporter gene, three individual element libraries were generated from 945 promoters, 12,000 RBSs, and 425 terminators by random mutation, de novo design, and database mining strategies, respectively. Then, the efficiency of three libraries in regulating gene expression was further enhanced by engineering the core region of each optimal element. After hybridizing the element libraries, the generated expression modules exhibited a 627-fold range in regulating gene expression without significantly affecting the autoinduction initiation. Here, the hybrid modules with broad expression strength may benefit the application of QS-based autoinduction systems in B. subtilis.

Engineered multiple translation initiation sites: a novel tool to enhance protein production in Bacillus licheniformis and other industrially relevant bacteria

Gram-positive bacteria are a nascent platform for synthetic biology and metabolic engineering that can provide new opportunities for the production of biomolecules. However, the lack of standardized methods and genetic parts is a major obstacle towards attaining the acceptance and widespread use of Gram-positive bacterial chassis for industrial bioproduction. In this study, we have engineered a novel mRNA leader sequence containing more than one ribosomal binding site (RBS) which could initiate translation from multiple sites, vastly enhancing the translation efficiency of the Gram-positive industrial strain Bacillus licheniformis. This is the first report elucidating the impact of more than one RBS to initiate translation and enhance protein output in B. licheniformis. We also explored the application of more than one RBS for both intracellular and extracellular protein production in B. licheniformis to demonstrate its efficiency, consistency and potential for biotechnological applications. Moreover, we applied these concepts for use in other industrially relevant Gram-positive bacteria, such as Bacillus subtilis and Corynebacterium glutamicum. In all, a highly efficient and robust broad-host expression element has been designed to strengthen and fine-tune the protein outputs for the use of bioproduction in microbial cell factories.

Analysis of the Contribution of Intrinsic Disorder in Shaping Potyvirus Genetic Diversity

Intrinsically disordered regions (IDRs) are abundant in the proteome of RNA viruses. The multifunctional properties of these regions are widely documented and their structural flexibility is associated with the low constraint in their amino acid positions. Therefore, from an evolutionary stand point, these regions could have a greater propensity to accumulate non-synonymous mutations (NS) than highly structured regions (ORs, or 'ordered regions'). To address this hypothesis, we compared the distribution of non-synonymous mutations (NS), which we relate here to mutational robustness, in IDRs and ORs in the genome of potyviruses, a major genus of plant viruses. For this purpose, a simulation model was built and used to distinguish a possible selection phenomenon in the biological datasets from randomly generated mutations. We analyzed several short-term experimental evolution datasets. An analysis was also performed on the natural diversity of three different species of potyviruses reflecting their long-term evolution. We observed that the mutational robustness of IDRs is significantly higher than that of ORs. Moreover, the substitutions in the ORs are very constrained by the conservation of the physico-chemical properties of the amino acids. This feature is not found in the IDRs where the substitutions tend to be more random. This reflects the weak structural constraints in these regions, wherein an amino acid polymorphism is naturally conserved. In the course of evolution, potyvirus IDRs and ORs follow different evolutive paths with respect to their mutational robustness. These results have forced the authors to consider the hypothesis that IDRs and their associated amino acid polymorphism could constitute a potential adaptive reservoir.

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.

The context of the ribosome binding site in mRNAs defines specificity of action of kasugamycin, an inhibitor of translation initiation

Several antibiotics targeting the large ribosomal subunit interfere with translation in a context-specific manner, preventing ribosomes from polymerizing specific amino acid sequences. Here, we reveal kasugamycin as a small ribosomal subunit-targeting antibiotic whose action depends on the sequence context of the untranslated messenger RNA (mRNA) segments. We show that kasugamycin-induced ribosomal arrest at the start codons of the genes and the resulting inhibition of gene expression depend on the nature of the mRNA nucleotide immediately preceding the start codon and on the proximity of the stop codon of the upstream cistron. Our findings underlie the importance of mRNA context for the action of protein synthesis inhibitors and might help to guide the development of better antibiotics.

Kasugamycin (KSG) is an aminoglycoside antibiotic widely used in agriculture and exhibits considerable medical potential. Previous studies suggested that KSG interferes with translation by blocking binding of canonical messenger RNA (mRNA) and initiator transfer tRNA (tRNA) to the small ribosomal subunit, thereby preventing initiation of protein synthesis. Here, by using genome-wide approaches, we show that KSG can interfere with translation even after the formation of the 70S initiation complex on mRNA, as the extent of KSG-mediated translation inhibition correlates with increased occupancy of start codons by 70S ribosomes. Even at saturating concentrations, KSG does not completely abolish translation, allowing for continuing expression of some Escherichia coli proteins. Differential action of KSG significantly depends on the nature of the mRNA residue immediately preceding the start codon, with guanine in this position being the most conducive to inhibition by the drug. In addition, the activity of KSG is attenuated by translational coupling as genes whose start codons overlap with the coding regions or the stop codons of the upstream cistrons tend to be less susceptible to drug-mediated inhibition. Altogether, our findings reveal KSG as an example of a small ribosomal subunit-targeting antibiotic with a well-pronounced context specificity of action.

Canary in a coal mine: collided ribosomes as sensors of cellular conditions

The recent discovery that collision of ribosomes triggers quality control and stress responses in eukaryotes has shifted the perspective of the field. Collided eukaryotic ribosomes adopt a unique structure, acting as a ubiquitin signaling platform for various response factors. While several of the signals that determine which downstream pathways are activated have been uncovered, we are only beginning to learn how the specificity for the activation of each process is achieved during collisions. This review will summarize those findings and how ribosome-associated factors act as molecular sentinels, linking aberrations in translation to the overall cellular state. Insights into how cells respond to ribosome collision events will provide greater understanding of the role of the ribosome in the maintenance of cellular homeostasis.

Membrane-dependent relief of translation elongation arrest on pseudouridine- and N1-methyl-pseudouridine-modified mRNAs

Expression of therapeutically important proteins has benefited dramatically from the advent of chemically modified mRNAs that feature decreased lability and immunogenicity. This had a momentous effect on the rapid development of COVID-19 mRNA vaccines. Incorporation of the naturally occurring pseudouridine (Ψ) or N1-methyl-pseudouridine (N1mΨ) into in vitro transcribed mRNAs prevents the activation of unwanted immune responses by blocking eIF2α phosphorylation, which inhibits translation. Here, we report that Ψs in luciferase (Luc) mRNA exacerbate translation pausing in nuclease-untreated rabbit reticulocyte lysate (uRRL) and promote the formation of high-order-ribosome structures. The major deceleration of elongation occurs at the Ψ-rich nucleotides 1294-1326 of Ψ-Luc mRNA and results in premature termination of translation. The impairment of translation is mainly due to the shortage of membranous components. Supplementing uRRL with canine microsomal membranes (CMMs) relaxes the impediments to ribosome movement, resolves collided ribosomes, and greatly enhances full-size luciferase production. CMMs also strongly stimulated an extremely inefficient translation of N1mΨ-Luc mRNA in uRRL. Evidence is presented that translational pausing can promote membrane recruitment of polysomes with nascent polypeptides that lack a signal sequence. Our results highlight an underappreciated role of membrane binding to polysomes in the prevention of ribosome collision and premature release of nascent polypeptides.

Combinations of slow-translating codon clusters can increase mRNA half-life in Saccharomyces cerevisiae

The presence of a single cluster of nonoptimal codons was found to decrease a transcript's half-life through the interaction of the ribosome-associated quality control machinery with stalled ribosomes in Saccharomyces cerevisiae The impact of multiple nonoptimal codon clusters on a transcript's half-life, however, is unknown. Using a kinetic model, we predict that inserting a second nonoptimal cluster near the 5' end can lead to synergistic effects that increase a messenger RNA's (mRNA's) half-life in S. cerevisiae Specifically, the 5' end cluster suppresses the formation of ribosome queues, reducing the interaction of ribosome-associated quality control factors with stalled ribosomes. We experimentally validate this prediction by introducing two nonoptimal clusters into three different genes and find that their mRNA half-life increases up to fourfold. The model also predicts that in the presence of two clusters, the cluster closest to the 5' end is the primary determinant of mRNA half-life. These results suggest the "translational ramp," in which nonoptimal codons are located near the start codon and increase translational efficiency, may have the additional biological benefit of allowing downstream slow-codon clusters to be present without decreasing mRNA half-life. These results indicate that codon usage bias plays a more nuanced role in controlling cellular protein levels than previously thought.

A nascent polypeptide sequence modulates DnaA translation elongation in response to nutrient availability

The ability to regulate DNA replication initiation in response to changing nutrient conditions is an important feature of most cell types. In bacteria, DNA replication is triggered by the initiator protein DnaA, which has long been suggested to respond to nutritional changes; nevertheless, the underlying mechanisms remain poorly understood. Here, we report a novel mechanism that adjusts DnaA synthesis in response to nutrient availability in Caulobacter crescentus. By performing a detailed biochemical and genetic analysis of the dnaA mRNA, we identified a sequence downstream of the dnaA start codon that inhibits DnaA translation elongation upon carbon exhaustion. Our data show that the corresponding peptide sequence, but not the mRNA secondary structure or the codon choice, is critical for this response, suggesting that specific amino acids in the growing DnaA nascent chain tune translational efficiency. Our study provides new insights into DnaA regulation and highlights the importance of translation elongation as a regulatory target. We propose that translation regulation by nascent chain sequences, like the one described, might constitute a general strategy for modulating the synthesis rate of specific proteins under changing conditions.

An Update on mRNA-Based Viral Vaccines

With the success of COVID-19 vaccines, newly created mRNA vaccines against other infectious diseases are beginning to emerge. Here, we review the structural elements required for designing mRNA vaccine constructs for effective in vitro synthetic transcription reactions. The unprecedently speedy development of mRNA vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was enabled with previous innovations in nucleoside modifications during in vitro transcription and lipid nanoparticle delivery materials of mRNA. Recent updates are briefly described in the status of mRNA vaccines against SARS-CoV-2, influenza virus, and other viral pathogens. Unique features of mRNA vaccine platforms and future perspectives are discussed.

The essential role of mRNA degradation in understanding and engineering E. coli metabolism

Metabolic engineering strategies are crucial for the development of bacterial cell factories with improved performance. Until now, optimal metabolic networks have been designed based on systems biology approaches integrating large-scale data on the steady-state concentrations of mRNA, protein and metabolites, sometimes with dynamic data on fluxes, but rarely with any information on mRNA degradation. In this review, we compile growing evidence that mRNA degradation is a key regulatory level in E. coli that metabolic engineering strategies should take into account. We first discuss how mRNA degradation interacts with transcription and translation, two other gene expression processes, to balance transcription regulation and remove poorly translated mRNAs. The many reciprocal interactions between mRNA degradation and metabolism are also highlighted: metabolic activity can be controlled by changes in mRNA degradation and in return, the activity of the mRNA degradation machinery is controlled by metabolic factors. The mathematical models of the crosstalk between mRNA degradation dynamics and other cellular processes are presented and discussed with a view towards novel mRNA degradation-based metabolic engineering strategies. We show finally that mRNA degradation-based strategies have already successfully been applied to improve heterologous protein synthesis. Overall, this review underlines how important mRNA degradation is in regulating E. coli metabolism and identifies mRNA degradation as a key target for innovative metabolic engineering strategies in biotechnology.

Spurious regulatory connections dictate the expression-fitness landscape of translation factors

During steady-state cell growth, individual enzymatic fluxes can be directly inferred from growth rate by mass conservation, but the inverse problem remains unsolved. Perturbing the flux and expression of a single enzyme could have pleiotropic effects that may or may not dominate the impact on cell fitness. Here, we quantitatively dissect the molecular and global responses to varied expression of translation termination factors (peptide release factors, RFs) in the bacterium Bacillus subtilis. While endogenous RF expression maximizes proliferation, deviations in expression lead to unexpected distal regulatory responses that dictate fitness reduction. Molecularly, RF depletion causes expression imbalance at specific operons, which activates master regulators and detrimentally overrides the transcriptome. Through these spurious connections, RF abundances are thus entrenched by focal points within the regulatory network, in one case located at a single stop codon. Such regulatory entrenchment suggests that predictive bottom-up models of expression-fitness landscapes will require near-exhaustive characterization of parts.

Signal Recognition Particle Suppressor Screening Reveals the Regulation of Membrane Protein Targeting by the Translation Rate

The signal recognition particle (SRP) is conserved in all living organisms, and it cotranslationally delivers proteins to the inner membrane or endoplasmic reticulum. Recently, SRP loss was found not to be lethal in either the eukaryote Saccharomyces cerevisiae or the prokaryote Streptococcus mutans In Escherichia coli, the role of SRP in mediating inner membrane protein (IMP) targeting has long been studied. However, the essentiality of SRP remains a controversial topic, partly hindered by the lack of strains in which SRP is completely absent. Here we show that the SRP was nonessential in E. coli by suppressor screening. We identified two classes of extragenic suppressors-two translation initiation factors and a ribosomal protein-all of which are involved in translation initiation. The translation rate and inner membrane proteomic analyses were combined to define the mechanism that compensates for the lack of SRP. The primary factor that contributes to the efficiency of IMP targeting is the extension of the time window for targeting by pausing the initiation of translation, which further reduces translation initiation and elongation rates. Furthermore, we found that easily predictable features in the nascent chain determine the specificity of protein targeting. Our results show why the loss of the SRP pathway does not lead to lethality. We report a new paradigm in which the time delay in translation initiation is beneficial during protein targeting in the absence of SRP.IMPORTANCE Inner membrane proteins (IMPs) are cotranslationally inserted into the inner membrane or endoplasmic reticulum by the signal recognition particle (SRP). Generally, the deletion of SRP can result in protein targeting defects in Escherichia coli Suppressor screening for loss of SRP reveals that pausing at the translation start site is likely to be critical in allowing IMP targeting and avoiding aggregation. In this work, we found for the first time that SRP is nonessential in E. coli The time delay in initiation is different from the previous mechanism that only slows down the elongation rate. It not only maximizes the opportunity for untranslated ribosomes to be near the inner membrane but also extends the time window for targeting translating ribosomes by decreasing the speed of translation. We anticipate that our work will be a starting point for a more delicate regulatory mechanism of protein targeting.

Translational Control by Ribosome Pausing in Bacteria: How a Non-uniform Pace of Translation Affects Protein Production and Folding

Protein homeostasis of bacterial cells is maintained by coordinated processes of protein production, folding, and degradation. Translational efficiency of a given mRNA depends on how often the ribosomes initiate synthesis of a new polypeptide and how quickly they read the coding sequence to produce a full-length protein. The pace of ribosomes along the mRNA is not uniform: periods of rapid synthesis are separated by pauses. Here, we summarize recent evidence on how ribosome pausing affects translational efficiency and protein folding. We discuss the factors that slow down translation elongation and affect the quality of the newly synthesized protein. Ribosome pausing emerges as important factor contributing to the regulatory programs that ensure the quality of the proteome and integrate the cellular and environmental cues into regulatory circuits of the cell.

A Modelling Framework Linking Resource-Based Stochastic Translation to the Optimal Design of Synthetic Constructs

Simple Summary

In synthetic biology, it is commonplace to design and insert gene expression constructs into cells for the production of useful proteins. In order to maximise production yield, it is useful to predict the performance of these “engineered cells” in advance of conducting experiments. This is typically a complex task, which in recent years has motivated the use of “whole-cell models” (WCMs) that act as computational tools for predicting different aspects of cell growth. Many useful WCMs exist, however a common problem is their over-simplification of ribosome movement on mRNA transcripts during translation. WCMs typically don’t consider that, for constructs with inefficient (“slow”) codons, ribosomes can stall and form “traffic jams”, thereby becoming unavailable for translation of other proteins. To more accurately address these scenarios, we have built a computational framework that combines whole-cell modelling with a detailed account of ribosome movement on mRNA. We show how our framework can be used to link the modular design of a gene expression construct (via its promoter, ribosome binding site and codon composition) to protein yield during continuous cell culture, with a particular focus on how the optimal design can change over time in the presence or absence of “slow” codons.

Abstract

The effect of gene expression burden on engineered cells has motivated the use of “whole-cell models” (WCMs) that use shared cellular resources to predict how unnatural gene expression affects cell growth. A common problem with many WCMs is their inability to capture translation in sufficient detail to consider the impact of ribosomal queue formation on mRNA transcripts. To address this, we have built a “stochastic cell calculator” (StoCellAtor) that combines a modified TASEP with a stochastic implementation of an existing WCM. We show how our framework can be used to link a synthetic construct’s modular design (promoter, ribosome binding site (RBS) and codon composition) to protein yield during continuous culture, with a particular focus on the effects of low-efficiency codons and their impact on ribosomal queues. Through our analysis, we recover design principles previously established in our work on burden-sensing strategies, namely that changing promoter strength is often a more efficient way to increase protein yield than RBS strength. Importantly, however, we show how these design implications can change depending on both the duration of protein expression, and on the presence of ribosomal queues.

Inferring efficiency of translation initiation and elongation from ribosome profiling

One of the main goals of ribosome profiling is to quantify the rate of protein synthesis at the level of translation. Here, we develop a method for inferring translation elongation kinetics from ribosome profiling data using recent advances in mathematical modelling of mRNA translation. Our method distinguishes between the elongation rate intrinsic to the ribosome’s stepping cycle and the actual elongation rate that takes into account ribosome interference. This distinction allows us to quantify the extent of ribosomal collisions along the transcript and identify individual codons where ribosomal collisions are likely. When examining ribosome profiling in yeast, we observe that translation initiation and elongation are close to their optima and traffic is minimized at the beginning of the transcript to favour ribosome recruitment. However, we find many individual sites of congestion along the mRNAs where the probability of ribosome interference can reach \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$50\%$\end{document}. Our work provides new measures of translation initiation and elongation efficiencies, emphasizing the importance of rating these two stages of translation separately.

Ribosome Collisions Result in +1 Frameshifting in the Absence of No-Go Decay

During translation, an mRNA is typically occupied by multiple ribosomes sparsely distributed across the coding sequence. This distribution, mediated by slow rates of initiation relative to elongation, ensures that they rarely collide with each other, but given the stochastic nature of protein synthesis, collision events do occur. Recent work from our lab suggested that collisions signal for mRNA degradation through no-go decay (NGD). We have explored the impact of stalling on ribosome function when NGD is compromised and found it to result in +1 frameshifting. We used reporters that limit the number of ribosomes on a transcript to show that +1 frameshifting is induced through ribosome collision in yeast and bacteria. Furthermore, we observe a positive correlation between ribosome density and frameshifting efficiency. It is thus tempting to speculate that NGD, in addition to its role in mRNA quality control, evolved to cope with stochastic collision events to prevent deleterious frameshifting events.

Ribosome collisions, resulting from stalling, activate quality control processes to degrade the aberrant mRNA and the incomplete peptide. mRNA degradation proceeds through an endonucleolytic cleavage between the stacked ribosomes, which resolves the collisions. Simms et al. show that, when cleavage is inhibited, colliding ribosomes move out of frame.

Mechanisms of drug interactions between translation-inhibiting antibiotics

Antibiotics that interfere with translation, when combined, interact in diverse and difficult-to-predict ways. Here, we explain these interactions by "translation bottlenecks": points in the translation cycle where antibiotics block ribosomal progression. To elucidate the underlying mechanisms of drug interactions between translation inhibitors, we generate translation bottlenecks genetically using inducible control of translation factors that regulate well-defined translation cycle steps. These perturbations accurately mimic antibiotic action and drug interactions, supporting that the interplay of different translation bottlenecks causes these interactions. We further show that growth laws, combined with drug uptake and binding kinetics, enable the direct prediction of a large fraction of observed interactions, yet fail to predict suppression. However, varying two translation bottlenecks simultaneously supports that dense traffic of ribosomes and competition for translation factors account for the previously unexplained suppression. These results highlight the importance of "continuous epistasis" in bacterial physiology.

Delivery of Heterologous Proteins, Enzymes, and Antigens via the Bacterial Type III Secretion System

The Type III Secretion System (T3SS) is a multimeric protein complex composed of over 20 different proteins, utilized by Gram-negative bacteria to infect eukaryotic host cells. The T3SS has been implicated as a virulence factor by which pathogens cause infection and has recently been characterized as a communication tool between bacteria and plant cells in the rhizosphere. The T3SS has been repurposed to be used as a tool for the delivery of non-native or heterologous proteins to eukaryotic cells or the extracellular space for a variety of purposes, including drug discovery and drug delivery. This review covers the methodology of heterologous protein secretion as well as multiple cases of utilizing the T3SS to deliver heterologous proteins or artificial materials. The research covered in this review will serve to outline the scope and limitations of utilizing the T3SS as a tool for protein delivery.

Codon usage bias affects α-amylase mRNA level by altering RNA stability and cytosine methylation patterns in Escherichia coli

Codon usage bias exists in almost every organism and is reported to regulate protein translation efficiency and folding. Besides translation, the preliminary role of codon usage bias on gene transcription has also been revealed in some eukaryotes such as Neurospora crassa. In this study, we took as an example the α-amylase-coding gene (amyA) and examined the role of codon usage bias in regulating gene expression in the typical prokaryote Escherichia coli. We confirmed the higher translation efficiency on codon-optimized amyA RNAs and found that the RNA level itself was also affected by codon optimization. The decreased RNA level was caused at least in part by altered mRNA stability at the post-transcriptional level. Codon optimization also altered the number of cytosine methylation sites. Examination on dcm knockouts suggested that cytosine methylation may be a minor mechanism adopted by codon bias to regulate gene RNA levels. More studies are required to verify the global effect of codon usage and to reveal its detailed mechanism on transcription.

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 Impact of the Stringent Response on TRAFAC GTPases and Prokaryotic Ribosome Assembly

Many facets of ribosome biogenesis and function, including ribosomal RNA (rRNA) transcription, 70S assembly and protein translation, are negatively impacted upon induction of a nutrient stress-sensing signalling pathway termed the stringent response. This stress response is mediated by the alarmones guanosine tetra- and penta-phosphate ((p)ppGpp), the accumulation of which leads to a massive cellular response that slows growth and aids survival. The 70S bacterial ribosome is an intricate structure, with assembly both complex and highly modular. Presiding over the assembly process is a group of P-loop GTPases within the TRAFAC (Translation Factor Association) superclass that are crucial for correct positioning of both early and late stage ribosomal proteins (r-proteins) onto the rRNA. Often described as 'molecular switches', members of this GTPase superfamily readily bind and hydrolyse GTP to GDP in a cyclic manner that alters the propensity of the GTPase to carry out a function. TRAFAC GTPases are considered to act as checkpoints to ribosome assembly, involved in binding to immature sections in the GTP-bound state, preventing further r-protein association until maturation is complete. Here we review our current understanding of the impact of the stringent response and (p)ppGpp production on ribosome maturation in prokaryotic cells, focusing on the inhibition of (p)ppGpp on GTPase-mediated subunit assembly, but also touching upon the inhibition of rRNA transcription and protein translation.

Two Old Dogs, One New Trick: A Review of RNA Polymerase and Ribosome Interactions during Transcription-Translation Coupling

The coupling of transcription and translation is more than mere translation of an mRNA that is still being transcribed. The discovery of physical interactions between RNA polymerase and ribosomes has spurred renewed interest into this long-standing paradigm of bacterial molecular biology. Here, we provide a concise presentation of recent insights gained from super-resolution microscopy, biochemical, and structural work, including cryo-EM studies. Based on the presented data, we put forward a dynamic model for the interaction between RNA polymerase and ribosomes, in which the interactions are repeatedly formed and broken. Furthermore, we propose that long intervening nascent RNA will loop out and away during the forming the interactions between the RNA polymerase and ribosomes. By comparing the effect of the direct interactions between RNA polymerase and ribosomes with those that transcription factors NusG and RfaH mediate, we submit that two distinct modes of coupling exist: Factor-free and factor-mediated coupling. Finally, we provide a possible framework for transcription-translation coupling and elude to some open questions in the field.

Driven transport on a flexible polymer with particle recycling: A model inspired by transcription and translation

Many theoretical works have attempted to coarse grain gene expression at the level of transcription and translation via frameworks based on exclusion processes. Usually in these models the three-dimensional conformation of the substrates (DNA and mRNA) is neglected, and particles move on a static unidimensional lattice in contact to an infinite reservoir. In this work we generalize the paradigmatic exclusion process and study the transport of particles along a unidimensional polymerlike flexible lattice immersed in a three-dimensional particle reservoir. We study the recycling of particles in the reservoir, how the transport is influenced by the global conformation of the lattice, and, in turn, how particle density dictates the structure of the polymer.

Toward a Kinetic Understanding of Eukaryotic Translation

The eukaryotic translation pathway has been studied for more than four decades, but the molecular mechanisms that regulate each stage of the pathway are not completely defined. This is in part because we have very little understanding of the kinetic framework for the assembly and disassembly of pathway intermediates. Steps of the pathway are thought to occur in the subsecond to second time frame, but most assays to monitor these events require minutes to hours to complete. Understanding translational control in sufficient detail will therefore require the development of assays that can precisely monitor the kinetics of the translation pathway in real time. Here, we describe the translation pathway from the perspective of its kinetic parameters, discuss advances that are helping us move toward the goal of a rigorous kinetic understanding, and highlight some of the challenges that remain.

Added value of autoregulation and multi-step kinetics of transcription initiation

Bacterial gene expression regulation occurs mostly during transcription, which has two main rate-limiting steps: the close complex formation, when the RNA polymerase binds to an active promoter, and the subsequent open complex formation, after which it follows elongation. Tuning these steps' kinetics by the action of e.g. transcription factors, allows for a wide diversity of dynamics. For example, adding autoregulation generates single-gene circuits able to perform more complex tasks. Using stochastic models of transcription kinetics with empirically validated parameter values, we investigate how autoregulation and the multi-step transcription initiation kinetics of single-gene autoregulated circuits can be combined to fine-tune steady state mean and cell-to-cell variability in protein expression levels, as well as response times. Next, we investigate how they can be jointly tuned to control complex behaviours, namely, time counting, switching dynamics and memory storage. Overall, our finding suggests that, in bacteria, jointly regulating a single-gene circuit's topology and the transcription initiation multi-step dynamics allows enhancing complex task performance.

Translation in Prokaryotes

This review summarizes our current understanding of translation in prokaryotes, focusing on the mechanistic and structural aspects of each phase of translation: initiation, elongation, termination, and ribosome recycling. The assembly of the initiation complex provides multiple checkpoints for messenger RNA (mRNA) and start-site selection. Correct codon-anticodon interaction during the decoding phase of elongation results in major conformational changes of the small ribosomal subunit and shapes the reaction pathway of guanosine triphosphate (GTP) hydrolysis. The ribosome orchestrates proton transfer during peptide bond formation, but requires the help of elongation factor P (EF-P) when two or more consecutive Pro residues are to be incorporated. Understanding the choreography of transfer RNA (tRNA) and mRNA movements during translocation helps to place the available structures of translocation intermediates onto the time axis of the reaction pathway. The nascent protein begins to fold cotranslationally, in the constrained space of the polypeptide exit tunnel of the ribosome. When a stop codon is reached at the end of the coding sequence, the ribosome, assisted by termination factors, hydrolyzes the ester bond of the peptidyl-tRNA, thereby releasing the nascent protein. Following termination, the ribosome is dissociated into subunits and recycled into another round of initiation. At each step of translation, the ribosome undergoes dynamic fluctuations between different conformation states. The aim of this article is to show the link between ribosome structure, dynamics, and function.

Power series solution of the inhomogeneous exclusion process

We develop a power series method for the nonequilibrium steady state of the inhomogeneous one-dimensional totally asymmetric simple exclusion process (TASEP) in contact with two particle reservoirs and with site-dependent hopping rates in the bulk. The power series is performed in the entrance or exit rates governing particle exchange with the reservoirs, and the corresponding particle current is computed analytically up to the cubic term in the entry or exit rate, respectively. We also show how to compute higher-order terms using combinatorial objects known as Young tableaux. Our results address the long outstanding problem of finding the exact nonequilibrium steady state of the inhomogeneous TASEP. The findings are particularly relevant to the modeling of mRNA translation in which the rate of translation initiation, corresponding to the entrance rate in the TASEP, is typically small.

Translation initiation in bacterial polysomes through ribosome loading on a standby site on a highly translated mRNA

Polysomes are ensembles of two or more consecutive ribosomes that translate mRNA into proteins. Adjacent ribosomes can affect the frequency with which a new ribosome is loaded into the polysome. Here we show that mRNA with a long 5′UTR can recruit the next ribosome when the genuine start site is still occupied by the leading ribosome. The second ribosome binds to the upstream standby site on the mRNA, helped by the ribosomal proteins S1/S2 of the preceding ribosome. When the translating ribosome has cleared the start codon, the consecutive ribosome can rapidly move to the translation start. Recruitment to the standby site is a mechanism to increase polysome density and to regulate the efficiency of translation in polysomes.

During translation, consecutive ribosomes load on an mRNA and form a polysome. The first ribosome binds to a single-stranded mRNA region and moves toward the start codon, unwinding potential mRNA structures on the way. In contrast, the following ribosomes can dock at the start codon only when the first ribosome has vacated the initiation site. Here we show that loading of the second ribosome on a natural 38-nt-long 5′ untranslated region of lpp mRNA, which codes for the outer membrane lipoprotein from Escherichia coli, takes place before the leading ribosome has moved away from the start codon. The rapid formation of this standby complex depends on the presence of ribosomal proteins S1/S2 in the leading ribosome. The early recruitment of the second ribosome to the standby site before translation by the leading ribosome and the tight coupling between translation elongation by the first ribosome and the accommodation of the second ribosome can contribute to high translational efficiency of the lpp mRNA.

Formulation of the protein synthesis rate with sequence information

Translation is a central biological process by which proteins are synthesized from genetic information contained within mRNAs. Here, we investigate the kinetics of translation at the molecular level by a stochastic simulation model. The model explicitly includes RNA sequences, ribosome dynamics, the tRNA pool and biochemical reactions involved in the translation elongation. The results show that the translation efficiency is mainly limited by the available ribosome number, translation initiation and the translation elongation time. The elongation time is a log-normal distribution, with the mean and variance determined by the codon saturation and the process of aa-tRNA selection at each codon binding site. Moreover, our simulations show that the translation accuracy exponentially decreases with the sequence length. These results suggest that aa-tRNA competition is crucial for both translation elongation, translation efficiency and the accuracy, which in turn determined the effective protein production rate of correct proteins. Our results improve the dynamical equation of protein production with a delay differential equation that is dependent on sequence information through both the effective production rate and the distribution of elongation time.

Deciphering mRNA Sequence Determinants of Protein Production Rate

One of the greatest challenges in biophysical models of translation is to identify coding sequence features that affect the rate of translation and therefore the overall protein production in the cell. We propose an analytic method to solve a translation model based on the inhomogeneous totally asymmetric simple exclusion process, which allows us to unveil simple design principles of nucleotide sequences determining protein production rates. Our solution shows an excellent agreement when compared to numerical genome-wide simulations of S. cerevisiae transcript sequences and predicts that the first 10 codons, which is the ribosome footprint length on the mRNA, together with the value of the initiation rate, are the main determinants of protein production rate under physiological conditions. Finally, we interpret the obtained analytic results based on the evolutionary role of the codons' choice for regulating translation rates and ribosome densities.

The extent of ribosome queuing in budding yeast

Ribosome queuing is a fundamental phenomenon suggested to be related to topics such as genome evolution, synthetic biology, gene expression regulation, intracellular biophysics, and more. However, this phenomenon hasn't been quantified yet at a genomic level. Nevertheless, methodologies for studying translation (e.g. ribosome footprints) are usually calibrated to capture only single ribosome protected footprints (mRPFs) and thus limited in their ability to detect ribosome queuing. On the other hand, most of the models in the field assume and analyze a certain level of queuing. Here we present an experimental-computational approach for studying ribosome queuing based on sequencing of RNA footprints extracted from pairs of ribosomes (dRPFs) using a modified ribosome profiling protocol. We combine our approach with traditional ribosome profiling to generate a detailed profile of ribosome traffic. The data are analyzed using computational models of translation dynamics. The approach was implemented on the Saccharomyces cerevisiae transcriptome. Our data shows that ribosome queuing is more frequent than previously thought: the measured ratio of ribosomes within dRPFs to mRPFs is 0.2–0.35, suggesting that at least one to five translating ribosomes is in a traffic jam; these queued ribosomes cannot be captured by traditional methods. We found that specific regions are enriched with queued ribosomes, such as the 5’-end of ORFs, and regions upstream to mRPF peaks, among others. While queuing is related to higher density of ribosomes on the transcript (characteristic of highly translated genes), we report cases where traffic jams are relatively more severe in lowly expressed genes and possibly even selected for. In addition, our analysis demonstrates that higher adaptation of the coding region to the intracellular tRNA levels is associated with lower queuing levels. Our analysis also suggests that the Saccharomyces cerevisiae transcriptome undergoes selection for eliminating traffic jams. Thus, our proposed approach is an essential tool for high resolution analysis of ribosome traffic during mRNA translation and understanding its evolution.

During translation, multiple ribosomes may translate the same mRNA. The density of ribosomal traffic across the transcript poses several open questions, such as how often a ribosome’s path is blocked by a second ribosome, do queues of multiple ribosomes typically form on mRNAs and what is their effect on the overall translation rate of an mRNA. However, this phenomenon hasn't been quantified yet at a genomic level. Nevertheless, methodologies for monitoring translation are limited in their ability to detect ribosome queuing. On the other hand, most of the models in the field assume and analyze a certain level of queuing. Here we present an experimental-computational approach for studying ribosome queuing based on sequencing of RNA footprints extracted from pairs of adjacent translating ribosomes, and a computational model of translation dynamics. Our data shows that ribosome queuing in Saccharomyces cerevisiae is more frequent than previously thought, suggesting that at least one to five translating ribosomes is in a traffic jam; these queued ribosomes cannot be captured by traditional methods. Our analysis also suggests that the S. cerevisiae transcriptome undergoes selection for eliminating traffic jams, while specific regions and genes may possibly be under selection for increased queuing.

Influence of multiplicative stochastic variation on translational elongation rates

Experimental data indicate that stochastic effects exerted at the level of translation contribute substantially to the variation in abundance of proteins expressed at moderate to high levels. This study analyzes the theoretical consequences of fluctuations in residue-specific elongation rates during translation. A simple analytical framework shows that rate variation during elongation gives rise to protein production rates that consist of sums of products of random variables. Simulations show that because the contribution to total variation of products of random variables greatly exceeds that of sums of random variables, the overall distribution exhibits approximately log-normal behavior. Empirical fits of the data can be satisfied by either sums of log-normal distributions, or sums of log-normal and log-logistic distributions. Elongation rate stochastic variation offers an accounting for a major component of biological variation. The analysis provided here highlights a probability distribution that is a natural extension of the Poisson and has broad applicability to many types of multiplicative noise processes.

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.

Codon optimality, bias and usage in translation and mRNA decay

The advent of ribosome profiling and other tools to probe mRNA translation has revealed that codon bias - the uneven use of synonymous codons in the transcriptome - serves as a secondary genetic code: a code that guides the efficiency of protein production, the fidelity of translation and the metabolism of mRNAs. Recent advancements in our understanding of mRNA decay have revealed a tight coupling between ribosome dynamics and the stability of mRNA transcripts; this coupling integrates codon bias into the concept of codon optimality, or the effects that specific codons and tRNA concentrations have on the efficiency and fidelity of the translation machinery. In this Review, we first discuss the evidence for codon-dependent effects on translation, beginning with the basic mechanisms through which translation perturbation can affect translation efficiency, protein folding and transcript stability. We then discuss how codon effects are leveraged by the cell to tailor the proteome to maintain homeostasis, execute specific gene expression programmes of growth or differentiation and optimize the efficiency of protein production.

Ribosome Collision Is Critical for Quality Control during No-Go Decay

No-go decay (NGD) is a eukaryotic quality control mechanism that evolved to cope with translational arrests. The process is characterized by an endonucleolytic cleavage near the stall sequence, but the mechanistic details are unclear. Our analysis of cleavage sites indicates that cleavage requires multiple ribosomes on the mRNA. We also show that reporters harboring stall sequences near the initiation codon, which cannot accommodate multiple ribosomes, are not subject to NGD. Consistent with our model, we uncover an inverse correlation between ribosome density per mRNA and cleavage efficiency. Furthermore, promoting global ribosome collision in vivo resulted in ubiquitination of ribosomal proteins, suggesting that collision is sensed by the cell to initiate downstream quality control processes. Collectively, our data suggest that NGD and subsequent quality control are triggered by ribosome collision. This model provides insight into the regulation of quality control processes and the manner by which they reduce off-target effects.

Application of sorting and next generation sequencing to study 5΄-UTR influence on translation efficiency in Escherichia coli

Yield of protein per translated mRNA may vary by four orders of magnitude. Many studies analyzed the influence of mRNA features on the translation yield. However, a detailed understanding of how mRNA sequence determines its propensity to be translated is still missing. Here, we constructed a set of reporter plasmid libraries encoding CER fluorescent protein preceded by randomized 5΄ untranslated regions (5΄-UTR) and Red fluorescent protein (RFP) used as an internal control. Each library was transformed into Escherchia coli cells, separated by efficiency of CER mRNA translation by a cell sorter and subjected to next generation sequencing. We tested efficiency of translation of the CER gene preceded by each of 48 natural 5΄-UTR sequences and introduced random and designed mutations into natural and artificially selected 5΄-UTRs. Several distinct properties could be ascribed to a group of 5΄-UTRs most efficient in translation. In addition to known ones, several previously unrecognized features that contribute to the translation enhancement were found, such as low proportion of cytidine residues, multiple SD sequences and AG repeats. The latter could be identified as translation enhancer, albeit less efficient than SD sequence in several natural 5΄-UTRs.

Generation of a novel TRAIL mutant by proline to arginine substitution based on codon bias and its antitumor effects

TNF ligand superfamily member 10 (TRAIL) is a member of the tumor necrosis factor superfamily. The present study was performed in an effort to increase the expression of soluble (s)TRAIL by rebuilding the gene sequence of TRAIL. Three principles based on the codon bias of Escherichia coli were put forward to design the rebuild strategy. Relying on these three principles, a P7R mutation near the N‑terminal region of sTRAIL, named TRAIL‑Mu, was designed. TRAIL‑Mu was subsequently cloned into the PTWIN1 plasmid and expressed in E. coli BL21 (DE3). Using a high‑level expression system and a three‑step purification method, soluble TRAIL‑Mu protein reached ~90% of total cellular protein and purity was >95%, demonstrating success in overcoming inclusion body formation. The cytotoxic effect of TRAIL‑Mu was evaluated by sulforhodamine B assay in the MD‑MB‑231, A549, NCI‑H460 and L02 cell lines. The results demonstrated that TRAIL‑Mu exerted stronger antitumor effects on TRAIL‑sensitive tumor cell lines, and was able to partially reverse the resistance of a TRAIL‑resistant tumor cell line. In addition, TRAIL‑Mu exhibited no notable biological effects in a normal liver cell line. The novel TRAIL variant generated in the present study may be useful for the mass production of this important protein for therapeutic purposes.

Tuning of Recombinant Protein Expression in Escherichia coli by Manipulating Transcription, Translation Initiation Rates, and Incorporation of Noncanonical Amino Acids

Protein synthesis in cells has been thoroughly investigated and characterized over the past 60 years. However, some fundamental issues remain unresolved, including the reasons for genetic code redundancy and codon bias. In this study, we changed the kinetics of the Eschrichia coli transcription and translation processes by mutating the promoter and ribosome binding domains and by using genetic code expansion. The results expose a counterintuitive phenomenon, whereby an increase in the initiation rates of transcription and translation lead to a decrease in protein expression. This effect can be rescued by introducing slow translating codons into the beginning of the gene, by shortening gene length or by reducing initiation rates. On the basis of the results, we developed a biophysical model, which suggests that the density of co-transcriptional-translation plays a role in bacterial protein synthesis. These findings indicate how cells use codon bias to tune translation speed and protein synthesis.

Kinetic modeling predicts a stimulatory role for ribosome collisions at elongation stall sites in bacteria

Ribosome stalling on mRNAs can decrease protein expression. To decipher ribosome kinetics at stall sites, we induced ribosome stalling at specific codons by starving the bacterium Escherichia coli for the cognate amino acid. We measured protein synthesis rates from a reporter library of over 100 variants that encoded systematic perturbations of translation initiation rate, the number of stall sites, and the distance between stall sites. Our measurements are quantitatively inconsistent with two widely-used kinetic models for stalled ribosomes: ribosome traffic jams that block initiation, and abortive (premature) termination of stalled ribosomes. Rather, our measurements support a model in which collision with a trailing ribosome causes abortive termination of the stalled ribosome. In our computational analysis, ribosome collisions selectively stimulate abortive termination without fine-tuning of kinetic rate parameters at ribosome stall sites. We propose that ribosome collisions serve as a robust timer for translational quality control pathways to recognize stalled ribosomes.