Trade-offs between tRNA abundance and mRNA secondary structure support smoothing of translation elongation rate

Cell-free prediction of protein expression costs for growing cells

Translating heterologous proteins places significant burden on host cells, consuming expression resources leading to slower cell growth and productivity. Yet predicting the cost of protein production for any given gene is a major challenge, as multiple processes and factors combine to determine translation efficiency. To enable prediction of the cost of gene expression in bacteria, we describe here a standard cell-free lysate assay that provides a relative measure of resource consumption when a protein coding sequence is expressed. These lysate measurements can then be used with a computational model of translation to predict the in vivo burden placed on growing E. coli cells for a variety of proteins of different functions and lengths. Using this approach, we can predict the burden of expressing multigene operons of different designs and differentiate between the fraction of burden related to gene expression compared to action of a metabolic pathway.

Scikit-ribo Enables Accurate Estimation and Robust Modeling of Translation Dynamics at Codon Resolution

Ribosome profiling (Ribo-seq) is a powerful technique for measuring protein translation; however, sampling errors and biological biases are prevalent and poorly understood. Addressing these issues, we present Scikit-ribo (https://github.com/schatzlab/scikit-ribo), an open-source analysis package for accurate genome-wide A-site prediction and translation efficiency (TE) estimation from Ribo-seq and RNA sequencing data. Scikit-ribo accurately identifies A-site locations and reproduces codon elongation rates using several digestion protocols (r = 0.99). Next, we show that the commonly used reads per kilobase of transcript per million mapped reads-derived TE estimation is prone to biases, especially for low-abundance genes. Scikit-ribo introduces a codon-level generalized linear model with ridge penalty that correctly estimates TE, while accommodating variable codon elongation rates and mRNA secondary structure. This corrects the TE errors for over 2,000 genes in S. cerevisiae, which we validate using mass spectrometry of protein abundances (r = 0.81), and allows us to determine the Kozak-like sequence directly from Ribo-seq. We conclude with an analysis of coverage requirements needed for robust codon-level analysis and quantify the artifacts that can occur from cycloheximide treatment.

Evolutionary analysis of polyproline motifs in Escherichia coli reveals their regulatory role in translation

Translation of consecutive prolines causes ribosome stalling, which is alleviated but cannot be fully compensated by the elongation factor P. However, the presence of polyproline motifs in about one third of the E. coli proteins underlines their potential functional importance, which remains largely unexplored. We conducted an evolutionary analysis of polyproline motifs in the proteomes of 43 E. coli strains and found evidence of evolutionary selection against translational stalling, which is especially pronounced in proteins with high translational efficiency. Against the overall trend of polyproline motif loss in evolution, we observed their enrichment in the vicinity of translational start sites, in the inter-domain regions of multi-domain proteins, and downstream of transmembrane helices. Our analysis demonstrates that the time gain caused by ribosome pausing at polyproline motifs might be advantageous in protein regions bracketing domains and transmembrane helices. Polyproline motifs might therefore be crucial for co-translational folding and membrane insertion.

Polyproline motifs induce ribosome stalling during translation, but the functional significance of this effect remains unclear. Our evolutionary analysis of polyproline motifs reveals that they are disfavored in E. coli proteomes as a consequence of the reduced translation efficiency, supporting the conjecture that translation efficiency-based evolutionary pressure shapes protein sequences. Enrichment of polyproline motifs in the protein regions bracketing structural domains and transmembrane helices indicates their regulatory role in co-translational protein folding and transmembrane helix insertion. Polyproline motifs could thus serve as protein-level cis-acting elements, which directly regulate the rate of translation elongation.

Determinants of translation speed are randomly distributed across transcripts resulting in a universal scaling of protein synthesis times

Ribosome profiling experiments have found greater than 100-fold variation in ribosome density along mRNA transcripts, indicating that individual codon elongation rates can vary to a similar degree. This wide range of elongation times, coupled with differences in codon usage between transcripts, suggests that the average codon translation-rate per gene can vary widely. Yet, ribosome run-off experiments have found that the average codon translation rate for different groups of transcripts in mouse stem cells is constant at 5.6 AA/s. How these seemingly contradictory results can be reconciled is the focus of this study. Here, we combine knowledge of the molecular factors shown to influence translation speed with genomic information from Escherichia coli, Saccharomyces cerevisiae and Homo sapiens to simulate the synthesis of cytosolic proteins in these organisms. The model recapitulates a near constant average translation rate, which we demonstrate arises because the molecular determinants of translation speed are distributed nearly randomly amongst most of the transcripts. Consequently, codon translation rates are also randomly distributed and fast-translating segments of a transcript are likely to be offset by equally probable slow-translating segments, resulting in similar average elongation rates for most transcripts. We also show that the codon usage bias does not significantly affect the near random distribution of codon translation rates because only about 10% of the total transcripts in an organism have high codon usage bias while the rest have little to no bias. Analysis of Ribo-Seq data and an in vivo fluorescent assay supports these conclusions.

Local genic base composition impacts protein production and cellular fitness

The maintenance of a G + C content that is higher than the mutational input to a genome provides support for the view that selection serves to increase G + C contents in bacteria. Recent experimental evidence from Escherichia coli demonstrated that selection for increasing G + C content operates at the level of translation, but the precise mechanism by which this occurs is unknown. To determine the substrate of selection, we asked whether selection on G + C content acts across all sites within a gene or is confined to particular genic regions or nucleotide positions. We systematically altered the G + C contents of the GFP gene and assayed its effects on the fitness of strains harboring each variant. Fitness differences were attributable to the base compositional variation in the terminal portion of the gene, suggesting a connection to the folding of a specific protein feature. Variants containing sequence features that are thought to result in rapid translation, such as low G + C content and high levels of codon adaptation, displayed highly reduced growth rates. Taken together, our results show that purifying selection acting against A and T mutations most likely results from their tendency to increase the rate of translation, which can perturb the dynamics of protein folding.

In vivo selection of sfGFP variants with improved and reliable functionality in industrially important thermophilic bacteria

BACKGROUND

Fluorescent reporter proteins (FP) have become an indispensable tool for the optimization of microbial cell factories and in synthetic biology per se. The applicability of the currently available FPs is, however, constrained by species-dependent performance and misfolding at elevated temperatures. To obtain functional reporters for thermophilic, biotechnologically important bacteria such as Parageobacillus thermoglucosidasius, an in vivo screening approach based on a mutational library of superfolder GFP was applied.

RESULTS

Flow cytometry-based benchmarking of a set of GFPs, sfGFPs and species-specific codon-optimized variants revealed that none of the proteins was satisfyingly detectable in P. thermoglucosidasius at its optimal growth temperature of 60 °C. An undirected mutagenesis approach coupled to fluorescence-activated cell sorting allowed the isolation of sfGFP variants that were extremely well expressed in the chassis background at 60 °C. Notably, a few nucleotide substitutions, including silent mutations, significantly improved the functionality and brightness. The best mutant sfGFP(N39D/A179A) showed an 885-fold enhanced mean fluorescence intensity (MFI) at 60 °C and is the most reliable reporter protein with respect to cell-to-cell variation and signal intensity reported so far. The in vitro spectral and thermostability properties were unaltered as compared to the parental sfGFP protein, strongly indicating that the combination of the amino acid exchange and an altered translation or folding speed, or protection from degradation, contribute to the strongly improved in vivo performance. Furthermore, sfGFP(N39D/A179A) and the newly developed cyan and yellow derivatives were successfully used for labeling several industrially relevant thermophilic bacilli, thus proving their broad applicability.

CONCLUSIONS

This study illustrates the power of in vivo isolation of thermostable proteins to obtain reporters for highly efficient fluorescence labeling. Successful expression in a variety of thermophilic bacteria proved that the novel FPs are highly suitable for imaging and flow cytometry-based studies. This enables a reliable cell tracking and single-cell-based real-time monitoring of biological processes that are of industrial and biotechnological interest.

Model-based genome-wide determination of RNA chain elongation rates in Escherichia coli

Dynamics in the process of transcription are often simplified, yet they play an important role in transcript folding, translation into functional protein and DNA supercoiling. While the modulation of the speed of transcription of individual genes and its role in regulation and proper protein folding has been analyzed in depth, the functional relevance of differences in transcription speeds as well as the factors influencing it have not yet been determined on a genome-wide scale. Here we determined transcription speeds for the majority of E. coli genes based on experimental data. We find large differences in transcription speed between individual genes and a strong influence of both cellular location as well as the relative importance of genes for cellular function on transcription speeds. Investigating factors influencing transcription speeds we observe both codon composition as well as factors associated to DNA topology as most important factors influencing transcription speeds. Moreover, we show that differences in transcription speeds are sufficient to explain the timing of regulatory responses during environmental shifts and highlight the importance of the consideration of transcription speeds in the design of experiments measuring transcriptomic responses to perturbations.

Translation efficiency is maintained at elevated temperature in Escherichia coli

Cellular protein levels are dictated by the balance between gene transcription, mRNA translation, and protein degradation, among other factors. Translation requires the interplay of several RNA hybridization processes, which are expected to be temperature-sensitive. We used ribosome profiling to monitor translation in Escherichia coli at 30 °C and to investigate how this changes after 10-20 min of heat shock at 42 °C. Translation efficiencies are robustly maintained after thermal heat shock and after mimicking the heat-shock response transcriptional program at 30 °C by overexpressing the heat shock σ factor encoded by the rpoH gene. We compared translation efficiency, the ratio of ribosome footprint reads to mRNA reads for each gene, to parameters derived from gene sequences. Genes with stable mRNA structures, non-optimal codon use, and those whose gene product is cotranslationally translocated into the inner membrane are generally less highly translated than other genes. Comparison with other published datasets suggests a role for translational elongation in coupling mRNA structures to translation initiation. Genome-wide calculations of the temperature dependence of mRNA structure predict that relatively few mRNAs show a melting transition between 30 and 42 °C, consistent with the observed lack of changes in translation efficiency. We developed a linear model with six parameters that can predict 38% of the variation in translation efficiency between genes, which may be useful in interpreting transcriptome data.

Effects of mRNA secondary structure on the expression of HEV ORF2 proteins in Escherichia coli

Background

Viral protein expression in Escherichia coli (E. coli) is a powerful tool for structural/functional studies as well as for vaccine and diagnostics development. However, numerous factors such as codon bias, mRNA secondary structure and nucleotides distribution, have been indentified to hamper this heterologous expression.

Results

In this study, we combined computational and biochemical methods to analyze the influence of these factors on the expression of different segments of hepatitis E virus (HEV) ORF 2 protein and hepatitis B virus surface antigen (HBsAg). Three out of five HEV antigens were expressed while all three HBsAg fragments were not. The computational analysis revealed a significant difference in nucleotide distribution between expressed and non-expressed genes; and all these non-expressing constructs shared similar stable 5′-end mRNA secondary structures that affected the accessibility of both Shine-Dalgarno (SD) sequence and start codon AUG. By modifying the 5′-end of HEV and HBV non-expressed genes, there was a significant increase in the total free energy of the mRNA secondary structures that permitted the exposure of the SD sequence and the start codon, which in turn, led to the successful expression of these genes in E. coli.

Conclusions

This study demonstrates that the mRNA secondary structure near the start codon is the key limiting factor for an efficient expression of HEV ORF2 proteins in E. coli. It describes also a simple and effective strategy for the production of viral proteins of different lengths for immunogenicity/antigenicity comparative studies during vaccine and diagnostics development.

Electronic supplementary material

The online version of this article (10.1186/s12934-017-0812-8) contains supplementary material, which is available to authorized users.

Precise quantification of translation inhibition by mRNA structures that overlap with the ribosomal footprint in N-terminal coding sequences

A mRNA's translation rate is controlled by several sequence determinants, including the presence of RNA structures within the N-terminal regions of its coding sequences. However, the physical rules that govern when such mRNA structures will inhibit translation remain unclear. Here, we introduced systematically designed RNA hairpins into the N-terminal coding region of a reporter protein with steadily increasing distances from the start codon, followed by characterization of their mRNA and expression levels in Escherichia coli. We found that the mRNAs' translation rates were repressed, by up to 530-fold, when mRNA structures overlapped with the ribosome's footprint. In contrast, when the mRNA structure was located outside the ribosome's footprint, translation was repressed by <2-fold. By combining our measurements with biophysical modeling, we determined that the ribosomal footprint extends 13 nucleotides into the N-terminal coding region and, when a mRNA structure overlaps or partially overlaps with the ribosomal footprint, the free energy to unfold only the overlapping structure controlled the extent of translation repression. Overall, our results provide precise quantification of the rules governing translation initiation at N-terminal coding regions, improving the predictive design of post-transcriptional regulatory elements that regulate translation rate.

Adaptation of mRNA structure to control protein folding

Comparison of mRNA and protein structures shows that highly structured mRNAs typically encode compact protein domains suggesting that mRNA structure controls protein folding. This function is apparently performed by distinct structural elements in the mRNA, which implies 'fine tuning' of mRNA structure under selection for optimal protein folding. We find that, during evolution, changes in the mRNA folding energy follow amino acid replacements, reinforcing the notion of an intimate connection between the structures of a mRNA and the protein it encodes, and the double encoding of protein sequence and folding in the mRNA.

BrisSynBio: a BBSRC/EPSRC-funded Synthetic Biology Research Centre

BrisSynBio is the Bristol-based Biotechnology and Biological Sciences Research Council (BBSRC)/Engineering and Physical Sciences Research Council (EPSRC)-funded Synthetic Biology Research Centre. It is one of six such Centres in the U.K. BrisSynBio's emphasis is on rational and predictive bimolecular modelling, design and engineering in the context of synthetic biology. It trains the next generation of synthetic biologists in these approaches, to facilitate translation of fundamental synthetic biology research to industry and the clinic, and to do this within an innovative and responsible research framework.

Ribosome profiling and dynamic regulation of translation in mammals

Protein synthesis is an energy-demanding cellular process. Consequently, a well-timed, fine-tuned and plastic regulation of translation is needed to adjust and maintain cell states under dynamically changing environments. Genome-wide monitoring of translation was recently facilitated by ribosome profiling, which uncovered key features of translation regulation. In this review, we summarize recent ribosome profiling studies in mammals providing novel insight in dynamic translation regulation, notably related to circadian rhythms, diurnal feeding/fasting cycles, cell cycle progression, stress responses, and tRNA landscapes. In particular, recent results show that regulating translation initiation and elongation represent important mechanisms used in mammalian cells to rapidly modulate protein expression in dynamically changing environments.

Making life difficult for Clostridium difficile: augmenting the pathogen's metabolic model with transcriptomic and codon usage data for better therapeutic target characterization

BACKGROUND

Clostridium difficile is a bacterium which can infect various animal species, including humans. Infection with this bacterium is a leading healthcare-associated illness. A better understanding of this organism and the relationship between its genotype and phenotype is essential to the search for an effective treatment. Genome-scale metabolic models contain all known biochemical reactions of a microorganism and can be used to investigate this relationship.

RESULTS

We present icdf834, an updated metabolic network of C. difficile that builds on iMLTC806cdf and features 1227 reactions, 834 genes, and 807 metabolites. We used this metabolic network to reconstruct the metabolic landscape of this bacterium. The standard metabolic model cannot account for changes in the bacterial metabolism in response to different environmental conditions. To account for this limitation, we also integrated transcriptomic data, which details the gene expression of the bacterium in a wide array of environments. Importantly, to bridge the gap between gene expression levels and protein abundance, we accounted for the synonymous codon usage bias of the bacterium in the model. To our knowledge, this is the first time codon usage has been quantified and integrated into a metabolic model. The metabolic fluxes were defined as a function of protein abundance. To determine potential therapeutic targets using the model, we conducted gene essentiality and metabolic pathway sensitivity analyses and calculated flux control coefficients. We obtained 92.3% accuracy in predicting gene essentiality when compared to experimental data for C. difficile R20291 (ribotype 027) homologs. We validated our context-specific metabolic models using sensitivity and robustness analyses and compared model predictions with literature on C. difficile. The model predicts interesting facets of the bacterium's metabolism, such as changes in the bacterium's growth in response to different environmental conditions.

CONCLUSIONS

After an extensive validation process, we used icdf834 to obtain state-of-the-art predictions of therapeutic targets for C. difficile. We show how context-specific metabolic models augmented with codon usage information can be a beneficial resource for better understanding C. difficile and for identifying novel therapeutic targets. We remark that our approach can be applied to investigate and treat against other pathogens.

An expanded genetic code for probing the role of electrostatics in enzyme catalysis by vibrational Stark spectroscopy

BACKGROUND

To find experimental validation for electrostatic interactions essential for catalytic reactions represents a challenge due to practical limitations in assessing electric fields within protein structures.

SCOPE OF REVIEW

This review examines the applications of non-canonical amino acids (ncAAs) as genetically encoded probes for studying the role of electrostatic interactions in enzyme catalysis.

MAJOR CONCLUSIONS

ncAAs constitute sensitive spectroscopic probes to detect local electric fields by exploiting the vibrational Stark effect (VSE) and thus have the potential to map the protein electrostatics.

GENERAL SIGNIFICANCE

Mapping the electrostatics in proteins will improve our understanding of natural catalytic processes and, in beyond, will be helpful for biocatalyst engineering. This article is part of a Special Issue entitled "Biochemistry of Synthetic Biology - Recent Developments" Guest Editor: Dr. Ilka Heinemann and Dr. Patrick O'Donoghue.

RPLP1 and RPLP2 Are Essential Flavivirus Host Factors That Promote Early Viral Protein Accumulation

The Flavivirus genus contains several arthropod-borne viruses that pose global health threats, including dengue viruses (DENV), yellow fever virus (YFV), and Zika virus (ZIKV). In order to understand how these viruses replicate in human cells, we previously conducted genome-scale RNA interference screens to identify candidate host factors. In these screens, we identified ribosomal proteins RPLP1 and RPLP2 (RPLP1/2) to be among the most crucial putative host factors required for DENV and YFV infection. RPLP1/2 are phosphoproteins that bind the ribosome through interaction with another ribosomal protein, RPLP0, to form a structure termed the ribosomal stalk. RPLP1/2 were validated as essential host factors for DENV, YFV, and ZIKV infection in two human cell lines: A549 lung adenocarcinoma and HuH-7 hepatoma cells, and for productive DENV infection of Aedes aegypti mosquitoes. Depletion of RPLP1/2 caused moderate cell-line-specific effects on global protein synthesis, as determined by metabolic labeling. In A549 cells, global translation was increased, while in HuH-7 cells it was reduced, albeit both of these effects were modest. In contrast, RPLP1/2 knockdown strongly reduced early DENV protein accumulation, suggesting a requirement for RPLP1/2 in viral translation. Furthermore, knockdown of RPLP1/2 reduced levels of DENV structural proteins expressed from an exogenous transgene. We postulate that these ribosomal proteins are required for efficient translation elongation through the viral open reading frame. In summary, this work identifies RPLP1/2 as critical flaviviral host factors required for translation.

IMPORTANCE

Flaviviruses cause important diseases in humans. Examples of mosquito-transmitted flaviviruses include dengue, yellow fever and Zika viruses. Viruses require a plethora of cellular factors to infect cells, and the ribosome plays an essential role in all viral infections. The ribosome is a complex macromolecular machine composed of RNA and proteins and it is responsible for protein synthesis. We identified two specific ribosomal proteins that are strictly required for flavivirus infection of human cells and mosquitoes: RPLP1 and RPLP2 (RPLP1/2). These proteins are part of a structure known as the ribosomal stalk and help orchestrate the elongation phase of translation. We show that flaviviruses are particularly dependent on the function of RPLP1/2. Our findings suggest that ribosome composition is an important factor for virus translation and may represent a regulatory layer for translation of specific cellular mRNAs.

Genome-Wide Analysis of RNA Secondary Structure

Single-stranded RNA molecules fold into extraordinarily complicated secondary and tertiary structures as a result of intramolecular base pairing. In vivo, these RNA structures are not static. Instead, they are remodeled in response to changes in the prevailing physicochemical environment of the cell and as a result of intermolecular base pairing and interactions with RNA-binding proteins. Remarkable technical advances now allow us to probe RNA secondary structure at single-nucleotide resolution and genome-wide, both in vitro and in vivo. These data sets provide new glimpses into the RNA universe. Analyses of RNA structuromes in HIV, yeast, Arabidopsis, and mammalian cells and tissues have revealed regulatory effects of RNA structure on messenger RNA (mRNA) polyadenylation, splicing, translation, and turnover. Application of new methods for genome-wide identification of mRNA modifications, particularly methylation and pseudouridylation, has shown that the RNA "epitranscriptome" both influences and is influenced by RNA structure. In this review, we describe newly developed genome-wide RNA structure-probing methods and synthesize the information emerging from their application.

Xenomicrobiology: a roadmap for genetic code engineering

Biology is an analytical and informational science that is becoming increasingly dependent on chemical synthesis. One example is the high‐throughput and low‐cost synthesis of DNA, which is a foundation for the research field of synthetic biology (SB). The aim of SB is to provide biotechnological solutions to health, energy and environmental issues as well as unsustainable manufacturing processes in the frame of naturally existing chemical building blocks. Xenobiology (XB) goes a step further by implementing non‐natural building blocks in living cells. In this context, genetic code engineering respectively enables the re‐design of genes/genomes and proteins/proteomes with non‐canonical nucleic (XNAs) and amino (ncAAs) acids. Besides studying information flow and evolutionary innovation in living systems, XB allows the development of new‐to‐nature therapeutic proteins/peptides, new biocatalysts for potential applications in synthetic organic chemistry and biocontainment strategies for enhanced biosafety. In this perspective, we provide a brief history and evolution of the genetic code in the context of XB. We then discuss the latest efforts and challenges ahead for engineering the genetic code with focus on substitutions and additions of ncAAs as well as standard amino acid reductions. Finally, we present a roadmap for the directed evolution of artificial microbes for emancipating rare sense codons that could be used to introduce novel building blocks. The development of such xenomicroorganisms endowed with a ‘genetic firewall’ will also allow to study and understand the relation between code evolution and horizontal gene transfer.

Deep sequencing reveals global patterns of mRNA recruitment during translation initiation

In this work, we developed a method to systematically study the sequence preference of mRNAs during translation initiation. Traditionally, the dynamic process of translation initiation has been studied at the single molecule level with limited sequencing possibility. Using deep sequencing techniques, we identified the sequence preference at different stages of the initiation complexes. Our results provide a comprehensive and dynamic view of the initiation elements in the translation initiation region (TIR), including the S1 binding sequence, the Shine-Dalgarno (SD)/anti-SD interaction and the second codon, at the equilibrium of different initiation complexes. Moreover, our experiments reveal the conformational changes and regional dynamics throughout the dynamic process of mRNA recruitment.

Role of mRNA structure in the control of protein folding

Specific structures in mRNA modulate translation rate and thus can affect protein folding. Using the protein structures from two eukaryotes and three prokaryotes, we explore the connections between the protein compactness, inferred from solvent accessibility, and mRNA structure, inferred from mRNA folding energy (ΔG). In both prokaryotes and eukaryotes, the ΔG value of the most stable 30 nucleotide segment of the mRNA (ΔGmin) strongly, positively correlates with protein solvent accessibility. Thus, mRNAs containing exceptionally stable secondary structure elements typically encode compact proteins. The correlations between ΔG and protein compactness are much more pronounced in predicted ordered parts of proteins compared to the predicted disordered parts, indicative of an important role of mRNA secondary structure elements in the control of protein folding. Additionally, ΔG correlates with the mRNA length and the evolutionary rate of synonymous positions. The correlations are partially independent and were used to construct multiple regression models which explain about half of the variance of protein solvent accessibility. These findings suggest a model in which the mRNA structure, particularly exceptionally stable RNA structural elements, act as gauges of protein co-translational folding by reducing ribosome speed when the nascent peptide needs time to form and optimize the core structure.

A Minimal Model of Ribosome Allocation Dynamics Captures Trade-offs in Expression between Endogenous and Synthetic Genes

Cells contain a finite set of resources that must be distributed across many processes to ensure survival. Among them, the largest proportion of cellular resources is dedicated to protein translation. Synthetic biology often exploits these resources in executing orthogonal genetic circuits, yet the burden this places on the cell is rarely considered. Here, we develop a minimal model of ribosome allocation dynamics capturing the demands on translation when expressing a synthetic construct together with endogenous genes required for the maintenance of cell physiology. Critically, it contains three key variables related to design parameters of the synthetic construct covering transcript abundance, translation initiation rate, and elongation time. We show that model-predicted changes in ribosome allocation closely match experimental shifts in synthetic protein expression rate and cellular growth. Intriguingly, the model is also able to accurately infer transcript levels and translation times after further exposure to additional ambient stress. Our results demonstrate that a simple model of resource allocation faithfully captures the redistribution of protein synthesis resources when faced with the burden of synthetic gene expression and environmental stress. The tractable nature of the model makes it a versatile tool for exploring the guiding principles of efficient heterologous expression and the indirect interactions that can arise between synthetic circuits and their host chassis because of competition for shared translational resources.

Identification of the mRNA targets of tRNA-specific regulation using genome-wide simulation of translation

tRNA gene copy number is a primary determinant of tRNA abundance and therefore the rate at which each tRNA delivers amino acids to the ribosome during translation. Low-abundance tRNAs decode rare codons slowly, but it is unclear which genes might be subject to tRNA-mediated regulation of expression. Here, those mRNA targets were identified via global simulation of translation. In-silico mRNA translation rates were compared for each mRNA in both wild-type and a \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${\rm{tRNA}}_{{\rm{CUG}}}^{{\rm{Gln}}}$\end{document}sup70-65 mutant, which exhibits a pseudohyphal growth phenotype and a 75% slower CAG codon translation rate. Of 4900 CAG-containing mRNAs, 300 showed significantly reduced in silico translation rates in a simulated tRNA mutant. Quantitative immunoassay confirmed that the reduced translation rates of sensitive mRNAs were \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${\rm{tRNA}}_{{\rm{CUG}}}^{{\rm{Gln}}}$\end{document} concentration-dependent. Translation simulations showed that reduced \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${\rm{tRNA}}_{{\rm{CUG}}}^{{\rm{Gln}}}$\end{document} concentrations triggered ribosome queues, which dissipated at reduced translation initiation rates. To validate this prediction experimentally, constitutive gcn2 kinase mutants were used to reduce in vivo translation initiation rates. This repaired the relative translational rate defect of target mRNAs in the sup70-65 background, and ameliorated sup70-65 pseudohyphal growth phenotypes. We thus validate global simulation of translation as a new tool to identify mRNA targets of tRNA-specific gene regulation.

The Frequency of Internal Shine-Dalgarno-like Motifs in Prokaryotes

In prokaryotes, translation initiation typically depends on complementary binding between a G-rich Shine–Dalgarno (SD) motif in the 5′ untranslated region of mRNAs, and the 3′ tail of the 16S ribosomal RNA (the anti-SD sequence). In some cases, internal SD-like motifs in the coding region generate “programmed” ribosomal pauses that are beneficial for protein folding or accurate targeting. On the other hand, such pauses can also reduce protein production, generating purifying selection against internal SD-like motifs. This selection should be stronger in GC-rich genomes that are more likely to harbor the G-rich SD motif. However, the nature and consequences of selection acting on internal SD-like motifs within genomes and across species remains unclear. We analyzed the frequency of SD-like hexamers in the coding regions of 284 prokaryotes (277 with known anti-SD sequences and 7 without a typical SD mechanism). After accounting for GC content, we found that internal SD-like hexamers are avoided in 230 species, including three without a typical SD mechanism. The degree of avoidance was higher in GC-rich genomes, mesophiles, and N-terminal regions of genes. In contrast, 54 species either showed no signature of avoidance or were enriched in internal SD-like motifs. C-terminal gene regions were relatively enriched in SD-like hexamers, particularly for genes in operons or those followed closely by downstream genes. Together, our results suggest that the frequency of internal SD-like hexamers is governed by multiple factors including GC content and genome organization, and further empirical work is necessary to understand the evolution and functional roles of these motifs.

The ribosome in action: Tuning of translational efficiency and protein folding

The cellular proteome is shaped by the combined activities of the gene expression and quality control machineries. While transcription plays an undoubtedly important role, in recent years also translation emerged as a key step that defines the composition and quality of the proteome and the functional activity of proteins in the cell. Among the different post-transcriptional control mechanisms, translation initiation and elongation provide multiple checkpoints that can affect translational efficiency. A multitude of specific signals in mRNAs can determine the frequency of translation initiation, choice of the open reading frame, global and local elongation velocities, and the folding of the emerging protein. In addition to specific signatures in the mRNAs, also variations in the global pools of translation components, including ribosomes, tRNAs, mRNAs, and translation factors can alter translational efficiencies. The cellular outcomes of phenomena such as mRNA codon bias are sometimes difficult to understand due to the staggering complexity of covariates that affect codon usage, translation, and protein folding. Here we summarize the experimental evidence on how the ribosome-together with the other components of the translational machinery-can alter translational efficiencies of mRNA at the initiation and elongation stages and how translation velocity affects protein folding. We seek to explain these findings in the context of mechanistic work on the ribosome. The results argue in favour of a new understanding of translation control as a hub that links mRNA homeostasis to production and quality control of proteins in the cell.

Silent Polymorphisms: Can the tRNA Population Explain Changes in Protein Properties?

Silent mutations are being intensively studied. We previously showed that the estrogen receptor alpha Ala87’s synonymous polymorphism affects its functional properties. Whereas a link has been clearly established between the effect of silent mutations, tRNA abundance and protein folding in prokaryotes, this connection remains controversial in eukaryotic systems. Although a synonymous polymorphism can affect mRNA structure or the interaction with specific ligands, it seems that the relative frequencies of isoacceptor tRNAs could play a key role in the protein-folding process, possibly through modulation of translation kinetics. Conformational changes could be subtle but enough to cause alterations in solubility, proteolysis profiles, functional parameters or intracellular targeting. Interestingly, recent advances describe dramatic changes in the tRNA population associated with proliferation, differentiation or response to chemical, physical or biological stress. In addition, several reports reveal changes in tRNAs’ posttranscriptional modifications in different physiological or pathological conditions. In consequence, since changes in the cell state imply quantitative and/or qualitative changes in the tRNA pool, they could increase the likelihood of protein conformational variants, related to a particular codon usage during translation, with consequences of diverse significance. These observations emphasize the importance of genetic code flexibility in the co-translational protein-folding process.

Secondary Structure across the Bacterial Transcriptome Reveals Versatile Roles in mRNA Regulation and Function

Messenger RNA acts as an informational molecule between DNA and translating ribosomes. Emerging evidence places mRNA in central cellular processes beyond its major function as informational entity. Although individual examples show that specific structural features of mRNA regulate translation and transcript stability, their role and function throughout the bacterial transcriptome remains unknown. Combining three sequencing approaches to provide a high resolution view of global mRNA secondary structure, translation efficiency and mRNA abundance, we unraveled structural features in E. coli mRNA with implications in translation and mRNA degradation. A poorly structured site upstream of the coding sequence serves as an additional unspecific binding site of the ribosomes and the degree of its secondary structure propensity negatively correlates with gene expression. Secondary structures within coding sequences are highly dynamic and influence translation only within a very small subset of positions. A secondary structure upstream of the stop codon is enriched in genes terminated by UAA codon with likely implications in translation termination. The global analysis further substantiates a common recognition signature of RNase E to initiate endonucleolytic cleavage. This work determines for the first time the E. coli RNA structurome, highlighting the contribution of mRNA secondary structure as a direct effector of a variety of processes, including translation and mRNA degradation.

A particular silent codon exchange in a recombinant gene greatly influences host cell metabolic activity

BACKGROUND

Recombinant protein production using Escherichia coli as expression host is highly efficient, however, it also induces strong host cell metabolic burden. Energy and biomass precursors are withdrawn from the host's metabolism as they are required for plasmid replication, heterologous gene expression and protein production. Rare codons in a heterologous gene may be a further drawback. This study aims to investigate the influence of particular silent codon exchanges within a heterologous gene on host cell metabolic activity. Silent mutations were introduced into the coding sequence of a model protein to introduce all synonymous arginine or leucine codons at two randomly defined positions, as well as substitutions leading to identical amino acid exchanges with different synonymous codons. The respective E. coli clones were compared during cultivation in a mineral autoinduction medium using specialized online and offline measuring techniques to quantitatively analyze effects on respiration, biomass and protein production, as well as on carbon source consumption, plasmid copy number, intracellular nucleobases and mRNA content of each clone.

RESULTS

Host stain metabolic burden correlates with recombinant protein production. Upon heterologous gene expression, tremendous differences in respiration, biomass and protein production were observed. According to their different respiration activity the E. coli clones could be classified into two groups, Type A and Type B. Type A clones tended to higher product formation, Type B clones showed stronger biomass formation. Whereas codon usage and intracellular nucleobases had no influence on the Type-A-Type-B-behavior, plasmid copy number, mRNA content and carbon source consumption strongly differed between the two groups.

CONCLUSIONS

Particular silent codon exchanges in a heterologous gene sequence led to differences in initial growth of Type A and Type B clones. Thus, the biomass concentration at the time point of induction varied. In consequence, not only plasmid copy number and expression levels differed between the two groups, but also the kinetics of lactose and glycerol consumption. Even though the underlying molecular mechanisms are not yet identified we observed the astonishing phenomenon that particular silent codon exchanges within a heterologous gene tremendously affect host cell metabolism and recombinant protein production. This could have great impact on codon optimization of heterologous genes, screening procedures for improved variants, and biotechnological protein production processes.