Beyond the Triplet Code: Context Cues Transform Translation

Dbp1 is a low performance paralog of RNA helicase Ded1 that drives impaired translation and heat stress response

Ded1 and Dbp1 are paralogous conserved RNA helicases that enable translation initiation in yeast. Ded1 has been heavily studied but the role of Dbp1 is poorly understood. We find that the expression of these two helicases is controlled in an inverse and condition-specific manner. In meiosis and other long-term starvation states, Dbp1 expression is upregulated and Ded1 is downregulated, whereas in mitotic cells, Dbp1 expression is extremely low. Inserting the DBP1 ORF in place of the DED1 ORF cannot replace the function of Ded1 in supporting translation, partly due to inefficient mitotic translation of the DBP1 mRNA, dependent on features of its ORF sequence but independent of codon optimality. Global measurements of translation rates and 5' leader translation, activity of mRNA-tethered helicases, ribosome association, and low temperature growth assays show that-even at matched protein levels-Ded1 is more effective than Dbp1 at activating translation, especially for mRNAs with structured 5' leaders. Ded1 supports halting of translation and cell growth in response to heat stress, but Dbp1 lacks this function, as well. These functional differences in the ability to efficiently mediate translation activation and braking can be ascribed to the divergent, disordered N- and C-terminal regions of these two helicases. Altogether, our data show that Dbp1 is a "low performance" version of Ded1 that cells employ in place of Ded1 under long-term conditions of nutrient deficiency.

A unifying network modeling approach for codon optimization

MOTIVATION

Synthesizing genes to be expressed in other organisms is an essential tool in biotechnology. While the many-to-one mapping from codons to amino acids makes the genetic code degenerate, codon usage in a particular organism is not random either. This bias in codon use may have a remarkable effect on the level of gene expression. A number of measures have been developed to quantify a given codon sequence's strength to express a gene in a host organism. Codon optimization aims to find a codon sequence that will optimize one or more of these measures. Efficient computational approaches are needed since the possible number of codon sequences grows exponentially as the number of amino acids increases.

RESULTS

We develop a unifying modeling approach for codon optimization. With our mathematical formulations based on graph/network representations of amino acid sequences, any combination of measures can be optimized in the same framework by finding a path satisfying additional limitations in an acyclic layered network. We tested our approach on bi-objectives commonly used in the literature, namely, Codon Pair Bias versus Codon Adaptation Index and Relative Codon Pair Bias versus Relative Codon Bias. However, our framework is general enough to handle any number of objectives concurrently with certain restrictions or preferences on the use of specific nucleotide sequences. We implemented our models using Python's Gurobi interface and showed the efficacy of our approach even for the largest proteins available. We also provided experimentation showing that highly expressed genes have objective values close to the optimized values in the bi-objective codon design problem.

AVAILABILITY AND IMPLEMENTATION

http://alpersen.bilkent.edu.tr/NetworkCodon.zip.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Recognition of 3' nucleotide context and stop codon readthrough are determined during mRNA translation elongation

The nucleotide context surrounding stop codons significantly affects the efficiency of translation termination. In eukaryotes, various 3′ contexts that are unfavorable for translation termination have been described; however, the exact molecular mechanism that mediates their effects remains unknown. In this study, we used a reconstituted mammalian translation system to examine the efficiency of stop codons in different contexts, including several previously described weak 3′ stop codon contexts. We developed an approach to estimate the level of stop codon readthrough in the absence of eukaryotic release factors (eRFs). In this system, the stop codon is recognized by the suppressor or near-cognate tRNAs. We observed that in the absence of eRFs, readthrough occurs in a 3′ nucleotide context-dependent manner, and the main factors determining readthrough efficiency were the type of stop codon and the sequence of the 3′ nucleotides. Moreover, the efficiency of translation termination in weak 3′ contexts was almost equal to that in the tested standard context. Therefore, the ability of eRFs to recognize stop codons and induce peptide release is not affected by mRNA context. We propose that ribosomes or other participants of the elongation cycle can independently recognize certain contexts and increase the readthrough of stop codons. Thus, the efficiency of translation termination is regulated by the 3′ nucleotide context following the stop codon and depends on the concentrations of eRFs and suppressor/near-cognate tRNAs.

Altering Compositional Properties of Viral Genomes to Design Live-Attenuated Vaccines

Live-attenuated vaccines have been historically used to successfully prevent numerous diseases caused by a broad variety of RNA viruses due to their ability to elicit strong and perdurable immune-protective responses. In recent years, various strategies have been explored to achieve viral attenuation by rational genetic design rather than using classic and empirical approaches, based on successive passages in cell culture. A deeper understanding of evolutionary implications of distinct viral genomic compositional aspects, as well as substantial advances in synthetic biology technologies, have provided a framework to achieve new viral attenuation strategies. Herein, we will discuss different approaches that are currently applied to modify compositional features of viruses in order to develop novel live-attenuated vaccines.

Refinement of the clinical variant interpretation framework by statistical evidence and machine learning

BACKGROUND

Although the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) guidelines for variant interpretation are used widely in clinical genetics, there is room for improvement of these knowledge-based guidelines.

METHODS

Statistical assessment of average deleteriousness of start-lost, stop-lost, and in-frame insertion and deletion (indel) variants and extraction of deleterious subsets was performed, being informed by proportions of rare variants in the general population of the Genome Aggregation Database (gnomAD). A machine learning-based model scoring the pathogenicity of start-lost variants (the PoStaL model) was constructed by predicting possible translation initiation sites on transcripts by deep learning and training a random forest on known pathogenic and likely benign variants.

FINDINGS

The proportion of rare variants was highest in stop-lost variants, followed by in-frame indels and start-lost variants, suggesting that the criteria in the ACMG/AMP guidelines assigning PVS (pathogenic very strong) to start-lost variants and PM (pathogenic moderate) to stop-lost and in-frame indel variants would not be appropriate. Regarding deleterious subsets, stop-lost variants introducing extensions of more than 30 amino acids and in-frame indels computationally predicted to be damaging are enriched for rare and known pathogenic variants. For start-lost variants, we developed the PoStaL model, which outperforms existing tools. We also provide comprehensive lists of the PoStaL scores for start-lost variants and the length of extended amino acids by stop-lost variants.

CONCLUSIONS

Our study could contribute to refinement of the ACMG/AMP guidelines, provides resources for future investigation, and provides an example of how to improve knowledge-based frameworks by data-driven approaches.

FUNDING

The study was supported by grants from the Japan Agency for Medical Research and Development (AMED) and the Japan Society for the Promotion of Science (JSPS).

Full-length ribosome density prediction by a multi-input and multi-output model

Translation elongation is regulated by a series of complicated mechanisms in both prokaryotes and eukaryotes. Although recent advance in ribosome profiling techniques has enabled one to capture the genome-wide ribosome footprints along transcripts at codon resolution, the regulatory codes of elongation dynamics are still not fully understood. Most of the existing computational approaches for modeling translation elongation from ribosome profiling data mainly focus on local contextual patterns, while ignoring the continuity of the elongation process and relations between ribosome densities of remote codons. Modeling the translation elongation process in full-length coding sequence (CDS) level has not been studied to the best of our knowledge. In this paper, we developed a deep learning based approach with a multi-input and multi-output framework, named RiboMIMO, for modeling the ribosome density distributions of full-length mRNA CDS regions. Through considering the underlying correlations in translation efficiency among neighboring and remote codons and extracting hidden features from the input full-length coding sequence, RiboMIMO can greatly outperform the state-of-the-art baseline approaches and accurately predict the ribosome density distributions along the whole mRNA CDS regions. In addition, RiboMIMO explores the contributions of individual input codons to the predictions of output ribosome densities, which thus can help reveal important biological factors influencing the translation elongation process. The analyses, based on our interpretable metric named codon impact score, not only identified several patterns consistent with the previously-published literatures, but also for the first time (to the best of our knowledge) revealed that the codons located at a long distance from the ribosomal A site may also have an association on the translation elongation rate. This finding of long-range impact on translation elongation velocity may shed new light on the regulatory mechanisms of protein synthesis. Overall, these results indicated that RiboMIMO can provide a useful tool for studying the regulation of translation elongation in the range of full-length CDS.

Translation elongation is a process in which amino acids are linked into proteins by ribosomes in cells. Translation elongation rates along the mRNAs are not constant, and are regulated by a series of mechanisms, such as codon rarity and mRNA stability. In this study, we modeled the translation elongation process at a full-length coding sequence level and developed a deep learning based approach to predict the translation elongation rates from mRNA sequences, through extracting the regulatory codes of elongation rates from the contextual sequences. The analyses, based on our interpretable metric named codon impact score, for the first time (to the best of our knowledge), revealed that in addition to the neighboring codons of the ribosomal A sites, the remote codons may also have an important impact on the translation elongation rates. This new finding may stimulate additional experiments and shed light on the regulatory mechanisms of protein synthesis.

OTTER, a new method quantifying absolute amounts of tRNAs

To maintain optimal proteome, both codon choice of each mRNA and supply of aminoacyl-tRNAs are two principal factors in translation. Recent reports have revealed that the amounts of tRNAs in cells are more dynamic than we had expected. High-throughput methods such as RNA-Seq and microarrays are versatile for comprehensive detection of changes in individual tRNA amounts, but they suffer from inability to assess signal production efficiencies of individual tRNA species. Thus, they are not the perfect choice to measure absolute amounts of tRNAs. Here, we introduce a novel method for this purpose, termed Oligonucleotide-directed Three-prime Terminal Extension of RNA (OTTER), which employs fluorescence-labeling at the 3'-terminus of a tRNA by optimized reverse primer extension and an assessment step of each labeling efficiency by northern blotting. Using this method, we quantified the absolute amounts of the 34 individual and 4 pairs of isoacceptor tRNAs out of the total 42 nuclear-encoded isoacceptors in the yeast Saccharomyces cerevisiae. We found that the amounts of tRNAs in log phase yeast cells grown in a rich glucose medium range from 0.030 to 0.73 pmol/µg RNA. The tRNA amounts seem to be altered at the isoacceptor level by a few folds in response to physiological growing conditions. The data obtained by OTTER are poorly correlated with those by simple RNA-Seq, marginally with those by microarrays and by microscale thermophoresis. However, the OTTER data showed good agreement with the data obtained by 2D-gel analysis of in vivo radiolabeled RNAs. Thus, OTTER is a suitable method for quantifying absolute amounts of tRNAs at the level of isoacceptor resolution.

Potential role of the X circular code in the regulation of gene expression

The X circular code is a set of 20 trinucleotides (codons) that has been identified in the protein-coding genes of most organisms (bacteria, archaea, eukaryotes, plasmids, viruses). It has been shown previously that the X circular code has the important mathematical property of being an error-correcting code. Thus, motifs of the X circular code, i.e. a series of codons belonging to X and called X motifs, allow identification and maintenance of the reading frame in genes. X motifs are significantly enriched in protein-coding genes, but have also been identified in many transfer RNA (tRNA) genes and in important functional regions of the ribosomal RNA (rRNA), notably in the peptidyl transferase center and the decoding center. Here, we investigate the potential role of X motifs as functional elements of protein-coding genes. First, we identify the codons of the X circular code which are frequent or rare in each domain of life (archaea, bacteria, eukaryota) and show that, for the amino acids with the highest codon bias, the preferred codon is often an X codon. We also observe a correlation between the 20 X codons and the optimal codons/dicodons that have been shown to influence translation efficiency. Then, we examined recently published experimental results concerning gene expression levels in diverse organisms. The approach used is the analysis of X motifs according to their density d_s(X), i.e. the number of X motifs per kilobase in a gene sequence s. Surprisingly, this simple parameter identifies several unexpected relations between the X circular code and gene expression. For example, the X motifs are significantly enriched in the minimal gene set belonging to the three domains of life, and in codon-optimized genes. Furthermore, the density of X motifs generally correlates with experimental measures of translation efficiency and mRNA stability. Taken together, these results lead us to propose that the X motifs may represent a genetic signal contributing to the maintenance of the correct reading frame and the optimization and regulation of gene expression.

Riboexp: an interpretable reinforcement learning framework for ribosome density modeling

Translation elongation is a crucial phase during protein biosynthesis. In this study, we develop a novel deep reinforcement learning-based framework, named Riboexp, to model the determinants of the uneven distribution of ribosomes on mRNA transcripts during translation elongation. In particular, our model employs a policy network to perform a context-dependent feature selection in the setting of ribosome density prediction. Our extensive tests demonstrated that Riboexp can significantly outperform the state-of-the-art methods in predicting ribosome density by up to 5.9% in terms of per-gene Pearson correlation coefficient on the datasets from three species. In addition, Riboexp can indicate more informative sequence features for the prediction task than other commonly used attribution methods in deep learning. In-depth analyses also revealed the meaningful biological insights generated by the Riboexp framework. Moreover, the application of Riboexp in codon optimization resulted in an increase of protein production by around 31% over the previous state-of-the-art method that models ribosome density. These results have established Riboexp as a powerful and useful computational tool in the studies of translation dynamics and protein synthesis. Availability: The data and code of this study are available on GitHub: https://github.com/Liuxg16/Riboexp. Contact:  zengjy321@tsinghua.edu.cn; songsen@tsinghua.edu.cn.

Termi-Luc: a versatile assay to monitor full-protein release from ribosomes

Termination of protein biosynthesis is an essential step of gene expression, during which a complete functional protein is released from the ribosome. Premature or inefficient termination results in truncated, nonfunctional, or toxic proteins that may cause disease. Indeed, more than 10% of human genetic diseases are caused by nonsense mutations leading to premature termination. Efficient and sensitive approaches are required to study eukaryotic termination mechanisms and to identify potential therapeutics that modulate termination. Canonical radioactivity-based termination assays are complex, report on a short peptide release, and are incompatible with high-throughput screening. Here we describe a robust and simple in vitro assay to study the kinetics of full-protein release. The assay monitors luminescence upon release of nanoluciferase from a mammalian pretermination complex. The assay can be used to record time-progress curves of protein release in a high-throughput format, making it optimal for studying release kinetics and for high-throughput screening for small molecules that modulate the efficiency of termination.

Universal Single-Residue Terminal Labels for Fluorescent Live Cell Imaging of Microproteins

Genetically encoded fluorescent tags for visualization of proteins in living cells add six to several hundred amino acids to the protein of interest. While suitable for most proteins, common tags easily match and exceed the size of microproteins of 60 amino acids or less. The added molecular weight and structure of such fluorescent tag may thus significantly affect in vivo biophysical and biochemical properties of microproteins. Here, we develop single-residue terminal labeling (STELLA) tags that introduce a single noncanonical amino acid either at the N- or C-terminus of a protein or microprotein of interest for subsequent specific fluorescent labeling. Efficient terminal noncanonical amino acid mutagenesis is achieved using a precursor tag that is tracelessly cleaved. Subsequent selective bioorthogonal reaction with a cell-permeable organic dye enables live cell imaging of microproteins with minimal perturbation of their native sequence. The use of terminal residues for labeling provides a universally applicable and easily scalable strategy, which avoids alteration of the core sequence of the microprotein.

Non-AUG Translation Initiation Generates Peroxisomal Isoforms of 6-Phosphogluconate Dehydrogenase in Fungi

Proteins destined for transport to specific organelles usually contain targeting information, which are embedded in their sequence. Many enzymes are required in more than one cellular compartment and different molecular mechanisms are used to achieve dual localization. Here we report a cryptic type 2 peroxisomal targeting signal encoded in the 5′ untranslated region of fungal genes coding for 6-phosphogluconate dehydrogenase (PGD), a key enzyme of the oxidative pentose phosphate pathway. The conservation of the cryptic PTS2 motif suggests a biological function. We observed that translation from a non-AUG start codon generates an N-terminally extended peroxisomal isoform of Ustilago maydis PGD. Non-canonical initiation occurred at the sequence AGG AUU, consisting of two near-cognate start codons in tandem. Taken together, our data reveal non-AUG translation initiation as an additional mechanism to achieve the dual localization of a protein required both in the cytosol and the peroxisomes.

Proteomic and interactomic insights into the molecular basis of cell functional diversity

The ability of living systems to adapt to changing conditions originates from their capacity to change their molecular constitution. This is achieved by multiple mechanisms that modulate the quantitative composition and the diversity of the molecular inventory. Molecular diversification is particularly pronounced on the proteome level, at which multiple proteoforms derived from the same gene can in turn combinatorially form different protein complexes, thus expanding the repertoire of functional modules in the cell. The study of molecular and modular diversity and their involvement in responses to changing conditions has only recently become possible through the development of new 'omics'-based screening technologies. This Review explores our current knowledge of the mechanisms regulating functional diversification along the axis of gene expression, with a focus on the proteome and interactome. We explore the interdependence between different molecular levels and how this contributes to functional diversity. Finally, we highlight several recent techniques for studying molecular diversity, with specific focus on mass spectrometry-based analysis of the proteome and its organization into functional modules, and examine future directions for this rapidly growing field.

Quantitative global studies reveal differential translational control by start codon context across the fungal kingdom

Eukaryotic protein synthesis generally initiates at a start codon defined by an AUG and its surrounding Kozak sequence context, but the quantitative importance of this context in different species is unclear. We tested this concept in two pathogenic Cryptococcus yeast species by genome-wide mapping of translation and of mRNA 5' and 3' ends. We observed thousands of AUG-initiated upstream open reading frames (uORFs) that are a major contributor to translation repression. uORF use depends on the Kozak sequence context of its start codon, and uORFs with strong contexts promote nonsense-mediated mRNA decay. Transcript leaders in Cryptococcus and other fungi are substantially longer and more AUG-dense than in Saccharomyces. Numerous Cryptococcus mRNAs encode predicted dual-localized proteins, including many aminoacyl-tRNA synthetases, in which a leaky AUG start codon is followed by a strong Kozak context in-frame AUG, separated by mitochondrial-targeting sequence. Analysis of other fungal species shows that such dual-localization is also predicted to be common in the ascomycete mould, Neurospora crassa. Kozak-controlled regulation is correlated with insertions in translational initiation factors in fidelity-determining regions that contact the initiator tRNA. Thus, start codon context is a signal that quantitatively programs both the expression and the structures of proteins in diverse fungi.

Translational Landscape of Protein-Coding and Non-Protein-Coding RNAs upon Light Exposure in Arabidopsis

Light is one of the most essential environmental clues for plant growth and morphogenesis. Exposure to blue monochromatic light from darkness is a turning point for plant biological activity, and as a result dramatic changes in gene expression occur. To understand the translational impacts of blue light, we have performed ribosome profiling analysis and called translated open reading frames (ORFs) de novo within not only mRNAs but also non-coding RNAs (ncRNAs). Translation efficiency of 3,823 protein-coding ORFs, such as nuclear chloroplast-related genes, was up-regulated by blue light exposure. Moreover, the translational activation of the microRNA biogenesis-related genes, DCL1 and HYL1, was induced by blue light. Considering the 3-nucleotide codon periodicity of ribosome footprints, a few hundred short ORFs lying on ncRNAs and upstream ORFs (uORFs) on mRNAs were found that had differential translation status between blue light and dark. uORFs are known to have a negative effect on the expression of the main ORFs (mORFs) on the same mRNAs. Our analysis suggests that the translation of uORFs is likely to be more stimulated than that of the corresponding mORFs, and uORF-mediated translational repression of the mORFs in five genes was alleviated by blue light exposure. With data-based annotation of the ORFs, our analysis provides insights into the translatome in response to environmental changes, such as those involving light.

Yeast applied readthrough inducing system (YARIS): an invivo assay for the comprehensive study of translational readthrough

Stop codon readthrough—the decoding of a stop codon by a near-cognate tRNA—is employed by viruses to balance levels of enzymatic and structural proteins and by eukaryotic cells to enable isoform-specific protein synthesis in response to external stimuli. Owing to the prevalence of premature termination codons in human disease, readthrough has emerged as an attractive therapeutic target. A growing list of various features, for example the +4 nucleotide immediately following the stop codon, modulate readthrough levels, underscoring the need for systematic investigation of readthrough. Here, we identified and described a complete group of yeast tRNAs that induce readthrough in the stop-codon tetranucleotide manner when overexpressed, designated readthrough-inducing tRNAs (rti-tRNAs). These rti-tRNAs are the keystones of YARIS (yeast applied readthrough inducing system), a reporter-based assay enabling simultaneous detection of readthrough levels at all twelve stop-codon tetranucleotides and as a function of the complete set of rti-tRNAs. We demonstrate the utility of YARIS for systematic study of translation readthrough by employing it to interrogate the effects of natural rti-tRNA modifications, as well as various readthrough-inducing drugs (RTIDs). This analysis identified a variety of genetic interactions demonstrating the power of YARIS to characterize existing and identify novel RTIDs.

Rare-variant pathogenicity triage and inclusion of synonymous variants improves analysis of disease associations of orphan G protein-coupled receptors

The pace of deorphanization of G protein-coupled receptors (GPCRs) has slowed, and new approaches are required. Small molecule targeting of orphan GPCRs can potentially be of clinical benefit even if the endogenous receptor ligand has not been identified. Many GPCRs lack common variants that lead to reproducible genome-wide disease associations, and rare-variant approaches have emerged as a viable alternative to identify disease associations for such genes. Therefore, our goal was to prioritize orphan GPCRs by determining their associations with human diseases in a large clinical population. We used sequence kernel association tests to assess the disease associations of 85 orphan or understudied GPCRs in an unselected cohort of 51,289 individuals. Using rare loss-of-function variants, missense variants predicted to be pathogenic or likely pathogenic, and a subset of rare synonymous variants that cause large changes in local codon bias as independent data sets, we found strong, phenome-wide disease associations shared by two or more variant categories for 39% of the GPCRs. To validate the bioinformatics and sequence kernel association test analyses, we functionally characterized rare missense and synonymous variants of GPR39, a family A GPCR, revealing altered expression or Zn²⁺-mediated signaling for members of both variant classes. These results support the utility of rare variant analyses for identifying disease associations for GPCRs that lack impactful common variants. We highlight the importance of rare synonymous variants in human physiology and argue for their routine inclusion in any comprehensive analysis of genomic variants as potential causes of disease.

Ribosome elongating footprints denoised by wavelet transform comprehensively characterize dynamic cellular translation events

Translation is dynamically regulated during cell development and stress response. In order to detect actively translated open reading frames (ORFs) and dynamic cellular translation events, we have developed a computational method, RiboWave, to process ribosome profiling data. RiboWave utilizes wavelet transform to denoise the original signal by extracting 3-nt periodicity of ribosomes and precisely locate their footprint denoted as Periodic Footprint P-site (PF P-site). Such high-resolution footprint is found to capture the full track of actively elongating ribosomes, from which translational landscape can be explicitly characterized. We compare RiboWave with several published methods, like RiboTaper, ORFscore and RibORF, and found that RiboWave outperforms them in both accuracy and usage when defining actively translated ORFs. Moreover, we show that PF P-site derived by RiboWave shows superior performance in characterizing the dynamics and complexity of cellular translatome by accurately estimating the abundance of protein levels, assessing differential translation and identifying dynamic translation frameshift.

Pathological changes are associated with shifts in the employment of synonymous codons at the transcriptome level

Background

The usage of different synonymous codons reflects the genome organization and has been connected to parameters such as mRNA abundance and protein folding. It is also been established that mutations targeting specific synonymous codons can trigger disease.

Results

We performed a systematic meta-analysis of transcriptome results from 75 datasets representing 40 pathologies. We found that a subset of codons was preferentially employed in abundant transcripts, while other codons were preferentially found in low-abundance transcripts. By comparing control and pathological transcriptomes, we observed a shift in the employment of synonymous codons for every analyzed disease. For example, cancerous tissue employed preferentially A- or U-ending codons, shifting from G- or C-ending codons, which were preferred by control tissues. This analysis was able to discriminate patients and controls with high specificity and sensitivity.

Conclusions

Here we show that the employment of specific synonymous codons, quantified at the whole transcriptome level, changes profoundly in many diseases. We propose that the changes in codon employment offer a novel perspective for disease studies, and could be used to design new diagnostic tools.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5921-9) contains supplementary material, which is available to authorized users.

Translation of upstream open reading frames in a model of neuronal differentiation

Background

Upstream open reading frames (uORFs) initiate translation within mRNA 5′ leaders, and have the potential to alter main coding sequence (CDS) translation on transcripts in which they reside. Ribosome profiling (RP) studies suggest that translating ribosomes are pervasive within 5′ leaders across model systems. However, the significance of this observation remains unclear. To explore a role for uORF usage in a model of neuronal differentiation, we performed RP on undifferentiated and differentiated human neuroblastoma cells.

Results

Using a spectral coherence algorithm (SPECtre), we identify 4954 consistently translated uORFs across 31% of all neuroblastoma transcripts. These uORFs predominantly utilize non-AUG initiation codons and exhibit translational efficiencies (TE) comparable to annotated coding regions. On a population basis, the global impact of both AUG and non-AUG initiated uORFs on basal CDS translation were small, even when analysis is limited to conserved and consistently translated uORFs. However, uORFs did alter the translation of a subset of genes, including the Diamond-Blackfan Anemia associated ribosomal gene RPS24. With retinoic acid induced differentiation, we observed an overall positive correlation in translational shifts between uORF/CDS pairs. However, CDSs downstream of uORFs show smaller shifts in TE with differentiation relative to CDSs without a predicted uORF, suggesting that uORF translation buffers cell state dependent fluctuations in CDS translation.

Conclusion

This work provides insights into the dynamic relationships and potential regulatory functions of uORF/CDS pairs in a model of neuronal differentiation.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5775-1) contains supplementary material, which is available to authorized users.

A chemical kinetic basis for measuring translation initiation and elongation rates from ribosome profiling data

Analysis methods based on simulations and optimization have been previously developed to estimate relative translation rates from next-generation sequencing data. Translation involves molecules and chemical reactions, hence bioinformatics methods consistent with the laws of chemistry and physics are more likely to produce accurate results. Here, we derive simple equations based on chemical kinetic principles to measure the translation-initiation rate, transcriptome-wide elongation rate, and individual codon translation rates from ribosome profiling experiments. Our methods reproduce the known rates from ribosome profiles generated from detailed simulations of translation. By applying our methods to data from S. cerevisiae and mouse embryonic stem cells, we find that the extracted rates reproduce expected correlations with various molecular properties, and we also find that mouse embryonic stem cells have a global translation speed of 5.2 AA/s, in agreement with previous reports that used other approaches. Our analysis further reveals that a codon can exhibit up to 26-fold variability in its translation rate depending upon its context within a transcript. This broad distribution means that the average translation rate of a codon is not representative of the rate at which most instances of that codon are translated, and it suggests that translational regulation might be used by cells to a greater degree than previously thought.

Stable G-quadruplex enabling sequences are selected against by the context-dependent codon bias

The distributions of secondary structural elements appear to differ between coding regions (CDS) of mRNAs compared to the untranslated regions (UTRs), presumably as a mechanism to fine-tune gene expression, including efficiency of translation. However, a systematic and comprehensive analysis of secondary structure avoidance because of potential bias in codon usage is difficult as some of the common secondary structures, such as, hairpins can be formed by numerous sequence combinations. Using G-quadruplex (GQ) as the model secondary structure we studied the impact of codon bias on GQs within the CDS. Because GQs can be predicted using specific consensus sequence motifs, they provide an excellent platform for investigation of the selectivity of such putative structures at the codon level. Using a bioinformatics approach, we calculated the frequencies of putative GQs within the CDS of a variety of species. Our results suggest that the most stable GQs appear to be significantly underrepresented within the CDS, through the use of specific synonymous codon combinations. Furthermore, we identified many peptide sequence motifs in which silent mutations can potentially alter translation via stable GQ formation. This work not only provides a comprehensive analysis on how stable secondary structures appear to be avoided within the CDS of mRNA, but also broadens the current understanding of synonymous codon usage as they relate to the structure-function relationship of RNA.

The Traffic Jam: Polyamine Prevalence Pauses Protein Production

In this issue of Molecular Cell, Ivanov et al. (2018) demonstrate how cells sense metabolite levels and regulate production of their biosynthetic enzymes through the formation of "ribosome queues."

m6A and eIF2α-ⓟ Team Up to Tackle ATF4 Translation during Stress

While m⁶A modification of mRNAs is now known to be widespread, the cellular roles of this modification remain largely mysterious. In this issue of Molecular Cell, Zhou et al. (2018) show that m⁶A modification unexpectedly contributes to the established uORF- and eIF2α-ⓟ-dependent mechanism of ATF4 translational regulation in response to stress.

The codon sequences predict protein lifetimes and other parameters of the protein life cycle in the mouse brain

The homeostasis of the proteome depends on the tight regulation of the mRNA and protein abundances, of the translation rates, and of the protein lifetimes. Results from several studies on prokaryotes or eukaryotic cell cultures have suggested that protein homeostasis is connected to, and perhaps regulated by, the protein and the codon sequences. However, this has been little investigated for mammals in vivo. Moreover, the link between the coding sequences and one critical parameter, the protein lifetime, has remained largely unexplored, both in vivo and in vitro. We tested this in the mouse brain, and found that the percentages of amino acids and codons in the sequences could predict all of the homeostasis parameters with a precision approaching experimental measurements. A key predictive element was the wobble nucleotide. G-/C-ending codons correlated with higher protein lifetimes, protein abundances, mRNA abundances and translation rates than A-/U-ending codons. Modifying the proportions of G-/C-ending codons could tune these parameters in cell cultures, in a proof-of-principle experiment. We suggest that the coding sequences are strongly linked to protein homeostasis in vivo, albeit it still remains to be determined whether this relation is causal in nature.

Dissecting the Contribution of Release Factor Interactions to Amber Stop Codon Reassignment Efficiencies of the Methanocaldococcus jannaschii Orthogonal Pair

Non-canonical amino acids (ncAAs) are finding increasing use in basic biochemical studies and biomedical applications. The efficiency of ncAA incorporation is highly variable, as a result of competing system composition and codon context effects. The relative quantitative contribution of the multiple factors affecting incorporation efficiency are largely unknown. This manuscript describes the use of green fluorescent protein (GFP) reporters to quantify the efficiency of amber codon reassignment using the Methanocaldococcus jannaschii orthogonal pair system, commonly employed for ncAA incorporation, and quantify the contribution of release factor 1 (RF1) to the overall efficiency of amino acid incorporation. The efficiencies of amber codon reassignments were quantified at eight positions in GFP and evaluated in multiple combinations. The quantitative contribution of RF1 competition to reassignment efficiency was evaluated through comparisons of amber codon suppression efficiencies in normal and genomically recoded Escherichia coli strains. Measured amber stop codon reassignment efficiencies for eight single stop codon GFP variants ranged from 51 to 117% in E. coli DH10B and 76 to 104% in the RF1 deleted E. coli C321.ΔA.exp. Evaluation of efficiency changes in specific sequence contexts in the presence and absence of RF1 suggested that RF1 specifically interacts with +4 Cs and that the RF1 interactions contributed approximately half of the observed sequence context-dependent variation in measured reassignment efficiency. Evaluation of multisite suppression efficiencies suggests that increasing demand for translation system components limits multisite incorporation in cells with competing RF1.

Disruption of TWIST1 translation by 5' UTR variants in Saethre-Chotzen syndrome

Saethre-Chotzen syndrome (SCS), one of the most common forms of syndromic craniosynostosis (premature fusion of the cranial sutures), results from haploinsufficiency of TWIST1, caused by deletions of the entire gene or loss-of-function variants within the coding region. To determine whether non-coding variants also contribute to SCS, we screened 14 genetically undiagnosed SCS patients using targeted capture sequencing, and identified novel single nucleotide variants (SNVs) in the 5' untranslated region (UTR) of TWIST1 in two unrelated SCS cases. We show experimentally that these variants, which create translation start sites in the TWIST1 leader sequence, reduce translation from the main open reading frame (mORF). This is the first demonstration that non-coding SNVs of TWIST1 can cause SCS, and highlights the importance of screening the 5' UTR in clinically diagnosed SCS patients without a coding mutation. Similar 5' UTR variants, particularly of haploinsufficient genes, may represent an under-ascertained cause of monogenic disease.

Correcting the F508del-CFTR variant by modulating eukaryotic translation initiation factor 3-mediated translation initiation

Inherited and somatic rare diseases result from >200,000 genetic variants leading to loss- or gain-of-toxic function, often caused by protein misfolding. Many of these misfolded variants fail to properly interact with other proteins. Understanding the link between factors mediating the transcription, translation, and protein folding of these disease-associated variants remains a major challenge in cell biology. Herein, we utilized the cystic fibrosis transmembrane conductance regulator (CFTR) protein as a model and performed a proteomics-based high-throughput screen (HTS) to identify pathways and components affecting the folding and function of the most common cystic fibrosis-associated mutation, the F508del variant of CFTR. Using a shortest-path algorithm we developed, we mapped HTS hits to the CFTR interactome to provide functional context to the targets and identified the eukaryotic translation initiation factor 3a (eIF3a) as a central hub for the biogenesis of CFTR. Of note, siRNA-mediated silencing of eIF3a reduced the polysome-to-monosome ratio in F508del-expressing cells, which, in turn, decreased the translation of CFTR variants, leading to increased CFTR stability, trafficking, and function at the cell surface. This finding suggested that eIF3a is involved in mediating the impact of genetic variations in CFTR on the folding of this protein. We posit that the number of ribosomes on a CFTR mRNA transcript is inversely correlated with the stability of the translated polypeptide. Polysome-based translation challenges the capacity of the proteostasis environment to balance message fidelity with protein folding, leading to disease. We suggest that this deficit can be corrected through control of translation initiation.

Host-Intrinsic Interferon Status in Infection and Immunity

Most genetic ablations of interferon (IFN) signaling abolish both the experimentally induced IFN response and constitutive IFN, whose effects are well established in autoimmunity but understudied during infection. In host-pathogen interactions, most IFN-mediated responses are attributed to infection-driven IFN. However, IFNs confer their activity by regulating networks of interferon-stimulated genes (ISGs), a process that requires de novo transcription and translation of both IFN and downstream ISGs through feedback of IFN receptor signaling. Due to the temporal requirement for IFN activity, many rapid antimicrobial responses may instead result from pre-established IFN signature stemming from host-intrinsic processes. Addressing the permeating effects of constitutive IFN is therefore needed to accurately describe immunity as host intrinsic or pathogen induced.

Transcripts from downstream alternative transcription start sites evade uORF-mediated inhibition of gene expression in Arabidopsis

The upstream ORFs (uORFs) in the 5′UTRs of mRNA often function as repressors of main ORF translation or triggers of nonsense-mediated mRNA decay. In this study, we report on transcription start site (TSS) selection when etiolated Arabidopsis seedlings are exposed to blue light, and reveal that transcription from uORF-avoiding TSSs is induced throughout the genome. It is possible that transcripts arising from TSSs downstream of uORFs evade uORF-mediated inhibition of gene expression. Thus, uORF-avoiding transcription starts are an important mechanism of gene expression regulation during a plant’s response to environmental changes.

Plants adapt to alterations in light conditions by controlling their gene expression profiles. Expression of light-inducible genes is transcriptionally induced by transcription factors such as HY5. However, few detailed analyses have been carried out on the control of transcription start sites (TSSs). Of the various wavelengths of light, it is blue light (BL) that regulates physiological responses such as hypocotyl elongation and flowering time. To understand how gene expression is controlled not only by transcript abundance but also by TSS selection, we examined genome-wide TSS profiles in Arabidopsis seedlings after exposure to BL irradiation following initial growth in the dark. Thousands of genes use multiple TSSs, and some transcripts have upstream ORFs (uORFs) that take precedence over the main ORF (mORF) encoding proteins. The uORFs often function as translation inhibitors of the mORF or as triggers of nonsense-mediated mRNA decay (NMD). Transcription from TSSs located downstream of the uORFs in 220 genes is enhanced by BL exposure. This type of regulation is found in HY5 and HYH, major regulators of light-dependent gene expression. Translation efficiencies of the genes showing enhanced usage of these TSSs increased upon BL exposure. We also show that transcripts from TSSs upstream of uORFs in 45 of the 220 genes, including HY5, accumulated in a mutant of NMD. These results suggest that BL controls gene expression not only by enhancing transcriptions but also by choosing the TSS, and transcripts from downstream TSSs evade uORF-mediated inhibition to ensure high expression of light-regulated genes.

Attenuation of Viruses by Large-Scale Recoding of their Genomes: the Selection Is Always Biased

Purpose of Review

This review summarizes the current understanding of virus attenuation by large-scale recoding of viral genomes and discusses what would ultimately be necessary for construction of better and safer live modified virus vaccines.

Recent Findings

It has been shown that codon and codon pair deoptimization are rapid and robust methods that can be used for the development of attenuated vaccine candidates. The viruses attenuated by large-scale recoding have the added value that they are extremely genetically stable. However, the exact mechanisms that lead to viral attenuation by recoding are yet to be determined.

Summary

While the advantages of large-scale recoding (speed, simplicity, potency, and universal applicability) have been known for more than a decade, this approach has been only inadequately explored and the attention was focused on a limited number of RNA viruses. Attenuation of viruses by large-scale recoding should be explored to combat known and future viral threats.

Identification of the amino acids inserted during suppression of CFTR nonsense mutations and determination of their functional consequences

In-frame premature termination codons (PTCs) account for ∼11% of all disease-associated mutations. PTC suppression therapy utilizes small molecules that suppress translation termination at a PTC to restore synthesis of a full-length protein. PTC suppression is mediated by the base pairing of a near-cognate aminoacyl-tRNA with a PTC and subsequently, the amino acid becomes incorporated into the nascent polypeptide at the site of the PTC. However, little is known about the identity of the amino acid(s) inserted at a PTC during this process in mammalian cells, or how the surrounding sequence context influences amino acid incorporation. Here, we determined the amino acids inserted at the cystic fibrosis transmembrane conductance regulator (CFTR) W1282X PTC (a UGA codon) in the context of its three upstream and downstream CFTR codons during G418-mediated suppression. We found that leucine, cysteine and tryptophan are inserted during W1282X suppression. Interestingly, these amino acids (and their proportions) are significantly different from those recently identified following G418-mediated suppression of the CFTR G542X UGA mutation. These results demonstrate for the first time that local mRNA sequence context plays a key role in near-cognate aminoacyl-tRNA selection during PTC suppression. We also found that some variant CFTR proteins generated by PTC suppression exhibit reduced maturation and activity, indicating the complexity of nonsense suppression therapy. However, both a CFTR corrector and potentiator enhanced activity of protein variants generated by G418-mediated suppression. These results suggest that PTC suppression in combination with CFTR modulators may be beneficial for the treatment of CF patients with PTCs.

Ribosomal Stalling During Translation: Providing Substrates for Ribosome-Associated Protein Quality Control

Cells of all organisms survey problems during translation elongation, which may happen as a consequence of mRNA aberrations, inefficient decoding, or other sources. In eukaryotes, ribosome-associated quality control (RQC) senses elongation-stalled ribosomes and promotes dissociation of ribosomal subunits. This so-called ribosomal rescue releases the mRNA for degradation and allows 40S subunits to be recycled for new rounds of translation. However, the nascent polypeptide chains remain linked to tRNA and associated with the rescued 60S subunits. As a final critical step in this pathway, the Ltn1/Listerin E3 ligase subunit of the RQC complex (RQCc) ubiquitylates the nascent chain, which promotes clearance of the 60S subunit while simultaneously marking the nascent chain for elimination. Here we review the ribosomal stalling and rescue steps upstream of the RQCc, where one witnesses intersection with cellular machineries implicated in translation elongation, translation termination, ribosomal subunit recycling, and mRNA quality control. We emphasize both recent progress and future directions in this area, as well as examples linking ribosomal rescue with the production of Ltn1-RQCc substrates.

Rewriting the Genetic Code

The genetic code-the language used by cells to translate their genomes into proteins that perform many cellular functions-is highly conserved throughout natural life. Rewriting the genetic code could lead to new biological functions such as expanding protein chemistries with noncanonical amino acids (ncAAs) and genetically isolating synthetic organisms from natural organisms and viruses. It has long been possible to transiently produce proteins bearing ncAAs, but stabilizing an expanded genetic code for sustained function in vivo requires an integrated approach: creating recoded genomes and introducing new translation machinery that function together without compromising viability or clashing with endogenous pathways. In this review, we discuss design considerations and technologies for expanding the genetic code. The knowledge obtained by rewriting the genetic code will deepen our understanding of how genomes are designed and how the canonical genetic code evolved.

Imaging Translational and Post-Translational Gene Regulatory Dynamics in Living Cells with Antibody-Based Probes

Antibody derivatives, such as antibody fragments (Fabs) and single-chain variable fragments (scFvs), are now being used to image traditionally hard-to-see protein subpopulations, including nascent polypeptides being translated and post-translationally modified proteins. This has allowed researchers to directly image and quantify, for the first time, translation initiation and elongation kinetics with single-transcript resolution and the temporal ordering and kinetics of post-translational histone and RNA polymerase II modifications. Here, we review these developments and discuss the strengths and weaknesses of live-cell imaging with antibody-based probes. Further development of these probes will increase their versatility and open new avenues of research for dissecting complex gene regulatory dynamics.

Synonymous Codons: Choose Wisely for Expression

The genetic code, which defines the amino acid sequence of a protein, also contains information that influences the rate and efficiency of translation. Neither the mechanisms nor functions of codon-mediated regulation were well understood. The prevailing model was that the slow translation of codons decoded by rare tRNAs reduces efficiency. Recent genome-wide analyses have clarified several issues. Specific codons and codon combinations modulate ribosome speed and facilitate protein folding. However, tRNA availability is not the sole determinant of rate; rather, interactions between adjacent codons and wobble base pairing are key. One mechanism linking translation efficiency and codon use is that slower decoding is coupled to reduced mRNA stability. Changes in tRNA supply mediate biological regulationfor instance,, changes in tRNA amounts facilitate cancer metastasis.