An integrated approach reveals regulatory controls on bacterial translation elongation

A survey of experimental and computational identification of small proteins

Small proteins (SPs) are typically characterized as eukaryotic proteins shorter than 100 amino acids and prokaryotic proteins shorter than 50 amino acids. Historically, they were disregarded because of the arbitrary size thresholds to define proteins. However, recent research has revealed the existence of many SPs and their crucial roles. Despite this, the identification of SPs and the elucidation of their functions are still in their infancy. To pave the way for future SP studies, we briefly introduce the limitations and advancements in experimental techniques for SP identification. We then provide an overview of available computational tools for SP identification, their constraints, and their evaluation. Additionally, we highlight existing resources for SP research. This survey aims to initiate further exploration into SPs and encourage the development of more sophisticated computational tools for SP identification in prokaryotes and microbiomes.

Riboformer: a deep learning framework for predicting context-dependent translation dynamics

Translation elongation is essential for maintaining cellular proteostasis, and alterations in the translational landscape are associated with a range of diseases. Ribosome profiling allows detailed measurements of translation at the genome scale. However, it remains unclear how to disentangle biological variations from technical artifacts in these data and identify sequence determinants of translation dysregulation. Here we present Riboformer, a deep learning-based framework for modeling context-dependent changes in translation dynamics. Riboformer leverages the transformer architecture to accurately predict ribosome densities at codon resolution. When trained on an unbiased dataset, Riboformer corrects experimental artifacts in previously unseen datasets, which reveals subtle differences in synonymous codon translation and uncovers a bottleneck in translation elongation. Further, we show that Riboformer can be combined with in silico mutagenesis to identify sequence motifs that contribute to ribosome stalling across various biological contexts, including aging and viral infection. Our tool offers a context-aware and interpretable approach for standardizing ribosome profiling datasets and elucidating the regulatory basis of translation kinetics.

Generation of DNAzyme in Bacterial Cells by a Bacterial Retron System

DNAzymes are catalytically active single-stranded DNAs in which DNAzyme 10-23 (Dz 10-23) consists of a catalytic core and a substrate-binding arm that reduces gene expression through sequence-specific mRNA cleavage. However, the in vivo application of Dz 10-23 depends on exogenous delivery, which leads to its inability to be synthesized and stabilized in vivo, thus limiting its application. As a unique reverse transcription system, the bacterial retron system can synthesize single-stranded DNA in vivo using ncRNA msr/msd as a template. The objective of this work is to reduce target gene expression using Dz 10-23 generated in vivo by the retron system. In this regard, we successfully generated Dz 10-23 by cloning the Dz 10-23 coding sequence into the retron msd gene and tested its ability to reduce specific gene expression by examining the mRNA levels of cfp encoding cyan fluorescence protein and other functional genes such as mreB and ftsZ. We found that Dz had different repressive effects when targeting different mRNA regions, and in general, the repressive effect was stronger when targeting downstream of mRNAs. Our results also suggested that the reduction effect was due to cleavage of the substrate mRNA by Dz 10-23 rather than the antisense effect of the substrate-binding arm. Therefore, this study not only provided a retron-based method for the intracellular generation of Dz 10-23 but also demonstrated that Dz 10-23 could reduce gene expression by cleaving target mRNAs in cells. We believe that this new strategy would have great potential in the regulation of gene expression.

spotter: a single-nucleotide resolution stochastic simulation model of supercoiling-mediated transcription and translation in prokaryotes

Stochastic simulation models have played an important role in efforts to understand the mechanistic basis of prokaryotic transcription and translation. Despite the fundamental linkage of these processes in bacterial cells, however, most simulation models have been limited to representations of either transcription or translation. In addition, the available simulation models typically either attempt to recapitulate data from single-molecule experiments without considering cellular-scale high-throughput sequencing data or, conversely, seek to reproduce cellular-scale data without paying close attention to many of the mechanistic details. To address these limitations, we here present spotter (Simulation of Prokaryotic Operon Transcription & Translation Elongation Reactions), a flexible, user-friendly simulation model that offers highly-detailed combined representations of prokaryotic transcription, translation, and DNA supercoiling. In incorporating nascent transcript and ribosomal profiling sequencing data, spotter provides a critical bridge between data collected in single-molecule experiments and data collected at the cellular scale. Importantly, in addition to rapidly generating output that can be aggregated for comparison with next-generation sequencing and proteomics data, spotter produces residue-level positional information that can be used to visualize individual simulation trajectories in detail. We anticipate that spotter will be a useful tool in exploring the interplay of processes that are crucially linked in prokaryotes.

Arginine regulates HSPA5/BiP translation through ribosome pausing in triple-negative breast cancer cells

BACKGROUND

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with a high mortality rate due to a lack of therapeutic targets. Many TNBC cells are reliant on extracellular arginine for survival and express high levels of binding immunoglobin protein (BiP), a marker of metastasis and endoplasmic reticulum (ER) stress response.

METHODS

In this study, the effect of arginine shortage on BiP expression in the TNBC cell line MDA-MB-231 was evaluated. Two stable cell lines were generated in MDA-MB-231 cells: the first expressed wild-type BiP, and the second expressed a mutated BiP free of the two arginine pause-site codons, CCU and CGU, termed G-BiP.

RESULTS

The results showed that arginine shortage induced a non-canonical ER stress response by inhibiting BiP translation via ribosome pausing. Overexpression of G-BiP in MDA-MB-231 cells promoted cell resistance to arginine shortage compared to cells overexpressing wild-type BiP. Additionally, limiting arginine led to decreased levels of the spliced XBP1 in the G-BiP overexpressing cells, potentially contributing to their improved survival compared to the parental WT BiP overexpressing cells.

CONCLUSION

In conclusion, these findings suggest that the downregulation of BiP disrupts proteostasis during arginine shortage-induced non-canonical ER stress and plays a key role in cell growth inhibition, indicating BiP as a target of codon-specific ribosome pausing upon arginine shortage.

Small Open Reading Frame-Encoded Micro-Peptides: An Emerging Protein World

Small open reading frames (sORFs) are often overlooked features in genomes. In the past, they were labeled as noncoding or "transcriptional noise". However, accumulating evidence from recent years suggests that sORFs may be transcribed and translated to produce sORF-encoded polypeptides (SEPs) with less than 100 amino acids. The vigorous development of computational algorithms, ribosome profiling, and peptidome has facilitated the prediction and identification of many new SEPs. These SEPs were revealed to be involved in a wide range of basic biological processes, such as gene expression regulation, embryonic development, cellular metabolism, inflammation, and even carcinogenesis. To effectively understand the potential biological functions of SEPs, we discuss the history and development of the newly emerging research on sORFs and SEPs. In particular, we review a range of recently discovered bioinformatics tools for identifying, predicting, and validating SEPs as well as a variety of biochemical experiments for characterizing SEP functions. Lastly, this review underlines the challenges and future directions in identifying and validating sORFs and their encoded micropeptides, providing a significant reference for upcoming research on sORF-encoded peptides.

Design and application of artificial rare L-lysine codons in Corynebacterium glutamicum

Background: L-lysine is widely used in the feed, food, and pharmaceutical industries, and screening for high L-lysine-producing strains has become a key goal for the industry. Methods: We constructed the rare L-lysine codon AAA by corresponding tRNA promoter replacement in C. glutamicum. Additionally, a screening marker related to the intracellular L-lysine content was constructed by converting all L-lysine codons of enhanced green fluorescent protein (EGFP) into the artificial rare codon AAA. The artificial EGFP was then ligated into pEC-XK99E and transformed into competent Corynebacterium glutamicum 23604 cells with the rare L-lysine codon. After atmospheric and room-temperature plasma mutation and induction culture, 55 mutants (0.01% of total cells) with stronger fluorescence were sorted using flow cytometry, and further screened by fermentation in a 96-deep-well plate and 500 mL shaker. Results: The fermentation results showed that the L-lysine production was increased by up to 9.7% in the mutant strains with higher fluorescence intensities, and that the highest screening positive rate was 69%, compared with that in the wild-type strain. Conclusion: The application of artificially constructed rare codons in this study represents an efficient, accurate, and simple method for screening other amino acid-producing microorganisms.

Riboformer: A Deep Learning Framework for Predicting Context-Dependent Translation Dynamics

Translation elongation is essential for maintaining cellular proteostasis, and alterations in the translational landscape are associated with a range of diseases. Ribosome profiling allows detailed measurement of translation at genome scale. However, it remains unclear how to disentangle biological variations from technical artifacts and identify sequence determinant of translation dysregulation. Here we present Riboformer, a deep learning-based framework for modeling context-dependent changes in translation dynamics. Riboformer leverages the transformer architecture to accurately predict ribosome densities at codon resolution. It corrects experimental artifacts in previously unseen datasets, reveals subtle differences in synonymous codon translation and uncovers a bottleneck in protein synthesis. Further, we show that Riboformer can be combined with in silico mutagenesis analysis to identify sequence motifs that contribute to ribosome stalling across various biological contexts, including aging and viral infection. Our tool offers a context-aware and interpretable approach for standardizing ribosome profiling datasets and elucidating the regulatory basis of translation kinetics.

spotter : A single-nucleotide resolution stochastic simulation model of supercoiling-mediated transcription and translation in prokaryotes

Stochastic simulation models have played an important role in efforts to understand the mechanistic basis of prokaryotic transcription and translation. Despite the fundamental linkage of these processes in bacterial cells, however, most simulation models have been limited to representations of either transcription or translation. In addition, the available simulation models typically either attempt to recapitulate data from single-molecule experiments without considering cellular-scale high-throughput sequencing data or, conversely, seek to reproduce cellular-scale data without paying close attention to many of the mechanistic details. To address these limitations, we here present spotter (Simulation of Prokaryotic Operon Transcription & Translation Elongation Reactions), a flexible, user-friendly simulation model that offers highly-detailed combined representations of prokaryotic transcription, translation, and DNA supercoiling. In incorporating nascent transcript and ribosomal profiling sequencing data, spotter provides a critical bridge between data collected in single-molecule experiments and data collected at the cellular scale. Importantly, in addition to rapidly generating output that can be aggregated for comparison with next-generation sequencing and proteomics data, spotter produces residue-level positional information that can be used to visualize individual simulation trajectories in detail. We anticipate that spotter will be a useful tool in exploring the interplay of processes that are crucially linked in prokaryotes.

Understanding the Stringent Response: Experimental Context Matters

As rapidly growing bacteria begin to exhaust essential nutrients, they enter a state of reduced growth, ultimately leading to stasis or quiescence. Investigation of the response to nutrient limitation has focused largely on the consequences of amino acid starvation, known as the "stringent response." Here, an uncharged tRNA in the A-site of the ribosome stimulates the ribosome-associated protein RelA to synthesize the hyperphosphorylated guanosine nucleotides (p)ppGpp that mediate a global slowdown of growth and biosynthesis. Investigations of the stringent response typically employ experimental methodologies that rapidly stimulate (p)ppGpp synthesis by abruptly increasing the fraction of uncharged tRNAs, either by explicit amino starvation or by inhibition of tRNA charging. Consequently, these methodologies inhibit protein translation, thereby interfering with the cellular pathways that respond to nutrient limitation. Thus, complete and/or rapid starvation is a problematic experimental paradigm for investigating bacterial responses to physiologically relevant nutrient-limited states.

Identification of a Rho-Dependent Termination Site In Vivo Using Synthetic Small RNA

Rho promotes Rho-dependent termination (RDT) at the Rho-dependent terminator, producing a variable-length region without secondary structure at the 3' end of mRNA. Determining the exact RDT site in vivo is challenging, because the 3' end of mRNA is rapidly removed after RDT by 3'-to-5' exonuclease processing. Here, we applied synthetic small RNA (sysRNA) to identify the RDT region in vivo by exploiting its complementary base-pairing ability to target mRNA. Through the combined analyses of rapid amplification of cDNA 3' ends, primer extension, and capillary electrophoresis, we could precisely map and quantify mRNA 3' ends. We found that complementary double-stranded RNA (dsRNA) formed between sysRNA and mRNA was efficiently cleaved by RNase III in the middle of the dsRNA region. The formation of dsRNA appeared to protect the cleaved RNA 3' ends from rapid degradation by 3'-to-5' exonuclease, thereby stabilizing the mRNA 3' end. We further verified that the signal intensity at the 3' end was positively correlated with the amount of mRNA. By constructing a series of sysRNAs with close target sites and comparing the difference in signal intensity at the 3' end of wild-type and Rho-impaired strains, we finally identified a region of increased mRNA expression within the 21-bp range, which was determined as the RDT region. Our results demonstrated the ability to use sysRNA as a novel tool to identify RDT regions in vivo and expand the range of applications of sysRNA. IMPORTANCE sysRNA, which was formerly widely employed, has steadily lost popularity as more novel techniques for suppressing gene expression come into existence because of issues such as unstable inhibition effect and low inhibition efficiency. However, it remains an interesting topic as a regulatory tool due to its ease of design and low metabolic burden on cells. Here, for the first time, we discovered a new method to identify RDT regions in vivo using sysRNA. This new feature is important because since the discovery of the Rho protein in 1969, specific identification of RDT sites in vivo has been difficult due to the rapid processing of RNA 3' ends by exonucleases, and sysRNA might provide a new approach to address this challenge.

Gut colonization by Bacteroides requires translation by an EF-G paralog lacking GTPase activity

Protein synthesis is crucial for cell growth and survival yet one of the most energy-consuming cellular processes. How, then, do cells sustain protein synthesis under starvation conditions when energy is limited? To accelerate the translocation of mRNA-tRNAs through the ribosome, bacterial elongation factor G (EF-G) hydrolyzes energy-rich guanosine triphosphate (GTP) for every amino acid incorporated into a protein. Here, we identify an EF-G paralog-EF-G2-that supports translocation without hydrolyzing GTP in the gut commensal bacterium Bacteroides thetaiotaomicron. EF-G2's singular ability to sustain protein synthesis, albeit at slow rates, is crucial for bacterial gut colonization. EF-G2 is ~10-fold more abundant than canonical EF-G1 in bacteria harvested from murine ceca and, unlike EF-G1, specifically accumulates during carbon starvation. Moreover, we uncover a 26-residue region unique to EF-G2 that is essential for protein synthesis, EF-G2 dissociation from the ribosome, and responsible for the absence of GTPase activity. Our findings reveal how cells curb energy consumption while maintaining protein synthesis to advance fitness in nutrient-fluctuating environments.

Global and gene-specific translational regulation in Escherichia coli across different conditions

How well mRNA transcript levels represent protein abundances has been a controversial issue. Particularly across different environments, correlations between mRNA and protein exhibit remarkable variability from gene to gene. Translational regulation is likely to be one of the key factors contributing to mismatches between mRNA level and protein abundance in bacteria. Here, we quantified genome-wide transcriptome and relative translation efficiency (RTE) under 12 different conditions in Escherichia coli. By quantifying the mRNA-RTE correlation both across genes and across conditions, we uncovered a diversity of gene-specific translational regulations, cooperating with transcriptional regulations, in response to carbon (C), nitrogen (N), and phosphate (P) limitations. Intriguingly, we found that many genes regulating translation are themselves subject to translational regulation, suggesting possible feedbacks. Furthermore, a random forest model suggests that codon usage partially predicts a gene's cross-condition variability in translation efficiency; such cross-condition variability tends to be an inherent quality of a gene, independent of the specific nutrient limitations. These findings broaden the understanding of translational regulation under different environments and provide novel strategies for the control of translation in synthetic biology. In addition, our data offers a resource for future multi-omics studies.

Maintenance of tRNA and elongation factors supports T3SS proteins translational elongations in pathogenic bacteria during nutrient starvation

Background

Sufficient nutrition contributes to rapid translational elongation and protein synthesis in eukaryotic cells and prokaryotic bacteria. Fast synthesis and accumulation of type III secretion system (T3SS) proteins conduce to the invasion of pathogenic bacteria into the host cells. However, the translational elongation patterns of T3SS proteins in pathogenic bacteria under T3SS-inducing conditions remain unclear. Here, we report a mechanism of translational elongation of T3SS regulators, effectors and structural protein in four model pathogenic bacteria (Pseudomonas syringae, Pseudomonas aeruginosa, Xanthomonas oryzae and Ralstonia solanacearum) and a clinical isolate (Pseudomonas aeruginosa UCBPP-PA14) under nutrient-limiting conditions. We proposed a luminescence reporter system to quantitatively determine the translational elongation rates (ERs) of T3SS regulators, effectors and structural protein under different nutrient-limiting conditions and culture durations.

Results

The translational ERs of T3SS regulators, effectors and structural protein in these pathogenic bacteria were negatively regulated by the nutrient concentration and culture duration. The translational ERs in 0.5× T3SS-inducing medium were the highest of all tested media. In 1× T3SS-inducing medium, the translational ERs were highest at 0 min and then rapidly decreased. The translational ERs of T3SS regulators, effectors and structural protein were inhibited by tRNA degradation and by reduced levels of elongation factors (EFs).

Conclusions

Rapid translational ER and synthesis of T3SS protein need adequate tRNAs and EFs in nutrient-limiting conditions. Numeric presentation of T3SS translation visually indicates the invasion of bacteria and provides new insights into T3SS expression that can be applied to other pathogenic bacteria.

Ribosome profiling enhances understanding of mycobacterial translation

A recent addition to the -omics toolkit, ribosome profiling, enables researchers to gain insight into the process and regulation of translation by mapping fragments of mRNA protected from nuclease digestion by ribosome binding. In this review, we discuss how ribosome profiling applied to mycobacteria has led to discoveries about translational regulation. Using case studies, we show that the traditional view of “canonical” translation mechanisms needs expanding to encompass features of mycobacterial translation that are more widespread than previously recognized. We also discuss the limitations of the method and potential future developments that could yield further insight into the fundamental biology of this important human pathogen.

A Neural Networks Approach for the Analysis of Reproducible Ribo–Seq Profiles

In recent years, the Ribosome profiling technique (Ribo–seq) has emerged as a powerful method for globally monitoring the translation process in vivo at single nucleotide resolution. Based on deep sequencing of mRNA fragments, Ribo–seq allows to obtain profiles that reflect the time spent by ribosomes in translating each part of an open reading frame. Unfortunately, the profiles produced by this method can vary significantly in different experimental setups, being characterized by a poor reproducibility. To address this problem, we have employed a statistical method for the identification of highly reproducible Ribo–seq profiles, which was tested on a set of E. coli genes. State-of-the-art artificial neural network models have been used to validate the quality of the produced sequences. Moreover, new insights into the dynamics of ribosome translation have been provided through a statistical analysis on the obtained sequences.

Oxygen level regulates N-terminal translation elongation of selected proteins through deoxyhypusine hydroxylation

Hypusine is a post-translational modification on eukaryotic translation initiation factor 5A (eIF5A). The last step of hypusine biosynthesis, deoxyhypusine hydroxylation, is an oxygen-dependent reaction. Here we show that deletion of the deoxyhypusine hydroxylase Lia1 compromises yeast respiration through translation downregulation of selected proteins in the respiration pathway. The translation suppression, because of the lack of deoxyhypusine hydroxylation, mainly affects translation of the N termini of the proteins, independent of the presence of proline residues but likely dependent on the interaction between the N-terminal nascent peptide and the ribosomal peptide exit tunnel. Proteomics and biochemical studies reveal that Lia1 deletion decreases N-terminal translation of proteins involved in mitochondrial respiration, oxidative stress response, and protein folding. Our work uncovers functions of the hypusine modification by considering the substrate requirement of the post-translational modification, highlights the unique challenges of translating the N termini of proteins, and reveals an oxygen-sensing mechanism in eukaryotic cells.

Short open reading frames (sORFs) and microproteins: an update on their identification and validation measures

A short open reading frame (sORFs) constitutes ≤ 300 bases, encoding a microprotein or sORF-encoded protein (SEP) which comprises ≤ 100 amino acids. Traditionally dismissed by genome annotation pipelines as meaningless noise, sORFs were found to possess coding potential with ribosome profiling (RIBO-Seq), which unveiled sORF-based transcripts at various genome locations. Nonetheless, the existence of corresponding microproteins that are stable and functional was little substantiated by experimental evidence initially. With recent advancements in multi-omics, the identification, validation, and functional characterisation of sORFs and microproteins have become feasible. In this review, we discuss the history and development of an emerging research field of sORFs and microproteins. In particular, we focus on an array of bioinformatics and OMICS approaches used for predicting, sequencing, validating, and characterizing these recently discovered entities. These strategies include RIBO-Seq which detects sORF transcripts via ribosome footprints, and mass spectrometry (MS)-based proteomics for sequencing the resultant microproteins. Subsequently, our discussion extends to the functional characterisation of microproteins by incorporating CRISPR/Cas9 screen and protein–protein interaction (PPI) studies. Our review discusses not only detection methodologies, but we also highlight on the challenges and potential solutions in identifying and validating sORFs and their microproteins. The novelty of this review lies within its validation for the functional role of microproteins, which could contribute towards the future landscape of microproteomics.

Ribosome collisions induce mRNA cleavage and ribosome rescue in bacteria

Ribosome rescue pathways recycle stalled ribosomes and target problematic mRNAs and aborted proteins for degradation^1,2. In bacteria, it remains unclear how rescue pathways distinguish ribosomes stalled in the middle of a transcript from actively translating ribosomes^3-6. Here, using a genetic screen in Escherichia coli, we discovered a new rescue factor that has endonuclease activity. SmrB cleaves mRNAs upstream of stalled ribosomes, allowing the ribosome rescue factor tmRNA (which acts on truncated mRNAs³) to rescue upstream ribosomes. SmrB is recruited to ribosomes and is activated by collisions. Cryo-electron microscopy structures of collided disomes from E. coli and Bacillus subtilis show distinct and conserved arrangements of individual ribosomes and the composite SmrB-binding site. These findings reveal the underlying mechanisms by which ribosome collisions trigger ribosome rescue in bacteria.

The landscape of translational stall sites in bacteria revealed by monosome and disome profiling

Ribosome pauses are associated with various cotranslational events and determine the fate of mRNAs and proteins. Thus, the identification of precise pause sites across the transcriptome is desirable; however, the landscape of ribosome pauses in bacteria remains ambiguous. Here, we harness monosome and disome (or collided ribosome) profiling strategies to survey ribosome pause sites in Escherichia coli Compared to eukaryotes, ribosome collisions in bacteria showed remarkable differences: a low frequency of disomes at stop codons, collisions occurring immediately after 70S assembly on start codons, and shorter queues of ribosomes trailing upstream. The pause sites corresponded with the biochemical validation by integrated nascent chain profiling (iNP) to detect polypeptidyl-tRNA, an elongation intermediate. Moreover, the subset of those sites showed puromycin resistance, presenting slow peptidyl transfer. Among the identified sites, the ribosome pause at Asn586 of ycbZ was validated by biochemical reporter assay, tRNA sequencing (tRNA-seq), and cryo-electron microscopy (cryo-EM) experiments. Our results provide a useful resource for ribosome stalling sites in bacteria.

Synergistic Regulation of Transcription and Translation in Escherichia coli Revealed by Codirectional Increases in mRNA Concentration and Translation Efficiency

Translational regulation was investigated at the genome-scale in Escherichia coli cells. Using the polysome profiling method, the ribosome occupancy (RO) and ribosome density (RD) of different mRNA copies were determined for several hundred mRNAs during the exponential- and stationary-phases, providing the most complete characterization of such regulation in E. coli. Although for most genes, nearly all mRNAs (>90%) were undergoing translation, they were loaded with far fewer than the theoretical maximum number of ribosomes, suggesting translation limitation at the initiation step. Multiple linear regression was used to identify key intrinsic factors involved in the genome-wide regulation of RO and RD (i.e., open reading frame GC%, protein function, and localization). Unexpectedly, mRNA concentration, a factor that depends on cell physiology, was predicted to positively regulate RO and RD during the exponential- and stationary-phases. Using a set of selected genes controlled by an inducible promoter, we confirmed that increasing the mRNA concentration upon transcription induction led to increases in both RO and ribosome load. The fact that this relationship between mRNA concentration and translation parameters was also effective when E. coli cells naturally adapted to carbon source changes demonstrates its physiological relevance. This work demonstrated that translation regulation is positively controlled by transcript availability. This new mechanism contributed to the codirectional regulation of transcription and translation with synergistic effects on gene expression and provided a systemic understanding of E. coli cell function. IMPORTANCE The process of gene expression is divided into translation and transcription. Considerable efforts have been made in bacteria to characterize the mechanisms underlying translational regulation and identify the regulatory factors for particular mRNAs. However, to understand bacterial physiology and adaptation, it is important to elucidate genome-wide translational regulation and examine its coordination with transcriptional regulation. Here, we provided a genome-wide picture of translational regulation in Escherichia coli. For most genes, nearly all mRNA copies were found to undergo translation but were loaded with a low number of ribosomes. We showed that mRNA concentration had a positive effect on translation regulation, linking translational regulation to transcriptional regulation as well as to cell physiology and growth conditions. The codirectional regulation of transcription and translation had synergistic effects on gene expression, contributing to E. coli cell function optimization. This finding could be used in biotechnology to optimize strategies for recombinant protein synthesis.

Translation complex stabilization on messenger RNA and footprint profiling to study the RNA responses and dynamics of protein biosynthesis in the cells

During protein biosynthesis, ribosomes bind to messenger (m)RNA, locate its protein-coding information, and translate the nucleotide triplets sequentially as codons into the corresponding sequence of amino acids, forming proteins. Non-coding mRNA features, such as 5' and 3' untranslated regions (UTRs), start sites or stop codons of different efficiency, stretches of slower or faster code and nascent polypeptide interactions can alter the translation rates transcript-wise. Most of the homeostatic and signal response pathways of the cells converge on individual mRNA control, as well as alter the global translation output. Among the multitude of approaches to study translational control, one of the most powerful is to infer the locations of translational complexes on mRNA based on the mRNA fragments protected by these complexes from endonucleolytic hydrolysis, or footprints. Translation complex profiling by high-throughput sequencing of the footprints allows to quantify the transcript-wise, as well as global, alterations of translation, and uncover the underlying control mechanisms by attributing footprint locations and sizes to different configurations of the translational complexes. The accuracy of all footprint profiling approaches critically depends on the fidelity of footprint generation and many methods have emerged to preserve certain or multiple configurations of the translational complexes, often in challenging biological material. In this review, a systematic summary of approaches to stabilize translational complexes on mRNA for footprinting is presented and major findings are discussed. Future directions of translation footprint profiling are outlined, focusing on the fidelity and accuracy of inference of the native in vivo translation complex distribution on mRNA.

First-principles model of optimal translation factors stoichiometry

Enzymatic pathways have evolved uniquely preferred protein expression stoichiometry in living cells, but our ability to predict the optimal abundances from basic properties remains underdeveloped. Here, we report a biophysical, first-principles model of growth optimization for core mRNA translation, a multi-enzyme system that involves proteins with a broadly conserved stoichiometry spanning two orders of magnitude. We show that predictions from maximization of ribosome usage in a parsimonious flux model constrained by proteome allocation agree with the conserved ratios of translation factors. The analytical solutions, without free parameters, provide an interpretable framework for the observed hierarchy of expression levels based on simple biophysical properties, such as diffusion constants and protein sizes. Our results provide an intuitive and quantitative understanding for the construction of a central process of life, as well as a path toward rational design of pathway-specific enzyme expression stoichiometry.

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

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

Quantitative Control for Stoichiometric Protein Synthesis

Bacterial protein synthesis rates have evolved to maintain preferred stoichiometries at striking precision, from the components of protein complexes to constituents of entire pathways. Setting relative protein production rates to be well within a factor of two requires concerted tuning of transcription, RNA turnover, and translation, allowing many potential regulatory strategies to achieve the preferred output. The last decade has seen a greatly expanded capacity for precise interrogation of each step of the central dogma genome-wide. Here, we summarize how these technologies have shaped the current understanding of diverse bacterial regulatory architectures underpinning stoichiometric protein synthesis. We focus on the emerging expanded view of bacterial operons, which encode diverse primary and secondary mRNA structures for tuning protein stoichiometry. Emphasis is placed on how quantitative tuning is achieved. We discuss the challenges and open questions in the application of quantitative, genome-wide methodologies to the problem of precise protein production. Expected final online publication date for the Annual Review of Microbiology, Volume 75 is October 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

N7-Methylguanosine tRNA modification enhances oncogenic mRNA translation and promotes intrahepatic cholangiocarcinoma progression

Cancer cells selectively promote translation of specific oncogenic transcripts to facilitate cancer survival and progression, but the underlying mechanisms are poorly understood. Here, we find that N⁷-methylguanosine (m⁷G) tRNA modification and its methyltransferase complex components, METTL1 and WDR4, are significantly upregulated in intrahepatic cholangiocarcinoma (ICC) and associated with poor prognosis. We further reveal the critical role of METTL1/WDR4 in promoting ICC cell survival and progression using loss- and gain-of-function assays in vitro and in vivo. Mechanistically, m⁷G tRNA modification selectively regulates the translation of oncogenic transcripts, including cell-cycle and epidermal growth factor receptor (EGFR) pathway genes, in m⁷G-tRNA-decoded codon-frequency-dependent mechanisms. Moreover, using overexpression and knockout mouse models, we demonstrate the crucial oncogenic function of Mettl1-mediated m⁷G tRNA modification in promoting ICC tumorigenesis and progression in vivo. Our study uncovers the important physiological function and mechanism of METTL1-mediated m⁷G tRNA modification in the regulation of oncogenic mRNA translation and cancer progression.

Genome-wide Survey of Ribosome Collision

Ribosome movement is not always smooth and is rather often impeded. For ribosome pauses, fundamental issues remain to be addressed, including where ribosomes pause on mRNAs, what kind of RNA/amino acid sequence causes this pause, and the physiological significance of this attenuation of protein synthesis. Here, we survey the positions of ribosome collisions caused by ribosome pauses in humans and zebrafish using modified ribosome profiling. Collided ribosomes, i.e., disomes, emerge at various sites: Pro-Pro/Gly/Asp motifs; Arg-X-Lys motifs; stop codons; and 3' untranslated regions. The electrostatic interaction between the charged nascent chain and the ribosome exit tunnel determines the eIF5A-mediated disome rescue at the Pro-Pro sites. In particular, XBP1u, a precursor of endoplasmic reticulum (ER)-stress-responsive transcription factor, shows striking queues of collided ribosomes and thus acts as a degradation substrate by ribosome-associated quality control. Our results provide insight into the causes and consequences of ribosome pause by dissecting collided ribosomes.

The World of Stable Ribonucleoproteins and Its Mapping With Grad-Seq and Related Approaches

Macromolecular complexes of proteins and RNAs are essential building blocks of cells. These stable supramolecular particles can be viewed as minimal biochemical units whose structural organization, i.e., the way the RNA and the protein interact with each other, is directly linked to their biological function. Whether those are dynamic regulatory ribonucleoproteins (RNPs) or integrated molecular machines involved in gene expression, the comprehensive knowledge of these units is critical to our understanding of key molecular mechanisms and cell physiology phenomena. Such is the goal of diverse complexomic approaches and in particular of the recently developed gradient profiling by sequencing (Grad-seq). By separating cellular protein and RNA complexes on a density gradient and quantifying their distributions genome-wide by mass spectrometry and deep sequencing, Grad-seq charts global landscapes of native macromolecular assemblies. In this review, we propose a function-based ontology of stable RNPs and discuss how Grad-seq and related approaches transformed our perspective of bacterial and eukaryotic ribonucleoproteins by guiding the discovery of new RNA-binding proteins and unusual classes of noncoding RNAs. We highlight some methodological aspects and developments that permit to further boost the power of this technique and to look for exciting new biology in understudied and challenging biological models.

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.

Synonymous but Not Silent: The Codon Usage Code for Gene Expression and Protein Folding

Codon usage bias, the preference for certain synonymous codons, is found in all genomes. Although synonymous mutations were previously thought to be silent, a large body of evidence has demonstrated that codon usage can play major roles in determining gene expression levels and protein structures. Codon usage influences translation elongation speed and regulates translation efficiency and accuracy. Adaptation of codon usage to tRNA expression determines the proteome landscape. In addition, codon usage biases result in nonuniform ribosome decoding rates on mRNAs, which in turn influence the cotranslational protein folding process that is critical for protein function in diverse biological processes. Conserved genome-wide correlations have also been found between codon usage and protein structures. Furthermore, codon usage is a major determinant of mRNA levels through translation-dependent effects on mRNA decay and translation-independent effects on transcriptional and posttranscriptional processes. Here, we discuss the multifaceted roles and mechanisms of codon usage in different gene regulatory processes.

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

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

Neurons Release Serine to Support mRNA Translation in Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) tumors have a nutrient-poor, desmoplastic, and highly innervated tumor microenvironment. Although neurons can release stimulatory factors to accelerate PDAC tumorigenesis, the metabolic contribution of peripheral axons has not been explored. We found that peripheral axons release serine (Ser) to support the growth of exogenous Ser (exSer)-dependent PDAC cells during Ser/Gly (glycine) deprivation. Ser deprivation resulted in ribosomal stalling on two of the six Ser codons, TCC and TCT, and allowed the selective translation and secretion of nerve growth factor (NGF) by PDAC cells to promote tumor innervation. Consistent with this, exSer-dependent PDAC tumors grew slower and displayed enhanced innervation in mice on a Ser/Gly-free diet. Blockade of compensatory neuronal innervation using LOXO-101, a Trk-NGF inhibitor, further decreased PDAC tumor growth. Our data indicate that axonal-cancer metabolic crosstalk is a critical adaptation to support PDAC growth in nutrient poor environments.

Diverse Mechanisms and Circuitry for Global Regulation by the RNA-Binding Protein CsrA

The carbon storage regulator (Csr) or repressor of stationary phase metabolites (Rsm) system of Gammaproteobacteria is among the most complex and best-studied posttranscriptional regulatory systems. Based on a small RNA-binding protein, CsrA and homologs, it controls metabolism, physiology, and bacterial lifestyle decisions by regulating gene expression on a vast scale. Binding of CsrA to sequences containing conserved GGA motifs in mRNAs can regulate translation, RNA stability, riboswitch function, and transcript elongation. CsrA governs the expression of dozens of transcription factors and other regulators, further expanding its influence on cellular physiology, and these factors can participate in feedback to the Csr system. Expression of csrA itself is subject to autoregulation via translational inhibition and indirect transcriptional activation. CsrA activity is controlled by small noncoding RNAs (sRNAs), CsrB and CsrC in Escherichia coli, which contain multiple high affinity CsrA binding sites that compete with those of mRNA targets. Transcription of CsrB/C is induced by certain nutrient limitations, cellular stresses, and metabolites, while these RNAs are targeted for degradation by the presence of a preferred carbon source. Consistent with these findings, CsrA tends to activate pathways and processes that are associated with robust growth and repress stationary phase metabolism and stress responses. Regulatory loops between Csr components affect the signaling dynamics of the Csr system. Recently, systems-based approaches have greatly expanded our understanding of the roles played by CsrA, while reinforcing the notion that much remains to be learned about the Csr system.

Genome-wide effects of the antimicrobial peptide apidaecin on translation termination in bacteria

Biochemical studies suggested that the antimicrobial peptide apidaecin (Api) inhibits protein synthesis by binding in the nascent peptide exit tunnel and trapping the release factor associated with a terminating ribosome. The mode of Api action in bacterial cells had remained unknown. Here genome-wide analysis reveals that in bacteria, Api arrests translating ribosomes at stop codons and causes pronounced queuing of the trailing ribosomes. By sequestering the available release factors, Api promotes pervasive stop codon bypass, leading to the expression of proteins with C-terminal extensions. Api-mediated translation arrest leads to the futile activation of the ribosome rescue systems. Understanding the unique mechanism of Api action in living cells may facilitate the development of new medicines and research tools for genome exploration.

RiboToolkit: an integrated platform for analysis and annotation of ribosome profiling data to decode mRNA translation at codon resolution

Ribosome profiling (Ribo-seq) is a powerful technology for globally monitoring RNA translation; ranging from codon occupancy profiling, identification of actively translated open reading frames (ORFs), to the quantification of translational efficiency under various physiological or experimental conditions. However, analyzing and decoding translation information from Ribo-seq data is not trivial. Although there are many existing tools to analyze Ribo-seq data, most of these tools are designed for specific or limited functionalities and an easy-to-use integrated tool to analyze Ribo-seq data is lacking. Fortunately, the small size (26–34 nt) of ribosome protected fragments (RPFs) in Ribo-seq and the relatively small amount of sequencing data greatly facilitates the development of such a web platform, which is easy to manipulate for users with or without bioinformatic expertise. Thus, we developed RiboToolkit (http://rnabioinfor.tch.harvard.edu/RiboToolkit), a convenient, freely available, web-based service to centralize Ribo-seq data analyses, including data cleaning and quality evaluation, expression analysis based on RPFs, codon occupancy, translation efficiency analysis, differential translation analysis, functional annotation, translation metagene analysis, and identification of actively translated ORFs. Besides, easy-to-use web interfaces were developed to facilitate data analysis and intuitively visualize results. Thus, RiboToolkit will greatly facilitate the study of mRNA translation based on ribosome profiling.

COPII mitigates ER stress by promoting formation of ER whorls

Cells mitigate ER stress through the unfolded protein response (UPR). Here, we report formation of ER whorls as an effector mechanism of the ER stress response. We found that strong ER stress induces formation of ER whorls, which contain ER-resident proteins such as the Sec61 complex and PKR-like ER kinase (PERK). ER whorl formation is dependent on PERK kinase activity and is mediated by COPII machinery, which facilitates ER membrane budding to form tubular-vesicular ER whorl precursors. ER whorl precursors then go through Sec22b-mediated fusion to form ER whorls. We further show that ER whorls contribute to ER stress-induced translational inhibition by possibly modulating PERK activity and by sequestering translocons in a ribosome-free environment. We propose that formation of ER whorls reflects a new type of ER stress response that controls inhibition of protein translation.

Computational discovery and modeling of novel gene expression rules encoded in the mRNA

The transcript is populated with numerous overlapping codes that regulate all steps of gene expression. Deciphering these codes is very challenging due to the large number of variables involved, the non-modular nature of the codes, biases and limitations in current experimental approaches, our limited knowledge in gene expression regulation across the tree of life, and other factors. In recent years, it has been shown that computational modeling and algorithms can significantly accelerate the discovery of novel gene expression codes. Here, we briefly summarize the latest developments and different approaches in the field.

Modulation of Escherichia coli Translation by the Specific Inactivation of tRNAGly Under Oxidative Stress

Bacterial oxidative stress responses are generally controlled by transcription factors that modulate the synthesis of RNAs with the aid of some sRNAs that control the stability, and in some cases the translation, of specific mRNAs. Here, we report that oxidative stress additionally leads to inactivation of tRNA^Gly in Escherichia coli, inducing a series of physiological changes. The observed inactivation of tRNA^Gly correlated with altered efficiency of translation of Gly codons, suggesting a possible mechanism of translational control of gene expression under oxidative stress. Changes in translation also depended on the availability of glycine, revealing a mechanism whereby bacteria modulate the response to oxidative stress according to the prevailing metabolic state of the cells.

Growth-Optimized Aminoacyl-tRNA Synthetase Levels Prevent Maximal tRNA Charging

Aminoacyl-tRNA synthetases (aaRSs) serve a dual role in charging tRNAs. Their enzymatic activities both provide protein synthesis flux and reduce uncharged tRNA levels. Although uncharged tRNAs can negatively impact bacterial growth, substantial concentrations of tRNAs remain deacylated even under nutrient-rich conditions. Here, we show that tRNA charging in Bacillus subtilis is not maximized due to optimization of aaRS production during rapid growth, which prioritizes demands in protein synthesis over charging levels. The presence of uncharged tRNAs is alleviated by precisely tuned translation kinetics and the stringent response, both insensitive to aaRS overproduction but sharply responsive to underproduction, allowing for just enough aaRS production atop a "fitness cliff." Notably, we find that the stringent response mitigates fitness defects at all aaRS underproduction levels even without external starvation. Thus, adherence to minimal, flux-satisfying protein production drives limited tRNA charging and provides a basis for the sensitivity and setpoints of an integrated growth-control network.

tRNA methylation: An unexpected link to bacterial resistance and persistence to antibiotics and beyond

A major threat to public health is the resistance and persistence of Gram-negative bacteria to multiple drugs during antibiotic treatment. The resistance is due to the ability of these bacteria to block antibiotics from permeating into and accumulating inside the cell, while the persistence is due to the ability of these bacteria to enter into a nonreplicating state that shuts down major metabolic pathways but remains active in drug efflux. Resistance and persistence are permitted by the unique cell envelope structure of Gram-negative bacteria, which consists of both an outer and an inner membrane (OM and IM, respectively) that lay above and below the cell wall. Unexpectedly, recent work reveals that m¹ G37 methylation of tRNA, at the N¹ of guanosine at position 37 on the 3'-side of the tRNA anticodon, controls biosynthesis of both membranes and determines the integrity of cell envelope structure, thus providing a novel link to the development of bacterial resistance and persistence to antibiotics. The impact of m¹ G37-tRNA methylation on Gram-negative bacteria can reach further, by determining the ability of these bacteria to exit from the persistence state when the antibiotic treatment is removed. These conceptual advances raise the possibility that successful targeting of m¹ G37-tRNA methylation can provide new approaches for treating acute and chronic infections caused by Gram-negative bacteria. This article is categorized under: Translation > Translation Regulation RNA Processing > RNA Editing and Modification RNA Structure and Dynamics > Influence of RNA Structure in Biological Systems.

Evolutionary selection against short nucleotide sequences in viruses and their related hosts

Viruses are under constant evolutionary pressure to effectively interact with the host intracellular factors, while evading its immune system. Understanding how viruses co-evolve with their hosts is a fundamental topic in molecular evolution and may also aid in developing novel viral based applications such as vaccines, oncologic therapies, and anti-bacterial treatments. Here, based on a novel statistical framework and a large-scale genomic analysis of 2,625 viruses from all classes infecting 439 host organisms from all kingdoms of life, we identify short nucleotide sequences that are under-represented in the coding regions of viruses and their hosts. These sequences cannot be explained by the coding regions' amino acid content, codon, and dinucleotide frequencies. We specifically show that short homooligonucleotide and palindromic sequences tend to be under-represented in many viruses probably due to their effect on gene expression regulation and the interaction with the host immune system. In addition, we show that more sequences tend to be under-represented in dsDNA viruses than in other viral groups. Finally, we demonstrate, based on in vitro and in vivo experiments, how under-represented sequences can be used to attenuated Zika virus strains.

A rare codon-based translational program of cell proliferation

BACKGROUND

The speed of translation elongation is primarily determined by the abundance of tRNAs. Thus, the codon usage influences the rate with which individual mRNAs are translated. As the nature of tRNA pools and modifications can vary across biological conditions, codon elongation rates may also vary, leading to fluctuations in the protein production from individual mRNAs. Although it has been observed that functionally related mRNAs exhibit similar codon usage, presumably to provide an effective way to coordinate expression of multiple proteins, experimental evidence for codon-mediated translation efficiency modulation of functionally related mRNAs in specific conditions is scarce and the associated mechanisms are still debated.

RESULTS

Here, we reveal that mRNAs whose expression increases during cell proliferation are enriched in rare codons, poorly adapted to tRNA pools. Ribosome occupancy profiling and proteomics measurements show that upon increased cell proliferation, transcripts enriched in rare codons undergo a higher translation boost than transcripts with common codons. Re-coding of a fluorescent reporter with rare codons increased protein output by ~ 30% relative to a reporter re-coded with common codons. Although the translation capacity of proliferating cells was higher compared to resting cells, we did not find evidence for the regulation of individual tRNAs. Among the models that were proposed so far to account for codon-mediated translational regulation upon changing conditions, the one that seems most consistent with our data involves a global upregulation of ready-to-translate tRNAs, which we show can lead to a higher increase in the elongation velocity at rare codons compared to common codons.

CONCLUSIONS

We propose that the alleviation of translation bottlenecks in rapidly dividing cells enables preferential upregulation of pro-proliferation proteins, encoded by mRNAs that are enriched in rare codons.

A short translational ramp determines the efficiency of protein synthesis

Translation initiation is a major rate-limiting step for protein synthesis. However, recent studies strongly suggest that the efficiency of protein synthesis is additionally regulated by multiple factors that impact the elongation phase. To assess the influence of early elongation on protein synthesis, we employed a library of more than 250,000 reporters combined with in vitro and in vivo protein expression assays. Here we report that the identity of the amino acids encoded by codons 3 to 5 impact protein yield. This effect is independent of tRNA abundance, translation initiation efficiency, or overall mRNA structure. Single-molecule measurements of translation kinetics revealed pausing of the ribosome and aborted protein synthesis on codons 4 and 5 of distinct amino acid and nucleotide compositions. Finally, introduction of preferred sequence motifs only at specific codon positions improves protein synthesis efficiency for recombinant proteins. Collectively, our data underscore the critical role of early elongation events in translational control of gene expression.

Several factors contribute to the efficiency of protein expression. Here the authors show that the identity of amino acids encoded by codons at position 3–5 significantly impact translation efficiency and protein expression levels.

Inverted translational control of eukaryotic gene expression by ribosome collisions

The canonical model of eukaryotic translation posits that efficient translation initiation increases protein expression and mRNA stability. Contrary to this model, we find that increasing initiation rate can decrease both protein expression and stability of certain mRNAs in the budding yeast Saccharomyces cerevisiae. These mRNAs encode a stretch of polybasic residues that cause ribosome stalling. Our computational modeling predicts that the observed decrease in gene expression at high initiation rates occurs when ribosome collisions at stalls stimulate abortive termination of the leading ribosome or cause endonucleolytic mRNA cleavage. Consistent with this prediction, the collision-associated quality-control factors Asc1 and Hel2 (orthologs of human RACK1 and ZNF598, respectively) decrease gene expression from stall-containing mRNAs only at high initiation rates. Remarkably, hundreds of S. cerevisiae mRNAs that contain ribosome stall sequences also exhibit lower translation efficiency. We propose that inefficient translation initiation allows these stall-containing endogenous mRNAs to escape collision-stimulated reduction in gene expression.

Higher rates of translation counterintuitively lead to lower protein levels from eukaryotic mRNAs that encode ribosome stalls; modelling suggests that this occurs when ribosome collisions at stalls trigger abortive termination of the leading ribosome or cause endonucleolytic mRNA cleavage.

GWIPS-viz: 2018 update

The GWIPS-viz browser (http://gwips.ucc.ie/) is an on-line genome browser which is tailored for exploring ribosome profiling (Ribo-seq) data. Since its publication in 2014, GWIPS-viz provides Ribo-seq data for an additional 14 genomes bringing the current total to 23. The integration of new Ribo-seq data has been automated thereby increasing the number of available tracks to 1792, a 10-fold increase in the last three years. The increase is particularly substantial for data derived from human sources. Following user requests, we added the functionality to download these tracks in bigWig format. We also incorporated new types of data (e.g. TCP-seq) as well as auxiliary tracks from other sources that help with the interpretation of Ribo-seq data. Improvements in the visualization of the data have been carried out particularly for bacterial genomes where the Ribo-seq data are now shown in a strand specific manner. For higher eukaryotic datasets, we provide characteristics of individual datasets using the RUST program which includes the triplet periodicity, sequencing biases and relative inferred A-site dwell times. This information can be used for assessing the quality of Ribo-seq datasets. To improve the power of the signal, we aggregate Ribo-seq data from several studies into Global aggregate tracks for each genome.

Computational resources for ribosome profiling: from database to Web server and software

Ribosome profiling is emerging as a powerful technique that enables genome-wide investigation of in vivo translation at sub-codon resolution. The increasing application of ribosome profiling in recent years has achieved remarkable progress toward understanding the composition, regulation and mechanism of translation. This benefits from not only the awesome power of ribosome profiling but also an extensive range of computational resources available for ribosome profiling. At present, however, a comprehensive review on these resources is still lacking. Here, we survey the recent computational advances guided by ribosome profiling, with a focus on databases, Web servers and software tools for storing, visualizing and analyzing ribosome profiling data. This review is intended to provide experimental and computational biologists with a reference to make appropriate choices among existing resources for the question at hand.

RadD Contributes to R-Loop Avoidance in Sub-MIC Tobramycin

Bacteria frequently encounter low concentrations of antibiotics. Active antibiotics are commonly detected in soil and water at concentrations much below lethal concentration. Although sub-MICs of antibiotics do not kill bacteria, they can have a major impact on bacterial populations by contributing to the development of antibiotic resistance through mutations in originally sensitive bacteria or acquisition of DNA from resistant bacteria. It was shown that concentrations as low as 100-fold below the MIC can actually lead to the selection of antibiotic-resistant cells. We seek to understand how bacterial cells react to such antibiotic concentrations using E. coli, the Gram-negative bacterial paradigm, and V. cholerae, the causative agent of cholera. Our findings shed light on the processes triggered at the DNA level by antibiotics targeting translation, how damage occurs, and what the bacterial strategies are to respond to such DNA damage.

We have previously identified Vibrio cholerae mutants in which the stress response to subinhibitory concentrations of aminoglycoside is altered. One gene identified, VC1636, encodes a putative DNA/RNA helicase, recently named RadD in Escherichia coli. Here we combined extensive genetic characterization and high-throughput approaches in order to identify partners and molecular mechanisms involving RadD. We show that double-strand DNA breaks (DSBs) are formed upon subinhibitory tobramycin treatment in the absence of radD and recBCD and that formation of these DSBs can be overcome by RNase H1 overexpression. Loss of RNase H1, or of the transcription-translation coupling factor EF-P, is lethal in the radD deletion mutant. We propose that R-loops are formed upon sublethal aminoglycoside treatment, leading to the formation of DSBs that can be repaired by the RecBCD homologous recombination pathway, and that RadD counteracts such R-loop accumulation. We discuss how R-loops that can occur upon translation-transcription uncoupling could be the link between tobramycin treatment and DNA break formation.

Translation imaging of single mRNAs in established cell lines and primary cultured neurons

The central dogma of molecular biology reaches a crescendo at its final step: the translation of an mRNA into its corresponding protein product. This process is highly regulated both spatially and temporally, requiring techniques to interrogate the subcellular translational status of mRNAs in both living and fixed cells. Single-molecule imaging of nascent peptides (SINAPs) and related techniques allow us to study this fundamental process for single mRNAs in live cells. These techniques enable researchers to address previously intractable questions in the central dogma, such as the origin of stochastic translational control and the role of local translation in highly polarized cells. In this review, we present the methodology and the theoretical framework for conducting studies using SINAPs in both established cell lines and primary cultured neurons.

Ribosome Profiling: Global Views of Translation

The translation of messenger RNA (mRNA) into protein and the folding of the resulting protein into an active form are prerequisites for virtually every cellular process and represent the single largest investment of energy by cells. Ribosome profiling-based approaches have revolutionized our ability to monitor every step of protein synthesis in vivo, allowing one to measure the rate of protein synthesis across the proteome, annotate the protein coding capacity of genomes, monitor localized protein synthesis, and explore cotranslational folding and targeting. The rich and quantitative nature of ribosome profiling data provides an unprecedented opportunity to explore and model complex cellular processes. New analytical techniques and improved experimental protocols will provide a deeper understanding of the factors controlling translation speed and its impact on protein function and cell physiology as well as the role of ribosomal RNA and mRNA modifications in regulating translation.

Effects of mRNA Degradation and Site-Specific Transcriptional Pausing on Protein Expression Noise

Genetically identical cells exhibit diverse phenotypes even when experiencing the same environment. This phenomenon in part originates from cell-to-cell variability (noise) in protein expression. Although various kinetic schemes of stochastic transcription initiation are known to affect gene expression noise, how posttranscription initiation events contribute to noise at the protein level remains incompletely understood. To address this question, we developed a stochastic simulation-based model of bacterial gene expression that integrates well-known dependencies between transcription initiation, transcription elongation dynamics, mRNA degradation, and translation. We identified realistic conditions under which mRNA lifetime and transcriptional pauses modulate the protein expression noise initially introduced by the promoter architecture. For instance, we found that the short lifetime of bacterial mRNAs facilitates the production of protein bursts. Conversely, RNA polymerase (RNAP) pausing at specific sites during transcription elongation can attenuate protein bursts by fluidizing the RNAP traffic to the point of erasing the effect of a bursty promoter. Pause-prone sites, if located close to the promoter, can also affect noise indirectly by reducing both transcription and translation initiation due to RNAP and ribosome congestion. Our findings highlight how the interplay between transcription initiation, transcription elongation, translation, and mRNA degradation shapes the distribution in protein numbers. They also have implications for our understanding of gene evolution and suggest combinatorial strategies for modulating phenotypic variability by genetic engineering.