Operon mRNAs are organized into ORF-centric structures that predict translation efficiency

Hfq mediates transcriptome-wide RNA structurome reprogramming under virulence-inducing conditions in a phytopathogen

Although RNA structures play important roles in regulating gene expression, the mechanism and function of mRNA folding in plant bacterial pathogens remain elusive. Therefore, we perform dimethyl sulfate sequencing (DMS-seq) on the Pseudomonas syringae under nutrition-rich and -deficient conditions, revealing that the mRNA structure changes substantially in the minimal medium (MM) that tunes global translation efficiency (TE), thereby inducing virulence. This process is led by the increased expression of hfq, which is directly activated by transcription regulators RpoS and CysB. The co-occurrence of Hfq and RpoS in diverse bacteria and the deep conservation of Hfq Y25 is critical for RNA-mediated regulation and implicates the wider biological importance of mRNA structure and feedback loops in the control of global gene expression.

Enrichment of rare codons at 5' ends of genes is a spandrel caused by evolutionary sequence turnover and does not improve translation

Previously, Tuller et al. found that the first 30-50 codons of the genes of yeast and other eukaryotes are slightly enriched for rare codons. They argued that this slowed translation, and was adaptive because it queued ribosomes to prevent collisions. Today, the translational speeds of different codons are known, and indeed rare codons are translated slowly. We re-examined this 5' slow translation 'ramp.' We confirm that 5' regions are slightly enriched for rare codons; in addition, they are depleted for downstream Start codons (which are fast), with both effects contributing to slow 5' translation. However, we also find that the 5' (and 3') ends of yeast genes are poorly conserved in evolution, suggesting that they are unstable and turnover relatively rapidly. When a new 5' end forms de novo, it is likely to include codons that would otherwise be rare. Because evolution has had a relatively short time to select against these codons, 5' ends are typically slightly enriched for rare, slow codons. Opposite to the expectation of Tuller et al., we show by direct experiment that genes with slowly translated codons at the 5' end are expressed relatively poorly, and that substituting faster synonymous codons improves expression. Direct experiment shows that slow codons do not prevent downstream ribosome collisions. Further informatic studies suggest that for natural genes, slow 5' ends are correlated with poor gene expression, opposite to the expectation of Tuller et al. Thus, we conclude that slow 5' translation is a 'spandrel'--a non-adaptive consequence of something else, in this case, the turnover of 5' ends in evolution, and it does not improve translation.

Phylogenetic and Chemical Probing Information as Soft Constraints in RNA Secondary Structure Prediction

Extrinsic, experimental information can be incorporated into thermodynamics-based RNA folding algorithms in the form of pseudo-energies. Evolutionary conservation of RNA secondary structure elements is detectable in alignments of phylogenetically related sequences and provides evidence for the presence of certain base pairs that can also be converted into pseudo-energy contributions. We show that the centroid base pairs computed from a consensus folding model such as RNAalifold result in a substantial improvement of the prediction accuracy for single sequences. Evidence for specific base pairs turns out to be more informative than a position-wise profile for the conservation of the pairing status. A comparison with chemical probing data, furthermore, strongly suggests that phylogenetic base pairing data are more informative than position-specific data on (un)pairedness as obtained from chemical probing experiments. In this context we demonstrate, in addition, that the conversion of signal from probing data into pseudo-energies is possible using thermodynamic structure predictions as a reference instead of known RNA structures.

Integrating cryo-OrbiSIMS with computational modelling and metadynamics simulations enhances RNA structure prediction at atomic resolution

The 3D architecture of RNAs governs their molecular interactions, chemical reactions, and biological functions. However, a large number of RNAs and their protein complexes remain poorly understood due to the limitations of conventional structural biology techniques in deciphering their complex structures and dynamic interactions. To address this limitation, we have benchmarked an integrated approach that combines cryogenic OrbiSIMS, a state-of-the-art solid-state mass spectrometry technique, with computational methods for modelling RNA structures at atomic resolution with enhanced precision. Furthermore, using 7SK RNP as a test case, we have successfully determined the full 3D structure of a native RNA in its apo, native and disease-remodelled states, which offers insights into the structural interactions and plasticity of the 7SK complex within these states. Overall, our study establishes cryo-OrbiSIMS as a valuable tool in the field of RNA structural biology as it enables the study of challenging, native RNA systems.

Effects of mRNA conformational switching on translational noise in gene circuits

Intragenic translational heterogeneity describes the variation in translation at the level of transcripts for an individual gene. A factor that contributes to this source of variation is the mRNA structure. Both the composition of the thermodynamic ensemble, i.e., the stationary distribution of mRNA structures, and the switching dynamics between those play a role. The effect of the switching dynamics on intragenic translational heterogeneity remains poorly understood. We present a stochastic translation model that accounts for mRNA structure switching and is derived from a Markov model via approximate stochastic filtering. We assess the approximation on various timescales and provide a method to quantify how mRNA structure dynamics contributes to translational heterogeneity. With our approach, we allow quantitative information on mRNA switching from biophysical experiments or coarse-grain molecular dynamics simulations of mRNA structures to be included in gene regulatory chemical reaction network models without an increase in the number of species. Thereby, our model bridges a gap between mRNA structure kinetics and gene expression models, which we hope will further improve our understanding of gene regulatory networks and facilitate genetic circuit design.

Mapping of the influenza A virus genome RNA structure and interactions reveals essential elements of viral replication

Influenza A virus (IAV) represents a constant public health threat. The single-stranded, segmented RNA genome of IAV is replicated in host cell nuclei as a series of 8 ribonucleoprotein complexes (vRNPs) with RNA structures known to exert essential function to support viral replication. Here, we investigate RNA secondary structures and RNA interactions networks of the IAV genome and construct an in vivo structure model for each of the 8 IAV genome segments. Our analyses reveal an overall in vivo and in virio resemblance of the IAV genome conformation but also wide disparities among long-range and intersegment interactions. Moreover, we identify a long-range RNA interaction that exerts an essential role in genome packaging. Disrupting this structure displays reduced infectivity, attenuating virus pathogenicity in mice. Our findings characterize the in vivo RNA structural landscape of the IAV genome and reveal viral RNA structures that can be targeted to develop antiviral interventions.

Cross-evaluation of E. coli's operon structures via a whole-cell model suggests alternative cellular benefits for low- versus high-expressing operons

Many bacteria use operons to coregulate genes, but it remains unclear how operons benefit bacteria. We integrated E. coli's 788 polycistronic operons and 1,231 transcription units into an existing whole-cell model and found inconsistencies between the proposed operon structures and the RNA-seq read counts that the model was parameterized from. We resolved these inconsistencies through iterative, model-guided corrections to both datasets, including the correction of RNA-seq counts of short genes that were misreported as zero by existing alignment algorithms. The resulting model suggested two main modes by which operons benefit bacteria. For 86% of low-expression operons, adding operons increased the co-expression probabilities of their constituent proteins, whereas for 92% of high-expression operons, adding operons resulted in more stable expression ratios between the proteins. These simulations underscored the need for further experimental work on how operons reduce noise and synchronize both the expression timing and the quantity of constituent genes. A record of this paper's transparent peer review process is included in the supplemental information.

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.

Causes, functions, and therapeutic possibilities of RNA secondary structure ensembles and alternative states

RNA secondary structure plays essential roles in encoding RNA regulatory fate and function. Most RNAs populate ensembles of alternatively paired states and are continually unfolded and refolded by cellular processes. Measuring these structural ensembles and their contributions to cellular function has traditionally posed major challenges, but new methods and conceptual frameworks are beginning to fill this void. In this review, we provide a mechanism- and function-centric compendium of the roles of RNA secondary structural ensembles and minority states in regulating the RNA life cycle, from transcription to degradation. We further explore how dysregulation of RNA structural ensembles contributes to human disease and discuss the potential of drugging alternative RNA states to therapeutically modulate RNA activity. The emerging paradigm of RNA structural ensembles as central to RNA function provides a foundation for a deeper understanding of RNA biology and new therapeutic possibilities.

Genetic components of Escherichia coli involved in its complex prey-predator interaction with Myxococcus xanthus

Myxococcus xanthus and Escherichia coli represent a well-studied microbial predator-prey pair frequently examined in laboratory settings. While significant progress has been made in comprehending the mechanisms governing M. xanthus predation, various aspects of the response and defensive mechanisms of E. coli as prey remain elusive. In this study, the E. coli MG1655 large-scale chromosome deletion library was screened, and a mutant designated as ME5012 was identified to possess significantly reduced susceptibility to predation by M. xanthus. Within the deleted region of ME5012 encompassing seven genes, the significance of dusB and fis genes in driving the observed phenotype became apparent. Specifically, the deletion of fis resulted in a notable reduction in flagellum production in E. coli, contributing to a certain level of resistance against predation by M. xanthus. Meanwhile, the removal of dusB in E. coli led to diminished inducibility of myxovirescin A production by M. xanthus, accompanied by a slight decrease in susceptibility to myxovirescin A. These findings shed light on the molecular mechanisms underlying the complex interaction between M. xanthus and E. coli in a predatory context.

Molecular bases for strong phenotypic effects of single synonymous codon substitutions in the E. coli ccdB toxin gene

BACKGROUND

Single synonymous codon mutations typically have only minor or no effects on gene function. Here, we estimate the effects on cell growth of ~ 200 single synonymous codon mutations in an operonic context by mutating almost all positions of ccdB, the 101-residue long cytotoxin of the ccdAB Toxin-Antitoxin (TA) operon to most degenerate codons. Phenotypes were assayed by transforming the mutant library into CcdB sensitive and resistant E. coli strains, isolating plasmid pools, and subjecting them to deep sequencing. Since autoregulation is a hallmark of TA operons, phenotypes obtained for ccdB synonymous mutants after transformation in a RelE toxin reporter strain followed by deep sequencing provided information on the amount of CcdAB complex formed.

RESULTS

Synonymous mutations in the N-terminal region involved in translation initiation showed the strongest non-neutral phenotypic effects. We observe an interplay of numerous factors, namely, location of the codon, codon usage, t-RNA abundance, formation of anti-Shine Dalgarno sequences, predicted transcript secondary structure, and evolutionary conservation in determining phenotypic effects of ccdB synonymous mutations. Incorporation of an N-terminal, hyperactive synonymous mutation, in the background of the single synonymous codon mutant library sufficiently increased translation initiation, such that mutational effects on either folding or termination of translation became more apparent. Introduction of putative pause sites not only affects the translational rate, but might also alter the folding kinetics of the protein in vivo.

CONCLUSION

In summary, the study provides novel insights into diverse mechanisms by which synonymous mutations modulate gene function. This information is useful in optimizing heterologous gene expression in E. coli and understanding the molecular bases for alteration in gene expression that arise due to synonymous mutations.

Research progress in mRNA drug modification and delivery systems

Messenger RNA (mRNA) has shown tremendous potential in disease prevention and therapy. The clinical application requires mRNA with enhanced stability and high translation efficiency, ensuring it not to be degraded by nucleases and targeting to specific tissues and cells. mRNA immunogenicity can be reduced by nucleotide modification, and translation efficiency can be enhanced by codon optimization. The 5´ capping structure and 3´ poly A increase mRNA stability, and the addition of 5' and 3' non-translational regions regulate mRNA translation initiation and protein production. Nanoparticle delivery system protects mRNA from degradation by ubiquitous nucleases, enhances mRNA concentration in circulation and assists it cytoplasmic entrance for the purpose of treatment and prevention. Here, we review the recent advances of mRNA technology, discuss the methods and principles to enhance mRNA stability and translation efficiency; summarize the requirements involved in designing mRNA delivery systems with the potential for industrial translation and biomedical application. Furthermore, we provide insights into future directions of mRNA therapeutics to meet the needs for personalized precision medicine.

Internal transcription termination widely regulates differential expression of operon-organized genes including ribosomal protein and RNA polymerase genes in an archaeon

Genes organized within operons in prokaryotes benefit from coordinated expression. However, within many operons, genes are expressed at different levels, and the mechanisms for this remain obscure. By integrating PacBio-seq, dRNA-seq, Term-seq and Illumina-seq data of a representative archaeon Methanococcus maripaludis, internal transcription termination sites (ioTTSs) were identified within 38% of operons. Higher transcript and protein abundances were found for genes upstream than downstream of ioTTSs. For representative operons, these differences were confirmed by northern blotting, qRT-PCR and western blotting, demonstrating that these ioTTS terminations were functional. Of special interest, mutation of ioTTSs in ribosomal protein (RP)-RNA polymerase (RNAP) operons not only elevated expression of the downstream RNAP genes but also decreased production of the assembled RNAP complex, slowed whole cell transcription and translation, and inhibited growth. Overexpression of the RNAP subunits with a shuttle vector generated the similar physiological effects. Therefore, ioTTS termination is a general and physiologically significant regulatory mechanism of the operon gene expression. Because the RP-RNAP operons are found to be widely distributed in archaeal species, this regulatory mechanism could be commonly employed in archaea.

Natural variation in codon bias and mRNA folding strength interact synergistically to modify protein expression in Saccharomyces cerevisiae

Codon bias and mRNA folding strength (mF) are hypothesized molecular mechanisms by which polymorphisms in genes modify protein expression. Natural patterns of codon bias and mF across genes as well as effects of altering codon bias and mF suggest that the influence of these 2 mechanisms may vary depending on the specific location of polymorphisms within a transcript. Despite the central role codon bias and mF may play in natural trait variation within populations, systematic studies of how polymorphic codon bias and mF relate to protein expression variation are lacking. To address this need, we analyzed genomic, transcriptomic, and proteomic data for 22 Saccharomyces cerevisiae isolates, estimated protein accumulation for each allele of 1,620 genes as the log of protein molecules per RNA molecule (logPPR), and built linear mixed-effects models associating allelic variation in codon bias and mF with allelic variation in logPPR. We found that codon bias and mF interact synergistically in a positive association with logPPR, and this interaction explains almost all the effects of codon bias and mF. We examined how the locations of polymorphisms within transcripts influence their effects and found that codon bias primarily acts through polymorphisms in domain-encoding and 3' coding sequences, while mF acts most significantly through coding sequences with weaker effects from untranslated regions. Our results present the most comprehensive characterization to date of how polymorphisms in transcripts influence protein expression.

Led-Seq: ligation-enhanced double-end sequence-based structure analysis of RNA

Structural analysis of RNA is an important and versatile tool to investigate the function of this type of molecules in the cell as well as in vitro. Several robust and reliable procedures are available, relying on chemical modification inducing RT stops or nucleotide misincorporations during reverse transcription. Others are based on cleavage reactions and RT stop signals. However, these methods address only one side of the RT stop or misincorporation position. Here, we describe Led-Seq, a new approach based on lead-induced cleavage of unpaired RNA positions, where both resulting cleavage products are investigated. The RNA fragments carrying 2', 3'-cyclic phosphate or 5'-OH ends are selectively ligated to oligonucleotide adapters by specific RNA ligases. In a deep sequencing analysis, the cleavage sites are identified as ligation positions, avoiding possible false positive signals based on premature RT stops. With a benchmark set of transcripts in Escherichia coli, we show that Led-Seq is an improved and reliable approach based on metal ion-induced phosphodiester hydrolysis to investigate RNA structures in vivo.

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.

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

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

The Influence of the Nucleotide Composition of Genes and Gene Regulatory Elements on the Efficiency of Protein Expression in Escherichia coli

Recombinant proteins expressed in Escherichia coli are widely used in biochemical research and industrial processes. At the same time, achieving higher protein expression levels and correct protein folding still remains the key problem, since optimization of nutrient media, growth conditions, and methods for induction of protein synthesis do not always lead to the desired result. Often, low protein expression is determined by the sequences of the expressed genes and their regulatory regions. The genetic code is degenerated; 18 out of 20 amino acids are encoded by more than one codon. Choosing between synonymous codons in the coding sequence can significantly affect the level of protein expression and protein folding due to the influence of the gene nucleotide composition on the probability of formation of secondary mRNA structures that affect the ribosome binding at the translation initiation phase, as well as the ribosome movement along the mRNA during elongation, which, in turn, influences the mRNA degradation and the folding of the nascent protein. The nucleotide composition of the mRNA untranslated regions, in particular the promoter and Shine-Dalgarno sequences, also affects the efficiency of mRNA transcription, translation, and degradation. In this review, we describe the genetic principles that determine the efficiency of protein production in Escherichia coli.

Reconstitution of Multi-Protein Complexes through Ribozyme-Assisted Polycistronic Co-Expression

In living cells, proteins often exert their functions by interacting with other proteins forming protein complexes. Obtaining homogeneous samples of protein complexes with correct fold and stoichiometry is critical for its biochemical and biophysical characterization as well as functional investigation. Here, we developed a Ribozyme-Assisted Polycistronic co-expression system (pRAP) for heterologous co-production and in vivo assembly of multi-subunit complexes. In the pRAP system, a polycistronic mRNA transcript is co-transcriptionally converted into individual mono-cistrons in vivo. Each cistron can initiate translation with comparable efficiency, resulting in balanced production for all subunits, thus permitting faithful protein complex assembly. With pRAP polycistronic co-expression, we have successfully reconstituted large functional multi-subunit complexes involved in mammalian translation initiation. Our invention provides a valuable tool for studying the molecular mechanisms of biological processes.

Predicting RNA secondary structure by a neural network: what features may be learned?

Deep learning is a class of machine learning techniques capable of creating internal representation of data without explicit preprogramming. Hence, in addition to practical applications, it is of interest to analyze what features of biological data may be learned by such models. Here, we describe PredPair, a deep learning neural network trained to predict base pairs in RNA structure from sequence alone, without any incorporated prior knowledge, such as the stacking energies or possible spatial structures. PredPair learned the Watson-Crick and wobble base-pairing rules and created an internal representation of the stacking energies and helices. Application to independent experimental (DMS-Seq) data on nucleotide accessibility in mRNA showed that the nucleotides predicted as paired indeed tend to be involved in the RNA structure. The performance of the constructed model was comparable with the state-of-the-art method based on the thermodynamic approach, but with a higher false positives rate. On the other hand, it successfully predicted pseudoknots. t-SNE clusters of embeddings of RNA sequences created by PredPair tend to contain embeddings from particular Rfam families, supporting the predictions of PredPair being in line with biological classification.

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.

INRI-seq enables global cell-free analysis of translation initiation and off-target effects of antisense inhibitors

Ribosome profiling (Ribo-seq) is a powerful method for the transcriptome-wide assessment of protein synthesis rates and the study of translational control mechanisms. Yet, Ribo-seq also has limitations. These include difficulties with the analysis of translation-modulating molecules such as antibiotics, which are often toxic or challenging to deliver into living cells. Here, we have developed in vitro Ribo-seq (INRI-seq), a cell-free method to analyze the translational landscape of a fully customizable synthetic transcriptome. Using Escherichia coli as an example, we show how INRI-seq can be used to analyze the translation initiation sites of a transcriptome of interest. We also study the global impact of direct translation inhibition by antisense peptide nucleic acid (PNA) to analyze PNA off-target effects. Overall, INRI-seq presents a scalable, sensitive method to study translation initiation in a transcriptome-wide manner without the potentially confounding effects of extracting ribosomes from living cells.

Bioinformatic Assessment of Factors Affecting the Correlation between Protein Abundance and Elongation Efficiency in Prokaryotes

Protein abundance is crucial for the majority of genetically regulated cell functions to act properly in prokaryotic organisms. Therefore, developing bioinformatic methods for assessing the efficiency of different stages of gene expression is of great importance for predicting the actual protein abundance. One of these steps is the evaluation of translation elongation efficiency based on mRNA sequence features, such as codon usage bias and mRNA secondary structure properties. In this study, we have evaluated correlation coefficients between experimentally measured protein abundance and predicted elongation efficiency characteristics for 26 prokaryotes, including non-model organisms, belonging to diverse taxonomic groups The algorithm for assessing elongation efficiency takes into account not only codon bias, but also number and energy of secondary structures in mRNA if those demonstrate an impact on predicted elongation efficiency of the ribosomal protein genes. The results show that, for a number of organisms, secondary structures are a better predictor of protein abundance than codon usage bias. The bioinformatic analysis has revealed several factors associated with the value of the correlation coefficient. The first factor is the elongation efficiency optimization type-the organisms whose genomes are optimized for codon usage only have significantly higher correlation coefficients. The second factor is taxonomical identity-bacteria that belong to the class Bacilli tend to have higher correlation coefficients among the analyzed set. The third is growth rate, which is shown to be higher for the organisms with higher correlation coefficients between protein abundance and predicted translation elongation efficiency. The obtained results can be useful for further improvement of methods for protein abundance prediction.

Chaperone Requirements for De Novo Folding of Saccharomyces cerevisiae Septins

Polymers of septin protein complexes play cytoskeletal roles in eukaryotic cells. The specific subunit composition within complexes controls functions and higher-order structural properties. All septins have globular GTPase domains. The other eukaryotic cytoskeletal NTPases strictly require assistance from molecular chaperones of the cytosol, particularly the cage-like chaperonins, to fold into oligomerization-competent conformations. We previously identified cytosolic chaperones that bind septins and influence the oligomerization ability of septins carrying mutations linked to human disease, but it was unknown to what extent wild-type septins require chaperone assistance for their native folding. Here we use a combination of in vivo and in vitro approaches to demonstrate chaperone requirements for de novo folding and complex assembly by budding yeast septins. Individually purified septins adopted non-native conformations and formed non-native homodimers. In chaperonin- or Hsp70-deficient cells, septins folded slower and were unable to assemble post-translationally into native complexes. One septin, Cdc12, was so dependent on co-translational chaperonin assistance that translation failed without it. Our findings point to distinct translation elongation rates for different septins as a possible mechanism to direct a stepwise, co-translational assembly pathway in which general cytosolic chaperones act as key intermediaries.

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.

Polar mutagenesis of polycistronic bacterial transcriptional units using Cas12a

Background

Functionally related genes in bacteria are often organized and transcribed as polycistronic transcriptional units. Examples are the fim operon, which codes for biogenesis of type 1 fimbriae in Escherichia coli, and the atp operon, which codes for the FoF1 ATP synthase. We tested the hypothesis that markerless polar mutations could be efficiently engineered using CRISPR/Cas12a in these loci.

Results

Cas12a-mediated engineering of a terminator sequence inside the fimA gene occurred with efficiencies between 10 and 80% and depended on the terminator’s sequence, whilst other types of mutations, such as a 97 bp deletion, occurred with 100% efficiency. Polar mutations using a terminator sequence were also engineered in the atp locus, which induced its transcriptional shutdown and produced identical phenotypes as a deletion of the whole atp locus (ΔatpIBEFHAGDC). Measuring the expression levels in the fim and atp loci showed that many supposedly non-polar mutants induced a significant polar effect on downstream genes. Finally, we also showed that transcriptional shutdown or deletion of the atp locus induces elevated levels of intracellular ATP during the exponential growth phase.

Conclusions

We conclude that Cas12a-mediated mutagenesis is an efficient simple system to generate polar mutants in E. coli. Different mutations were induced with varying degrees of efficiency, and we confirmed that all these mutations abolished the functions encoded in the fim and atp loci. We also conclude that it is difficult to predict which mutagenesis strategy will induce a polar effect in genes downstream of the mutation site. Furthermore the strategies described here can be used to manipulate the metabolism of E. coli as showcased by the increase in intracellular ATP in the markerless ΔatpIBEFHAGDC mutant.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12934-022-01844-y.

Translation initiation site of mRNA is selected through dynamic interaction with the ribosome

SignificanceRibosomes translate the genetic codes of messenger RNA (mRNA) to make proteins. Translation must begin at the correct initiation site; otherwise, abnormal proteins will be produced. Here, we show that a short ribosome-specific sequence in the upstream followed by an unstructured downstream sequence is a favorable initiation site. Those mRNAs lacking either of these two characteristics do not associate tightly with the ribosome. Initiator transfer RNA (tRNA) and initiation factors facilitate the binding. However, when the downstream site forms structures, initiation factor 3 triggers the dissociation of the accommodated initiator tRNA and the subsequent disassembly of the ribosome-mRNA complex. Thus, initiation factors help the ribosome distinguish unfavorable structured sequences that may not act as the mRNA translation initiation site.

An overview of gene regulation in bacteria by small RNAs derived from mRNA 3' ends

Over the past two decades, small noncoding RNAs (sRNAs) that regulate mRNAs by short base pairing have gone from a curiosity to a major class of post-transcriptional regulators in bacteria. They are integral to many stress responses and regulatory circuits, affecting almost all aspects of bacterial life. Following pioneering sRNA searches in the early 2000s, the field quickly focused on conserved sRNA genes in the intergenic regions of bacterial chromosomes. Yet, it soon emerged that there might be another rich source of bacterial sRNAs—processed 3′ end fragments of mRNAs. Several such 3′ end-derived sRNAs have now been characterized, often revealing unexpected, conserved functions in diverse cellular processes. Here, we review our current knowledge of these 3′ end-derived sRNAs—their biogenesis through ribonucleases, their molecular mechanisms, their interactions with RNA-binding proteins such as Hfq or ProQ and their functional scope, which ranges from acting as specialized regulators of single metabolic genes to constituting entire noncoding arms in global stress responses. Recent global RNA interactome studies suggest that the importance of functional 3′ end-derived sRNAs has been vastly underestimated and that this type of cross-regulation between genes at the mRNA level is more pervasive in bacteria than currently appreciated.

Probing in vivo RNA Structure With Optimized DMS-MaPseq in Rice

RNA transcripts form various secondary and tertiary structures that have a wide range of regulatory functions. Several methods have been developed to profile in vivo RNA secondary structure in prokaryotes and eukaryotes. These methods, such as dimethyl sulfate (DMS) mutational profiling with high-throughput sequencing (DMS-MaPseq), couple small chemical-mediated RNA modifications with next-generation sequencing. DMS-MaPseq, a powerful method for genome-wide and target-specific RNA secondary structure profiling, has been applied in yeast, mammals, Drosophila, and Arabidopsis thaliana, but not in crops. Here, we used DMS-MaPseq to conduct a target-specific and genome-wide profile of in vivo RNA secondary structure in rice (Oryza sativa). The DMS treatment conditions were optimized for rice leaf and root tissues. To increase the sequencing depth and coverage of low-abundance transcripts in genome-wide DMS-MaPseq, we used streptavidin-biotin depletion to reduce the abundance of highly expressed chloroplast transcripts during library construction. The resulting target-specific and genome-wide rice DMS-MaPseq data were of high quality and reproducibility. Furthermore, we used DMS-MaPseq to profile the in vivo RNA secondary structure of an OsmiR399 target region located at 5'UTR of OsPHO2, which participates in rice phosphate homeostasis. An unfolded RNA structure downstream of miRNA target site was observed in predicted in vivo RNA secondary structure, reminiscence of the TAM (Target Adjacent nucleotide Motif) involved in mRNA structure-mediated regulation in miRNA cleavage. Our study optimized DMS-MaPseq for probing in vivo RNA secondary structure in rice, facilitating the study of RNA structure-mediated regulations in crops.

Quality control of protein complex assembly by the ubiquitin-proteasome system

The majority of human proteins operate as multimeric complexes with defined compositions and distinct architectures. How the assembly of these complexes is surveyed and how defective complexes are recognized is just beginning to emerge. In eukaryotes, over 600 E3 ubiquitin ligases form part of the ubiquitin-proteasome system (UPS) which detects structural characteristics in its target proteins and selectively induces their degradation. The UPS has recently been shown to oversee key quality control steps during the assembly of protein complexes. We review recent findings on how E3 ubiquitin ligases regulate protein complex assembly and highlight unanswered questions relating to their mechanism of action.

Specific length and structure rather than high thermodynamic stability enable regulatory mRNA stem-loops to pause translation

Translating ribosomes unwind mRNA secondary structures by three basepairs each elongation cycle. Despite the ribosome helicase, certain mRNA stem-loops stimulate programmed ribosomal frameshift by inhibiting translation elongation. Here, using mutagenesis, biochemical and single-molecule experiments, we examine whether high stability of three basepairs, which are unwound by the translating ribosome, is critical for inducing ribosome pauses. We find that encountering frameshift-inducing mRNA stem-loops from the E. coli dnaX mRNA and the gag-pol transcript of Human Immunodeficiency Virus (HIV) hinders A-site tRNA binding and slows down ribosome translocation by 15-20 folds. By contrast, unwinding of first three basepairs adjacent to the mRNA entry channel slows down the translating ribosome by only 2-3 folds. Rather than high thermodynamic stability, specific length and structure enable regulatory mRNA stem-loops to stall translation by forming inhibitory interactions with the ribosome. Our data provide the basis for rationalizing transcriptome-wide studies of translation and searching for novel regulatory mRNA stem-loops.

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.

Relating Translation Efficiency to Protein Networks Provides Evolutionary Insights in Shewanella and Its Implications for Extracellular Electron Transfer

Shewanella species are well-known for their extracellular electron transfer (EET) capacity, by which these microorganisms can transfer the electrons from intracellular environment to extracellular space for the reduction of the extracellular insoluble electron acceptors. Using a time-stamped data for the paired protein-mRNA, we investigate the impact of differential translation on the EET process of Shewanella oneidensis MR-1. Firstly, differentially translated proteins when O₂ levels are switched from high-O₂ to low-O₂ are identified by using a soft clustering method, 629 up-regulated translated proteins and 767 down-regulated translated proteins are considered to reflect the changes from inactivated to activated EET process. Then, we showed that the degrees of connectivity of differentially translated proteins were significantly larger than those of non-differentially translated proteins, and thereby these differentially translated proteins will be more important in the protein networks. After that, we networked these differentially translated proteins to construct the differentially translated sub-networks, and discussed the most important proteins that are involved in the EET process with the help of centralization analysis of these differentially translated networks. Furthermore, we also studied the differentially translated operonic genes. Taking together, this work searches the key proteins that potentially activated the EET process from a translational efficiency viewpoint.

Evolutionary repair reveals an unexpected role of the tRNA modification m1G37 in aminoacylation

The tRNA modification m¹G37, introduced by the tRNA methyltransferase TrmD, is thought to be essential for growth in bacteria because it suppresses translational frameshift errors at proline codons. However, because bacteria can tolerate high levels of mistranslation, it is unclear why loss of m¹G37 is not tolerated. Here, we addressed this question through experimental evolution of trmD mutant strains of Escherichia coli. Surprisingly, trmD mutant strains were viable even if the m¹G37 modification was completely abolished, and showed rapid recovery of growth rate, mainly via duplication or mutation of the proline-tRNA ligase gene proS. Growth assays and in vitro aminoacylation assays showed that G37-unmodified tRNA^Pro is aminoacylated less efficiently than m¹G37-modified tRNA^Pro, and that growth of trmD mutant strains can be largely restored by single mutations in proS that restore aminoacylation of G37-unmodified tRNA^Pro. These results show that inefficient aminoacylation of tRNA^Pro is the main reason for growth defects observed in trmD mutant strains and that proS may act as a gatekeeper of translational accuracy, preventing the use of error-prone unmodified tRNA^Pro in translation. Our work shows the utility of experimental evolution for uncovering the hidden functions of essential genes and has implications for the development of antibiotics targeting TrmD.

Global Analysis of the Specificities and Targets of Endoribonucleases from Escherichia coli Toxin-Antitoxin Systems

Toxin-antitoxin systems are widely distributed genetic modules typically featuring toxins that can inhibit bacterial growth and antitoxins that can reverse inhibition. Although Escherichia coli encodes 11 toxins with known or putative endoribonuclease activity, the targets of most of these toxins remain poorly characterized. Using a new RNA sequencing (RNA-seq) pipeline that enables the mapping and quantification of RNA cleavage with single-nucleotide resolution, we characterized the targets and specificities of 9 endoribonuclease toxins from E. coli. We found that these toxins use low-information cleavage motifs to cut a significant proportion of mRNAs in E. coli, but not tRNAs or the rRNAs from mature ribosomes. However, all the toxins, including those that are ribosome dependent and cleave only translated RNA, inhibit ribosome biogenesis. This inhibition likely results from the cleavage of ribosomal protein transcripts, which disrupts the stoichiometry and biogenesis of new ribosomes and causes the accumulation of aberrant ribosome precursors. Collectively, our results provide a comprehensive, global analysis of endoribonuclease-based toxin-antitoxin systems in E. coli and support the conclusion that, despite their diversity, each disrupts translation and ribosome biogenesis.

Analysis of 11,430 recombinant protein production experiments reveals that protein yield is tunable by synonymous codon changes of translation initiation sites

Recombinant protein production is a key process in generating proteins of interest in the pharmaceutical industry and biomedical research. However, about 50% of recombinant proteins fail to be expressed in a variety of host cells. Here we show that the accessibility of translation initiation sites modelled using the mRNA base-unpairing across the Boltzmann's ensemble significantly outperforms alternative features. This approach accurately predicts the successes or failures of expression experiments, which utilised Escherichia coli cells to express 11,430 recombinant proteins from over 189 diverse species. On this basis, we develop TIsigner that uses simulated annealing to modify up to the first nine codons of mRNAs with synonymous substitutions. We show that accessibility captures the key propensity beyond the target region (initiation sites in this case), as a modest number of synonymous changes is sufficient to tune the recombinant protein expression levels. We build a stochastic simulation model and show that higher accessibility leads to higher protein production and slower cell growth, supporting the idea of protein cost, where cell growth is constrained by protein circuits during overexpression.

Regulation of gene expression via translational buffering

Translation of an mRNA represents a critical step during the expression of protein-coding genes. As mechanisms governing post-transcriptional regulation of gene expression are progressively unveiled, it is becoming apparent that transcriptional programs are not fully reflected in the proteome. Herein, we highlight a previously underappreciated post-transcriptional mode of regulation of gene expression termed translational buffering. In principle, translational buffering opposes the impact of alterations in mRNA levels on the proteome. We further describe three types of translational buffering: compensation, which maintains protein levels e.g. across species or individuals; equilibration, which retains pathway stoichiometry; and offsetting, which acts as a reversible mechanism that maintains the levels of selected subsets of proteins constant despite genetic alteration and/or stress-induced changes in corresponding mRNA levels. While mechanisms underlying compensation and equilibration have been reviewed elsewhere, the principal focus of this review is on the less-well understood mechanism of translational offsetting. Finally, we discuss potential roles of translational buffering in homeostasis and disease.

The Classical, Yet Controversial, First Enzyme of Lipid Synthesis: Escherichia coli Acetyl-CoA Carboxylase

Escherichia coli acetyl-CoA carboxylase (ACC), the enzyme responsible for synthesis of malonyl-CoA, the building block of fatty acid synthesis, is the paradigm bacterial ACC. Many reports on the structures and stoichiometry of the four subunits comprising the active enzyme as well as on regulation of ACC activity and expression have appeared in the almost 20 years since this subject was last reviewed. This review seeks to update and expand on these reports.

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.

Ribosomal RNA degradation induced by the bacterial RNA polymerase inhibitor rifampicin

Rifampicin, a broad-spectrum antibiotic, inhibits bacterial RNA polymerase. Here we show that rifampicin treatment of Escherichia coli results in a 50% decrease in cell size due to a terminal cell division. This decrease is a consequence of inhibition of transcription as evidenced by an isogenic rifampicin-resistant strain. There is also a 50% decrease in total RNA due mostly to a 90% decrease in 23S and 16S rRNA levels. Control experiments showed this decrease is not an artifact of our RNA purification protocol and therefore due to degradation in vivo. Since chromosome replication continues after rifampicin treatment, ribonucleotides from rRNA degradation could be recycled for DNA synthesis. Rifampicin-induced rRNA degradation occurs under different growth conditions and in different strain backgrounds. However, rRNA degradation is never complete thus permitting the re-initiation of growth after removal of rifampicin. The orderly shutdown of growth under conditions where the induction of stress genes is blocked by rifampicin is noteworthy. Inhibition of protein synthesis by chloramphenicol resulted in a partial decrease in 23S and 16S rRNA levels whereas kasugamycin treatment had no effect. Analysis of temperature-sensitive mutant strains implicate RNase E, PNPase and RNase R in rifampicin-induced rRNA degradation. We cannot distinguish between a direct role for RNase E in rRNA degradation versus an indirect role involving a slowdown of mRNA degradation. Since mRNA and rRNA appear to be degraded by the same ribonucleases, competition by rRNA is likely to result in slower mRNA degradation rates in the presence of rifampicin than under normal growth conditions.

An antisense noncoding RNA enhances translation via localized structural rearrangements of its cognate mRNA

A large portion of eukaryotic genes are associated with noncoding, natural antisense transcripts (NATs). Despite sharing extensive sequence complementarity with their sense mRNAs, mRNA-NAT pairs elusively often evade dsRNA-cleavage and siRNA-triggered silencing. More surprisingly, some NATs enhance translation of their sense mRNAs by yet unknown mechanism(s). Here, we show that translation enhancement of the rice (Oryza sativa) PHOSPHATE1.2 (PHO1.2) mRNA is enabled by specific structural rearrangements guided by its noncoding antisense RNA (cis-NATpho1.2). Their interaction in vitro revealed no evidence of widespread intermolecular dsRNA formation, but rather specific local changes in nucleotide base pairing, leading to higher flexibility of PHO1.2 mRNA at a key high guanine-cytosine�(GC) regulatory region inhibiting translation, ∼350-nt downstream of the start codon. Sense-antisense RNA interaction increased formation of the 80S complex in PHO1.2, possibly by inducing structural rearrangement within this inhibitory region, thus making this mRNA more accessible to 60S. This work presents a framework for nucleotide resolution studies of functional mRNA-antisense pairs.

Sigma factor dependent translational activation in Bacillus subtilis

Sigma factors are an important class of bacterial transcription factors that lend specificity to RNA polymerases by binding to distinct promoter elements for genes in their regulons. Here we show that activation of the general stress sigma factor, σB, in Bacillus subtilis paradoxically leads to dramatic induction of translation for a subset of its regulon genes. These genes are translationally repressed when transcribed by the housekeeping sigma factor, σA, owing to extended RNA secondary structures as determined in vivo using DMS-MaPseq. Transcription from σB-dependent promoters ablates the secondary structures and activates translation, leading to dual induction. Translation efficiencies between σB- and σA-dependent RNA isoforms can vary by up to 100-fold, which in multiple cases exceeds the magnitude of transcriptional induction. These results highlight the role of long-range RNA folding in modulating translation and demonstrate that a transcription factor can regulate protein synthesis beyond its effects on transcript levels.

An mRNA-mRNA Interaction Couples Expression of a Virulence Factor and Its Chaperone in Listeria monocytogenes

Bacterial pathogens often employ RNA regulatory elements located in the 5' untranslated regions (UTRs) to control gene expression. Using a comparative structural analysis, we examine the structure of 5' UTRs at a global scale in the pathogenic bacterium Listeria monocytogenes under different conditions. In addition to discovering an RNA thermoswitch and detecting simultaneous interaction of ribosomes and small RNAs with mRNA, we identify structural changes in the 5' UTR of an mRNA encoding the post-translocation chaperone PrsA2 during infection conditions. We demonstrate that the 5' UTR of the prsA2 mRNA base pairs with the 3' UTR of the full-length hly mRNA encoding listeriolysin O, thus preventing RNase J1-mediated degradation of the prsA2 transcript. Mutants lacking the hly-prsA2 interaction exhibit reduced virulence properties. This work highlights an additional level of RNA regulation, where the mRNA encoding a chaperone is stabilized by the mRNA encoding its substrate.

Post-transcriptional regulation is involved in the cold-active methanol-based methanogenic pathway of a psychrophilic methanogen

The methanol-derived methanogenetic pathway contributes to bulk methane production in cold regions, but the cold adaptation mechanisms are obscure. This work investigated the mechanisms using a psychrophilic methylotrophic methanogen Methanolobus psychrophilus R15. R15 possesses two mtaCB operon paralogues-encoding methanol:corrinoid methyltransferase that is key to methanol-based methanogenesis. Molecular combined methanogenic assays determined that MtaC1 is important in methanogenesis at the optimal temperature of 18°C, but MtaC2 can be a cold-adaptive paralogue by highly upregulated at 8°C. The 5'P-seq and 5'RACE all assayed that processing occurred at the 5' untranslated region (5'-UTR) of mtaC2; reporter genes detected higher protein expression, and RNA half-life experiments assayed prolonged lifespan of the processed transcript. Therefore, mtaC2 5'-UTR processing to move the bulged structure elevated both the translation efficiency and transcript stability. 5'P-seq, quantitative RT-PCR and northern blot all identified enhanced mtaC2 5'-UTR processing at 8°C, which could contribute to the upregulation of mtaC2 at cold. The R15 cell extract contains an endoribonuclease cleaving an identified 10 nt-processing motif and the native mtaC2 5'-UTR particularly folded at 8°C. Therefore, this study revealed a 5'-UTR processing mediated post-transcriptional regulation mechanism controlling the cold-adaptive methanol-supported methanogenetic pathway, which may be used by other methylotrophic methanogens.

Specificity of RNA Folding and Its Association with Evolutionarily Adaptive mRNA Secondary Structures

The secondary structure is a fundamental feature of both noncoding and messenger RNAs. However, our understanding of the secondary structure of mRNA, especially that of the coding regions, remains elusive, likely due to translation and the lack of RNA-binding proteins that sustain the consensus structure, such as those that bind to noncoding RNA. Indeed, mRNA has recently been found to adopt diverse alternative structures, the overall functional significance of which remains untested. We hereby approached this problem by estimating the folding specificity, i.e., the probability that a fragment of RNA folds back to the same partner once refolded. We showed that the folding specificity of mRNA is lower than that of noncoding RNA and exhibits moderate evolutionary conservation. Notably, we found that specific rather than alternative folding is likely evolutionarily adaptive since specific folding is frequently associated with functionally important genes or sites within a gene. Additional analysis in combination with ribosome density suggests the ability to modulate ribosome movement as one potential functional advantage provided by specific folding. Our findings revealed a novel facet of the RNA structurome with important functional and evolutionary implications and indicated a potential method for distinguishing the mRNA secondary structures maintained by natural selection from molecular noise.

In vivo structural characterization of the SARS-CoV-2 RNA genome identifies host proteins vulnerable to repurposed drugs

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of the ongoing coronavirus disease 2019 (COVID-19) pandemic. Understanding of the RNA virus and its interactions with host proteins could improve therapeutic interventions for COVID-19. By using icSHAPE, we determined the structural landscape of SARS-CoV-2 RNA in infected human cells and from refolded RNAs, as well as the regulatory untranslated regions of SARS-CoV-2 and six other coronaviruses. We validated several structural elements predicted in silico and discovered structural features that affect the translation and abundance of subgenomic viral RNAs in cells. The structural data informed a deep-learning tool to predict 42 host proteins that bind to SARS-CoV-2 RNA. Strikingly, antisense oligonucleotides targeting the structural elements and FDA-approved drugs inhibiting the SARS-CoV-2 RNA binding proteins dramatically reduced SARS-CoV-2 infection in cells derived from human liver and lung tumors. Our findings thus shed light on coronavirus and reveal multiple candidate therapeutics for COVID-19 treatment.

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.

Monitoring Bacterial Translation Rates Genome-Wide

Modern DNA sequencing technologies have allowed for the sequencing of tens of thousands of bacterial genomes. While this explosion of information has brought about new insights into the diversity of the prokaryotic world, much less is known of the identity of proteins encoded within these genomes, as well as their rates of production. The advent of ribosome profiling, or the deep sequencing of ribosome-protected footprints, has recently enabled the systematic evaluation of every protein-coding region in a given experimental condition, the rates of protein production for each gene, and the variability in translation rates across each message. Here, I provide an update to the bacterial ribosome profiling approach, with a particular emphasis on a simplified strategy to reduce cloning time.

The diversity of Shine-Dalgarno sequences sheds light on the evolution of translation initiation

Shine-Dalgarno (SD) sequences, the core element of prokaryotic ribosome-binding sites, facilitate mRNA translation by base-pair interaction with the anti-SD (aSD) sequence of 16S rRNA. In contrast to this paradigm, an inspection of thousands of prokaryotic species unravels tremendous SD sequence diversity both within and between genomes, whereas aSD sequences remain largely static. The pattern has led many to suggest unidentified mechanisms for translation initiation. Here we review known translation-initiation pathways in prokaryotes. Moreover, we seek to understand the cause and consequence of SD diversity through surveying recent advances in biochemistry, genomics, and high-throughput genetics. These findings collectively show: (1) SD:aSD base pairing is beneficial but nonessential to translation initiation. (2) The 5' untranslated region of mRNA evolves dynamically and correlates with organismal phylogeny and ecological niches. (3) Ribosomes have evolved distinct usage of translation-initiation pathways in different species. We propose a model portraying the SD diversity shaped by optimization of gene expression, adaptation to environments and growth demands, and the species-specific prerequisite of ribosomes to initiate translation. The model highlights the coevolution of ribosomes and mRNA features, leading to functional customization of the translation apparatus in each organism.

How Many Messenger RNAs Can Be Translated by the START Mechanism?

Translation initiation is a key step in the protein synthesis stage of the gene expression pathway of all living cells. In this important process, ribosomes have to accurately find the AUG start codon in order to ensure the integrity of the proteome. “Structure Assisted RNA Translation”, or “START”, has been proposed to use stable secondary structures located in the coding sequence to augment start site selection by steric hindrance of the progression of pre-initiation complex on messenger RNA. This implies that such structures have to be located downstream and at on optimal distance from the AUG start codon (i.e., downstream nucleotide +16). In order to assess the importance of the START mechanism in the overall mRNA translation process, we developed a bioinformatic tool to screen coding sequences for such stable structures in a 50 nucleotide-long window spanning the nucleotides from +16 to +65. We screened eight bacterial genomes and six eukaryotic genomes. We found stable structures in 0.6–2.5% of eukaryotic coding sequences. Among these, approximately half of them were structures predicted to form G-quadruplex structures. In humans, we selected 747 structures. In bacteria, the coding sequences from Gram-positive bacteria contained 2.6–4.2% stable structures, whereas the structures were less abundant in Gram-negative bacteria (0.2–2.7%). In contrast to eukaryotes, putative G-quadruplex structures are very rare in the coding sequence of bacteria. Altogether, our study reveals that the START mechanism seems to be an ancient strategy to facilitate the start codon recognition that is used in different kingdoms of life.