Conservation of mRNA secondary structures may filter out mutations in Escherichia coli evolution

"Outlaw" mutations in quasispecies of SARS-CoV-2 inhibit replication

The evolution of SARS-CoV-2, the agent of COVID-19, has been remarkable for its high mutation potential, leading to the appearance of variants. Some mutations have never appeared in the published genomes, which represent consensus, or bona fide genomes. Here we tested the hypothesis that mutations that did not appear in consensus genomes were, in fact, as frequent as the mutations that appeared during the various epidemic episodes, but were not expressed because lethal. To identify these mutations, we analysed the genomes of 90 nasopharyngeal samples and the quasispecies determined by next-generation sequencing. Mutations observed in the quasispecies and not in the consensus genomes were considered to be lethal, what we called "outlaw" mutations. Among these mutations, we analysed the 21 most frequent. Eight of these "outlaws" were in the RNA polymerase and we were able to use a structural biology model and molecular dynamics simulations to demonstrate the functional incapacity of these mutated RNA polymerases. Three other mutations affected the spike, a major protein involved in the pathogenesis of COVID-19. Overall, by analysing the SARS-CoV-2 quasispecies obtained during sequencing, this method made it possible to identify "outlaws," showing areas that could potentially become the target of treatments.

Rock, scissors, paper: How RNA structure informs function

RNA can fold back on itself to adopt a wide range of structures. These range from relatively simple hairpins to intricate 3D folds and can be accompanied by regulatory interactions with both metabolites and macromolecules. The last 50 yr have witnessed elucidation of an astonishing array of RNA structures including transfer RNAs, ribozymes, riboswitches, the ribosome, the spliceosome, and most recently entire RNA structuromes. These advances in RNA structural biology have deepened insight into fundamental biological processes including gene editing, transcription, translation, and structure-based detection and response to temperature and other environmental signals. These discoveries reveal that RNA can be relatively static, like a rock; that it can have catalytic functions of cutting bonds, like scissors; and that it can adopt myriad functional shapes, like paper. We relate these extraordinary discoveries in the biology of RNA structure to the plant way of life. We trace plant-specific discovery of ribozymes and riboswitches, alternative splicing, organellar ribosomes, thermometers, whole-transcriptome structuromes and pan-structuromes, and conclude that plants have a special set of RNA structures that confer unique types of gene regulation. We finish with a consideration of future directions for the RNA structure-function field.

Mechanisms governing codon usage bias and the implications for protein expression in the chloroplast of Chlamydomonas reinhardtii

Chloroplasts possess a considerably reduced genome that is decoded via an almost minimal set of tRNAs. These features make an excellent platform for gaining insights into fundamental mechanisms that govern protein expression. Here, we present a comprehensive and revised perspective of the mechanisms that drive codon selection in the chloroplast of Chlamydomonas reinhardtii and the functional consequences for protein expression. In order to extract this information, we applied several codon usage descriptors to genes with different expression levels. We show that highly expressed genes strongly favor translationally optimal codons, while genes with lower functional importance are rather affected by directional mutational bias. We demonstrate that codon optimality can be deduced from codon-anticodon pairing affinity and, for a small number of amino acids (leucine, arginine, serine, and isoleucine), tRNA concentrations. Finally, we review, analyze, and expand on the impact of codon usage on protein yield, secondary structures of mRNA, translation initiation and termination, and amino acid composition of proteins, as well as cotranslational protein folding. The comprehensive analysis of codon choice provides crucial insights into heterologous gene expression in the chloroplast of C. reinhardtii, which may also be applicable to other chloroplast-containing organisms and bacteria.

Effects of synonymous mutations beyond codon bias: The evidence for adaptive synonymous substitutions from microbial evolution experiments

Synonymous mutations are often assumed to be neutral with respect to fitness because they do not alter the encoded amino acid and so cannot be 'seen' by natural selection. Yet a growing body of evidence suggests that synonymous mutations can have fitness effects that drive adaptive evolution through their impacts on gene expression and protein folding. Here, we review what microbial experiments have taught us about the contribution of synonymous mutations to adaptation. A survey of site-directed mutagenesis experiments reveals the distributions of fitness effects for nonsynonymous and synonymous mutations are more similar, especially for beneficial mutations, than expected if all synonymous mutations were neutral, suggesting they should drive adaptive evolution more often than is typically observed. A review of experimental evolution studies where synonymous mutations have contributed to adaptation shows they can impact fitness through a range of mechanisms including the creation of illicit RNA polymerase binding sites impacting transcription and changes to mRNA folding stability that modulate translation. We suggest that clonal interference in evolving microbial populations may be the reason synonymous mutations play a smaller role in adaptive evolution than expected based on their observed fitness effects. We finish by discussing the impacts of falsely assuming synonymous mutations are neutral and discuss directions for future work exploring the role of synonymous mutations in adaptive evolution.

Structural landscape of the complete genomes of dengue virus serotypes and other viral hemorrhagic fevers

BACKGROUND

With more than 300 million potentially infected people every year, and with the expanded habitat of mosquitoes due to climate change, Dengue virus (DENV) cannot be considered anymore only a tropical disease. The RNA secondary structure is a functional characteristic of RNA viruses, and together with the accumulated high-throughput sequencing data could provide general insights towards understanding virus biology. Here, we profiled the RNA secondary structure of > 7000 complete viral genomes from 11 different species focusing on viral hemorrhagic fevers, including DENV serotypes, EBOV, and YFV.

RESULTS

In our work we demonstrated that the secondary structure and presence of protein-binding domains in the genomes can be used as intrinsic signature to further classify the viruses. With our predictive approach, we achieved high prediction scores of the secondary structure (AUC up to 0.85 with experimental data), and computed consensus secondary structure profiles using hundreds of in silico models. We observed that viruses show different structural patterns, where e.g., DENV-2 and Ebola virus tend to be less structured than the other viruses. Furthermore, we observed virus-specific correlations between secondary structure and the number of interaction sites with human proteins, reaching a correlation of 0.89 in the case of Zika virus. We also identified that helicases-encoding regions are more structured in several flaviviruses, while the regions encoding for the contact proteins exhibit virus-specific clusters in terms of RNA structure and potential protein-RNA interactions. We also used structural data to study the geographical distribution of DENV, finding a significant difference between DENV-3 from Asia and South-America, where the structure is also driving the clustering more than sequence identity, which could imply different evolutionary routes of this subtype.

CONCLUSIONS

Our massive computational analysis provided novel results regarding the secondary structure and the interaction with human proteins, not only for DENV serotypes, but also for other flaviviruses and viral hemorrhagic fevers-associated viruses. We showed how the RNA secondary structure can be used to categorise viruses, and even to further classify them based on the interaction with proteins. We envision that these approaches can be used to further classify and characterise these complex viruses.

MutaRNA: analysis and visualization of mutation-induced changes in RNA structure

RNA molecules fold into complex structures as a result of intramolecular interactions between their nucleotides. The function of many non-coding RNAs and some cis-regulatory elements of messenger RNAs highly depends on their fold. Single-nucleotide variants (SNVs) and other types of mutations can disrupt the native function of an RNA element by altering its base pairing pattern. Identifying the effect of a mutation on an RNA’s structure is, therefore, a crucial step in evaluating the impact of mutations on the post-transcriptional regulation and function of RNAs within the cell. Even though a single nucleotide variation can have striking impacts on the structure formation, interpreting and comparing the impact usually needs expertise and meticulous efforts. Here, we present MutaRNA, a web server for visualization and interpretation of mutation-induced changes on the RNA structure in an intuitive and integrative fashion. To this end, probabilities of base pairing and position-wise unpaired probabilities of wildtype and mutated RNA sequences are computed and compared. Differential heatmap-like dot plot representations in combination with circular plots and arc diagrams help to identify local structure abberations, which are otherwise hidden in standard outputs. Eventually, MutaRNA provides a comprehensive and comparative overview of the mutation-induced changes in base pairing potentials and accessibility. The MutaRNA web server is freely available at http://rna.informatik.uni-freiburg.de/MutaRNA.

A pan-cancer analysis of synonymous mutations

Synonymous mutations have been viewed as silent mutations, since they only affect the DNA and mRNA, but not the amino acid sequence of the resulting protein. Nonetheless, recent studies suggest their significant impact on splicing, RNA stability, RNA folding, translation or co-translational protein folding. Hence, we compile 659194 synonymous mutations found in human cancer and characterize their properties. We provide the user-friendly, comprehensive resource for synonymous mutations in cancer, SynMICdb (http://SynMICdb.dkfz.de), which also contains orthogonal information about gene annotation, recurrence, mutation loads, cancer association, conservation, alternative events, impact on mRNA structure and a SynMICdb score. Notably, synonymous and missense mutations are depleted at the 5'-end of the coding sequence as well as at the ends of internal exons independent of mutational signatures. For patient-derived synonymous mutations in the oncogene KRAS, we indicate that single point mutations can have a relevant impact on expression as well as on mRNA secondary structure.

Synonymous mutations do not alter amino acid sequence but may exert oncogenic effects in other ways. Here, the authors present a catalogue of synonymous mutations in cancer and characterise their properties.

Conformational Dynamics of the RNA G-Quadruplex and its Effect on Translation Efficiency

During translation, intracellular mRNA folds co-transcriptionally and must refold following the passage of ribosome. The mRNAs can be entrapped in metastable structures during these folding events. In the present study, we evaluated the conformational dynamics of the kinetically favored, metastable, and hairpin-like structure, which disturbs the thermodynamically favored G-quadruplex structure, and its effect on co-transcriptional translation in prokaryotic cells. We found that nascent mRNA forms a metastable hairpin-like structure during co-transcriptional folding instead of the G-quadruplex structure. When the translation progressed co-transcriptionally before the metastable hairpin-like structure transition to the G-quadruplex, function of the G-quadruplex as a roadblock of the ribosome was sequestered. This suggested that kinetically formed RNA structures had a dominant effect on gene expression in prokaryotes. The results of this study indicate that it is critical to consider the conformational dynamics of RNA-folding to understand the contributions of the mRNA structures in controlling gene expression.

A Method for RNA Structure Prediction Shows Evidence for Structure in lncRNAs

To compare the secondary structure profiles of RNA molecules we developed the CROSSalign method. CROSSalign is based on the combination of the Computational Recognition Of Secondary Structure (CROSS) algorithm to predict the RNA secondary structure profile at single-nucleotide resolution and the Dynamic Time Warping (DTW) method to align profiles of different lengths. We applied CROSSalign to investigate the structural conservation of long non-coding RNAs such as XIST and HOTAIR as well as ssRNA viruses including HIV. CROSSalign performs pair-wise comparisons and is able to find homologs between thousands of matches identifying the exact regions of similarity between profiles of different lengths. In a pool of sequences with the same secondary structure CROSSalign accurately recognizes repeat A of XIST and domain D2 of HOTAIR and outperforms other methods based on covariance modeling. The algorithm is freely available at the webpage http://service.tartaglialab.com//new_submission/crossalign.

Links between Transcription, Environmental Adaptation and Gene Variability in Escherichia coli: Correlations between Gene Expression and Gene Variability Reflect Growth Efficiencies

Gene expression is known to be the principle factor explaining how fast genes evolve. Highly transcribed genes evolve slowly because any negative impact caused by a particular mutation is magnified by protein abundance. However, gene expression is a phenotype that depends both on the environment and on the strains or species. We studied this phenotypic plasticity by analyzing the transcriptome profiles of four Escherichia coli strains grown in three different culture media, and explored how expression variability was linked to gene allelic diversity. Genes whose expression changed according to the media and not to the strains were less polymorphic than other genes. Genes for which transcription depended predominantly on the strain were more polymorphic than other genes and were involved in sensing and responding to environmental changes, with an overrepresentation of two-component system genes. Surprisingly, we found that the correlation between transcription and gene diversity was highly variable among growth conditions and could be used to quantify growth efficiency of a strain in a medium. Genetic variability was found to increase with gene expression in poor growth conditions. As such conditions are also characterized by down-regulation of all DNA repair systems, including transcription-coupled repair, we suggest that gene expression under stressful conditions may be mutagenic and thus leads to a variability in mutation rate among genes in the genome which contributes to the pattern of protein evolution.

Population transcriptomics uncovers the regulation of gene expression variation in adaptation to changing environment

Expression variation plays an important role in plant adaptation, but little is known about the factors impacting the expression variation when population adapts to changing environment. We used RNA-seq data from 80 individuals in 14 Miscanthus lutarioriparius populations, which were transplanted into a harsh environment from native habitat, to investigate the expression level, expression diversity and genetic diversity for genes expressed in both environments. The expression level of genes with lower expression level or without SNP tended to be more changeable in new environment, which suggested highly expressed genes experienced stronger purifying selection than those at lower level. Low proportion of genes with population effect confirmed the weak population structure and frequent gene flow in these populations. Meanwhile, the number of genes with environment effect was the most frequent compared with that with population effect. Our results showed that environment and genetic diversity were the main factors determining gene expression variation in population. This study could facilitate understanding the mechanisms of global gene expression variation when plant population adapts to changing environment.

Large-Effect Beneficial Synonymous Mutations Mediate Rapid and Parallel Adaptation in a Bacterium

Contrary to previous understanding, recent evidence indicates that synonymous codon changes may sometimes face strong selection. However, it remains difficult to generalize the nature, strength, and mechanism(s) of such selection. Previously, we showed that synonymous variants of a key enzyme-coding gene (fae) of Methylobacterium extorquens AM1 decreased enzyme production and reduced fitness dramatically. We now show that during laboratory evolution, these variants rapidly regained fitness via parallel yet variant-specific, highly beneficial point mutations in the N-terminal region of fae. These mutations (including four synonymous mutations) had weak but consistently positive impacts on transcript levels, enzyme production, or enzyme activity. However, none of the proposed mechanisms (including internal ribosome pause sites or mRNA structure) predicted the fitness impact of evolved or additional, engineered point mutations. This study shows that synonymous mutations can be fixed through strong positive selection, but the mechanism for their benefit varies depending on the local sequence context.

Compensating the Fitness Costs of Synonymous Mutations

Synonymous mutations do not change the sequence of the polypeptide but they may still influence fitness. We investigated in Salmonella enterica how four synonymous mutations in the rpsT gene (encoding ribosomal protein S20) reduce fitness (i.e., growth rate) and the mechanisms by which this cost can be genetically compensated. The reduced growth rates of the synonymous mutants were correlated with reduced levels of the rpsT transcript and S20 protein. In an adaptive evolution experiment, these fitness impairments could be compensated by mutations that either caused up-regulation of S20 through increased gene dosage (due to duplications), increased transcription of the rpsT gene (due to an rpoD mutation or mutations in rpsT), or increased translation from the rpsT transcript (due to rpsT mutations). We suggest that the reduced levels of S20 in the synonymous mutants result in production of a defective subpopulation of 30S subunits lacking S20 that reduce protein synthesis and bacterial growth and that the compensatory mutations restore S20 levels and the number of functional ribosomes. Our results demonstrate how specific synonymous mutations can cause substantial fitness reductions and that many different types of intra- and extragenic compensatory mutations can efficiently restore fitness. Furthermore, this study highlights that also synonymous sites can be under strong selection, which may have implications for the use of dN/dS ratios as signature for selection.

Roles for Synonymous Codon Usage in Protein Biogenesis

Owing to the degeneracy of the genetic code, a protein sequence can be encoded by many different synonymous mRNA coding sequences. Synonymous codon usage was once thought to be functionally neutral, but evidence now indicates it is shaped by evolutionary selection and affects other aspects of protein biogenesis beyond specifying the amino acid sequence of the protein. Synonymous rare codons, once thought to have only negative impacts on the speed and accuracy of translation, are now known to play an important role in diverse functions, including regulation of cotranslational folding, covalent modifications, secretion, and expression level. Mutations altering synonymous codon usage are linked to human diseases. However, much remains unknown about the molecular mechanisms connecting synonymous codon usage to efficient protein biogenesis and proper cell physiology. Here we review recent literature on the functional effects of codon usage, including bioinformatics approaches aimed at identifying general roles for synonymous codon usage.

The impact of RNA structure on coding sequence evolution in both bacteria and eukaryotes

Background

Many studies have found functional RNA secondary structures are selectively conserved among species. But, the effect of RNA structure selection on coding sequence evolution remains unknown. To address this problem, we systematically investigated the relationship between nucleotide conservation level and its structural sensitivity in four model organisms, Escherichia coli, yeast, fly, and mouse.

Results

We define structurally sensitive sites as those with putative local structure-disruptive mutations. Using both the Mantel-Haenszel procedure and association test, we found structurally sensitive nucleotide sites evolved more slowly than non-sensitive sites in all four organisms. Furthermore, we observed that this association is more obvious in highly expressed genes and region near the start codon.

Conclusion

We conclude that structurally sensitive sites in mRNA sequences normally have less nucleotide divergence in all species we analyzed. This study extends our understanding of the impact of RNA structure on coding sequence evolution, and is helpful to the development of a codon model with RNA structure information.