Codon optimality is a major determinant of mRNA stability

Kingdom-Wide Analysis of Fungal Transcriptomes and tRNAs Reveals Conserved Patterns of Adaptive Evolution

Protein-coding genes evolved codon usage bias due to the combined but uneven effects of adaptive and nonadaptive influences. Studies in model fungi agree on codon usage bias as an adaptation for fine-tuning gene expression levels; however, such knowledge is lacking for most other fungi. Our comparative genomics analysis of over 450 species supports codon usage and transfer RNAs (tRNAs) as coadapted for translation speed and this is most likely a realization of convergent evolution. Rather than drift, phylogenetic reconstruction inferred adaptive radiation as the best explanation for the variation of interspecific codon usage bias. Although the phylogenetic signals for individual codon and tRNAs frequencies are lower than expected by genetic drift, we found remarkable conservation of highly expressed genes being codon optimized for translation by the most abundant tRNAs, especially by inosine-modified tRNAs. As an application, we present a sequence-to-expression neural network that uses codons to reliably predict highly expressed transcripts. The kingdom Fungi, with over a million species, includes many key players in various ecosystems and good targets for biotechnology. Collectively, our results have implications for better understanding the evolutionary success of fungi, as well as informing the biosynthetic manipulation of fungal genes.

Transcription-wide mapping of dihydrouridine reveals that mRNA dihydrouridylation is required for meiotic chromosome segregation

The epitranscriptome has emerged as a new fundamental layer of control of gene expression. Nevertheless, the determination of the transcriptome-wide occupancy and function of RNA modifications remains challenging. Here we have developed Rho-seq, an integrated pipeline detecting a range of modifications through differential modification-dependent rhodamine labeling. Using Rho-seq, we confirm that the reduction of uridine to dihydrouridine (D) by the Dus reductase enzymes targets tRNAs in E. coli and fission yeast. We find that the D modification is also present on fission yeast mRNAs, particularly those encoding cytoskeleton-related proteins, which is supported by large-scale proteome analyses and ribosome profiling. We show that the α-tubulin encoding mRNA nda2 undergoes Dus3-dependent dihydrouridylation, which affects its translation. The absence of the modification on nda2 mRNA strongly impacts meiotic chromosome segregation, resulting in low gamete viability. Applying Rho-seq to human cells revealed that tubulin mRNA dihydrouridylation is evolutionarily conserved.

Strong negative correlation between codon usage bias and protein structural disorder impedes protein expression after codon optimization

As a common phenomenon existing in almost all genomes, codon usage bias has been studied for a long time. Codon optimization is a frequently used strategy to accelerate protein synthesis rate. Besides regulating protein translation speed, codon usage bias has also be reported to affect co-translation folding and transcription. P. pastoris is a well-developed expression system, whose efficiency is tightly correlated with commercial value. However, few studies focus on the role of codon usage bias in affecting protein expression in P. pastoris. Besides, many genes in P. pastoris genome show significant negative correlation between codon usage bias and protein structural disorder tendency. It's not known whether this feature is important for their expression. In order to answer these questions, we picked 4P. pastoris gene candidates with strong negative correlation between codon usage bias and protein structural disorder. We then performed full-length codon optimization which completely eliminated the correlation. Protein and RNA assays were then used to compare protein and mRNA levels before and after codon optimization. As a result, codon optimization failed to elevate their protein expression levels, and even resulted in a decrease. As represented by the trypsin sensitivity assays, codon optimization also altered the protein structure of 0616 and 0788. Besides protein, codon optimization also affected mRNA levels. Shown by in vitro and in vivo RNA degradation assays, the mRNA stability of 0616, 0788 and 0135 were also altered by codon optimization. For each gene, the detailed effect may be related with its specific sequence and protein structure. Our results suggest that codon usage bias is an important factor to regulate gene expression level, as well as mRNA and protein stabilities in P. pastoris. "Extreme" codon optimization in genes with strong negative correlation between codon usage bias and protein structural disorder tendency may not be favored. Compromised strategies should be tried if expression is not successful. Besides, codon optimization may affect protein structural conformation more severely in structural disordered proteins.

Determinants of the temperature adaptation of mRNA degradation

The rate of chemical reactions increases proportionally with temperature, but the interplay of biochemical reactions permits deviations from this relation and adaptation. The degradation of individual mRNAs in yeast increased to varying degrees with temperature. We examined how these variations are influenced by the translation and codon composition of mRNAs. We developed a method that revealed the existence of a neutral half-life above which mRNAs are stabilized by translation but below which they are destabilized. The proportion of these two mRNA subpopulations remained relatively constant under different conditions, even with slow cell growth due to nutrient limitation, but heat shock reduced the proportion of translationally stabilized mRNAs. At the same time, the degradation of these mRNAs was partially temperature-compensated through Upf1, the mediator of nonsense-mediated decay. Compensation was also promoted by some asparagine and serine codons, whereas tyrosine codons promote temperature sensitization. These codons play an important role in the degradation of mRNAs encoding key cell membrane and cell wall proteins, which promote cell integrity.

Non-liver mRNA Delivery

mRNA drugs can preempt infectious disease and treat Mendelian disorders, such as sickle cell anemia, muscular dystrophy, and cystic fibrosis, as well as autoimmunity and cancer. The three major therapeutic areas for which mRNA delivery is currently being explored are antigen production, including the COVID-19 vaccine, protein replacement therapy, and genome engineering. It was demonstrated 30 years ago that introducing in vitro transcribed mRNA intramuscularly results in detectable protein expression for specific antigens protecting against the likes of influenza and cancer. Utilizing mRNA as a therapeutic modality, however, is challenging. mRNA is large and anionic and, as a result, cannot passively diffuse across the negatively charged plasma membrane. In addition, RNases present in the bloodstream and tissues rapidly degrade mRNA, and its administration induces the innate immune response. In consequence, lipid-, polymer-, dendrimer-, and natural membrane-based mRNA drug delivery systems have been developed to deliver mRNA to target cells. Significant efforts and investments have been made to translate some of these systems into the clinic. Specifically, systemically administered lipid nanoparticles (LNPs) have delivered mRNA to the liver, and intramuscularly administered LNPs have delivered mRNA to immune cells to protect against coronavirus disease of 2019. However, clinically relevant delivery in non-liver tissues such as the spleen, lungs, heart, eye, central nervous system, and lymphatics requires improved drug delivery systems.In this Account, we provide an overview of key advances that have led us to Food and Drug Administration approval for the Pfizer/BioNTech mRNA-based vaccine against SARS-CoV-2 and Emergency Use Authorization for the Moderna mRNA-based vaccine against the same disease, and we explain how these developments will contribute to the clinical translation of mRNA therapeutics targeted outside of the liver. We first focus on the chemical modifications and sequence optimization that can improve the potency of mRNA, resulting in greatly improved pharmacokinetics. After detailing what makes an ideal mRNA payload, we review drug delivery systems used to deliver the payload into target cells. We describe efforts to reduce clearance by the liver, a key obstacle to the development of non-liver therapies. We then consider recent examples of nanoparticles that have delivered mRNA to non-liver tissues. Finally, we discuss current clinical mRNA programs, focusing on the COVID vaccines and highlighting lessons that may be applied to future mRNA drugs.

Canary in a coal mine: collided ribosomes as sensors of cellular conditions

The recent discovery that collision of ribosomes triggers quality control and stress responses in eukaryotes has shifted the perspective of the field. Collided eukaryotic ribosomes adopt a unique structure, acting as a ubiquitin signaling platform for various response factors. While several of the signals that determine which downstream pathways are activated have been uncovered, we are only beginning to learn how the specificity for the activation of each process is achieved during collisions. This review will summarize those findings and how ribosome-associated factors act as molecular sentinels, linking aberrations in translation to the overall cellular state. Insights into how cells respond to ribosome collision events will provide greater understanding of the role of the ribosome in the maintenance of cellular homeostasis.

Delivery of therapeutic oligonucleotides in nanoscale

Therapeutic oligonucleotides (TOs) represent one of the most promising drug candidates in the targeted cancer treatment due to their high specificity and capability of modulating cellular pathways that are not readily druggable. However, efficiently delivering of TOs to cancer cellular targets is still the biggest challenge in promoting their clinical translations. Emerging as a significant drug delivery vector, nanoparticles (NPs) can not only protect TOs from nuclease degradation and enhance their tumor accumulation, but also can improve the cell uptake efficiency of TOs as well as the following endosomal escape to increase the therapeutic index. Furthermore, targeted and on-demand drug release of TOs can also be approached to minimize the risk of toxicity towards normal tissues using stimuli-responsive NPs. In the past decades, remarkable progresses have been made on the TOs delivery based on various NPs with specific purposes. In this review, we will first give a brief introduction on the basis of TOs as well as the action mechanisms of several typical TOs, and then describe the obstacles that prevent the clinical translation of TOs, followed by a comprehensive overview of the recent progresses on TOs delivery based on several various types of nanocarriers containing lipid-based nanoparticles, polymeric nanoparticles, gold nanoparticles, porous nanoparticles, DNA/RNA nanoassembly, extracellular vesicles, and imaging-guided drug delivery nanoparticles.

The life and death of RNA across temperatures

Temperature is an environmental condition that has a pervasive effect on cells along with all the molecules and reactions in them. The mechanisms by which prototypical RNA molecules sense and withstand heat have been identified mostly in bacteria and archaea. The relevance of these phenomena is, however, broader, and similar mechanisms have been recently found throughout the tree of life, from sex determination in reptiles to adaptation of viral RNA polymerases, to genetic disorders in humans. We illustrate the temperature dependence of RNA metabolism with examples from the synthesis to the degradation of mRNAs, and review recently emerged questions. Are cells exposed to greater temperature variations and gradients than previously surmised? How do cells reconcile the conflicting thermal stability requirements of primary and tertiary structures of RNAs? To what extent do enzymes contribute to the temperature compensation of the reaction rates in mRNA turnover by lowering the energy barrier of the catalyzed reactions? We conclude with the ecological, forensic applications of the temperature-dependence of RNA degradation and the biotechnological aspects of mRNA vaccine production.

mRNA Therapeutic Modalities Design, Formulation and Manufacturing under Pharma 4.0 Principles

In the quest for a formidable weapon against the SARS-CoV-2 pandemic, mRNA therapeutics have stolen the spotlight. mRNA vaccines are a prime example of the benefits of mRNA approaches towards a broad array of clinical entities and druggable targets. Amongst these benefits is the rapid cycle "from design to production" of an mRNA product compared to their peptide counterparts, the mutability of the production line should another target be chosen, the side-stepping of safety issues posed by DNA therapeutics being permanently integrated into the transfected cell's genome and the controlled precision over the translated peptides. Furthermore, mRNA applications are versatile: apart from vaccines it can be used as a replacement therapy, even to create chimeric antigen receptor T-cells or reprogram somatic cells. Still, the sudden global demand for mRNA has highlighted the shortcomings in its industrial production as well as its formulation, efficacy and applicability. Continuous, smart mRNA manufacturing 4.0 technologies have been recently proposed to address such challenges. In this work, we examine the lab and upscaled production of mRNA therapeutics, the mRNA modifications proposed that increase its efficacy and lower its immunogenicity, the vectors available for delivery and the stability considerations concerning long-term storage.

Combinations of slow-translating codon clusters can increase mRNA half-life in Saccharomyces cerevisiae

The presence of a single cluster of nonoptimal codons was found to decrease a transcript's half-life through the interaction of the ribosome-associated quality control machinery with stalled ribosomes in Saccharomyces cerevisiae The impact of multiple nonoptimal codon clusters on a transcript's half-life, however, is unknown. Using a kinetic model, we predict that inserting a second nonoptimal cluster near the 5' end can lead to synergistic effects that increase a messenger RNA's (mRNA's) half-life in S. cerevisiae Specifically, the 5' end cluster suppresses the formation of ribosome queues, reducing the interaction of ribosome-associated quality control factors with stalled ribosomes. We experimentally validate this prediction by introducing two nonoptimal clusters into three different genes and find that their mRNA half-life increases up to fourfold. The model also predicts that in the presence of two clusters, the cluster closest to the 5' end is the primary determinant of mRNA half-life. These results suggest the "translational ramp," in which nonoptimal codons are located near the start codon and increase translational efficiency, may have the additional biological benefit of allowing downstream slow-codon clusters to be present without decreasing mRNA half-life. These results indicate that codon usage bias plays a more nuanced role in controlling cellular protein levels than previously thought.

Decoding the effects of synonymous variants

Synonymous single nucleotide variants (sSNVs) are common in the human genome but are often overlooked. However, sSNVs can have significant biological impact and may lead to disease. Existing computational methods for evaluating the effect of sSNVs suffer from the lack of gold-standard training/evaluation data and exhibit over-reliance on sequence conservation signals. We developed synVep (synonymous Variant effect predictor), a machine learning-based method that overcomes both of these limitations. Our training data was a combination of variants reported by gnomAD (observed) and those unreported, but possible in the human genome (generated). We used positive-unlabeled learning to purify the generated variant set of any likely unobservable variants. We then trained two sequential extreme gradient boosting models to identify subsets of the remaining variants putatively enriched and depleted in effect. Our method attained 90% precision/recall on a previously unseen set of variants. Furthermore, although synVep does not explicitly use conservation, its scores correlated with evolutionary distances between orthologs in cross-species variation analysis. synVep was also able to differentiate pathogenic vs. benign variants, as well as splice-site disrupting variants (SDV) vs. non-SDVs. Thus, synVep provides an important improvement in annotation of sSNVs, allowing users to focus on variants that most likely harbor effects.

Analysis of eukaryotic lincRNA sequences indicates signatures of hindered translation linked to selection pressure

Long intergenic noncoding RNAs (lincRNAs) represent a large fraction of transcribed loci in eukaryotic genomes. Although classified as noncoding, most lincRNAs contain open reading frames (ORFs), and it remains unclear why cytoplasmic lincRNAs are not or very inefficiently translated. Here, we analyzed signatures of hindered translation in lincRNA sequences from five eukaryotes, covering a range of natural selection pressures. In fission yeast and Caenorhabditis elegans, that is, species under strong selection, we detected significantly shorter ORFs, a suboptimal sequence context around start codons for translation initiation, and trinucleotides (“codons”) corresponding to less abundant tRNAs than for neutrally evolving control sequences, likely impeding translation elongation. For human, we detected signatures for cell-type-specific hindrance of lincRNA translation, in particular codons in abundant cytoplasmic lincRNAs corresponding to lower expressed tRNAs than control codons, in three out of five human cell lines. We verified that varying tRNA expression levels between cell lines are reflected in the amount of ribosomes bound to cytoplasmic lincRNAs in each cell line. We further propose that codons at ORF starts are particularly important for reducing ribosome-binding to cytoplasmic lincRNA ORFs. Altogether, our analyses indicate that in species under stronger selection lincRNAs evolved sequence features generally hindering translation and support cell-type-specific hindrance of translation efficiency in human lincRNAs. The sequence signatures we have identified may improve predicting peptide-coding and genuine noncoding lincRNAs in a cell type.

Therapeutic mRNA Engineering from Head to Tail

Synthetic messenger RNA (mRNA), once delivered into cells, can be readily translated into proteins by ribosomes, which do not distinguish exogenous mRNAs from endogenous transcripts. Until recently, the intrinsic instability and immunostimulatory property of exogenous RNAs largely hindered the therapeutic application of synthetic mRNAs. Thanks to major technological innovations, such as introduction of chemically modified nucleosides, synthetic mRNAs have become programmable therapeutic reagents. Compared to DNA or protein-based therapeutic reagents, synthetic mRNAs bear several advantages: flexible design, easy optimization, low-cost preparation, and scalable synthesis. Therapeutic mRNAs are commonly designed to encode specific antigens to elicit organismal immune response to pathogens like viruses, express functional proteins to replace defective ones inside cells, or introduce novel enzymes to achieve unique functions like genome editing. Recent years have witnessed stunning progress on the development of mRNA vaccines against SARS-Cov2. This success is built upon our fundamental understanding of mRNA metabolism and translational control, a knowledge accumulated during the past several decades. Given the astronomical number of sequence combinations of four nucleotides, sequence-dependent control of mRNA translation remains incompletely understood. Rational design of synthetic mRNAs with robust translation and optimal stability remains challenging. Massively paralleled reporter assay (MPRA) has been proven to be powerful in identifying sequence elements in controlling mRNA translatability and stability. Indeed, a completely randomized sequence in 5' untranslated region (5'UTR) drives a wide range of translational outputs. In this Account, we will discuss general principles of mRNA translation in eukaryotic cells and elucidate the role of coding and noncoding regions in the translational regulation. From the therapeutic perspective, we will highlight the unique features of 5' cap, 5'UTR, coding region (CDS), stop codon, 3'UTR, and poly(A) tail. By focusing on the design strategies in mRNA engineering, we hope this Account will contribute to the rational design of synthetic mRNAs with broad therapeutic potential.

Recent Advances in the Noninvasive Delivery of mRNA

Over the past two decades, research on mRNA-based therapies has exploded, mainly because of the inherent advantages of mRNA, including a low integration probability, transient expression, and simple and rapid in vitro transcription production approaches. In addition, thanks to improved stability and reduced immunogenicity by advanced strategies, the application of mRNA has expanded from protein replacement therapy to vaccination, gene editing and other fields, showing great promise for clinical application. Recently, with the successive launch of two mRNA-based COVID-19 vaccines, mRNA technology has attracted an enormous amount of attention from scientific researchers as well as pharmaceutical companies. Because of the large molecular weight, hydrophilicity, and highly negative charge densities of mRNA, it is difficult to overcome the intracellular delivery barriers. Therefore, various delivery vehicles have been developed to achieve more effective mRNA delivery. In general, conventional mRNA administration methods are based on injection strategies, including intravenous, intramuscular, intradermal, and subcutaneous injections. Although these routes circumvent the absorption barriers to some extent, they bring about injection-related concerns such as safety issues, pain, low compliance, and difficulty in repeated dosing, increasing the need to explore alternative strategies for noninvasive delivery. The ideal noninvasive delivery systems are featured with easy to use, low risks of infection, and good patient compliance. At the same time, they allow patients to self-administer, reducing reliance on professional healthcare workers and interference with bodily functions and daily life. In particular, the noninvasive mucosal delivery of mRNA vaccines can induce mucosal immune responses, which are important for resisting pathogens infected through mucosal routes.Because of the potential clinical benefits mentioned above, we detailed the existing strategies for the noninvasive delivery of mRNA in this review, including delivery via the nasal, pulmonary, vaginal, and transdermal routes. First, we discussed the unique strengths and biological hindrances of each route on the basis of physiology. Next, we comprehensively summarized the research progress reported so far and analyzed the technologies and delivery vehicles used, hoping to provide some references for further explorations. Among these noninvasive routes, nasal and pulmonary delivery are the earliest and most intensively studied areas, mostly owing to their favorable physiological structures: the nasal or pulmonary mucosa is easily accessible, highly permeable and highly vascularized. In contrast, the development of vaginal mRNA delivery is relatively less reported, and the current research mainly focused on some local applications. In addition, microneedles have also been investigated to overcome skin barriers for mRNA delivery in recent years, making microneedle-based delivery an emerging alternative pathway. In summary, a variety of mRNA formulations and delivery strategies have been developed for noninvasive mRNA delivery, skillfully combining appropriate vehicles or physical technologies to enhance effectiveness. We surmise that continuous advances and technological innovations in the development of mRNA noninvasive delivery will accelerate the translation from experimental research to clinical application.

A synonymous mutation in IGF-1 impacts the transcription and translation process of gene expression

Insulin-like growth factor 1 (IGF-1) is considered to be a crucial gene in the animal development of bone and body size. In this study, a unique synonymous mutation (c.258 A > G) of the IGF-1 gene was modified with an adenine base editor to observe the growth and developmental situation of mutant mice. Significant expression differences and molecular mechanisms among vectors with different alanine synonymous codons were explored. Although modification of a single synonymous codon rarely interferes with animal phenotypes, we observed that the expression and secretion of IGF-1 were different between 8-week-old homozygous (Ho) and wild-type (WT) mice. In addition, the IGF-1 with optimal codon combinations showed a higher expression content than other codon combination modes at both transcription and translation levels and performed proliferation promotion. The gene stability and translation initiation efficiency also changed significantly. Our findings illustrated that the synonymous mutation altered the IGF-1 gene expression in individual mice and suggested that the synonymous mutation affected the IGF-1 expression and biological function through the transcription and translation processes.

Determinants of efficient modulation of ribosomal traffic jams

mRNA translation is the process which consumes most of the cellular energy. Thus, this process is under strong evolutionary selection for its optimization and rational optimization or reduction of the translation efficiency can impact the cell growth rate. Algorithms for modulating cell growth rate can have various applications in biotechnology, medicine, and agriculture. In this study, we demonstrate that the analysis of these algorithms can also be used for understanding translation.

We specifically describe and analyze various generic algorithms, based on comprehensive computational models and whole cell simulations of translation, for introducing silent mutations that can either reduce or increase ribosomal traffic jams along the mRNA. As a result, more or less resources are available, for the cell, promoting improved or reduced cells growth-rate, respectively. We then explore the cost of these algorithms' performance, in terms of their computational time, the number of mutations they introduce, the modified genomic region, the effect on local translation rates, and the properties of the modified genes.

Among others, we show that mRNA levels of a gene are much stronger predictors for the effect of its engineering on the ribosomal pool than the ribosomal density of the gene. We also demonstrate that the mutations at the ends of the coding regions have a stronger effect on the ribosomal pool. Furthermore, we report two optimization algorithms that exhibit a tread-off between the number of mutations they introduce and their executing time.

The reported results here are fundamental both for understanding the biophysics and evolution of translation, as well as for developing efficient approaches for its engineering.

Cell type-specific analysis by single-cell profiling identifies a stable mammalian tRNA-mRNA interface and increased translation efficiency in neurons

The correlation between codon and anticodon pools influences the efficiency of translation, but whether differences exist in these pools across individual cells is unknown. We determined that codon usage and amino acid demand are highly stable across different cell types using available mouse and human single-cell RNA-sequencing atlases. After showing the robustness of ATAC-sequencing measurements for the analysis of tRNA gene usage, we quantified anticodon usage and amino acid supply in both mouse and human single-cell ATAC-seq atlases. We found that tRNA gene usage is overall coordinated across cell types, except in neurons, which clustered separately from other cell types. Integration of these data sets revealed a strong and statistically significant correlation between amino acid supply and demand across almost all cell types. Neurons have an enhanced translation efficiency over other cell types, driven by an increased supply of tRNA^Ala (AGC) anticodons. This results in faster decoding of the Ala-GCC codon, as determined by cell type–specific ribosome profiling, suggesting that the reduction of tRNA^Ala (AGC) anticodon pools may be implicated in neurological pathologies. This study, the first such examination of codon usage, anticodon usage, and translation efficiency resolved at the cell-type level with single-cell information, identifies a conserved landscape of translation elongation across mammalian cellular diversity and evolution.

Evolutionary perspectives and adaptation dynamics of human seasonal influenza viruses from 2009 to 2019: An insight from codon usage

The annually recurrent seasonal influenza viruses, namely, influenza A viruses (H1N1/pdm2009 and H3N2) and influenza B viruses, contribute substantially to human disease burden. Elucidation of host adaptation, population dynamics and evolutionary patterns of these viruses contribute to better control of current epidemic situation and bolster efforts towards pandemic preparedness. Present study has been addressed at unraveling the signatures of codon usage and dinucleotide distribution of these seasonal influenza viruses associating with their fitness and ongoing adaptive evolution in human population. Thorough analysis of codon usage adaptation revealed that H3N2 has been exhibited best adapted to human cellular system, which correlate with its highest epidemic intensity as compared with the other seasonal influenza viruses. CpG dinucleotide was found to be strongly avoided among the seasonal influenza viruses with more restraint among influenza B viruses than influenza A viruses, and might be accounted to the strategy of the viral pathogens in evading human immune signals. Dynamic scenes of ongoing evolution in codon usage and elimination of CpG motif among the viruses, which correlate with their distinct host adaption state, signifying the marked impact of selective force operational on the viral genomes, aimed at proficient circulation, enhanced fitness and successful infective manifestations in humans.

Codon Usage Bias in Autophagy-Related Gene 13 in Eukaryotes: Uncovering the Genetic Divergence by the Interplay Between Nucleotides and Codon Usages

Synonymous codon usage bias is a universal characteristic of genomes across various organisms. Autophagy-related gene 13 (atg13) is one essential gene for autophagy initiation, yet the evolutionary trends of the atg13 gene at the usages of nucleotide and synonymous codon remains unexplored. According to phylogenetic analyses for the atg13 gene of 226 eukaryotic organisms at the nucleotide and amino acid levels, it is clear that their nucleotide usages exhibit more genetic information than their amino acid usages. Specifically, the overall nucleotide usage bias quantified by information entropy reflected that the usage biases at the first and second codon positions were stronger than those at the third position of the atg13 genes. Furthermore, the bias level of nucleotide ‘G’ usage is highest, while that of nucleotide ‘C’ usage is lowest in the atg13 genes. On top of that, genetic features represented by synonymous codon usage exhibits a species-specific pattern on the evolution of the atg13 genes to some extent. Interestingly, the codon usages of atg13 genes in the ancestor animals (Latimeria chalumnae, Petromyzon marinus, and Rhinatrema bivittatum) are strongly influenced by mutation pressure from nucleotide composition constraint. However, the distributions of nucleotide composition at different codon positions in the atg13 gene display that natural selection still dominates atg13 codon usages during organisms’ evolution.

Ribosome dynamics and mRNA turnover, a complex relationship under constant cellular scrutiny

Eukaryotic gene expression is closely regulated by translation and turnover of mRNAs. Recent advances highlight the importance of translation in the control of mRNA degradation, both for aberrant and apparently normal mRNAs. During translation, the information contained in mRNAs is decoded by ribosomes, one codon at a time, and tRNAs, by specifically recognizing codons, translate the nucleotide code into amino acids. Such a decoding step does not process regularly, with various obstacles that can hinder ribosome progression, then leading to ribosome stalling or collisions. The progression of ribosomes is constantly monitored by the cell which has evolved several translation-dependent mRNA surveillance pathways, including nonsense-mediated decay (NMD), no-go decay (NGD), and non-stop decay (NSD), to degrade certain problematic mRNAs and the incomplete protein products. Recent progress in sequencing and ribosome profiling has made it possible to discover new mechanisms controlling ribosome dynamics, with numerous crosstalks between translation and mRNA decay. We discuss here various translation features critical for mRNA decay, with particular focus on current insights from the complexity of the genetic code and also the emerging role for the ribosome as a regulatory hub orchestrating mRNA decay, quality control, and stress signaling. Even if the interplay between mRNA translation and degradation is no longer to be demonstrated, a better understanding of their precise coordination is worthy of further investigation. This article is categorized under: RNA Turnover and Surveillance > Regulation of RNA Stability Translation > Translation Regulation RNA Interactions with Proteins and Other Molecules > RNA-Protein Complexes.

Codon optimality in cancer

A key characteristic of cancer cells is their increased proliferative capacity, which requires elevated levels of protein synthesis. The process of protein synthesis involves the translation of codons within the mRNA coding sequence into a string of amino acids to form a polypeptide chain. As most amino acids are encoded by multiple codons, the nucleotide sequence of a coding region can vary dramatically without altering the polypeptide sequence of the encoded protein. Although mutations that do not alter the final amino acid sequence are often thought of as silent/synonymous, these can still have dramatic effects on protein output. Because each codon has a distinct translation elongation rate and can differentially impact mRNA stability, each codon has a different degree of 'optimality' for protein synthesis. Recent data demonstrates that the codon preference of a transcriptome matches the abundance of tRNAs within the cell and that this supply and demand between tRNAs and mRNAs varies between different cell types. The largest observed distinction is between mRNAs encoding proteins associated with proliferation or differentiation. Nevertheless, precisely how codon optimality and tRNA expression levels regulate cell fate decisions and their role in malignancy is not fully understood. This review describes the current mechanistic understanding on codon optimality, its role in malignancy and discusses the potential to target codon optimality therapeutically in the context of cancer.

The Dynamic Codon Biaser: calculating prokaryotic codon usage biases

Bacterial genomes often reflect a bias in the usage of codons. These biases are often most notable within highly expressed genes. While deviations in codon usage can be attributed to selection or mutational biases, they can also be functional, for example controlling gene expression or guiding protein structure. Several different metrics have been developed to identify biases in codon usage. Previously we released a database, CBDB: The Codon Bias Database, in which users could retrieve precalculated codon bias data for bacterial RefSeq genomes. With the increase of bacterial genome sequence data since its release a new tool was needed. Here we present the Dynamic Codon Biaser (DCB) tool, a web application that dynamically calculates the codon usage bias statistics of prokaryotic genomes. DCB bases these calculations on 40 different highly expressed genes (HEGs) that are highly conserved across different prokaryotic species. A user can either specify an NCBI accession number or upload their own sequence. DCB returns both the bias statistics and the genome’s HEG sequences. These calculations have several downstream applications, such as evolutionary studies and phage–host predictions. The source code is freely available, and the website is hosted at www.cbdb.info.

The Expression Level of HIV-1 Vif Is Optimized by Nucleotide Changes in the Genomic SA1D2prox Region during the Viral Adaptation Process

HIV-1 Vif plays an essential role in viral replication by antagonizing anti-viral cellular restriction factors, a family of APOBEC3 proteins. We have previously shown that naturally-occurring single-nucleotide mutations in the SA1D2prox region, which surrounds the splicing acceptor 1 and splicing donor 2 sites of the HIV-1 genome, dramatically alter the Vif expression level, resulting in variants with low or excessive Vif expression. In this study, we investigated how these HIV-1 variants with poor replication ability adapt and evolve under the pressure of APOBEC3 proteins. Adapted clones obtained through adaptation experiments exhibited an altered replication ability and Vif expression level compared to each parental clone. While various mutations were present throughout the viral genome, all replication-competent adapted clones with altered Vif expression levels were found to bear them within SA1D2prox, without exception. Indeed, the mutations identified within SA1D2prox were responsible for changes in the Vif expression levels and altered the splicing pattern. Moreover, for samples collected from HIV-1-infected patients, we showed that the nucleotide sequences of SA1D2prox can be chronologically changed and concomitantly affect the Vif expression levels. Taken together, these results demonstrated the importance of the SA1D2prox nucleotide sequence for modulating the Vif expression level during HIV-1 replication and adaptation.

Evaluation of Suspected Autosomal Alport Syndrome Synonymous Variants

Background

Alport syndrome is an inherited disorder characterized by progressive renal disease, variable sensorineural hearing loss, and ocular abnormalities. Although many pathogenic variants in COL4A3 and COL4A4 have been identified in patients with autosomal Alport syndrome, synonymous mutations in these genes have rarely been identified.

Methods

We conducted in silico splicing analysis using Human Splicing Finder (HSF) and Alamut to predict splicing domain strength and disruption of the sites. Furthermore, we performed in vitro splicing assays using minigene constructs and mRNA analysis of patient samples to determine the pathogenicity of four synonymous variants detected in four patients with suspected autosomal dominant Alport syndrome (COL4A3 [c.693G>A (p.Val231=)] and COL4A4 [c.1353C>T (p.Gly451=), c.735G>A (p.Pro245=), and c.870G>A (p.Lys290=)]).

Results

Both in vivo and in vitro splicing assays showed exon skipping in two out of the four synonymous variants identified (c.735G>A and c.870G>A in COL4A4). Prediction analysis of wild-type and mutated COL4A4 sequences using HSF and Alamut suggested these two variants may lead to the loss of binding sites for several splicing factors, e.g., in acceptor sites and exonic splicing enhancers. The other two variants did not induce aberrant splicing.

Conclusions

This study highlights the pitfalls of classifying the functional consequences of variants by a simple approach. Certain synonymous variants, although they do not alter the amino acid sequence of the encoded protein, can dramatically affect pre-mRNA splicing, as shown in two of our patients. Our findings indicate that transcript analysis should be carried out to evaluate synonymous variants detected in patients with autosomal dominant Alport syndrome.

Theoretical basis for stabilizing messenger RNA through secondary structure design

RNA hydrolysis presents problems in manufacturing, long-term storage, world-wide delivery and in vivo stability of messenger RNA (mRNA)-based vaccines and therapeutics. A largely unexplored strategy to reduce mRNA hydrolysis is to redesign RNAs to form double-stranded regions, which are protected from in-line cleavage and enzymatic degradation, while coding for the same proteins. The amount of stabilization that this strategy can deliver and the most effective algorithmic approach to achieve stabilization remain poorly understood. Here, we present simple calculations for estimating RNA stability against hydrolysis, and a model that links the average unpaired probability of an mRNA, or AUP, to its overall hydrolysis rate. To characterize the stabilization achievable through structure design, we compare AUP optimization by conventional mRNA design methods to results from more computationally sophisticated algorithms and crowdsourcing through the OpenVaccine challenge on the Eterna platform. We find that rational design on Eterna and the more sophisticated algorithms lead to constructs with low AUP, which we term 'superfolder' mRNAs. These designs exhibit a wide diversity of sequence and structure features that may be desirable for translation, biophysical size, and immunogenicity. Furthermore, their folding is robust to temperature, computer modeling method, choice of flanking untranslated regions, and changes in target protein sequence, as illustrated by rapid redesign of superfolder mRNAs for B.1.351, P.1 and B.1.1.7 variants of the prefusion-stabilized SARS-CoV-2 spike protein. Increases in in vitro mRNA half-life by at least two-fold appear immediately achievable.

Differential regulation of mRNA fate by the human Ccr4-Not complex is driven by coding sequence composition and mRNA localization

BACKGROUND

Regulation of protein output at the level of translation allows for a rapid adaptation to dynamic changes to the cell's requirements. This precise control of gene expression is achieved by complex and interlinked biochemical processes that modulate both the protein synthesis rate and stability of each individual mRNA. A major factor coordinating this regulation is the Ccr4-Not complex. Despite playing a role in most stages of the mRNA life cycle, no attempt has been made to take a global integrated view of how the Ccr4-Not complex affects gene expression.

RESULTS

This study has taken a comprehensive approach to investigate post-transcriptional regulation mediated by the Ccr4-Not complex assessing steady-state mRNA levels, ribosome position, mRNA stability, and protein production transcriptome-wide. Depletion of the scaffold protein CNOT1 results in a global upregulation of mRNA stability and the preferential stabilization of mRNAs enriched for G/C-ending codons. We also uncover that mRNAs targeted to the ER for their translation have reduced translational efficiency when CNOT1 is depleted, specifically downstream of the signal sequence cleavage site. In contrast, translationally upregulated mRNAs are normally localized in p-bodies, contain disorder-promoting amino acids, and encode nuclear localized proteins. Finally, we identify ribosome pause sites that are resolved or induced by the depletion of CNOT1.

CONCLUSIONS

We define the key mRNA features that determine how the human Ccr4-Not complex differentially regulates mRNA fate and protein synthesis through a mechanism linked to codon composition, amino acid usage, and mRNA localization.

SARS-CoV-2 (Covid-19) vaccines structure, mechanisms and effectiveness: A review

The world has been suffering from COVID-19 disease for more than a year, and it still has a high mortality rate. In addition to the need to minimize transmission of the virus through non-pharmacological measures such as the use of masks and social distance, many efforts are being made to develop a variety of vaccines to prevent the disease worldwide. So far, several vaccines have reached the final stages of safety and efficacy in various phases of clinical trials, and some, such as Moderna/NIAID and BioNTech/Pfizer, have reported very high safety and protection. The important point is that comparing different vaccines is not easy because there is no set standard for measuring neutralization. In this study, we have reviewed the common platforms of COVID-19 vaccines and tried to present the latest reports on the effectiveness of these vaccines.

Characterizing RNA Pseudouridylation by Convolutional Neural Networks

Pseudouridine (Ψ) is the most prevalent post-transcriptional RNA modification and is widespread in small cellular RNAs and mRNAs. However, the functions, mechanisms, and precise distribution of Ψs (especially in mRNAs) still remain largely unclear. The landscape of Ψs across the transcriptome has not yet been fully delineated. Here, we present a highly effective model based on a convolutional neural network (CNN), called PseudoUridyLation Site Estimator (PULSE), to analyze large-scale profiling data of Ψ sites and characterize the contextual sequence features of pseudouridylation. PULSE, consisting of two alternatively-stacked convolution and pooling layers followed by a fully-connected neural network, can automatically learn the hidden patterns of pseudouridylation from the local sequence information. Extensive validation tests demonstrated that PULSE can outperform other state-of-the-art prediction methods and achieve high prediction accuracy, thus enabling us to further characterize the transcriptome-wide landscape of Ψ sites. We further showed that the prediction results derived from PULSE can provide novel insights into understanding the functional roles of pseudouridylation, such as the regulations of RNA secondary structure, codon usage, translation, and RNA stability, and the connection to single nucleotide variants. The source code and final model for PULSE are available at https://github.com/mlcb-thu/PULSE.

Translational control of stem cell function

Stem cells are characterized by their ability to self-renew and differentiate into many different cell types. Research has focused primarily on how these processes are regulated at a transcriptional level. However, recent studies have indicated that stem cell behaviour is strongly coupled to the regulation of protein synthesis by the ribosome. In this Review, we discuss how different translation mechanisms control the function of adult and embryonic stem cells. Stem cells are characterized by low global translation rates despite high levels of ribosome biogenesis. The maintenance of pluripotency, the commitment to a specific cell fate and the switch to cell differentiation depend on the tight regulation of protein synthesis and ribosome biogenesis. Translation regulatory mechanisms that impact on stem cell function include mTOR signalling, ribosome levels, and mRNA and tRNA features and amounts. Understanding these mechanisms important for stem cell self-renewal and differentiation may also guide our understanding of cancer grade and metastasis.

Analysis of Codon Usage Patterns of Six Sequenced Brachypodium distachyon Lines Reveals a Declining CG Skew of the CDSs from the 5'-ends to the 3'-ends

Brachypodium distachyon, a new monocotyledonous model plant, has received wide attention in biological research due to its small genome and numerous genetic resources. Codon usage bias is an important feature of genes and genomes, and it can be used in transgenic and evolutionary studies. In this study, the nucleotide compositions and patterns of codon usage bias were calculated using Codon W. Additionally, an ENC plot, Parity rule 2 and correspondence analyses were used to explore the major factors influencing codon usage bias patterns. The numbers of hydrogen bonds and skews were used to analyze the GC trend in the 5'-ends of the coding sequences. The results showed that minor differences in the codon usage bias patterns were revealed by the ENC plot, Parity rule 2 and correspondence analyses. The analyses of the CG-skew and the number of hydrogen bonds showed a declining trend in the number of cytosines at the 5'-ends of the CDSs (from the 5'-ends to the 3'-ends), indicating that GC may play a major role in codon usage bias. In addition, our results laid a foundation for the study of codon usage bias patterns in Brachypodium genus and suggested that the GC plays a major role in determining these patterns.

4EHP and GIGYF1/2 Mediate Translation-Coupled Messenger RNA Decay

Current models of mRNA turnover indicate that cytoplasmic degradation is coupled with translation. However, our understanding of the molecular events that coordinate ribosome transit with the mRNA decay machinery is still limited. Here, we show that 4EHP-GIGYF1/2 complexes trigger co-translational mRNA decay. Human cells lacking these proteins accumulate mRNAs with prominent ribosome pausing. They include, among others, transcripts encoding secretory and membrane-bound proteins or tubulin subunits. In addition, 4EHP-GIGYF1/2 complexes fail to reduce mRNA levels in the absence of ribosome stalling or upon disruption of their interaction with the cap structure, DDX6, and ZNF598. We further find that co-translational binding of GIGYF1/2 to the mRNA marks transcripts with perturbed elongation to decay. Our studies reveal how a repressor complex linked to neurological disorders minimizes the protein output of a subset of mRNAs.

Codon usage and protein length-dependent feedback from translation elongation regulates translation initiation and elongation speed

Essential cellular functions require efficient production of many large proteins but synthesis of large proteins encounters many obstacles in cells. Translational control is mostly known to be regulated at the initiation step. Whether translation elongation process can feedback to regulate initiation efficiency is unclear. Codon usage bias, a universal feature of all genomes, plays an important role in determining gene expression levels. Here, we discovered that there is a conserved but codon usage-dependent genome-wide negative correlation between protein abundance and CDS length. The codon usage effects on protein expression and ribosome flux on mRNAs are influenced by CDS length; optimal codon usage preferentially promotes production of large proteins. Translation of mRNAs with long CDS and non-optimal codon usage preferentially induces phosphorylation of initiation factor eIF2α, which inhibits translation initiation efficiency. Deletion of the eIF2α kinase CPC-3 (GCN2 homolog) in Neurospora preferentially up-regulates large proteins encoded by non-optimal codons. Surprisingly, CPC-3 also inhibits translation elongation rate in a codon usage and CDS length-dependent manner, resulting in slow elongation rates for long CDS mRNAs. Together, these results revealed a codon usage and CDS length-dependent feedback mechanism from translation elongation to regulate both translation initiation and elongation kinetics.

Modifications of mRNA vaccine structural elements for improving mRNA stability and translation efficiency

Background

mRNA vaccines hold great potential as therapeutic techniques against viral infections due to their efficacy, safety, and large-scale production. mRNA vaccines offer flexibility in development as any protein can be produced from mRNA without altering the production or application process.

Objective

This review highlights the iterative optimization of mRNA vaccine structural elements that impact the type, specificity, and intensity of immune responses leading to higher translational potency and intracellular stability.

Results

Modifying the mRNA structural elements particularly the 5′ cap, 5′-and 3′-untranslated regions (UTRs), the coding region, and polyadenylation tail help reduce the excessive mRNA immunogenicity and consistently improve its intracellular stability and translational efficiency.

Conclusion

Further studies regarding mRNA-structural elements and their optimization are needed to create new opportunities for engineering mRNA vaccines.

Developing a second-generation clinical candidate AAV vector for gene therapy of familial hypercholesterolemia

Gene therapy for hypercholesterolemia offers the potential to sustainably ameliorate disease for life with a single dose. In this study, we demonstrate the combinatorial effects of codon and vector optimization, which significantly improve the efficacy of an adeno-associated virus (AAV) vector in the low-density lipoprotein receptor (LDLR)-deficient mouse model (Ldlr -/-, Apobec1 -/- double knockout [DKO]). This study investigated vector efficacy following the combination of intervening sequence 2 (IVS2) of the human beta-globin gene and codon optimization with the previously developed gain-of-function, human LDLR triple-mutant variant (hLDLR-L318D/K809R/C818A) in the treatment of homozygous familial hypercholesterolemia (HoFH). Vector doses as low as 3 × 1011 genome copies (GC)/kg achieved a robust reduction of serum low-density lipoprotein cholesterol (LDL-C) by 98% in male LDLR-deficient mice. Less efficient LDL-C reduction was observed in female mice, which was attributable to lower gene transfer efficiency in liver. We also observed persistent and stable transgene expression for 120 days, with LDL-C levels being undetectable in male DKO mice treated with the second-generation vector. In conclusion, codon and vector optimization enhanced transgene expression and reduced serum LDL-C levels effectively at a lower dose in LDLR-deficient mice. The second-generation clinical candidate vector we have developed has the potential to achieve therapeutic effects in HoFH patients.

Variability in Codon Usage in Coronaviruses Is Mainly Driven by Mutational Bias and Selective Constraints on CpG Dinucleotide

The Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the third human-emerged virus of the 21st century from the Coronaviridae family, causing the ongoing coronavirus disease 2019 (COVID-19) pandemic. Due to the high zoonotic potential of coronaviruses, it is critical to unravel their evolutionary history of host species breadth, host-switch potential, adaptation and emergence, to identify viruses posing a pandemic risk in humans. We present here a comprehensive analysis of the composition and codon usage bias of the 82 Orthocoronavirinae members, infecting 47 different avian and mammalian hosts. Our results clearly establish that synonymous codon usage varies widely among viruses, is only weakly dependent on their primary host, and is dominated by mutational bias towards AU-enrichment and by CpG avoidance. Indeed, variation in GC3 explains around 34%, while variation in CpG frequency explains around 14% of total variation in codon usage bias. Further insight on the mutational equilibrium within Orthocoronavirinae revealed that most coronavirus genomes are close to their neutral equilibrium, the exception being the three recently infecting human coronaviruses, which lie further away from the mutational equilibrium than their endemic human coronavirus counterparts. Finally, our results suggest that, while replicating in humans, SARS-CoV-2 is slowly becoming AU-richer, likely until attaining a new mutational equilibrium.

A Code Within a Code: How Codons Fine-Tune Protein Folding in the Cell

The genetic code sets the correspondence between the sequence of a given nucleotide triplet in an mRNA molecule, called a codon, and the amino acid that is added to the growing polypeptide chain during protein synthesis. With four bases (A, G, U, and C), there are 64 possible triplet codons: 61 sense codons (encoding amino acids) and 3 nonsense codons (so-called, stop codons that define termination of translation). In most organisms, there are 20 common/standard amino acids used in protein synthesis; thus, the genetic code is redundant with most amino acids (with the exception of Met and Trp) are being encoded by more than one (synonymous) codon. Synonymous codons were initially presumed to have entirely equivalent functions, however, the finding that synonymous codons are not present at equal frequencies in mRNA suggested that the specific codon choice might have functional implications beyond coding for amino acid. Observation of nonequivalent use of codons in mRNAs implied a possibility of the existence of auxiliary information in the genetic code. Indeed, it has been found that genetic code contains several layers of such additional information and that synonymous codons are strategically placed within mRNAs to ensure a particular translation kinetics facilitating and fine-tuning co-translational protein folding in the cell via step-wise/sequential structuring of distinct regions of the polypeptide chain emerging from the ribosome at different points in time. This review summarizes key findings in the field that have identified the role of synonymous codons and their usage in protein folding in the cell.

A (dis)integrated stress response: Genetic diseases of eIF2α regulators

The integrated stress response (ISR) is a conserved mechanism by which eukaryotic cells remodel gene expression to adapt to intrinsic and extrinsic stressors rapidly and reversibly. The ISR is initiated when stress-activated protein kinases phosphorylate the major translation initiation factor eukaryotic translation initiation factor 2ɑ (eIF2ɑ), which globally suppresses translation initiation activity and permits the selective translation of stress-induced genes including important transcription factors such as activating transcription factor 4 (ATF4). Translationally repressed messenger RNAs (mRNAs) and noncoding RNAs assemble into cytoplasmic RNA-protein granules and polyadenylated RNAs are concomitantly stabilized. Thus, regulated changes in mRNA translation, stability, and localization to RNA-protein granules contribute to the reprogramming of gene expression that defines the ISR. We discuss fundamental mechanisms of RNA regulation during the ISR and provide an overview of a growing class of genetic disorders associated with mutant alleles of key translation factors in the ISR pathway. This article is categorized under: RNA Interactions with Proteins and Other Molecules > Protein-RNA Interactions: Functional Implications RNA in Disease and Development > RNA in Disease Translation > Translation Regulation RNA in Disease and Development > RNA in Development.

New SHH and Known SIX3 Variants in a Series of Latin American Patients with Holoprosencephaly

Holoprosencephaly (HPE) is the failure of the embryonic forebrain to develop into 2 hemispheres promoting midline cerebral and facial defects. The wide phenotypic variability and causal heterogeneity make genetic counseling difficult. Heterozygous variants with incomplete penetrance and variable expressivity in the SHH, SIX3, ZIC2, and TGIF1 genes explain ∼25% of the known causes of nonchromosomal HPE. We studied these 4 genes and clinically described 27 Latin American families presenting with nonchromosomal HPE. Three new SHH variants and a third known SIX3 likely pathogenic variant found by Sanger sequencing explained 15% of our cases. Genotype-phenotype correlation in these 4 families and published families with identical or similar driver gene, mutated domain, conservation of residue in other species, and the type of variant explain the pathogenicity but not the phenotypic variability. Nine patients, including 2 with SHH pathogenic variants, presented benign variants of the SHH, SIX3, ZIC2, and TGIF1 genes with potential alteration of splicing, a causal proposition in need of further studies. Finding more families with the same SIX3 variant may allow further identification of genetic or environmental modifiers explaining its variable phenotypic expression.

Landscape of the Dark Transcriptome Revealed Through Re-mining Massive RNA-Seq Data

The "dark transcriptome" can be considered the multitude of sequences that are transcribed but not annotated as genes. We evaluated expression of 6,692 annotated genes and 29,354 unannotated open reading frames (ORFs) in the Saccharomyces cerevisiae genome across diverse environmental, genetic and developmental conditions (3,457 RNA-Seq samples). Over 30% of the highly transcribed ORFs have translation evidence. Phylostratigraphic analysis infers most of these transcribed ORFs would encode species-specific proteins ("orphan-ORFs"); hundreds have mean expression comparable to annotated genes. These data reveal unannotated ORFs most likely to be protein-coding genes. We partitioned a co-expression matrix by Markov Chain Clustering; the resultant clusters contain 2,468 orphan-ORFs. We provide the aggregated RNA-Seq yeast data with extensive metadata as a project in MetaOmGraph (MOG), a tool designed for interactive analysis and visualization. This approach enables reuse of public RNA-Seq data for exploratory discovery, providing a rich context for experimentalists to make novel, experimentally testable hypotheses about candidate genes.

Global view on the metabolism of RNA poly(A) tails in yeast Saccharomyces cerevisiae

The polyadenosine tail (poly[A]-tail) is a universal modification of eukaryotic messenger RNAs (mRNAs) and non-coding RNAs (ncRNAs). In budding yeast, Pap1-synthesized mRNA poly(A) tails enhance export and translation, whereas Trf4/5-mediated polyadenylation of ncRNAs facilitates degradation by the exosome. Using direct RNA sequencing, we decipher the extent of poly(A) tail dynamics in yeast defective in all relevant exonucleases, deadenylases, and poly(A) polymerases. Predominantly ncRNA poly(A) tails are 20-60 adenosines long. Poly(A) tails of newly transcribed mRNAs are 50 adenosine long on average, with an upper limit of 200. Exonucleolysis by Trf5-assisted nuclear exosome and cytoplasmic deadenylases trim the tails to 40 adenosines on average. Surprisingly, PAN2/3 and CCR4-NOT deadenylase complexes have a large pool of non-overlapping substrates mainly defined by expression level. Finally, we demonstrate that mRNA poly(A) tail length strongly responds to growth conditions, such as heat and nutrient deprivation.

Estimating the predictive power of silent mutations on cancer classification and prognosis

In recent years it has been shown that silent mutations, in and out of the coding region, can affect gene expression and may be related to tumorigenesis and cancer cell fitness. However, the predictive ability of these mutations for cancer type diagnosis and prognosis has not been evaluated yet. In the current study, based on the analysis of 9,915 cancer genomes and approximately three million mutations, we provide a comprehensive quantitative evaluation of the predictive power of various types of silent and non-silent mutations over cancer classification and prognosis. The results indicate that silent-mutation models outperform the equivalent null models in classifying all examined cancer types and in estimating the probability of survival 10 years after the initial diagnosis. Additionally, combining both non-silent and silent mutations achieved the best classification results for 68% of the cancer types and the best survival estimation results for up to nine years after the diagnosis. Thus, silent mutations hold considerable predictive power over both cancer classification and prognosis, most likely due to their effect on gene expression. It is highly advised that silent mutations are integrated in cancer research in order to unravel the full genomic landscape of cancer and its ramifications on cancer fitness.

RNA degradation is required for the germ-cell to maternal transition in Drosophila

In sexually reproducing animals, the oocyte contributes a large supply of RNAs that are essential to launch development upon fertilization. The mechanisms that regulate the composition of the maternal RNA contribution during oogenesis are unclear. Here, we show that a subset of RNAs expressed during the early stages of oogenesis is subjected to regulated degradation during oocyte specification. Failure to remove these RNAs results in oocyte dysfunction and death. We identify the RNA-degrading Super Killer complex and No-Go Decay factor Pelota as key regulators of oogenesis via targeted degradation of specific RNAs expressed in undifferentiated germ cells. These regulators target RNAs enriched for cytidine sequences that are bound by the polypyrimidine tract binding protein Half pint. Thus, RNA degradation helps orchestrate a germ cell-to-maternal transition that gives rise to the maternal contribution to the zygote.

Platforms for Production of Protein-Based Vaccines: From Classical to Next-Generation Strategies

To date, vaccination has become one of the most effective strategies to control and reduce infectious diseases, preventing millions of deaths worldwide. The earliest vaccines were developed as live-attenuated or inactivated pathogens, and, although they still represent the most extended human vaccine types, they also face some issues, such as the potential to revert to a pathogenic form of live-attenuated formulations or the weaker immune response associated with inactivated vaccines. Advances in genetic engineering have enabled improvements in vaccine design and strategies, such as recombinant subunit vaccines, have emerged, expanding the number of diseases that can be prevented. Moreover, antigen display systems such as VLPs or those designed by nanotechnology have improved the efficacy of subunit vaccines. Platforms for the production of recombinant vaccines have also evolved from the first hosts, Escherichia coli and Saccharomyces cerevisiae, to insect or mammalian cells. Traditional bacterial and yeast systems have been improved by engineering and new systems based on plants or insect larvae have emerged as alternative, low-cost platforms. Vaccine development is still time-consuming and costly, and alternative systems that can offer cost-effective and faster processes are demanding to address infectious diseases that still do not have a treatment and to face possible future pandemics.

Dynamics of transcriptional and post-transcriptional regulation

Despite gene expression programs being notoriously complex, RNA abundance is usually assumed as a proxy for transcriptional activity. Recently developed approaches, able to disentangle transcriptional and post-transcriptional regulatory processes, have revealed a more complex scenario. It is now possible to work out how synthesis, processing and degradation kinetic rates collectively determine the abundance of each gene's RNA. It has become clear that the same transcriptional output can correspond to different combinations of the kinetic rates. This underscores the fact that markedly different modes of gene expression regulation exist, each with profound effects on a gene's ability to modulate its own expression. This review describes the development of the experimental and computational approaches, including RNA metabolic labeling and mathematical modeling, that have been disclosing the mechanisms underlying complex transcriptional programs. Current limitations and future perspectives in the field are also discussed.

A deep learning model for predicting next-generation sequencing depth from DNA sequence

Targeted high-throughput DNA sequencing is a primary approach for genomics and molecular diagnostics, and more recently as a readout for DNA information storage. Oligonucleotide probes used to enrich gene loci of interest have different hybridization kinetics, resulting in non-uniform coverage that increases sequencing costs and decreases sequencing sensitivities. Here, we present a deep learning model (DLM) for predicting Next-Generation Sequencing (NGS) depth from DNA probe sequences. Our DLM includes a bidirectional recurrent neural network that takes as input both DNA nucleotide identities as well as the calculated probability of the nucleotide being unpaired. We apply our DLM to three different NGS panels: a 39,145-plex panel for human single nucleotide polymorphisms (SNP), a 2000-plex panel for human long non-coding RNA (lncRNA), and a 7373-plex panel targeting non-human sequences for DNA information storage. In cross-validation, our DLM predicts sequencing depth to within a factor of 3 with 93% accuracy for the SNP panel, and 99% accuracy for the non-human panel. In independent testing, the DLM predicts the lncRNA panel with 89% accuracy when trained on the SNP panel. The same model is also effective at predicting the measured single-plex kinetic rate constants of DNA hybridization and strand displacement.

DNA probes used in next generation sequencing (NGS) have variable hybridisation kinetics, resulting in non-uniform coverage. Here, the authors develop a deep learning model to predict NGS depth using DNA probe sequences and apply to human and non-human sequencing panels.

Enhancing immunogenicity of HPV16 E7 DNA vaccine by conjugating codon-optimized GM-CSF to HPV16 E7 DNA

OBJECTIVE

To generate immunity against human papillomavirus (HPV), the use of a recombinant DNA vaccine to carry an appropriate target gene is a promising and cost-effective approach. Granulocyte-macrophage colony-stimulating factor (GM-CSF) is a potent immunomodulatory cytokine that enhances the efficacy of vaccines by promoting the development and prolongation of humoral and cellular immunity. In this study, we linked codon-optimized GM-CSF (cGM-CSF) to the HPV16 E7 sequence as fused protein and evaluated the immunogenic potential of this DNA vaccine.

MATERIALS AND METHODS

We have demonstrated that cGM-CSF enhanced immunity against tumor challenges by generating and promoting the proliferation of HPV16 E7-specific CD8+ T cells, which secrete IFN-γ in the murine model. In this study, we aimed to evaluate the immunogenic potential of DNA vaccine that constructed by linking codon-optimized GM-CSF to HPV16 E7 sequence in the animal model. We study the half-life of RNA decay and cellular location of HPV16 E7 by Q-PCR and Western blot. We also assess immune response in the animal model by flow cytometry and ELISA.

RESULTS

The cGM-CSF-E7 sequence increased and extended the expression of E7 mRNA, in comparison with the E7 sequence alone. Mice vaccinated with the cGM-CSF-E7 DNA vaccine exhibited a slower rate of tumor growth than those vaccinated with the unconjugated E7 DNA vaccine. We also found that the CD4 and CD8+ T cells from these mice showed strong secretion of IFN-γ.

CONCLUSION

Through in vivo antibody depletion experiments, we demonstrated that both CD4+ and CD8+ T cells play an important role in the suppression of tumor growth.

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

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

Resistance Exercise, Aging, Disuse, and Muscle Protein Metabolism

Skeletal muscle is the organ of locomotion, its optimal function is critical for athletic performance, and is also important for health due to its contribution to resting metabolic rate and as a site for glucose uptake and storage. Numerous endogenous and exogenous factors influence muscle mass. Much of what is currently known regarding muscle protein turnover is owed to the development and use of stable isotope tracers. Skeletal muscle mass is determined by the meal- and contraction-induced alterations of muscle protein synthesis and muscle protein breakdown. Increased loading as resistance training is the most potent nonpharmacological strategy by which skeletal muscle mass can be increased. Conversely, aging (sarcopenia) and muscle disuse lead to the development of anabolic resistance and contribute to the loss of skeletal muscle mass. Nascent omics-based technologies have significantly improved our understanding surrounding the regulation of skeletal muscle mass at the gene, transcript, and protein levels. Despite significant advances surrounding the mechanistic intricacies that underpin changes in skeletal muscle mass, these processes are complex, and more work is certainly needed. In this article, we provide an overview of the importance of skeletal muscle, describe the influence that resistance training, aging, and disuse exert on muscle protein turnover and the molecular regulatory processes that contribute to changes in muscle protein abundance. © 2021 American Physiological Society. Compr Physiol 11:2249-2278, 2021.

Genome-wide role of codon usage on transcription and identification of potential regulators

Codon usage bias is a fundamental feature of all genomes and plays an important role in determining gene expression levels. The codon usage was thought to influence gene expression mainly due to its impact on translation. Recently, however, codon usage was shown to affect transcription of fungal and mammalian genes, indicating the existence of a gene regulatory phenomenon with unknown mechanism. In Neurospora, codon usage biases strongly correlate with mRNA levels genome-wide, and here we show that the correlation between codon usage and RNA levels is maintained in the nucleus. In addition, codon optimality is tightly correlated with both total and nuclear RNA levels, suggesting that codon usage broadly influences mRNA levels through transcription in a translation-independent manner. A large-scale RNA sequencing-based genetic screen in Neurospora identified 18 candidate factors that when deleted decreased the genome-wide correlation between codon usage and RNA levels and reduced the codon usage effect on gene expression. Most of these factors, such as the H3K36 methyltransferase, are chromatin regulators or transcription factors. Together, our results suggest that the transcriptional effect of codon usage is mediated by multiple transcriptional regulatory mechanisms.

Translational autoregulation of RF2 protein in E. coli through programmed frameshifting

Various feedback mechanisms regulate the expression of different genes to ensure the required protein levels inside a cell. In this paper, we develop a kinetic model for one such mechanism that autoregulates RF2 protein synthesis in E. coli through programmed frameshifting. The model finds that the programmed frameshifting autoregulates RF2 protein synthesis by two independent mechanisms. First, it increases the rate of RF2 synthesis from each mRNA transcript at low RF2 concentration. Second, programmed frameshifting can dramatically increase the lifetime of RF2 transcripts when RF2 protein levels are lower than a threshold. This sharp increase in mRNA lifetime is caused by a first-order phase transition from a low to a high ribosome density on an RF2 transcript. The high ribosome density prevents the transcript's degradation by shielding it from nucleases, which increases its average lifetime and hence RF2 protein levels. Our study identifies this quality control mechanism that regulates the cellular protein levels by breaking the hierarchy of processes involved in gene expression.