Codon optimality, bias and usage in translation and mRNA decay

Combinatorial optimization of mRNA structure, stability, and translation for RNA-based therapeutics

Therapeutic mRNAs and vaccines are being developed for a broad range of human diseases, including COVID-19. However, their optimization is hindered by mRNA instability and inefficient protein expression. Here, we describe design principles that overcome these barriers. We develop an RNA sequencing-based platform called PERSIST-seq to systematically delineate in-cell mRNA stability, ribosome load, as well as in-solution stability of a library of diverse mRNAs. We find that, surprisingly, in-cell stability is a greater driver of protein output than high ribosome load. We further introduce a method called In-line-seq, applied to thousands of diverse RNAs, that reveals sequence and structure-based rules for mitigating hydrolytic degradation. Our findings show that highly structured "superfolder" mRNAs can be designed to improve both stability and expression with further enhancement through pseudouridine nucleoside modification. Together, our study demonstrates simultaneous improvement of mRNA stability and protein expression and provides a computational-experimental platform for the enhancement of mRNA medicines.

Bias at the third nucleotide of codon pairs in virus and host genomes

Genomes of different sizes and complexity can be compared using common features. Most genomes contain open reading frames, and most genomes use the same genetic code. Redundancy in the genetic code means that different biases in the third nucleotide position of a codon exist in different genomes. However, the nucleotide composition of viruses can be quite different from host nucleotide composition making it difficult to assess the relevance of these biases. Here we show that grouping codons of a codon-pair according to the GC content of the first two nucleotide positions of each codon reveals patterns in nucleotide usage at the third position of the 1st codon. Differences between the observed and expected biases occur predominantly when the first two nucleotides of the 2nd codon are both S (strong, G or C) or both W (weak, A or T), not a mixture of strong and weak. The data indicates that some codon pairs are preferred because of the strength of the interactions between the codon and anticodon, the adjacent tRNAs and the ribosome. Using base-pairing strength and third position bias facilitates the comparison of genomes of different size and nucleotide composition and reveals patterns not previously described.

Integrative genetic and immune cell analysis of plasma proteins in healthy donors identifies novel associations involving primary immune deficiency genes

BACKGROUND

Blood plasma proteins play an important role in immune defense against pathogens, including cytokine signaling, the complement system, and the acute-phase response. Recent large-scale studies have reported genetic (i.e., protein quantitative trait loci, pQTLs) and non-genetic factors, such as age and sex, as major determinants to inter-individual variability in immune response variation. However, the contribution of blood-cell composition to plasma protein heterogeneity has not been fully characterized and may act as a mediating factor in association studies.

METHODS

Here, we evaluated plasma protein levels from 400 unrelated healthy individuals of western European ancestry, who were stratified by sex and two decades of life (20-29 and 60-69 years), from the Milieu Intérieur cohort. We quantified 229 proteins by Luminex in a clinically certified laboratory and their levels of variation were analyzed together with 5.2 million single-nucleotide polymorphisms. With respect to non-genetic variables, we included 254 lifestyle and biochemical factors, as well as counts of seven circulating immune cell populations measured by hemogram and standardized flow cytometry.

RESULTS

Collectively, we found 152 significant associations involving 49 proteins and 20 non-genetic variables. Consistent with previous studies, age and sex showed a global, pervasive impact on plasma protein heterogeneity, while body mass index and other health status variables were among the non-genetic factors with the highest number of associations. After controlling for these covariates, we identified 100 and 12 pQTLs acting in cis and trans, respectively, collectively associated with 87 plasma proteins and including 19 novel genetic associations. Genetic factors explained the largest fraction of the variability of plasma protein levels, as compared to non-genetic factors. In addition, blood-cell fractions, including leukocytes, lymphocytes, monocytes, neutrophils, eosinophils, basophils, and platelets, had a larger contribution to inter-individual variability than age and sex and appeared as confounders of specific genetic associations. Finally, we identified new genetic associations with plasma protein levels of five monogenic Mendelian disease genes including two primary immunodeficiency genes (Ficolin-3 and FAS).

CONCLUSIONS

Our study identified novel genetic and non-genetic factors associated to plasma protein levels which may inform health status and disease management.

Immunogenicity mechanism of mRNA vaccines and their limitations in promoting adaptive protection against SARS-CoV-2

Since the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19) in late 2019, hundreds of millions of people have been infected worldwide. There have been unprecedented efforts in acquiring effective vaccines to confer protection against the disease. mRNA vaccines have emerged as promising alternatives to conventional vaccines due to their high potency with the capacity for rapid development and low manufacturing costs. In this review, we summarize the currently available vaccines against SARS-CoV-2 in development, with the focus on the concepts of mRNA vaccines, their antigen selection, delivery and optimization to increase the immunostimulatory capability of mRNA as well as its stability and translatability. We also discuss the host immune responses to the SARS-CoV-2 infection and expound in detail, the adaptive immune response upon immunization with mRNA vaccines, in which high levels of spike-specific IgG and neutralizing antibodies were detected after two-dose vaccination. mRNA vaccines have been shown to induce a robust CD8⁺T cell response, with a balanced CD4⁺ T_H1/T_H2 response. We further discuss the challenges and limitations of COVID-19 mRNA vaccines, where newly emerging variants of SARS-CoV-2 may render currently deployed vaccines less effective. Imbalanced and inappropriate inflammatory responses, resulting from hyper-activation of pro-inflammatory cytokines, which may lead to vaccine-associated enhanced respiratory disease (VAERD) and rare cases of myocarditis and pericarditis also are discussed.

Codon-Restrained Method for Both Eliminating and Creating Intragenic Bacterial Promoters

Future applications of synthetic biology will require refactored genetic sequences devoid of internal regulatory elements within coding sequences. These regulatory elements include cryptic and intragenic promoters, which may constitute up to a third of the predicted Escherichia coli promoters. The promoter activity is dependent on the structural interaction of core bases with a σ factor. Rational engineering can be used to alter key promoter element nucleotides interacting with σ factors and eliminate downstream transcriptional activity. In this paper, we present codon-restrained promoter silencing (CORPSE), a system for removing intragenic promoters. CORPSE exploits the DNA-σ factor structural relationship to disrupt σ⁷⁰ promoters embedded within gene coding sequences with a minimum of synonymous codon changes. Additionally, we present an inverted CORPSE system, iCORPSE, which can create highly active promoters within a gene sequence while not perturbing the function of the modified gene.

Roles of mRNA poly(A) tails in regulation of eukaryotic gene expression

In eukaryotes, poly(A) tails are present on almost every mRNA. Early experiments led to the hypothesis that poly(A) tails and the cytoplasmic polyadenylate-binding protein (PABPC) promote translation and prevent mRNA degradation, but the details remained unclear. More recent data suggest that the role of poly(A) tails is much more complex: poly(A)-binding protein can stimulate poly(A) tail removal (deadenylation) and the poly(A) tails of stable, highly translated mRNAs at steady state are much shorter than expected. Furthermore, the rate of translation elongation affects deadenylation. Consequently, the interplay between poly(A) tails, PABPC, translation and mRNA decay has a major role in gene regulation. In this Review, we discuss recent work that is revolutionizing our understanding of the roles of poly(A) tails in the cytoplasm. Specifically, we discuss the roles of poly(A) tails in translation and control of mRNA stability and how poly(A) tails are removed by exonucleases (deadenylases), including CCR4-NOT and PAN2-PAN3. We also discuss how deadenylation rate is determined, the integration of deadenylation with other cellular processes and the function of PABPC. We conclude with an outlook for the future of research in this field.

Removing the Bottleneck: Introducing cMatch - A Lightweight Tool for Construct-Matching in Synthetic Biology

We present a software tool, called cMatch, to reconstruct and identify synthetic genetic constructs from their sequences, or a set of sub-sequences—based on two practical pieces of information: their modular structure, and libraries of components. Although developed for combinatorial pathway engineering problems and addressing their quality control (QC) bottleneck, cMatch is not restricted to these applications. QC takes place post assembly, transformation and growth. It has a simple goal, to verify that the genetic material contained in a cell matches what was intended to be built - and when it is not the case, to locate the discrepancies and estimate their severity. In terms of reproducibility/reliability, the QC step is crucial. Failure at this step requires repetition of the construction and/or sequencing steps. When performed manually or semi-manually QC is an extremely time-consuming, error prone process, which scales very poorly with the number of constructs and their complexity. To make QC frictionless and more reliable, cMatch performs an operation we have called “construct-matching” and automates it. Construct-matching is more thorough than simple sequence-matching, as it matches at the functional level-and quantifies the matching at the individual component level and across the whole construct. Two algorithms (called CM_1 and CM_2) are presented. They differ according to the nature of their inputs. CM_1 is the core algorithm for construct-matching and is to be used when input sequences are long enough to cover constructs in their entirety (e.g., obtained with methods such as next generation sequencing). CM_2 is an extension designed to deal with shorter data (e.g., obtained with Sanger sequencing), and that need recombining. Both algorithms are shown to yield accurate construct-matching in a few minutes (even on hardware with limited processing power), together with a set of metrics that can be used to improve the robustness of the decision-making process. To ensure reliability and reproducibility, cMatch builds on the highly validated pairwise-matching Smith-Waterman algorithm. All the tests presented have been conducted on synthetic data for challenging, yet realistic constructs - and on real data gathered during studies on a metabolic engineering example (lycopene production).

Computational modeling of mRNA degradation dynamics using deep neural networks

MOTIVATION

messenger RNA (mRNA) degradation plays critical roles in post-transcriptional gene regulation. A major component of mRNA degradation is determined by 3'-UTR elements. Hence, researchers are interested in studying mRNA dynamics as a function of 3'-UTR elements. A recent study measured the mRNA degradation dynamics of tens of thousands of 3'-UTR sequences using a massively parallel reporter assay. However, the computational approach used to model mRNA degradation was based on a simplifying assumption of a linear degradation rate. Consequently, the underlying mechanism of 3'-UTR elements is still not fully understood.

RESULTS

Here, we developed deep neural networks to predict mRNA degradation dynamics and interpreted the networks to identify regulatory elements in the 3'-UTR and their positional effect. Given an input of a 110 nt-long 3'-UTR sequence and an initial mRNA level, the model predicts mRNA levels of eight consecutive time points. Our deep neural networks significantly improved prediction performance of mRNA degradation dynamics compared with extant methods for the task. Moreover, we demonstrated that models predicting the dynamics of two identical 3'-UTR sequences, differing by their poly(A) tail, performed better than single-task models. On the interpretability front, by using Integrated Gradients, our convolutional neural networks (CNNs) models identified known and novel cis-regulatory sequence elements of mRNA degradation. By applying a novel systematic evaluation of model interpretability, we demonstrated that the recurrent neural network models are inferior to the CNN models in terms of interpretability and that random initialization ensemble improves both prediction and interoperability performance. Moreover, using a mutagenesis analysis, we newly discovered the positional effect of various 3'-UTR elements.

AVAILABILITY AND IMPLEMENTATION

All the code developed through this study is available at github.com/OrensteinLab/DeepUTR/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Plasma cell-free RNA characteristics in COVID-19 patients

The pathogenesis of COVID-19 is still elusive, which impedes disease progression prediction, differential diagnosis, and targeted therapy. Plasma cell-free RNAs (cfRNAs) carry unique information from human tissue and thus could point to resourceful solutions for pathogenesis and host-pathogen interactions. Here, we performed a comparative analysis of cfRNA profiles between COVID-19 patients and healthy donors using serial plasma. Analyses of the cfRNA landscape, potential gene regulatory mechanisms, dynamic changes in tRNA pools upon infection, and microbial communities were performed. A total of 380 cfRNA molecules were up-regulated in all COVID-19 patients, of which seven could serve as potential biomarkers (AUC > 0.85) with great sensitivity and specificity. Antiviral (NFKB1A, IFITM3, and IFI27) and neutrophil activation (S100A8, CD68, and CD63)–related genes exhibited decreased expression levels during treatment in COVID-19 patients, which is in accordance with the dynamically enhanced inflammatory response in COVID-19 patients. Noncoding RNAs, including some microRNAs (let 7 family) and long noncoding RNAs (GJA9-MYCBP) targeting interleukin (IL6/IL6R), were differentially expressed between COVID-19 patients and healthy donors, which accounts for the potential core mechanism of cytokine storm syndromes; the tRNA pools change significantly between the COVID-19 and healthy group, leading to the accumulation of SARS-CoV-2 biased codons, which facilitate SARS-CoV-2 replication. Finally, several pneumonia-related microorganisms were detected in the plasma of COVID-19 patients, raising the possibility of simultaneously monitoring immune response regulation and microbial communities using cfRNA analysis. This study fills the knowledge gap in the plasma cfRNA landscape of COVID-19 patients and offers insight into the potential mechanisms of cfRNAs to explain COVID-19 pathogenesis.

tRNA biogenesis and specific aminoacyl-tRNA synthetases regulate senescence stability under the control of mTOR

Oncogenes or chemotherapy treatments trigger the induction of suppressive pathways such as apoptosis or senescence. Senescence was initially defined as a definitive arrest of cell proliferation but recent results have shown that this mechanism is also associated with cancer progression and chemotherapy resistance. Senescence is therefore much more heterogeneous than initially thought. How this response varies is not really understood, it has been proposed that its outcome relies on the secretome of senescent cells and on the maintenance of their epigenetic marks. Using experimental models of senescence escape, we now described that the stability of this proliferative arrest relies on specific tRNAs and aminoacyl-tRNA synthetases. Following chemotherapy treatment, the DNA binding of the type III RNA polymerase was reduced to prevent tRNA transcription and induce a complete cell cycle arrest. By contrast, during senescence escape, specific tRNAs such as tRNA-Leu-CAA and tRNA-Tyr-GTA were up-regulated. Reducing tRNA transcription appears necessary to control the strength of senescence since RNA pol III inhibition through BRF1 depletion maintained senescence and blocked the generation of escaping cells. mTOR inhibition also prevented chemotherapy-induced senescence escape in association with a reduction of tRNA-Leu-CAA and tRNA-Tyr-GTA expression. Further confirming the role of the tRNA-Leu-CAA and tRNA-Tyr-GTA, results showed that their corresponding tRNA ligases, LARS and YARS, were necessary for senescence escape. This effect was specific since the CARS ligase had no effect on persistence. By contrast, the down-regulation of LARS and YARS reduced the emergence of persistent cells and this was associated with the modulation of E2F1 target genes expression. Overall, these findings highlight a new regulation of tRNA biology during senescence and suggest that specific tRNAs and ligases contribute to the strength and heterogeneity of this tumor suppressive pathway.

Senescence is a tumor suppressive mechanism induced in response to oncogenes or chemotherapy. Senescence was initially defined as a definitive arrest of cell proliferation but doubts have emerged as to the value of this mechanism in terms of suppression. Recent findings published by several laboratories including our own have shown that some cells escape senescence to become more transformed. This study shows that different tRNAs are expressed in growing, senescent or emerging cells. The tRNA-Leu-CAA and tRNA-Tyr-GTA are up-regulated during senescence escape whereas this was not the case of the other tRNAs tested. In addition, using proteomic analysis and inactivation experiments, we found that the corresponding tRNA ligases, YARS for tRNA-Tyr-GTA and LARS for the tRNA-Leu-CAA, are necessary for senescence escape. Results also show that the expression of the tRNA-Leu-CAA and tRNA-Tyr-GTA are controlled by the mTOR pathway and that this kinase is necessary for senescence escape. Reducing tRNA transcription appears necessary to control the strength of senescence since RNA pol III inhibition maintained senescence and blocked the generation of escaping cells. In light of these results, we propose the hypothesis that the heterogeneity of tRNAs and ligases expression leads to distinct states of light or deep senescence.

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.

Strategies and Patterns of Codon Bias in Molluscum Contagiosum Virus

Trends associated with codon usage in molluscum contagiosum virus (MCV) and factors governing the evolution of codon usage have not been investigated so far. In this study, attempts were made to decipher the codon usage trends and discover the major evolutionary forces that influence the patterns of codon usage in MCV with special reference to sub-types 1 and 2, MCV-1 and MCV-2, respectively. Three hypotheses were tested: (1) codon usage patterns of MCV-1 and MCV-2 are identical; (2) SCUB (synonymous codon usage bias) patterns of MCV-1 and MCV-2 slightly deviate from that of human host to avoid affecting the fitness of host; and (3) translational selection predominantly shapes the SCUB of MCV-1 and MCV-2. Various codon usage indices viz. relative codon usage value, effective number of codons and codon adaptation index were calculated to infer the nature of codon usage. Correspondence analysis and correlation analysis were performed to assess the relative contribution of silent base contents and significance of codon usage indices in defining bias in codon usage. Among the tested hypotheses, only the second and third hypotheses were accepted.

Codon usage in the flatworm Schistosoma mansoni is shaped by the mutational bias towards A+T and translational selection, which increases GC-ending codons in highly expressed genes

Schistosoma mansoni is a trematode flatworm that parasitizes humans and produces a disease called bilharzia. At the genomic level, it is characterized by a low genomic GC content and an "isochore-like" structure, where GC-richest regions, mainly placed at the extremes of the chromosomes, are interspersed with low GC-regions. Furthermore, the GC-richest regions are at the same time the gene-richest, and where the most heavily expressed genes are placed. Taking these features into account, we decided to reanalyze the codon usage of this flatworm. Our results show that a) when all genes are considered together, the strong mutational bias towards A + T leads to a predominance of A/T-ending codons, b) a multivariate analysis discriminates between highly and lowly expressed genes, c) the sequences expressed at highest levels display a significant increase in G/C-ending codons, d) when comparing the molecular distances with a closely related species the synonymous distance in highly expressed genes is significantly lower than in lowly expressed sequences. Therefore, we conclude that despite previous results, which were performed with a small sample of genes, codon usage in S. mansoni is the result of two forces that operate in opposite directions: while mutational bias leads to a predominance of A/T codons, translational selection, working at the level of speed, increment G/C ending triplets.

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.

A dual role of human tRNA methyltransferase hTrmt13 in regulating translation and transcription

Since numerous RNAs and RBPs prevalently localize to active chromatin regions, many RNA-binding proteins (RBPs) may be potential transcriptional regulators. RBPs are generally thought to regulate transcription via noncoding RNAs. Here, we describe a distinct, dual mechanism of transcriptional regulation by the previously uncharacterized tRNA-modifying enzyme, hTrmt13. On one hand, hTrmt13 acts in the cytoplasm to catalyze 2'-O-methylation of tRNAs, thus regulating translation in a manner depending on its tRNA-modification activity. On the other hand, nucleus-localized hTrmt13 directly binds DNA as a transcriptional co-activator of key epithelial-mesenchymal transition factors, thereby promoting cell migration independent of tRNA-modification activity. These dual functions of hTrmt13 are mutually exclusive, as it can bind either DNA or tRNA through its CHHC zinc finger domain. Finally, we find that hTrmt13 expression is tightly associated with poor prognosis and survival in diverse cancer patients. Our discovery of the noncatalytic roles of an RNA-modifying enzyme provides a new perspective for understanding epitranscriptomic regulation.

Codon usage bias

Codon usage bias is the preferential or non-random use of synonymous codons, a ubiquitous phenomenon observed in bacteria, plants and animals. Different species have consistent and characteristic codon biases. Codon bias varies not only with species, family or group within kingdom, but also between the genes within an organism. Codon usage bias has evolved through mutation, natural selection, and genetic drift in various organisms. Genome composition, GC content, expression level and length of genes, position and context of codons in the genes, recombination rates, mRNA folding, and tRNA abundance and interactions are some factors influencing codon bias. The factors shaping codon bias may also be involved in evolution of the universal genetic code. Codon-usage bias is critical factor determining gene expression and cellular function by influencing diverse processes such as RNA processing, protein translation and protein folding. Codon usage bias reflects the origin, mutation patterns and evolution of the species or genes. Investigations of codon bias patterns in genomes can reveal phylogenetic relationships between organisms, horizontal gene transfers, molecular evolution of genes and identify selective forces that drive their evolution. Most important application of codon bias analysis is in the design of transgenes, to increase gene expression levels through codon optimization, for development of transgenic crops. The review gives an overview of deviations of genetic code, factors influencing codon usage or bias, codon usage bias of nuclear and organellar genes, computational methods to determine codon usage and the significance as well as applications of codon usage analysis in biological research, with emphasis on plants.

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.

Protein Abundance Prediction Through Machine Learning Methods

Proteins are responsible for most physiological processes, and their abundance provides crucial information for systems biology research. However, absolute protein quantification, as determined by mass spectrometry, still has limitations in capturing the protein pool. Protein abundance is impacted by translation kinetics, which rely on features of codons. In this study, we evaluated the effect of codon usage bias of genes on protein abundance. Notably, we observed differences regarding codon usage patterns between genes coding for highly abundant proteins and genes coding for less abundant proteins. Analysis of synonymous codon usage and evolutionary selection showed a clear split between the two groups. Our machine learning models predicted protein abundances from codon usage metrics with remarkable accuracy, achieving strong correlation with experimental data. Upon integration of the predicted protein abundance in enzyme-constrained genome-scale metabolic models, the simulated phenotypes closely matched experimental data, which demonstrates that our predictive models are valuable tools for systems metabolic engineering approaches.

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.

Regulation of translation by site-specific ribosomal RNA methylation

Ribosomes are complex ribozymes that interpret genetic information by translating messenger RNA (mRNA) into proteins. Natural variation in ribosome composition has been documented in several organisms and can arise from several different sources. A key question is whether specific control over ribosome heterogeneity represents a mechanism by which translation can be regulated. We used RiboMeth-seq to demonstrate that differential 2'-O-methylation of ribosomal RNA (rRNA) represents a considerable source of ribosome heterogeneity in human cells, and that modification levels at distinct sites can change dynamically in response to upstream signaling pathways, such as MYC oncogene expression. Ablation of one prominent methylation resulted in altered translation of select mRNAs and corresponding changes in cellular phenotypes. Thus, differential rRNA 2'-O-methylation can give rise to ribosomes with specialized function. This suggests a broader mechanism where the specific regulation of rRNA modification patterns fine tunes translation.

Mutations in the regulatory regions result in increased streptomycin resistance and keratinase synthesis in Bacillus thuringiensis

Keratinases are a group of proteases of great industrial significance. To take full advantage of Bacillus species as an inherent superior microbial producer of proteases, we performed the ribosome engineering to improve the keratinase synthesis capacity of the wild-type Bacillus thuringiensis by inducing streptomycin resistance. Mutant Bt(Str-O) was identified as a stable keratinase overproducer. Comparative characterization of the two strains revealed that, although the resistance to Streptomycin increased by eight-fold in MIC, the mutant's resistance to other commonly used antibiotics was not affected. Furthermore, the mutant exhibited an enhanced keratinase synthesis (1.5-fold) when cultured in a liquid LB medium. In the whole feather degradation experiment, the mutant could secret twofold keratinase into the medium, reaching 640 U/mL per 10⁷ CFU. By contrast, no significant differences were found in the scanning electron microscopic analysis and spore formation experiment. To understand the genetic factors causing these phenotypic changes, we cloned and analyzed the rpsL gene. No mutation was observed. We subsequently determined the genome sequences of the two strains. Comparing the rpsL gene revealed that the emergence of streptomycin resistance was not necessarily dependent on the mutation(s) in the generally recognized "hotspot." Genome-wide analysis showed that the phenotypic changes of the mutant were the collective consequence of the genetic variations occurring in the regulatory regions and the non-coding RNA genes. This study demonstrated the importance of genetic changes in regulatory regions and the effectiveness of irrational ribosome engineering in creating prokaryotic microbial mutants without sufficient genetic information.

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.

CAMAP: Artificial neural networks unveil the role of codon arrangement in modulating MHC-I peptides presentation

MHC-I associated peptides (MAPs) play a central role in the elimination of virus-infected and neoplastic cells by CD8 T cells. However, accurately predicting the MAP repertoire remains difficult, because only a fraction of the transcriptome generates MAPs. In this study, we investigated whether codon arrangement (usage and placement) regulates MAP biogenesis. We developed an artificial neural network called Codon Arrangement MAP Predictor (CAMAP), predicting MAP presentation solely from mRNA sequences flanking the MAP-coding codons (MCCs), while excluding the MCC per se. CAMAP predictions were significantly more accurate when using original codon sequences than shuffled codon sequences which reflect amino acid usage. Furthermore, predictions were independent of mRNA expression and MAP binding affinity to MHC-I molecules and applied to several cell types and species. Combining MAP ligand scores, transcript expression level and CAMAP scores was particularly useful to increase MAP prediction accuracy. Using an in vitro assay, we showed that varying the synonymous codons in the regions flanking the MCCs (without changing the amino acid sequence) resulted in significant modulation of MAP presentation at the cell surface. Taken together, our results demonstrate the role of codon arrangement in the regulation of MAP presentation and support integration of both translational and post-translational events in predictive algorithms to ameliorate modeling of the immunopeptidome.

MHC-I associated peptides (MAPs) are small fragments of intracellular proteins presented at the surface of cells and used by the immune system to detect and eliminate cancerous or virus-infected cells. While it is theoretically possible to predict which portions of the intracellular proteins will be naturally processed by the cells to ultimately reach the surface, current methodologies have prohibitively high false discovery rates. Here we introduce an artificial neural network called Codon Arrangement MAP Predictor (CAMAP) which integrates information from mRNA-to-protein translation to other factors regulating MAP biogenesis (e.g. MAP ligand score and transcript expression levels) to improve MAP prediction accuracy. While most MAP predictive approaches focus on MAP sequences per se, CAMAP’s novelty is to analyze the MAP-flanking mRNA sequences, thereby providing completely independent information for MAP prediction. We show on several datasets that the integration of CAMAP scores with other known factors involved in MAP presentation (i.e. MAP ligand score and mRNA expression) significantly improves MAP prediction accuracy, and further validate CAMAP learned features using an in-vitro assay. These findings may have major implications for the design of vaccines against cancers and viruses, and in times of pandemics could accelerate the identification of relevant MAPs of viral origins.

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.

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

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

Direct in vivo observation of the effect of codon usage bias on gene expression in Arabidopsis hybrids

Hybrids are the perfect materials to study cis regulatory elements because the two parental alleles are subjected to identical trans environments. There has been a debate on whether synonymous codon usage could affect gene expression. In vitro experiments found that luciferase genes with enhanced codon optimality showed elevated mRNA expression. However, the underlying mechanism is still unclear, and no direct evidence is observed to support this notion. By mapping the RNA-seq data of hybrids of Arabidopsis thaliana and Arabidopsis lyrata, we quantified the allele-specific reads and estimated the relative expression of orthologous genes. We focused on orthologous genes with dN = 0 and dS > 0, which means that they only differ in synonymous codon usage. We found that orthologous genes with higher codon optimality in A. thaliana tend to have higher expression levels of the A. thaliana allele. Codon usage bias could influence gene expression. This phenomenon is not only found in in vitro experiments but also supported by in vivo observations. Therefore, synonymous mutations could have a broad impact from multiple aspects and should not be automatically ignored in genomic studies. KEY MESSAGE: In Arabidopsis hybrids, alleles with higher codon optimality tend to have higher expression levels.

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.

Regulatory roles of RNA modifications in breast cancer

Collectively referred to as the epitranscriptome, RNA modifications play important roles in gene expression control regulating relevant cellular processes. In the last few decades, growing numbers of RNA modifications have been identified not only in abundant ribosomal (rRNA) and transfer RNA (tRNA) but also in messenger RNA (mRNA). In addition, many writers, erasers and readers that dynamically regulate the chemical marks have also been characterized. Correct deposition of RNA modifications is prerequisite for cellular homeostasis, and its alteration results in aberrant transcriptional programs that dictate human disease, including breast cancer, the most frequent female malignancy, and the leading cause of cancer-related death in women. In this review, we emphasize the major RNA modifications that are present in tRNA, rRNA and mRNA. We have categorized breast cancer-associated chemical marks and summarize their contribution to breast tumorigenesis. In addition, we describe less abundant tRNA modifications with related pathways implicated in breast cancer. Finally, we discuss current limitations and perspectives on epitranscriptomics for use in therapeutic strategies against breast and other cancers.

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.

Post-transcriptional and translational control of the morphology and virulence in human fungal pathogens

Host-pathogen interactions at the molecular level are the key to fungal pathogenesis. Fungal pathogens utilize several mechanisms such as adhesion, invasion, phenotype switching and metabolic adaptations, to survive in the host environment and respond. Post-transcriptional and translational regulations have emerged as key regulatory mechanisms ensuring the virulence and survival of fungal pathogens. Through these regulations, fungal pathogens effectively alter their protein pool, respond to various stress, and undergo morphogenesis, leading to efficient and comprehensive changes in fungal physiology. The regulation of virulence through post-transcriptional and translational regulatory mechanisms is mediated through mRNA elements (cis factors) or effector molecules (trans factors). The untranslated regions upstream and downstream of the mRNA, as well as various RNA-binding proteins involved in translation initiation or circularization of the mRNA, play pivotal roles in the regulation of morphology and virulence by influencing protein synthesis, protein isoforms, and mRNA stability. Therefore, post-transcriptional and translational mechanisms regulating the morphology, virulence and drug-resistance processes in fungal pathogens can be the target for new therapeutics. With improved "omics" technologies, these regulatory mechanisms are increasingly coming to the forefront of basic biology and drug discovery. This review aims to discuss various modes of post-transcriptional and translation regulations, and how these mechanisms exert influence in the virulence and morphogenesis of fungal pathogens.

From influenza to COVID-19: Lipid nanoparticle mRNA vaccines at the frontiers of infectious diseases

Vaccination represents the best line of defense against infectious diseases and is crucial in curtailing pandemic spread of emerging pathogens to which a population has limited immunity. In recent years, mRNA vaccines have been proposed as the new frontier in vaccination, owing to their facile and rapid development while providing a safer alternative to traditional vaccine technologies such as live or attenuated viruses. Recent breakthroughs in mRNA vaccination have been through formulation with lipid nanoparticles (LNPs), which provide both protection and enhanced delivery of mRNA vaccines in vivo. In this review, current paradigms and state-of-the-art in mRNA-LNP vaccine development are explored through first highlighting advantages posed by mRNA vaccines, establishing LNPs as a biocompatible delivery system, and finally exploring the use of mRNA-LNP vaccines in vivo against infectious disease towards translation to the clinic. Furthermore, we highlight the progress of mRNA-LNP vaccine candidates against COVID-19 currently in clinical trials, with the current status and approval timelines, before discussing their future outlook and challenges that need to be overcome towards establishing mRNA-LNPs as next-generation vaccines. STATEMENT OF SIGNIFICANCE: With the recent success of mRNA vaccines developed by Moderna and BioNTech/Pfizer against COVID-19, mRNA technology and lipid nanoparticles (LNP) have never received more attention. This manuscript timely reviews the most advanced mRNA-LNP vaccines that have just been approved for emergency use and are in clinical trials, with a focus on the remarkable development of several COVID-19 vaccines, faster than any other vaccine in history. We aim to give a comprehensive introduction of mRNA and LNP technology to the field of biomaterials science and increase accessibility to readers with a new interest in mRNA-LNP vaccines. We also highlight current limitations and future outlook of the mRNA vaccine technology that need further efforts of biomaterials scientists to address.

The plasticity of mRNA translation during cancer progression and therapy resistance

Translational control of mRNAs during gene expression allows cells to promptly and dynamically adapt to a variety of stimuli, including in neoplasia in response to aberrant oncogenic signalling (for example, PI3K-AKT-mTOR, RAS-MAPK and MYC) and microenvironmental stress such as low oxygen and nutrient supply. Such translational rewiring allows rapid, specific changes in the cell proteome that shape specific cancer phenotypes to promote cancer onset, progression and resistance to anticancer therapies. In this Review, we illustrate the plasticity of mRNA translation. We first highlight the diverse mechanisms by which it is regulated, including by translation factors (for example, eukaryotic initiation factor 4F (eIF4F) and eIF2), RNA-binding proteins, tRNAs and ribosomal RNAs that are modulated in response to aberrant intracellular pathways or microenvironmental stress. We then describe how translational control can influence tumour behaviour by impacting on the phenotypic plasticity of cancer cells as well as on components of the tumour microenvironment. Finally, we highlight the role of mRNA translation in the cellular response to anticancer therapies and its promise as a key therapeutic target.

Strategies for controlling the innate immune activity of conventional and self-amplifying mRNA therapeutics: Getting the message across

The recent approval of messenger RNA (mRNA)-based vaccines to combat the SARS-CoV-2 pandemic highlights the potential of both conventional mRNA and self-amplifying mRNA (saRNA) as a flexible immunotherapy platform to treat infectious diseases. Besides the antigen it encodes, mRNA itself has an immune-stimulating activity that can contribute to vaccine efficacy. This self-adjuvant effect, however, will interfere with mRNA translation and may influence the desired therapeutic outcome. To further exploit its potential as a versatile therapeutic platform, it will be crucial to control mRNA's innate immune-stimulating properties. In this regard, we describe the mechanisms behind the innate immune recognition of mRNA and provide an extensive overview of strategies to control its innate immune-stimulating activity. These strategies range from modifications to the mRNA backbone itself, optimization of production and purification processes to the combination with innate immune inhibitors. Furthermore, we discuss the delicate balance of the self-adjuvant effect in mRNA vaccination strategies, which can be both beneficial and detrimental to the therapeutic outcome.

Codon Usage Bias: An Endless Tale

Since the genetic code is degenerate, several codons are translated to the same amino acid. Although these triplets were historically considered to be "synonymous" and therefore expected to be used at rather equal frequencies in all genomes, we now know that this is not the case. Indeed, since several coding sequences were obtained in the late '70s and early '80s in the last century, coming from either the same or different species, it was evident that (a) each genome, taken globally, displayed different codon usage patterns, which means that different genomes display a particular global codon usage table when all genes are considered together, and (b) there is a strong intragenomic diversity: in other words, within a given species the codon usage pattern can (and usually do) differ greatly among genes in the same genome. These different patterns were attributed to two main factors: first, the mutational bias characteristic of each genome, which determines that GC- poor species display a general bias towards A/T codons while the reverse is true for GC- rich species. Second, the differences in codon usage among genes from the same species are due to natural selection acting at the level of translation, in such a way that highly expressed genes tend to use codons that match with the most abundant isoacceptor tRNAs. Thus, these genes are translated at a highest rate, which in turn leads to avoid the limiting factor in translation which is the number of available ribosomes per cell. Although these explanations are still valid, new factors are almost constantly postulated to affect codon usage. In this mini review, we shall try to summarize them.

METTL1/WDR4 mediated m7G tRNA modifications and m7G codon usage promote mRNA translation and lung cancer progression

Mis-regulated epigenetic modifications in RNAs are associated with human cancers. The transfer RNAs (tRNAs) are the most heavily modified RNA species in cells, however, little is known about the functions of tRNA modifications in cancers. In this study, we uncovered that the expression levels of tRNA N⁷-methylguanosine (m⁷G) methyltransferase complex components METTL1 and WDR4 are significantly elevated in human lung cancer samples and negatively associated with patient prognosis. Impaired m⁷G tRNA modification upon METTL1/WDR4 depletion resulted in decreased cell proliferation, colony formation, cell invasion and impaired tumorigenic capacities of lung cancer cells in vitro and in vivo. Moreover, gain-of-function and mutagenesis experiments revealed that METTL1 promoted lung cancer growth and invasion through regulation of m⁷G tRNA modifications. Profiling of tRNA methylation and mRNA translation revealed that highly translated mRNAs have higher frequencies of m⁷G tRNA decoded codons and knockdown of METTL1 resulted in decreased translation of mRNAs with higher frequencies of m⁷G tRNA codons, suggesting that tRNA modifications and codon usage play essential function in mRNA translation regulation. Our data uncovered novel insights on mRNA translation regulation through tRNA modifications and the corresponding mRNA codon compositions in lung cancer, providing new molecular basis underlying lung cancer progression.

Targeted genome editing of plants and plant cells for biomanufacturing

Plants have provided humans with useful products since antiquity, but in the last 30 years they have also been developed as production platforms for small molecules and recombinant proteins. This initially niche area has blossomed with the growth of the global bioeconomy, and now includes chemical building blocks, polymers and renewable energy. All these applications can be described as "plant molecular farming" (PMF). Despite its potential to increase the sustainability of biologics manufacturing, PMF has yet to be embraced broadly by industry. This reflects a combination of regulatory uncertainty, limited information on process cost structures, and the absence of trained staff and suitable manufacturing capacity. However, the limited adaptation of plants and plant cells to the requirements of industry-scale manufacturing is an equally important hurdle. For example, the targeted genetic manipulation of yeast has been common practice since the 1980s, whereas reliable site-directed mutagenesis in most plants has only become available with the advent of CRISPR/Cas9 and similar genome editing technologies since around 2010. Here we summarize the applications of new genetic engineering technologies to improve plants as biomanufacturing platforms. We start by identifying current bottlenecks in manufacturing, then illustrate the progress that has already been made and discuss the potential for improvement at the molecular, cellular and organism levels. We discuss the effects of metabolic optimization, adaptation of the endomembrane system, modified glycosylation profiles, programmable growth and senescence, protease inactivation, and the expression of enzymes that promote biodegradation. We outline strategies to achieve these modifications by targeted gene modification, considering case-by-case examples of individual improvements and the combined modifications needed to generate a new general-purpose "chassis" for PMF.

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.

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.

Natural selection on synonymous mutations in SARS-CoV-2 and the impact on estimating divergence time

To adapt to human host environment, synonymous mutations in SARS-CoV-2 are shaped by tRNA selection, energy cost and RNA structure.

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.

Cloning, high-level gene expression and bioinformatics analysis of SP15 and LeIF from Leishmania major and Iranian Phlebotomus papatasi saliva as single and novel fusion proteins: a potential vaccine candidate against leishmaniasis

BACKGROUND

Early exacerbation of cutaneous leishmaniasis is mainly affected by both the salivary and Leishmania parasite components. Little is known of the vaccine combination made by immunogenic proteins of sandfly saliva (SP15) with Leishmania parasites (LeIF) as a single prophylactic vaccine, namely SaLeish. Also, there are no data available to determine the species-specific sequence of SP15 isolated from the Iranian Phlebotomus papatasi.

METHODS

Integrated bioinformatics and genetic engineering methods were employed to design, optimize and obtain a vector-parasite-based vaccine formulation in a whole-length fusion form of LeIF-SP15 against leishmaniasis. Holistic gene optimization was initially performed to obtain a high yield of pure 'whole-SaLeish' expression using bioinformatics analyses. Genomic and salivary gland RNAs of wild-caught P. papatasi were extracted and their complementary DNA was amplified and cloned into pJET vector.

RESULTS

The new chimeric protein of whole-SaLeish and randomly selected transcripts of native PpIRSP15 (GenBank accession nos. MT025054 and MN938854, MN938855 and MN938856) were successfully expressed, purified and validated by immunoblotting assay. Furthermore, despite the single amino acid polymorphisms of PpIRSP15 found at positions Y23 and E73 within the population of wild Iranian sandflies, antigenicity and conservancy of PpIRSP15 epitopes remained constant to activate T cells.

CONCLUSIONS

The SaLeish vaccine strategy takes advantage of a plethora of vector-parasite immunogenic proteins with potential protective efficacy to stimulate both the innate and specific cellular immune responses against Leishmania parasites.

The Functional Consequences of the Novel Ribosomal Pausing Site in SARS-CoV-2 Spike Glycoprotein RNA

The SARS-CoV-2 Spike glycoprotein (S protein) acquired a unique new 4 amino acid -PRRA- insertion sequence at amino acid residues (aa) 681-684 that forms a new furin cleavage site in S protein as well as several new glycosylation sites. We studied various statistical properties of the -PRRA- insertion at the RNA level (CCUCGGCGGGCA). The nucleotide composition and codon usage of this sequence are different from the rest of the SARS-CoV-2 genome. One of such features is two tandem CGG codons, although the CGG codon is the rarest codon in the SARS-CoV-2 genome. This suggests that the insertion sequence could cause ribosome pausing as the result of these rare codons. Due to population variants, the Nextstrain divergence measure of the CCU codon is extremely large. We cannot exclude that this divergence might affect host immune responses/effectiveness of SARS-CoV-2 vaccines, possibilities awaiting further investigation. Our experimental studies show that the expression level of original RNA sequence "wildtype" spike protein is much lower than for codon-optimized spike protein in all studied cell lines. Interestingly, the original spike sequence produces a higher titer of pseudoviral particles and a higher level of infection. Further mutagenesis experiments suggest that this dual-effect insert, comprised of a combination of overlapping translation pausing and furin sites, has allowed SARS-CoV-2 to infect its new host (human) more readily. This underlines the importance of ribosome pausing to allow efficient regulation of protein expression and also of cotranslational subdomain folding.

Learning the Regulatory Code of Gene Expression

Data-driven machine learning is the method of choice for predicting molecular phenotypes from nucleotide sequence, modeling gene expression events including protein-DNA binding, chromatin states as well as mRNA and protein levels. Deep neural networks automatically learn informative sequence representations and interpreting them enables us to improve our understanding of the regulatory code governing gene expression. Here, we review the latest developments that apply shallow or deep learning to quantify molecular phenotypes and decode the cis-regulatory grammar from prokaryotic and eukaryotic sequencing data. Our approach is to build from the ground up, first focusing on the initiating protein-DNA interactions, then specific coding and non-coding regions, and finally on advances that combine multiple parts of the gene and mRNA regulatory structures, achieving unprecedented performance. We thus provide a quantitative view of gene expression regulation from nucleotide sequence, concluding with an information-centric overview of the central dogma of molecular biology.

Association between a genetic variant in scavenger receptor class B type 1 and its role on codon usage bias with increased risk of developing coronary artery disease

OBJECTIVE

Coronary artery disease (CAD) as an important cause of morbidity and mortality globally. The scavenger receptor class B type 1 (SCARB1) plays an essential role in the reverse cholesterol transport. We have explored the association between a genetic variant, rs5888, in the SCARB1 gene with CAD and serum HDL-C levels.

METHODS

Patients were categorized into two groups' angiogram positive (>50% coronary stenosis) and angiogram negative (<50% coronary stenosis). Genotyping was carried out using polymerase chain reaction-amplification refractory mutation system. The association between the SNP rs5888 and serum HDL-C was analyzed using a logistic regression model.

RESULTS

The results showed that the subjects carrying a T allele was associated with a decreased serum HDL-C levels compared to the C allele in total population (p < 0.001). The risk of angiogram positivity in subjects carrying a T allele was 3.1-fold higher than for the control group (p < 0.001).

CONCLUSION

CVD patients carrying the T allele of rs5888 variant in the SCARB1 gene was associated with decreased serum level of HDL.

CRISPR screens in plants: approaches, guidelines, and future prospects

Clustered regularly interspaced short palindromic repeat (CRISPR)-associated systems have revolutionized genome engineering by facilitating a wide range of targeted DNA perturbations. These systems have resulted in the development of powerful new screens to test gene functions at the genomic scale. While there is tremendous potential to map and interrogate gene regulatory networks at unprecedented speed and scale using CRISPR screens, their implementation in plants remains in its infancy. Here we discuss the general concepts, tools, and workflows for establishing CRISPR screens in plants and analyze the handful of recent reports describing the use of this strategy to generate mutant knockout collections or to diversify DNA sequences. In addition, we provide insight into how to design CRISPR knockout screens in plants given the current challenges and limitations and examine multiple design options. Finally, we discuss the unique multiplexing capabilities of CRISPR screens to investigate redundant gene functions in highly duplicated plant genomes. Combinatorial mutant screens have the potential to routinely generate higher-order mutant collections and facilitate the characterization of gene networks. By integrating this approach with the numerous genomic profiles that have been generated over the past two decades, the implementation of CRISPR screens offers new opportunities to analyze plant genomes at deeper resolution and will lead to great advances in functional and synthetic biology.