The effects of codon bias and optimality on mRNA and protein regulation

Perspectives on the use of the CRISPR system in plants to improve recombinant therapeutic protein production

The plant-based system is a promising platform for producing biotherapeutics due to its scalability, cost-effectiveness, and lower risk of contamination by human pathogens. However, several challenges remain, including optimizing yield, stability, functionality, and the immunogenic properties of recombinant proteins. In this context, this review explores the application of CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) technology to improve the production of recombinant therapeutic proteins in plants. Traditional tools and strategies for plant-based recombinant protein production are discussed, highlighting their limitations and the potential of CRISPR to overcome these boundaries. It delves into the components of the CRISPR-Cas system and its application in optimizing therapeutic protein function and yield. Major strategies include modifying glycosylation patterns to humanize plant-produced proteins, metabolic pathway engineering to increase protein accumulation, and the precise integration of transgenes into specific genomic loci to enhance expression stability and productivity. These advancements demonstrate how CRISPR system can overcome bottlenecks in plant molecular farming and enable the production of high-quality therapeutic proteins. Lastly, future trends and perspectives are examined, emphasizing ongoing innovations and challenges in the field. The review underscores the potential of CRISPR to reshape plant biotechnology and support the growing demand for recombinant therapeutics, offering new avenues for sustainable and efficient protein production systems. KEY MESSAGE: CRISPR technology has the potential to improve plant-based therapeutic protein production by optimizing yield, stability, and humanization, overcoming bottlenecks, and enabling sustainable, efficient systems for recombinant biotherapeutics.

Lost in translation: conserved amino acid usage despite extreme codon bias in foraminifera

Analyses of codon usage in eukaryotes suggest that amino acid usage responds to GC pressure so AT-biased substitutions drive higher usage of amino acids with AT-ending codons. Here, we combine single-cell transcriptomics and phylogenomics to explore codon usage patterns in foraminifera, a diverse and ancient clade of predominantly uncultivable microeukaryotes. We curate data from 1,044 gene families in 49 individuals representing 28 genera, generating perhaps the largest existing dataset of data from a predominantly uncultivable clade of protists, to analyze compositional bias and codon usage. We find extreme variation in composition, with a median GC content at fourfold degenerate silent sites below 3% in some species and above 75% in others. The most AT-biased species are distributed among diverse non-monophyletic lineages. Surprisingly, despite the extreme variation in compositional bias, amino acid usage is highly conserved across all foraminifera. By analyzing nucleotide, codon, and amino acid composition within this diverse clade of amoeboid eukaryotes, we expand our knowledge of patterns of genome evolution across the eukaryotic tree of life.IMPORTANCEPatterns of molecular evolution in protein-coding genes reflect trade-offs between substitution biases and selection on both codon and amino acid usage. Most analyses of these factors in microbial eukaryotes focus on model species such as Acanthamoeba, Plasmodium, and yeast, where substitution bias is a primary contributor to patterns of amino acid usage. Foraminifera, an ancient clade of single-celled eukaryotes, present a conundrum, as we find highly conserved amino acid usage underlain by divergent nucleotide composition, including extreme AT-bias at silent sites among multiple non-sister lineages. We speculate that these paradoxical patterns are enabled by the dynamic genome structure of foraminifera, whose life cycles can include genome endoreplication and chromatin extrusion.

The Complete Mitochondrial Genome of Thymus mongolicus and Its Phylogenetic Relationship with Lamiaceae Species

Thymus mongolicus (Lamiaceae) is a plant commonly found throughout China, in which it is widely used in chemical products for daily use, traditional medicinal preparations, ecological management, and cooking. In this study, we have assembled and annotated for the first time the entire mitochondrial genome (mitogenome) of T. mongolicus. The mitochondrial genome of T. mongolicus is composed in a monocyclic structure, with an overall size of 450,543 base pairs (bp) and a GC composition of 45.63%. It contains 32 unique protein-encoding genes. The repetitive sequences of the T. mongolicus mitogenome include 165 forward repetitive sequences and 200 palindromic repetitive sequences, in addition to 88 simple sequence repeats, of which tetramers accounted for the highest proportion (40.91%). An analysis of the mitogenome codons revealed that synonymous codons generally end with A/U. With the exception of nad4L, which uses ACG/ATG as an initiation codon, all other genes begin with the ATG start codon. Codon analysis of the mitogenome also showed that leucine (909) are the most abundant amino acid, while tryptophan (134) are the least prevalent. In total, 374 RNA editing sites were detected. Moreover, 180 homologous segments totaling 105,901 bp were found when the mitochondrial and chloroplast genomes of T. mongolicus were compared. Phylogenetic analysis further indicated that T. mongolicus is most closely related to Prunella vulgaris in the Lamiaceae family. Our findings offer important genetic insights for further research on this Lamiaceae species. To the best of our knowledge, this study is the first description of the entire mitogenome of T. mongolicus.

Role of silent mutations in KRAS -mutant tumors

ABSTRACT

Silent mutations within the RAS  gene have garnered increasing attention for their potential roles in tumorigenesis and therapeutic strategies. Kirsten-RAS ( KRAS ) mutations, predominantly oncogenic, are pivotal drivers in various cancers. While extensive research has elucidated the molecular mechanisms and biological consequences of active KRAS  mutations, the functional significance of silent mutations remains relatively understudied. This review synthesizes current knowledge on KRAS  silent mutations, highlighting their impact on cancer development. Silent mutations, which do not alter protein sequences but can affect RNA stability and translational efficiency, pose intriguing questions regarding their contribution to tumor biology. Understanding these mutations is crucial for comprehensively unraveling KRAS -driven oncogenesis and exploring novel therapeutic avenues. Moreover, investigations into the clinical implications of silent mutations in KRAS -mutant tumors suggest potential diagnostic and therapeutic strategies. Despite being in early stages, research on KRAS  silent mutations holds promise for uncovering novel insights that could inform personalized cancer treatments. In conclusion, this review underscores the evolving landscape of KRAS  silent mutations, advocating for further exploration to bridge fundamental biology with clinical applications in oncology.

Predicting gene sequences with AI to study codon usage patterns

Selective pressure acts on the codon use, optimizing multiple, overlapping signals that are only partially understood. We trained AI models to predict codons given their amino acid sequence in the eukaryotes Saccharomyces cerevisiae and Schizosaccharomyces pombe and the bacteria Escherichia coli and Bacillus subtilis to study the extent to which we can learn patterns in naturally occurring codons to improve predictions. We trained our models on a subset of the proteins and evaluated their predictions on large, separate sets of proteins of varying lengths and expression levels. Our models significantly outperformed naïve frequency-based approaches, demonstrating that there are learnable dependencies in evolutionary-selected codon usage. The prediction accuracy advantage of our models is greater for highly expressed genes and is greater in bacteria than eukaryotes, supporting the hypothesis that there is a monotonic relationship between selective pressure for complex codon patterns and effective population size. In S. cerevisiae and bacteria, our models were more accurate for longer proteins, suggesting that the learned patterns may be related to cotranslational folding. Gene functionality and conservation were also important determinants that affect the performance of our models. Finally, we showed that using information encoded in homologous proteins has only a minor effect on prediction accuracy, perhaps due to complex codon-usage codes in genes undergoing rapid evolution. Our study employing contemporary AI methods offers a unique perspective and a deep-learning-based prediction tool for evolutionary-selected codons. We hope that these can be useful to optimize codon usage in endogenous and heterologous proteins.

Assembly and analysis of the complete mitochondrial genome of Carya illinoinensis to provide insights into the conserved sequences of tRNA genes

Carya illinoinensis is an economically important nut tree, and its chloroplast (cp.) genome has been reported; however, its mitochondrial (mt) genome remains unknown. In the present study, we assembled the first mt genome of C. illinoinensis. The circular mt genome of C. illinoinensis is 495,205 bp long, with 37 protein-coding genes(PCGs), 24 tRNA genes, and 3 rRNA genes. All the tRNAs could be folded into typical cloverleaf secondary structures, with lengths of 58-88 bp. A conserved U-U-C-x-A-x2 consensus nucleotide sequence was discovered in the Ψ-loops of tRNA sequences. In addition, 447 dispersed repeats were detected, as well as found 482 RNA editing sites and 9,960 codons in the mt genome. Furthermore, a total of 27 DNA sequences with a length of 43,277 bp were transferred from the cp. to the mt genome, and eight integrated cp-derived genes (trnL-CAA, trnV-GAC, trnD-GUC, trnW-CCA, trnN-GUU, trnH-GUG, trnM-CAU, and rps7) were identified. We also obtained 1,086 hits, including 364.023 kp of nuclear genome sequences, that were transferred to the mt genome. To determine the evolutionary position of C. illinoinensis, we conducted a phylogenetic analysis of the mitogenomes of C. illinoinensis and 14 other taxa. The results strongly suggested that C. illinoinensis and Fagus sylvatica formed a single clade with 100% bootstrap support. This study sequenced comprehensive data on the C. illinoinensis mitochondrial genome and provided insights into the conserved sequences of tRNA genes, which could facilitate evolutionary research in other Carya trees in the future.

Unravelling Prokaryotic Codon Usage: Insights from Phylogeny, Influencing Factors and Pathogenicity

Analyzing prokaryotic codon usage trends has become a crucial topic of study with significant ramifications for comprehending microbial genetics, classification, evolution, and the control of gene expression. This review study explores the numerous facets of prokaryotic codon usage patterns, looking at different parameters like habitat and lifestyle across broad groups of prokaryotes by emphasizing the role of codon reprogramming in adaptive strategies and its integration into systems biology. We also explored the numerous variables driving codon usage bias, including natural selection, mutation, horizontal gene transfer, codon-anticodon interaction, and genomic composition in prokaryotes through a thorough study of current literature. Furthermore, a special session on codon usage on pathogenic prokaryotes and the role of codon usage in the phylogeny of prokaryotes has been discussed. We also looked at the various software and indices that have been recently applied to prokaryotic genomes. The promising directions that lay ahead to map the future of codon usage research on prokaryotes have been emphasized. Codon usage variations across prokaryotic communities could be better understood by combining environmental, metagenomic, and system biology approaches.

Analysis of codon usage bias of exonuclease genes in invertebrate iridescent viruses

Invertebrate iridescent viruses (IIVs) are double-stranded DNA viruses that belong to the Iridoviridae family. IIVs result diseases that vary in severity from subclinical to lethal in invertebrate hosts. Codon usage bias (CUB) analysis is a versatile method for comprehending the genetic and evolutionary aspects of species. In this study, we analyzed the CUB in 10 invertebrate iridescent viruses exonuclease genes by calculating and comparing the nucleotide contents, effective number of codons (ENC), codon adaptation index (CAI), relative synonymous codon usage (RSCU), and others. The results revealed that IIVs exonuclease genes are rich in A/T. The ENC analysis displayed a low codon usage bias in IIVs exonuclease genes. ENC-plot, neutrality plot, and parity rule 2 plot demonstrated that besides mutational pressure, other factors like natural selection, dinucleotide content, and aromaticity also contributed to CUB. The findings could enhance our understanding of the evolution of IIVs exonuclease genes.

Non-viral delivery of RNA for therapeutic T cell engineering

Adoptive T cell transfer has shown great success in treating blood cancers, resulting in a growing number of FDA-approved therapies using chimeric antigen receptor (CAR)-engineered T cells. However, the effectiveness of this treatment for solid tumors is still not satisfactory, emphasizing the need for improved T cell engineering strategies and combination approaches. Currently, CAR T cells are mainly manufactured using gammaretroviral and lentiviral vectors due to their high transduction efficiency. However, there are concerns about their safety, the high cost of producing them in compliance with current Good Manufacturing Practices (cGMP), regulatory obstacles, and limited cargo capacity, which limit the broader use of engineered T cell therapies. To overcome these limitations, researchers have explored non-viral approaches, such as membrane permeabilization and carrier-mediated methods, as more versatile and sustainable alternatives for next-generation T cell engineering. Non-viral delivery methods can be designed to transport a wide range of molecules, including RNA, which allows for more controlled and safe modulation of T cell phenotype and function. In this review, we provide an overview of non-viral RNA delivery in adoptive T cell therapy. We first define the different types of RNA therapeutics, highlighting recent advancements in manufacturing for their therapeutic use. We then discuss the challenges associated with achieving effective RNA delivery in T cells. Next, we provide an overview of current and emerging technologies for delivering RNA into T cells. Finally, we discuss ongoing preclinical and clinical studies involving RNA-modified T cells.

Advances in lipid nanoparticle mRNA therapeutics beyond COVID-19 vaccines

The remarkable success of two lipid nanoparticle-mRNA vaccines against coronavirus disease (COVID-19) has placed the therapeutic and prophylactic potential of messenger RNA (mRNA) in the spotlight. It has also drawn attention to the indispensable role of lipid nanoparticles in enabling the effects of this nucleic acid. To date, lipid nanoparticles are the most clinically advanced non-viral platforms for mRNA delivery. This is thanks to their favorable safety profile and efficiency in protecting the nucleic acid from degradation and allowing its cellular uptake and cytoplasmic release upon endosomal escape. Moreover, the development of lipid nanoparticle-mRNA therapeutics was already a very active area of research even before the COVID-19 pandemic, which has likely only begun to bear its fruits. In this Review, we first discuss key aspects of the development of lipid nanoparticles as mRNA carriers. We then highlight promising preclinical and clinical studies involving lipid nanoparticle-mRNA formulations against infectious diseases and cancer, and to enable protein replacement or supplementation and genome editing. Finally, we elaborate on the challenges in advancing lipid nanoparticle-mRNA technology to widespread therapeutic use.

Pleiotropic effects of different exonic nucleotide changes at the same position contribute to hemophilia B phenotypic variation

BACKGROUND

The disease-causing effects of genetic variations often depend on their location within a gene. Exonic changes generally lead to alterations in protein production, secretion, activity, or clearance. However, owing to the overlap between proteins and splicing codes, missense variants can also affect messenger RNA splicing, thus adding a layer of complexity and influencing disease phenotypes.

OBJECTIVES

To extensively characterize a panel of 13 exonic variants in the F9 gene occurring at 6 different factor IX positions and associated with varying severities of hemophilia B (HB).

METHODS

Computational predictions, splicing analysis, and recombinant factor IX assays were exploited to characterize F9 variants.

RESULTS

We demonstrated that 5 (38%) of 13 selected F9 exonic variants have pleiotropic effects. Although bioinformatic approaches accurately classified effects, extensive experimental assays were required to elucidate and deepen the molecular mechanisms underlying the pleiotropic effects. Importantly, their characterization was instrumental in developing tailored RNA therapeutics based on engineered U7 small nuclear RNA to mask cryptic splice sites and compensatory U1 small nuclear RNA to enhance exon definition.

CONCLUSION

Overall, albeit a multitool bioinformatic approach suggested the molecular effects of multiple HB variants, the deep investigation of molecular mechanisms revealed insights into the HB phenotype-genotype relationship, enabling accurate classification of HB variants. Importantly, knowledge of molecular mechanisms allowed the development of tailored RNA therapeutics, which can also be translated to other genetic diseases.

Non-Coding RNAs: Regulators of Stress, Ageing, and Developmental Decisions in Yeast?

Cells must change their properties in order to adapt to a constantly changing environment. Most of the cellular sensing and regulatory mechanisms described so far are based on proteins that serve as sensors, signal transducers, and effectors of signalling pathways, resulting in altered cell physiology. In recent years, however, remarkable examples of the critical role of non-coding RNAs in some of these regulatory pathways have been described in various organisms. In this review, we focus on all classes of non-coding RNAs that play regulatory roles during stress response, starvation, and ageing in different yeast species as well as in structured yeast populations. Such regulation can occur, for example, by modulating the amount and functional state of tRNAs, rRNAs, or snRNAs that are directly involved in the processes of translation and splicing. In addition, long non-coding RNAs and microRNA-like molecules are bona fide regulators of the expression of their target genes. Non-coding RNAs thus represent an additional level of cellular regulation that is gradually being uncovered.

Schlafen14 Impairs HIV-1 Expression in a Codon Usage-Dependent Manner

Schlafen (SLFN) is a family of proteins upregulated by type I interferons with a regulatory role in translation. Intriguingly, SLFN14 associates with the ribosome and can degrade rRNA, tRNA, and mRNA in vitro, but a role in translation is still unknown. Ribosomes are important regulatory hubs during translation elongation of mRNAs rich in rare codons. Therefore, we evaluated the potential role of SLFN14 in the expression of mRNAs enriched in rare codons, using HIV-1 genes as a model. We found that, in a variety of cell types, including primary immune cells, SLFN14 regulates the expression of HIV-1 and non-viral genes based on their codon adaptation index, a measurement of the synonymous codon usage bias; consequently, SLFN14 inhibits the replication of HIV-1. The potent inhibitory effect of SLFN14 on the expression of the rare codon-rich transcript HIV-1 Gag was minimized by codon optimization. Mechanistically, we found that the endoribonuclease activity of SLFN14 is required, and that ribosomal RNA degradation is involved. Therefore, we propose that SLFN14 impairs the expression of HIV-1 transcripts rich in rare codons, in a catalytic-dependent manner.

Molecular Mechanisms and the Significance of Synonymous Mutations

Synonymous mutations result from the degeneracy of the genetic code. Most amino acids are encoded by two or more codons, and mutations that change a codon to another synonymous codon do not change the amino acid in the gene product. Historically, such mutations have been considered silent because they were assumed to have no to very little impact. However, research in the last few decades has produced several examples where synonymous mutations play important roles. These include optimizing expression by enhancing translation initiation and accelerating or decelerating translation elongation via codon usage and mRNA secondary structures, stabilizing mRNA molecules and preventing their breakdown before translation, and faulty protein folding or increased degradation due to enhanced ubiquitination and suboptimal secretion of proteins into the appropriate cell compartments. Some consequences of synonymous mutations, such as mRNA stability, can lead to different outcomes in prokaryotes and eukaryotes. Despite these examples, the significance of synonymous mutations in evolution and in causing disease in comparison to nonsynonymous mutations that do change amino acid residues in proteins remains controversial. Whether the molecular mechanisms described by which synonymous mutations affect organisms can be generalized remains poorly understood and warrants future research in this area.

Bioinformatic Analysis Reveals the Role of Translation Elongation Efficiency Optimisation in the Evolution of Ralstonia Genus

Translation efficiency modulates gene expression in prokaryotes. The comparative analysis of translation elongation efficiency characteristics of Ralstonia genus bacteria genomes revealed that these characteristics diverge in accordance with the phylogeny of Ralstonia. The first branch of this genus is a group of bacteria commonly found in moist environments such as soil and water that includes the species R. mannitolilytica, R. insidiosa, and R. pickettii, which are also described as nosocomial infection pathogens. In contrast, the second branch is plant pathogenic bacteria consisting of R. solanacearum, R. pseudosolanacearum, and R. syzygii. We found that the soil Ralstonia have a significantly lower number and energy of potential secondary structures in mRNA and an increased role of codon usage bias in the optimization of highly expressed genes' translation elongation efficiency, not only compared to phytopathogenic Ralstonia but also to Cupriavidus necator, which is closely related to the Ralstonia genus. The observed alterations in translation elongation efficiency of orthologous genes are also reflected in the difference of potentially highly expressed gene' sets' content among Ralstonia branches with different lifestyles. Analysis of translation elongation efficiency characteristics can be considered a promising approach for studying complex mechanisms that determine the evolution and adaptation of bacteria in various environments.

Polysome propensity and tunable thresholds in coding sequence length enable differential mRNA stability

The half-life of mRNAs, as well as their translation, increases in proportion to the optimal codons, indicating a tight coupling of codon-dependent differential translation and degradation. Little is known about the regulation of this coupling. We found that the mRNA stability gain in yeast depends on the mRNA coding sequence length. Below a critical length, codon optimality fails to affect the stability of mRNAs although they can be efficiently translated into short peptides and proteins. Above this threshold length, codon optimality-dependent differential mRNA stability emerges in a switch-like fashion, which coincides with a similar increase in the polysome propensity of the mRNAs. This threshold length can be tuned by the untranslated regions (UTR). Some of these UTRs can destabilize mRNAs without reducing translation, which plays a role in controlling the amplitude of the oscillatory expression of cell cycle genes. Our findings help understand the translation of short peptides from noncoding RNAs and the translation by localized monosomes in neurons.

Assembly and analysis of the mitochondrial genome of Prunella vulgaris

Prunella vulgaris (Lamiaceae) is widely distributed in Eurasia. Former studies have demonstrated that P. vulgaris has a wide range of pharmacological effects. Nevertheless, no complete P. vulgaris mitochondrial genome has been reported, which limits further understanding of the biology of P. vulgaris. Here, we assembled the first complete mitochondrial genome of P. vulgaris using a hybrid assembly strategy based on sequencing data from both Nanopore and Illumina platforms. Then, the mitochondrial genome of P. vulgaris was analyzed comprehensively in terms of gene content, codon preference, intercellular gene transfer, phylogeny, and RNA editing. The mitochondrial genome of P. vulgaris has two circular structures. It has a total length of 297, 777 bp, a GC content of 43.92%, and 29 unique protein-coding genes (PCGs). There are 76 simple sequence repeats (SSRs) in the mitochondrial genome, of which tetrameric accounts for a large percentage (43.4%). A comparative analysis between the mitochondrial and chloroplast genomes revealed that 36 homologous fragments exist in them, with a total length of 28, 895 bp. The phylogenetic analysis showed that P. vulgaris belongs to the Lamiales family Lamiaceae and P. vulgaris is closely related to Salvia miltiorrhiza. In addition, the mitochondrial genome sequences of seven species of Lamiaceae are unconservative in their alignments and undergo frequent genome reorganization. This work reports for the first time the complete mitochondrial genome of P. vulgaris, which provides useful genetic information for further Prunella studies.

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

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

Analysis of synonymous codon usage patterns in mitochondrial genomes of nine Amanita species

Introduction

Codon basis is a common and complex natural phenomenon observed in many kinds of organisms.

Methods

In the present study, we analyzed the base bias of 12 mitochondrial core protein-coding genes (PCGs) shared by nine Amanita species.

Results

The results showed that the codons of all Amanita species tended to end in A/T, demonstrating the preference of mitochondrial codons of Amanita species for a preference for this codon. In addition, we detected the correlation between codon base composition and the codon adaptation index (CAI), codon bias index (CBI), and frequency of optimal codons (FOP) indices, indicating the influence of base composition on codon bias. The average effective number of codons (ENC) of mitochondrial core PCGs of Amanita is 30.81, which is <35, demonstrating the strong codon preference of mitochondrial core PCGs of Amanita. The neutrality plot analysis and PR2-Bias plot analysis further demonstrated that natural selection plays an important role in Amanita codon bias. In addition, we obtained 5–10 optimal codons (ΔRSCU > 0.08 and RSCU > 1) in nine Amanita species, and GCA and AUU were the most widely used optimal codons. Based on the combined mitochondrial sequence and RSCU value, we deduced the genetic relationship between different Amanita species and found large variations between them.

Discussion

This study promoted the understanding of synonymous codon usage characteristics and evolution of this important fungal group.

Recoding of Nonsense Mutation as a Pharmacological Strategy

Approximately 11% of genetic human diseases are caused by nonsense mutations that introduce a premature termination codon (PTC) into the coding sequence. The PTC results in the production of a potentially harmful shortened polypeptide and activation of a nonsense-mediated decay (NMD) pathway. The NMD pathway reduces the burden of unproductive protein synthesis by lowering the level of PTC mRNA. There is an endogenous rescue mechanism that produces a full-length protein from a PTC mRNA. Nonsense suppression therapies aim to increase readthrough, suppress NMD, or are a combination of both strategies. Therefore, treatment with translational readthrough-inducing drugs (TRIDs) and NMD inhibitors may increase the effectiveness of PTC suppression. Here we discuss the mechanism of PTC readthrough and the development of novel approaches to PTC suppression. We also discuss the toxicity and bioavailability of therapeutics used to stimulate PTC readthrough.

Insights into Synonymous Codon Usage Bias in Hepatitis C Virus and Its Adaptation to Hosts

Hepatitis C virus (HCV) is enveloped RNA virus, encoding for a polyprotein that is processed by cellular proteases. The virus is responsible for liver cirrhosis, allograft rejection, and human hepatocellular carcinoma. Based on studies including compositional analysis, odds ratio analysis, parity analysis, skew analysis, relative synonymous codon usage, codon bias, and protein properties, it was evident that codon usage bias in HCV is dependent upon the nucleotide composition. Codon context analysis revealed CTC-CTG as a preferred codon pair. While CGA and CGT codons were rare, none of the codons were rare in HCV-like viruses envisaged in the present study. Many of the preferred codon pairs were valine amino acid-initiated, which possibly infers viral infectivity; hence the role of selection forces appears to act on the HCV genome, which was further validated by neutrality analysis where selection accounted for 87.28%, while mutation accounted for 12.72% force shaping codon usage. Furthermore, codon usage was correlated with the length of the genome. HCV viruses prefer valine-initiated codon pairs, while HCV-like viruses prefer alanine-initiated codon pairs. The HCV host range is very narrow and is confined to only humans and chimpanzees. Based on indices including codon usage correlation analysis, similarity index, and relative codon deoptimization index, it is evident in the study that the chimpanzee is the primary host of the virus. The present study helped elucidate the preferred host for HCV. The information presented in the study paved the way for generating an attenuated vaccine candidate through viral recoding, with finely tuned nucleotide composition and a perfect balance of preferred and rare codons.

mRNA in the Context of Protein Replacement Therapy

Protein replacement therapy is an umbrella term used for medical treatments that aim to substitute or replenish specific protein deficiencies that result either from the protein being absent or non-functional due to mutations in affected patients. Traditionally, such an approach requires a well characterized but arduous and expensive protein production procedure that employs in vitro expression and translation of the pharmaceutical protein in host cells, followed by extensive purification steps. In the wake of the SARS-CoV-2 pandemic, mRNA-based pharmaceuticals were recruited to achieve rapid in vivo production of antigens, proving that the in vivo translation of exogenously administered mRNA is nowadays a viable therapeutic option. In addition, the urgency of the situation and worldwide demand for mRNA-based medicine has led to an evolution in relevant technologies, such as in vitro transcription and nanolipid carriers. In this review, we present preclinical and clinical applications of mRNA as a tool for protein replacement therapy, alongside with information pertaining to the manufacture of modified mRNA through in vitro transcription, carriers employed for its intracellular delivery and critical quality attributes pertaining to the finished product.

Comprehensive analysis of codon bias in 13 Ganoderma mitochondrial genomes

Introduction

Codon usage bias is a prevalent phenomenon observed across various species and genes. However, the specific attributes of codon usage in the mitochondrial genome of Ganoderma species remain unknown.

Methods

In this study, we investigated the codon bias of 12 mitochondrial core protein-coding genes (PCGs) in 9 Ganoderma species, including 13 Ganoderma strains.

Results

The codons of all Ganoderma strains showed a preference for ending in A/T. Additionally, correlations between codon base composition and the codon adaptation index (CAI), codon bias index (CBI) and frequency of optimal codons (FOP) were identified, demonstrating the impact of base composition on codon bias. Various base bias indicators were found to vary between or within Ganoderma strains, including GC3s, the CAI, the CBI, and the FOP. The results also revealed that the mitochondrial core PCGs of Ganoderma have an average effective number of codons (ENC) lower than 35, indicating strong bias toward certain codons. Evidence from neutrality plot and PR2-bias plot analysis indicates that natural selection is a major factor affecting codon bias in Ganoderma. Additionally, 11 to 22 optimal codons (ΔRSCU>0.08 and RSCU>1) were identified in 13 Ganoderma strains, with GCA, AUC, and UUC being the most widely used optimal codons in Ganoderma. By analyzing the combined mitochondrial sequences and relative synonymous codon usage (RSCU) values, the genetic relationships between or within Ganoderma strains were determined, indicating variations between them. Nevertheless, RSCU-based analysis illustrated the intra- and interspecies relationships of certain Ganoderma species.

Discussion

This study deepens our insight into the synonymous codon usage characteristics, genetics, and evolution of this important fungal group.

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

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

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.

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.

Harnessing the information theory and chaos game representation for pattern searching among essential and non-essential genes in Bacteria

Proteins encoded by genes are engaged in most of the processes within a cell. Typing a minimal set of genes required for survival is still a challenging task. Essential genes seem to be more conservative and are usually responsible for basic functions, for instance, genetic information flow or energy production. Despite persistent advances in experimental methods, computer predictions may constitute an important part of this investigation. Firstly, they may embrace a huge amount of data and provide some characteristic patterns. Furthermore, they enable scientists to build models for predicting essential genes which are not yet verified experimentally. Some papers indicate interesting dependencies within essential genes sequences using different computer models. In this paper, an author took a three-step analysis for a deeper understanding of the fundamentals of essential and non-essential genes. Beginning from a simple nucleotide composition and finishing at long-range correlations, presents some characteristic patterns that are expected to be developed in future studies.

Quantitative elucidation of associations between nucleotide identity and physicochemical properties of amino acids and the functional insight

Studies on codon property would deepen our understanding of the origin of primitive life and enlighten biotechnical application. Here, we proposed a quantitative measurement of codon-amino acid association and found that seven out of 13 physicochemical properties have stronger associations with the nucleotide identity at the second codon position, indicating that protein structure and function may associate more closely with it than the other two sites. When extending the effect of codon-amino acid association to protein level, it was found that the correlation between the second codon position (measured by the relative frequencies of nucleobase T and A at this codon site) and hydrophobicity (by the form of GRAVY value) became stronger with 96% genomes having R > 0.90 and p < 1e-60. Furthermore, we revealed that informational genes encoding proteins have lower GRAVY values than operational proteins (p < 3e-37) in both prokaryotic and eukaryotic genomes. The above results reveal a complete link from codon identity (A₂ versus T₂) to amino acid property (hydrophilic versus hydrophobic) and then to protein functions (informational versus operational). Hence, our work may help to understand how the nucleotide sequence determines protein function.

Entropy and Fractal Dimension Study of the TDP-43 Protein Low Complexity Domain Sequence in ALS Disease Severity and SARS-CoV-2 Gene Sequences in Virulence Variability

The low complexity domain (LCD) sequence has been defined in terms of entropy using a 12 amino acid sliding window along a protein sequence in the study of disease-related genes. The amyotrophic lateral sclerosis (ALS)-related TDP-43 protein sequence with intra-LCD structural information based on cryo-EM data was published recently. An application of entropy and Higuchi fractal dimension calculations was described using the Znf521 and HAR1 sequences. A computational analysis of the intra-LCD sequence entropy and Higuchi fractal dimension values at the amino acid level and at the ATCG nucleotide level were conducted without the sliding window requirement. The computational results were consistent in predicting the intermediate entropy/fractal dimension value produced when two subsequences at two different entropy/fractal dimension values were combined. The computational method without the application of a sliding-window was extended to an analysis of the recently reported virulent genes—Orf6, Nsp6, and Orf7a—in SARS-CoV-2. The relationship between the virulence functionality and entropy values was found to have correlation coefficients between 0.84 and 0.99, using a 5% uncertainty on the cell viability data. The analysis found that the most virulent Orf6 gene sequence had the lowest nucleotide entropy and the highest protein fractal dimension, in line with extreme value theory. The Orf6 codon usage bias in relation to vaccine design was discussed.

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.