Codon Bias as a Means to Fine-Tune Gene Expression

Investigations on genomic, topological and structural properties of diguanylate cyclases involved in Vibrio cholerae biofilm signalling using in silico techniques: Promising drug targets in combating cholera

During various stages of its life cycle, Vibrio cholerae initiate biofilm signalling cascade. Intercellular high level of the signalling nucleotide 3'-5' cyclic dimeric guanosine monophosphate (c-di-GMP), synthesized by diguanylate cyclases (DGCs) from its precursor molecule GTP, is crucial for biofilm formation. Present study endeavours to in silico approaches in evaluating genomic, physicochemical, topological and functional properties of six c-di-GMP regulatory DGCs (CdgA, CdgH, CdgK, CdgL, CdgM, VpvC) of V. cholerae. Genomic investigations unveiled that codon preferences were inclined towards AU ending over GC ending codons and overall GC content ranged from 44.6 to 49.5 with codon adaptation index ranging from 0.707 to 0.783. Topological analyses deciphered the presence of transmembrane domains in all proteins. All the DGCs were acidic, hydrophilic and thermostable. Only CdgA, CdgH and VpvC were predicted to be stable during in vitro conditions. Non-polar amino acids with leucine being the most abundant amino acid among these DGCs with α-helix as the predominant secondary structure, responsible for forming the transmembrane regions by secondary structure analysis. Tertiary structures of the proteins were obtained by computation using AlphaFold and trRosetta. Predicted structures by both the servers were compared in various aspects using PROCHECK, ERRAT and Modfold8 servers. Selected 3D structures were refined using GalaxyRefine. InterPro Scan revealed presence of a conserved GGDEF domain in all DGCs and predicted the active site residues in the GGDEF domain. Molecular docking studies using CB-DOCK 2 tool revealed that among the DGCs, VpvC exhibited highest affinity for GTP (-5.6 kcal/mol), which was closely followed by CdgL (-5.5 kcal/mol). MD simulations depicted all DGC-GTP complexes to be stable due to its considerably low eigenvalues. Such studies are considered to provide maiden insights into the genomic and structural properties of V. cholerae DGCs, actively involved in biofilm signalling systems, and it is projected to be beneficial in the discovery of novel DGC inhibitors that can target and downregulate the c-di-GMP regulatory system to develop anti-biofilm strategies against the cholera pathogen.

Efficient Expression of an Engineered Heparan Sulfate 2-O-Sulfotransferase with Improved Catalytic Properties

Heparin, as a type of highly sulfated polysaccharide, is crucial for various physiological and pathophysiological functions. Heparan sulfate 2-O-sulfotransferase (2OST) is responsible for the second sequential sulfation modification in heparin biosynthesis. However, challenges such as low expression and poor enzyme activity performance limit its application. To this end, a combination of strategies was employed to improve expression level and catalytic performance. First, SUMO fusion tag was used to enable the active expression of Gallus gallus-derived 2OST (Ga2OST), followed by enhancing its expression level through N-terminal synonymous codon optimization. Under the principle of considering both catalytic activity and stability, the combinatorial mutant SUMO-Ga2OST A98K/Y145F was successfully constructed, resulting in a 2.32-fold increase in catalytic activity and a 7.80-fold extension of its half-life. Eventually, the enzyme activity was improved to 5720 U/mL with a 14.79-fold increase in a 5 L fermenter, which, to the best of our knowledge, is the highest reported to date. The engineered mutant SUMO-Ga2OST A98K/Y145F with markedly enhanced active expression and catalytic performance could provide a solid foundation for heparin biomanufacturing.

The design and engineering of synthetic genomes

Synthetic genomics seeks to design and construct entire genomes to mechanistically dissect fundamental questions of genome function and to engineer organisms for diverse applications, including bioproduction of high-value chemicals and biologics, advanced cell therapies, and stress-tolerant crops. Recent progress has been fuelled by advancements in DNA synthesis, assembly, delivery and editing. Computational innovations, such as the use of artificial intelligence to provide prediction of function, also provide increasing capabilities to guide synthetic genome design and construction. However, translating synthetic genome-scale projects from idea to implementation remains highly complex. Here, we aim to streamline this implementation process by comprehensively reviewing the strategies for design, construction, delivery, debugging and tailoring of synthetic genomes as well as their potential applications.

Unlocking the power of antimicrobial peptides: advances in production, optimization, and therapeutics

Antimicrobial peptides (AMPs) are critical effectors of innate immunity, presenting a compelling alternative to conventional antibiotics amidst escalating antimicrobial resistance. Their broad-spectrum efficacy and inherent low resistance development are countered by production challenges, including limited yields and proteolytic degradation, which restrict their clinical translation. While chemical synthesis offers precise structural control, it is often prohibitively expensive and complex for large-scale production. Heterologous expression systems provide a scalable, cost-effective platform, but necessitate optimization. This review comprehensively examines established and emerging AMP production strategies, encompassing fusion protein technologies, molecular engineering approaches, rational peptide design, and post-translational modifications, with an emphasis on maximizing yield, bioactivity, stability, and safety. Furthermore, we underscore the transformative role of artificial intelligence, particularly machine learning algorithms, in accelerating AMP discovery and optimization, thereby propelling their expanded therapeutic application and contributing to the global fight against drug-resistant infections.

Dynamic Regulation of 5-Formylcytidine on tRNA

Post-transcriptional modifications on RNA play an important role in biological processes, but we lack an understanding of the molecular mechanisms underlying the function of many modifications. Here we characterize the distribution and dynamic regulation of 5-formylcytidine (f5C), a modification primarily found on tRNAs, across different cell lines, mouse tissues, and in response to environmental stress. We identify perturbation in bulk f5C levels using nucleoside LC-MS and quantify individual modification stoichiometry at the wobble base of mt-tRNA-Met and tRNA-Leu-CAA using nucleotide resolution f5C sequencing technology. Our studies show that f5C modifications on tRNAs are dynamic, and responsive to fluctuations in cellular iron levels and O2 concentration. Further, we show using a translation reporter assay that decoding of Leu UUA codons is impaired in cells lacking f5C, implicating f5C(m)34 on tRNA-Leu-CAA in wobble decoding. Together, our work illuminates dynamic epitranscriptomic mechanisms regulating protein translation in response to environment.

Non-Viral RNA Therapies for Non-Small Cell Lung Cancer and Their Corresponding Clinical Trials

Ribonucleic acid (RNA)-based therapies represent a promising class of drugs for the treatment of non-small cell lung cancer (NSCLC) due to their ability to modulate gene expression. Therapies leveraging small interfering RNA (siRNA), messenger RNA (mRNA), microRNA (miRNA), and antisense oligonucleotides (ASOs) offer various advantages over conventional treatments, including the ability to target specific genetic mutations and the potential for personalized medicine approaches. However, the clinical translation of these therapeutics for the treatment of NSCLC faces challenges in delivery due to their immunogenicity, negative charge, and large size, which can be mitigated with delivery platforms. In this review, we provide a description of the pathophysiology of NSCLC and an overview of RNA-based therapeutics, specifically highlighting their potential application in the treatment of NSCLC. We discuss relevant classes of RNA and their therapeutic potential for NSCLC. We then discuss challenges in delivery and non-viral delivery strategies such as lipid- and polymer-based nanoparticles that have been developed to address these issues in preclinical models. Furthermore, we provide a summary table of clinical trials that leverage RNA therapies for NSCLC [which includes their National Clinical Trial (NCT) numbers] to highlight the current progress in NSCLC. We also discuss how these NSCLC therapies can be integrated with existing treatment modalities to enhance their efficacy and improve patient outcomes. Overall, we aim to highlight non-viral strategies that tackle RNA delivery challenges while showcasing RNA's potential as a next-generation therapy for NSCLC treatment.

CodonTransformer: a multispecies codon optimizer using context-aware neural networks

Degeneracy in the genetic code allows many possible DNA sequences to encode the same protein. Optimizing codon usage within a sequence to meet organism-specific preferences faces combinatorial explosion. Nevertheless, natural sequences optimized through evolution provide a rich source of data for machine learning algorithms to explore the underlying rules. Here, we introduce CodonTransformer, a multispecies deep learning model trained on over 1 million DNA-protein pairs from 164 organisms spanning all domains of life. The model demonstrates context-awareness thanks to its Transformers architecture and to our sequence representation strategy that combines organism, amino acid, and codon encodings. CodonTransformer generates host-specific DNA sequences with natural-like codon distribution profiles and with minimum negative cis-regulatory elements. This work introduces the strategy of Shared Token Representation and Encoding with Aligned Multi-masking (STREAM) and provides a codon optimization framework with a customizable open-access model and a user-friendly Google Colab interface.

Unlocking the potential of circular RNA vaccines: a bioinformatics and computational biology perspective

Bioinformatics has significantly advanced RNA-based therapeutics, particularly circular RNAs (circRNAs), which outperform mRNA vaccines, by offering superior stability, sustained expression, and enhanced immunogenicity due to their covalently closed structure. This review highlights how bioinformatics and computational biology optimise circRNA vaccine design, elucidates internal ribosome entry sites (IRES) selection, open reading frame (ORF) optimisation, codon usage, RNA secondary structure prediction, and delivery system development. While circRNA vaccines may not always surpass traditional vaccines in stability, their production efficiency and therapeutic efficacy can be enhanced through computational strategies. The discussion also addresses challenges and future prospects, emphasizing the need for innovative solutions to overcome current limitations and advance circRNA vaccine applications.

A deep learning model trained on expressed transcripts across different tissue types reveals cell-type codon-optimization preferences

Species-specific differences in protein translation can affect the design of protein-based drugs. Consequently, efficient expression of recombinant proteins often requires codon optimization. Publicly available optimization tools do not always result in higher expression levels and can lead to protein misfolding and reduced expression. Here, we aimed to develop a novel deep learning (DL) tool using a recurrent neural network (RNN) to define cell type-dependent codon biases. Using gene expression data from three different tissue types (brain, liver, and muscle) and all secretory genes, we trained DL models to predict optimal codon usage. Codon-optimized sequences for test reporter genes exhibited enhanced protein expression compared to their original sequences and those optimized using a publicly available tool. Interestingly, DL models trained on genes expressed in liver cells (hepatocytes) resulted in the highest levels of expression when tested in vitro, irrespective of the cell type. Our findings also demonstrate that DL-based codon optimization algorithms can significantly enhance protein translation, particularly for secretory proteins, which are crucial for therapeutic applications. This research represents a novel approach to codon optimization with broader implications for protein-based pharmaceuticals, vaccine manufacturing, gene therapy, and other recombinant DNA products.

Comparative analysis of chloroplast genomes on Meliaceae species: insights into the evolution and species identification

Introduction

Meliaceae, a significant group in Sapindales, possesses material and medicinal value due to its applications in timber and bioactive compounds. However, the high morphological diversity of the Meliaceae species and the lack of comparative studies of chloroplast (cp) genomes have led to great challenges in the classification and identification of Meliaceae species.

Methods

In this study, we sequenced the complete cp genomes of three Toona species (Toona fargesii, Toona ciliata, and Toona sinensis), and conducted comparative analyses of these cp genomes along with 29 previously published cp genomes of Meliaceae. Additionally, we performed the phylogenetic analyses and estimated the divergence times of Meliaceae.

Results

The cp genomes of 32 Meliaceae species ranged from 158,558 bp to 160,978 bp in length. Specifically, the cp genomes of Toona varied from 159,242 bp to 159,617 bp in length. These cp genomes contained a total of 135 unique genes, comprising 90 protein-coding, 8 rRNA, and 37 tRNA genes. Divergence time estimation revealed that the Meliaceae family diverged into two subfamilies (Cedreloideae and Melioideae) approximately 72.92 Ma (95% HPD: 60.62-87.01 Ma) in the Late Cretaceous. The diversification of Cedreloideae (47.86 Ma, 95% HPD: 47.42-48.22 Ma) occurred later than that of Melioideae (66.60 Ma, 95% HPD: 55.41-79.73 Ma). Furthermore, comparative genomic analysis identified 52 to 116 simple sequence repeats (SSRs) and twelve highly variable regions (HVRs) found among the cp genomes of Meliaceae.

Discussion

Divergence time estimation indicates that most Meliaceae species have a relatively recent origin, with rapid divergence occurring during the Late Oligocene or Early Miocene epochs. Comparative analysis of cp genomes revealed that Meliaceae exhibits relative conservation in terms of cp genome size, inverted-repeat (IR) boundary, genome structure, HVRs and codon patterns. Although differences exist between the Cedreloideae and Melioideae subfamilies, the overall similarity remains notably high. Furthermore, the ycf1, trnK-rps16, and ndhF-rpl32 regions exhibited the highest nucleotide polymorphism within Meliaceae, while the rpl22 gene displayed significant genetic diversity within both subfamilies. As candidate molecular markers, these regions may effectively distinguish among species. These findings not only provide insights into the evolution and species identification but also establish a scientific foundation for future systematics within Meliaceae.

Analysis of Codon Usage Patterns in a Rare Palmitoleic Acid Production Oleaginous Yeast, Scheffersomyces segobiensis

Scheffersomyces segobiensis DSM27193 has been identified as a potential host for Palmitoleic acid (POA)-rich lipids production. Our previous study has found that S. segobiensis DSM27193 possesses a broad substrate spectrum, excellent xylose fermentation capability, rapid growth, high biomass, and an abundance of intracellular acetyl-CoA. These characteristics make S. segobiensis DSM27193 an ideal chassis for metabolic engineering and the synthesis of various chemicals. However, the genetic coding features of this strain remain unclear. Analysis of the internal transcribed spacer (ITS) region suggested that S. segobiensis DSM27193 is closely related to Pichia stipitis (renamed Scheffersomyces stipitis), both of which exhibit CTG coding characteristic. In this study, we utilized software tools, such as CodonW, CUPS, and others to analyze the codon preference of the S. segobiensis DSM27193 genome. Additionally, we validated the reliability of the codon table through the expression of green fluorescent protein (GFP). The analysis results serve as a theoretical foundation for enhancing the expression of exogenous genes in S. segobiensis DSM27193.

Analysis of synonymous codon usage bias of Lassa virus

Lassa virus genome consists of two single-stranded, negative-sense RNA segments that lie in the genus Arenavirus. The disease associated with the Lassa virus is distributed all over the world, with approximately 3,000,000-5,000,000 infections diagnosed annually in West Africa. It shows high health risks to the human being. Previous research used the evolutionary time scale and adaptive evolution to describe the Lassa virus population pattern. However, it is still unclear how the Lassa virus takes advantage of synonymous codons. In this study, we analyzed the codon usage bias in 162 Lassa virus strains 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 disclosed that LASV strains are rich in A/T. The average ENC value indicated a low codon usage bias in LASVs. The ENC-plot, neutrality plot and parity rule 2 plot demonstrated that, besides mutational pressure, other factors like natural selection also contributed to codon usage bias. This study is significant because it described the pattern of codon usage in the genomes of the Lassa viruses and provided the information needed for a fundamental evolutionary study of them.

Bioinformatic Analysis of L-Asparaginase Structures in Halophilic (Bacillus subtilis), Mesophilic (Kibdelosporangium), and Thermophilic (Thermococcus kodakarensis) Bacteria: New Insights on L-asparaginase as a Potent Antileukemic Agent

Background: The L-asparaginase enzyme is used as an anticancer agent in treating acute lymphoblastic leukemia (ALL). Moreover, it has widespread applications in medicine, food, and pharmaceutical industries. Methods: The nucleotide and amino acid sequences of L-asparaginase derived from Bacillus subtilis BEST7613, Kibdelosporangium sp. MJ126-NF4, and Thermococcus kodakarensis KOD1 have been obtained from the GenBank and the NCBI databases. The EMBOSS Water pairwise sequence alignments were performed using ClustalW 1.83. Prediction of secondary and tertiary protein structures of the different L-asparaginase molecules studied was done using SWISS-MODEL software. In addition, the protein domains of L-asparaginase originating from the three mentioned bacteria were analyzed using PROSITE software. Theoretical isoelectric point (pI), molecular weight, and amino acid composition were predicted using the protein pI calculator (http:// isoelectric.ovh.org/). Results: Despite the structural differences in L-asparaginase enzymes in the three bacterial strains, there were no differences in their functional characteristics, including molecular weight, pI, and functional domain. Conclusion: Analyzing structural differences and finding functional similarities can be useful in designing drugs with higher stability and biological half-life. Our analysis showed that proteins with different structures could have similar functional characteristics, which proves the codon usage hypothesis.

Codon usage patterns and genomic variation analysis of chloroplast genomes provides new insights into the evolution of Aroideae

Aroideae is an important subfamily of the Araceae family and contains many plants with medicinal and edible value. It is difficult to identify and classify Aroideae species accurately on the basis of morphology alone because of their polymorphic phenotypic traits. The chloroplast genome (CPG) is useful for studying on plant taxonomy and phylogeny, and the analysis of codon usage bias (CUB) in CPGs provides further insights into the intricate phylogenetic relationships among Aroideae. The results showed that the codon third position of the chloroplast genome coding sequence in Aroideae was rich in A and T, with a GC content of 37.91%. The ENC-plot and PR2-plot revealed that the codon usage bias of Aroideae was influenced by multiple factors, with natural selection as the dominant factor. Thirteen to twenty optimal codons ending in A/T were identified in 61 Aroideae species. Additionally, the comparative analysis of CPGs revealed that two single copy regions and non-coding regions were variable in Aroideae. Eight highly divergent regions (Pi > 0.064) were identified (ndhF, rpl32, ccsA, ndhE, ndhG, ndhF-rpl32, ccsA-ndhD, and ndhE-ndhG) , in which ndhE have the potential to serve as a reliable DNA marker to discriminate chloroplasts in Aroideae subfamily. Furthermore, the maximum likelihood-based phylogenetic trees constructed from complete chloroplast genomes and protein-coding sequences presented similar topologies. Principal component clustering analysis based on relative synonymous codon usage values (RSCUs) revealed that Calla was clearly deviated from Montrichardia and Anubias, and that Alocasia was closer to Colocasieae than to Arisaemateae. These findings suggest that the use of RSCU for clustering analysis could offer new theoretical support for species classification and evolution. Our research could provide a theoretical foundation for the chloroplast genetic engineering, taxonomy, and phylogenetic relationships of Aroideae chloroplasts.

Multi-omics investigation of high-transglutaminase production mechanisms in Streptomyces mobaraensis and co-culture-enhanced fermentation strategies

Transglutaminase (TGase) has been widely applied in the food industry. However, achieving high-yield TGase production remains a challenge, limiting its broader industrial application. In this study, a high-yield strain with stable genetic traits was obtained through UV-ARTP combined mutagenesis, achieving a maximum TGase activity of 13.77 U/mL, representing a 92.43% increase. Using this strain as a forward mutation gene pool, comparative genomic research identified 95 mutated genes, which were mostly due to base substitutions that led to changes in codon usage preference. Transcriptomic analysis revealed significant expression changes in 470 genes, with 232 upregulated and 238 downregulated genes. By investigating potential key regulatory factors, comprehensive analysis indicated that changes in codon usage preference, amino acid metabolism, carbon metabolism, protein export processes, TGase activation, and spore production pathways collectively contributed to the enhancement of TGase activity. Subsequently, the in vitro activation efficiency of TGase was further improved using co-cultivation techniques with neutral proteases secreted by Bacillus amyloliquefaciens CICC10888, and a TGase activity of 16.91 U/mL was achieved, accounting for a 22.71% increase. This study provides a comprehensive understanding of the mechanisms underlying high-yield TGase production and valuable insights and data references for future research.

Analysis of the Codon Usage Bias Pattern in the Chloroplast Genomes of Chloranthus Species (Chloranthaceae)

BACKGROUND

The codon preference of chloroplast genomes not only reflects mutation patterns during the evolutionary processes of species but also significantly affects the efficiency of gene expression. This characteristic holds significant scientific importance in the application of chloroplast genetic engineering and the genetic improvement of species. Chloranthus, an ancestral angiosperm with significant economic, medicinal, and ornamental value, belongs to the basal angiosperms. However, the codon usage patterns among Chloranthus species have remained unclear.

METHODS

To investigate codon usage bias and its influencing factors in Chloranthus chloroplast genomes, we utilized CodonW, CUSP, and SPSS software to analyze the chloroplast genomes of seven Chloranthus species.

RESULTS

In this study, we reported and characterized the complete chloroplast genome of the Chinese endemic species Chloranthus angustifolius. The phylogenetic tree based on the whole chloroplast genomes showed that C. angustifolius is sister to Chloranthus fortunei, and the genus Chloranthus is divided into two major clades, consistent with previous studies. Our results revealed that the GC content at different codon positions across all seven Chloranthus species was less than 50%, with GC1 > GC2 > GC3. Additionally, the average effective number of codons (ENC) values exceeded 45. A total of 10 shared optimal codons were identified, nine of which end with A or U. PR2-plot, ENC-plot, and neutrality plot analyses indicated that natural selection primarily influenced codon usage bias in the chloroplast genomes of Chloranthus.

CONCLUSIONS

We newly obtained the chloroplast genome of C. angustifolius and proposed that natural selection played a key role in codon usage patterns in Chloranthus species. These findings contribute to our understanding of evolutionary history and genetic diversity within this genus.

MicroRNA-regulated suppression of some overexpressed genes in schizophrenia and their evolutionary significance

Impaired formation of the brain or nervous system is the root cause of neurodevelopmental disorders which appear in pregnancy or soon after birth. One such neurodevelopmental disorder is Schizophrenia. Among the most serious forms of psychosis, Schizophrenia (SCZ) affects 1 % of the general population. MiRNA targeting sites and codon usage of nine overexpressed genes in Schizophrenia were investigated in this study. The neutrality plot demonstrated the importance of natural selection over mutational pressure in the evolution of these genes. The analysis of COSM revealed that the miRNA target regions of the genes were encoded by non-optimal codons, resulting in low translational efficiency, whereas the GC content revealed that the miRNA-mRNA binding was strong. From this study it was concluded that each overexpressed gene was targeted by several human miRNAs for putative suppression. These identified miRNAs could have therapeutic potential in Schizophrenia therapy.

Improving the generalization of protein expression models with mechanistic sequence information

The growing demand for biological products drives many efforts to maximize expression of heterologous proteins. Advances in high-throughput sequencing can produce data suitable for building sequence-to-expression models with machine learning. The most accurate models have been trained on one-hot encodings, a mechanism-agnostic representation of nucleotide sequences. Moreover, studies have consistently shown that training on mechanistic sequence features leads to much poorer predictions, even with features that are known to correlate with expression, such as DNA sequence motifs, codon usage, or properties of mRNA secondary structures. However, despite their excellent local accuracy, current sequence-to-expression models can fail to generalize predictions far away from the training data. Through a comparative study across datasets in Escherichia coli and Saccharomyces cerevisiae, here we show that mechanistic sequence features can provide gains on model generalization, and thus improve their utility for predictive sequence design. We explore several strategies to integrate one-hot encodings and mechanistic features into a single predictive model, including feature stacking, ensemble model stacking, and geometric stacking, a novel architecture based on graph convolutional neural networks. Our work casts new light on mechanistic sequence features, underscoring the importance of domain-knowledge and feature engineering for accurate prediction of protein expression levels.

Comprehensive analysis of 111 Pleuronectiformes mitochondrial genomes: insights into structure, conservation, variation and evolution

BACKGROUND

Pleuronectiformes, also known as flatfish, are important model and economic animals. However, a comprehensive genome survey of their important organelles, mitochondria, has been limited. Therefore, we aim to analyze the genomic structure, codon preference, nucleotide diversity, selective pressure and repeat sequences, as well as reconstruct the phylogenetic relationship using the mitochondrial genomes of 111 flatfish species.

RESULTS

Our analysis revealed a conserved gene content of protein-coding genes and rRNA genes, but varying numbers of tRNA genes and control regions across species. Various gene rearrangements were found in flatfish species, especially for the rearrangement of nad5-nad6-cytb block in Samaridae family, the swapping rearrangement of nad6 and cytb gene in Bothidae family, as well as the control region translocation and tRNA-Gln gene inversion in the subfamily Cynoglossinae, suggesting their unique evolutionary history and/or functional benefit. Codon usage showed obvious biases, with adenine being the most frequent nucleotide at the third codon position. Nucleotide diversity and selective pressure analysis suggested that different protein-coding genes underwent varying degrees of evolutionary pressure, with cytb and cox genes being the most conserved ones. Phylogenetic analysis using both whole mitogenome information and concatenated independently aligned protein-coding genes largely mirrored the taxonomic classification of the species, but showed different phylogeny. The identification of simple sequence repeats and various long repetitive sequences provided additional complexity of genome organization and offered markers for evolutionary studies and breeding practices.

CONCLUSIONS

This study represents a significant step forward in our comprehension of the flatfish mitochondrial genomes, providing valuable insights into the structure, conservation and variation within flatfish mitogenomes, with implications for understanding their evolutionary history, functional genomics and fisheries management. Future research can delve deeper into conservation biology, evolutionary biology and functional usages of variations.

Complete mitochondrial genome assembly and comparative analysis of Colocasia esculenta

Colocasia esculenta ranks as the fifth most important tuber crop and is known for its high nutritional and medicinal value. However, there is no research on its mitochondrial genome, hindering in-depth exploration of its genomic resources and genetic relationships. Using second- and third-generation sequencing technologies, we assembled and annotated the mitogenome of C. esculenta. Its mitogenome mainly consists of five circular DNA molecules, with a total length of 594,811 bp and a GC content of 46.25%. A total of 55 genes, 157 simple sequence repeats, 29 tandem repeat sequences, 202 dispersed repeat sequences, and 625 RNA editing sites were detected. Most protein-coding genes use ATG as the start codon, and the third position of the codon tends to be A or T (U). GAA, AUU, and UUU are the most common codons in C. esculenta mitochondria. Finally, based on 28 representative plant species, a phylogenetic tree was constructed, revealing a close relationship between C. esculenta and Araceae. This study provides comprehensive information on C. esculenta, laying a foundation for crop genetics and molecular breeding.

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.

Genome-modified Caenorhabditis elegans expressing the human cytochrome P450 (CYP1A1 and CYP1A2) pathway: An experimental model for environmental carcinogenesis and pharmacological research

Polycyclic aromatic hydrocarbons (PAHs), including the Group 1 human carcinogen benzo[a]pyrene (BaP), are produced by the incomplete combustion of organic matter and thus are present in tobacco smoke, charbroiled food and diesel exhaust. The nematode Caenorhabditis elegans is an established model organism, however it lacks the genetic components of the classical mammalian cytochrome P450 (CYP)-mediated BaP-diol-epoxide metabolism pathway. We therefore introduced human CYP1A1 or CYP1A2 together with human epoxide hydrolase (EPHX) into the worm genome by Mos1-mediated Single Copy Insertion (MosSCI) and evaluated their response to BaP exposure via toxicological endpoints. Compared to wild-type control, CYP-humanised worms were characterised by an increase in pharyngeal pumping rate and a decrease in volumetric surface area. Furthermore, BaP exposure reduced reproductive performance, as reflected in smaller brood size, which coincided with the downregulation of the nematode-specific major sperm protein as determined by transcriptomics (RNAseq). BaP-mediated reproductive toxicity was exacerbated in CYP-humanised worms at higher exposure levels. Collagen-related genes were downregulated in BaP-exposed animals, which correlate with the reduction in volumetric size. Whole genome DNA sequencing revealed a higher frequency of T > G (A > C) base substitution mutations in worms expressing human CYP1A1;EPHX which aligned with an increase in DNA adducts identified via an ELISA method (but not classical 32P-postlabelling). Overall, the CYP-humanised worms provided new insights into the value of genome-optimised invertebrate models by identifying the benefits and limitations within the context of the (3Rs) concept which aims to replace, reduce and refine the use of animals in research.

Comprehensive Analysis of Codon Usage Bias in Human Papillomavirus Type 51

Human papillomavirus type 51 (HPV-51) is associated with various cancers, including cervical cancer. Examining the codon usage bias of the organism can offer valuable insights into its evolutionary patterns and its relationship with the host. This study comprehensively analyzed codon usage bias in HPV-51 by examining 64 complete genome sequences sourced from the NCBI GenBank database. Our analysis revealed no noteworthy preference for codon usage in HPV-51 overall. However, there was a noticeable bias towards A/T-ending codons, accompanied by GC3s below 32%. Dinucleotide frequency analysis revealed reduced frequencies for ApA, CpG, and TpC dinucleotides, while CpA and TpG dinucleotides were more frequent than others. Relative Synonymous Codon Usage analysis revealed 30 favored codons, primarily concluding with A/T nucleotides. Further analysis using Parity Rule 2, Effective Number of Codons plot, and neutrality plot indicated a balance between mutational pressure and natural selection, with natural selection being the primary force shaping codon usage bias. The Isoacceptor tRNA Pool analysis indicates that HPV-51 has a higher translation efficiency within the human cellular translational system. Moreover, the Codon Adaptation Index and Relative Codon Deoptimization Index analyses suggested a moderate adaptation of HPV-51 to human codon preferences. Our discoveries offer valuable perspectives on how HPV-51 evolves and uses genetic codes, contributing to a deeper comprehension of its endurance and disease-causing potential.

ENaC gene variants and their involvement in Covid‑19 severity

Epidemiological studies report the association of diverse cardiovascular conditions with coronavirus disease 2019 (COVID-19), but the causality has remained to be established. Specific genetic factors and the extent to which they can explain variation in susceptibility or severity are largely elusive. The present study aimed to evaluate the link between 32 cardio-metabolic traits and COVID-19. A total of 60 participants were enrolled, who were categorized into the following 4 groups: A control group with no COVID-19 or any other underlying pathologies, a group of patients with a certain form of dyslipidemia and predisposition to atherosclerotic disease, a COVID-19 group with mild or no symptoms and a COVID-19 group with severe symptomatology hospitalized at the Intensive Care Unit of Sotiria Hospital (Athens, Greece). Demographic, clinical and laboratory data were recorded and genetic material was isolated, followed by simultaneous analysis of the genes related to dyslipidemia using a custom-made next-generation sequencing panel. In the COVID-19 group with mild or absent symptoms, the variant c.112C>T:p.P38S was detected in the sodium channel epithelial 1 subunit α (SCNN1A) gene, with a major allele frequency (Maf) of <0.01. In the COVID-19 group with severe symptoms, the variant c.786G>A:p.T262T was detected in the SCNN1B gene, which encodes for the β-subunit of the epithelial sodium channel ENaC, with a Maf <0.01. None of the two rare variants were detected in the control or dyslipidemia groups. In conclusion, the current study suggests that ENaC variants are likely associated with genetic susceptibility to COVID-19, supporting the rationale for the risk and protective genetic factors for the morbidity and mortality of COVID-19.

Scaled codon usage similarity index: A comprehensive resource for crop plants

Over the past three decades species-specific codon usage bias has been used to optimize heterologous gene expression in the target host. However, synthesizing codon optimized gene for multiple species is not achievable due to the prohibitive expense of DNA synthesis. To address this challenge, grouping species with similar codon usage can reduce the need for species-specific codon optimised gene synthesis. We introduced Scaled Codon Usage Similarity (SCUS) index to standardize species similarity assessments based on codon usage profiles. By analysing the SCUS index of 77 plant nuclear genomes from 13 families, we identified codon usage patterns and similarities. We developed an online SCUS index database and a Consensus Relative Synonymous Codon Usage (CRSCU) calculator, available at https://pcud.plantcodon.info. The CRSCU calculator helps determine the most suitable codon usage pattern among two or more species. The SCUS index and CRSCU calculator will facilitate the development of multi-species expression systems, enabling the efficient expression of a single synthetic gene across various crop species. This innovation paves the way for cost-effective and efficient heterologous gene expression across diverse crop species.

Characteristics and phylogenetic distribution of megaplasmids and prediction of a putative chromid in Pseudomonas aeruginosa

Research on megaplasmids that contribute to the spread of antimicrobial resistance (AMR) in Pseudomonas aeruginosa strains has grown in recent years due to the now widely used technologies allowing long-read sequencing. Here, we systematically analyzed distinct and consistent genetic characteristics of megaplasmids found in P. aeruginosa. Our data provide information on their phylogenetic distribution and hypotheses tracing the potential evolutionary paths of megaplasmids. Most of the megaplasmids we found belong to the IncP-2-type, with conserved and syntenic genetic backbones carrying modules of genes associated with chemotaxis apparatus, tellurite resistance and plasmid replication, segregation, and transmission. Extensively variable regions harbor abundant AMR genes, especially those encoding β-lactamases such as VIM-2, IMP-45, and KPC variants, which are high-risk elements in nosocomial infection. IncP-2 megaplasmids act as effective vehicles transmitting AMR genes to diverse regions. One evolutionary model of the origin of megaplasmids claims that chromids can develop from megaplasmids. These chromids have been characterized as an intermediate between a megaplasmid and a chromosome, also containing core genes that can be found on the chromosome but not on the megaplasmid. Using in silico prediction, we identified the "PABCH45 unnamed replicon" as a putative chromid in P. aeruginosa, which shows a much higher similarity and closer phylogenetic relationship to chromosomes than to megaplasmids while also encoding plasmid-like partition genes. We propose that such a chromid could facilitate genome expansion, allowing for more rapid adaptations to novel ecological niches or selective conditions, in comparison to megaplasmids.

Modeling and measuring how codon usage modulates the relationship between burden and yield during protein overexpression in bacteria

Excess utilization of translational resources is a critical source of burden on cells engineered to over-express exogenous proteins. To improve protein yields and genetic stability, researchers often use codon optimization strategies that improve translational efficiency by matching an exogenous gene's codon usage with that of the host organism's highly expressed genes. Despite empirical data that shows the benefits of codon optimization, little is known quantitatively about the relationship between codon usage bias and the burden imposed by protein overexpression. Here, we develop and experimentally evaluate a stochastic gene expression model that considers the impact of codon usage bias on the availability of ribosomes and different tRNAs in a cell. In agreement with other studies, our model shows that increasing exogenous protein expression decreases production of native cellular proteins in a linear fashion. We also find that the slope of this relationship is modulated by how well the codon usage bias of the exogenous gene and the host's genes match. Strikingly, we predict that an overoptimization domain exists where further increasing usage of optimal codons worsens yield and burden. We test our model by expressing sfGFP and mCherry2 from constructs that have a wide range of codon optimization levels in Escherichia coli . The results agree with our model, including for an mCherry2 gene sequence that appears to lose expression and genetic stability from codon overoptimization. Our findings can be leveraged by researchers to predict and design more optimal cellular systems through the use of more nuanced codon optimization strategies.

Genetic Code Expansion History and Modern Innovations

The genetic code is the foundation for all life. With few exceptions, the translation of nucleic acid messages into proteins follows conserved rules, which are defined by codons that specify each of the 20 proteinogenic amino acids. For decades, leading research groups have developed a catalogue of innovative approaches to extend nature's amino acid repertoire to include one or more noncanonical building blocks in a single protein. In this review, we summarize advances in the history of in vitro and in vivo genetic code expansion, and highlight recent innovations that increase the scope of biochemically accessible monomers and codons. We further summarize state-of-the-art knowledge in engineered cellular translation, as well as alterations to regulatory mechanisms that improve overall genetic code expansion. Finally, we distill existing limitations of these technologies into must-have improvements for the next generation of technologies, and speculate on future strategies that may be capable of overcoming current gaps in knowledge.

Description of mitochondrial genomes and phylogenetic analysis of Megophthalminae (Hemiptera: Cicadellidae)

To elucidate phylogenetic relationships within the leafhopper's subfamily Megophthalminae (Hemiptera: Cicadellidae), mitogenomes of 12 species of the subfamily were sequenced and assembled. These were added to the mitogenomes of the eight other species that are currently available. Mitogenome size ranged from 15,193 bp in Onukigallia onukii (Matsumura, 1912) to 15,986 bp in Multinervis guangxiensis (Li and Li, 2013), they all contained 37 genes, and gene order was similar to that in other leafhoppers. Nucleotide composition analysis showed that the AT content was higher than that of GC, and the protein-coding genes usually ended with A/T at the 3rd codon position. The Ka/Ks ratio showed that the CYTB gene has the slowest evolutionary rate, while ND4 is the gene with the fastest evolutionary rate. Relative synonymous codon usage analysis revealed the most frequently used codon was UUA (L), followed by CGA (R), and the least frequently used codon was CCG (P). Parity plot and neutrality plot analyses showed that the codon usage bias of mitochondrial genes was influenced by natural selection and mutation pressure. However, natural selection plays a major role, while the effect of mutation pressure was small. Effective number of codons values were 40.15-49.17, which represented relatively low codon bias. Phylogenetic analyses based on three datasets (AA, 13PCG, 13PCG_2rRNA) using two methods (maximum likelihood and Bayesian inference). In the obtained topology, the Megophthalminae species were clustered into a monophyletic group. In conclusion, our results clarify structural modules of the mitochondrial genes and confirm the monophyly of Megophthalminae within Cicadellidae.

SARS-CoV-2 Displays a Suboptimal Codon Usage Bias for Efficient Translation in Human Cells Diverted by Hijacking the tRNA Epitranscriptome

Codon bias analysis of SARS-CoV-2 reveals suboptimal adaptation for translation in human cells it infects. The detailed examination of the codons preferentially used by SARS-CoV-2 shows a strong preference for LysAAA, GlnCAA, GluGAA, and ArgAGA, which are infrequently used in human genes. In the absence of an adapted tRNA pool, efficient decoding of these codons requires a 5-methoxycarbonylmethyl-2-thiouridine (mcm5s2) modification at the U34 wobble position of the corresponding tRNAs (tLysUUU; tGlnUUG; tGluUUC; tArgUCU). The optimal translation of SARS-CoV-2 open reading frames (ORFs) may therefore require several adjustments to the host's translation machinery, enabling the highly biased viral genome to achieve a more favorable "Ready-to-Translate" state in human cells. Experimental approaches based on LC-MS/MS quantification of tRNA modifications and on alteration of enzymatic tRNA modification pathways provide strong evidence to support the hypothesis that SARS-CoV-2 induces U34 tRNA modifications and relies on these modifications for its lifecycle. The conclusions emphasize the need for future studies on the evolution of SARS-CoV-2 codon bias and its ability to alter the host tRNA pool through the manipulation of RNA modifications.

A review on the development of bacterial multi-epitope recombinant protein vaccines via reverse vaccinology

Bacterial vaccines play a crucial role in combating bacterial infectious diseases. Apart from the prevention of disease, bacterial vaccines also help to reduce the mortality rates in infected populations. Advancements in vaccine development technologies have addressed the constraints of traditional vaccine design, providing novel approaches for the development of next-generation vaccines. Advancements in reverse vaccinology, bioinformatics, and comparative proteomics have opened horizons in vaccine development. Specifically, the use of protein structural data in crafting multi-epitope vaccines (MEVs) to target pathogens has become an important research focus in vaccinology. In this review, we focused on describing the methodologies and tools for epitope vaccine development, along with recent progress in this field. Moreover, this article also discusses the challenges in epitope vaccine development, providing insights for the future development of bacterial multi-epitope genetically engineered vaccines.

Is there a bias in the codon frequency corresponding to homo-repeats found in human proteins?

It is well known that there is a codon usage bias in genomes, that is, some codons are observed more often than others. Codons implicated in the homo-repeats regions in human proteins are no exception. In this work, we analyzed the codon usage bias for all amino acid residues in homo-repeats larger than 4 in 3753 human proteins from 20447 protein sequences from the canonically reviewed human proteome. We have discovered that almost all homo-repeats in the human proteome, most of which encode Ala, Glu, Gly, Leu, Pro, and Ser (∼80% of all homo-repeats), have a codon usage bias, i.e. are mainly encoded by one codon. Moreover, there is a strong shift in homo-repeats in favor of the content of GC rich codons. Homo-repeats with Ala, Glu, Gly, Leu, Pro, and Ser predominate in the PDB, which has both ordered and disordered status. Examining the distribution of splicing sites, we found that about 15% of homo-repeats either contain or are located within 10 nucleotides of the splicing site, and Glu and Leu predominate in these homo-repeats. Our data is important for future study of the functions of homo-repeats, protein-protein interactions, and evolutionary fitness.

Comparative Phylogenomic Study of Malaxidinae (Orchidaceae) Sheds Light on Plastome Evolution and Gene Divergence

Malaxidinae is one of the most confusing groups in the Orchidaceae classification. Previous phylogenetic analyses have revealed that the relationships between the taxa in Malaxidinae have not yet been reliably established, using only a few plastome regions and nuclear ribosomal internal transcribed spacer (nrITS). In the present study, the complete plastomes of Oberonia integerrima and Crepidium purpureum were assembled using high-throughput sequencing. Combined with publicly available complete plastome data, this resulted in a dataset of 19 plastomes, including 17 species of Malaxidinae. The plastome features and phylogenetic relationships were compared and analyzed. The results showed the following: (1) Malaxidinae species plastomes possess the quadripartite structure of typical angiosperms, with sizes ranging from 142,996 to 158,787 bp and encoding from 125 to 133 genes. The ndh genes were lost or pseudogenized to varying degrees in six species. An unusual inversion was detected in the large single-copy region (LSC) of Oberonioides microtatantha. (2) Eight regions, including ycf1, matK, rps16, rpl32, ccsA-ndhD, clpP-psbB, trnFGAA-ndhJ, and trnSGCU-trnGUCC, were identified as mutational hotspots. (3) Based on complete plastomes, 68 protein-coding genes, and 51 intergenic regions, respectively, our phylogenetic analyses revealed the genus-level relationships in this subtribe with strong support. The Liparis was supported as non-monophyletic.

The amino acid composition of a protein influences its expression

The quantity of each protein in a cell only is only partially correlated with its gene transcription rate. Independent influences on protein synthesis levels include mRNA sequence motifs, amino acyl-tRNA synthesis levels, elongation factor action, and protein susceptibility to degradation. Here we report that the amino acid composition of a protein can also influence its expression level in two distinct ways. The nutritional classification of amino acids in animals reflects their potential for scarcity-essential amino acids (EAA) are reliant on dietary supply, non-essential amino acids (NEAA) from internal biosynthesis, and conditionally essential amino acids (CEAA) from both. Accessing public proteomic datasets, we demonstrate that a protein's CEAA sequence composition is inversely correlated with expression-a correlation enhanced during rapid cellular proliferation-suggesting CEAA availability can limit translation. Similarly, proteins with the most extreme compositions of EAA are generally reduced in abundance. These latter proteins participate in biological systems such as taste and food-seeking behaviour, oxidative phosphorylation, and chemokine function, and so linking their expression to EAA availability may act as a homeostatic response to malnutrition. Protein composition can also influence general human phenotypes and disease susceptibility: stature proteins are enriched in CEAAs, and a curated dataset of over 700 cancer proteins is significantly under-represented in EAAs. We also show that individual amino acids can influence protein expression across all kingdoms of life and that this effect appears to be rooted in the unchanging structural and mRNA encoding features of each amino acid. Species-specific environmental survival pathways are shown to be enriched in proteins with individual amino acid compositions favouring higher expression. These two forms of amino acid-driven protein expression regulation promise new insights into systems biology, evolutionary studies, experimental research design, and public health intervention.

Codon Bias of the DDR1 Gene and Transcription Factor EHF in Multiple Species

Milk production is an essential economic trait in cattle, and understanding the genetic regulation of this trait can enhance breeding strategies. The discoidin domain receptor 1 (DDR1) gene has been identified as a key candidate gene that influences milk production, and ETS homologous factor (EHF) is recognized as a critical transcription factor that regulates DDR1 expression. Codon usage bias, which affects gene expression and protein function, has not been fully explored in cattle. This study aims to examine the codon usage bias of DDR1 and EHF transcription factors to understand their roles in dairy production traits. Data from 24 species revealed that both DDR1 and EHF predominantly used G/C-ending codons, with the GC3 content averaging 75.49% for DDR1 and 61.72% for EHF. Synonymous codon usage analysis identified high-frequency codons for both DDR1 and EHF, with 17 codons common to both genes. Correlation analysis indicated a negative relationship between the effective number of codons and codon adaptation index for both DDR1 and EHF. Phylogenetic and clustering analyses revealed similar codon usage patterns among closely related species. These findings suggest that EHF plays a crucial role in regulating DDR1 expression, offering new insights into genetically regulating milk production in cattle.

Alternate RNA decoding results in stable and abundant proteins in mammals

Amino acid substitutions may substantially alter protein stability and function, but the contribution of substitutions arising from alternate translation (deviations from the genetic code) is unknown. To explore it, we analyzed deep proteomic and transcriptomic data from over 1,000 human samples, including 6 cancer types and 26 healthy human tissues. This global analysis identified 60,024 high confidence substitutions corresponding to 8,801 unique sites in proteins derived from 1,990 genes. Some substitutions are shared across samples, while others exhibit strong tissue-type and cancer specificity. Surprisingly, products of alternate translation are more abundant than their canonical counterparts for hundreds of proteins, suggesting sense codon recoding. Recoded proteins include transcription factors, proteases, signaling proteins, and proteins associated with neurodegeneration. Mechanisms contributing to substitution abundance include protein stability, codon frequency, codon-anticodon mismatches, and RNA modifications. We characterize sequence motifs around alternatively translated amino acids and how substitution ratios vary across protein domains, tissue types and cancers. The substitution ratios are positively associated with intrinsically disordered regions and genetic polymorphisms in gnomAD, though the polymorphisms cannot account for the substitutions. Both the sequence and the tissue-specificity of alternatively translated proteins are conserved between human and mouse. These results demonstrate the contribution of alternate translation to diversifying mammalian proteomes, and its association with protein stability, tissue-specific proteomes, and diseases.

Compositional Features and Codon Usage Pattern of Genes Associated with Parkinson's Disease

Codon usage bias (CUB) is the phenomenon of non-uniform usage of synonymous codons in which some codons are more used than others and it helps in understanding the molecular organization of genome. Bioinformatic approach was used to analyze the protein-coding sequences of genes associated with Parkinson's disease (PD) to explore compositional features and codon usage pattern as no details work was reported yet. The average improved effective number of codons (Nc) and Nc prime were 42.74 and 44.26 respectively, indicated that CUB was low in these genes. In most of the genes, the overall GC content was almost 50% and GC content at the 1st codon position was the highest while GC content at the 2nd codon position was lowest. Relative synonymous codon usage (RSCU) analysis elucidated over-represented (p > 1.6) and under-represented codons (p < 0.6). The GTG (Val) is the only codon over-represented in all genes. Over-represented codons except (GTG) were A or T ending while under-represented codons (except ACT) were G or C ending. The codons namely TTA (Leu), CTA (Leu), ATC (Ile), ATA (Ile), AGT (Ser), AAC (Asn), TGT (Cys), TGC (Cys), CGC (Arg), AGA (Arg), and AGG (Arg) were absent in SNCA1 to SNCA8 genes. The codon TCG (Ser) was absent in all genes except UCHL1 and PINK1. Correspondence analysis (COA) revealed that the pattern of codon usage differs among genes associated with PD. Neutrality plot analysis indicated some of the points are diagonal distribution suggested that mutation pressure influenced the CUB in genes associated with PD.

Strategies to overcome the challenges of low or no expression of heterologous proteins in Escherichia coli

Protein expression is a critical process in diverse biological systems. For Escherichia coli, a widely employed microbial host in industrial catalysis and healthcare, researchers often face significant challenges in constructing recombinant expression systems. To maximize the potential of E. coli expression systems, it is essential to address problems regarding the low or absent production of certain target proteins. This article presents viable solutions to the main factors posing challenges to heterologous protein expression in E. coli, which includes protein toxicity, the intrinsic influence of gene sequences, and mRNA structure. These strategies include specialized approaches for managing toxic protein expression, addressing issues related to mRNA structure and codon bias, advanced codon optimization methodologies that consider multiple factors, and emerging optimization techniques facilitated by big data and machine learning.

GenRCA: a user-friendly rare codon analysis tool for comprehensive evaluation of codon usage preferences based on coding sequences in genomes

BACKGROUND

The study of codon usage bias is important for understanding gene expression, evolution and gene design, providing critical insights into the molecular processes that govern the function and regulation of genes. Codon Usage Bias (CUB) indices are valuable metrics for understanding codon usage patterns across different organisms without extensive experiments. Considering that there is no one-fits-all index for all species, a comprehensive platform supporting the calculation and analysis of multiple CUB indices for codon optimization is greatly needed.

RESULTS

Here, we release GenRCA, an updated version of our previous Rare Codon Analysis Tool, as a free and user-friendly website for all-inclusive evaluation of codon usage preferences of coding sequences. In this study, we manually reviewed and implemented up to 31 codon preference indices, with 65 expression host organisms covered and batch processing of multiple gene sequences supported, aiming to improve the user experience and provide more comprehensive and efficient analysis.

CONCLUSIONS

Our website fills a gap in the availability of comprehensive tools for species-specific CUB calculations, enabling researchers to thoroughly assess the protein expression level based on a comprehensive list of 31 indices and further guide the codon optimization.

Genome-wide impact of codon usage bias on translation optimization in Drosophila melanogaster

Accuracy and efficiency are fundamental to mRNA translation. Codon usage bias is widespread across species. Despite the long-standing association between optimized codon usage and improved translation, our understanding of its evolutionary basis and functional effects remains limited. Drosophila is widely used to study codon usage bias, but genome-scale experimental data are scarce. Using high-resolution mass spectrometry data from Drosophila melanogaster, we show that optimal codons have lower translation errors than nonoptimal codons after accounting for these biases. Genomic-scale analysis of ribosome profiling data shows that optimal codons are translated more rapidly than nonoptimal codons. Although we find no long-term selection favoring synonymous mutations in D. melanogaster after diverging from D. simulans, we identify signatures of positive selection driving codon optimization in the D. melanogaster population. These findings expand our understanding of the functional consequences of codon optimization and serve as a foundation for future investigations.

The regulatory landscape of interacting RNA and protein pools in cellular homeostasis and cancer

Biological systems encompass intricate networks governed by RNA-protein interactions that play pivotal roles in cellular functions. RNA and proteins constituting 1.1% and 18% of the mammalian cell weight, respectively, orchestrate vital processes from genome organization to translation. To date, disentangling the functional fraction of the human genome has presented a major challenge, particularly for noncoding regions, yet recent discoveries have started to unveil a host of regulatory functions for noncoding RNAs (ncRNAs). While ncRNAs exist at different sizes, structures, degrees of evolutionary conservation and abundances within the cell, they partake in diverse roles either alone or in combination. However, certain ncRNA subtypes, including those that have been described or remain to be discovered, are poorly characterized given their heterogeneous nature. RNA activity is in most cases coordinated through interactions with RNA-binding proteins (RBPs). Extensive efforts are being made to accurately reconstruct RNA-RBP regulatory networks, which have provided unprecedented insight into cellular physiology and human disease. In this review, we provide a comprehensive view of RNAs and RBPs, focusing on how their interactions generate functional signals in living cells, particularly in the context of post-transcriptional regulatory processes and cancer.

tRNA expression and modification landscapes, and their dynamics during zebrafish embryo development

tRNA genes exist in multiple copies in the genome of all organisms across the three domains of life. Besides the sequence differences across tRNA copies, extensive post-transcriptional modification adds a further layer to tRNA diversification. Whilst the crucial role of tRNAs as adapter molecules in protein translation is well established, whether all tRNAs are actually expressed, and whether the differences across isodecoders play any regulatory role is only recently being uncovered. Here we built upon recent developments in the use of NGS-based methods for RNA modification detection and developed tRAM-seq, an experimental protocol and in silico analysis pipeline to investigate tRNA expression and modification. Using tRAM-seq, we analysed the full ensemble of nucleo-cytoplasmic and mitochondrial tRNAs during embryonic development of the model vertebrate zebrafish. We show that the repertoire of tRNAs changes during development, with an apparent major switch in tRNA isodecoder expression and modification profile taking place around the start of gastrulation. Taken together, our findings suggest the existence of a general reprogramming of the expressed tRNA pool, possibly gearing the translational machinery for distinct stages of the delicate and crucial process of embryo development.

Comparative analysis of codon usage bias in the chloroplast genomes of eighteen Ampelopsideae species (Vitaceae)

BACKGROUND

The tribe Ampelopsideae plants are important garden plants with both medicinal and ornamental values. The study of codon usage bias (CUB) facilitates a deeper comprehension of the molecular genetic evolution of species and their adaptive strategies. The joint analysis of CUB in chloroplast genomes (cpDNA) offers valuable insights for in-depth research on molecular genetic evolution, biological resource conservation, and elite breeding within this plant family.

RESULTS

The base composition and codon usage preferences of the eighteen chloroplast genomes were highly similar, with the GC content of bases at all positions of their codons being less than 50%. This indicates that they preferred A/T bases. Their effective codon numbers were all in the range of 35-61, which indicates that the codon preferences of the chloroplast genomes of the 18 Ampelopsideae plants were relatively weak. A series of analyses indicated that the codon preference of the chloroplast genomes of the 18 Ampelopsideae plants was influenced by a combination of multiple factors, with natural selection being the primary influence. The clustering tree generated based on the relative usage of synonymous codons is consistent with some of the results obtained from the phylogenetic tree of chloroplast genomes, which indicates that the clustering tree based on the relative usage of synonymous codons can be an important supplement to the results of the sequence-based phylogenetic analysis. Eventually, 10 shared best codons were screened on the basis of the chloroplast genomes of 18 species.

CONCLUSION

The codon preferences of the chloroplast genome in Ampelopsideae plants are relatively weak and are primarily influenced by natural selection. The codon composition of the chloroplast genomes of the eighteen Ampelopsideae plants and their usage preferences were sufficiently similar to demonstrate that the chloroplast genomes of Ampelopsideae plants are highly conserved. This study provides a scientific basis for the genetic evolution of chloroplast genes in Ampelopsideae species and their suitable strategies.

Comparative analysis of mitochondrial genomes in Ceratocystis fimbriata complex across diverse hosts

The decline ofAcacia mangiumWilld. in Malaysia, especially in Sabah since 2010, is primarily due to Ceratocystiswilt and canker disease (CWCD) caused by theCeratocystis fimbriataEllis & Halst. complex. This study was aimed to investigate the mitochondrial genome architecture of two differentC. fimbriatacomplex isolates from Malaysia: one fromA. mangiumin Pahang (FRIM1162) and another fromEucalyptus pellitain Sarawak (FRIM1441). This research employed Next-Generation Sequencing (NGS) to contrast genomes from diverse hosts with nine additional mitochondrial sequences, identifying significant genetic diversity and mutational hotspots in the mitochondrial genome alignment. The mitochondrial genome-based phylogenetic analysis revealed a significant genetic relationship between the studied isolates and theC. fimbriatacomplex in the South American Subclade, indicating that theC. fimbriatacomplex discovered in Malaysia isC. manginecans. The comparative mitochondrial genome demonstrates the adaptability of the complex due to mobile genetic components and genomic rearrangements in the studiedfungal isolates. This research enhances our knowledge of the genetic diversity and evolutionary patterns within theC. fimbriatacomplex, aiding in a deeper understanding of fungal disease development and host adaption processes. The acquired insights are crucial for creating specific management strategies for CWCD, improving the overall understanding of fungal disease evolution and control.

Association between ACE (rs4343 and rs1799752), AGTR1 (rs5186), and PAI-1 (rs2227631) polymorphisms in the host and the severity of Covid-19 infection

OBJECTIVE

It is necessary to identify appropriate clinical, biochemical, epidemiological and genetic biomarkers to elucidate the underlying mechanisms of the coronavirus disease-2019 (COVID-19) disease. The study focused on not only the link between disease severity (non-intense unit care (non-ICU) versus intensive unit care (ICU) and genetic susceptibility in COVID-19 patients but also the connection between comorbidity and genetic susceptibility affecting the severity of COVID-19.

SUBJECT AND METHODS

One hundred and sixty-two COVID-19 patients treated in the non-ICU and ICU in Kayseri City Hospital were included. All volunteers underwent a physical examination and biochemical evaluation. Angiotensin-converting enzyme (ACE p.T776T G > A(rs4343) and g.16471_16472delinsALU (also referred to as I/D polymorphism; rs1799752), angiotensin II receptor type-1 (AGTR1) c.*86A > C (also referred to as A1166C; rs5186), and plasminogen activator inhibitor-1 (PAI-1-844 G > A (rs2227631) polymorphisms were analysed as well.

RESULTS

To have ACE "ID" genotype did not change the severity of the disease (OR: 0.92, 95% CI: 0.41-2.1, p = 0.84), but decreased the mortality risk 2.9-fold (OR: 2.9, 95% CI: 1.1-7.0, p = 0.03). In PAI-1-844 G > A, having the "AA" genotype in the "A" recessive model increased the risk of the diabetes mellitus (DM) 2.3-fold (OR: 2.3 95%, CI: 1.16-4.66, p = 0.018). In the "G" recessive model, to have the GG genotype increased the risk of chronic kidney disease (CKD) 4.8-fold (OR:4.8, 95% CI: 1.5-15.5, p = 0.008). "GG" genotype in the DM group had a higher fibrinogen level compared to those with the "AG" genotype (AG:4847.2 mg/L (1704.3) versus GG:6444.67 mg/L (1861.62) p = 0.019) and "AA" genotype in the CKD group had lower platelet levels and those with "GG" had higher platelet levels (AA:149 µL (18-159) versus GG: 228 µL (146-357) p = 0.022).

CONCLUSION

This study was shown that genetic predispositions that causes comorbidities were also likely to affect the prognosis of COVID-19.

Analysis of Codon Usage Bias in Chloroplast Genomes of Dryas octopetala var. asiatica (Rosaceae)

Dryas octopetala var. asiatica, a dwarf shrub belonging to the Rosaceae family and native to Asia, exhibits notable plasticity in photosynthesis in response to temperature variations. However, the codon usage patterns and factors influencing them in the chloroplast genome of this species have not yet been documented. This study sequenced and assembled the complete genome of D. octopetala var. asiatica. The annotated genes in the chloroplast genome were analyzed for codon composition through multivariate statistical methods including a neutrality plot, a parity rule 2 (PR2) bias plot, and an effective number of codons (ENC) plot using CodonW 1.4.2 software. The results indicated that the mean GC content of 53 CDSs was 38.08%, with the average GC content at the third codon base position being 27.80%, suggesting a preference for A/U(T) at the third codon position in chloroplast genes. Additionally, the chloroplast genes exhibited a weak overall codon usage bias (CUB) based on ENC values and other indicators. Correlation analysis showed a significant negative correlation between ENC value and GC2, an extremely positive correlation with GC3, but no correlation with GC1 content. These findings highlight the importance of the codon composition at the third position in influencing codon usage bias. Furthermore, our analysis indicated that the CUB of the chloroplast genome of D. octopetala var. asiatica was primarily influenced by natural selection and other factors. Finally, this study identified UCA, CCU, GCU, AAU, GAU, and GGU as the optimal codons. These results offer a foundational understanding for genetic modification and evolutionary dynamics of the chloroplast genome of D. octopetala var. asiatica.

Repetitive Sequences, Codon Usage Bias and Phylogenetic Analysis of the Plastome of Miliusa glochidioides

Annonaceae is the largest family in Magnoliales, exhibiting the greatest diversity among and within genera. In this study, we conducted an analysis of repetitive sequences and codon usage bias in the previously acquired plastome of Miliusa glochidioides. Using a concatenated dataset of shared genes, we constructed the phylogenetic relationships among 27 Annonaceae species. The results showed that the size of the plastomes in the Annonaceae ranged from 159 to 202 kb, with the size of the inverted repeat region ranging from 40 to 65 kb. Within the plastome of M. glochidioides, we identified 42 SSRs, 36 tandem repeats, and 9 dispersed repeats. These SSRs consist of three nucleotide types and eight motif types, with a preference for A/T bases, primarily located in the large single-copy regions and intergenic spacers. Tandem and dispersed repeat sequences were predominantly detected in the IR region. Through codon usage bias analysis, we identified 30 high-frequency codons and 11 optimal codons. The plastome of M. glochidioides demonstrated relatively weak codon usage bias, favoring codons with A/T endings, primarily influenced by natural selection. Phylogenetic analysis revealed that all four subfamilies formed monophyletic groups, with Cananga odorata (Ambavioideae) and Anaxagorea javanica (Anaxagoreoideae) successively nested outside Annonoideae + Malmeoideae. These findings improve our understanding of the plastome of M. glochidioides and provide additional insights for studying plastome evolution in Annonaceae.

tRNA Modifications and Dysregulation: Implications for Brain Diseases

Transfer RNAs (tRNAs) are well-known for their essential function in protein synthesis. Recent research has revealed a diverse range of chemical modifications that tRNAs undergo, which are crucial for various cellular processes. These modifications are necessary for the precise and efficient translation of proteins and also play important roles in gene expression regulation and cellular stress response. This review examines the role of tRNA modifications and dysregulation in the pathophysiology of various brain diseases, including epilepsy, stroke, neurodevelopmental disorders, brain tumors, Alzheimer's disease, and Parkinson's disease. Through a comprehensive analysis of existing research, our study aims to elucidate the intricate relationship between tRNA dysregulation and brain diseases. This underscores the critical need for ongoing exploration in this field and provides valuable insights that could facilitate the development of innovative diagnostic tools and therapeutic approaches, ultimately improving outcomes for individuals grappling with complex neurological conditions.

Synthetic genomes unveil the effects of synonymous recoding

Engineering the genetic code of an organism provides the basis for (i) making any organism safely resistant to natural viruses and (ii) preventing genetic information flow into and out of genetically modified organisms while (iii) allowing the biosynthesis of genetically encoded unnatural polymers1-4. Achieving these three goals requires the reassignment of multiple of the 64 codons nature uses to encode proteins. However, synonymous codon replacement-recoding-is frequently lethal, and how recoding impacts fitness remains poorly explored. Here, we explore these effects using whole-genome synthesis, multiplexed directed evolution, and genome-transcriptome-translatome-proteome co-profiling on multiple recoded genomes. Using this information, we assemble a synthetic Escherichia coli genome in seven sections using only 57 codons to encode proteins. By discovering the rules responsible for the lethality of synonymous recoding and developing a data-driven multi-omics-based genome construction workflow that troubleshoots synthetic genomes, we overcome the lethal effects of 62,007 synonymous codon swaps and 11,108 additional genomic edits. We show that synonymous recoding induces transcriptional noise including new antisense RNAs, leading to drastic transcriptome and proteome perturbation. As the elimination of select codons from an organism's genetic code results in the widespread appearance of cryptic promoters, we show that synonymous codon choice may naturally evolve to minimize transcriptional noise. Our work provides the first genome-scale description of how synonymous codon changes influence organismal fitness and paves the way for the construction of functional genomes that provide genetic firewalls from natural ecosystems and safely produce biopolymers, drugs, and enzymes with an expanded chemistry.

Comparative and phylogenetic analysis of the complete chloroplast genomes of 10 Artemisia selengensis resources based on high-throughput sequencing

BACKGROUND

Artemisia selengensis, classified within the genus Artemisia of the Asteraceae family, is a perennial herb recognized for its dual utility in culinary and medicinal domains. There are few studies on the chloroplast genome of A. selengensis, and the phylogeographic classification is vague, which makes phylogenetic analysis and evolutionary studies very difficult.

RESULTS

The chloroplast genomes of 10 A. selengensis in this study were highly conserved in terms of gene content, gene order, and gene intron number. The genome lengths ranged from 151,148 to 151,257 bp and were typical of a quadripartite structure with a total GC content of approximately 37.5%. The chloroplast genomes of all species encode 133 genes, including 88 protein-coding genes, 37 tRNA genes, and 8 rRNA genes. Due to the contraction and expansion of the inverted repeats (IR), the overlap of ycf1 and ndhF genes occurred at the inverted repeats B (IRB) and short single copy sequence (SSC) boundaries. According to a codon use study, the frequent base in the chloroplast genome of A. selengensis' third codon position was A/T. The number of SSR repeats was 42-44, most of which were single nucleotide A/T repeats. Sequence alignment analysis of the chloroplast genome showed that variable regions were mainly distributed in single copy regions, nucleotide diversity values of 0 to 0.009 were calculated by sliding window analysis, 8 mutation hotspot regions were detected, and coding regions were more conserved than non-coding regions. Analysis of non-synonymous substitution (Ka) and synonymous substitution (Ks) revealed that accD, rps12, petB, and atpF genes were affected by positive selection and no genes were affected by neutral selection. Based on the findings of the phylogenetic analysis, Artemisia selengensis was sister to the genus Artemisia Chrysanthemum and formed a monophyletic group with other Artemisia genera.

CONCLUSIONS

In this research, the present study systematically compared the chloroplast genomic features of A. selengensis and provided important information for the study of the chloroplast genome of A. selengensis and the evolutionary relationships among Asteraceae species.