Codon and Codon-Pair Usage Tables (CoCoPUTs): Facilitating Genetic Variation Analyses and Recombinant Gene Design

Mouse embryo CoCoPUTs: novel murine transcriptomic-weighted usage website featuring multiple strains, tissues, and stages

Mouse (Mus musculus) models have been heavily utilized in developmental biology research to understand mammalian embryonic development, as mice share many genetic, physiological, and developmental characteristics with humans. New explorations into the integration of temporal (stage-specific) and transcriptional (tissue-specific) data have expanded our knowledge of mouse embryo tissue-specific gene functions. To better understand the substantial impact of synonymous mutational variations in the cell-state-specific transcriptome on a tissue's codon and codon pair usage landscape, we have established a novel resource-Mouse Embryo Codon and Codon Pair Usage Tables (Mouse Embryo CoCoPUTs). This webpage not only offers codon and codon pair usage, but also GC, dinucleotide, and junction dinucleotide usage, encompassing four strains, 15 murine embryonic tissue groups, 18 Theiler stages, and 26 embryonic days. Here, we leverage Mouse Embryo CoCoPUTs and employ the use of heatmaps to depict usage changes over time and a comparison to human usage for each strain and embryonic time point, highlighting unique differences and similarities. The usage similarities found between mouse and human central nervous system data highlight the translation for projects leveraging mouse models. Data for this analysis can be directly retrieved from Mouse Embryo CoCoPUTs. This cutting-edge resource plays a crucial role in deciphering the complex interplay between usage patterns and embryonic development, offering valuable insights into variation across diverse tissues, strains, and stages. Its applications extend across multiple domains, with notable advantages for biotherapeutic development, where optimizing codon usage can enhance protein expression; one can compare strains, tissues, and mouse embryonic stages in one query. Additionally, Mouse Embryo CoCoPUTs holds great potential in the field of tissue-specific genetic engineering, providing insights for tailoring gene expression to specific tissues for targeted interventions. Furthermore, this resource may enhance our understanding of the nuanced connections between usage biases and tissue-specific gene function, contributing to the development of more accurate predictive models for genetic disorders.

Genome-scale quantification and prediction of pathogenic stop codon readthrough by small molecules

Premature termination codons (PTCs) cause ~10-20% of inherited diseases and are a major mechanism of tumor suppressor gene inactivation in cancer. A general strategy to alleviate the effects of PTCs would be to promote translational readthrough. Nonsense suppression by small molecules has proven effective in diverse disease models, but translation into the clinic is hampered by ineffective readthrough of many PTCs. Here we directly tackle the challenge of defining drug efficacy by quantifying the readthrough of ~5,800 human pathogenic stop codons by eight drugs. We find that different drugs promote the readthrough of complementary subsets of PTCs defined by local sequence context. This allows us to build interpretable models that accurately predict drug-induced readthrough genome-wide, and we validate these models by quantifying endogenous stop codon readthrough. Accurate readthrough quantification and prediction will empower clinical trial design and the development of personalized nonsense suppression therapies.

A conserved opal termination codon optimizes a temperature-dependent tradeoff between protein production and processing in alphaviruses

Alphaviruses are enveloped, single-stranded, positive-sense RNA viruses that often require transmission between arthropod and vertebrate hosts for their sustained propagation. Most alphaviruses encode an opal (UGA) termination codon in nonstructural protein 3 (nsP3) upstream of the viral polymerase, nsP4. The selective constraints underlying the conservation of the opal codon are poorly understood. Using primate and mosquito cells, we explored the role and selective pressure on the nsP3 opal codon through extensive mutational analysis in the prototype alphavirus, Sindbis virus (SINV). We found that the opal codon is highly favored over all other codons in primate cells under native 37°C growth conditions. However, this preference is diminished in mosquito and primate cells grown at a lower temperature. Thus, the primary determinant driving the selection of the opal stop codon is not host genetics but the passaging temperature. We show that the opal codon is preferred over amber and ochre termination codons because it results in the highest translational readthrough and polymerase production. However, substituting the opal codon with sense codons leads to excessive full-length polyprotein (P1234) production, which disrupts optimal nsP polyprotein processing, delays the switch from minus-strand to positive-strand RNA production, and significantly reduces SINV fitness at 37°C; this fitness defect is relieved at lower temperatures. A naturally occurring suppressor mutation unexpectedly compensates for a delayed transition from minus to genomic RNA production by also delaying the subsequent transition between genomic and sub-genomic RNA production. Our study reveals that the opal stop codon is the best solution for alphavirus replication at 37°C, producing enough nsP4 protein to maximize replication without disrupting nsP processing and RNA replication transitions needed for optimal fitness. Our study uncovers the intricate strategy dual-host alphaviruses use at a single codon to optimize fitness.

Variation in the Spectrum of New Mutations among Inbred Strains of Mice

The mouse serves as a mammalian model for understanding the nature of variation from new mutations, a question that has both evolutionary and medical significance. Previous studies suggest that the rate of single-nucleotide mutations (SNMs) in mice is ∼50% of that in humans. However, information largely comes from studies involving the C57BL/6 strain, and there is little information from other mouse strains. Here, we study the mutations that accumulated in 59 mouse lines derived from four inbred strains that are commonly used in genetics and clinical research (BALB/cAnNRj, C57BL/6JRj, C3H/HeNRj, and FVB/NRj), maintained for eight to nine generations by brother-sister mating. By analyzing Illumina whole-genome sequencing data, we estimate that the average rate of new SNMs in mice is ∼μ = 6.7 × 10-9. However, there is substantial variation in the spectrum of SNMs among strains, so the burden from new mutations also varies among strains. For example, the FVB strain has a spectrum that is markedly skewed toward C→A transversions and is likely to experience a higher deleterious load than other strains, due to an increased frequency of nonsense mutations in glutamic acid codons. Finally, we observe substantial variation in the rate of new SNMs among DNA sequence contexts, CpG sites, and their adjacent nucleotides playing an important role.

Wheat NAC transcription factor NAC5-1 is a positive regulator of senescence

Wheat (Triticum aestivum L.) is an important source of both calories and protein in global diets, but there is a trade-off between grain yield and protein content. The timing of leaf senescence could mediate this trade-off as it is associated with both declines in photosynthesis and nitrogen remobilization from leaves to grain. NAC transcription factors play key roles in regulating senescence timing. In rice, OsNAC5 expression is correlated with increased protein content and upregulated in senescing leaves, but the role of the wheat ortholog in senescence had not been characterized. We verified that NAC5-1 is the ortholog of OsNAC5 and that it is expressed in senescing flag leaves in wheat. To characterize NAC5-1, we combined missense mutations in NAC5-A1 and NAC5-B1 from a TILLING mutant population and overexpressed NAC5-A1 in wheat. Mutation in NAC5-1 was associated with delayed onset of flag leaf senescence, while overexpression of NAC5-A1 was associated with slightly earlier onset of leaf senescence. DAP-seq was performed to locate transcription factor binding sites of NAC5-1. Analysis of DAP-seq and comparison with other studies identified putative downstream target genes of NAC5-1 which could be associated with senescence. This work showed that NAC5-1 is a positive transcriptional regulator of leaf senescence in wheat. Further research is needed to test the effect of NAC5-1 on yield and protein content in field trials, to assess the potential to exploit this senescence regulator to develop high-yielding wheat while maintaining grain protein content.

GENTANGLE: integrated computational design of gene entanglements

SUMMARY

The design of two overlapping genes in a microbial genome is an emerging technique for adding more reliable control mechanisms in engineered organisms for increased stability. The design of functional overlapping gene pairs is a challenging procedure, and computational design tools are used to improve the efficiency to deploy successful designs in genetically engineered systems. GENTANGLE (Gene Tuples ArraNGed in overLapping Elements) is a high-performance containerized pipeline for the computational design of two overlapping genes translated in different reading frames of the genome. This new software package can be used to design and test gene entanglements for microbial engineering projects using arbitrary sets of user-specified gene pairs.

AVAILABILITY AND IMPLEMENTATION

The GENTANGLE source code and its submodules are freely available on GitHub at https://github.com/BiosecSFA/gentangle. The DATANGLE (DATA for genTANGLE) repository contains related data and results and is freely available on GitHub at https://github.com/BiosecSFA/datangle. The GENTANGLE container is freely available on Singularity Cloud Library at https://cloud.sylabs.io/library/khyox/gentangle/gentangle.sif. The GENTANGLE repository wiki (https://github.com/BiosecSFA/gentangle/wiki), website (https://biosecsfa.github.io/gentangle/), and user manual contain detailed instructions on how to use the different components of software and data, including examples and reproducing the results. The code is licensed under the GNU Affero General Public License version 3 (https://www.gnu.org/licenses/agpl.html).

Fish antifreeze protein origin in sculpins by frameshifting within a duplicated housekeeping gene

Antifreeze proteins (AFPs) are found in a variety of marine cold-water fishes where they prevent freezing by binding to nascent ice crystals. Their diversity (types I, II, III and antifreeze glycoproteins), as well as their scattered taxonomic distribution hint at their complex evolutionary history. In particular, type I AFPs appear to have arisen in response to the Late Cenozoic Ice Age that began ~ 34 million years ago via convergence in four different groups of fish that diverged from lineages lacking this AFP. The progenitor of the alanine-rich α-helical type I AFPs of sculpins has now been identified as lunapark, an integral membrane protein of the endoplasmic reticulum. Following gene duplication and loss of all but three of the 15 exons, the final exon, which encoded a glutamate- and glutamine-rich segment, was converted to an alanine-rich sequence by a combination of frameshifting and mutation. Subsequent gene duplications produced numerous isoforms falling into four distinct groups. The origin of the flounder type I AFP is quite different. Here, a small segment from the original antiviral protein gene was amplified and the rest of the coding sequence was lost, while the gene structure was largely retained. The independent origins of type I AFPs with up to 83% sequence identity in flounder and sculpin demonstrate strong convergent selection at the level of protein sequence for alanine-rich single alpha helices that bind to ice. Recent acquisition of these AFPs has allowed sculpins to occupy icy seawater niches with reduced competition and predation from other teleost species.

Genetic background of adaptation of Crimean-Congo haemorrhagic fever virus to the different tick hosts

Crimean-Congo haemorrhagic fever orthonairovirus (CCHFV) is a negative-sense, single-stranded RNA virus with a segmented genome and the causative agent of a severe Crimean-Congo haemorrhagic fever (CCHF) disease. The virus is transmitted mainly by tick species in Hyalomma genus but other ticks such as representatives of genera Dermacentor and Rhipicephalus may also be involved in virus life cycle. To improve our understanding of CCHFV adaptation to its tick species, we compared nucleotide composition and codon usage patterns among the all CCHFV strains i) which sequences and other metadata as locality of collection and date of isolation are available in GenBank and ii) which were isolated from in-field collected tick species. These criteria fulfilled 70 sequences (24 coding for S, 23 for M, and 23 for L segment) of virus isolates originating from different representatives of Hyalomma and Rhipicephalus genera. Phylogenetic analyses confirmed that Hyalomma- and Rhipicephalus-originating CCHFV isolates belong to phylogenetically distinct CCHFV clades. Analyses of nucleotide composition among the Hyalomma- and Rhipicephalus-originating CCHFV isolates also showed significant differences, mainly in nucleotides located at the 3rd codon positions indicating changes in codon usage among these lineages. Analyses of codon adaptation index (CAI), effective number of codons (ENC), and other codon usage statistics revealed significant differences between Hyalomma- and Rhipicephalus-isolated CCHFV strains. Despite both sets of strains displayed a higher adaptation to use codons that are preferred by Hyalomma ticks than Rhipicephalus ticks, there were distinct codon usage preferences observed between the two tick species. These findings suggest that over the course of its long co-evolution with tick vectors, CCHFV has optimized its codon usage to efficiently utilize translational resources of Hyalomma species.

Quantifying negative selection on synonymous variants

Widespread adoption of DNA sequencing has resulted in large numbers of genetic variants, whose contribution to disease is not easily determined. Although many types of variation are known to disrupt cellular processes in predictable ways, for some categories of variants, the effects may not be directly detectable. A particular example is synonymous variants, that is, those single-nucleotide variants that create a codon substitution, such that the produced amino acid sequence is unaffected. Contrary to the original theory suggesting that synonymous variants are benign, there is a growing volume of research showing that, despite their "silent" mechanism of action, some synonymous variation may be deleterious. Here, we studied the extent of the negative selective pressure acting on different classes of synonymous variants by analyzing the relative enrichment of synonymous singleton variants in the human exomes provided by gnomAD. Using a modification of the mutability-adjusted proportion of singletons (MAPS) metric as a measure of purifying selection, we found that some classes of synonymous variants are subject to stronger negative selection than others. For instance, variants that reduce codon optimality undergo stronger selection than optimality-increasing variants. Besides, selection affects synonymous variants implicated in splice-site-loss or splice-site-gain events. To understand what drives this negative selection, we tested a number of predictors in the aim to explain the variability in the selection scores. Our findings provide insights into the effects of synonymous variants at the population level, highlighting the specifics of the role that these variants play in health and disease.

Comprehensive Genomics Investigation of Neboviruses Reveals Distinct Codon Usage Patterns and Host Specificity

Neboviruses (NeVs) from the Caliciviridae family have been linked to enteric diseases in bovines and have been detected worldwide. As viruses rely entirely on the cellular machinery of the host for replication, their ability to thrive in a specific host is greatly impacted by the specific codon usage preferences. Here, we systematically analyzed the codon usage bias in NeVs to explore the genetic and evolutionary patterns. Relative Synonymous Codon Usage and Effective Number of Codon analyses indicated a marginally lower codon usage bias in NeVs, predominantly influenced by the nucleotide compositional constraints. Nonetheless, NeVs showed a higher codon usage bias for codons containing G/C at the third codon position. The neutrality plot analysis revealed natural selection as the primary factor that shaped the codon usage bias in both the VP1 (82%) and VP2 (57%) genes of NeVs. Furthermore, the NeVs showed a highly comparable codon usage pattern to bovines, as reflected through Codon Adaptation Index and Relative Codon Deoptimization Index analyses. Notably, yak NeVs showed considerably different nucleotide compositional constraints and mutational pressure compared to bovine NeVs, which appear to be predominantly host-driven. This study sheds light on the genetic mechanism driving NeVs' adaptability, evolution, and fitness to their host species.

Codon-optimization in gene therapy: promises, prospects and challenges

Codon optimization has evolved to enhance protein expression efficiency by exploiting the genetic code's redundancy, allowing for multiple codon options for a single amino acid. Initially observed in E. coli, optimal codon usage correlates with high gene expression, which has propelled applications expanding from basic research to biopharmaceuticals and vaccine development. The method is especially valuable for adjusting immune responses in gene therapies and has the potenial to create tissue-specific therapies. However, challenges persist, such as the risk of unintended effects on protein function and the complexity of evaluating optimization effectiveness. Despite these issues, codon optimization is crucial in advancing gene therapeutics. This study provides a comprehensive review of the current metrics for codon-optimization, and its practical usage in research and clinical applications, in the context of gene therapy.

Genomic Analyses of Major SARS-CoV-2 Variants Predicting Multiple Regions of Pathogenic and Transmissive Importance

The rapid evolution of SARS-CoV-2 has fueled its global proliferation since its discovery in 2019, with several notable variants having been responsible for increases in cases of coronavirus disease 2019 (COVID-19). Analyses of codon bias and usage in these variants between phylogenetic clades or lineages may grant insights into the evolution of SARS-CoV-2 and identify target codons indicative of evolutionary or mutative trends that may prove useful in tracking or defending oneself against emerging strains. We processed a cohort of 120 SARS-CoV-2 genome sequences through a statistical and bioinformatic pipeline to identify codons presenting evidence of selective pressure as well as codon coevolution. We report the identification of two codon sites in the orf8 and N genes demonstrating such evidence with real-world impacts on pathogenicity and transmissivity.

Metabolic modeling predicts unique drug targets in Borrelia burgdorferi

IMPORTANCE

Lyme disease is often treated using long courses of antibiotics, which can cause side effects for patients and risks the evolution of antimicrobial resistance. Narrow-spectrum antimicrobials would reduce these risks, but their development has been slow because the Lyme disease bacterium, Borrelia burgdorferi, is difficult to work with in the laboratory. To accelerate the drug discovery pipeline, we developed a computational model of B. burgdorferi's metabolism and used it to predict essential enzymatic reactions whose inhibition prevented growth in silico. These predictions were validated using small-molecule enzyme inhibitors, several of which were shown to have specific activity against B. burgdorferi. Although the specific compounds used are not suitable for clinical use, we aim to use them as lead compounds to develop optimized drugs targeting the pathways discovered here.

r/K selection of GC content in prokaryotes

The guanine/cytosine (GC) content of prokaryotic genomes is species-specific, taking values from 16% to 77%. This diversity of selection for GC content remains contentious. We analyse the correlations between GC content and a range of phenotypic and genotypic data in thousands of prokaryotes. GC content integrates well with these traits into r/K selection theory when phenotypic plasticity is considered. High GC-content prokaryotes are r-strategists with cheaper descendants thanks to a lower average amino acid metabolic cost, colonize unstable environments thanks to flagella and a bacillus form and are generalists in terms of resource opportunism and their defence mechanisms. Low GC content prokaryotes are K-strategists specialized for stable environments that maintain homeostasis via a high-cost outer cell membrane and endospore formation as a response to nutrient deprivation, and attain a higher nutrient-to-biomass yield. The lower proteome cost of high GC content prokaryotes is driven by the association between GC-rich codons and cheaper amino acids in the genetic code, while the correlation between GC content and genome size may be partly due to functional diversity driven by r/K selection. In all, molecular diversity in the GC content of prokaryotes may be a consequence of ecological r/K selection.

Proteostasis regulation through ribosome quality control and no-go-decay

Cell functionality relies on the existing pool of proteins and their folding into functional conformations. This is achieved through the regulation of protein synthesis, which requires error-free mRNAs and ribosomes. Ribosomes are quality control hubs for mRNAs and proteins. Problems during translation elongation slow down the decoding rate, leading to ribosome halting and the eventual collision with the next ribosome. Collided ribosomes form a specific disome structure recognized and solved by ribosome quality control (RQC) mechanisms. RQC pathways orchestrate the degradation of the problematic mRNA by no-go decay and the truncated nascent peptide, the repression of translation initiation, and the recycling of the stalled ribosomes. All these events maintain protein homeostasis and return valuable ribosomes to translation. As such, cell homeostasis and function are maintained at the mRNA level by preventing the production of aberrant or unnecessary proteins. It is becoming evident that the crosstalk between RQC and the protein homeostasis network is vital for cell function, as the absence of RQC components leads to the activation of stress response and neurodegenerative diseases. Here, we review the molecular events of RQC discovered through well-designed stalling reporters. Given the impact of RQC in proteostasis, we discuss the relevance of identifying endogenous mRNA regulated by RQC and their preservation in stress conditions. This article is categorized under: RNA Turnover and Surveillance > Turnover/Surveillance Mechanisms Translation > Regulation.

Non-adaptive evolution in codon usage of human-origin monkeypox virus

Monkeypox virus (Mpox) is a zoonotic infectious disease that threatens human and animal health, with a global outbreak of the low-pathogenic Mpox beginning from 2022. In this study, we analyzed the codon usage of Mpox between two clades, Clade-I and Clade-IIb-B, to understand changes in host adaptation. Clade-IIb-B of the Mpox genome underwent non-adaptive evolution making it less adapted to its host than Clade-I. The analysis of individual genes revealed that 48 genes exhibited non-adaptive mutation, while 38 genes underwent adaptive mutations. Genes involved in replication, transcription, and host-modulation exhibited a mix of adaptive and non-adaptive evolutionary patterns. This study also found that the mutations of Mpox led to changes in non-adaptative genes in different organs. Additionally, we found that codon usage of Mpox was less similar to that of up-regulated host genes and more similar to that of down-regulated host genes post-infection, indicating that codon usage affects host gene expression. Overall, the study highlights the non-adaptive changes in codon usage as a potential cause of differences in Mpox virulence and provides insights into the evolutionary and adaptive mechanisms of Mpox and its potential impact on pathogenicity and host adaptation.

Streamlined assembly of cloning and genome editing vectors for genus Clostridium

Reported herein is a new set of vectors designed to streamline molecular cloning and genome editing by exploiting modern cloning methods. The new vectors build on the existing pMTL8000 vectors that have been a staple of Clostridium research for more than a decade. The introduction of two pairs of type IIS restriction sites flanking an insulated multiple cloning site in both a cloning vector and a CRISPR-Cas9 gene editing vector enables plasmid construction in a "one-pot" reaction, avoiding the more laborious steps of conventional cloning. A synthetic lacZα expression cassette introduced between the cloning sites enables visual detection of background colonies. In addition, distinct selection markers on each vector permit selection of the desired clones according to antibiotic resistance. An example of strain development using the new vectors is demonstrated.

Phylogenetic Analysis and Codon Usage Bias Reveal the Base of Feline and Canine Chaphamaparvovirus for Cross-Species Transmission

Chaphamaparvoviruses (ChPVs) are ancient viruses that have been detected in a variety of hosts. In this study, through a phylogenetic analysis and the adaptability of ChPV to multiple hosts, we evaluated the basis for the ability of feline (FeChPV) and canine ChPV (CaChPV) for cross-species transmission. Phylogenetic analysis showed that FeChPV and CaChPV were closely related. Notably, two strains of ChPVs isolated from domestic cats and two from dogs clustered together with CaChPVs and FeChPVs, respectively, suggesting that the stringent boundaries between canine and feline ChPV may be broken. Further analysis revealed that CaChPV and FeChPV were more adapted to dogs than to cats. Mutation analysis identified several shared mutations in cross-species-transmissible strains. Furthermore, the VP structures of FeChPV and CaChPV exhibited a high degree of similarity across both cross-species-transmissible and non-cross-species-transmissible strains. However, it is crucial to note that these results are largely computational, and limitations exist in terms of the number and diversity of samples analyzed; the capacity for cross-species transmission should be approached with caution and elucidated in further studies.

Insights into the Evolution and Host Adaptation of the Monkeypox Virus from a Codon Usage Perspective: Focus on the Ongoing 2022 Outbreak

The exceptionally widespread outbreak of human monkeypox, an emerging zoonosis caused by the monkeypox virus (MPXV), with more than 69,000 confirmed cases in 100 non-endemic countries since 2022, is a major public health concern. Codon usage patterns reflect genetic variation and adaptation to new hosts and ecological niches. However, detailed analyses of codon usage bias in MPXV based on large-scale genomic data, especially for strains responsible for the 2022 outbreak, are lacking. In this study, we analyzed codon usage in MPXV and its relationship with host adaptation. We confirmed the ongoing outbreak of MPXVs belonging to the West Africa (WA) lineage by principal component analysis based on their codon usage patterns. The 2022 outbreak strains had a relatively low codon usage bias. Codon usage of MPXVs was shaped by mutation and natural selection; however, different from past strains, codon usage in the 2022 outbreak strains was predominantly determined by mutation pressure. Additionally, as revealed by the codon adaptation index (CAI), relative codon deoptimization index (RCDI), and similarity index (SiD) analyses, the codon usage patterns of MPXVs were also affected by their hosts. In particular, the 2022 outbreak strains showed slightly but significantly greater adaptation to many primates, including humans, and were subjected to stronger selection pressure induced by hosts. Our results suggest that MPXVs contributing to the 2022 outbreak have unique evolutionary features, emphasizing the importance of sustained monitoring of their transmission and evolution.

Deoptimization of FMDV P1 Region Results in Robust Serotype-Independent Viral Attenuation

Foot-and-mouth disease (FMD), caused by the FMD virus (FMDV), is a highly contagious disease of cloven-hoofed livestock that can have severe economic impacts. Control and prevention strategies, including the development of improved vaccines, are urgently needed to effectively control FMD outbreaks in endemic settings. Previously, we employed two distinct strategies (codon pair bias deoptimization (CPD) and codon bias deoptimization (CD)) to deoptimize various regions of the FMDV serotype A subtype A12 genome, which resulted in the development of an attenuated virus in vitro and in vivo, inducing varying levels of humoral responses. In the current study, we examined the versatility of the system by using CPD applied to the P1 capsid coding region of FMDV serotype A subtype, A24, and another serotype, Asia1. Viruses carrying recoded P1 (A24-P1Deopt or Asia1-P1Deopt) exhibited different degrees of attenuation (i.e., delayed viral growth kinetics and replication) in cultured cells. Studies in vivo using a mouse model of FMD demonstrated that inoculation with the A24-P1Deopt and Asia1-P1Deopt strains elicited a strong humoral immune response capable of offering protection against challenge with homologous wildtype (WT) viruses. However, different results were obtained in pigs. While clear attenuation was detected for both the A24-P1Deopt and Asia1-P1Deopt strains, only a limited induction of adaptive immunity and protection against challenge was detected, depending on the inoculated dose and serotype deoptimized. Our work demonstrates that while CPD of the P1 coding region attenuates viral strains of multiple FMDV serotypes/subtypes, a thorough assessment of virulence and induction of adaptive immunity in the natural host is required in each case in order to finely adjust the degree of deoptimization required for attenuation without affecting the induction of protective adaptive immune responses.

Dicodon-based measures for modeling gene expression

MOTIVATION

Codon usage preference patterns have been associated with modulation of translation efficiency, protein folding, and mRNA decay. However, new studies support that codon pair usage has also a remarkable effect at the gene expression level. Here, we expand the concept of CAI to answer if codon pair usage patterns can be understood in terms of codon usage bias, or if they offer new information regarding coding translation efficiency.

RESULTS

Through the implementation of a weighting strategy to consider the dicodon contributions, we observe that the dicodon-based measure has greater correlations with gene expression level than CAI. Interestingly, we have noted that dicodons associated with a low value of adaptiveness are related to dicodons which mediate strong translational inhibition in yeast. We have also noticed that some codon-pairs have a smaller dicodon contribution than estimated by the product of the respective codon contributions.

AVAILABILITY AND IMPLEMENTATION

Scripts, implemented in Python, are freely available for download at https://zenodo.org/record/7738276#.ZBIDBtLMIdU.

In silico methods for predicting functional synonymous variants

Single nucleotide variants (SNVs) contribute to human genomic diversity. Synonymous SNVs are previously considered to be "silent," but mounting evidence has revealed that these variants can cause RNA and protein changes and are implicated in over 85 human diseases and cancers. Recent improvements in computational platforms have led to the development of numerous machine-learning tools, which can be used to advance synonymous SNV research. In this review, we discuss tools that should be used to investigate synonymous variants. We provide supportive examples from seminal studies that demonstrate how these tools have driven new discoveries of functional synonymous SNVs.

Genes enriched in A/T-ending codons are co-regulated and conserved across mammals

Codon usage influences gene expression distinctly depending on the cell context. Yet, the importance of codon bias in the simultaneous turnover of specific groups of protein-coding genes remains to be investigated. Here, we find that genes enriched in A/T-ending codons are expressed more coordinately in general and across tissues and development than those enriched in G/C-ending codons. tRNA abundance measurements indicate that this coordination is linked to the expression changes of tRNA isoacceptors reading A/T-ending codons. Genes with similar codon composition are more likely to be part of the same protein complex, especially for genes with A/T-ending codons. The codon preferences of genes with A/T-ending codons are conserved among mammals and other vertebrates. We suggest that this orchestration contributes to tissue-specific and ontogenetic-specific expression, which can facilitate, for instance, timely protein complex formation.

Using protein-per-mRNA differences among human tissues in codon optimization

BACKGROUND

Codon usage and nucleotide composition of coding sequences have profound effects on protein expression. However, while it is recognized that different tissues have distinct tRNA profiles and codon usages in their transcriptomes, the effect of tissue-specific codon optimality on protein synthesis remains elusive.

RESULTS

We leverage existing state-of-the-art transcriptomics and proteomics datasets from the GTEx project and the Human Protein Atlas to compute the protein-to-mRNA ratios of 36 human tissues. Using this as a proxy of translational efficiency, we build a machine learning model that identifies codons enriched or depleted in specific tissues. We detect two clusters of tissues with an opposite pattern of codon preferences. We then use these identified patterns for the development of CUSTOM, a codon optimizer algorithm which suggests a synonymous codon design in order to optimize protein production in a tissue-specific manner. In human cell-line models, we provide evidence that codon optimization should take into account particularities of the translational machinery of the tissues in which the target proteins are expressed and that our approach can design genes with tissue-optimized expression profiles.

CONCLUSIONS

We provide proof-of-concept evidence that codon preferences exist in tissue-specific protein synthesis and demonstrate its application to synthetic gene design. We show that CUSTOM can be of benefit in biological and biotechnological applications, such as in the design of tissue-targeted therapies and vaccines.

mRNA-Based Therapeutics in Cancer Treatment

Over the past two decades, significant technological innovations have led to messenger RNA (mRNA) becoming a promising option for developing prophylactic and therapeutic vaccines, protein replacement therapies, and genome engineering. The success of the two COVID-19 mRNA vaccines has sparked new enthusiasm for other medical applications, particularly in cancer treatment. In vitro-transcribed (IVT) mRNAs are structurally designed to resemble naturally occurring mature mRNA. Delivery of IVT mRNA via delivery platforms such as lipid nanoparticles allows host cells to produce many copies of encoded proteins, which can serve as antigens to stimulate immune responses or as additional beneficial proteins for supplements. mRNA-based cancer therapeutics include mRNA cancer vaccines, mRNA encoding cytokines, chimeric antigen receptors, tumor suppressors, and other combination therapies. To better understand the current development and research status of mRNA therapies for cancer treatment, this review focused on the molecular design, delivery systems, and clinical indications of mRNA therapies in cancer.

Implementing computational methods in tandem with synonymous gene recoding for therapeutic development

Synonymous gene recoding, the substitution of synonymous variants into the genetic sequence, has been used to overcome many production limitations in therapeutic development. However, the safety and efficacy of recoded therapeutics can be difficult to evaluate because synonymous codon substitutions can result in subtle, yet impactful changes in protein features and require sensitive methods for detection. Given that computational approaches have made significant leaps in recent years, we propose that machine-learning (ML) tools may be leveraged to assess gene-recoded therapeutics and foresee an opportunity to adapt codon contexts to enhance some powerful existing tools. Here, we examine how synonymous gene recoding has been used to address challenges in therapeutic development, explain the biological mechanisms underlying its effects, and explore the application of computational platforms to improve the surveillance of functional variants in therapeutic design.

A comprehensive analysis of Usutu virus (USUV) genomes revealed lineage-specific codon usage patterns and host adaptations

The Usutu virus (USUV) is an emerging arbovirus virus maintained in the environment of Afro-Eurasia via a bird-mosquito-bird enzootic cycle and sporadically infected other vertebrates. Despite primarily asymptomatic or mild symptoms, humans infected by USUV can develop severe neurological diseases such as meningoencephalitis. However, no detailed study has yet been conducted to investigate its evolution from the perspective of codon usage patterns. Codon usage choice of viruses reflects the genetic variations that enable them to reconcile their viability and fitness toward the external environment and new hosts. This study performed a comprehensive evolution and codon usage analysis of USUVs. Our reconstructed phylogenetic tree confirmed that the circulation viruses belong to eight distinct lineages, reaffirmed by principal component analysis based on codon usage patterns. We also found a relatively small codon usage bias and that natural selection, mutation pressure, dinucleotide abundance, and evolutionary processes collectively shaped the codon usage of the USUV, with natural selection predominating over the others. Additionally, a complex interaction of codon usage between the USUV and its host was observed. This process could have enabled USUV to adapt to various hosts and vectors, including humans. Therefore, the USUV may possess a potential risk of cross-species transmission and subsequent outbreaks. In this respect, further epidemiologic surveys, diversity monitoring, and pathogenetic research are warranted.

AIP gene germline variants in adult Polish patients with apparently sporadic pituitary macroadenomas

INTRODUCTION

Up to 5% of all pituitary tumors are hereditary e.g. due to MEN1 or aryl hydrocarbon receptor-interacting protein (AIP) genes mutations.

OBJECTIVES

The study was aimed at the assessment of the frequency and characteristics of AIP-mutation related tumors in patients with apparently sporadic pituitary macroadenomas in the Polish population.

MATERIALS AND METHODS

The study included 131 patients (57 males, 74 females; median age 42 years) diagnosed with pituitary macroadenomas, and with a negative family history of familial isolated pituitary adenoma (FIPA) or multiple endocrine neoplasia type 1 (MEN1) syndromes. Sanger sequencing was used for the assessment of AIP gene variants. The study was approved by the Ethics Board of JUMC.

RESULTS

AIP variants were identified in five of the 131 included subjects (3.8%): one diagnosed with Cushing's disease, two with acromegaly, and two with non-secreting adenomas. Patients harboring hereditary AIP gene alterations did not differ from the rest of the study group in median age at diagnosis (41.0 vs. 42.5 years, P=0.8), median largest tumor diameter (25 vs. 24 mm, P=0.6), gender distribution (60.0% vs. 56.3% females, P=0.8), secreting tumor frequency (60.0% vs. 67.5%, P=0.7), or acromegaly diagnosis frequency (40.0% vs.37.3%, P=0.9).

CONCLUSIONS

In our series of apparently sporadic pituitary macroadenomas, AIP gene variant carriers did not differ substantially from patients with negative genetic testing. A risk factor-centred approach to AIP genetic screening may result in missing germline variants. Considering the clinical impact of such genetic variants and their relatively low penetrance, it is, however, doubtful if general genetic screening benefits the whole cohort of pituitary macroadenoma patients and their families.

pXOOY: A dual-function vector for expression of membrane proteins in Saccharomyces cerevisiae and Xenopus laevis oocytes

On the quest for solving structures of membrane proteins by X-ray crystallography or cryo-EM, large quantities of ultra-pure protein are a paramount prerequisite. Obtaining enough protein of such high standard is not a trivial task, especially for difficult-to-express membrane proteins. Producing membrane protein for structural studies is often performed in Escherichia coli or Saccharomyces cerevisiae and is frequently complemented with functional studies. Ion channels and electrogenic receptors are traditionally studied in terms of their electrophysiological behavior, which cannot be performed in neither E. coli nor yeast. Therefore, they are frequently characterized in mammalian cells or in Xenopus laevis oocytes. To avoid generating two different plasmids, we here describe the construction of a dual-function plasmid, pXOOY, for membrane protein production in yeast and for electrophysiology in oocytes. pXOOY was constructed such that all elements required for oocyte expression were copied from the dual Xenopus-mammalian vector pXOOM and meticulously introduced into the high-yield yeast expression vector pEMBLyex4. pXOOY is thus designed to preserve the high yield of protein from pEMBLyex4 while simultaneously permitting in vitro transcription for expression in oocytes. We evaluated the performance of pXOOY by comparing expression of two yeast codon optimized human potassium channels, ohERG and ohSlick (Slo2.1) from pXOOY to expression of these channels obtained from the reference vectors pEMBLyex4 and pXOOM. Our proof-of-concept study indicates that accumulation in PAP1500 yeast cells was higher when the channels were expressed from pXOOY, which was verified both qualitatively and quantitatively. Two-electrode voltage clamp measurements in oocytes showed that the pXOOY constructs encoding ohERG and ohSlick gave currents with full preservation of electrophysiological characteristics. Our results show that it is possible to design a dual-function Xenopus-yeast vector without compromising expression in yeast and simultaneously maintaining channel activity in oocytes.

Ancestral reconstruction reveals catalytic inactivation of activation-induced cytidine deaminase concomitant with cold water adaption in the Gadiformes bony fish

BACKGROUND

Antibody affinity maturation in vertebrates requires the enzyme activation-induced cytidine deaminase (AID) which initiates secondary antibody diversification by mutating the immunoglobulin loci. AID-driven antibody diversification is conserved across jawed vertebrates since bony and cartilaginous fish. Two exceptions have recently been reported, the Pipefish and Anglerfish, in which the AID-encoding aicda gene has been lost. Both cases are associated with unusual reproductive behavior, including male pregnancy and sexual parasitism. Several cold water fish in the Atlantic cod (Gadinae) family carry an aicda gene that encodes for a full-length enzyme but lack affinity-matured antibodies and rely on antibodies of broad antigenic specificity. Hence, we examined the functionality of their AID.

RESULTS

By combining genomics, transcriptomics, immune responsiveness, and functional enzymology of AID from 36 extant species, we demonstrate that AID of that Atlantic cod and related fish have extremely lethargic or no catalytic activity. Through ancestral reconstruction and functional enzymology of 71 AID enzymes, we show that this enzymatic inactivation likely took place relatively recently at the emergence of the true cod family (Gadidae) from their ancestral Gadiformes order. We show that this AID inactivation is not only concordant with the previously shown loss of key adaptive immune genes and expansion of innate and cell-based immune genes in the Gadiformes but is further reflected in the genomes of these fish in the form of loss of AID-favored sequence motifs in their immunoglobulin variable region genes.

CONCLUSIONS

Recent demonstrations of the loss of the aicda gene in two fish species challenge the paradigm that AID-driven secondary antibody diversification is absolutely conserved in jawed vertebrates. These species have unusual reproductive behaviors forming an evolutionary pressure for a certain loss of immunity to avoid tissue rejection. We report here an instance of catalytic inactivation and functional loss of AID rather than gene loss in a conventionally reproducing vertebrate. Our data suggest that an expanded innate immunity, in addition to lower pathogenic pressures in a cold environment relieved the pressure to maintain robust secondary antibody diversification. We suggest that in this unique scenario, the AID-mediated collateral genome-wide damage would form an evolutionary pressure to lose AID function.

Machine learning approaches demonstrate that protein structures carry information about their genetic coding

Synonymous codons translate into the same amino acid. Although the identity of synonymous codons is often considered inconsequential to the final protein structure, there is mounting evidence for an association between the two. Our study examined this association using regression and classification models, finding that codon sequences predict protein backbone dihedral angles with a lower error than amino acid sequences, and that models trained with true dihedral angles have better classification of synonymous codons given structural information than models trained with random dihedral angles. Using this classification approach, we investigated local codon-codon dependencies and tested whether synonymous codon identity can be predicted more accurately from codon context than amino acid context alone, and most specifically which codon context position carries the most predictive power.

Analysis of nested alternate open reading frames and their encoded proteins

Transcriptional and post-transcriptional mechanisms diversify the proteome beyond gene number, while maintaining a sequence relationship between original and altered proteins. A new mechanism breaks this paradigm, generating novel proteins by translating alternative open reading frames (Alt-ORFs) within canonical host mRNAs. Uniquely, ‘alt-proteins’ lack sequence homology with host ORF-derived proteins. We show global amino acid frequencies, and consequent biochemical characteristics of Alt-ORFs nested within host ORFs (nAlt-ORFs), are genetically-driven, and predicted by summation of frequencies of hundreds of encompassing host codon-pairs. Analysis of 101 human nAlt-ORFs of length ≥150 codons confirms the theoretical predictions, revealing an extraordinarily high median isoelectric point (pI) of 11.68, due to anomalous charged amino acid levels. Also, nAlt-ORF proteins exhibit a >2-fold preference for reading frame 2 versus 3, predicted mitochondrial and nuclear localization, and elevated codon adaptation index indicative of natural selection. Our results provide a theoretical and conceptual framework for exploration of these largely unannotated, but potentially significant, alternative ORFs and their encoded proteins.

A unifying network modeling approach for codon optimization

MOTIVATION

Synthesizing genes to be expressed in other organisms is an essential tool in biotechnology. While the many-to-one mapping from codons to amino acids makes the genetic code degenerate, codon usage in a particular organism is not random either. This bias in codon use may have a remarkable effect on the level of gene expression. A number of measures have been developed to quantify a given codon sequence's strength to express a gene in a host organism. Codon optimization aims to find a codon sequence that will optimize one or more of these measures. Efficient computational approaches are needed since the possible number of codon sequences grows exponentially as the number of amino acids increases.

RESULTS

We develop a unifying modeling approach for codon optimization. With our mathematical formulations based on graph/network representations of amino acid sequences, any combination of measures can be optimized in the same framework by finding a path satisfying additional limitations in an acyclic layered network. We tested our approach on bi-objectives commonly used in the literature, namely, Codon Pair Bias versus Codon Adaptation Index and Relative Codon Pair Bias versus Relative Codon Bias. However, our framework is general enough to handle any number of objectives concurrently with certain restrictions or preferences on the use of specific nucleotide sequences. We implemented our models using Python's Gurobi interface and showed the efficacy of our approach even for the largest proteins available. We also provided experimentation showing that highly expressed genes have objective values close to the optimized values in the bi-objective codon design problem.

AVAILABILITY AND IMPLEMENTATION

http://alpersen.bilkent.edu.tr/NetworkCodon.zip.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Protocol to identify host-viral protein interactions between coagulation-related proteins and their genetic variants with SARS-CoV-2 proteins

Here, we describe a bioinformatics pipeline that evaluates the interactions between coagulation-related proteins and genetic variants with SARS-CoV-2 proteins. This pipeline searches for host proteins that may bind to viral protein and identifies and scores the protein genetic variants to predict the disease pathogenesis in specific subpopulations. Additionally, it is able to find structurally similar motifs and identify potential binding sites within the host-viral protein complexes to unveil viral impact on regulated biological processes and/or host-protein impact on viral invasion or reproduction. For complete details on the use and execution of this protocol, please refer to Holcomb et al. (2021).

mRNA delivery technologies: Toward clinical translation

Messenger RNA (mRNA)-therapies have recently taken a huge step toward clinic thanks to the first mRNA-based medicinal products marketed. mRNA features for clinical purposes are improved by chemical modifications, but the inclusion in a delivery system is a regular requirement. mRNA nanomedicines must be designed for the specific therapeutic purpose, protecting the nucleic acid and facilitating the overcoming of biological barriers. Polymers, polypeptides, and cationic lipids are the main used materials to design mRNA delivery systems. Among them, lipid nanoparticles (LNPs) are the most advanced ones, and currently they are at the forefront of preclinical and clinical evaluation in several fields, including immunotherapy (against infectious diseases and cancer), protein replacement, gene editing and regenerative medicine. This chapter includes an overview on mRNA delivery technologies, with special interest in LNPs, and the most recent advances in their clinical application. Liposomes are the mRNA delivery technology with the highest clinical translation among LNPs, whereas the first clinical trial of a therapeutic mRNA formulated in exosomes has been recently approved for protein replacement therapy. The first mRNA products approved by the regulatory agencies worldwide are LNP-based mRNA vaccines against viral infections, specifically against the 2019 coronavirus disease (COVID-19). The clinical translation of mRNA-therapies for cancer is mainly focused on three strategies: anti-cancer vaccination by means of delivering cancer antigens or acting as an adjuvant, mRNA-engineered chimeric antigen receptors (CARs) and T-cell receptors (TCRs), and expression of antibodies and immunomodulators. Cancer immunotherapy and, more recently, COVID-19 vaccines spearhead the advance of mRNA clinical use.

Traditional Protocols and Optimization Methods Lead to Absent Expression in a Mycoplasma Cell-Free Gene Expression Platform

Cell-free expression (CFE) systems are one of the main platforms for building synthetic cells. A major drawback is the orthogonality of cell-free systems across species. To generate a CFE system compatible with recently established minimal cell constructs, we attempted to optimize a Mycoplasma bacterium-based CFE system using lysates of the genome-minimized cell JCVI-syn3A (Syn3A) and its close phylogenetic relative Mycoplasma capricolum (Mcap). To produce mycoplasma-derived crude lysates, we systematically tested methods commonly used for bacteria, based on the S30 protocol of Escherichia coli. Unexpectedly, after numerous attempts to optimize lysate production methods or composition of feeding buffer, none of the Mcap or Syn3A lysates supported cell-free gene expression. Only modest levels of in vitro transcription of RNA aptamers were observed. While our experimental systems were intended to perform transcription and translation, our assays focused on RNA. Further investigations identified persistently high ribonuclease (RNase) activity in all lysates, despite removal of recognizable nucleases from the respective genomes and attempts to inhibit nuclease activities in assorted CFE preparations. An alternative method using digitonin to permeabilize the mycoplasma cell membrane produced a lysate with diminished RNase activity yet still was unable to support cell-free gene expression. We found that intact mycoplasma cells poisoned E. coli cell-free extracts by degrading ribosomal RNAs, indicating that the mycoplasma cells, even the minimal cell, have a surface-associated RNase activity. However, it is not clear which gene encodes the RNase. This work summarizes attempts to produce mycoplasma-based CFE and serves as a cautionary tale for researchers entering this field.

Graphical Abstract

Codon-specific Ramachandran plots show amino acid backbone conformation depends on identity of the translated codon

Synonymous codons translate into chemically identical amino acids. Once considered inconsequential to the formation of the protein product, there is evidence to suggest that codon usage affects co-translational protein folding and the final structure of the expressed protein. Here we develop a method for computing and comparing codon-specific Ramachandran plots and demonstrate that the backbone dihedral angle distributions of some synonymous codons are distinguishable with statistical significance for some secondary structures. This shows that there exists a dependence between codon identity and backbone torsion of the translated amino acid. Although these findings cannot pinpoint the causal direction of this dependence, we discuss the vast biological implications should coding be shown to directly shape protein conformation and demonstrate the usefulness of this method as a tool for probing associations between codon usage and protein structure. Finally, we urge for the inclusion of exact genetic information into structural databases.

Evolution and host adaptability of plant RNA viruses: Research insights on compositional biases

During recent decades, many new emerging or re-emerging RNA viruses have been found in plants through the development of deep-sequencing technology and big data analysis. These findings largely changed our understanding of the origin, evolution and host range of plant RNA viruses. There is evidence that their genetic composition originates from viruses, and host populations play a key role in the evolution and host adaptability of plant RNA viruses. In this mini-review, we describe the state of our understanding of the evolution of plant RNA viruses in view of compositional biases and explore how they adapt to the host. It appears that adenine rich (A-rich) coding sequences, low CpG and UpA dinucleotide frequencies and lower codon usage patterns were found in the vast majority of plant RNA viruses. The codon usage pattern of plant RNA viruses was influenced by both natural selection and mutation pressure, and natural selection mostly from hosts was the dominant factor. The codon adaptation analyses support that plant RNA viruses probably evolved a dynamic balance between codon adaptation and deoptimization to maintain efficient replication cycles in multiple hosts with various codon usage patterns. In the future, additional combinations of computational and experimental analyses of the nucleotide composition and codon usage of plant RNA viruses should be addressed.

An overview of dinucleotide and codon usage in all viruses

Viruses are, by far, the most abundant biological entities on earth. They are found in all known ecological niches and are the causative agents of many important diseases in plants and animals. From an evolutionary point of view, since viruses do not share any orthologous genes, there is a general consensus that they are polyphyletic; that is, they do not have a common ancestor. This means that they appeared several times during the course of evolution. For their life cycle, they are always obligate parasites of a free cellular life form, which can be bacteria, archaea, or eukaryotes. More complexity is added to these entities by the fact that their genetic material can be DNA or RNA (double- or single-stranded) or retrotranscribed. Given these features, we wondered if some general rules can be inferred when studying two basic genomic signatures-dinucleotides and codon usage-analyzing all available complete and non-redundant viral sequences. In spite of the obviously biased sample of sequences available, some general features appear to emerge.

Large-Scale Analysis of SARS-CoV-2 Synonymous Mutations Reveals the Adaptation to the Human Codon Usage During the Virus Evolution

Many large national and transnational studies have been dedicated to the analysis of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) genome, most of which focused on missense and nonsense mutations. However, approximately 30 per cent of the SARS-CoV-2 variants are synonymous, therefore changing the target codon without affecting the corresponding protein sequence.

By performing a large-scale analysis of sequencing data generated from almost 400,000 SARS-CoV-2 samples, we show that silent mutations increasing the similarity of viral codons to the human ones tend to fixate in the viral genome overtime. This indicates that SARS-CoV-2 codon usage is adapting to the human host, likely improving its effectiveness in using the human aminoacyl-tRNA set through the accumulation of deceitfully neutral silent mutations.

One-Sentence Summary. Synonymous SARS-CoV-2 mutations related to the activity of different mutational processes may positively impact viral evolution by increasing its adaptation to the human codon usage.

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

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

Codon usage studies and epitope-based peptide vaccine prediction against Tropheryma whipplei

Background

The Tropheryma whipplei causes acute gastroenteritis to neuronal damages in Homo sapiens. Genomics and codon adaptation studies would be helpful advancements of disease evolution prediction, prevention, and treatment of disease. The codon usage data and codon usage measurement tools were deployed to detect the rare, very rare codons, and also synonymous codons usage. The higher effective number of codon usage values indicates the low codon usage bias in T. whipplei and also in the 23S and 16S ribosomal RNA genes.

Results

In T. whipplei, it was found to hold low codon biasness in genomic sets. The synonymous codons possess the base content in 3rd position that was calculated as A3S% (24.47 and 22.88), C3S% (20.99 and 22.88), T3S% (21.47 and 19.53), and G3S% (33.08 and 34.71) for 23s and 16s rRNA, respectively.

Conclusion

Amino acids like valine, aspartate, leucine, and phenylalanine hold high codon usage frequency and also found to be present in epitopes KPSYLSALSAHLNDK and FKSFNYNVAIGVRQP that were screened from proteins excinuclease ABC subunit UvrC and 3-oxoacyl-ACP reductase FabG, respectively. This method opens novel ways to determine epitope-based peptide vaccines against different pathogenic organisms.

Collaborative Mining of Whole Genome Sequences for Intelligent HIV-1 Sub-Strain(s) Discovery

BACKGROUND

Effective global antiretroviral vaccines and therapeutic strategies depend on the diversity, evolution, and epidemiology of their various strains as well as their transmission and pathogenesis. Most viral disease-causing particles are clustered into a taxonomy of subtypes to suggest pointers toward nucleotide-specific vaccines or therapeutic applications of clinical significance sufficient for sequence-specific diagnosis and homologous viral studies. These are very useful to formulate predictors to induce cross-resistance to some retroviral control drugs being used across study areas.

OBJECTIVE

This research proposed a collaborative framework of hybridized (Machine Learning and Natural Language Processing) techniques to discover hidden genome patterns and feature predictors, for HIV-1 genome sequences mining.

METHOD

630 human HIV-1 genome sequences above 8500 bps were excavated from the National Center for Biotechnology Information (NCBI) database (https://www.ncbi.nlm.nih.gov) for 21 countries across different continents, Antarctica exempt. These sequences were transformed and learned using a self-organizing map (SOM). To discriminate emerging/new sub-strain(s), the HIV-1 reference genome was included as part of the input isolates/samples during the training. After training the SOM, component planes defining pattern clusters of the input datasets were generated, for cognitive knowledge mining and subsequent labelling of the datasets. Additional genome features including dinucleotide transmission recurrences, codon recurrences, and mutation recurrences, were finally extracted from the raw genomes to construct output classification targets for supervised learning.

RESULTS

SOM training explains the inherent pattern diversity of HIV-1 genomes as well as inter- and intra-country transmissions in which mobility might play an active role, as corroborated by literature. Nine sub-strains were discovered after disassembling the SOM correlation hunting matrix space attributed to disparate clusters. Cognitive knowledge mining separated similar pattern clusters bounded by a certain degree of correlation range, discovered by the SOM. A Kruskal-Wallis rank-sum test and Wilcoxon rank-sum test showed statistically significant variations in dinucleotide, codon, and mutation patterns.

CONCLUSION

Results of the discovered sub-strains and response clusters visualizations corroborate existing literature, with significant haplotype variations. The proposed framework would assist in the development of decision support systems for easy contact tracing, infectious disease surveillance, and studying the progressive evolution of the reference HIV-1 genome.

CHARMING: Harmonizing synonymous codon usage to replicate a desired codon usage pattern

There is a growing appreciation that synonymous codon usage, although historically regarded as phenotypically silent, can instead alter a wide range of mechanisms related to functional protein production, a term we use here to describe the net effect of transcription (mRNA synthesis), mRNA half-life, translation (protein synthesis) and the probability of a protein folding correctly to its active, functional structure. In particular, recent discoveries have highlighted the important role that sub-optimal codons can play in modifying co-translational protein folding. These results have drawn increased attention to the patterns of synonymous codon usage within coding sequences, particularly in light of the discovery that these patterns can be conserved across evolution for homologous proteins. Because synonymous codon usage differs between organisms, for heterologous gene expression it can be desirable to make synonymous codon substitutions to match the codon usage pattern from the original organism in the heterologous expression host. Here we present CHARMING (for Codon HARMonizING), a robust and versatile algorithm to design mRNA sequences for heterologous gene expression and other related codon harmonization tasks. CHARMING can be run as a downloadable Python script or via a web portal at http://www.codons.org.

Codon pair optimization (CPO): a software tool for synthetic gene design based on codon pair bias to improve the expression of recombinant proteins in Pichia pastoris

Background

Codon optimization is a common method to improve protein expression levels in Pichia pastoris and the current strategy is to replace rare codons with preferred codons to match the codon usage bias. However, codon-pair contexts have a profound effect on translation efficiency by influencing both translational elongation rates and accuracy. Until now, it remains untested whether optimized genes based on codon pair bias results in higher protein expression levels compared to codon usage bias.

Results

In this study, an algorithm based on dynamic programming was introduced to develop codon pair optimization (CPO) which is a software tool to provide simple and efficient codon pair optimization for synthetic gene design in Pichia pastoris. Two reporters (MT1-MMP E2C6 and ADAM17 A9B8 scFvs) were employed to test the effects of codon pair bias and CPO optimization on their protein expression levels. Four variants of MT1-MMP E2C6 and ADAM17 A9B8 for each were generated, one variant with the best codon-pair context, one with the worst codon-pair context, one with unbiased codon-pair context, and another optimized based on codon usage. The expression levels of variants with the worst codon-pair context were almost undetectable by Western blot and the variants with the best codon-pair context were expressed well. The expression levels on MT1-MMP E2C6 and ADAM17 A9B8 were more than five times and seven times higher in the optimized sequences based on codon-pair context compared to that based on codon usage, respectively. The results indicated that the codon-pair context-based codon optimization is more effective in enhancing expression of protein in Pichia pastoris.

Conclusions

Codon-pair context plays an important role on the protein expression in Pichia pastoris. The codon pair optimization (CPO) software developed in this study efficiently improved the protein expression levels of exogenous genes in Pichia pastoris, suggesting gene design based on codon pair bias is an alternative strategy for high expression of recombinant proteins in Pichia pastoris.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12934-021-01696-y.

The Dynamic Codon Biaser: calculating prokaryotic codon usage biases

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

A multispecies BCO2 beak color polymorphism in the Darwin's finch radiation

Carotenoid-based polymorphisms are widespread in populations of birds, fish, and reptiles,¹ but generally little is known about the factors affecting their maintenance in populations.² We report a combined field and molecular-genetic investigation of a nestling beak color polymorphism in Darwin's finches. Beaks are pink or yellow, and yellow is recessive.³ Here we show that the polymorphism arose in the Galápagos half a million years ago through a mutation associated with regulatory change in the BCO2 gene and is shared by 14 descendant species. The polymorphism is probably a balanced polymorphism, maintained by ecological selection associated with survival and diet. In cactus finches, the frequency of the yellow genotype is correlated with cactus fruit abundance and greater hatching success and may be altered by introgressive hybridization. Polymorphisms that are hidden as adults, as here, may be far more common than is currently recognized, and contribute to diversification in ways that are yet to be discovered.

Causes and Consequences of Purifying Selection on SARS-CoV-2

Owing to a lag between a deleterious mutation's appearance and its selective removal, gold-standard methods for mutation rate estimation assume no meaningful loss of mutations between parents and offspring. Indeed, from analysis of closely related lineages, in SARS-CoV-2, the Ka/Ks ratio was previously estimated as 1.008, suggesting no within-host selection. By contrast, we find a higher number of observed SNPs at 4-fold degenerate sites than elsewhere and, allowing for the virus's complex mutational and compositional biases, estimate that the mutation rate is at least 49-67% higher than would be estimated based on the rate of appearance of variants in sampled genomes. Given the high Ka/Ks one might assume that the majority of such intrahost selection is the purging of nonsense mutations. However, we estimate that selection against nonsense mutations accounts for only ∼10% of all the "missing" mutations. Instead, classical protein-level selective filters (against chemically disparate amino acids and those predicted to disrupt protein functionality) account for many missing mutations. It is less obvious why for an intracellular parasite, amino acid cost parameters, notably amino acid decay rate, is also significant. Perhaps most surprisingly, we also find evidence for real-time selection against synonymous mutations that move codon usage away from that of humans. We conclude that there is common intrahost selection on SARS-CoV-2 that acts on nonsense, missense, and possibly synonymous mutations. This has implications for methods of mutation rate estimation, for determining times to common ancestry and the potential for intrahost evolution including vaccine escape.

Pirahy virus: Identification of a new and potential emerging arbovirus in South Brazil

Genomic and epidemiological surveillance are paramount for the discovery of new viruses with the potential to cross species barriers. Here, we present a new member of the genus Alphavirus found in Trichoprosopon and Wyeomia mosquitoes, tentatively named Pirahy virus (PIRAV). PIRAV was isolated from mosquito pools collected in a rural area of Piraí do Sul, South Brazil. In vitro assays revealed that PIRAV replicates and causes cytopathic effects in vertebrate cell lines such as Vero E6, SH-SY5Y, BHK-21 and UMNSAH/DF-1. Genomic signature analysis supports these results showing a dinucleotide and codon usage balance compatible with several hosts. Phylogenetic analyses placed PIRAV basal to the Venezuelan equine encephalitis complex. Genome analyses, electron microscopy, and biological characterization show findings that may alert for the emergence of a new arbovirus in South America.

Distinct signatures of codon and codon pair usage in 32 primary tumor types in the novel database CancerCoCoPUTs for cancer-specific codon usage

BACKGROUND

Gene expression is highly variable across tissues of multi-cellular organisms, influencing the codon usage of the tissue-specific transcriptome. Cancer disrupts the gene expression pattern of healthy tissue resulting in altered codon usage preferences. The topic of codon usage changes as they relate to codon demand, and tRNA supply in cancer is of growing interest.

METHODS

We analyzed transcriptome-weighted codon and codon pair usage based on The Cancer Genome Atlas (TCGA) RNA-seq data from 6427 solid tumor samples and 632 normal tissue samples. This dataset represents 32 cancer types affecting 11 distinct tissues. Our analysis focused on tissues that give rise to multiple solid tumor types and cancer types that are present in multiple tissues.

RESULTS

We identified distinct patterns of synonymous codon usage changes for different cancer types affecting the same tissue. For example, a substantial increase in GGT-glycine was observed in invasive ductal carcinoma (IDC), invasive lobular carcinoma (ILC), and mixed invasive ductal and lobular carcinoma (IDLC) of the breast. Change in synonymous codon preference favoring GGT correlated with change in synonymous codon preference against GGC in IDC and IDLC, but not in ILC. Furthermore, we examined the codon usage changes between paired healthy/tumor tissue from the same patient. Using clinical data from TCGA, we conducted a survival analysis of patients based on the degree of change between healthy and tumor-specific codon usage, revealing an association between larger changes and increased mortality. We have also created a database that contains cancer-specific codon and codon pair usage data for cancer types derived from TCGA, which represents a comprehensive tool for codon-usage-oriented cancer research.

CONCLUSIONS

Based on data from TCGA, we have highlighted tumor type-specific signatures of codon and codon pair usage. Paired data revealed variable changes to codon usage patterns, which must be considered when designing personalized cancer treatments. The associated database, CancerCoCoPUTs, represents a comprehensive resource for codon and codon pair usage in cancer and is available at https://dnahive.fda.gov/review/cancercocoputs/ . These findings are important to understand the relationship between tRNA supply and codon demand in cancer states and could help guide the development of new cancer therapeutics.