Elucidation of Codon Usage Signatures across the Domains of Life

The protein domains of vertebrate species in which selection is more effective have greater intrinsic structural disorder

The nearly neutral theory of molecular evolution posits variation among species in the effectiveness of selection. In an idealized model, the census population size determines both this minimum magnitude of the selection coefficient required for deleterious variants to be reliably purged, and the amount of neutral diversity. Empirically, an 'effective population size' is often estimated from the amount of putatively neutral genetic diversity and is assumed to also capture a species' effectiveness of selection. A potentially more direct measure of the effectiveness of selection is the degree to which selection maintains preferred codons. However, past metrics that compare codon bias across species are confounded by among-species variation in %GC content and/or amino acid composition. Here, we propose a new Codon Adaptation Index of Species (CAIS), based on Kullback-Leibler divergence, that corrects for both confounders. We demonstrate the use of CAIS correlations, as well as the Effective Number of Codons, to show that the protein domains of more highly adapted vertebrate species evolve higher intrinsic structural disorder.

Re-examining Correlations Between Synonymous Codon Usage and Protein Bond Angles in Escherichia coli

Rosenberg AA, Marx A, Bronstein AM (Codon-specific Ramachandran plots show amino acid backbone conformation depends on identity of the translated codon. Nat Commun. 2022:13:2815) recently found a surprising correlation between synonymous codon usage and the dihedral bond angles of the resulting amino acid. However, their analysis did not account for the strongest known correlate of codon usage: gene expression. We re-examined the relationship between bond angles and codon usage by applying the approach of Rosenberg et al. to simulated protein-coding sequences that (i) have random codon usage, (ii) codon usage determined by mutation biases, and (iii) maintain the general relationship between codon usage and gene expression via the assumption of selection-mutation-drift equilibrium. We observed correlations between dihedral bond angle and codon usage when codon usage is entirely random, indicating possible conflation of noise with differences in bond angle distributions between synonymous codons. More relevant to the general analysis of codon usage patterns, we found surprisingly good agreement between the analysis of the real sequences and the analysis of sequences simulated assuming selection-mutation-drift equilibrium, with 91% of significant synonymous codon pairs detected in the former were also detected in the latter. We believe the correlation between codon usage and dihedral bond angles resulted from the variation in codon usage across genes due to the interplay between mutation bias, natural selection for translation efficiency, and gene expression, further underscoring these factors must be controlled for when looking for novel patterns related to codon usage.

The protein domains of vertebrate species in which selection is more effective have greater intrinsic structural disorder

The nearly neutral theory of molecular evolution posits variation among species in the effectiveness of selection. In an idealized model, the census population size determines both this minimum magnitude of the selection coefficient required for deleterious variants to be reliably purged, and the amount of neutral diversity. Empirically, an "effective population size" is often estimated from the amount of putatively neutral genetic diversity and is assumed to also capture a species' effectiveness of selection. A potentially more direct measure of the effectiveness of selection is the degree to which selection maintains preferred codons. However, past metrics that compare codon bias across species are confounded by among-species variation in %GC content and/or amino acid composition. Here we propose a new Codon Adaptation Index of Species (CAIS), based on Kullback-Leibler divergence, that corrects for both confounders. We demonstrate the use of CAIS correlations, as well as the Effective Number of Codons, to show that the protein domains of more highly adapted vertebrate species evolve higher intrinsic structural disorder.

Fitness difference between two synonymous mutations of Phytophthora infestans ATP6 gene

BACKGROUND

Sequence variation produced by mutation provides the ultimate source of natural selection for species adaptation. Unlike nonsynonymous mutation, synonymous mutations are generally considered to be selectively neutral but accumulating evidence suggests they also contribute to species adaptation by regulating the flow of genetic information and the development of functional traits. In this study, we analysed sequence characteristics of ATP6, a housekeeping gene from 139 Phytophthora infestans isolates, and compared the fitness components including metabolic rate, temperature sensitivity, aggressiveness, and fungicide tolerance among synonymous mutations.

RESULTS

We found that the housekeeping gene exhibited low genetic variation and was represented by two major synonymous mutants at similar frequency (0.496 and 0.468, respectively). The two synonymous mutants were generated by a single nucleotide substitution but differed significantly in fitness as well as temperature-mediated spatial distribution and expression. The synonymous mutant ending in AT was more common in cold regions and was more expressed at lower experimental temperature than the synonymous mutant ending in GC and vice versa.

CONCLUSION

Our results are consistent with the argument that synonymous mutations can modulate the adaptive evolution of species including pathogens and have important implications for sustainable disease management, especially under climate change.

Molecular insights into codon usage analysis of mitochondrial fission and fusion gene: relevance to neurodegenerative diseases

Mitochondrial dysfunction is the leading cause of neurodegenerative disorders like Alzheimer's disease and Parkinson's disease. Mitochondria is a highly dynamic organelle continuously undergoing the process of fission and fusion for even distribution of components and maintaining proper shape, number, and bioenergetic functionality. A set of genes governs the process of fission and fusion. OPA1, Mfn1, and Mfn2 govern fusion, while Drp1, Fis1, MIEF1, and MIEF2 genes control fission. Determination of specific molecular patterns of transcripts of these genes revealed the impact of compositional constraints on selecting optimal codons. AGA and CCA codons were over-represented, and CCC, GTC, TTC, GGG, ACG were under-represented in the fusion gene set. In contrast, CTG was over-represented, and GCG, CCG, and TCG were under-represented in the fission gene set. Hydropathicity analysis revealed non-polar protein products of both fission and fusion gene set transcripts. AGA codon repeats are an integral part of translational regulation machinery and present a distinct pattern of over-representation and under-representation in different transcripts within the gene sets, suggestive of selective translational force precisely controlling the occurrence of the codon. Out of six synonymous codons, five synonymous codons encoding for leucine were used differently in both gene sets. Hence, forces regulating the occurrence of AGA and five synonymous leucine-encoding codons suggest translational selection. A correlation of mutational bias with gene expression and codon bias and GRAVY and AROMA signifies the selection pressure in both gene sets, while the correlation of compositional bias with gene expression, codon bias, protein properties, and minimum free energy signifies the presence of compositional constraints. More than 25% of codons of both gene sets showed a significant difference in codon usage. The overall analysis shed light on molecular features of gene sets involved in fission and fusion.

In-silico Codon Context and Synonymous Usage Analysis of Genes for Molecular Mechanisms Inducing Autophagy and Apoptosis with Reference to Neurodegenerative Disorders

Background

Autophagy and apoptosis are cellular processes that maintain cellular homeostasis and remove damaged or aged organelles or aggregated and misfolded proteins. Stress factors initiate the signaling pathways common to autophagy and apoptosis. An imbalance in the autophagy and apoptosis, led by cascade of molecular mechanism prior to both processes culminate into neurodegeneration.

Objective

In present study, we urge to investigate the codon usage pattern of genes which are common before initiating autophagy and apoptosis.

Methods

In the present study, we took up eleven genes (DAPK1, BECN1, PIK3C3 (VPS34), BCL2, MAPK8, BNIP3 L (NIX), PMAIP1, BAD, BID, BBC3, MCL1) that are part of molecular signaling mechanism prior to autophagy and apoptosis. We analyzed dinucleotide odds ratio, codon bias, usage, context, and rare codon analysis.

Results

CpC and GpG dinucleotides were abundant, with the dominance of G/C ending codons as preferred codons. Clustering analysis revealed that MAPK8 had a distinct codon usage pattern compared to other envisaged genes. Both positive and negative contexts were observed, and GAG-GAG followed by CTG-GCC was the most abundant codon pair. Of the six synonymous arginine codons, two codons CGT and CGA were the rarest.

Conclusions

The information presented in the study may be used to manipulate the process of autophagy and apoptosis and to check the pathophysiology associated with their dysregulation.

Accurate prediction of in vivo protein abundances by coupling constraint-based modelling and machine learning

Quantification of how different environmental cues affect protein allocation can provide important insights for understanding cell physiology. While absolute quantification of proteins can be obtained by resource-intensive mass-spectrometry-based technologies, prediction of protein abundances offers another way to obtain insights into protein allocation. Here we present CAMEL, a framework that couples constraint-based modelling with machine learning to predict protein abundance for any environmental condition. This is achieved by building machine learning models that leverage static features, derived from protein sequences, and condition-dependent features predicted from protein-constrained metabolic models. Our findings demonstrate that CAMEL results in excellent prediction of protein allocation in E. coli (average Pearson correlation of at least 0.9), and moderate performance in S. cerevisiae (average Pearson correlation of at least 0.5). Therefore, CAMEL outperformed contending approaches without using molecular read-outs from unseen conditions and provides a valuable tool for using protein allocation in biotechnological applications.

Subfunctionalisation of paralogous genes and evolution of differential codon usage preferences: The showcase of polypyrimidine tract binding proteins

Gene paralogs are copies of an ancestral gene that appear after gene or full genome duplication. When two sister gene copies are maintained in the genome, redundancy may release certain evolutionary pressures, allowing one of them to access novel functions. Here, we focused our study on gene paralogs on the evolutionary history of the three polypyrimidine tract binding protein genes (PTBP) and their concurrent evolution of differential codon usage preferences (CUPrefs) in vertebrate species. PTBP1-3 show high identity at the amino acid level (up to 80%) but display strongly different nucleotide composition, divergent CUPrefs and, in humans and in many other vertebrates, distinct tissue-specific expression levels. Our phylogenetic inference results show that the duplication events leading to the three extant PTBP1-3 lineages predate the basal diversification within vertebrates, and genomic context analysis illustrates that local synteny has been well preserved over time for the three paralogs. We identify a distinct evolutionary pattern towards GC3-enriching substitutions in PTBP1, concurrent with enrichment in frequently used codons and with a tissue-wide expression. In contrast, PTBP2s are enriched in AT-ending, rare codons, and display tissue-restricted expression. As a result of this substitution trend, CUPrefs sharply differ between mammalian PTBP1s and the rest of PTBPs. Genomic context analysis suggests that GC3-rich nucleotide composition in PTBP1s is driven by local substitution processes, while the evidence in this direction is thinner for PTBP2-3. An actual lack of co-variation between the observed GC composition of PTBP2-3 and that of the surrounding non-coding genomic environment would raise an interrogation on the origin of CUPrefs, warranting further research on a putative tissue-specific translational selection. Finally, we communicate an intriguing trend for the use of the UUG-Leu codon, which matches the trends of AT-ending codons. Our results are compatible with a scenario in which a combination of directional mutation-selection processes would have differentially shaped CUPrefs of PTBPs in vertebrates: the observed GC-enrichment of PTBP1 in placental mammals may be linked to genomic location and to the strong and broad tissue-expression, while AT-enrichment of PTBP2 and PTBP3 would be associated with rare CUPrefs and thus, possibly to specialized spatio-temporal expression. Our interpretation is coherent with a gene subfunctionalisation process by differential expression regulation associated with the evolution of specific CUPrefs.

Base Composition, Codon Usage, and Patterns of Gene Sequence Evolution in Butterflies

Coding sequence evolution is influenced by both natural selection and neutral evolutionary forces. In many species, the effects of mutation bias, codon usage, and GC-biased gene conversion (gBGC) on gene sequence evolution have not been detailed. Quantification of how these forces shape substitution patterns is therefore necessary to understand the strength and direction of natural selection. Here, we used comparative genomics to investigate the association between base composition and codon usage bias on gene sequence evolution in butterflies and moths (Lepidoptera), including an in-depth analysis of underlying patterns and processes in one species, Leptidea sinapis. The data revealed significant G/C to A/T substitution bias at third codon position with some variation in the strength among different butterfly lineages. However, the substitution bias was lower than expected from previously estimated mutation rate ratios, partly due to the influence of gBGC. We found that A/T-ending codons were overrepresented in most species, but there was a positive association between the magnitude of codon usage bias and GC-content in third codon positions. In addition, the tRNA-gene population in L. sinapis showed higher GC-content at third codon positions compared to coding sequences in general and less overrepresentation of A/T-ending codons. There was an inverse relationship between synonymous substitutions and codon usage bias indicating selection on synonymous sites. We conclude that the evolutionary rate in Lepidoptera is affected by a complex interaction between underlying G/C -> A/T mutation bias and partly counteracting fixation biases, predominantly conferred by overall purifying selection, gBGC, and selection on codon usage.

Transcriptomic, proteomic, and functional consequences of codon usage bias in human cells during heterologous gene expression

Differences in codon frequency between genomes, genes, or positions along a gene, modulate transcription and translation efficiency, leading to phenotypic and functional differences. Here, we present a multiscale analysis of the effects of synonymous codon recoding during heterologous gene expression in human cells, quantifying the phenotypic consequences of codon usage bias at different molecular and cellular levels, with an emphasis on translation elongation. Six synonymous versions of an antibiotic resistance gene were generated, fused to a fluorescent reporter, and independently expressed in HEK293 cells. Multiscale phenotype was analyzed by means of quantitative transcriptome and proteome assessment, as proxies for gene expression; cellular fluorescence, as a proxy for single-cell level expression; and real-time cell proliferation in absence or presence of antibiotic, as a proxy for the cell fitness. We show that differences in codon usage bias strongly impact the molecular and cellular phenotype: (i) they result in large differences in mRNA levels and protein levels, leading to differences of over 15 times in translation efficiency; (ii) they introduce unpredicted splicing events; (iii) they lead to reproducible phenotypic heterogeneity; and (iv) they lead to a trade-off between the benefit of antibiotic resistance and the burden of heterologous expression. In human cells in culture, codon usage bias modulates gene expression by modifying mRNA availability and suitability for translation, leading to differences in protein levels and eventually eliciting functional phenotypic changes.

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.

Protein expression/secretion boost by a novel unique 21-mer cis-regulatory motif (Exin21) via mRNA stabilization

Boosting protein production is invaluable in both industrial and academic applications. We discovered a novel expression-increasing 21-mer cis-regulatory motif (Exin21) that inserts between SARS-CoV-2 envelope (E) protein-encoding sequence and luciferase reporter gene. This unique Exin21 (CAACCGCGGTTCGCGGCCGCT), encoding a heptapeptide (QPRFAAA, designated as Qα), significantly (34-fold on average) boosted E production. Both synonymous and nonsynonymous mutations within Exin21 diminished its boosting capability, indicating the exclusive composition and order of 21 nucleotides. Further investigations demonstrated that Exin21/Qα addition could boost the production of multiple SARS-CoV-2 structural proteins (S, M, and N) and accessory proteins (NSP2, NSP16, and ORF3), and host cellular gene products such as IL-2, IFN-γ, ACE2, and NIBP. Exin21/Qα enhanced the packaging yield of S-containing pseudoviruses and standard lentivirus. Exin21/Qα addition on the heavy and light chains of human anti-SARS-CoV monoclonal antibody robustly increased antibody production. The extent of such boosting varied with protein types, cellular density/function, transfection efficiency, reporter dosage, secretion signaling, and 2A-mediated auto-cleaving efficiency. Mechanistically, Exin21/Qα increased mRNA synthesis/stability, and facilitated protein expression and secretion. These findings indicate that Exin21/Qα has the potential to be used as a universal booster for protein production, which is of importance for biomedicine research and development of bioproducts, drugs, and vaccines.

On distinguishing between canonical tRNA genes and tRNA gene fragments in prokaryotes

Automated genome annotation is essential for extracting biological information from sequence data. The identification and annotation of tRNA genes is frequently performed by the software package tRNAscan-SE, the output of which is listed for selected genomes in the Genomic tRNA database (GtRNAdb). Here, we highlight a pervasive error in prokaryotic tRNA gene sets on GtRNAdb: the mis-categorization of partial, non-canonical tRNA genes as standard, canonical tRNA genes. Firstly, we demonstrate the issue using the tRNA gene sets of 20 organisms from the archaeal taxon Thermococcaceae. According to GtRNAdb, these organisms collectively deviate from the expected set of tRNA genes in 15 instances, including the listing of eleven putative canonical tRNA genes. However, after detailed manual annotation, only one of these eleven remains; the others are either partial, non-canonical tRNA genes resulting from the integration of genetic elements or CRISPR-Cas activity (seven instances), or attributable to ambiguities in input sequences (three instances). Secondly, we show that similar examples of the mis-categorization of predicted tRNA sequences occur throughout the prokaryotic sections of GtRNAdb. While both canonical and non-canonical prokaryotic tRNA gene sequences identified by tRNAscan-SE are biologically interesting, the challenge of reliably distinguishing between them remains. We recommend employing a combination of (i) screening input sequences for the genetic elements typically associated with non-canonical tRNA genes, and ambiguities, (ii) activating the tRNAscan-SE automated pseudogene detection function, and (iii) scrutinizing predicted tRNA genes with low isotype scores. These measures greatly reduce manual annotation efforts, and lead to improved prokaryotic tRNA gene set predictions.

Natural selection plays a significant role in governing the codon usage bias in the novel SARS-CoV-2 variants of concern (VOC)

The ongoing prevailing COVID-19 pandemic caused by SARS-CoV-2 is becoming one of the major global health concerns worldwide. The SARS-CoV-2 genome encodes spike (S) glycoprotein that plays a very crucial role in viral entry into the host cell via binding of its receptor binding domain (RBD) to the host angiotensin converting enzyme 2 (ACE2) receptor. The continuously evolving SARS-CoV-2 genome results in more severe and transmissible variants characterized by the emergence of novel mutations called 'variants of concern' (VOC). The currently designated alpha, beta, gamma, delta and omicron VOC are the focus of this study due to their high transmissibility, increased virulence, and concerns for decreased effectiveness of the available vaccines. In VOC, the spike (S) gene and other non-structural protein mutations may affect the efficacies of the approved COVID-19 vaccines. To understand the diversity of SARS-CoV-2, several studies have been performed on a limited number of sequences. However, only a few studies have focused on codon usage bias (CUBs) pattern analysis of all the VOC strains. Therefore, to evaluate the evolutionary divergence of all VOC S-genes, we performed CUBs analysis on 300,354 sequences to understand the evolutionary relationship with its adaptation in different hosts, i.e., humans, bats, and pangolins. Base composition and RSCU analysis revealed the presence of 20 preferred AU-ended and 10 under-preferred GC-ended codons. In addition, CpG was found to be depleted, which may be attributable to the adaptive response by viruses to escape from the host defense process. Moreover, the ENC values revealed a higher bias in codon usage in the VOC S-gene. Further, the neutrality plot analysis demonstrated that S-genes analyzed in this study are under 83.93% influence of natural selection, suggesting its pivotal role in shaping the CUBs. The CUBs pattern of S-genes was found to be very similar among all the VOC strains. Interestingly, we observed that VOC strains followed a trend of antagonistic codon usage with respect to the human host. The identified CUBs divergence would help to understand the virus evolution and its host adaptation, thus help design novel vaccine strategies against the emerging VOC strains. To the best of our knowledge, this is the first report for identifying the evolution of CUBs pattern in all the currently identified VOC.

A Distinct Tobamovirus Associated With Trichosanthes kirilowii Mottle Mosaic Disease

Trichosanthes kirilowii is one of the most important perennial herbaceous vines that have been used in traditional Chinese medicine. In this study, a novel RNA virus was discovered in T. kirilowii plants showing leaf mottling and mosaic symptoms. The complete genome of this virus is 6,524 nucleotides long and encodes four open reading frames which are arranged in a manner typical of tobamoviruses. Phylogenetic analysis based on the complete genome sequence revealed that the virus was clustered into a branch with the tobamoviruses whose natural host are plants belonging to the family Cucurbitaceae. A full-length infectious cDNA clone was then constructed and demonstrated to establish a systemic infection with typical symptoms in Nicotiana benthamiana, T. kirilowii, and five other cucurbitaceous crops including Cucumis melo, C. lanatus, C. sativus, Luffa aegyptiaca, and Cucurbita pepo via agrobacterium-mediated infectivity assays. Further experiments provided evidence that the rod-shaped viral particles derived from the infectious clone could be mechanically transmitted and reproduce indistinguishable symptoms in the tested plants. Taken together, the mottle mosaic disease of T. kirilowii is caused by a distinct tobamovirus, for which the name Trichosanthes mottle mosaic virus (TrMMV) is proposed. As the infectious cDNA clone of TrMMV could also infect five other cucurbit crops, this distinct tobamovirus could be a potential threat to other cucurbitaceous crops.

Frameshift and wild-type proteins are often highly similar because the genetic code and genomes were optimized for frameshift tolerance

Frameshift mutations have been considered of significant importance for the molecular evolution of proteins and their coding genes, while frameshift protein sequences encoded in the alternative reading frames of coding genes have been considered to be meaningless. However, functional frameshifts have been found widely existing. It was puzzling how a frameshift protein kept its structure and functionality while substantial changes occurred in its primary amino-acid sequence. This study shows that the similarities among frameshifts and wild types are higher than random similarities and are determined at different levels. Frameshift substitutions are more conservative than random substitutions in the standard genetic code (SGC). The frameshift substitutions score of SGC ranks in the top 2.0-3.5% of alternative genetic codes, showing that SGC is nearly optimal for frameshift tolerance. In many genes and certain genomes, frameshift-resistant codons and codon pairs appear more frequently than expected, suggesting that frameshift tolerance is achieved through not only the optimality of the genetic code but, more importantly, the further optimization of a specific gene or genome through the usages of codons/codon pairs, which sheds light on the role of frameshift mutations in molecular and genomic evolution.

T-G-A Deficiency Pattern in Protein-Coding Genes and Its Potential Reason

If a stop codon appears within one gene, then its translation will be terminated earlier than expected. False folding of premature protein will be adverse to the host; hence, all functional genes would tend to avoid the intragenic stop codons. Therefore, we hypothesize that there will be less frequency of nucleotides corresponding to stop codons at each codon position of genes. Here, we validate this inference by investigating the nucleotide frequency at a large scale and results from 19,911 prokaryote genomes revealed that nucleotides coinciding with stop codons indeed have the lowest frequency in most genomes. Interestingly, genes with three types of stop codons all tend to follow a T-G-A deficiency pattern, suggesting that the property of avoiding intragenic termination pressure is the same and the major stop codon TGA plays a dominant role in this effect. Finally, a positive correlation between the TGA deficiency extent and the base length was observed in start-experimentally verified genes of Escherichia coli (E. coli). This strengthens the proof of our hypothesis. The T-G-A deficiency pattern observed would help to understand the evolution of codon usage tactics in extant organisms.

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.

Comparative Genomic Analysis Reveals Potential Pathogenicity and Slow-Growth Characteristics of Genus Brevundimonas and Description of Brevundimonas pishanensis sp. nov

The genus Brevundimonas consists of Gram-negative bacteria widely distributed in environment and can cause human infections. However, the genomic characteristics and pathogenicity of Brevundimonas remain poorly studied. Here, the whole-genome features of 24 Brevundimonas type strains were described. Brevundimonas spp. had relatively small genomes (3.13 ± 0.29 Mb) within the family Caulobacteraceae but high G+C contents (67.01 ± 2.19 mol%). Two-dimensional hierarchical clustering divided those genomes into 5 major clades, in which clades II and V contained nine and five species, respectively. Interestingly, phylogenetic analysis showed a one-to-one match between core and accessory genomes, which suggested coevolution of species within the genus Brevundimonas. The unique genes were annotated to biological functions like catalytic activity, signaling and cellular processes, multisubstance metabolism, etc. The majority of Brevundimonas spp. harbored virulence-associated genes icl, tufA, kdsA, htpB, and acpXL, which encoded isocitrate lyase, elongation factor, 2-dehydro-3-deoxyphosphooctonate aldolase, heat shock protein, and acyl carrier protein, respectively. In addition, genomic islands (GIs) and phages/prophages were identified within the Brevundimonas genus. Importantly, a novel Brevundimonas species was identified from the feces of a patient (suffering from diarrhea) by the analyses of biochemical characteristics, phylogenetic tree of 16S rRNA gene, multilocus sequence analysis (MLSA) sequences, and genomic data. The name Brevundimonas pishanensis sp. nov. was proposed, with type strain CHPC 1.3453 (= GDMCC 1.2503^T= KCTC 82824^T). Brevundimonas spp. also showed obvious slow growth compared with that of Escherichia coli. Our study reveals insights into genomic characteristics and potential virulence-associated genes of Brevundimonas spp., and provides a basis for further intensive study of the pathogenicity of Brevundimonas.

IMPORTANCEBrevundimonas spp., a group of bacteria from the family Caulobacteraceae, is associated with nosocomial infections, deserve widespread attention. Our study elucidated genes potentially associated with the pathogenicity of the Brevundimonas genus. We also described some new characteristics of Brevundimonas spp., such as small chromosome size, high G+C content, and slow-growth phenotypes, which made the Brevundimonas genus a good model organism for in-depth studies of growth rate traits. Apart from the comparative analysis of the genomic features of the Brevundimonas genus, we also reported a novel Brevundimonas species, Brevundimonas pishanensis, from the feces of a patient with diarrhea. Our study promotes the understanding of the pathogenicity characteristics of Brevundimonas species bacteria.

Ionizing radiation and chemical oxidant exposure impacts on Cryptococcus neoformans transfer RNAs

Cryptococcus neoformans is a fungus that is able to survive abnormally high levels of ionizing radiation (IR). The radiolysis of water by IR generates reactive oxygen species (ROS) such as H₂O₂ and OH^-. C. neoformans withstands the damage caused by IR and ROS through antioxidant production and enzyme-catalyzed breakdown of ROS. Given these particular cellular protein needs, questions arise whether transfer ribonucleic acids molecules (tRNAs) undergo unique chemical modifications to maintain their structure, stability, and/or function under such environmental conditions. Here, we investigated the effects of IR and H₂O₂ exposure on tRNAs in C. neoformans. We experimentally identified the modified nucleosides present in C. neoformans tRNAs and quantified changes in those modifications upon exposure to oxidative conditions. To better understand these modified nucleoside results, we also evaluated tRNA pool composition in response to the oxidative conditions. We found that regardless of environmental conditions, tRNA modifications and transcripts were minimally affected. A rationale for the stability of the tRNA pool and its concomitant profile of modified nucleosides is proposed based on the lack of codon bias throughout the C. neoformans genome and in particular for oxidative response transcripts. Our findings suggest that C. neoformans can rapidly adapt to oxidative environments as mRNA translation/protein synthesis are minimally impacted by codon bias.

Analysis of SARS-CoV-2 synonymous codon usage evolution throughout the COVID-19 pandemic

SARS-CoV-2, the seventh coronavirus known to infect humans, can cause severe life-threatening respiratory pathologies. To better understand SARS-CoV-2 evolution, genome-wide analyses have been made, including the general characterization of its codons usage profile. Here we present a bioinformatic analysis of the evolution of SARS-CoV-2 codon usage over time using complete genomes collected since December 2019. Our results show that SARS-CoV-2 codon usage pattern is antagonistic to, and it is getting farther away from that of the human host. Further, a selection of deoptimized codons over time, which was accompanied by a decrease in both the codon adaptation index and the effective number of codons, was observed. All together, these findings suggest that SARS-CoV-2 could be evolving, at least from the perspective of the synonymous codon usage, to become less pathogenic.

GC content of plant genes is linked to past gene duplications

The frequency of G and C nucleotides in genomes varies from species to species, and sometimes even between different genes in the same genome. The monocot grasses have a bimodal distribution of genic GC content absent in dicots. We categorized plant genes from 5 dicots and 4 monocot grasses by synteny to related species and determined that syntenic genes have significantly higher GC content than non-syntenic genes at their 5`-end in the third position within codons for all 9 species. Lower GC content is correlated with gene duplication, as lack of synteny to distantly related genomes is associated with past interspersed gene duplications. Two mutation types can account for biased GC content, mutation of methylated C to T and gene conversion from A to G. Gene conversion involves non-reciprocal exchanges between homologous alleles and is not detectable when the alleles are identical or heterozygous for presence-absence variation, both likely situations for genes duplicated to new loci. Gene duplication can cause production of siRNA which can induce targeted methylation, elevating mC→T mutations. Recently duplicated plant genes are more frequently methylated and less likely to undergo gene conversion, each of these factors synergistically creating a mutational environment favoring AT nucleotides. The syntenic genes with high GC content in the grasses compose a subset that have undergone few duplications, or for which duplicate copies were purged by selection. We propose a “biased gene duplication / biased mutation” (BDBM) model that may explain the origin and trajectory of the observed link between duplication and genic GC bias. The BDBM model is supported by empirical data based on joint analyses of 9 angiosperm species with their genes categorized by duplication status, GC content, methylation levels and functional classes.

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

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

Determination of the Amino Acid Recruitment Order in Early Life by Genome-Wide Analysis of Amino Acid Usage Bias

The mechanisms shaping the amino acids recruitment pattern into the proteins in the early life history presently remains a huge mystery. In this study, we conducted genome-wide analyses of amino acids usage and genetic codons structure in 7270 species across three domains of life. The carried-out analyses evidenced ubiquitous usage bias of amino acids that were likely independent from codon usage bias. Taking advantage of codon usage bias, we performed pseudotime analysis to re-determine the chronological order of the species emergence, which inspired a new species relationship by tracing the imprint of codon usage evolution. Furthermore, the multidimensional data integration showed that the amino acids A, D, E, G, L, P, R, S, T and V might be the first recruited into the last universal common ancestry (LUCA) proteins. The data analysis also indicated that the remaining amino acids most probably were gradually incorporated into proteogenesis process in the course of two long-timescale parallel evolutionary routes: I→F→Y→C→M→W and K→N→Q→H. This study provides new insight into the origin of life, particularly in terms of the basic protein composition of early life. Our work provides crucial information that will help in a further understanding of protein structure and function in relation to their evolutionary history.

Strategies and Patterns of Codon Bias in Molluscum Contagiosum Virus

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

Arginine Depletion in Human Cancers

Arginine is encoded by six different codons. Base pair changes in any of these codons can have a broad spectrum of effects including substitutions to twelve different amino acids, eighteen synonymous changes, and two stop codons. Four amino acids (histidine, cysteine, glutamine, and tryptophan) account for over 75% of amino acid substitutions of arginine. This suggests that a mutational bias, or "purifying selection", mechanism is at work. This bias appears to be driven by C > T and G > A transitions in four of the six arginine codons, a signature that is universal and independent of cancer tissue of origin or histology. Here, we provide a review of the available literature and reanalyze publicly available data from the Catalogue of Somatic Mutations in Cancer (COSMIC). Our analysis identifies several genes with an arginine substitution bias. These include known factors such as IDH1, as well as previously unreported genes, including four cancer driver genes (FGFR3, PPP6C, MAX, GNAQ). We propose that base pair substitution bias and amino acid physiology both play a role in purifying selection. This model may explain the documented arginine substitution bias in cancers.

Protein Abundance Prediction Through Machine Learning Methods

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

Codon optimality in cancer

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

Design and assembly of DNA molecules using multi-objective optimization

Rapid engineering of biological systems is currently hindered by limited integration of manufacturing constraints into the design process, ultimately reducing the yield of many synthetic biology workflows. Here we tackle DNA engineering as a multi-objective optimization problem aiming at finding the best tradeoff between design requirements and manufacturing constraints. We developed a new open-source algorithm for DNA engineering, called Multi-Objective Optimisation algorithm for DNA Design and Assembly, available as a Python and Anaconda package, as well as a Docker image. Experimental results show that our method provides near-optimal constructs and scales linearly with design complexity, effectively paving the way to rational engineering of DNA molecules from genes to genomes.

Regulation of gene expression via translational buffering

Translation of an mRNA represents a critical step during the expression of protein-coding genes. As mechanisms governing post-transcriptional regulation of gene expression are progressively unveiled, it is becoming apparent that transcriptional programs are not fully reflected in the proteome. Herein, we highlight a previously underappreciated post-transcriptional mode of regulation of gene expression termed translational buffering. In principle, translational buffering opposes the impact of alterations in mRNA levels on the proteome. We further describe three types of translational buffering: compensation, which maintains protein levels e.g. across species or individuals; equilibration, which retains pathway stoichiometry; and offsetting, which acts as a reversible mechanism that maintains the levels of selected subsets of proteins constant despite genetic alteration and/or stress-induced changes in corresponding mRNA levels. While mechanisms underlying compensation and equilibration have been reviewed elsewhere, the principal focus of this review is on the less-well understood mechanism of translational offsetting. Finally, we discuss potential roles of translational buffering in homeostasis and disease.

Codon Usage Bias: An Endless Tale

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

Codon usage bias and dinucleotide preference in 29 Drosophila species

Codon usage bias, where certain codons are used more frequently than their synonymous counterparts, is an interesting phenomenon influenced by three evolutionary forces: mutation, selection, and genetic drift. To better understand how these evolutionary forces affect codon usage bias, an extensive study to detect how codon usage patterns change across species is required. This study investigated 668 single-copy orthologous genes independently in 29 Drosophila species to determine how the codon usage patterns change with phylogenetic distance. We found a strong correlation between phylogenetic distance and codon usage bias and observed striking differences in codon preferences between the two subgenera Drosophila and Sophophora. As compared to the subgenus Sophophora, species of the subgenus Drosophila showed reduced codon usage bias and a reduced preference specifically for codons ending with C, except for codons with G in the second position. We found that codon usage patterns in all species were influenced by the nucleotides in the codon’s 2nd and 3rd positions rather than the biochemical properties of the amino acids encoded. We detected a concordance between preferred codons and preferred dinucleotides (at positions 2 and 3 of codons). Furthermore, we observed an association between speciation, codon preferences, and dinucleotide preferences. Our study provides the foundation to understand how selection acts on dinucleotides to influence codon usage bias.

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

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

Evolutionary responses to codon usage of horizontally transferred genes in Pseudomonas aeruginosa: gene retention, amelioration and compensatory evolution

Prokaryote genome evolution is characterized by the frequent gain of genes through horizontal gene transfer (HGT). For a gene, being horizontally transferred can represent a strong change in its genomic and physiological context. If the codon usage of a transferred gene deviates from that of the receiving organism, the fitness benefits it provides can be reduced due to a mismatch with the expression machinery. Consequently, transferred genes with a deviating codon usage can be selected against or elicit evolutionary responses that enhance their integration, such as gene amelioration and compensatory evolution. Within bacterial species, the extent and relative importance of these different mechanisms has never been considered altogether. In this study, a phylogeny-based method was used to investigate the occurrence of these different evolutionary responses in Pseudomonas aeruginosa. Selection on codon usage of genes acquired through HGT was observed over evolutionary time, with the overall codon usage converging towards that of the core genome. Gene amelioration, through the accumulation of synonymous mutations after HGT, did not seem to systematically affect transferred genes. This pattern therefore seemed to be mainly driven by selective retention of transferred genes with an initial codon usage similar to that of the core genes. Additionally, variation in the copy number of tRNA genes was often associated with the acquisition of genes for which the observed variation could enhance their expression. This provides evidence that compensatory evolution might be an important mechanism for the integration of horizontally transferred genes.

The hunt for a yet unknown: Common molecular signature in some genetically monomorphic enterobacteria

Mark Achtman introduced the term "genetically monomorphic bacteria" (GM bacteria) for some human and plant pathogens. They displayed a great uniformity in terms of their "genetic" properties. This "uniformity" poses a challenge to microbiologists. To address these problems, we used CodonW and IslandViewer 3 as analytical tools and took Escherichia coli, Salmonella, and Shigella strains as a model organisms. We hypothesized that GM bacterium contains a common molecular signature among them. We have found a significant correlation regarding the number of protein-coding genes, predicted highly expressed genes, and the highest length of gene in this regard. On the other hand, the correspondence analysis of pathogenicity-related genes identified by IslandViewer 3 displayed a somewhat unique pattern in GM bacteria. The probable pathogenic genes are clustered into two separate groups, which is a hallmark of some pattern. Similar genes of non-monomorphic pathogenic strain clustered almost similarly, but the clusters are joined together, they are not completely separated. These features, in our considered view, may be considered as codon usages signatures of these bacteria, and E. coli in particular.

Effective, safe, and sustained correction of murine XLA using a UCOE-BTK promoter-based lentiviral vector

X-linked agammaglobulinemia (XLA) is an immune disorder caused by mutations in Bruton’s tyrosine kinase (BTK). BTK is expressed in B and myeloid cells, and its deficiency results in a lack of mature B cells and protective antibodies. We previously reported a lentivirus (LV) BTK replacement therapy that restored B cell development and function in Btk and Tec double knockout mice (a phenocopy of human XLA). In this study, with the goal of optimizing both the level and lineage specificity of BTK expression, we generated LV incorporating the proximal human BTK promoter. Hematopoietic stem cells from Btk^−/−Tec^−/− mice transduced with this vector rescued lineage-specific expression and restored B cell function in Btk^−/−Tec^−/− recipients. Next, we tested addition of candidate enhancers and/or ubiquitous chromatin opening elements (UCOEs), as well as codon optimization to improve BTK expression. An Eμ enhancer improved B cell rescue, but increased immunoglobulin G (IgG) autoantibodies. Addition of the UCOE avoided autoantibody generation while improving B cell development and function and reducing vector silencing. An optimized vector containing a truncated UCOE upstream of the BTK promoter and codon-optimized BTK cDNA resulted in stable, lineage-regulated BTK expression that mirrored endogenous BTK, making it a strong candidate for XLA therapy.

Codon usage signatures in the genus Cryptococcus: A complex interplay of gene expression, translational selection and compositional bias

The fungal genus Cryptococcus comprises of several diverse species. The pathogens forming Cryptococcus neoformans/ Cryptococcus gatti species complex are of immense clinical significance owing to the high frequency of infections and deaths globally. Three closely related non-pathogenic species namely, Cryptococcus amylolentus, Cryptococcus wingfieldii and Cryptococcus depauperatus are the non-pathogenic ancestral species from which pathogenic lineages have diverged. In the current study, a comprehensive analysis of factors influencing the codon and amino acid usage bias in six pathogenic and three non-pathogenic species was performed. Our results revealed that though compositional bias played a crucial role, translational selection and gene expression were the key determinants of codon usage variations. Analysis of relative dinucleotide abundance and codon context signatures revealed strict avoidance of TpA dinucleotide across genomes. Multivariate statistical analysis based on codon usage data resulted in discrete clustering of pathogens and non-pathogens which correlated with previous reports on their phylogenetic distribution.

Diverse species in the genus Cryptococcus: Pathogens and their non-pathogenic ancestors

The genus Cryptococcus comprises of more than 30 species. It consists of clinically significant pathogenic Cryptococcus neoformans/Cryptococcus gattii species complex comprising of a minimum of seven species. These pathogens cost more than 200,000 lives annually by causing cryptococcal meningoencephalitis. The evolution of the pathogenic species from closely related non-pathogenic species of the Cryptococcus amylolentus complex is of particular importance and several advances have been made to understand their phylogenetic and genomic relationships. The current review briefly describes the sexual reproduction process followed by an individual description of the members focusing on their key attributes and virulence mechanisms of the pathogenic species. A special section on phylogenetic studies is aimed at understanding the evolutionary divergence of pathogens from non-pathogens. Recent findings from our group pertaining to parameters affecting codon usage bias in six pathogenic and three non-pathogenic ancestral species and their corroboration with existing phylogenetic reports are also included in the current review.

Probability of change in life: Amino acid changes in single nucleotide substitutions

Mutations underpin the processes in life, be it beneficial or detrimental. While mutations are assumed to be random in the bereft of selection pressures, the genetic code has underlying computable probabilities in amino acid phenotypic changes. With a wide range of implications including drug resistance, understanding amino acid changes is important. In this study, we calculated the probabilities of substitutions mutations in the genetic code leading to the 20 amino acids and stop codons. Our calculations reveal an enigmatic in-built self-preserving organization of the genetic code that averts disruptive changes at the physicochemical properties level. These changes include changes to start, aromatic, negative charged amino acids and stop codons. Our findings thus reveal a statistical mechanism governing the relationship between amino acids and the universal genetic code.