Amino Acid Usage Research Articles

Phenotypic response of yeast metabolic network to availability of proteinogenic amino acids.

Genome-scale metabolism can best be described as a highly interconnected network of biochemical reactions and metabolites. The flow of metabolites, i.e., flux, throughout these networks can be predicted and analyzed using approaches such as flux balance analysis (FBA). By knowing the network topology and employing only a few simple assumptions, FBA can efficiently predict metabolic functions at the genome scale as well as microbial phenotypes. The network topology is represented in the form of genome-scale metabolic models (GEMs), which provide a direct mapping between network structure and function via the enzyme-coding genes and corresponding metabolic capacity. Recently, the role of protein limitations in shaping metabolic phenotypes have been extensively studied following the reconstruction of enzyme-constrained GEMs. This framework has been shown to significantly improve the accuracy of predicting microbial phenotypes, and it has demonstrated that a global limitation in protein availability can prompt the ubiquitous metabolic strategy of overflow metabolism. Being one of the most abundant and differentially expressed proteome sectors, metabolic proteins constitute a major cellular demand on proteinogenic amino acids. However, little is known about the impact and sensitivity of amino acid availability with regards to genome-scale metabolism. Here, we explore these aspects by extending on the enzyme-constrained GEM framework by also accounting for the usage of amino acids in expressing the metabolic proteome. Including amino acids in an enzyme-constrained GEM of Saccharomyces cerevisiae, we demonstrate that the expanded model is capable of accurately reproducing experimental amino acid levels. We further show that the metabolic proteome exerts variable demands on amino acid supplies in a condition-dependent manner, suggesting that S. cerevisiae must have evolved to efficiently fine-tune the synthesis of amino acids for expressing its metabolic proteins in response to changes in the external environment. Finally, our results demonstrate how the metabolic network of S. cerevisiae is robust towards perturbations of individual amino acids, while simultaneously being highly sensitive when the relative amino acid availability is set to mimic a priori distributions of both yeast and non-yeast origins.

Susceptibility to mice and potential evolutionary characteristics of porcine deltacoronavirus.

Porcine deltacoronavirus (PDCoV) is a novel coronavirus that causes diarrhea in suckling piglets and has the potential for cross-species transmission, posing a threat to animal and human health. However, the susceptibility profile of different species of mice to PDCoV infection and its evolutionary characteristics are still unclear. In the current study, we found that BALB/c and Kunming mice are susceptible to PDCoV. Our results showed that there were obvious lesions in intestinal and lung tissues from the infected mice. PDCoV RNAs were detected in the lung, kidney, and intestinal tissues from the infected mice of both strains, and there existed wider tissue tropism in the PDCoV-infected BALB/c mice. The RNA and protein levels of aminopeptidase N from micewere relatively high in the kidney and intestinal tissues and obviously increased after PDCoV infection. The viral-specific IgG and neutralizing antibodies against PDCoV were detected inthe serum of infected mice. An interesting finding was thattwo key amino acid mutations, D138H and Q641K, in the S protein were identified in the PDCoV-infected mice. The essential roles of these two mutations for PDCoV-adaptive evolution were confirmed by cryo-electron microscope structure model analysis. The evolutionary characteristics of PDCoV among Deltacoronaviruses (δ-CoVs) were further analyzed. δ-CoVs from multiple mammals are closely related based on the phylogenetic analysis. The codon usage analysis demonstrated that similar codon usage patterns were used by most of the mammalian δ-CoVs at the global codon, synonymous codon, and amino acid usage levels. These results may provide more insights into the evolution, host ranges, and cross-species potential of PDCoV.

Global genomic and proteomic analysis indicates co-evolution of Neisseria species and with their human host

Neisseria, a genus from the beta-proteobacteria class, is of potential clinical importance. This genus contains both pathogenic and commensal strains. Gonorrhea and meningitis are two major diseasescaused by pathogens belonging to this genus. With the increased use of antimicrobial agents against these pathogens they have evolved the antimicrobial resistance capacity making these diseases nearly untreatable. The set of anti-bacterial resistance genes (resistome) and genes associated with signal processing (secretomes) are crucial for the host-microbial interaction. With the virtue of whole-genome sequences and computational biology, it is now possible to study the genomic and proteomic riddles ofNeisseriaalong with their comprehensive evolutionary and metabolic profiling. We have studied relative synonymous codon usage, amino acid usage, reverse ecology, comparative genomics, evolutionary analysis andpathogen-host (Neisseria-human) interaction through bioinformatics analysis. Our analysis revealed the co-evolution ofNeisseriagenomes with the human host. Moreover, the co-occurrence ofNeisseriaand humans has been supported through reverse ecology analysis. A differential pattern of the evolutionary rate of resistomes and secretomes was evident among the pathogenic and commensal strains. Comparative genomics supported the presence of virulent genes in both pathogenic and commensal strains of the select genus. Our analysis also indicated a transition from commensal to pathogenicNeisseriastrains through the long run of evolution.

In Silico Analyses of the Role of Codon Usage at the Hemagglutinin Cleavage Site in Highly Pathogenic Avian Influenza Genesis.

A vast diversity of 16 influenza hemagglutinin (HA) subtypes are found in birds. Interestingly, viruses from only two subtypes, H5 and H7, have so far evolved into highly pathogenic avian influenza viruses (HPAIVs) following insertions or substitutions at the HA cleavage site by the viral polymerase. The mechanisms underlying this striking subtype specificity are still unknown. Here, we compiled a comprehensive dataset of 20,488 avian influenza virus HA sequences to investigate differences in nucleotide and amino acid usage at the HA cleavage site between subtypes and how these might impact the genesis of HPAIVs by polymerase stuttering and realignment. We found that sequences of the H5 and H7 subtypes stand out by their high purine content at the HA cleavage site. In addition, fewer substitutions were necessary in H5 and H7 HAs than in HAs from other subtypes to acquire an insertion-prone HA cleavage site sequence, as defined based on in vitro and in vivo data from the literature. Codon usage was more favorable for HPAIV genesis in sequences of viruses isolated from species or geographical regions in which HPAIV genesis is more frequently observed in nature. The results of the present analyses suggest that the subtype restriction of HPAIV genesis to H5 and H7 influenza viruses might be due to the particular codon usage at the HA cleavage site in these subtypes.

Complete mitochondrial genome of Kentrochrysalis streckeri (Lepidoptera: Sphingidae) and phylogenetic analysis

In this study, we sequenced the complete mitogenome of Kentrochrysalis streckeri (Staudinger, 1880). The complete mitogenome sequence of K. streckeri is circular, 15,253 bp in size and contains 13 protein-coding genes (PCGs), two ribosomal RNA (rRNA) genes, 22 transfer RNA (tRNA) genes, and a control region (CR). Nucleotide composition was A + T biased, and all the PCGs exhibited a positive AT-skew, which was reflected in the nucleotide composition, codon, and amino acid usage. Most PCGs start with ATG or ATT and stop with TAA. However, COX1 gene starts with CGA and three genes (COX1, COX2, NAD5) use the incomplete stop codon T. Phylogenetic analyses showed that the relationship (K. streckeri+((Manduca sexta+Sphinx morio)+(Psilogramma increta+(Psilogramma menephron+Notonagemia analis scribae)))).

Quantifying shifts in natural selection on codon usage between protein regions: a population genetics approach

BackgroundCodon usage bias (CUB), the non-uniform usage of synonymous codons, occurs across all domains of life. Adaptive CUB is hypothesized to result from various selective pressures, including selection for efficient ribosome elongation, accurate translation, mRNA secondary structure, and/or protein folding. Given the critical link between protein folding and protein function, numerous studies have analyzed the relationship between codon usage and protein structure. The results from these studies have often been contradictory, likely reflecting the differing methods used for measuring codon usage and the failure to appropriately control for confounding factors, such as differences in amino acid usage between protein structures and changes in the frequency of different structures with gene expression.ResultsHere we take an explicit population genetics approach to quantify codon-specific shifts in natural selection related to protein structure in S. cerevisiae and E. coli. Unlike other metrics of codon usage, our approach explicitly separates the effects of natural selection, scaled by gene expression, and mutation bias while naturally accounting for a region’s amino acid usage. Bayesian model comparisons suggest selection on codon usage varies only slightly between helix, sheet, and coil secondary structures and, similarly, between structured and intrinsically-disordered regions. Similarly, in contrast to prevous findings, we find selection on codon usage only varies slightly at the termini of helices in E. coli. Using simulated data, we show this previous work indicating “non-optimal” codons are enriched at the beginning of helices in S. cerevisiae was due to failure to control for various confounding factors (e.g. amino acid biases, gene expression, etc.), and rather than selection to modulate cotranslational folding.ConclusionsOur results reveal a weak relationship between codon usage and protein structure, indicating that differences in selection on codon usage between structures are slight. In addition to the magnitude of differences in selection between protein structures being slight, the observed shifts appear to be idiosyncratic and largely codon-specific rather than systematic reversals in the nature of selection. Overall, our work demonstrates the statistical power and benefits of studying selective shifts on codon usage or other genomic features from an explicitly evolutionary approach. Limitations of this approach and future potential research avenues are discussed.

Using in vivo barcoding to capture T versus B cell fate commitment in the thymus.

Abstract B cells are a rare subset in the thymus, an environment that supports T cell development and inhibits commitment to other immune cell lineages. Yet thymic B cells play an important role in the negative selection of autoreactive T cells. The origin of thymic B cells from either committed B cells or early thymocyte progenitors remains uncertain. We hypothesize that early thymic progenitor cells are a heterogenous population that can give rise to both T cells and B cells. In our study we combined the CRISPR/Cas9-dependent lineage recorder GESTALT with single cell RNAseq to capture cell lineage and type information to follow progressive cell fate decisions and to identify thymic B cell progenitors and transcriptional regulators permitting B cell differentiation in the thymus. Additionally, to evaluate the functional importance of thymic B cells in shaping the T cell repertoire, we performed TCR-seq on conventional CD4 T cells and Tregs. In the absence of B cells, amino acid usage within either TCR alpha or beta CDR3 regions remained unchanged. However, the dominant TCR alpha CDR3 length from the most abundant thymic Treg clones was reduced compared to wild type. Whether this repertoire shift impacts self-tolerance to B cell or AIRE-dependent antigens, both of which are expressed by thymic B cells, remains to be determined. Together, our data directly assesses lineage relationships leading to thymic T and B cell fate commitment and deepen our understanding of intra-thymic development and function of B cells that are required for central tolerance. Supported by AI089805 Burroughs-Wellcome Fellowship

Evolutionary origin and sequence signatures of the heterodimeric ABCG5/ABCG8 transporter.

ATP-binding cassette (ABC) systems, characterized by ABC-type nucleotide-binding domains (NBDs), play crucial roles in various aspects of human physiology. Human ABCG5 and ABCG8 form a heterodimeric transporter that functions in the efflux of sterols. We used sequence similarity search, multiple sequence alignment, phylogenetic analysis, and structure comparison to study the evolutionary origin and sequence signatures of ABCG5 and ABCG8. Orthologs of ABCG5 and ABCG8, supported by phylogenetic analysis and signature residues, were identified in bilaterian animals, Filasterea, Fungi, and Amoebozoa. Such a phylogenetic distribution suggests that ABCG5 and ABCG8 could have originated in the last common ancestor of Amorphea (the unikonts), the eukaryotic group including Amoebozoa and Opisthokonta. ABCG5 and ABCG8 were missing in genomes of various lineages such as snakes, jawless vertebrates, non-vertebrate chordates, echinoderms, and basal metazoan groups. Amino-acid changes in key positions in ABCG8 Walker A motif and/or ABCG5 C-loop were observed in most tetrapod organisms, likely resulted in the loss of ATPase activity at one nucleotide-binding site. ABCG5 and ABCG8 in Ecdysozoa (such as insects) exhibit elevated evolutionary rates and accumulate various changes in their NBD functional motifs. Alignment inspection revealed several residue positions that show different amino-acid usages in ABCG5/ABCG8 compared to other ABCG subfamily proteins. These residues were mapped to the structural cores of transmembrane domains (TMDs), the NBD-TMD interface, and the interface between TMDs. They serve as sequence signatures to differentiate ABCG5/ABCG8 from other ABCG subfamily proteins, and some of them may contribute to substrate specificity of the ABCG5/ABCG8 transporter.

Structural insights into the amino acid usage variations in the profilin gene family.

Profilin protein is present ubiquitously in all forms of life and is allied with allergic responses among atopic individuals. In addition to this, profilins from various food sources are also associated with IgE cross-reactivity and are thus classified as pan-allergens. The present study unravels the physicochemical basis of differential amino acid usage patterns observed in the profilin gene family. Correspondence analysis based on amino acid usage of allergen and non-allergen profilins revealed discrete clusters among them, signifying differential patterns of amino acid usage. The amino acids, namely methionine, proline, histidine, glutamine, glutamic acid, tryptophan and glycine were found to be more frequently utilised by the allergen profilins compared to the non-allergens. Correlation analysis revealed that physicochemical features like protein disorder, trypsin digestion and solubility differed significantly among the allergen and non-allergen profilins, thus supporting the observations from correspondence analysis. In addition, comprehensive sequence analysis revealed that the allergen profilins possess conserved motifs which may correlate with their distinct physicochemical features. An in-depth structural analysis revealed that the over-represented amino acids in allergen profilins have a propensity of being exposed on the surface, which may be attributed to their distinct allergenic characteristics. The distinguished physicochemical features observed among allergens and non-allergens can be employed as descriptors to develop machine learning-based allergenicity prediction models.

The Influence of Codon Usage, Protein Abundance, and Protein Stability on Protein Evolution Vary by Evolutionary Distance and the Type of Protein.

In general, the evolutionary rate of proteins is not primarilyrelated to protein and amino acid functions, and factors such as protein abundance, codon usage, and the protein's TM are more important. To better understand the factors that affect protein evolution, E. coli MG1655 orthologs were compared to those in closely related bacteria and to more distantly related prokaryotes, eukaryotes, and archaea. Also, the evolution of different types of proteins was studied. The analyses indicate that the amino acid conservation of enzymes that do not use macromolecules (e.g. DNA, RNA, and proteins) as substrates and that carry out metabolic processes involving small molecules (i.e. small molecule enzymes) is different than other enzymes. For example, the small molecule enzymes have a lower percent identity than other enzymes when sequences from closely related bacteria are compared. Analyses indicate the lower percent identity is not a result of the amino acid or codon usage of the small molecule enzymes. The small molecule enzymes also don't have a significantly lower protein abundance indicating that is also not likely an important factor driving differences in amino acid conservation. Analyses indicate different methods to measure the TM of proteins have different relationships between amino acid conservation over different evolutionary distances. In totality, the results demonstrate that the relationship between the factors thought to affect protein evolution (protein abundance, codon usage, and proteins TMs) and protein evolution are complex and depend on the factor, the organisms, and the type of proteins being analyzed.

Evolution of Viral Pathogens Follows a Linear Order.

ABSTRACTAlthough lessons have been learned from previous severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) outbreaks, the rapid evolution of the viruses means that future outbreaks of a much larger scale are possible, as shown by the current coronavirus disease 2019 (COVID-19) outbreak. Therefore, it is necessary to better understand the evolution of coronaviruses as well as viruses in general. This study reports a comparative analysis of the amino acid usage within several key viral families and genera that are prone to triggering outbreaks, including coronavirus (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2], SARS-CoV, MERS-CoV, human coronavirus-HKU1 [HCoV-HKU1], HCoV-OC43, HCoV-NL63, and HCoV-229E), influenza A (H1N1 and H3N2), flavivirus (dengue virus serotypes 1 to 4 and Zika) and ebolavirus (Zaire, Sudan, and Bundibugyo ebolavirus). Our analysis reveals that the distribution of amino acid usage in the viral genome is constrained to follow a linear order, and the distribution remains closely related to the viral species within the family or genus. This constraint can be adapted to predict viral mutations and future variants of concern. By studying previous SARS and MERS outbreaks, we have adapted this naturally occurring pattern to determine that although pangolin plays a role in the outbreak of COVID-19, it may not be the sole agent as an intermediate animal. In addition to this study, our findings contribute to the understanding of viral mutations for subsequent development of vaccines and toward developing a model to determine the source of the outbreak.IMPORTANCE This study reports a comparative analysis of amino acid usage within several key viral genera that are prone to triggering outbreaks. Interestingly, there is evidence that the amino acid usage within the viral genomes is not random but in a linear order.

Natural selection shaped the evolution of amino acid usage in mammalian toll like receptor genes

AbstractToll-like receptors (TLRs) are important as they are able to sense diverse set of pathogens associated molecular patterns (PAMPs) as ligands. These receptors are involved in functions such as immune response, development of signaling process and cell adhesion. In the present study we are interested to analyze the influence of evolutionary selection pressure on the mutational diversity of mammalian TLR genes. We observed differential patterns of amino acid usage between primate and non-primate mammalian TLR genes. GC-content of TLR genes and hydrophobicity of the encoded proteins are the most influential factors correlated with the differential pattern of amino acid usage.The influence of the subcellular location on the amino acid usage pattern of TLRs is evident in present study. Purifying selection is uniformly present on TLR genes, positively selected sites are mostly located over the ligand binding domain. Our study clearly demonstrates that natural selection has shaped the evolution of primate and non-primate mammalian TLR genes.

Niche adaptation of Frankia do not drastically influence their metabolic profiling

ABSTRACT Metabolic-profiling (metabolomics/metabonomics) is a measurement strategy among biological systems for low-molecular-weight metabolites and their corresponding intermediates acting as dynamic physiological, pathophysiological and developmental stimuli. Information regarding the metabolomics of Frankia is elusive. In this study, we analyzed 48 Frankia whole-genome sequences. Kyoto Encyclopedia of Genes and Genomes (KEGG) database and KEGG Automatic Annotation Server (KAAS) were used for the prediction and functional annotation of genes associated with diverse metabolic pathways. Comprehensive codon and amino-acid usage analyses along with tRNA adaptation index and dN/dS-based evolutionary inquest were performed. We have used the Database-of-Essential-Genes (DEG) server to predict the essentiality of the metabolic pathway-related-genes. We found a strong effect of compositional constraints on the metabolic pathway genes of Frankia. The evolutionary analysis revealed the conserved nature of the studied genes. Since the metabolic pathway-related genes were found to be housekeeping genes, they are conserved and less evolved. This was further validated with a dN/dS value of less than 1. Moreover, the number of synonymous changes was more than non-synonymous changes so that the amino acid sequence remains identical. The cluster of orthologs (COG) analysis revealed “metabolism” as the main functional category of the studied gene set. The core metabolic pathway-related genes among considered Frankia strains accumulated 115 genes. This study for the first time reveals the genomic characteristics of the metabolic pathway-related genes among Frankia. From all the analysis, we could hypothesize that in spite of their host specificity and differential taxonomical distribution, Frankia maintain a core metabolic proficiency among them.

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.

Metabolic plasticity of Francisella tularensis subsp. holarctica (wild type), Francisella novicida and Francisella sp. strain W12-1067

Francisella tularensis is a Gram-negative bacterium that causes a potentially fatal disease called tularemia. The highly infectious agent can spread via arthropod vectors, including ticks, and via rodents such as rabbits or beavers. The facultative intracellular pathogen typically invades human macrophages at the onset of human infection. For intracellular replication of the bacteria, the usage of amino acids from the host cells and gluconeogenesis seem to be detrimental, but other carbon sources including glucose and glycerol are also utilized. Here, we compared the growth phase-dependent degradation of glucose, glycerol, and alanine in F. tularensis subsp. holarctica isolated from an infected beaver with the respective metabolism in the less virulent strains F. novicida strain U112 and Francisella sp. strain W12-1067. To this aim, we performed 13C-labeling experiments with the bacteria growing in medium T supplemented with either [U-13C6]glucose, [U-13C3]glycerol, or [2,3-13C2]alanine during different growth phases. After cell harvest, mechanical disruption, and hydrolysis of cellular fractions, we determined the 13C-profiles in various metabolites by mass spectrometry. The detected 13C-patterns elucidated the metabolic fate of the supplied carbon nutrients and revealed minor, but significant differences indicative of various metabolic phenotypes of the Francisella strains under study. Glucose served as the main substrate for all strains under the experimental conditions. The sugar was degraded via the Embden-Meyerhof-Parnas pathway as the major catabolic route during growth. At lower rates, exogenous glycerol and alanine were used as co-substrates, particularly in the less pathogenic strains during the later growth phases. Our data support the hypothesis that, among other factors, the capability to adapt substrate usages efficiently and metabolic fluxes could determine the virulence of Francisella strains.

Post combustion carbon capture from diesel engine exhaust using phase change solvents with absorption technique

Carbon capture from air pollution is essential because industrialization and globalisation increase carbon dioxide (CO2) and other carbon emissions. CO2 is a source of global warming greenhouse gases. As a result, it draws more attention among the researcher's community to use novel techniques to control carbon emissions from various sources. In this study, the amino acids are employed in a carbon capture device (CCD) in the form of solution to limit carbon emissions from engine exhaust. The CCD is filled with different amino acids (L-Alanine and L-Arginine) and fixed at the end of tailpipe. A single cylinder, constant speed, four stroke diesel engine was operated at the rated power output of 5.2 kW using diesel fuel. The readings were taken for different loading condition and reaction time with and without CCD. The usage of amino acids of L-Alanine and L-Arginine in the CCD reduces the formation of carbon emissions than without CCD. At peak power output, the CO2 emission was decreased by 13.04% for L-Alanine and 21.73% for L-Arginine. Similarly, the carbon monoxide (CO) was decreased by 23.07% for L-Alanine and 38.46% for L-Arginine when compared to without CCD operation. The usage of amino acids resulted in a reduction in CO2 and CO emissions due to the variance in reaction time. Overall, it was concluded that the use of L-Arginine in the CCD absorbed maximum amount of carbon emissions (CO2 and CO) from engine exhaust than L-Alanine.

MPEPE, a predictive approach to improve protein expression in E. coli based on deep learning

The expression of proteins in Escherichia coli is often essential for their characterization, modification, and subsequent application. Gene sequence is the major factor contributing expression. In this study, we used the expression data from 6438 heterologous proteins under the same expression condition in E. coli to construct a deep learning classifier for screening high- and low-expression proteins. In conjunction with conserved residue analysis to minimize functional disruption, a mutation predictor for enhanced protein expression (MPEPE) was proposed to identify mutations conducive to protein expression. MPEPE identified mutation sites in laccase 13B22 and the glucose dehydrogenase FAD-AtGDH, that significantly increased both expression levels and activity of these proteins. Additionally, a significant correlation of 0.46 between the predicted high level expression propensity with the constructed models and the protein abundance of endogenous genes in E. coli was also been detected. Therefore, the study provides foundational insights into the relationship between specific amino acid usage, codon usage, and protein expression, and is essential for research and industrial applications.

Underlying selection for the diversity of spike protein sequences of SARS-CoV-2.

The global spread of SARS‐CoV‐2 is fast moving and has caused a worldwide public health crisis. In the present article, we analyzed spike protein sequences of SARS‐CoV‐2 genomes to assess the impact of mutational diversity. We observed from amino acid usage patterns that spike proteins are associated with a diversity of mutational changes and most important underlying cause of variation of amino acid usage is the changes in hydrophobicity of spike proteins. The changing patterns of hydrophobicity of spike proteins over time and its influence on the receptor binding affinity provides crucial information on the SARS‐CoV‐2 interaction with human receptor. Our results also show that spike proteins have evolved to prefer more hydrophobic residues over time. The present study provides a comprehensive analysis of molecular sequence data to consider that mutational variants might play a crucial role in modulating the virulence and spread of the virus and has immediate implications for therapeutic strategies.

Codon Usage Bias in Autophagy-Related Gene 13 in Eukaryotes: Uncovering the Genetic Divergence by the Interplay Between Nucleotides and Codon Usages.

Synonymous codon usage bias is a universal characteristic of genomes across various organisms. Autophagy-related gene 13 (atg13) is one essential gene for autophagy initiation, yet the evolutionary trends of the atg13 gene at the usages of nucleotide and synonymous codon remains unexplored. According to phylogenetic analyses for the atg13 gene of 226 eukaryotic organisms at the nucleotide and amino acid levels, it is clear that their nucleotide usages exhibit more genetic information than their amino acid usages. Specifically, the overall nucleotide usage bias quantified by information entropy reflected that the usage biases at the first and second codon positions were stronger than those at the third position of the atg13 genes. Furthermore, the bias level of nucleotide ‘G’ usage is highest, while that of nucleotide ‘C’ usage is lowest in the atg13 genes. On top of that, genetic features represented by synonymous codon usage exhibits a species-specific pattern on the evolution of the atg13 genes to some extent. Interestingly, the codon usages of atg13 genes in the ancestor animals (Latimeria chalumnae, Petromyzon marinus, and Rhinatrema bivittatum) are strongly influenced by mutation pressure from nucleotide composition constraint. However, the distributions of nucleotide composition at different codon positions in the atg13 gene display that natural selection still dominates atg13 codon usages during organisms’ evolution.

CompoDynamics: a comprehensive database for characterizing sequence composition dynamics.

Sequence compositions of nucleic acids and proteins have significant impact on gene expression, RNA stability, translation efficiency, RNA/protein structure and molecular function, and are associated with genome evolution and adaptation across all kingdoms of life. Therefore, a devoted resource of sequence compositions and associated features is fundamentally crucial for a wide range of biological research. Here, we present CompoDynamics (https://ngdc.cncb.ac.cn/compodynamics/), a comprehensive database of sequence compositions of coding sequences (CDSs) and genomes for all kinds of species. Taking advantage of the exponential growth of RefSeq data, CompoDynamics presents a wealth of sequence compositions (nucleotide content, codon usage, amino acid usage) and derived features (coding potential, physicochemical property and phase separation) for 118 689 747 high-quality CDSs and 34 562 genomes across 24 995 species. Additionally, interactive analytical tools are provided to enable comparative analyses of sequence compositions and molecular features across different species and gene groups. Collectively, CompoDynamics bears the great potential to better understand the underlying roles of sequence composition dynamics across genes and genomes, providing a fundamental resource in support of a broad spectrum of biological studies.