Analysis of 3.5 million SARS-CoV-2 sequences reveals unique mutational trends with consistent nucleotide and codon frequencies.

BACKGROUND: Since the onset of the SARS-CoV-2 pandemic, bioinformatic analyses have been performed to understand the nucleotide and synonymous codon usage features and mutational patterns of the virus. However, comparatively few have attempted to perform such analyses on a considerably large cohort of viral genomes while organizing the plethora of available sequence data for a month-by-month analysis to observe changes over time. Here, we aimed to perform sequence composition and mutation analysis of SARS-CoV-2, separating sequences by gene, clade, and timepoints, and contrast the mutational profile of SARS-CoV-2 to other comparable RNA viruses. METHODS: Using a cleaned, filtered, and pre-aligned dataset of over 3.5 million sequences downloaded from the GISAID database, we computed nucleotide and codon usage statistics, including calculation of relative synonymous codon usage values. We then calculated codon adaptation index (CAI) changes and a nonsynonymous/synonymous mutation ratio (dN/dS) over time for our dataset. Finally, we compiled information on the types of mutations occurring for SARS-CoV-2 and other comparable RNA viruses, and generated heatmaps showing codon and nucleotide composition at high entropy positions along the Spike sequence. RESULTS: We show that nucleotide and codon usage metrics remain relatively consistent over the 32-month span, though there are significant differences between clades within each gene at various timepoints. CAI and dN/dS values vary substantially between different timepoints and different genes, with Spike gene on average showing both the highest CAI and dN/dS values. Mutational analysis showed that SARS-CoV-2 Spike has a higher proportion of nonsynonymous mutations than analogous genes in other RNA viruses, with nonsynonymous mutations outnumbering synonymous ones by up to 20:1. However, at several specific positions, synonymous mutations were overwhelmingly predominant. CONCLUSIONS: Our multifaceted analysis covering both the composition and mutation signature of SARS-CoV-2 gives valuable insight into the nucleotide frequency and codon usage heterogeneity of SARS-CoV-2 over time, and its unique mutational profile compared to other RNA viruses.

Utilizing the codon adaptation index to evaluate the susceptibility to HIV-1 and SARS-CoV-2 related coronaviruses in possible target cells in humans.

Comprehensive identification of possible target cells for viruses is crucial for understanding the pathological mechanism of virosis. The susceptibility of cells to viruses depends on many factors. Besides the existence of receptors at the cell surface, effective expression of viral genes is also pivotal for viral infection. The regulation of viral gene expression is a multilevel process including transcription, translational initiation and translational elongation. At the translational elongation level, the translational efficiency of viral mRNAs mainly depends on the match between their codon composition and cellular translational machinery (usually referred to as codon adaptation). Thus, codon adaptation for viral ORFs in different cell types may be related to their susceptibility to viruses. In this study, we selected the codon adaptation index (CAI) which is a common codon adaptation-based indicator for assessing the translational efficiency at the translational elongation level to evaluate the susceptibility to two-pandemic viruses (HIV-1 and SARS-CoV-2) of different human cell types. Compared with previous studies that evaluated the infectivity of viruses based on codon adaptation, the main advantage of our study is that our analysis is refined to the cell-type level. At first, we verified the positive correlation between CAI and translational efficiency and strengthened the rationality of our research method. Then we calculated CAI for ORFs of two viruses in various human cell types. We found that compared to high-expression endogenous genes, the CAIs of viral ORFs are relatively low. This phenomenon implied that two kinds of viruses have not been well adapted to translational regulatory machinery in human cells. Also, we indicated that presumptive susceptibility to viruses according to CAI is usually consistent with the results of experimental research. However, there are still some exceptions. Finally, we found that two viruses have different effects on cellular translational mechanisms. HIV-1 decouples CAI and translational efficiency of endogenous genes in host cells and SARS-CoV-2 exhibits increased CAI for its ORFs in infected cells. Our results implied that at least in cases of HIV-1 and SARS-CoV-2, CAI can be regarded as an auxiliary index to assess cells' susceptibility to viruses but cannot be used as the only evidence to identify viral target cells.

RASCL: Rapid Assessment of Selection in CLades through molecular sequence analysis.

An important unmet need revealed by the COVID-19 pandemic is the near-real-time identification of potentially fitness-altering mutations within rapidly growing SARS-CoV-2 lineages. Although powerful molecular sequence analysis methods are available to detect and characterize patterns of natural selection within modestly sized gene-sequence datasets, the computational complexity of these methods and their sensitivity to sequencing errors render them effectively inapplicable in large-scale genomic surveillance contexts. Motivated by the need to analyze new lineage evolution in near-real time using large numbers of genomes, we developed the Rapid Assessment of Selection within CLades (RASCL) pipeline. RASCL applies state of the art phylogenetic comparative methods to evaluate selective processes acting at individual codon sites and across whole genes. RASCL is scalable and produces automatically updated regular lineage-specific selection analysis reports: even for lineages that include tens or hundreds of thousands of sampled genome sequences. Key to this performance is (i) generation of automatically subsampled high quality datasets of gene/ORF sequences drawn from a selected "query" viral lineage; (ii) contextualization of these query sequences in codon alignments that include high-quality "background" sequences representative of global SARS-CoV-2 diversity; and (iii) the extensive parallelization of a suite of computationally intensive selection analysis tests. Within hours of being deployed to analyze a novel rapidly growing lineage of interest, RASCL will begin yielding JavaScript Object Notation (JSON)-formatted reports that can be either imported into third-party analysis software or explored in standard web-browsers using the premade RASCL interactive data visualization dashboard. By enabling the rapid detection of genome sites evolving under different selective regimes, RASCL is well-suited for near-real-time monitoring of the population-level selective processes that will likely underlie the emergence of future variants of concern in measurably evolving pathogens with extensive genomic surveillance.

Hepatitis B virus (HBV) codon adapts well to the gene expression profile of liver cancer: an evolutionary explanation for HBV's oncogenic role.

Due to the evolutionary arms race between hosts and viruses, viruses must adapt to host translation systems to rapidly synthesize viral proteins. Highly expressed genes in hosts have a codon bias related to tRNA abundance, the primary RNA translation rate determinant. We calculated the relative synonymous codon usage (RSCU) of three hepatitis viruses (HAV, HBV, and HCV), SARS-CoV-2, 30 human tissues, and hepatocellular carcinoma (HCC). After comparing RSCU between viruses and human tissues, we calculated the codon adaptation index (CAI) of viral and human genes. HBV and HCV showed the highest correlations with HCC and the normal liver, while SARS-CoV-2 had the strongest association with lungs. In addition, based on HCC RSCU, the CAI of HBV and HCV genes was the highest. HBV and HCV preferentially adapt to the tRNA pool in HCC, facilitating viral RNA translation. After an initial trigger, rapid HBV/HCV translation and replication may change normal liver cells into HCC cells. Our findings reveal a novel perspective on virus-mediated oncogenesis.

Comprehensive analysis of codon usage patterns of porcine deltacoronavirus and its host adaptability.

The porcine deltacoronavirus (PDCoV) is a newly discovered pig enteric coronavirus that can infect cells from various species. In Haiti, PDCoV infections in children with acute undifferentiated febrile fever were recently reported. Considering the great potential of inter-species transmission of PDCoV, we performed a comprehensive analysis of codon usage patterns and host adaptation profiles of 54 representative PDCoV strains with the spike (S) gene. Phylogenetic analysis of the PDCoV S gene indicates that the PDCoV strains can be divided into five genogroups. We found a certain codon usage bias existed in the S gene, in which the synonymous codons are often ended with U or A. Heat map analysis revealed that all the PDCoV strains shared a similar codon usage trend. The PDCoV S gene with a dN/dS ratio lower than 1 reveals a negative selection on the PDCoV S gene. Neutrality analysis showed that natural selection is the dominant force in shaping the codon usage bias of the PDCoV S gene. Unexpectedly, host adaptation analysis reveals a higher adaptation level of PDCoV to Homo sapiens and Gallus gallus than to Sus scrofa. Compared to the USA lineage, the PDCoV strains in the Early China lineage and Thailand lineage were less adapted to their hosts, which indicates that the evolutionary process plays an important role in the adaptation ability of PDCoV. These findings of this study add to our understanding of PDCoV's evolution, adaptability, and inter-species transmission.

Expression of Codon-Optimized Gene Encoding Murine Moloney Leukemia Virus Reverse Transcriptase in Escherichia coli.

Moloney murine leukemia virus reverse transcriptase (MMLV-RT) is the most frequently used enzyme in molecular biology for cDNA synthesis. To date, reverse transcription coupled with Polymerase Chain Reaction, known as RT-PCR, has been popular as an excellent approach for the detection of SARS-CoV-2 during the COVID-19 pandemic. In this study, we aimed to improve the enzymatic production and performance of MMLV-RT by optimizing both codon and culture conditions in E. coli expression system. By applying the optimized codon and culture conditions, the enzyme was successfully overexpressed and increased at high level based on the result of SDS-PAGE and Western blotting. The total amount of MMLV-RT has improved 85-fold from 0.002 g L-1 to 0.175 g L-1 of culture. One-step purification by nickel affinity chromatography has been performed to generate the purified enzyme for further analysis of qualitative and quantitative RT activity. Overall, our investigation provides useful strategies to enhance the recombinant enzyme of MMLV-RT in both production and performance. More importantly, the enzyme has shown promising activity to be used for RT-PCR assay.

NGS data vectorization, clustering, and finding key codons in SARS-CoV-2 variations.

The rapid global spread and dissemination of SARS-CoV-2 has provided the virus with numerous opportunities to develop several variants. Thus, it is critical to determine the degree of the variations and in which part of the virus those variations occurred. Therefore, in this study, methods that could be used to vectorize the sequence data, perform clustering analysis, and visualize the results were proposed using machine learning methods. To conduct this study, a total of 224,073 cases of SARS-CoV-2 sequence data were collected through NCBI and GISAID, and the data were visualized using dimensionality reduction and clustering analysis models such as T-SNE and DBSCAN. The SARS-CoV-2 virus, which was first detected, was distinguished from different variations, including Omicron and Delta, in the cluster results. Furthermore, it was possible to examine which codon changes in the spike protein caused the variants to be distinguished using feature importance extraction models such as Random Forest or Shapely Value. The proposed method has the advantage of being able to analyse and visualize a large amount of data at once compared to the existing tree-based sequence data analysis. The proposed method was able to identify and visualize significant changes between the SARS-CoV-2 virus, which was first detected in Wuhan, China, in December 2019, and the newly formed mutant virus group. As a result of clustering analysis using sequence data, it was possible to confirm the formation of clusters among various variants in a two-dimensional graph, and by extracting the importance of variables, it was possible to confirm which codon changes played a major role in distinguishing variants. Furthermore, since the proposed method can handle a variety of data sequences, it can be used for all kinds of diseases, including influenza and SARS-CoV-2. Therefore, the proposed method has the potential to become widely used for the effective analysis of disease variations.

Codon Usage and Phenotypic Divergences of SARS-CoV-2 Genes.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which first occurred in Wuhan (China) in December of 2019, causes a severe acute respiratory illness with a high mortality rate, and has spread around the world. To gain an understanding of the evolution of the newly emerging SARS-CoV-2, we herein analyzed the codon usage pattern of SARS-CoV-2. For this purpose, we compared the codon usage of SARS-CoV-2 with that of other viruses belonging to the subfamily of Orthocoronavirinae. We found that SARS-CoV-2 has a high AU content that strongly influences its codon usage, which appears to be better adapted to the human host. We also studied the evolutionary pressures that influence the codon usage of five conserved coronavirus genes encoding the viral replicase, spike, envelope, membrane and nucleocapsid proteins. We found different patterns of both mutational bias and natural selection that affect the codon usage of these genes. Moreover, we show here that the two integral membrane proteins (matrix and envelope) tend to evolve slowly by accumulating nucleotide mutations on their corresponding genes. Conversely, genes encoding nucleocapsid (N), viral replicase and spike proteins (S), although they are regarded as are important targets for the development of vaccines and antiviral drugs, tend to evolve faster in comparison to the two genes mentioned above. Overall, our results suggest that the higher divergence observed for the latter three genes could represent a significant barrier in the development of antiviral therapeutics against SARS-CoV-2.

Chemical modifications to mRNA nucleobases impact translation elongation and termination.

Messenger RNAs (mRNAs) serve as blueprints for protein synthesis by the molecular machine the ribosome. The ribosome relies on hydrogen bonding interactions between adaptor aminoacyl-transfer RNA molecules and mRNAs to ensure the rapid and faithful translation of the genetic code into protein. There is a growing body of evidence suggesting that chemical modifications to mRNA nucleosides impact the speed and accuracy of protein synthesis by the ribosome. Modulations in translation rates have downstream effects beyond protein production, influencing protein folding and mRNA stability. Given the prevalence of such modifications in mRNA coding regions, it is imperative to understand the consequences of individual modifications on translation. In this review we present the current state of our knowledge regarding how individual mRNA modifications influence ribosome function. Our comprehensive comparison of the impacts of 16 different mRNA modifications on translation reveals that most modifications can alter the elongation step in the protein synthesis pathway. Additionally, we discuss the context dependence of these effects, highlighting the necessity of further study to uncover the rules that govern how any given chemical modification in an mRNA codon is read by the ribosome.

Evolution of Viral Pathogens Follows a Linear Order.

Although 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.

Human SARS-CoV-2 has evolved to increase U content and reduce genome size.

Infections caused by SARS-CoV-2 have brought great harm to human health. After transmission for over two years, SARS-CoV-2 has diverged greatly and formed dozens of different lineages. Understanding the trend of its genome evolution could help foresee difficulties in controlling transmission of the virus. In this study, we conducted an extensive monthly survey and in-depth analysis on variations of nucleotide, amino acid and codon numbers in 311,260 virus samples collected till January 2022. The results demonstrate that the evolution of SARS-CoV-2 is toward increasing U-content and reducing genome-size. C, G and A to U mutations have all contributed to this U-content increase. Mutations of C, G and A at codon position 1, 2 or 3 have no significant difference in most SARS-CoV-2 lineages. Current viruses are more cryptic and more efficient in replication, and are thus less virulent yet more infectious. Delta and Omicron variants have high mutability over other lineages, bringing new threat to human health. This trend of genome evolution may provide a clue for tracing the origin of SARS-CoV-2, because ancestral viruses should have lower U-content and probably bigger genome-size.

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.

Codon usage divergence in Delta variants (B.1.617.2) of SARS-CoV-2.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spreads all over the world and brings great harm to humans in many countries. Many new SARS-CoV-2 variants appeared during its transmission. In the present study, the Delta variants (B.1.617.2) of SARS-CoV-2, which have appeared in many countries, were considered for analysis. In order to evaluate the evolutionary divergence of the Delta variants(B.1.617.2), the codon usage divergence in Delta variants (B.1.617.2) of SARS-CoV-2 was compared to that of the SARS-CoV-2 genomes emerged before June 2020. All Delta variants (B.1.617.2) and 350 early genomes of SARS-CoV-2 in the NCBI database were downloaded. Codon usage pattern including the basic composition, the GC ratio of the third position (GC3) and the first two positions (GC12) in codons, overall GC contents, the effective number of codons (ENC), the codon bias index (CBI), the relative synonymous codon usage (RSCU) values, etc., of all concerned important gene sequences were all calculated. Codon usage divergence of them was calculated via summing their standard deviations. The results suggested that base compositions in both Delta variants (B.1.617.2) of SARS-CoV-2 and the early SARS-CoV-2 genomes were similar to each other. However, the internal codon usage divergence for most genes in Delta variants (B.1.617.2) was significantly wider than that of SARS-CoV-2. The RSCU values were further used to explore the synonymous and non-synonymous mutations in the sequences of the Delta variants (B.1.617.2), and the results showed the synonymous mutations are more obvious than the non-synonymous in the concerned sequences. The related codon usage divergence analysis is helpful for further study on the adaptability and disease prognosis of the SARS-CoV-2 variants.

Polymorphic landscape of SARS-CoV-2 genomes isolated from Indian population in 2020 demonstrates rapid evolution in ORF3a, ORF8, nucleocapsid phosphoprotein and spike glycoprotein.

India, with around 15 million COVID-19 cases, recently became the second worst-hit nation by the SARS-CoV-2 pandemic. In this study, we analyzed the mutation and selection landscape of 516 unique and complete genomes of SARS-CoV-2 isolates from India in a 12-month span (from Jan to Dec 2020) to understand how the virus is evolving in this geographical region. We identified 953 genome-wide loci displaying single nucleotide polymorphism (SNP) and the Principal Component Analysis and mutation plots of the datasets indicate an increase in genetic variance with time. The 42% of the polymorphic sites display substitutions in the third nucleotide position of codons indicating that non-synonymous substitutions are more prevalent. These isolates displayed strong evidence of purifying selection in ORF1ab, spike, nucleocapsid, and membrane glycoprotein. We also find some evidence of localized positive selections ORF1ab, spike glycoprotein, and nucleocapsid. The CDSs for ORF3a, ORF8, nucleocapsid phosphoprotein, and spike glycoprotein were found to evolve at rapid rate. This study will be helpful in understanding the dynamics of rapidly evolving SARS-CoV-2.

The emergence and ongoing convergent evolution of the SARS-CoV-2 N501Y lineages.

The independent emergence late in 2020 of the B.1.1.7, B.1.351, and P.1 lineages of SARS-CoV-2 prompted renewed concerns about the evolutionary capacity of this virus to overcome public health interventions and rising population immunity. Here, by examining patterns of synonymous and non-synonymous mutations that have accumulated in SARS-CoV-2 genomes since the pandemic began, we find that the emergence of these three "501Y lineages" coincided with a major global shift in the selective forces acting on various SARS-CoV-2 genes. Following their emergence, the adaptive evolution of 501Y lineage viruses has involved repeated selectively favored convergent mutations at 35 genome sites, mutations we refer to as the 501Y meta-signature. The ongoing convergence of viruses in many other lineages on this meta-signature suggests that it includes multiple mutation combinations capable of promoting the persistence of diverse SARS-CoV-2 lineages in the face of mounting host immune recognition.

SARS-CoV-2 has the advantage of competing the iMet-tRNAs with human hosts to allow efficient translation.

To better understand the interaction between SARS-CoV-2 and human host and find potential ways to block the pandemic, one of the unresolved questions is that how the virus economically utilizes the resources of the hosts. Particularly, the tRNA pool has been adapted to the host genes. If the virus intends to translate its own RNA, then it has to compete with the abundant host mRNAs for the tRNA molecules. Translation initiation is the rate-limiting step during protein synthesis. The tRNAs carrying the initiation Methionine (iMet) recognize the start codon termed initiation ATG (iATG). Other normal Met-carrying tRNAs recognize the internal ATGs. The tAI of virus genes is significantly lower than the tAI of human genes. This disadvantage in translation elongation of viral RNAs must be compensated by more efficient initiation rates. In the human genome, the abundance of iMet-tRNAs to Met-tRNAs is five times higher than the iATG to ATG ratio. However, when SARS-CoV-2 infects human cells, the iMet has an 8.5-time enrichment to iATG. We collected 58 virus species and found that the enrichment of iMet is higher in all viruses compared to human. Our study indicates that the genome sequences of viruses like SARS-CoV-2 have the advantage of competing for the iMet-tRNAs with host mRNAs. The capture of iMet-tRNAs allows the fast translation initiation and the reproduction of virus itself, which compensates the lower tAI of viral genes. This might explain why the virus could rapidly translate its own RNA and reproduce itself from the sea of host mRNAs. Meanwhile, our study reminds the researchers not to ignore the mutations related to ATGs.

Betacoronaviruses genome analysis reveals evolution toward specific codons usage: Implications for SARS-CoV-2 mitigation strategies.

Since the start of the coronavirus disease 2019 (COVID-19) pandemic, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has rapidly widespread worldwide becoming one of the major global public health issues of the last centuries. Currently, COVID-19 vaccine rollouts are finally upon us carrying the hope of herd immunity once a sufficient proportion of the population has been vaccinated or infected, as a new horizon. However, the emergence of SARS-CoV-2 variants brought concerns since, as the virus is exposed to environmental selection pressures, it can mutate and evolve, generating variants that may possess enhanced virulence. Codon usage analysis is a strategy to elucidate the evolutionary pressure of the viral genome suffered by different hosts, as possible cause of the emergence of new variants. Therefore, to get a better picture of the SARS-CoV-2 codon bias, we first identified the relative codon usage rate of all Betacoronaviruses lineages. Subsequently, we correlated putative cognate transfer ribonucleic acid (tRNAs) to reveal how those viruses adapt to hosts in relation to their preferred codon usage. Our analysis revealed seven preferred codons located in three different open reading frame which appear preferentially used by SARS-CoV-2. In addition, the tRNA adaptation analysis indicates a wide strategy of competition between the virus and mammalian as principal hosts highlighting the importance to reinforce the genomic monitoring to prompt identify any potential adaptation of the virus into new potential hosts which appear to be crucial to prevent and mitigate the pandemic.

Compositional biases in RNA viruses: Causes, consequences and applications.

If each of the four nucleotides were represented equally in the genomes of viruses and the hosts they infect, each base would occur at a frequency of 25%. However, this is not observed in nature. Similarly, the order of nucleotides is not random (e.g., in the human genome, guanine follows cytosine at a frequency of ~0.0125, or a quarter the number of times predicted by random representation). Codon usage and codon order are also nonrandom. Furthermore, nucleotide and codon biases vary between species. Such biases have various drivers, including cellular proteins that recognize specific patterns in nucleic acids, that once triggered, induce mutations or invoke intrinsic or innate immune responses. In this review we examine the types of compositional biases identified in viral genomes and current understanding of the evolutionary mechanisms underpinning these trends. Finally, we consider the potential for large scale synonymous recoding strategies to engineer RNA virus vaccines, including those with pandemic potential, such as influenza A virus and Severe Acute Respiratory Syndrome Coronavirus Virus 2. This article is categorized under: RNA in Disease and Development > RNA in Disease RNA Evolution and Genomics > Computational Analyses of RNA RNA Interactions with Proteins and Other Molecules > Protein-RNA Recognition.

Designing of Potential Polyvalent Vaccine Model for Respiratory Syncytial Virus by System Level Immunoinformatics Approaches.

BACKGROUND: Respiratory syncytial virus (RSV) infection is a public health epidemic, leading to around 3 million hospitalization and about 66,000 deaths each year. It is a life-threatening condition exclusive to children with no effective treatment. METHODS: In this study, we used system-level and vaccinomics approaches to design a polyvalent vaccine for RSV, which could stimulate the immune components of the host to manage this infection. Our framework involves data accession, antigenicity and subcellular localization analysis, T cell epitope prediction, proteasomal and conservancy evaluation, host-pathogen-protein interactions, pathway studies, and in silico binding affinity analysis. RESULTS: We found glycoprotein (G), fusion protein (F), and small hydrophobic protein (SH) of RSV as potential vaccine candidates. Of these proteins (G, F, and SH), we found 9 epitopes for multiple alleles of MHC classes I and II bear significant binding affinity. These potential epitopes were linked to form a polyvalent construct using AAY, GPGPG linkers, and cholera toxin B adjuvant at N-terminal with a 23.9 kDa molecular weight of 224 amino acid residues. The final construct was a stable, immunogenic, and nonallergenic protein containing cleavage sites, TAP transport efficiency, posttranslation shifts, and CTL epitopes. The molecular docking indicated the optimum binding affinity of RSV polyvalent construct with MHC molecules (-12.49 and -10.48 kcal/mol for MHC classes I and II, respectively). This interaction showed that a polyvalent construct could manage and control this disease. CONCLUSION: Our vaccinomics and system-level investigation could be appropriate to trigger the host immune system to prevent RSV infection.

Comparative analysis of human coronaviruses focusing on nucleotide variability and synonymous codon usage patterns.

The prevailing COVID-19 pandemic has drawn the attention of the scientific community to study the evolutionary origin of Severe Acute Respiratory Syndrome Corona Virus 2 (SARS-CoV-2). This study is a comprehensive quantitative analysis of the protein-coding sequences of seven human coronaviruses (HCoVs) to decipher the nucleotide sequence variability and codon usage patterns. It is essential to understand the survival ability of the viruses, their adaptation to hosts, and their evolution. The current analysis revealed a high abundance of the relative dinucleotide (odds ratio), GC and CT pairs in the first and last two codon positions, respectively, as well as a low abundance of the CG pair in the last two positions of the codon, which might be related to the evolution of the viruses. A remarkable level of variability of GC content in the third position of the codon among the seven coronaviruses was observed. Codons with high RSCU values are primarily from the aliphatic and hydroxyl amino acid groups, and codons with low RSCU values belong to the aliphatic, cyclic, positively charged, and sulfur-containing amino acid groups. In order to elucidate the evolutionary processes of the seven coronaviruses, a phylogenetic tree (dendrogram) was constructed based on the RSCU scores of the codons. The severe and mild categories CoVs were positioned in different clades. A comparative phylogenetic study with other coronaviruses depicted that SARS-CoV-2 is close to the CoV isolated from pangolins (Manis javanica, Pangolin-CoV) and cats (Felis catus, SARS(r)-CoV). Further analysis of the effective number of codon (ENC) usage bias showed a relatively higher bias for SARS-CoV and MERS-CoV compared to SARS-CoV-2. The ENC plot against GC3 suggested that the mutational bias might have a role in determining the codon usage variation among candidate viruses. A codon adaptability study on a few human host parasites (from different kingdoms), including CoVs, showed a diverse adaptability pattern. SARS-CoV-2 and SARS-CoV exhibit relatively lower but similar codon adaptability compared to MERS-CoV.