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

Fitness and adaptive evolution of a Rhodococcus sp. harboring dioxin-catabolic plasmids

Catabolic plasmids are critical factors in the degradation of recalcitrant xenobiotics, such as dioxins. Understanding the persistence and evolution of native catabolic plasmids is pivotal for controlling their function in microbial remediation. Here, we track the fitness and evolution of Rhodococcus sp. strain p52 harboring dioxin-catabolic plasmids under nonselective conditions without contaminant. Growth curve analysis and competition experiments demonstrated that pDF01 imposed fitness costs, whereas pDF02 conferred fitness benefits. During stability tests, pDF01 tended to be lost from the population, while pDF02 maintained at least one copy in the cell until proliferation of the 400th generation. Genome-wide gene expression profiling combined with codon usage bias analysis revealed that the high expression of pDF01 genes involved in dibenzofuran catabolism and regulation caused metabolic burdens. In contrast, potential cooperation between the pDF02-encoded short-chain dehydrogenase/reductase family oxidoreductase and the redox cofactor mycofactocin, which synthetic genes are located on the chromosome, may explain the benefit of pDF02. The fitness cost imposed by pDF01 was alleviated during adaptive evolution and was associated with the transcriptional downregulation of the dibenzofuran degradation genes on pDF01, and the global regulation of genome-wide gene expression involving basic metabolism, transport, and signal transduction. This study broadens our understandings on the persistence and evolution of dioxin-catabolic mega-plasmids, thus paving the way for the bioremediation of recalcitrant xenobiotic pollution in the environment.

Time Reveals the Truth! What Treatments for COVID-19 Were Quickly Abandoned, and Which Methods, Contrary to Popular Belief, Are Still Flourishing?

During the early days of the COVID-19 pandemic, low dose radiation therapy (LDRT) was proposed as a potentially effective treatment method. To minimize potential toxicity, the initial treatment approach involved a few mGy of adapting radiation followed by a single 250 mGy whole lung challenging dose. However, antiviral drugs were also introduced as a promising treatment option, which were thought to have the potential to revolutionize the management of the crisis. Despite early warnings, many physicians did not fully consider the key point that, in contrast with LDRT, antiviral drug treatments can result in strong selective pressure on the virus. This can lead to the emergence of new SARS-CoV-2 variants, a phenomenon that can have serious global consequences. After more than two years, the truth has been revealed the WHO Guideline Development Group has advised against the use of remdesivir, a widely used antiviral medication, for COVID-19. Meanwhile, a growing body of evidence suggests that LDRT can be a promising, low-risk approach for avoiding or delaying invasive respiratory support in COVID-19 patients. Although there is substantial supporting documentation, more high-quality, controlled, and randomized double-blind clinical trials are needed to further investigate the efficacy and potential therapeutic mechanisms of LDRT for COVID-19.

Severe acute respiratory syndrome Coronavirus-2 GenoAnalyzer and mutagenic anomaly detector using FCMFI and NSCE

In order to deepen our understanding of the virus and help guide the creation of efficient therapies, this study uses artificial intelligence tools to thoroughly explore the genetic sequences of the SARS-CoV-2 virus. The process starts by using the Fuzzy Closure Miner for Frequent Itemsets (FCMFI) on a large corpus of SARS-CoV-2 genomic sequences to reveal hidden patterns, including nucleotides base sequences, repeating motifs, and corresponding interchanges. Then, using the Nucleotide Sequence Comprehension Engine (NSCE) technique, we were able to precisely define the genomic areas for mutation analysis. Structured and unstructured proteins are both strongly impacted by virus mutations, with spike proteins that are linked to the severity of COVID-19 pneumonia being particularly affected. Notably, the Mutagenic Anomaly Detector shows a 65 % efficiency boost in computing genome mutation rates compared to conventional point mutation analysis, while GenoAnalyzer offers a remarkable 93.33 % improvement over existing approaches in recognizing common genomic sequence patterns. These results highlight the potential of FCMFI to reveal complex genomic patterns and significant insights in COVID-19 genetic sequences when combined with mutation analysis. The Mutagenic Anomaly Detector and GenoAnalyzer show promise for revealing hidden genomic patterns and precisely estimating the SARS-CoV-2 mutation rate.

Analysis of codon usage patterns of porcine enteric alphacoronavirus and its host adaptability

Porcine enteric alphacoronavirus (PEAV) is a newly emerging swine enteropathogen that poses a threat to the swine industry. To understand the PEAV genome evolution, we performed a comprehensive analysis of the codon usage patterns in fifty-nine PEAV strains currently available. Phylogenetic analysis showed that PEAV can be divided into six lineages. Effective number of codons analysis demonstrated that the PEAV genome exhibits a low codon usage bias (CUB). Nucleotide composition analysis indicated that the PEAV genome has the most abundant nucleotide U content, with GC content (39.37% ± 0.08%) much lower than AU content (60.63% ± 0.08%). Neutrality and effective number of codons plot analyses suggested that natural selection rather than mutation pressure dominates the CUB of PEAV. Host adaptation analysis revealed that PEAV fits the codon usage pattern of non-human primates, humans and mice better than that of pigs. Our data enriches information on PEAV evolution, host adaptability, and cross-species transmission.

Optimization and Deoptimization of Codons in SARS-CoV-2 and Related Implications for Vaccine Development

The spread of coronavirus disease 2019 (COVID-19), caused by severe respiratory syndrome coronavirus 2 (SARS-CoV-2), has progressed into a global pandemic. To date, thousands of genetic variants have been identified among SARS-CoV-2 isolates collected from patients. Sequence analysis reveals that the codon adaptation index (CAI) values of viral sequences have decreased over time but with occasional fluctuations. Through evolution modeling, it is found that this phenomenon may result from the virus's mutation preference during transmission. Using dual-luciferase assays, it is further discovered that the deoptimization of codons in the viral sequence may weaken protein expression during virus evolution, indicating that codon usage may play an important role in virus fitness. Finally, given the importance of codon usage in protein expression and particularly for mRNA vaccines, it is designed several codon-optimized Omicron BA.2.12.1, BA.4/5, and XBB.1.5 spike mRNA vaccine candidates and experimentally validated their high levels of expression. This study highlights the importance of codon usage in virus evolution and provides guidelines for codon optimization in mRNA and DNA vaccine development.

Comparative Analysis of Codon Usage Patterns in Nuclear and Chloroplast Genome of Dalbergia (Fabaceae)

The Dalbergia plants are widely distributed across more than 130 tropical and subtropical countries and have significant economic and medicinal value. Codon usage bias (CUB) is a critical feature for studying gene function and evolution, which can provide a better understanding of biological gene regulation. In this study, we comprehensively analyzed the CUB patterns of the nuclear genome, chloroplast genome, and gene expression, as well as systematic evolution of Dalbergia species. Our results showed that the synonymous and optimal codons in the coding regions of both nuclear and chloroplast genome of Dalbergia preferred ending with A/U at the third codon base. Natural selection was the primary factor affecting the CUB features. Furthermore, in highly expressed genes of Dalbergia odorifera, we found that genes with stronger CUB exhibited higher expression levels, and these highly expressed genes tended to favor the use of G/C-ending codons. In addition, the branching patterns of the protein-coding sequences and the chloroplast genome sequences were very similar in the systematic tree, and different with the cluster from the CUB of the chloroplast genome. This study highlights the CUB patterns and features of Dalbergia species in different genomes, explores the correlation between CUB preferences and gene expression, and further investigates the systematic evolution of Dalbergia, providing new insights into codon biology and the evolution of Dalbergia plants.

Variation in synonymous evolutionary rates in the SARS-CoV-2 genome

Introduction

Coronavirus disease 2019 is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Influential variants and mutants of this virus continue to emerge, and more effective virus-related information is urgently required for identifying and predicting new mutants. According to earlier reports, synonymous substitutions were considered phenotypically silent; thus, such mutations were frequently ignored in studies of viral mutations because they did not directly cause amino acid changes. However, recent studies have shown that synonymous substitutions are not completely silent, and their patterns and potential functional correlations should thus be delineated for better control of the pandemic.

Methods

In this study, we estimated the synonymous evolutionary rate (SER) across the SARS-CoV-2 genome and used it to infer the relationship between the viral RNA and host protein. We also assessed the patterns of characteristic mutations found in different viral lineages.

Results

We found that the SER varies across the genome and that the variation is primarily influenced by codon-related factors. Moreover, the conserved motifs identified based on the SER were found to be related to host RNA transport and regulation. Importantly, the majority of the existing fixed-characteristic mutations for five important virus lineages (Alpha, Beta, Gamma, Delta, and Omicron) were significantly enriched in partially constrained regions.

Discussion

Taken together, our results provide unique information on the evolutionary and functional dynamics of SARS-CoV-2 based on synonymous mutations and offer potentially useful information for better control of the SARS-CoV-2 pandemic.

Comparative analysis of adenylate isopentenyl transferase genes in plant growth-promoting bacteria and plant pathogenic bacteria

Cytokinin is a major phytohormone that has been used in agriculture as a plant-growth stimulating compound since its initial discovery in the 1960s. Isopentenyl transferase (IPT) is a rate-limiting enzyme for cytokinin biosynthesis, which is produced by plants as well as bacteria including both plant pathogenic species and plant growth-promoting bacteria (PGPB). It has been hypothesized that there may be differences in IPT function between plant pathogens and PGPB. However, a comprehensive comparison of IPT genes between plant pathogenic and PGPB species has not been performed. Here, we performed a global comparison of IPT genes across bacteria, analyzing their DNA sequences, codon usage, phyletic distribution, promoter structure and genomic context. We found that adenylate type IPT genes are highly specific to plant-associated bacteria and subdivide into two major clades: clade A, largely composed of proteobacterial plant pathogens; and clade B, largely composed of actinomycete PGPB species. Besides these phylogenetic differences, we identified several genomic features that suggest differences in IPT regulation between pathogens and PGPB. Pathogen-associated IPTs tended to occur in predicted virulence loci, whereas PGPB-associated IPTs tended to co-occur with other genes involved in cytokinin metabolism and degradation. Pathogen-associated IPTs also showed elevated gene copy numbers, significant deviation in codon usage patterns, and extended promoters, suggesting differences in regulation and activity levels. Our results are consistent with the hypothesis that differences in IPT regulation and activity exist between plant pathogens and PGPB, which determine their effect on plant host phenotypes through the control of cytokinin levels.

Correlated substitutions reveal SARS-like coronaviruses recombine frequently with a diverse set of structured gene pools

Quantifying SARS-like coronavirus (SL-CoV) evolution is critical to understanding the origins of SARS-CoV-2 and the molecular processes that could underlie future epidemic viruses. While genomic analyses suggest recombination was a factor in the emergence of SARS-CoV-2, few studies have quantified recombination rates among SL-CoVs. Here, we infer recombination rates of SL-CoVs from correlated substitutions in sequencing data using a coalescent model with recombination. Our computationally-efficient, non-phylogenetic method infers recombination parameters of both sampled sequences and the unsampled gene pools with which they recombine. We apply this approach to infer recombination parameters for a range of positive-sense RNA viruses. We then analyze a set of 191 SL-CoV sequences (including SARS-CoV-2) and find that ORF1ab and S genes frequently undergo recombination. We identify which SL-CoV sequence clusters have recombined with shared gene pools, and show that these pools have distinct structures and high recombination rates, with multiple recombination events occurring per synonymous substitution. We find that individual genes have recombined with different viral reservoirs. By decoupling contributions from mutation and recombination, we recover the phylogeny of non-recombined portions for many of these SL-CoVs, including the position of SARS-CoV-2 in this clonal phylogeny. Lastly, by analyzing >400,000 SARS-CoV-2 whole genome sequences, we show current diversity levels are insufficient to infer the within-population recombination rate of the virus since the pandemic began. Our work offers new methods for inferring recombination rates in RNA viruses with implications for understanding recombination in SARS-CoV-2 evolution and the structure of clonal relationships and gene pools shaping its origins.

In Vitro and In Silico Studies for the Identification of Potent Metabolites of Some High-Altitude Medicinal Plants from Nepal Inhibiting SARS-CoV-2 Spike Protein

Despite ongoing vaccination programs against COVID-19 around the world, cases of infection are still rising with new variants. This infers that an effective antiviral drug against COVID-19 is crucial along with vaccinations to decrease cases. A potential target of such antivirals could be the membrane components of the causative pathogen, SARS-CoV-2, for instance spike (S) protein. In our research, we have deployed in vitro screening of crude extracts of seven ethnomedicinal plants against the spike receptor-binding domain (S1-RBD) of SARS-CoV-2 using an enzyme-linked immunosorbent assay (ELISA). Following encouraging in vitro results for Tinospora cordifolia, in silico studies were conducted for the 14 reported antiviral secondary metabolites isolated from T. cordifolia-a species widely cultivated and used as an antiviral drug in the Himalayan country of Nepal-using Genetic Optimization for Ligand Docking (GOLD), Molecular Operating Environment (MOE), and BIOVIA Discovery Studio. The molecular docking and binding energy study revealed that cordifolioside-A had a higher binding affinity and was the most effective in binding to the competitive site of the spike protein. Molecular dynamics (MD) simulation studies using GROMACS 5.4.1 further assayed the interaction between the potent compound and binding sites of the spike protein. It revealed that cordifolioside-A demonstrated better binding affinity and stability, and resulted in a conformational change in S1-RBD, hence hindering the activities of the protein. In addition, ADMET analysis of the secondary metabolites from T. cordifolia revealed promising pharmacokinetic properties. Our study thus recommends that certain secondary metabolites of T. cordifolia are possible medicinal candidates against SARS-CoV-2.

The Advantage of Using Immunoinformatic Tools on Vaccine Design and Development for Coronavirus

After the outbreak of SARS-CoV-2 by the end of 2019, the vaccine development strategies became a worldwide priority. Furthermore, the appearances of novel SARS-CoV-2 variants challenge researchers to develop new pharmacological or preventive strategies. However, vaccines still represent an efficient way to control the SARS-CoV-2 pandemic worldwide. This review describes the importance of bioinformatic and immunoinformatic tools (in silico) for guide vaccine design. In silico strategies permit the identification of epitopes (immunogenic peptides) which could be used as potential vaccines, as well as nonacarriers such as: vector viral based vaccines, RNA-based vaccines and dendrimers through immunoinformatics. Currently, nucleic acid and protein sequential as well structural analyses through bioinformatic tools allow us to get immunogenic epitopes which can induce immune response alone or in complex with nanocarriers. One of the advantages of in silico techniques is that they facilitate the identification of epitopes, while accelerating the process and helping to economize some stages of the development of safe vaccines.

Molecular adaptations during viral epidemics

In 1977, the world witnessed both the eradication of smallpox and the beginning of the modern age of genomics. Over the following half-century, 7 epidemic viruses of international concern galvanized virologists across the globe and led to increasingly extensive virus genome sequencing. These sequencing efforts exerted over periods of rapid adaptation of viruses to new hosts, in particular, humans provide insight into the molecular mechanisms underpinning virus evolution. Investment in virus genome sequencing was dramatically increased by the unprecedented support for phylogenomic analyses during the COVID-19 pandemic. In this review, we attempt to piece together comprehensive molecular histories of the adaptation of variola virus, HIV-1 M, SARS, H1N1-SIV, MERS, Ebola, Zika, and SARS-CoV-2 to the human host. Disruption of genes involved in virus-host interaction in animal hosts, recombination including genome segment reassortment, and adaptive mutations leading to amino acid replacements in virus proteins involved in host receptor binding and membrane fusion are identified as the key factors in the evolution of epidemic viruses.

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.

Comprehensive analysis of codon usage pattern in Withania somnifera and its associated pathogens: Meloidogyne incognita and Alternaria alternata

Meloidogyne incognita (Root-knot nematode) and Alternaria alternata (fungus) were among the dominant parasites of the medicinal plant Withania somnifera. Despite the fatal nature of their infection, a comprehensive study to explore their evolution and adaptation is lacking. The present study elucidates evolutionary and codon usage bias analysis of W. somnifera (host plant), M. incognita (root-knot nematode) and A. alternata (fungal parasite). The results of the present study revealed a weak codon usage bias prevalent in all the three organisms. Based on the nucleotide analysis, genome of W. somnifera and M. incognita was found to be A-T biased while A. alternata had GC biased genome. We found high similarity of CUB pattern between host and its nematode pathogen as compared to the fungal pathogen. Inclusively, both the evolutionary forces influenced the CUB in host and its associated pathogens. However, neutrality plot indicated the pervasiveness of natural selection on CUB of the host and its pathogens. Correspondence analysis revealed the dominant effect of mutation on CUB of W. somnifera and M. incognita while natural selection was the main force affecting CUB of A. alternata. Taken together the present study would provide some prolific insight into the role of codon usage bias in the adaptability of pathogens to the host’s environment for establishing parasitic relationship.

Statistical modeling of SARS-CoV-2 substitution processes: predicting the next variant

We build statistical models to describe the substitution process in the SARS-CoV-2 as a function of explanatory factors describing the sequence, its function, and more. These models serve two different purposes: first, to gain knowledge about the evolutionary biology of the virus; and second, to predict future mutations in the virus, in particular, non-synonymous amino acid substitutions creating new variants. We use tens of thousands of publicly available SARS-CoV-2 sequences and consider tens of thousands of candidate models. Through a careful validation process, we confirm that our chosen models are indeed able to predict new amino acid substitutions: candidates ranked high by our model are eight times more likely to occur than random amino acid changes. We also show that named variants were highly ranked by our models before their appearance, emphasizing the value of our models for identifying likely variants and potentially utilizing this knowledge in vaccine design and other aspects of the ongoing battle against COVID-19.

As the virus that causes COVID-19 continues to mutate and spread, new methods are needed to predict new potential variants. Here, the authors identify the best regression models for predicting likely mutation sites in the SARS-CoV-2 genome using a candidate set that considers sequence, gene location, and biological function.

SARS-CoV-2 host prediction based on virus-host genetic features

The genetic diversity of the Coronaviruses gives them different biological abilities, such as infect different cells and/or organisms, a wide spectrum of clinical manifestations, their different routes of dispersion, and viral transmission in a specific host. In recent decades, different Coronaviruses have emerged that are highly adapted for humans and causing serious diseases, leaving their host of unknown origin. The viral genome information is particularly important to enable the recognition of patterns linked to their biological characteristics, such as the specificity in the host-parasite relationship. Here, based on a previously computational tool, the Seq2Hosts, we developed a novel approach which uses new variables obtained from the frequency of spike-Coronaviruses codons, the Relative Synonymous Codon Usage (RSCU) to shed new light on the molecular mechanisms involved in the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) host specificity. By using the RSCU obtained from nucleotide sequences before the SARS-CoV-2 pandemic, we assessed the possibility of know the hosts capable to be infected by these new emerging species, which was first identified infecting humans during 2019 in Wuhan, China. According to the model trained and validated using sequences available before the pandemic, bats are the most likely the natural host to the SARS-CoV-2 infection, as previously suggested in other studies that searched for the host viral origin.

Exploring Noncovalent Protease Inhibitors for the Treatment of Severe Acute Respiratory Syndrome and Severe Acute Respiratory Syndrome-Like Coronaviruses

Over the last 20 years, both severe acute respiratory syndrome coronavirus-1 and severe acute respiratory syndrome coronavirus-2 have transmitted from animal hosts to humans causing zoonotic outbreaks of severe disease. Both viruses originate from a group of betacoronaviruses known as subgroup 2b. The emergence of two dangerous human pathogens from this group along with previous studies illustrating the potential of other subgroup 2b members to transmit to humans has underscored the need for antiviral development against them. Coronaviruses modify the host innate immune response in part through the reversal of ubiquitination and ISGylation with their papain-like protease (PLpro). To identify unique or overarching subgroup 2b structural features or enzymatic biases, the PLpro from a subgroup 2b bat coronavirus, BtSCoV-Rf1.2004, was biochemically and structurally evaluated. This evaluation revealed that PLpros from subgroup 2b coronaviruses have narrow substrate specificity for K48 polyubiquitin and ISG15 originating from certain species. The PLpro of BtSCoV-Rf1.2004 was used as a tool alongside PLpro of CoV-1 and CoV-2 to design 30 novel noncovalent drug-like pan subgroup 2b PLpro inhibitors that included determining the effects of using previously unexplored core linkers within these compounds. Two crystal structures of BtSCoV-Rf1.2004 PLpro bound to these inhibitors aided in compound design as well as shared structural features among subgroup 2b proteases. Screening of these three subgroup 2b PLpros against this novel set of inhibitors along with cytotoxicity studies provide new directions for pan-coronavirus subgroup 2b antiviral development of PLpro inhibitors.

Unheeded SARS-CoV-2 proteins? A deep look into negative-sense RNA

SARS-CoV-2 is a novel positive-sense single-stranded RNA virus from the Coronaviridae family (genus Betacoronavirus), which has been established as causing the COVID-19 pandemic. The genome of SARS-CoV-2 is one of the largest among known RNA viruses, comprising of at least 26 known protein-coding loci. Studies thus far have outlined the coding capacity of the positive-sense strand of the SARS-CoV-2 genome, which can be used directly for protein translation. However, it has been recently shown that transcribed negative-sense viral RNA intermediates that arise during viral genome replication from positive-sense viruses can also code for proteins. No studies have yet explored the potential for negative-sense SARS-CoV-2 RNA intermediates to contain protein-coding loci. Thus, using sequence and structure-based bioinformatics methodologies, we have investigated the presence and validity of putative negative-sense ORFs (nsORFs) in the SARS-CoV-2 genome. Nine nsORFs were discovered to contain strong eukaryotic translation initiation signals and high codon adaptability scores, and several of the nsORFs were predicted to interact with RNA-binding proteins. Evolutionary conservation analyses indicated that some of the nsORFs are deeply conserved among related coronaviruses. Three-dimensional protein modeling revealed the presence of higher order folding among all putative SARS-CoV-2 nsORFs, and subsequent structural mimicry analyses suggest similarity of the nsORFs to DNA/RNA-binding proteins and proteins involved in immune signaling pathways. Altogether, these results suggest the potential existence of still undescribed SARS-CoV-2 proteins, which may play an important role in the viral lifecycle and COVID-19 pathogenesis.

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.

Are There Hidden Genes in DNA/RNA Vaccines?

Due to the fast global spreading of the Severe Acute Respiratory Syndrome Coronavirus - 2 (SARS-CoV-2), prevention and treatment options are direly needed in order to control infection-related morbidity, mortality, and economic losses. Although drug and inactivated and attenuated virus vaccine development can require significant amounts of time and resources, DNA and RNA vaccines offer a quick, simple, and cheap treatment alternative, even when produced on a large scale. The spike protein, which has been shown as the most antigenic SARS-CoV-2 protein, has been widely selected as the target of choice for DNA/RNA vaccines. Vaccination campaigns have reported high vaccination rates and protection, but numerous unintended effects, ranging from muscle pain to death, have led to concerns about the safety of RNA/DNA vaccines. In parallel to these studies, several open reading frames (ORFs) have been found to be overlapping SARS-CoV-2 accessory genes, two of which, ORF2b and ORF-Sh, overlap the spike protein sequence. Thus, the presence of these, and potentially other ORFs on SARS-CoV-2 DNA/RNA vaccines, could lead to the translation of undesired proteins during vaccination. Herein, we discuss the translation of overlapping genes in connection with DNA/RNA vaccines. Two mRNA vaccine spike protein sequences, which have been made publicly-available, were compared to the wild-type sequence in order to uncover possible differences in putative overlapping ORFs. Notably, the Moderna mRNA-1273 vaccine sequence is predicted to contain no frameshifted ORFs on the positive sense strand, which highlights the utility of codon optimization in DNA/RNA vaccine design to remove undesired overlapping ORFs. Since little information is available on ORF2b or ORF-Sh, we use structural bioinformatics techniques to investigate the structure-function relationship of these proteins. The presence of putative ORFs on DNA/RNA vaccine candidates implies that overlapping genes may contribute to the translation of smaller peptides, potentially leading to unintended clinical outcomes, and that the protein-coding potential of DNA/RNA vaccines should be rigorously examined prior to administration.

Plasma cell-free RNA characteristics in COVID-19 patients

The pathogenesis of COVID-19 is still elusive, which impedes disease progression prediction, differential diagnosis, and targeted therapy. Plasma cell-free RNAs (cfRNAs) carry unique information from human tissue and thus could point to resourceful solutions for pathogenesis and host-pathogen interactions. Here, we performed a comparative analysis of cfRNA profiles between COVID-19 patients and healthy donors using serial plasma. Analyses of the cfRNA landscape, potential gene regulatory mechanisms, dynamic changes in tRNA pools upon infection, and microbial communities were performed. A total of 380 cfRNA molecules were up-regulated in all COVID-19 patients, of which seven could serve as potential biomarkers (AUC > 0.85) with great sensitivity and specificity. Antiviral (NFKB1A, IFITM3, and IFI27) and neutrophil activation (S100A8, CD68, and CD63)–related genes exhibited decreased expression levels during treatment in COVID-19 patients, which is in accordance with the dynamically enhanced inflammatory response in COVID-19 patients. Noncoding RNAs, including some microRNAs (let 7 family) and long noncoding RNAs (GJA9-MYCBP) targeting interleukin (IL6/IL6R), were differentially expressed between COVID-19 patients and healthy donors, which accounts for the potential core mechanism of cytokine storm syndromes; the tRNA pools change significantly between the COVID-19 and healthy group, leading to the accumulation of SARS-CoV-2 biased codons, which facilitate SARS-CoV-2 replication. Finally, several pneumonia-related microorganisms were detected in the plasma of COVID-19 patients, raising the possibility of simultaneously monitoring immune response regulation and microbial communities using cfRNA analysis. This study fills the knowledge gap in the plasma cfRNA landscape of COVID-19 patients and offers insight into the potential mechanisms of cfRNAs to explain COVID-19 pathogenesis.

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.

Synthetic DNA spike-ins (SDSIs) enable sample tracking and detection of inter-sample contamination in SARS-CoV-2 sequencing workflows

The global spread and continued evolution of SARS-CoV-2 has driven an unprecedented surge in viral genomic surveillance. Amplicon-based sequencing methods provide a sensitive, low-cost and rapid approach but suffer a high potential for contamination, which can undermine laboratory processes and results. This challenge will increase with the expanding global production of sequences across a variety of laboratories for epidemiological and clinical interpretation, as well as for genomic surveillance of emerging diseases in future outbreaks. We present SDSI + AmpSeq, an approach that uses 96 synthetic DNA spike-ins (SDSIs) to track samples and detect inter-sample contamination throughout the sequencing workflow. We apply SDSIs to the ARTIC Consortium's amplicon design, demonstrate their utility and efficiency in a real-time investigation of a suspected hospital cluster of SARS-CoV-2 cases and validate them across 6,676 diagnostic samples at multiple laboratories. We establish that SDSI + AmpSeq provides increased confidence in genomic data by detecting and correcting for relatively common, yet previously unobserved modes of error, including spillover and sample swaps, without impacting genome recovery.

SARS-CoV-2 Variants with T135I Nucleocapsid Mutations may Affect Antigen Test Performance

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a pandemic. Diagnostic testing for SARS-CoV-2 has continuously been challenged due to several variants with diverse spike (S) and nucleocapsid (N) protein mutations []. SARS-CoV-2 variant proliferation potentially affects N protein-targeted rapid antigen testing. In this study, rapid antigen and reverse transcription PCR (RT-PCR) tests were performed simultaneously in patients with suspected coronavirus disease 2019 (COVID-19). Direct whole genome sequencing was performed to determine the N protein variations, and the viral assemblies were uploaded to GISAID. The genomes were then compared with those of global virus strains from GISAID. These isolates belonged to the B.1.1.7 variant, exhibiting several amino acid substitutions, including D3L, R203K, G204R, and S235F N protein mutations. The T135I mutation was also identified in one variant case in which the rapid antigen test and RT-PCR test were discordantly negative and positive, respectively. These findings suggest that the variants undetected by the Panbio COVID-19 rapid antigen test may be due to the T135I mutation in the N protein, posing a potential diagnostic risk for commercially available antigen tests. Hence, we recommend concomitant paired rapid antigen tests and molecular diagnostic methods to detect SARS-CoV-2. False-negative results could be rapidly corrected using confirmatory RT-PCR results to prevent future COVID-19 outbreaks.

Review: Development of SARS-CoV-2 immuno-enhanced COVID-19 vaccines with nano-platform

Vaccination is the most effective way to prevent coronavirus disease 2019 (COVID-19). Vaccine development approaches consist of viral vector vaccines, DNA vaccine, RNA vaccine, live attenuated virus, and recombinant proteins, which elicit a specific immune response. The use of nanoparticles displaying antigen is one of the alternative approaches to conventional vaccines. This is due to the fact that nano-based vaccines are stable, able to target, form images, and offer an opportunity to enhance the immune responses. The diameters of ultrafine nanoparticles are in the range of 1-100 nm. The application of nanotechnology on vaccine design provides precise fabrication of nanomaterials with desirable properties and ability to eliminate undesirable features. To be successful, nanomaterials must be uptaken into the cell, especially into the target and able to modulate cellular functions at the subcellular levels. The advantages of nano-based vaccines are the ability to protect a cargo such as RNA, DNA, protein, or synthesis substance and have enhanced stability in a broad range of pH, ambient temperatures, and humidity for long-term storage. Moreover, nano-based vaccines can be engineered to overcome biological barriers such as nonspecific distribution in order to elicit functions in antigen presenting cells. In this review, we will summarize on the developing COVID-19 vaccine strategies and how the nanotechnology can enhance antigen presentation and strong immunogenicity using advanced technology in nanocarrier to deliver antigens. The discussion about their safe, effective, and affordable vaccines to immunize against COVID-19 will be highlighted.

Genomic analysis of early transmissibility assessment of the D614G mutant strain of SARS-CoV-2 in travelers returning to Taiwan from the United States of America

Background

There is a global pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Information on viral genomics is crucial for understanding global dispersion and for providing insight into viral pathogenicity and transmission. Here, we characterized the SARS-CoV-2 genomes isolated from five travelers who returned to Taiwan from the United States of America (USA) between March and April 2020.

Methods

Haplotype network analysis was performed using genome-wide single-nucleotide variations to trace potential infection routes. To determine the genetic variations and evolutionary trajectory of the isolates, the genomes of isolates were compared to those of global virus strains from GISAID. Pharyngeal specimens were confirmed to be SARS-CoV-2-positive by RT-PCR. Direct whole-genome sequencing was performed, and viral assemblies were subsequently uploaded to GISAID. Comparative genome sequence and single-nucleotide variation analyses were performed.

Results

The D614G mutation was identified in imported cases, which separated into two clusters related to viruses originally detected in the USA. Our findings highlight the risk of spreading SARS-CoV-2 variants through air travel and the need for continued genomic tracing for the epidemiological investigation and surveillance of SARS-CoV-2 using viral genomic data.

Conclusions

Continuous genomic surveillance is warranted to trace virus circulation and evolution in different global settings during future outbreaks.

Potential Achilles heels of SARS-CoV-2 are best displayed by the base order-dependent component of RNA folding energy

The base order-dependent component of folding energy has revealed a highly conserved region in HIV-1 genomes that associates with RNA structure. This corresponds to a packaging signal that is recognized by the nucleocapsid domain of the Gag polyprotein. Long viewed as a potential HIV-1 "Achilles heel," the signal can be targeted by a new antiviral compound. Although SARS-CoV-2 differs in many respects from HIV-1, the same technology displays regions with a high base order-dependent folding energy component, which are also highly conserved. This indicates structural invariance (SI) sustained by natural selection. While the regions are often also protein-encoding (e. g. NSP3, ORF3a), we suggest that their nucleic acid level functions can be considered potential "Achilles heels" for SARS-CoV-2, perhaps susceptible to therapies like those envisaged for AIDS. The ribosomal frameshifting element scored well, but higher SI scores were obtained in other regions, including those encoding NSP13 and the nucleocapsid (N) protein.

Variability in Codon Usage in Coronaviruses Is Mainly Driven by Mutational Bias and Selective Constraints on CpG Dinucleotide

The Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the third human-emerged virus of the 21st century from the Coronaviridae family, causing the ongoing coronavirus disease 2019 (COVID-19) pandemic. Due to the high zoonotic potential of coronaviruses, it is critical to unravel their evolutionary history of host species breadth, host-switch potential, adaptation and emergence, to identify viruses posing a pandemic risk in humans. We present here a comprehensive analysis of the composition and codon usage bias of the 82 Orthocoronavirinae members, infecting 47 different avian and mammalian hosts. Our results clearly establish that synonymous codon usage varies widely among viruses, is only weakly dependent on their primary host, and is dominated by mutational bias towards AU-enrichment and by CpG avoidance. Indeed, variation in GC3 explains around 34%, while variation in CpG frequency explains around 14% of total variation in codon usage bias. Further insight on the mutational equilibrium within Orthocoronavirinae revealed that most coronavirus genomes are close to their neutral equilibrium, the exception being the three recently infecting human coronaviruses, which lie further away from the mutational equilibrium than their endemic human coronavirus counterparts. Finally, our results suggest that, while replicating in humans, SARS-CoV-2 is slowly becoming AU-richer, likely until attaining a new mutational equilibrium.

Variants in SARS-CoV-2 associated with mild or severe outcome

Introduction

The coronavirus disease 2019 (COVID-19) pandemic is a global public health emergency causing a disparate burden of death and disability around the world. The viral genetic variants associated with outcome severity are still being discovered.

Methods

We downloaded 155 958 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from GISAID. Of these genomes, 3637 samples included useable metadata on patient outcomes. Using this subset, we evaluated whether SARS-CoV-2 viral genomic variants improved prediction of reported severity beyond age and region. First, we established whether including genomic variants as model features meaningfully increased the predictive power of our model. Next, we evaluated specific variants in order to determine the magnitude of association with severity and the frequency of these variants among SARS-CoV-2 genomes.

Results

Logistic regression models that included viral genomic variants outperformed other models (area under the curve = 0.91 as compared with 0.68 for age and gender alone; P < 0.001). We found 84 variants with odds ratios greater than 2 for outcome severity (17 and 67 for higher and lower severity, respectively). The median frequency of associated variants was 0.15% (interquartile range 0.09-0.45%). Altogether 85% of genomes had at least one variant associated with patient outcome.

Conclusion

Numerous SARS-CoV-2 variants have 2-fold or greater association with odds of mild or severe outcome and collectively, these variants are common. In addition to comprehensive mitigation efforts, public health measures should be prioritized to control the more severe manifestations of COVID-19 and the transmission chains linked to these severe cases.Lay summary: This study explores which, if any, SARS-CoV-2 viral genomic variants are associated with mild or severe COVID-19 patient outcomes. Our results suggest that there are common genomic variants in SARS-CoV-2 that are more often associated with negative patient outcomes, which may impact downstream public health measures.

Novel approach for Monte Carlo simulation of the new COVID-19 spread dynamics

A Monte Carlo simulation in a novel approach is used for studying the problem of the outbreak and spread dynamics of the new COVID-19 pandemic in this work. In particular, our goal was to generate epidemiological data based on natural mechanism of transmission of this disease assuming random interactions of a large-finite number of individuals in very short distance ranges. In the simulation we also take into account the stochastic character of the individuals in a finite population and given densities of people. On the other hand, we include in the simulation the appropriate statistical distributions for the parameters characterizing this disease. An important outcome of our work, besides the generated epidemic curves, is the methodology of determining the effective reproductive number during the main part of the daily new cases of the epidemic. Since this quantity constitutes a fundamental parameter of the SIR-based epidemic models, we also studied how it is affected by small variations of the incubation time and the crucial distance distributions, and furthermore, by the degree of quarantine measures. In addition, we compare our qualitative results with those of selected real epidemiological data

Coronavirus, the King Who Wanted More Than a Crown: From Common to the Highly Pathogenic SARS-CoV-2, Is the Key in the Accessory Genes?

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), that emerged in late 2019, is the etiologic agent of the current "coronavirus disease 2019" (COVID-19) pandemic, which has serious health implications and a significant global economic impact. Of the seven human coronaviruses, all of which have a zoonotic origin, the pandemic SARS-CoV-2, is the third emerging coronavirus, in the 21st century, highly pathogenic to the human population. Previous human coronavirus outbreaks (SARS-CoV-1 and MERS-CoV) have already provided several valuable information on some of the common molecular and cellular mechanisms of coronavirus infections as well as their origin. However, to meet the new challenge caused by the SARS-CoV-2, a detailed understanding of the biological specificities, as well as knowledge of the origin are crucial to provide information on viral pathogenicity, transmission and epidemiology, and to enable strategies for therapeutic interventions and drug discovery. Therefore, in this review, we summarize the current advances in SARS-CoV-2 knowledges, in light of pre-existing information of other recently emerging coronaviruses. We depict the specificity of the immune response of wild bats and discuss current knowledge of the genetic diversity of bat-hosted coronaviruses that promotes viral genome expansion (accessory gene acquisition). In addition, we describe the basic virology of coronaviruses with a special focus SARS-CoV-2. Finally, we highlight, in detail, the current knowledge of genes and accessory proteins which we postulate to be the major keys to promote virus adaptation to specific hosts (bat and human), to contribute to the suppression of immune responses, as well as to pathogenicity.

Relative synonymous codon usage of ORF1ab in SARS-CoV-2 and SARS-CoV

Background

COVID-19, as a novel coronavirus disease caused by new coronavirus SARS-CoV-2, spreads all over the world, and brings harm to human in many countries. Humans suffered a lot from both SARS-CoV-2 now and by SARS-CoV in the year 2003. It is important to understand the differences and the relationships between these two types of viruses.

Objective

To compare relative synonymous codon usage of ORF1ab gene in SARS-CoV-2 and SARS-CoV, relative synonymous codon usage of their genomes are studied in this paper from the bioinformatics perspective.

Methods

The ORF1ab gene, which is an important non-structural polyprotein coding gene and now used for nucleic acid detection markers in many measurement method, in both SARS-CoV-2 (30 strains) and SARS-CoV (20 strains) are considered to be the research object in the present paper. The relative synonymous codon usage values of the ORF1ab gene are calculated to characterize the differences and the evolutionary characteristics among 50 strains.

Results

There is a significant difference between SARS-CoV and SARS-CoV-2 when the relative synonymous codon usage value of ORF1ab genes is concerned. The results suggest that codon usage pattern of SARS-CoV is more similar to human than that of the SARS-CoV-2, and that the inner difference in SARS-CoV-2 strains is larger than that of SARS-CoV, which denote the larger diversity exits in the SARS-CoV-2 virus.

Conclusion

These results show that the relative synonymous codon usage values in the coronavirus could be used for further research on their evolutionary phenomenon.

The Evolution of Severe Acute Respiratory Syndrome Coronavirus-2 during Pandemic and Adaptation to the Host

Severe Acute Respiratory Syndrome Coronavirus-2 is a zoonotic virus with a possible origin in bats and potential transmission to humans through an intermediate host. When zoonotic viruses jump to a new host, they undergo both mutational and natural selective pressures that result in non-synonymous and synonymous adaptive changes, necessary for efficient replication and rapid spread of diseases in new host species. The nucleotide composition and codon usage pattern of SARS-CoV-2 indicate the presence of a highly conserved, gene-specific codon usage bias. The codon usage pattern of SARS-CoV-2 is mostly antagonistic to human and bat codon usage. SARS-CoV-2 codon usage bias is mainly shaped by the natural selection, while mutational pressure plays a minor role. The time-series analysis of SARS-CoV-2 genome indicates that the virus is slowly evolving. Virus isolates from later stages of the outbreak have more biased codon usage and nucleotide composition than virus isolates from early stages of the outbreak.

Genome-Wide Analysis of Codon Usage Patterns of SARS-CoV-2 Virus Reveals Global Heterogeneity of COVID-19

The ongoing outbreak of coronavirus disease COVID-19 is significantly implicated by global heterogeneity in the genome organization of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The causative agents of global heterogeneity in the whole genome of SARS-CoV-2 are not well characterized due to the lack of comparative study of a large enough sample size from around the globe to reduce the standard deviation to the acceptable margin of error. To better understand the SARS-CoV-2 genome architecture, we have performed a comprehensive analysis of codon usage bias of sixty (60) strains to get a snapshot of its global heterogeneity. Our study shows a relatively low codon usage bias in the SARS-CoV-2 viral genome globally, with nearly all the over-preferred codons' A.U. ended. We concluded that the SARS-CoV-2 genome is primarily shaped by mutation pressure; however, marginal selection pressure cannot be overlooked. Within the A/U rich virus genomes of SARS-CoV-2, the standard deviation in G.C. (42.91% ± 5.84%) and the GC3 value (30.14% ± 6.93%) points towards global heterogeneity of the virus. Several SARS-CoV-2 viral strains were originated from different viral lineages at the exact geographic location also supports this fact. Taking all together, these findings suggest that the general root ancestry of the global genomes are different with different genome's level adaptation to host. This research may provide new insights into the codon patterns, host adaptation, and global heterogeneity of SARS-CoV-2.

Role of SARS-CoV-2 and ACE2 variations in COVID-19

Coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is one of the worst medical emergencies that has hit the world in almost a century. The virus has now spread to a large number of countries/territories and has caused over three million deaths. Evidently, the virus has been mutating and adapting during this period. Significant effort has been spent on identifying these variations and their impact on transmission, virulence and pathogenicity of SARS-CoV-2. Binding of the SARS-CoV-2 spike protein to the angiotensin converting enzyme 2 (ACE2) promotes cellular entry. Therefore, human ACE2 variations could also influence susceptibility or resistance to the virus. A deeper understanding of the evolution and genetic variations in SARS-CoV-2 as well as ACE2 could contribute to the development of effective treatment and preventive measures. Here, we review the literature on SARS-CoV-2 and ACE2 variations and their role in COVID-19.

CryoEM and AI reveal a structure of SARS-CoV-2 Nsp2, a multifunctional protein involved in key host processes

The SARS-CoV-2 protein Nsp2 has been implicated in a wide range of viral processes, but its exact functions, and the structural basis of those functions, remain unknown. Here, we report an atomic model for full-length Nsp2 obtained by combining cryo-electron microscopy with deep learning-based structure prediction from AlphaFold2. The resulting structure reveals a highly-conserved zinc ion-binding site, suggesting a role for Nsp2 in RNA binding. Mapping emerging mutations from variants of SARS-CoV-2 on the resulting structure shows potential host-Nsp2 interaction regions. Using structural analysis together with affinity tagged purification mass spectrometry experiments, we identify Nsp2 mutants that are unable to interact with the actin-nucleation-promoting WASH protein complex or with GIGYF2, an inhibitor of translation initiation and modulator of ribosome-associated quality control. Our work suggests a potential role of Nsp2 in linking viral transcription within the viral replication-transcription complexes (RTC) to the translation initiation of the viral message. Collectively, the structure reported here, combined with mutant interaction mapping, provides a foundation for functional studies of this evolutionary conserved coronavirus protein and may assist future drug design.

Prevention of COVID-19: Preventive Strategies for General Population, Healthcare Setting, and Various Professions

The disease 2019 (COVID-19) made a public health emergency in early 2020. Despite attempts for the development of therapeutic modalities, there is no effective treatment yet. Therefore, preventive measures in various settings could help reduce the burden of disease. In this chapter, the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causing COVID-19, non-pharmaceutical approaches at individual and population level, chemoprevention, immunoprevention, preventive measures in different healthcare settings and other professions, special considerations in high-risk groups, and the role of organizations to hamper the psychosocial effects will be discussed.

CryoEM and AI reveal a structure of SARS-CoV-2 Nsp2, a multifunctional protein involved in key host processes

The SARS-CoV-2 protein Nsp2 has been implicated in a wide range of viral processes, but its exact functions, and the structural basis of those functions, remain unknown. Here, we report an atomic model for full-length Nsp2 obtained by combining cryo-electron microscopy with deep learning-based structure prediction from AlphaFold2. The resulting structure reveals a highly-conserved zinc ion-binding site, suggesting a role for Nsp2 in RNA binding. Mapping emerging mutations from variants of SARS-CoV-2 on the resulting structure shows potential host-Nsp2 interaction regions. Using structural analysis together with affinity tagged purification mass spectrometry experiments, we identify Nsp2 mutants that are unable to interact with the actin-nucleation-promoting WASH protein complex or with GIGYF2, an inhibitor of translation initiation and modulator of ribosome-associated quality control. Our work suggests a potential role of Nsp2 in linking viral transcription within the viral replication-transcription complexes (RTC) to the translation initiation of the viral message. Collectively, the structure reported here, combined with mutant interaction mapping, provides a foundation for functional studies of this evolutionary conserved coronavirus protein and may assist future drug design.

A scheme for inferring viral-host associations based on codon usage patterns identifies the most affected signaling pathways during COVID-19

Understanding the molecular mechanism of COVID-19 pathogenesis helps in the rapid therapeutic target identification. Usually, viral protein targets host proteins in an organized fashion. The expression of any viral gene depends mostly on the host translational machinery. Recent studies report the great significance of codon usage biases in establishing host-viral protein–protein interactions (PPI). Exploring the codon usage patterns between a pair of co-evolved host and viral proteins may present novel insight into the host-viral protein interactomes during disease pathogenesis. Leveraging the similarity in codon usage patterns, we propose a computational scheme to recreate the host-viral protein–protein interaction network. We use host proteins from seventeen (17) essential signaling pathways for our current work towards understanding the possible targeting mechanism of SARS-CoV-2 proteins. We infer both negatively and positively interacting edges in the network. Further, extensive analysis is performed to understand the host PPI network topologically and the attacking behavior of the viral proteins. Our study reveals that viral proteins mostly utilize codons, rare in the targeted host proteins (negatively correlated interaction). Among them, non-structural proteins, NSP3 and structural protein, Spike (S), are the most influential proteins in interacting with multiple host proteins. While ranking the most affected pathways, MAPK pathways observe to be the worst affected during the SARS-CoV-2 infection. Several proteins participating in multiple pathways are highly central in host PPI and mostly targeted by multiple viral proteins. We observe many potential targets (host proteins) from the affected pathways associated with the various drug molecules, including Arsenic trioxide, Dexamethasone, Hydroxychloroquine, Ritonavir, and Interferon beta, which are either under clinical trial or in use during COVID-19.

Codon-based indices for modeling gene expression and transcript evolution

Codon usage bias (CUB) refers to the phenomena that synonymous codons are used in different frequencies in most genes and organisms. The general assumption is that codon biases reflect a balance between mutational biases and natural selection. Today we understand that the codon content is related and can affect all gene expression steps. Starting from the 1980s, codon-based indices have been used for answering different questions in all biomedical fields, including systems biology, agriculture, medicine, and biotechnology. In general, codon usage bias indices weigh each codon or a small set of codons to estimate the fitting of a certain coding sequence to a certain phenomenon (e.g., bias in codons, adaptation to the tRNA pool, frequencies of certain codons, transcription elongation speed, etc.) and are usually easy to implement. Today there are dozens of such indices; thus, this paper aims to review and compare the different codon usage bias indices, their applications, and advantages. In addition, we perform analysis that demonstrates that most indices tend to correlate even though they aim to capture different aspects. Due to the centrality of codon usage bias on different gene expression steps, it is important to keep developing new indices that can capture additional aspects that are not modeled with the current indices.

Base Composition and Host Adaptation of the SARS-CoV-2: Insight From the Codon Usage Perspective

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been spreading rapidly all over the world and has raised grave concern globally. The present research aims to conduct a robust base compositional analysis of SARS-CoV-2 to reveal adaptive intricacies to the human host. Multivariate statistical analysis revealed a complex interplay of various factors including compositional constraint, natural selection, length of viral coding sequences, hydropathicity, and aromaticity of the viral gene products that are operational to codon usage patterns, with compositional bias being the most crucial determinant. UpG and CpA dinucleotides were found to be highly preferred whereas, CpG dinucleotide was mostly avoided in SARS-CoV-2, a pattern consistent with the human host. Strict avoidance of the CpG dinucleotide might be attributed to a strategy for evading a human immune response. A lower degree of adaptation of SARS-CoV-2 to the human host, compared to Middle East respiratory syndrome (MERS) coronavirus and SARS-CoV, might be indicative of its milder clinical severity and progression contrasted to SARS and MERS. Similar patterns of enhanced adaptation between viral isolates from intermediate and human hosts, contrasted with those isolated from the natural bat reservoir, signifies an indispensable role of the intermediate host in transmission dynamics and spillover events of the virus to human populations. The information regarding avoided codon pairs in SARS-CoV-2, as conferred by the present analysis, promises to be useful for the design of vaccines employing codon pair deoptimization based synthetic attenuated virus engineering.

Predicting the animal hosts of coronaviruses from compositional biases of spike protein and whole genome sequences through machine learning

The COVID-19 pandemic has demonstrated the serious potential for novel zoonotic coronaviruses to emerge and cause major outbreaks. The immediate animal origin of the causative virus, SARS-CoV-2, remains unknown, a notoriously challenging task for emerging disease investigations. Coevolution with hosts leads to specific evolutionary signatures within viral genomes that can inform likely animal origins. We obtained a set of 650 spike protein and 511 whole genome nucleotide sequences from 222 and 185 viruses belonging to the family Coronaviridae, respectively. We then trained random forest models independently on genome composition biases of spike protein and whole genome sequences, including dinucleotide and codon usage biases in order to predict animal host (of nine possible categories, including human). In hold-one-out cross-validation, predictive accuracy on unseen coronaviruses consistently reached ~73%, indicating evolutionary signal in spike proteins to be just as informative as whole genome sequences. However, different composition biases were informative in each case. Applying optimised random forest models to classify human sequences of MERS-CoV and SARS-CoV revealed evolutionary signatures consistent with their recognised intermediate hosts (camelids, carnivores), while human sequences of SARS-CoV-2 were predicted as having bat hosts (suborder Yinpterochiroptera), supporting bats as the suspected origins of the current pandemic. In addition to phylogeny, variation in genome composition can act as an informative approach to predict emerging virus traits as soon as sequences are available. More widely, this work demonstrates the potential in combining genetic resources with machine learning algorithms to address long-standing challenges in emerging infectious diseases.

Non-optimal codon usage preferences of coronaviruses determine their promiscuity for infecting multiple hosts

Circulating animal coronaviruses occasionally infect humans. The SARS-CoV-2 is responsible for the current worldwide outbreak of COVID-19 that has resulted in 2 112 844 deaths as of late January 2021. We compared genetic code preferences in 496 viruses, including 34 coronaviruses and 242 corresponding hosts, to uncover patterns that distinguish single- and 'promiscuous' multiple-host-infecting viruses. Based on a codon usage preference score, promiscuous viruses were shown to significantly employ nonoptimal codons, namely codons that involve 'wobble' binding to anticodons, as compared to single-host viruses. The codon adaptation index (CAI) and the effective number of codons (ENC) were calculated for all viruses and hosts. Promiscuous viruses were less adapted hosts vs single-host viruses (P-value = 4.392e-11). All coronaviruses exploit nonoptimal codons to infect multiple hosts. We found that nonoptimal codon preferences at the beginning of viral coding sequences enhance the translational efficiency of viral proteins within the host. Finally, coronaviruses lack endogenous RNA degradation motifs to a significant degree, thereby increasing viral mRNA burden and infection load. To conclude, we found that promiscuously infecting coronaviruses prefer nonoptimal codon usage to remove degradation motifs from their RNAs and to dramatically increase their viral RNA production rates.

Characterizing genomic variants and mutations in SARS-CoV-2 proteins from Indian isolates

SARS-CoV-2 is mutating and creating divergent variants by altering the composition of essential constituent proteins. Pharmacologically, it is crucial to understand the diverse mechanism of mutations for stable vaccine or anti-viral drug design. Our current study concentrates on all the constituent proteins of 469 SARS-CoV-2 genome samples, derived from Indian patients. However, the study may easily be extended to the samples across the globe.

We perform clustering analysis towards identifying unique variants in each of the SARS-CoV-2 proteins. A total of 536 mutated positions within the coding regions of SARS-CoV-2 proteins are detected among the identified variants from Indian isolates. We quantify mutations by focusing on the unique variants of each SARS-CoV-2 protein. We report the average number of mutation per variant, percentage of mutated positions, synonymous and non-synonymous mutations, mutations occurring in three codon positions and so on. Our study reveals the most susceptible six (06) proteins, which are ORF1ab, Spike (S), Nucleocapsid (N), ORF3a, ORF7a, and ORF8. Several non-synonymous substitutions are observed to be unique in different SARS-CoV-2 proteins. A total of 57 possible deleterious amino acid substitutions are predicted, which may impact on the protein functions. Several mutations show a large decrease in protein stability and are observed in putative functional domains of the proteins that might have some role in disease pathogenesis. We observe a good number of physicochemical property change during above deleterious substitutions.

Codon usage analysis of zoonotic coronaviruses reveals lower adaptation to humans by SARS-CoV-2

Since 2002, the world has witnessed major outbreaks of acute respiratory illness by three zoonotic coronaviruses (CoVs), which differ from each other in pathogenicity. Reasons for the lower pathogenicity of SARS-CoV-2 than the other two zoonotic coronaviruses, SARS-CoV and MERS-CoV, are not well understood. We herein compared the codon usage patterns of the three zoonotic CoVs causing severe acute respiratory syndromes and four human-specific CoVs (NL63, 229E, OC43, and HKU1) causing mild diseases. We found that the seven viruses have different codon usages, with SARS-CoV-2 having the lowest effective number of codons (ENC) among the zoonotic CoVs. Human codon adaptation index (CAI) analysis revealed that the CAI value of SARS-CoV-2 is the lowest among the zoonotic CoVs. The ENC and CAI values of SARS-CoV-2 were more similar to those of the less-pathogenic human-specific CoVs. To further investigate adaptive evolution within SARS-CoV-2, we examined codon usage patterns in 3573 genomes of SARS-CoV-2 collected over the initial 4 months of the pandemic. We showed that the ENC values and the CAI values of SARS-CoV-2 were decreasing over the period. The low ENC and CAI values could be responsible for the lower pathogenicity of SARS-CoV-2. While mutational pressure appears to shape codon adaptation in the overall genomes of SARS-CoV-2 and other zoonotic CoVs, the E gene of SARS-CoV-2, which has the highest codon usage bias, appears to be under strong natural selection. Data from the study contribute to our understanding of the pathogenicity and evolution of SARS-CoV-2 in humans.

Evidence for Strong Mutation Bias toward, and Selection against, U Content in SARS-CoV-2: Implications for Vaccine Design

Large-scale re-engineering of synonymous sites is a promising strategy to generate vaccines either through synthesis of attenuated viruses or via codon-optimized genes in DNA vaccines. Attenuation typically relies on deoptimization of codon pairs and maximization of CpG dinucleotide frequencies. So as to formulate evolutionarily informed attenuation strategies that aim to force nucleotide usage against the direction favored by selection, here, we examine available whole-genome sequences of SARS-CoV-2 to infer patterns of mutation and selection on synonymous sites. Analysis of mutational profiles indicates a strong mutation bias toward U. In turn, analysis of observed synonymous site composition implicates selection against U. Accounting for dinucleotide effects reinforces this conclusion, observed UU content being a quarter of that expected under neutrality. Possible mechanisms of selection against U mutations include selection for higher expression, for high mRNA stability or lower immunogenicity of viral genes. Consistent with gene-specific selection against CpG dinucleotides, we observe systematic differences of CpG content between SARS-CoV-2 genes. We propose an evolutionarily informed approach to attenuation that, unusually, seeks to increase usage of the already most common synonymous codons. Comparable analysis of H1N1 and Ebola finds that GC3 deviated from neutral equilibrium is not a universal feature, cautioning against generalization of results.

Isolating SARS-CoV-2 Strains From Countries in the Same Meridian: Genome Evolutionary Analysis

BACKGROUND

COVID-19, caused by the novel SARS-CoV-2, is considered the most threatening respiratory infection in the world, with over 40 million people infected and over 0.934 million related deaths reported worldwide. It is speculated that epidemiological and clinical features of COVID-19 may differ across countries or continents. Genomic comparison of 48,635 SARS-CoV-2 genomes has shown that the average number of mutations per sample was 7.23, and most SARS-CoV-2 strains belong to one of 3 clades characterized by geographic and genomic specificity: Europe, Asia, and North America.

OBJECTIVE

The aim of this study was to compare the genomes of SARS-CoV-2 strains isolated from Italy, Sweden, and Congo, that is, 3 different countries in the same meridian (longitude) but with different climate conditions, and from Brazil (as an outgroup country), to analyze similarities or differences in patterns of possible evolutionary pressure signatures in their genomes.

METHODS

We obtained data from the Global Initiative on Sharing All Influenza Data repository by sampling all genomes available on that date. Using HyPhy, we achieved the recombination analysis by genetic algorithm recombination detection method, trimming, removal of the stop codons, and phylogenetic tree and mixed effects model of evolution analyses. We also performed secondary structure prediction analysis for both sequences (mutated and wild-type) and "disorder" and "transmembrane" analyses of the protein. We analyzed both protein structures with an ab initio approach to predict their ontologies and 3D structures.

RESULTS

Evolutionary analysis revealed that codon 9628 is under episodic selective pressure for all SARS-CoV-2 strains isolated from the 4 countries, suggesting it is a key site for virus evolution. Codon 9628 encodes the P0DTD3 (Y14_SARS2) uncharacterized protein 14. Further investigation showed that the codon mutation was responsible for helical modification in the secondary structure. The codon was positioned in the more ordered region of the gene (41-59) and near to the area acting as the transmembrane (54-67), suggesting its involvement in the attachment phase of the virus. The predicted protein structures of both wild-type and mutated P0DTD3 confirmed the importance of the codon to define the protein structure. Moreover, ontological analysis of the protein emphasized that the mutation enhances the binding probability.

CONCLUSIONS

Our results suggest that RNA secondary structure may be affected and, consequently, the protein product changes T (threonine) to G (glycine) in position 50 of the protein. This position is located close to the predicted transmembrane region. Mutation analysis revealed that the change from G (glycine) to D (aspartic acid) may confer a new function to the protein-binding activity, which in turn may be responsible for attaching the virus to human eukaryotic cells. These findings can help design in vitro experiments and possibly facilitate a vaccine design and successful antiviral strategies.

Natural Selection Plays an Important Role in Shaping the Codon Usage of Structural Genes of the Viruses Belonging to the Coronaviridae Family

Viruses belonging to the Coronaviridae family have a single-stranded positive-sense RNA with a poly-A tail. The genome has a length of ~29.9 kbps, which encodes for genes that are essential for cell survival and replication. Different evolutionary constraints constantly influence the codon usage bias (CUB) of different genes. A virus optimizes its codon usage to fit the host environment on which it savors. This study is a comprehensive analysis of the CUB for the different genes encoded by viruses of the Coronaviridae family. Different methods including relative synonymous codon usage (RSCU), an Effective number of codons (ENc), parity plot 2, and Neutrality plot, were adopted to analyze the factors responsible for the genetic evolution of the Coronaviridae family. Base composition and RSCU analyses demonstrated the presence of A-ended and U-ended codons being preferred in the 3rd codon position and are suggestive of mutational selection. The lesser ENc value for the spike ‘S’ gene suggests a higher bias in the codon usage of this gene compared to the other structural genes. Parity plot 2 and neutrality plot analyses demonstrate the role and the extent of mutational and natural selection towards the codon usage pattern. It was observed that the structural genes of the Coronaviridae family analyzed in this study were at the least under 84% influence of natural selection, implying a major role of natural selection in shaping the codon usage.

Comprehensive evolution and molecular characteristics of a large number of SARS-CoV-2 genomes reveal its epidemic trends

OBJECTIVES

To further reveal the phylogenetic evolution and molecular characteristics of the whole genome of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) based on a large number of genomes and provide a basis for the prevention and treatment of SARS-CoV-2.

METHODS

Various evolution analysis methods were employed.

RESULTS

The estimated ratio of the rates of non-synonymous to synonymous changes (Ka/Ks) of SARS-CoV-2 was 1.008 or 1.094 based on 622 or 3624 SARS-CoV-2 genomes and nine key specific sites of high linkage, and four major haplotypes were found: H1, H2, H3 and H4. The results of Ka/Ks, detected population size and development trends of each major haplotype showed that H3 and H4 subgroups were going through a purify evolution and almost disappeared after detection, indicating that they might have existed for a long time. The H1 and H2 subgroups were going through a near neutral or neutral evolution and globally increased with time, and the frequency of H1 was generally high in Europe and correlated with the death rate (r >0.37), suggesting that these two haplotypes might relate to the infectivity or pathogenicity of SARS-CoV-2.

CONCLUSIONS

Several key specific sites and haplotypes related to the infectivity or pathogenicity of SARS-CoV-2, and the possible earlier origin time and place of SARS-CoV-2 were indicated based on the evolution and epidemiology of 16,373 SARS-CoV-2 genomes.

Comprehensive evolution and molecular characteristics of a large number of SARS-CoV-2 genomes reveal its epidemic trends

OBJECTIVES

To further reveal the phylogenetic evolution and molecular characteristics of the whole genome of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) based on a large number of genomes and provide a basis for the prevention and treatment of SARS-CoV-2.

METHODS

Various evolution analysis methods were employed.

RESULTS

The estimated ratio of the rates of non-synonymous to synonymous changes (Ka/Ks) of SARS-CoV-2 was 1.008 or 1.094 based on 622 or 3624 SARS-CoV-2 genomes and nine key specific sites of high linkage, and four major haplotypes were found: H1, H2, H3 and H4. The results of Ka/Ks, detected population size and development trends of each major haplotype showed that H3 and H4 subgroups were going through a purify evolution and almost disappeared after detection, indicating that they might have existed for a long time. The H1 and H2 subgroups were going through a near neutral or neutral evolution and globally increased with time, and the frequency of H1 was generally high in Europe and correlated with the death rate (r >0.37), suggesting that these two haplotypes might relate to the infectivity or pathogenicity of SARS-CoV-2.

CONCLUSIONS

Several key specific sites and haplotypes related to the infectivity or pathogenicity of SARS-CoV-2, and the possible earlier origin time and place of SARS-CoV-2 were indicated based on the evolution and epidemiology of 16,373 SARS-CoV-2 genomes.