Biased Mutation and Selection in RNA Viruses

Prediction of viral families and hosts of single-stranded RNA viruses based on K-Mer coding from phylogenetic gene sequences

There are billions of virus species worldwide, and viruses, the smallest parasitic entities, pose a serious threat. Therefore, fighting associated disorders requires an understanding of the genetic structure of viruses. Considering the wide diversity and rapid evolution of viruses, there is a critical need to quickly and accurately classify viral species and their potential hosts to better understand transmission dynamics, facilitating the development of targeted therapies. Recognizing this, this study has investigated the classes of RNA viruses based on their genomic sequences using Machine Learning (ML) and Deep Learning (DL) models. The PhyVirus dataset, consisting of pathogenic Single-stranded RNA viruses of Baltimore group four (+ssRNA) and five (-ssRNA) with different hosts and species, was analyzed. The dataset containing viral gene sequences was analyzed using the K-Mer coding technique, which is based on base words of various lengths. The study used classical ML algorithms (Random Forest, Gradient Boosting and Extra Trees) and the Fully Connected Deep Neural Network, a Deep Learning algorithm, to predict viral families and hosts. Detailed analyses were performed on the classifier performance in scenarios with different train-test ratios and different word lengths (k-values) for K-Mer. The observed results show that Fully Connected Deep Neural Network has a high success rate of 99.60 % in predicting virus families. In predicting virus hosts, the Extra Trees classifier achieved the highest success rate of 81.53 %. This study is considered to be the first classification study in the literature on this dataset, which has a very large family and host diversity consisting of gene sequences of Single-stranded RNA viruses. Our detailed investigations on how varying word lengths based on K-Mer coding in gene sequences affect the classification into viral families and hosts make this study particularly valuable. This study shows that ML and DL methods have the potential to produce valuable results in phylogenetic studies. In addition, the results and high-performance values show that these methods can be successfully used in regenerative applications of gene sequences or in studies such as the elimination of losses in gene sequences.

Dengue virus preferentially uses human and mosquito non-optimal codons

Codon optimality refers to the effect that codon composition has on messenger RNA (mRNA) stability and translation level and implies that synonymous codons are not silent from a regulatory point of view. Here, we investigated the adaptation of virus genomes to the host optimality code using mosquito-borne dengue virus (DENV) as a model. We demonstrated that codon optimality exists in mosquito cells and showed that DENV preferentially uses nonoptimal (destabilizing) codons and avoids codons that are defined as optimal (stabilizing) in either human or mosquito cells. Human genes enriched in the codons preferentially and frequently used by DENV are upregulated during infection, and so is the tRNA decoding the nonoptimal and DENV preferentially used codon for arginine. We found that adaptation during single-host passaging in human or mosquito cells results in the selection of synonymous mutations towards DENV's preferred nonoptimal codons that increase virus fitness. Finally, our analyses revealed that hundreds of viruses preferentially use nonoptimal codons, with those infecting a single host displaying an even stronger bias, suggesting that host-pathogen interaction shapes virus-synonymous codon choice.

Prediction of Prospective Mutational Landscape of SARS-CoV-2 Spike ssRNA and Evolutionary Basis of Its Host Interaction

Booster doses are crucial against severe COVID-19, as rapid virus mutations and variant emergence prolong the pandemic crisis. The virus's quick evolution, short generation-time, and adaptive changes impact virulence and evolvability, helping predictions about variant of concerns' (VOCs') landscapes. Here, in this study, we used a new computational algorithm, to predict the mutational pattern in SARS-CoV-2 ssRNA, proteomics, structural identification, mutation stability, and functional correlation, as well as immune escape mechanisms. Interestingly, the sequence diversity of SARS Coronavirus-2 has demonstrated a predominance of G- > A and C- > U substitutions. The best validation statistics are explored here in seven homologous models of the expected mutant SARS-CoV-2 spike ssRNA and employed for hACE2 and IgG interactions. The interactome profile of SARS-CoV-2 spike with hACE2 and IgG revealed a strong correlation between phylogeny and divergence time. The systematic adaptation of SARS-CoV-2 spike ssRNA influences infectivity and immune escape. Data suggest higher propensity of Adenine rich sequence promotes MHC system avoidance, preferred by A-rich codons. Phylogenetic data revealed the evolution of SARS-CoV-2 lineages' epidemiology. Our findings may unveil processes governing the genesis of immune-resistant variants, prompting a critical reassessment of the coronavirus mutation rate and exploration of hypotheses beyond mechanical aspects.

RNAVirHost: a machine learning-based method for predicting hosts of RNA viruses through viral genomes

BACKGROUND

The high-throughput sequencing technologies have revolutionized the identification of novel RNA viruses. Given that viruses are infectious agents, identifying hosts of these new viruses carries significant implications for public health and provides valuable insights into the dynamics of the microbiome. However, determining the hosts of these newly discovered viruses is not always straightforward, especially in the case of viruses detected in environmental samples. Even for host-associated samples, it is not always correct to assign the sample origin as the host of the identified viruses. The process of assigning hosts to RNA viruses remains challenging due to their high mutation rates and vast diversity.

RESULTS

In this study, we introduce RNAVirHost, a machine learning-based tool that predicts the hosts of RNA viruses solely based on viral genomes. RNAVirHost is a hierarchical classification framework that predicts hosts at different taxonomic levels. We demonstrate the superior accuracy of RNAVirHost in predicting hosts of RNA viruses through comprehensive comparisons with various state-of-the-art techniques. When applying to viruses from novel genera, RNAVirHost achieved the highest accuracy of 84.3%, outperforming the alignment-based strategy by 12.1%.

CONCLUSIONS

The application of machine learning models has proven beneficial in predicting hosts of RNA viruses. By integrating genomic traits and sequence homologies, RNAVirHost provides a cost-effective and efficient strategy for host prediction. We believe that RNAVirHost can greatly assist in RNA virus analyses and contribute to pandemic surveillance.

Systematic analysis of the codon usage patterns of African swine fever virus genome coding sequences reveals its host adaptation phenotype

African swine fever (ASF) is a severe haemorrhagic disease caused by the African swine fever virus (ASFV), transmitted by ticks, resulting in high mortality among domestic pigs and wild boars. The global spread of ASFV poses significant economic threats to the swine industry. This study employs diverse analytical methods to explore ASFV's evolution and host adaptation, focusing on codon usage patterns and associated factors. Utilizing phylogenetic analysis methods including neighbour-joining and maximum-likelihood, 64 ASFV strains were categorized into four clades. Codon usage bias (CUB) is modest in ASFV coding sequences. This research identifies multiple factors - such as nucleotide composition, mutational pressures, natural selection and geographical diversity - contributing to the formation of CUB in ASFV. Analysis of relative synonymous codon usage reveals CUB variations within clades and among ASFVs and their hosts. Both Codon Adaptation Index and Similarity Index analyses confirm that ASFV strains are highly adapted to soft ticks (Ornithodoros moubata) but less so to domestic pigs, which could be a result of the long-term co-evolution of ASFV with ticks. This study sheds light on the factors influencing ASFV's codon usage and fitness dynamics, enriching our understanding of its evolution, adaptation and host interactions.

Codon usage bias analysis of the spike protein of human coronavirus 229E and its host adaptability

Human coronavirus 229E (HCoV-229E) represents one of the known coronaviruses capable of infecting humans and causes mild respiratory symptoms. It is also considered to have a zoonotic source, originating from animals and being transmitted the humans. In this study, a comprehensive phylogenetic and codon usage analysis of the spike (S) gene of HCoV-229E was conducted. Utilizing phylogenetic analysis and principal component analysis, HCoV-229E was categorized into four distinct clusters, each demonstrating unique host affiliations. Furthermore, it was observed that the codon usage bias within the S gene of HCoV-229E is relatively low, primarily influenced by natural selection patterns, with contributions from mutation pressure and dinucleotide abundance. Comparative analysis involving Codon Adaptation Index (CAI) and Relative Codon Deoptimization Index (RCDI) revealed that the codon usage pattern of HCoV-229E mirrors more closely that of camels, as opposed to alpacas and humans. The elucidation of the codon usage pattern within HCoV-229E, which we have meticulously examined, offers valuable insights for a more comprehensive comprehension of viral features, history, and evolutionary trajectory.

Emerging perspectives on RNA virus-mediated infections: from pathogenesis to therapeutic interventions

RNA viruses continue to pose significant threats to global public health, necessitating a profound understanding of their pathogenic mechanisms and the development of effective therapeutic interventions. This manuscript provides a comprehensive overview of emerging perspectives on RNA virus-mediated infections, spanning from the intricate intricacies of viral pathogenesis to the forefront of innovative therapeutic strategies. A critical exploration of antiviral drugs sets the stage, highlighting the diverse classes of compounds that target various stages of the viral life cycle, underscoring the ongoing efforts to combat viral infections. Central to this discussion is the exploration of RNA-based therapeutics, with a spotlight on messenger RNA (mRNA)-based approaches that have revolutionized the landscape of antiviral interventions. Furthermore, the manuscript delves into the intricate world of delivery systems, exploring inno-vative technologies designed to enhance the efficiency and safety of mRNA vaccines. By analyzing the challenges and advancements in delivery mechanisms, this review offers a roadmap for future research and development in this critical area. Beyond conventional infectious diseases, the document explores the expanding applications of mRNA vaccines, including their promising roles in cancer immunotherapy and personalized medicine approaches. This manuscript serves as a valuable resource for researchers, clinicians, and policymakers alike, offering a nuanced perspective on RNA virus pathogenesis and the cutting-edge therapeutic interventions. By synthesizing the latest advancements and challenges, this review contributes significantly to the ongoing discourse in the field, driving the development of novel strategies to combat RNA virus-mediated infections effectively.

Long-term dynamic shifts in genomic base content and evolutionary trajectories of SARS-CoV-2 variants

The rapid spread and remarkable mutations of SARS-CoV-2 variants, particularly Omicron, necessitate an understanding of their evolutionary characteristics. In this study, we analyzed representative high-quality whole-genome sequences of 2008 SARS-CoV-2 variants to explore long-term dynamic changes in genomic base (especially GC) content and variations during viral evolution. Our results demonstrated a highly negative correlation between GC content and variant emergence time (r = -0.765, p < 2.22e-16). Major gene partitions (S, N, ORF1ab) displayed similar trends. Omicron exhibited a significantly lower GC content than non-Omicron variants (p < 2.22e-16). Notably, we observed a robust negative correlation between C and T content (r = -0.778, p < 2.22e-16) and between G and A content (r = -0.773, p < 2.22e-16). Among all strains, Omicron showed the greatest base variation, with C->T mutations being the most frequent (median [interquartile range [IQR]]: 29 (27, 31), 37.67%), succeeded by G->A mutations (11 (9, 13), 14.63%). Over a 3-year span, an annual decline rate of 0.12% in SARS-CoV-2 GC content was observed and could become more pronounced in future emerging variants. These findings provided insights into the evolutionary trajectory of SARS-CoV-2, underscoring the significance of continuous genomic surveillance for effective prediction of and response to future variants.

Sensing nucleotide composition in virus RNA

Nucleotide composition plays a crucial role in the structure, function and recognition of RNA molecules. During infection, virus RNA is exposed to multiple endogenous proteins that detect local or global compositional biases and interfere with virus replication. Recent advancements in RNA:protein mapping technologies have enabled the identification of general RNA-binding preferences in the human proteome at basal level and in the context of virus infection. In this review, we explore how cellular proteins recognise nucleotide composition in virus RNA and the impact these interactions have on virus replication. Protein-binding G-rich and C-rich sequences are common examples of how host factors detect and limit infection, and, in contrast, viruses may have evolved to purge their genomes from such motifs. We also give examples of how human RNA-binding proteins inhibit virus replication, not only by destabilising virus RNA, but also by interfering with viral protein translation and genome encapsidation. Understanding the interplay between cellular proteins and virus RNA composition can provide insights into host-virus interactions and uncover potential targets for antiviral strategies.

An Overview on Anti-COVID-19 Drug Achievements and Challenges Ahead

The appearance of several coronavirus pandemics/epidemics during the last two decades (SARS-CoV-1 in 2002, MERS-CoV in 2012, and SARS-CoV-2 in 2019) indicates that humanity will face increasing challenges from coronaviruses in the future. The emergence of new strains with similar transmission characteristics as SARS-CoV-2 and mortality rates similar to SARS-CoV-1 (∼10% mortality) or MERS-CoV (∼35% mortality) in the future is a terrifying possibility. Therefore, getting enough preparations to face such risks is an inevitable necessity. The present study aims to review the drug achievements and challenges in the fight against SARS-CoV-2 with a combined perspective derived from pharmacology, pharmacotherapy, and medicinal chemistry insights. Appreciating all the efforts made during the past few years, there is strong evidence that the desired results have not yet been achieved and research in this area should still be pursued seriously. By expressing some pessimistic possibilities and concluding that the drug discovery and pharmacotherapy of COVID-19 have not been successful so far, this short essay tries to draw the attention of responsible authorities to be more prepared against future coronavirus epidemics/pandemics.

Consequences of asymmetric mutational pressure for the dynamic of linear B-cell epitopes repertoire of influenza a virus neuraminidase rearrangement

Full-length nucleotide sequences of avian influenza A virus neuraminidase coding region (20,631 sequences) were analyzed and compared with those isolated from viruses infecting human and swine (63,750 sequences). If in fourfold degenerate sites there is asymmetric A-bias that may be more or less asymmetric depending on the type of neuraminidase and the host, than in twofold degenerate sites from third codon positions there is a strong asymmetric U-bias in coding regions of N4, N5, and N8 isolated from viruses infecting birds, as well as in those of N1 and N2 isolated from viruses infecting human, swine, and birds, while in coding regions of N9 isolated from birds, there is surprisingly strong C-bias, and in sequences of N3, N6, and N7 the usage of C is quite close to the level of U. Revealed stabilization of both U and C in twofold degenerate sites is the evidence of frequent changes in mutational pressure direction. Asymmetric mutational pressure was one of the sources of amino acid replacements that resulted in an equal percentage of sites with appeared and disappeared linear B-cell epitopes in N1, N2, N4, and N5 (33.62-35.33% vs. 32.41-36.45%, respectively), and controlled by the immune pressure it resulted in a stronger tendency to disappear for B-cell epitopes of N3, N6, N7, N8, and N9 of avian viruses (8.74-28.77% vs. 28.96-38.89%). The lack of correlation between nucleotide usages in fourfold and twofold degenerate sites for three nucleotides, except U, is a strong evidence of mutational pressure theory.

Tracking the evolution of the SARS-CoV-2 Delta variant of concern: analysis of genetic diversity and selection across the whole viral genome

Background

Since 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has diversified extensively, producing five highly virulent lineages designated as variants of concern (VOCs). The Delta VOC emerged in India with increased transmission, immune evasion, and mortality, causing a massive global case surge in 2021. This study aims to understand how the Delta VOC evolved by characterizing mutation patterns in the viral population before and after its emergence. Furthermore, we aim to identify the influence of positive and negative selection on VOC evolution and understand the prevalence of different mutation types in the viral genome.

Methods

Three groups of whole viral genomes were retrieved from GISAID, sourced from India, with collection periods as follows: Group A-during the initial appearance of SARS-CoV-2; Group B-just before the emergence of the Delta variant; Group C-after the establishment of the Delta variant in India. Mutations in >1% of each group were identified with BioEdit to reveal differences in mutation quantity and type. Sites under positive or negative selection were identified with FUBAR. The results were compared to determine how mutations correspond with selective pressures and how viral mutation profiles changed to reflect genetic diversity before and after VOC emergence.

Results

The number of mutations increased progressively in Groups A-C, with Group C reporting a 2.2- and 1.9-fold increase from Groups A and B, respectively. Among all the observed mutations, Group C had the highest percentage of deletions (22.7%; vs. 4.2% and 2.6% in Groups A and B, respectively), and most mutations altered the final amino acid code, such as non-synonymous substitutions and deletions. Conversely, Group B had the most synonymous substitutions that are effectively silent. The number of sites experiencing positive selection increased in Groups A-C, but Group B had 2.4- and 2.6 times more sites under negative selection compared to Groups A and C, respectively.

Conclusion

Our findings demonstrated that viral genetic diversity continuously increased during and after the emergence of the Delta VOC. Despite this, Group B reports heightened negative selection, which potentially preserves important gene regions during evolution. Group C contains an unprecedented quantity of mutations and positively selected sites, providing strong evidence of active viral adaptation in the population.

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.

Distinguishing Genetic Drift from Selection in Papillomavirus Evolution

Pervasive purifying selection on non-synonymous substitutions is a hallmark of papillomavirus genome history, but the role of selection on and the drift of non-coding DNA motifs on HPV diversification is poorly understood. In this study, more than a thousand complete genomes representing Alphapapillomavirus types, lineages, and SNP variants were examined phylogenetically and interrogated for the number and position of non-coding DNA sequence motifs using Principal Components Analyses, Ancestral State Reconstructions, and Phylogenetic Independent Contrasts. For anciently diverged Alphapapillomavirus types, composition of the four nucleotides (A, C, G, T), codon usage, trimer usage, and 13 established non-coding DNA sequence motifs revealed phylogenetic clusters consistent with genetic drift. Ancestral state reconstruction and Phylogenetic Independent Contrasts revealed ancient genome alterations, particularly for the CpG and APOBEC3 motifs. Each evolutionary analytical method we performed supports the unanticipated conclusion that genetic drift and different evolutionary drivers have structured Alphapapillomavirus genomes in distinct ways during successive epochs, even extending to differences in more recently formed variant lineages.

Different Patterns of Codon Usage and Amino Acid Composition across Primate Lentiviruses

A common feature of the mammalian Lentiviruses (family Retroviridae) is an RNA genome that contains an extremely high frequency of adenine (31.7-38.2%) while being extremely poor in cytosine (13.9-21.2%). Such a biased nucleotide composition has implications for codon usage, causing a striking difference between the frequency of synonymous codons in Lentiviruses and that in their hosts. To test whether primate Lentiviruses present differences in codon and amino acid composition, we assembled a dataset of genome sequences that includes SIV species infecting Old-World monkeys and African apes, HIV-2, and the four groups of HIV-1. Using principal component analysis, we found that HIV-1 shows a significant enrichment in adenine plus thymine in the third synonymous codon position and in adenine and guanine in the first and second nonsynonymous codon positions. Similarly, we observed an enrichment in adenine and in guanine in nonsynonymous first and second codon positions, which affects the amino acid composition of the proteins Gag, Pol, Vif, Vpr, Tat, Rev, Env, and Nef. This result suggests an effect of natural selection in shaping codon usage. Under the hypothesis that the use of synonyms in HIV-1 could reflect adaptation to that of genes expressed in specific cell types, we found a highly significant correlation between codon usage in HIV-1 and monocytes, which was remarkably higher than that with B and T lymphocytes. This finding is in line with the notion that monocytes represent an HIV-1 reservoir in infected patients, and it could help understand how this reservoir is established and maintained.

Compositional biases and evolution of the largest plant RNA virus order Patatavirales

Patatavirales is the largest order of plant RNA viruses and exclusively contains the family Potyviridae, accounting for 30 % of all known plant viruses. The composition bias of animal RNA viruses and several plant RNA viruses has been determined. However, the comprehensive nucleic acid composition, codon pair usage patterns, dinucleotide preference and codon pair preference of plant RNA viruses have not been investigated to date. In this study, integrated analysis and discussion of the nucleic acid composition, codon usage patterns, dinucleotide composition and codon pair bias of potyvirids were performed using 3732 complete genome coding sequences. The nucleic acid composition of potyvirids was significantly enriched in A/U. Interestingly, the A/U-rich nucleotide composition of Patatavirales is essential for determining the preferred A-ended and U-ended codons and the overexpression of UpG and CpA dinucleotides. The codon usage patterns and codon pair bias of potyvirids were significantly correlated with their nucleic acid composition. Additionally, the codon usage pattern, dinucleotide composition and codon-pair bias of potyvirids are more dependent on the classification of the virus compared with their hosts. Our analysis provides a better understanding of future research on the origin and evolution patterns of the order Patatavirales.

Codon usage bias of Venezuelan equine encephalitis virus and its host adaption

Venezuelan equine encephalitis virus (VEEV) is an emerging zoonotic virus in the alphavirus genus. It can be transmitted to humans due to spillover from equid-mosquito cycles. The symptoms caused by VEEV include fever, headache, myalgia, nausea, and vomiting. It can also cause encephalitis in severe cases. The evolutionary features of VEEV are largely unknown. In this study, we comprehensively analyzed the codon usage pattern of VEEV by computing a variety of indicators, such as effective number of codons (ENc), codon adaptation index (CAI), relative synonymous codon usage (RSCU), on 130 VEEV coding sequences retrieved from GenBank. The results showed that the codon usage bias of VEEV is relatively low. ENc-GC3s plot, neutrality plot, and CAI-ENc correlation analyses supported that translational selection plays an important role in shaping the codon usage pattern of VEEV whereas the mutation pressure has a minor influence. Analysis of RSCU values showed that most of the preferred codons in VEEV are C/G-ended. Analysis of dinucleotide composition found that all CG- and UA-containing codons are not preferentially used. Phylogenetic analysis showed that VEEV isolates can be clustered into three genera and evolutionary force affects the codon usage pattern. Furthermore, a correspondence analysis (COA) showed that aromaticity and hydrophobicity as well as geographical distribution also have certain effects on the codon usage variation of VEEV, suggesting the possible involvement of translational selection. Overall, the codon usage of VEEV is comparatively slight and translational selection might be the main factor that shapes the codon usage pattern of VEEV. This study will promote our understanding about the evolution of VEEV and its host adaption, and might provide some clues for preventing the cross-species transmission of VEEV.

Evolution of the SARS-CoV-2 Mutational Spectrum

SARS-CoV-2 evolves rapidly in part because of its high mutation rate. Here, we examine whether this mutational process itself has changed during viral evolution. To do this, we quantify the relative rates of different types of single-nucleotide mutations at 4-fold degenerate sites in the viral genome across millions of human SARS-CoV-2 sequences. We find clear shifts in the relative rates of several types of mutations during SARS-CoV-2 evolution. The most striking trend is a roughly 2-fold decrease in the relative rate of G→T mutations in Omicron versus early clades, as was recently noted by Ruis et al. (2022. Mutational spectra distinguish SARS-CoV-2 replication niches. bioRxiv, doi:10.1101/2022.09.27.509649). There is also a decrease in the relative rate of C→T mutations in Delta, and other subtle changes in the mutation spectrum along the phylogeny. We speculate that these changes in the mutation spectrum could arise from viral mutations that affect genome replication, packaging, and antagonization of host innate-immune factors, although environmental factors could also play a role. Interestingly, the mutation spectrum of Omicron is more similar than that of earlier SARS-CoV-2 clades to the spectrum that shaped the long-term evolution of sarbecoviruses. Overall, our work shows that the mutation process is itself a dynamic variable during SARS-CoV-2 evolution and suggests that human SARS-CoV-2 may be trending toward a mutation spectrum more similar to that of other animal sarbecoviruses.

Lactobacillus for ribosome peptide editing cancer

This study reviews newly discovered insect peptide point mutations as new possible cancer research targets. To interpret newly discovered peptide point mutations in insects as new possible cancer research targets, we focused on the numerous peptide changes found in the 'CSP' family on the sex pheromone gland of the female silkworm moth Bombyx mori. We predict that the Bombyx peptide modifications will have a significant effect on cancer CUP (cancers of unknown primary) therapy and that bacterial peptide editing techniques, specifically Lactobacillus combined to CRISPR, will be used to regulate ribosomes and treat cancer in humans.

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

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

Structural and Functional RNA Motifs of SARS-CoV-2 and Influenza A Virus as a Target of Viral Inhibitors

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the COVID-19 pandemic, whereas the influenza A virus (IAV) causes seasonal epidemics and occasional pandemics. Both viruses lead to widespread infection and death. SARS-CoV-2 and the influenza virus are RNA viruses. The SARS-CoV-2 genome is an approximately 30 kb, positive sense, 5' capped single-stranded RNA molecule. The influenza A virus genome possesses eight single-stranded negative-sense segments. The RNA secondary structure in the untranslated and coding regions is crucial in the viral replication cycle. The secondary structure within the RNA of SARS-CoV-2 and the influenza virus has been intensively studied. Because the whole of the SARS-CoV-2 and influenza virus replication cycles are dependent on RNA with no DNA intermediate, the RNA is a natural and promising target for the development of inhibitors. There are a lot of RNA-targeting strategies for regulating pathogenic RNA, such as small interfering RNA for RNA interference, antisense oligonucleotides, catalytic nucleic acids, and small molecules. In this review, we summarized the knowledge about the inhibition of SARS-CoV-2 and influenza A virus propagation by targeting their RNA secondary structure.

SARS-CoV-2 Variants Identification; A Fast and Affordable Strategy Based on Partial S-Gene Targeted PCR Sequencing

A considerable number of new SARS-CoV-2 lineages have emerged since the first COVID-19 cases were reported in Wuhan. As a few variants showed higher COVID-19 disease transmissibility and the ability to escape from immune responses, surveillance became relevant at that time. Single-nucleotide mutation PCR-based protocols were not always specific, and consequently, determination of a high number of informative sites was needed for accurate lineage identification. A detailed in silico analysis of SARS-CoV-2 sequences retrieved from GISAID database revealed the S gene 921 bp-fragment, positions 22784-23705 of SARS-CoV-2 reference genome, as the most informative fragment (30 variable sites) to determine relevant SARS-CoV-2 variants. Consequently, a method consisting of the PCR-amplification of this fragment, followed by Sanger's sequencing and a "single-click" informatic program based on a reference database, was developed and validated. PCR-fragments obtained from clinical SARS-CoV-2 samples were compared with homologous variant-sequences and the resulting phylogenetic tree allowed the identification of Alpha, Delta, Omicron, Beta, Gamma, and other variants. The data analysis procedure was automatized and simplified to the point that it did not require specific technical skills. The method is faster and cheaper than current whole-genome sequencing methods; it is available worldwide, and it may help to enhance efficient surveillance in the fight against the COVID-19 pandemic.

Biochemical Characterization of Emerging SARS-CoV-2 Nsp15 Endoribonuclease Variants

Global sequencing efforts from the ongoing COVID-19 pandemic, caused by the novel coronavirus SARS-CoV-2, continue to provide insight into the evolution of the viral genome. Coronaviruses encode 16 nonstructural proteins, within the first two-thirds of their genome, that facilitate viral replication and transcription as well as evasion of the host immune response. However, many of these viral proteins remain understudied. Nsp15 is a uridine-specific endoribonuclease conserved across all coronaviruses. The nuclease activity of Nsp15 helps the virus evade triggering an innate immune response. Understanding how Nsp15 has changed over the course of the pandemic, and how mutations affect its RNA processing function, will provide insight into the evolution of an oligomerization-dependent endoribonuclease and inform drug design. In combination with previous structural data, bioinformatics analyses of 1.9 + million SARS-CoV-2 sequences revealed mutations across Nsp15's three structured domains (N-terminal, Middle, EndoU). Selected Nsp15 variants were characterized biochemically and compared to wild type Nsp15. We found that mutations to important catalytic residues decreased cleavage activity but increased the hexamer/monomer ratio of the recombinant protein. Many of the highly prevalent variants we analyzed led to decreased nuclease activity as well as an increase in the inactive, monomeric form. Overall, our work establishes how Nsp15 variants seen in patient samples affect nuclease activity and oligomerization, providing insight into the effect of these variants in vivo.

Massive-scale genomic analysis reveals SARS-CoV-2 mutation characteristics and evolutionary trends

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic resulted in significant societal costs. Hence, an in-depth understanding of SARS-CoV-2 virus mutation and its evolution will help determine the direction of the COVID-19 pandemic. In this study, we identified 296,728 de novo mutations in more than 2,800,000 high-quality SARS-CoV-2 genomes. All possible factors affecting the mutation frequency of SARS-CoV-2 in human hosts were analyzed, including zinc finger antiviral proteins, sequence context, amino acid change, and translation efficiency. As a result, we proposed that when adenine (A) and tyrosine (T) bases are in the context of AM (M stands for adenine or cytosine) or TA motif, A or T base has lower mutation frequency. Furthermore, we hypothesized that translation efficiency can affect the mutation frequency of the third position of the codon by the selection, which explains why SARS-CoV-2 prefers AT3 codons usage. In addition, we found a host-specific asymmetric dinucleotide mutation frequency in the SARS-CoV-2 genome, which provides a new basis for determining the origin of the SARS-CoV-2. Finally, we summarize all possible factors affecting mutation frequency and provide insights into the mutation characteristics and evolutionary trends of SARS-CoV-2.

Contrasting patterns in the early stage of SARS-CoV-2 evolution between humans and minks

One of the unique features of SARS-CoV-2 is its apparent neutral evolution during the early pandemic (before February 2020). This contrasts with the preceding SARS-CoV epidemics, where viruses evolved adaptively. SARS-CoV-2 may exhibit a unique or adaptive feature which deviates from other coronaviruses. Alternatively, the virus may have been cryptically circulating in humans for a sufficient time to have acquired adaptive changes before the onset of the current pandemic. To test the scenarios above, we analyzed the SARS-CoV-2 sequences from minks (Neovision vision) and parental humans. In the early phase of the mink epidemic (April to May 2020), nonsynonymous to synonymous mutation ratio per site in the spike protein is 2.93, indicating a selection process favoring adaptive amino acid changes. Mutations in the spike protein were concentrated within its receptor binding domain and receptor binding motif. An excess of high frequency derived variants produced by genetic hitchhiking was found during the middle (June to July 2020) and late phase I (August to September 2020) of the mink epidemic. In contrast, the site frequency spectra of early SARS-CoV-2 in humans only show an excess of low frequency mutations, consistent with the recent outbreak of the virus. Strong positive selection in the mink SARS-CoV-2 implies the virus may not be pre-adapted to a wide range of hosts and illustrates how a virus evolves to establish a continuous infection in a new host. Therefore, the lack of positive selection signal during the early pandemic in humans deserves further investigation.

Advances in COVID-19 Vaccines and New Coronavirus Variants

With the successful development of the Corona Virus Disease 2019 (COVID-19) vaccines and increased vaccination coverage, great progress in global outbreak control has been made in several countries. However, new coronavirus variants emerge and their rapid spread, causing a new wave of economic and social upheaval worldwide. The spread of new coronavirus variants poses a new and enormous challenge to vaccination and pandemic control, so further studies to explore and develop vaccines for the prevention and control virus infection are warranted. In this review, we provide an overview of the most prevalent variants including Omicron, and explore the effectiveness of COVID-19 vaccines against related variants to better understand existing vaccines and to facilitate improved research into new vaccines. In addition, this review discusses existing strategies to increase vaccine efficacy and introduces novel vaccines by the non-injection route.

Evolutionary Dynamics of Foot and Mouth Disease Virus Serotype A and Its Endemic Sub-Lineage A/ASIA/Iran-05/SIS-13 in Pakistan

Foot and mouth disease (FMD) causes severe economic losses to the livestock industry of endemic countries, including Pakistan. Pakistan is part of the endemic pool 3 for foot and mouth disease viruses (FMDV), characterized by co-circulating O, A, and Asia 1 serotypes, as designated by the world reference laboratory for FMD (WRL-FMD). FMDV serotype A lineage ASIA/Iran-05 is widespread in buffalos and cattle populations and was first reported in Pakistan in 2006. This lineage has a high turnover, with as many as 10 sub-lineages reported from Pakistan over the years. In this study, we reconstructed the evolutionary, demographic, and spatial history of serotype A and one of its sub-lineages, A/ASIA/Iran-05/SIS-13, prevalent in Pakistan. We sequenced nearly complete genomes of three isolates belonging to sub-lineage A/ASIA/Iran-05/SIS-13. We estimated recombination patterns and natural selection acting on the serotype A genomes. Source and transmission routes in Pakistan were inferred, and the clustering pattern of isolates of the SIS-13 sub-lineage were mapped on a tree. We hereby report nearly complete genome sequences of isolates belonging to sub-lineage A/ASIA/Iran-05/SIS-13, along with purported recombinant genomes, and highlight that complete coding sequences can better elucidate the endemic history and evolutionary pressures acting on long-term co-circulating FMDV strains.

Efficacy and safety of regdanvimab in patients with mild/moderate COVID-19 and high risk of progression of the disease: a retrospective study in a short-term stay unit

Background. The use of virus-neutralizing monoclonal antibodies is an effective method of etiotropic therapy for SARS-CoV-2 in patients of high-risk groups of severe COVID-19. Regdanvimab is a single-component monoclonal antibodies immunoglobulin G1, whose mechanism of action is aimed at binding SARS-CoV-2 virus at the RBD site of the spike protein S1 domain. In the Russian Federation, regdanvimab is approved for emergency administration in COVID-19 for adult patients not requiring respiratory therapy who are at high risk of developing a severe course of the disease. Aim. To evaluate the efficacy and safety of therapy with regdanvimab in patients with mild/moderate COVID-19 in a short-term hospital unit. Materials and methods. Virus-neutralizing therapy with regdanvimab was performed at the short-term hospital unit of the Moscow City Clinic. An open retrospective observational single-center study included 92 adult patients with mild/moderate coronavirus infection. All patients had comorbid chronic diseases and belonged to the high-risk group for the development of a severe COVID-19. Inclusion criteria: age 18 to 75 years; presence of a verified diagnosis of COVID-19 of mild/moderate COVID-19, polymerase chain reaction (PCR) confirmed; one or more chronic diseases; first 7 days from the onset of the first symptoms of COVID-19 (including day 7). Exclusion criteria: need for oxygen support. Clinical efficacy was assessed according to the World Health Organization Сlinical Progression Scale and supplemented with laboratory markers at baseline and in dynamics, as well as with monitoring of virus elimination by PCR. Statistics. Calculations were performed using the statistical computing environment R 4.1.3 (R Foundation for Statistical Computing, Austria). For quantitative indices the median (1; 3 quartiles) was indicated. For binomial signs we calculated 95% confidence intervals according to Wilson's method. Time interval analysis was performed according to the KaplanMeier method. The significance level was determined at p0.05. Results. A significant decrease in the severity of clinical manifestations according to the World Health Organization Clinical Progression Scale was noted by patients by day 4 after regdanvimab administration. All 92 patients in the cohort were discharged from the hospital l on average on day 5 after regdanvimab administration and on day 9 of the disease. On day 4 after drug administration 82% of patients was being PCR negative. No adverse events related to the administration of regdanvimab were reported during the study. Conclusion. In real clinical practice, the efficacy and safety of regdanvimab in patients at high risk of severe COVID-19 was confirmed once again, with a positive clinical result observed in a mixed cohort by the causative agent omicron and delta strain.

Biochemical Characterization of Emerging SARS-CoV-2 Nsp15 Endoribonuclease Variants

Global sequencing efforts from the ongoing COVID-19 pandemic, caused by the novel coronavirus SARS-CoV-2, continue to provide insight into the evolution of the viral genome. Coronaviruses encode 16 nonstructural proteins, within the first two-thirds of their genome, that facilitate viral replication and transcription as well as evasion of the host immune response. However, many of these viral proteins remain understudied. Nsp15 is a uridine-specific endoribonuclease conserved across all coronaviruses. The nuclease activity of Nsp15 helps the virus evade triggering an innate immune response. Understanding how Nsp15 has changed over the course of the pandemic, and how mutations affect its RNA processing function, will provide insight into the evolution of an oligomerization-dependent endoribonuclease and inform drug design. In combination with previous structural data, bioinformatics analyses of 1.9+ million SARS-CoV-2 sequences revealed mutations across Nsp15’s three structured domains (N-terminal, Middle, EndoU). Selected Nsp15 variants were characterized biochemically and compared to wild type Nsp15. We found that mutations to important catalytic residues decreased cleavage activity but increased the hexamer/monomer ratio of the recombinant protein. Many of the highly prevalent variants we analyzed led to decreased nuclease activity as well as an increase in the inactive, monomeric form. Overall, our work establishes how Nsp15 variants seen in patient samples affect nuclease activity and oligomerization, providing insight into the effect of these variants in vivo .

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

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

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.

A High Rate Algal Pond Hosting a Dynamic Community of RNA Viruses

Despite a surge of RNA virome sequencing in recent years, there are still many RNA viruses to uncover-as indicated by the relevance of viral dark matter to RNA virome studies (i.e., putative viruses that do not match to taxonomically identified viruses). This study explores a unique site, a high-rate algal pond (HRAP), for culturing industrially microalgae, to elucidate new RNA viruses. The importance of viral-host interactions in aquatic systems are well documented, and the ever-expanding microalgae industry is no exception. As the industry becomes a more important source of sustainable plastic manufacturing, a producer of cosmetic pigments and alternative protein sources, and a means of CO2 remediation in the face of climate change, studying microalgal viruses becomes a vital practice for proactive management of microalgae cultures at the industrial level. This study provides evidence of RNA microalgal viruses persisting in a CO2 remediation pilot project HRAP and uncovers the diversity of the RNA virosphere contained within it. Evidence shows that family Marnaviridae is cultured in the basin, alongside other potential microalgal infecting viruses (e.g., family Narnaviridae, family Totitiviridae, and family Yueviridae). Finally, we demonstrate that the RNA viral diversity of the HRAP is temporally dynamic across two successive culturing seasons.

Near real-time determination of B.1.1.7 in proportion to total SARS-CoV-2 viral load in wastewater using an allele-specific primer extension PCR strategy

The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has claimed millions of lives to date. Antigenic drift has resulted in viral variants with putatively greater transmissibility, virulence, or both. Early and near real-time detection of these variants of concern (VOC) and the ability to accurately follow their incidence and prevalence in communities is wanting. Wastewater-based epidemiology (WBE), which uses nucleic acid amplification tests to detect viral fragments, is a reliable proxy of COVID-19 incidence and prevalence, and thus offers the potential to monitor VOC viral load in a given population. Here, we describe and validate a primer extension PCR strategy targeting a signature mutation in the N gene of SARS-CoV-2. This allows quantification of B.1.1.7 versus non-B.1.1.7 allele frequency in wastewater without the need to employ quantitative RT-PCR standard curves. We show that the wastewater B.1.1.7 profile correlates with its clinical counterpart and benefits from a near real-time and facile data collection and reporting pipeline. This assay can be quickly implemented within a current SARS-CoV-2 WBE framework with minimal cost; allowing early and contemporaneous estimates of B.1.1.7 community transmission prior to, or in lieu of, clinical screening and identification. Our study demonstrates that this strategy can provide public health units with an additional and much needed tool to rapidly triangulate VOC incidence/prevalence with high sensitivity and lineage specificity.

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

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

Patterns of within-host genetic diversity in SARS-CoV-2

Monitoring the spread of SARS-CoV-2 and reconstructing transmission chains has become a major public health focus for many governments around the world. The modest mutation rate and rapid transmission of SARS-CoV-2 prevents the reconstruction of transmission chains from consensus genome sequences, but within-host genetic diversity could theoretically help identify close contacts. Here we describe the patterns of within-host diversity in 1181 SARS-CoV-2 samples sequenced to high depth in duplicate. 95.1% of samples show within-host mutations at detectable allele frequencies. Analyses of the mutational spectra revealed strong strand asymmetries suggestive of damage or RNA editing of the plus strand, rather than replication errors, dominating the accumulation of mutations during the SARS-CoV-2 pandemic. Within- and between-host diversity show strong purifying selection, particularly against nonsense mutations. Recurrent within-host mutations, many of which coincide with known phylogenetic homoplasies, display a spectrum and patterns of purifying selection more suggestive of mutational hotspots than recombination or convergent evolution. While allele frequencies suggest that most samples result from infection by a single lineage, we identify multiple putative examples of co-infection. Integrating these results into an epidemiological inference framework, we find that while sharing of within-host variants between samples could help the reconstruction of transmission chains, mutational hotspots and rare cases of superinfection can confound these analyses.

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.

A Codon-Pair Bias Associated With Network Interactions in Influenza A, B, and C Genomes

A new codon-pair bias present in the genomes of different types of influenza virus is described. Codons with fewer network interactions are more frequency paired together than other codon-pairs in influenza A, B, and C genomes. A shared feature among three different influenza types suggests an evolutionary bias. Codon-pair preference can affect both speed of protein translation and RNA structure. This newly identified bias may provide insight into drivers of virus evolution.

Nucleotide Composition and Codon Usage Across Viruses and Their Respective Hosts

The genetic material of the three domains of life (Bacteria, Archaea, and Eukaryota) is always double-stranded DNA, and their GC content (molar content of guanine plus cytosine) varies between ≈ 13% and ≈ 75%. Nucleotide composition is the simplest way of characterizing genomes. Despite this simplicity, it has several implications. Indeed, it is the main factor that determines, among other features, dinucleotide frequencies, repeated short DNA sequences, and codon and amino acid usage. Which forces drive this strong variation is still a matter of controversy. For rather obvious reasons, most of the studies concerning this huge variation and its consequences, have been done in free-living organisms. However, no recent comprehensive study of all known viruses has been done (that is, concerning all available sequences). Viruses, by far the most abundant biological entities on Earth, are the causative agents of many diseases. An overview of these entities is important also because their genetic material is not always double-stranded DNA: indeed, certain viruses have as genetic material single-stranded DNA, double-stranded RNA, single-stranded RNA, and/or retro-transcribing. Therefore, one may wonder if what we have learned about the evolution of GC content and its implications in prokaryotes and eukaryotes also applies to viruses. In this contribution, we attempt to describe compositional properties of ∼ 10,000 viral species: base composition (globally and according to Baltimore classification), correlations among non-coding regions and the three codon positions, and the relationship of the nucleotide frequencies and codon usage of viruses with the same feature of their hosts. This allowed us to determine how the base composition of phages strongly correlate with the value of their respective hosts, while eukaryotic viruses do not (with fungi and protists as exceptions). Finally, we discuss some of these results concerning codon usage: reinforcing previous results, we found that phages and hosts exhibit moderate to high correlations, while for eukaryotes and their viruses the correlations are weak or do not exist.

A Comparative NLP-Based Study on the Current Trends and Future Directions in COVID-19 Research

COVID-19 is a global health crisis that has altered human life and still promises to create ripples of death and destruction in its wake. The sea of scientific literature published over a short time-span to understand and mitigate this global phenomenon necessitates concerted efforts to organize our findings and focus on the unexplored facets of the disease. In this work, we applied natural language processing (NLP) based approaches on scientific literature published on COVID-19 to infer significant keywords that have contributed to our social, economic, demographic, psychological, epidemiological, clinical, and medical understanding of this pandemic. We identify key terms appearing in COVID literature that vary in representation when compared to other virus-borne diseases such as MERS, Ebola, and Influenza. We also identify countries, topics, and research articles that demonstrate that the scientific community is still reacting to the short-term threats such as transmissibility, health risks, treatment plans, and public policies, underpinning the need for collective international efforts towards long-term immunization and drug-related challenges. Furthermore, our study highlights several long-term research directions that are urgently needed for COVID-19 such as: global collaboration to create international open-access data repositories, policymaking to curb future outbreaks, psychological repercussions of COVID-19, vaccine development for SARS-CoV-2 variants and their long-term efficacy studies, and mental health issues in both children and elderly.

Transcription, mRNA export and immune evasion shape the codon usage of viruses

The nucleotide composition, dinucleotide composition, and codon usage of many viruses differs from their hosts. These differences arise because viruses are subject to unique mutation and selection pressures that do not apply to host genomes; however, the molecular mechanisms that underlie these evolutionary forces are unclear. Here, we analysed the patterns of codon usage in 1,520 vertebrate-infecting viruses, focusing on parameters known to be under selection and associated with gene regulation. We find that GC content, dinucleotide content, and splicing and m6A modification-related sequence motifs are associated with the type of genetic material (DNA or RNA), strandedness, and replication compartment of viruses. In an experimental follow-up, we find that the effects of GC content on gene expression depend on whether the genetic material is delivered to the cell as DNA or mRNA, whether it is transcribed by endogenous or exogenous RNA polymerase, and whether transcription takes place in the nucleus or cytoplasm. Our results suggest that viral codon usage cannot be explained by a simple adaptation to the codon usage of the host - instead, it reflects the combination of multiple selective and mutational pressures, including the need for efficient transcription, export, and immune evasion.