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.

Longitudinal monitoring in Cambodia suggests higher circulation of alpha and betacoronaviruses in juvenile and immature bats of three species.

Recent studies suggest that coronaviruses circulate widely in Southeast Asian bat species and that the progenitors of the SARS-Cov-2 virus could have originated in rhinolophid bats in the region. Our objective was to assess the diversity and circulation patterns of coronavirus in several bat species in Southeast Asia. We undertook monthly live-capture sessions and sampling in Cambodia over 17 months to cover all phases of the annual reproduction cycle of bats and test specifically the association between their age and CoV infection status. We additionally examined current information on the reproductive phenology of Rhinolophus and other bat species presently known to occur in mainland southeast China, Vietnam, Laos and Cambodia. Results from our longitudinal monitoring (573 bats belonging to 8 species) showed an overall proportion of positive PCR tests for CoV of 4.2% (24/573) in cave-dwelling bats from Kampot and 4.75% (22/463) in flying-foxes from Kandal. Phylogenetic analysis showed that the PCR amplicon sequences of CoVs (n = 46) obtained clustered in Alphacoronavirus and Betacoronavirus. Interestingly, Hipposideros larvatus sensu lato harbored viruses from both genera. Our results suggest an association between positive detections of coronaviruses and juvenile and immature bats in Cambodia (OR = 3.24 [1.46-7.76], p = 0.005). Since the limited data presently available from literature review indicates that reproduction is largely synchronized among rhinolophid and hipposiderid bats in our study region, particularly in its more seasonal portions (above 16° N), this may lead to seasonal patterns in CoV circulation. Overall, our study suggests that surveillance of CoV in insectivorous bat species in Southeast Asia, including SARS-CoV-related coronaviruses in rhinolophid bats, could be targeted from June to October for species exhibiting high proportions of juveniles and immatures during these months. It also highlights the need to develop long-term longitudinal surveys of bats and improve our understanding of their ecology in the region, for both biodiversity conservation and public health reasons.

Utilizing the VirIdAl Pipeline to Search for Viruses in the Metagenomic Data of Bat Samples.

According to various estimates, only a small percentage of existing viruses have been discovered, naturally much less being represented in the genomic databases. High-throughput sequencing technologies develop rapidly, empowering large-scale screening of various biological samples for the presence of pathogen-associated nucleotide sequences, but many organisms are yet to be attributed specific loci for identification. This problem particularly impedes viral screening, due to vast heterogeneity in viral genomes. In this paper, we present a new bioinformatic pipeline, VirIdAl, for detecting and identifying viral pathogens in sequencing data. We also demonstrate the utility of the new software by applying it to viral screening of the feces of bats collected in the Moscow region, which revealed a significant variety of viruses associated with bats, insects, plants, and protozoa. The presence of alpha and beta coronavirus reads, including the MERS-like bat virus, deserves a special mention, as it once again indicates that bats are indeed reservoirs for many viral pathogens. In addition, it was shown that alignment-based methods were unable to identify the taxon for a large proportion of reads, and we additionally applied other approaches, showing that they can further reveal the presence of viral agents in sequencing data. However, the incompleteness of viral databases remains a significant problem in the studies of viral diversity, and therefore necessitates the use of combined approaches, including those based on machine learning methods.

Metagenomic identification of a new sarbecovirus from horseshoe bats in Europe.

The source of the COVID-19 pandemic is unknown, but the natural host of the progenitor sarbecovirus is thought to be Asian horseshoe (rhinolophid) bats. We identified and sequenced a novel sarbecovirus (RhGB01) from a British horseshoe bat, at the western extreme of the rhinolophid range. Our results extend both the geographic and species ranges of sarbecoviruses and suggest their presence throughout the horseshoe bat distribution. Within the spike protein receptor binding domain, but excluding the receptor binding motif, RhGB01 has a 77% (SARS-CoV-2) and 81% (SARS-CoV) amino acid homology. While apparently lacking hACE2 binding ability, and hence unlikely to be zoonotic without mutation, RhGB01 presents opportunity for SARS-CoV-2 and other sarbecovirus homologous recombination. Our findings highlight that the natural distribution of sarbecoviruses and opportunities for recombination through intermediate host co-infection are underestimated. Preventing transmission of SARS-CoV-2 to bats is critical with the current global mass vaccination campaign against this virus.

SARS-CoV-2 gene content and COVID-19 mutation impact by comparing 44 Sarbecovirus genomes.

Despite its clinical importance, the SARS-CoV-2 gene set remains unresolved, hindering dissection of COVID-19 biology. We use comparative genomics to provide a high-confidence protein-coding gene set, characterize evolutionary constraint, and prioritize functional mutations. We select 44 Sarbecovirus genomes at ideally-suited evolutionary distances, and quantify protein-coding evolutionary signatures and overlapping constraint. We find strong protein-coding signatures for ORFs 3a, 6, 7a, 7b, 8, 9b, and a novel alternate-frame gene, ORF3c, whereas ORFs 2b, 3d/3d-2, 3b, 9c, and 10 lack protein-coding signatures or convincing experimental evidence of protein-coding function. Furthermore, we show no other conserved protein-coding genes remain to be discovered. Mutation analysis suggests ORF8 contributes to within-individual fitness but not person-to-person transmission. Cross-strain and within-strain evolutionary pressures agree, except for fewer-than-expected within-strain mutations in nsp3 and S1, and more-than-expected in nucleocapsid, which shows a cluster of mutations in a predicted B-cell epitope, suggesting immune-avoidance selection. Evolutionary histories of residues disrupted by spike-protein substitutions D614G, N501Y, E484K, and K417N/T provide clues about their biology, and we catalog likely-functional co-inherited mutations. Previously reported RNA-modification sites show no enrichment for conservation. Here we report a high-confidence gene set and evolutionary-history annotations providing valuable resources and insights on SARS-CoV-2 biology, mutations, and evolution.

An application of slow feature analysis to the genetic sequences of coronaviruses and influenza viruses.

BACKGROUND: Mathematical approaches have been for decades used to probe the structure of DNA sequences. This has led to the development of Bioinformatics. In this exploratory work, a novel mathematical method is applied to probe the DNA structure of two related viral families: those of coronaviruses and those of influenza viruses. The coronaviruses are SARS-CoV-2, SARS-CoV-1, and MERS. The influenza viruses include H1N1-1918, H1N1-2009, H2N2-1957, and H3N2-1968. METHODS: The mathematical method used is the slow feature analysis (SFA), a rather new but promising method to delineate complex structure in DNA sequences. RESULTS: The analysis indicates that the DNA sequences exhibit an elaborate and convoluted structure akin to complex networks. We define a measure of complexity and show that each DNA sequence exhibits a certain degree of complexity within itself, while at the same time there exists complex inter-relationships between the sequences within a family and between the two families. From these relationships, we find evidence, especially for the coronavirus family, that increasing complexity in a sequence is associated with higher transmission rate but with lower mortality. CONCLUSIONS: The complexity measure defined here may hold a promise and could become a useful tool in the prediction of transmission and mortality rates in future new viral strains.

Evaluation of deep learning approaches for identification of different corona-virus species and time series prediction.

Novel corona-virus (nCOV) has been declared as a pandemic that started from the city Wuhan of China. This deadly virus is infecting people rapidly and has targeted 4.93 million people across the world, with 227 K people being infected only in Italy. Cases of nCOV are quickly increasing whereas the number of nCOV test kits available in hospitals are limited. Under these conditions, an automated system for the classification of patients into nCOV positive and negative cases, is a much needed tool against the pandemic, helping in a selective use of the limited number of test kits. In this research, Convolutional Neural Network-based models (one block VGG, two block VGG, three block VGG, four block VGG, LetNet-5, AlexNet, and Resnet-50) have been employed for the detection of Corona-virus and SARS_MERS infected patients, distinguishing them from the healthy subjects, using lung X-ray scans, which has proven to be a challenging task, due to overlapping characteristics of different corona virus types. Furthermore, LSTM model has been used for time series forecasting of nCOV cases, in the following 10 days, in Italy. The evaluation results obtained, proved that the VGG1 model distinguishes the three classes at an accuracy of almost 91%, as compared to other models, whereas the approach based on the LSTM predicts the number of nCOV cases with 99% accuracy.

A comparative review of pathogenesis and host innate immunity evasion strategies among the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), severe acute respiratory syndrome coronavirus (SARS-CoV) and the Middle East respiratory syndrome coronavirus (MERS-CoV).

COVID-19 pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has put the global public health at its highest threat around the world. Previous epidemic caused by the acute respiratory syndrome coronavirus (SARS-CoV) in 2002 is also considered since both the coronaviruses resulted in the similar clinical complications. The outbreak caused by the Middle East respiratory syndrome coronavirus (MERS-CoV) in 2012 had a low rate of disease transmission and death cases. Modes of entry by MERS and SARS coronaviruses are similar to that of SARS-CoV-2, except MERS-CoV utilize different receptor. They all belong to the lineage C of ß-coronavirus. Based on the information from the previous reports, the present review is mainly focused on the mechanisms of disease progression by each of these viruses in association to their strategies to escape the host immunity. The viral entry is the first step of pathogenesis associated with attachment of viral spike protein with host receptor help releasing the viral RNA into the host cell. Models of molecular pathogenesis are outlined with virus strategies escaping the host immunity along with the role of various inflammatory cytokines and chemokines in the process. The molecular aspects of pathogenesis have also been discussed.

A conserved immunogenic and vulnerable site on the coronavirus spike protein delineated by cross-reactive monoclonal antibodies.

The coronavirus spike glycoprotein, located on the virion surface, is the key mediator of cell entry and the focus for development of protective antibodies and vaccines. Structural studies show exposed sites on the spike trimer that might be targeted by antibodies with cross-species specificity. Here we isolated two human monoclonal antibodies from immunized humanized mice that display a remarkable cross-reactivity against distinct spike proteins of betacoronaviruses including SARS-CoV, SARS-CoV-2, MERS-CoV and the endemic human coronavirus HCoV-OC43. Both cross-reactive antibodies target the stem helix in the spike S2 fusion subunit which, in the prefusion conformation of trimeric spike, forms a surface exposed membrane-proximal helical bundle. Both antibodies block MERS-CoV infection in cells and provide protection to mice from lethal MERS-CoV challenge in prophylactic and/or therapeutic models. Our work highlights an immunogenic and vulnerable site on the betacoronavirus spike protein enabling elicitation of antibodies with unusual binding breadth.

Coronavirus Receptors as Immune Modulators.

The Coronaviridae family includes the seven known human coronaviruses (CoV) that cause mild to moderate respiratory infections (HCoV-229E, HCoV-NL63, HCoV-OC43, HCoV-HKU1) as well as severe illness and death (MERS-CoV, SARS-CoV, SARS-CoV-2). Severe infections induce hyperinflammatory responses that are often intensified by host adaptive immune pathways to profoundly advance disease severity. Proinflammatory responses are triggered by CoV entry mediated by host cell surface receptors. Interestingly, five of the seven strains use three cell surface metallopeptidases (CD13, CD26, and ACE2) as receptors, whereas the others employ O-acetylated-sialic acid (a key feature of metallopeptidases) for entry. Why CoV evolved to use peptidases as their receptors is unknown, but the peptidase activities of the receptors are dispensable, suggesting the virus uses/benefits from other functions of these molecules. Indeed, these receptors participate in the immune modulatory pathways that contribute to the pathological hyperinflammatory response. This review will focus on the role of CoV receptors in modulating immune responses.

Genotype and phenotype of COVID-19: Their roles in pathogenesis.

COVID-19 is a novel coronavirus with an outbreak of unusual viral pneumonia in Wuhan, China, and then pandemic. Based on its phylogenetic relationships and genomic structures the COVID-19 belongs to genera Betacoronavirus. Human Betacoronaviruses (SARS-CoV-2, SARS-CoV, and MERS-CoV) have many similarities, but also have differences in their genomic and phenotypic structure that can influence their pathogenesis. COVID-19 is containing single-stranded (positive-sense) RNA associated with a nucleoprotein within a capsid comprised of matrix protein. A typical CoV contains at least six ORFs in its genome. All the structural and accessory proteins are translated from the sgRNAs of CoVs. Four main structural proteins are encoded by ORFs 10, 11 on the one-third of the genome near the 3'-terminus. The genetic and phenotypic structure of COVID-19 in pathogenesis is important. This article highlights the most important of these features compared to other Betacoronaviruses.

RNAcentral 2021: secondary structure integration, improved sequence search and new member databases.

RNAcentral is a comprehensive database of non-coding RNA (ncRNA) sequences that provides a single access point to 44 RNA resources and >18 million ncRNA sequences from a wide range of organisms and RNA types. RNAcentral now also includes secondary (2D) structure information for >13 million sequences, making RNAcentral the world's largest RNA 2D structure database. The 2D diagrams are displayed using R2DT, a new 2D structure visualization method that uses consistent, reproducible and recognizable layouts for related RNAs. The sequence similarity search has been updated with a faster interface featuring facets for filtering search results by RNA type, organism, source database or any keyword. This sequence search tool is available as a reusable web component, and has been integrated into several RNAcentral member databases, including Rfam, miRBase and snoDB. To allow for a more fine-grained assignment of RNA types and subtypes, all RNAcentral sequences have been annotated with Sequence Ontology terms. The RNAcentral database continues to grow and provide a central data resource for the RNA community. RNAcentral is freely available at https://rnacentral.org.

Recombination events are concentrated in the spike protein region of Betacoronaviruses.

The Betacoronaviruses comprise multiple subgenera whose members have been implicated in human disease. As with SARS, MERS and now SARS-CoV-2, the origin and emergence of new variants are often attributed to events of recombination that alter host tropism or disease severity. In most cases, recombination has been detected by searches for excessively similar genomic regions in divergent strains; however, such analyses are complicated by the high mutation rates of RNA viruses, which can produce sequence similarities in distant strains by convergent mutations. By applying a genome-wide approach that examines the source of individual polymorphisms and that can be tested against null models in which recombination is absent and homoplasies can arise only by convergent mutations, we examine the extent and limits of recombination in Betacoronaviruses. We find that recombination accounts for nearly 40% of the polymorphisms circulating in populations and that gene exchange occurs almost exclusively among strains belonging to the same subgenus. Although experimental studies have shown that recombinational exchanges occur at random along the coronaviral genome, in nature, they are vastly overrepresented in regions controlling viral interaction with host cells.

Recombination and Positive Selection Differentially Shaped the Diversity of Betacoronavirus Subgenera.

The Betacoronavirus genus of mammal-infecting viruses includes three subgenera (Sarbecovirus, Embecovirus, and Merbecovirus), in which most known human coronaviruses, including SARS-CoV-2, cluster. Coronaviruses are prone to host shifts, with recombination and positive selection possibly contributing to their high zoonotic potential. We analyzed the role of these two forces in the evolution of viruses belonging to the Betacoronavirus genus. The results showed that recombination has been pervasive during sarbecovirus evolution, and it is more widespread in this subgenus compared to the other two. In both sarbecoviruses and merbecoviruses, recombination hotspots are clearly observed. Conversely, positive selection was a less prominent force in sarbecoviruses compared to embecoviruses and merbecoviruses and targeted distinct genomic regions in the three subgenera, with S being the major target in sarbecoviruses alone. Overall, the results herein indicate that Betacoronavirus subgenera evolved along different trajectories, which might recapitulate their host preferences or reflect the origins of the presently available coronavirus sequences.

Large scale genomic analysis of 3067 SARS-CoV-2 genomes reveals a clonal geo-distribution and a rich genetic variations of hotspots mutations.

In late December 2019, an emerging viral infection COVID-19 was identified in Wuhan, China, and became a global pandemic. Characterization of the genetic variants of SARS-CoV-2 is crucial in following and evaluating it spread across countries. In this study, we collected and analyzed 3,067 SARS-CoV-2 genomes isolated from 55 countries during the first three months after the onset of this virus. Using comparative genomics analysis, we traced the profiles of the whole-genome mutations and compared the frequency of each mutation in the studied population. The accumulation of mutations during the epidemic period with their geographic locations was also monitored. The results showed 782 variants sites, of which 512 (65.47%) had a non-synonymous effect. Frequencies of mutated alleles revealed the presence of 68 recurrent mutations, including ten hotspot non-synonymous mutations with a prevalence higher than 0.10 in this population and distributed in six SARS-CoV-2 genes. The distribution of these recurrent mutations on the world map revealed that certain genotypes are specific to geographic locations. We also identified co-occurring mutations resulting in the presence of several haplotypes. Moreover, evolution over time has shown a mechanism of mutation co-accumulation which might affect the severity and spread of the SARS-CoV-2. The phylogentic analysis identified two major Clades C1 and C2 harboring mutations L3606F and G614D, respectively and both emerging for the first time in China. On the other hand, analysis of the selective pressure revealed the presence of negatively selected residues that could be taken into considerations as therapeutic targets. We have also created an inclusive unified database (http://covid-19.medbiotech.ma) that lists all of the genetic variants of the SARS-CoV-2 genomes found in this study with phylogeographic analysis around the world.

International Orientation for Certifying and Coding COVID-19

SARS-CoV-2 spike protein predicted to form complexes with host receptor protein orthologues from a broad range of mammals.

SARS-CoV-2 has a zoonotic origin and was transmitted to humans via an undetermined intermediate host, leading to infections in humans and other mammals. To enter host cells, the viral spike protein (S-protein) binds to its receptor, ACE2, and is then processed by TMPRSS2. Whilst receptor binding contributes to the viral host range, S-protein:ACE2 complexes from other animals have not been investigated widely. To predict infection risks, we modelled S-protein:ACE2 complexes from 215 vertebrate species, calculated changes in the energy of the complex caused by mutations in each species, relative to human ACE2, and correlated these changes with COVID-19 infection data. We also analysed structural interactions to better understand the key residues contributing to affinity. We predict that mutations are more detrimental in ACE2 than TMPRSS2. Finally, we demonstrate phylogenetically that human SARS-CoV-2 strains have been isolated in animals. Our results suggest that SARS-CoV-2 can infect a broad range of mammals, but few fish, birds or reptiles. Susceptible animals could serve as reservoirs of the virus, necessitating careful ongoing animal management and surveillance.