Animal Coronaviruses Induced Apoptosis

Serpentoviruses Exhibit Diverse Organization and ORF Composition with Evidence of Recombination

Serpentoviruses are a subfamily of positive sense RNA viruses in the order Nidovirales, family Tobaniviridae, associated with respiratory disease in multiple clades of reptiles. While the broadest viral diversity is reported from captive pythons, other reptiles, including colubrid snakes, turtles, and lizards of captive and free-ranging origin are also known hosts. To better define serpentoviral diversity, eleven novel serpentovirus genomes were sequenced with an Illumina MiSeq and, when necessary, completed with other Sanger sequencing methods. The novel serpentoviral genomes, along with 57 other previously published serpentovirus genomes, were analyzed alongside four outgroup genomes. Genomic analyses included identifying unique genome templates for each serpentovirus clade, as well as analysis of coded protein composition, potential protein function, protein glycosylation sites, differences in phylogenetic history between open-reading frames, and recombination. Serpentoviral genomes contained diverse protein compositions. In addition to the fundamental structural spike, matrix, and nucleoprotein proteins required for virion formation, serpentovirus genomes also included 20 previously uncharacterized proteins. The uncharacterized proteins were homologous to a number of previously characterized proteins, including enzymes, transcription factors, scaffolding, viral resistance, and apoptosis-related proteins. Evidence for recombination was detected in multiple instances in genomes from both captive and free-ranging snakes. These results show serpentovirus as a diverse clade of viruses with genomes that code for a wide diversity of proteins potentially enhanced by recombination events.

Viral Infections and Schizophrenia: A Comprehensive Review

Schizophrenia is a complex mental disorder with multiple genetic and environmental factors contributing to its pathogenesis. Viral infections have been suggested to be one of the environmental factors associated with the development of this disorder. We comprehensively review all relevant published literature focusing on the relationship between schizophrenia and various viral infections, such as influenza virus, herpes virus 1 and 2 (HSV-1 and HSV-2), cytomegalovirus (CMV), Epstein-Barr virus (EBV), retrovirus, coronavirus, and Borna virus. These viruses may interfere with the normal maturation of the brain directly or through immune-induced mediators, such as cytokines, leading to the onset of schizophrenia. Changes in the expression of critical genes and elevated levels of inflammatory cytokines have been linked to virally-induced infections and relevant immune activities in schizophrenia. Future research is necessary to understand this relationship better and provide insight into the molecular mechanisms underlying the pathophysiology of schizophrenia.

Pharmacogenomics deliberations of 2-deoxy-d-glucose in the treatment of COVID-19 disease: an in silico approach

The outbreak of COVID-19 caused by the coronavirus (SARS-CoV-2) prompted number of computational and laboratory efforts to discover molecules against the virus entry or replication. Simultaneously, due to the availability of clinical information, drug-repurposing efforts led to the discovery of 2-deoxy-d-glucose (2-DG) for treating COVID-19 infection. 2-DG critically accumulates in the infected cells to prevent energy production and viral replication. As there is no clarity on the impact of genetic variations on the efficacy and adverse effects of 2-DG in treating COVID-19 using in silico approaches, we attempted to extract the genes associated with the 2-DG pathway using the Comparative Toxicogenomics Database. The interaction between selected genes was assessed using ClueGO, to identify the susceptible gene loci for SARS-CoV infections. Further, SNPs that were residing in the distinct genomic regions were retrieved from the Ensembl genome browser and characterized. A total of 80 SNPs were retrieved using diverse bioinformatics resources after assessing their (a) detrimental influence on the protein stability using Swiss-model, (b) miRNA regulation employing miRNASNP3, PolymiRTS, MirSNP databases, (c) binding of transcription factors by SNP2TFBS, SNPInspector, and (d) enhancers regulation using EnhancerDB and HaploReg reported A2M rs201769751, PARP1 rs193238922 destabilizes protein, six polymorphisms of XIAP effecting microRNA binding sites, EGFR rs712829 generates 15 TFBS, BECN1 rs60221525, CASP9 rs4645980, SLC2A2 rs5393 impairs 14 TFBS, STK11 rs3795063 altered 19 regulatory motifs. These data may provide the relationship between genetic variations and drug effects of 2-DG which may further assist in assigning the right individuals to benefit from the treatment.

Cross-attention PHV: Prediction of human and virus protein-protein interactions using cross-attention-based neural networks

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Cross-attention PHV implements two key technologies: cross-attention mechanism and 1D-CNN.

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It accurately predicts PPIs between human and unknown influenza viruses/SARS-CoV-2.

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It extracts critical taxonomic and evolutionary differences responsible for PPI prediction.

Viral infections represent a major health concern worldwide. The alarming rate at which SARS-CoV-2 spreads, for example, led to a worldwide pandemic. Viruses incorporate genetic material into the host genome to hijack host cell functions such as the cell cycle and apoptosis. In these viral processes, protein–protein interactions (PPIs) play critical roles. Therefore, the identification of PPIs between humans and viruses is crucial for understanding the infection mechanism and host immune responses to viral infections and for discovering effective drugs. Experimental methods including mass spectrometry-based proteomics and yeast two-hybrid assays are widely used to identify human-virus PPIs, but these experimental methods are time-consuming, expensive, and laborious. To overcome this problem, we developed a novel computational predictor, named cross-attention PHV, by implementing two key technologies of the cross-attention mechanism and a one-dimensional convolutional neural network (1D-CNN). The cross-attention mechanisms were very effective in enhancing prediction and generalization abilities. Application of 1D-CNN to the word2vec-generated feature matrices reduced computational costs, thus extending the allowable length of protein sequences to 9000 amino acid residues. Cross-attention PHV outperformed existing state-of-the-art models using a benchmark dataset and accurately predicted PPIs for unknown viruses. Cross-attention PHV also predicted human–SARS-CoV-2 PPIs with area under the curve values >0.95. The Cross-attention PHV web server and source codes are freely available at https://kurata35.bio.kyutech.ac.jp/Cross-attention_PHV/ and https://github.com/kuratahiroyuki/Cross-Attention_PHV, respectively.

Apoptosis Enhances the Replication of Human Coronavirus OC43

Human coronavirus OC43 (HCoV-OC43) is one of the coronaviruses causing a mild common cold, but few studies have been made on this strain. Here, we identified the molecular mechanisms involved in HCoV-OC43-induced apoptosis and its implications for viral reproduction in Vero cells and MRC-5 cells. HCoV-OC43 infection induced apoptosis that was accompanied by cleavage of caspase-3 and PARP, degradation of cyclin D1, and cell cycle arrest at S and G2M phases. Dephosphorylation of STAT1 and STAT3, induced by HCoV-OC43 infection, was also associated with HCoV-OC43-mediated apoptosis. The pan-caspase inhibitor effectively prevented HCoV-OC43-induced apoptosis and reduced viral replication, suggesting that apoptosis contributes to viral replication. Collectively our results indicate that HCoV-OC43 induces caspase-dependent apoptosis to promote viral replication in Vero cells and MRC-5 cells.

Potential Molecular Mechanisms of Rare Anti-Tumor Immune Response by SARS-CoV-2 in Isolated Cases of Lymphomas

Recently, two cases of complete remission of classical Hodgkin lymphoma (cHL) and follicular lymphoma (FL) after SARS-CoV-2 infection were reported. However, the precise molecular mechanism of this rare event is yet to be understood. Here, we hypothesize a potential anti-tumor immune response of SARS-CoV-2 and based on a computational approach show that: (i) SARS-CoV-2 Spike-RBD may bind to the extracellular domains of CD15, CD27, CD45, and CD152 receptors of cHL or FL and may directly inhibit cell proliferation. (ii) Alternately, upon internalization after binding to these CD molecules, the SARS-CoV-2 membrane (M) protein and ORF3a may bind to gamma-tubulin complex component 3 (GCP3) at its tubulin gamma-1 chain (TUBG1) binding site. (iii) The M protein may also interact with TUBG1, blocking its binding to GCP3. (iv) Both the M and ORF3a proteins may render the GCP2-GCP3 lateral binding where the M protein possibly interacts with GCP2 at its GCP3 binding site and the ORF3a protein to GCP3 at its GCP2 interacting residues. (v) Interactions of the M and ORF3a proteins with these gamma-tubulin ring complex components potentially block the initial process of microtubule nucleation, leading to cell-cycle arrest and apoptosis. (vi) The Spike-RBD may also interact with and block PD-1 signaling similar to pembrolizumab and nivolumab- like monoclonal antibodies and may induce B-cell apoptosis and remission. (vii) Finally, the TRADD interacting “PVQLSY” motif of Epstein-Barr virus LMP-1, that is responsible for NF-kB mediated oncogenesis, potentially interacts with SARS-CoV-2 M^pro, NSP7, NSP10, and spike (S) proteins, and may inhibit the LMP-1 mediated cell proliferation. Taken together, our results suggest a possible therapeutic potential of SARS-CoV-2 in lymphoproliferative disorders.

The Role of Coronavirus RNA-Processing Enzymes in Innate Immune Evasion

Viral RNA sensing triggers innate antiviral responses in humans by stimulating signaling pathways that include crucial antiviral genes such as interferon. RNA viruses have evolved strategies to inhibit or escape these mechanisms. Coronaviruses use multiple enzymes to synthesize, modify, and process their genomic RNA and sub-genomic RNAs. These include Nsp15 and Nsp16, whose respective roles in RNA capping and dsRNA degradation play a crucial role in coronavirus escape from immune surveillance. Evolutionary studies on coronaviruses demonstrate that genome expansion in Nidoviruses was promoted by the emergence of Nsp14-ExoN activity and led to the acquisition of Nsp15- and Nsp16-RNA-processing activities. In this review, we discuss the main RNA-sensing mechanisms in humans as well as recent structural, functional, and evolutionary insights into coronavirus Nsp15 and Nsp16 with a view to potential antiviral strategies.