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

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

Protocol to identify host-viral protein interactions between coagulation-related proteins and their genetic variants with SARS-CoV-2 proteins.

Here, we describe a bioinformatics pipeline that evaluates the interactions between coagulation-related proteins and genetic variants with SARS-CoV-2 proteins. This pipeline searches for host proteins that may bind to viral protein and identifies and scores the protein genetic variants to predict the disease pathogenesis in specific subpopulations. Additionally, it is able to find structurally similar motifs and identify potential binding sites within the host-viral protein complexes to unveil viral impact on regulated biological processes and/or host-protein impact on viral invasion or reproduction. For complete details on the use and execution of this protocol, please refer to Holcomb et al. (2021).

A Structurally Conserved RNA Element within SARS-CoV-2 ORF1a RNA and S mRNA Regulates Translation in Response to Viral S Protein-Induced Signaling in Human Lung Cells.

The positive-sense, single-stranded RNA genome SARS-CoV-2 harbors functionally important cis-acting elements governing critical aspects of viral gene expression. However, insights on how these elements sense various signals from the host cell and regulate viral protein synthesis are lacking. Here, we identified two novel cis-regulatory elements in SARS-CoV-2 ORF1a and S RNAs and describe their role in translational control of SARS-CoV-2. These elements are sequence-unrelated but form conserved hairpin structures (validated by NMR) resembling gamma activated inhibitor of translation (GAIT) elements that are found in a cohort of human mRNAs directing translational suppression in myeloid cells in response to IFN-γ. Our studies show that treatment of human lung cells with receptor-binding S1 subunit, S protein pseudotyped lentivirus, and S protein-containing virus-like particles triggers a signaling pathway involving DAP-kinase1 that leads to phosphorylation and release of the ribosomal protein L13a from the large ribosomal subunit. Released L13a forms a virus activated inhibitor of translation (VAIT) complex that binds to ORF1a and S VAIT elements, causing translational silencing. Translational silencing requires extracellular S protein (and its interaction with host ACE2 receptor), but not its intracellular synthesis. RNA-protein interaction analyses and in vitro translation experiments showed that GAIT and VAIT elements do not compete with each other, highlighting differences between the two pathways. Sequence alignments of SARS-CoV-2 genomes showed a high level of conservation of VAIT elements, suggesting their functional importance. This VAIT-mediated translational control mechanism of SARS-CoV-2 may provide novel targets for small molecule intervention and/or facilitate development of more effective mRNA vaccines. IMPORTANCE Specific RNA elements in the genomes of RNA viruses play important roles in host-virus interaction. For SARS-CoV-2, the mechanistic insights on how these RNA elements could sense the signals from the host cell are lacking. Here we report a novel relationship between the GAIT-like SARS-CoV-2 RNA element (called VAITs) and the signal generated from the host cell. We show that for SARS-CoV-2, the interaction of spike protein with ACE2 not only serves the purpose for viral entry into the host cell, but also transduces signals that culminate into the phosphorylation and the release of L13a from the large ribosomal subunit. We also show that this event leads to the translational arrest of ORF1a and S mRNAs in a manner dependent on the structure of the RNA elements. Translational control of viral mRNA by a host-cell generated signal triggered by viral protein is a new paradigm in the host-virus relationship.

In Silico Evaluation of Cyclophilin Inhibitors as Potential Treatment for SARS-CoV-2.

BACKGROUND: The advent of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) provoked researchers to propose multiple antiviral strategies to improve patients' outcomes. Studies provide evidence that cyclosporine A (CsA) decreases SARS-CoV-2 replication in vitro and decreases mortality rates of coronavirus disease 2019 (COVID-19) patients. CsA binds cyclophilins, which isomerize prolines, affecting viral protein activity. METHODS: We investigated the proline composition from various coronavirus proteomes to identify proteins that may critically rely on cyclophilin's peptidyl-proline isomerase activity and found that the nucleocapsid (N) protein significantly depends on cyclophilin A (CyPA). We modeled CyPA and N protein interactions to demonstrate the N protein as a potential indirect therapeutic target of CsA, which we propose may impede coronavirus replication by obstructing nucleocapsid folding. RESULTS: Finally, we analyzed the literature and protein-protein interactions, finding evidence that, by inhibiting CyPA, CsA may impact coagulation proteins and hemostasis. CONCLUSIONS: Despite CsA's promising antiviral characteristics, the interactions between cyclophilins and coagulation factors emphasize risk stratification for COVID patients with thrombosis dispositions.

Gene variants of coagulation related proteins that interact with SARS-CoV-2.

Thrombosis is a recognized complication of Coronavirus disease of 2019 (COVID-19) and is often associated with poor prognosis. There is a well-recognized link between coagulation and inflammation, however, the extent of thrombotic events associated with COVID-19 warrants further investigation. Poly(A) Binding Protein Cytoplasmic 4 (PABPC4), Serine/Cysteine Proteinase Inhibitor Clade G Member 1 (SERPING1) and Vitamin K epOxide Reductase Complex subunit 1 (VKORC1), which are all proteins linked to coagulation, have been shown to interact with SARS proteins. We computationally examined the interaction of these with SARS-CoV-2 proteins and, in the case of VKORC1, we describe its binding to ORF7a in detail. We examined the occurrence of variants of each of these proteins across populations and interrogated their potential contribution to COVID-19 severity. Potential mechanisms, by which some of these variants may contribute to disease, are proposed. Some of these variants are prevalent in minority groups that are disproportionally affected by severe COVID-19. Therefore, we are proposing that further investigation around these variants may lead to better understanding of disease pathogenesis in minority groups and more informed therapeutic approaches.

Sequence analysis of SARS-CoV-2 genome reveals features important for vaccine design.

As the SARS-CoV-2 pandemic is rapidly progressing, the need for the development of an effective vaccine is critical. A promising approach for vaccine development is to generate, through codon pair deoptimization, an attenuated virus. This approach carries the advantage that it only requires limited knowledge specific to the virus in question, other than its genome sequence. Therefore, it is well suited for emerging viruses, for which we may not have extensive data. We performed comprehensive in silico analyses of several features of SARS-CoV-2 genomic sequence (e.g., codon usage, codon pair usage, dinucleotide/junction dinucleotide usage, RNA structure around the frameshift region) in comparison with other members of the coronaviridae family of viruses, the overall human genome, and the transcriptome of specific human tissues such as lung, which are primarily targeted by the virus. Our analysis identified the spike (S) and nucleocapsid (N) proteins as promising targets for deoptimization and suggests a roadmap for SARS-CoV-2 vaccine development, which can be generalizable to other viruses.