Identification and molecular characterization of mutations in nucleocapsid phosphoprotein of SARS-CoV-2

COV2Var, a function annotation database of SARS-CoV-2 genetic variation

The COVID-19 pandemic, caused by the coronavirus SARS-CoV-2, has resulted in the loss of millions of lives and severe global economic consequences. Every time SARS-CoV-2 replicates, the viruses acquire new mutations in their genomes. Mutations in SARS-CoV-2 genomes led to increased transmissibility, severe disease outcomes, evasion of the immune response, changes in clinical manifestations and reducing the efficacy of vaccines or treatments. To date, the multiple resources provide lists of detected mutations without key functional annotations. There is a lack of research examining the relationship between mutations and various factors such as disease severity, pathogenicity, patient age, patient gender, cross-species transmission, viral immune escape, immune response level, viral transmission capability, viral evolution, host adaptability, viral protein structure, viral protein function, viral protein stability and concurrent mutations. Deep understanding the relationship between mutation sites and these factors is crucial for advancing our knowledge of SARS-CoV-2 and for developing effective responses. To fill this gap, we built COV2Var, a function annotation database of SARS-CoV-2 genetic variation, available at http://biomedbdc.wchscu.cn/COV2Var/. COV2Var aims to identify common mutations in SARS-CoV-2 variants and assess their effects, providing a valuable resource for intensive functional annotations of common mutations among SARS-CoV-2 variants.

A computational study on mitogenome-encoded proteins of Pavo cristatus and Pavo muticus identifies key genetic variations with functional implications

BACKGROUND

The Pavo cristatus population, native to the Indian subcontinent, is thriving well in India. However, the Pavo muticus population, native to the tropical forests of Southeast Asia, has reduced drastically and has been categorised as an endangered group. To understand the probable genetic factors associated with the decline of P. muticus, we compared the mitogenome-encoded proteins (13 proteins) between these two species.

RESULTS

Our data revealed that the most frequent variant between these two species was mtND1, which had an alteration in 9.57% residues, followed by mtND5 and mtATP6. We extended our study on the rest of the proteins and observed that cytochrome c oxidase subunits 1, 2, and 3 do not have any change. The 3-dimensional structure of all 13 proteins was modeled using the Phyre2 programme. Our data show that most of the proteins are alpha helical, and the variations observed in P. muticus reside on the surface of the respective proteins. The effect of variation on protein function was also predicted, and our results show that amino acid substitution in mtND1 at 14 sites could be deleterious. Similarly, destabilising changes were observed in mtND1, 2, 3, 4, 5, and 6 and mtATP6-8 due to amino acid substitution in P. muticus. Furthermore, protein disorder scores were considerably altered in mtND1, 2, and 5 of P. muticus.

CONCLUSIONS

The results presented here strongly suggest that variations in mitogenome-encoded proteins of P. cristatus and P. muticus may alter their structure and functions. Subsequently, these variations could alter energy production and may correlate with the decline in the population of P. muticus.

A multi-population-based genomic analysis uncovers unique haplotype variants and crucial mutant genes in SARS-CoV-2

Background

COVID-19 is a disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Rigorous detection and treatment strategies against SARS-CoV-2 have become very challenging due to continuous evolutions to the viral genome. Therefore, careful genomic analysis is sorely needed to understand transmission, the cellular mechanism of pathogenicity, and the development of vaccines or drugs.

Objective

In this study, we intended to identify SARS-CoV-2 genome variants that may help understand the cellular and molecular foundation of coronavirus infections required to develop effective intervention strategies.

Methods

SARS-CoV-2 genome sequences were downloaded from an open-source public database, processed, and analyzed for variants in target detection sites and genes.

Results

We have identified six unique variants, G---AAC, T---AAC---T, AAC---T, AAC--------T, C----------T, and C--------C, at the nucleocapsid region and eleven major hotspot mutant genes: nsp3, surface glycoprotein, nucleocapsid phosphoprotein, ORF8, nsp6, nsp2, nsp4, helicase, membrane glycoprotein, 3′-5′ exonuclease, and 2′-O-ribose methyltransferases. In addition, we have identified eleven major mutant genes that may have a crucial role in SARS-CoV-2 pathogenesis.

Conclusion

Studying haplotype variants and 11 major mutant genes to understand the mechanism of action of fatal pathogenicity and inter-individual variations in immune responses is inevitable for managing target patient groups with identified variants and developing effective anti-viral drugs and vaccines.

Supplementary Information

The online version contains supplementary material available at 10.1186/s43141-022-00431-3.

The impacts of 13 novel mutations of SARS-CoV-2 on protein dynamics: In silico analysis from Turkey

SARS-CoV-2 inherits a high rate of mutations making it better suited to the host since its fundamental role in evolution is to provide diversity into the genome. This research aims to identify variations in Turkish isolates and predict their impacts on proteins. To identify novel variations and predict their impacts on protein dynamics, in silico methodology was used. The 411 sequences from Turkey were analysed. Secondary structure prediction by Garnier-Osguthorpe-Robson (GOR) was used. To find the effects of identified Spike mutations on protein dynamics, the SARS-CoV-2 structures (PDB:6VYB, 6M0J) were uploaded and predicted by Cutoff Scanning Matrix (mCSM), DynaMut and MutaBind2. To understand the effects of these mutations on Spike protein molecular dynamics (MD) simulation was employed. Turkish sequences were aligned with sequences worldwide by MUSCLE, and phylogenetic analysis was performed via MegaX. The 13 novel mutations were identified, and six of them belong to spike glycoprotein. Ten of these variations revealed alteration in the secondary structure of the protein. Differences of free energy between the reference sequence and six mutants were found below zero for each of six isolates, demonstrating these variations have stabilizing effects on protein structure. Differences in vibrational entropy calculation revealed that three variants have rigidification, while the other three have a flexibility effect. MD simulation revealed that point mutations in spike glycoprotein and RBD:ACE-2 complex cause changes in protein dynamics compared to the wild-type, suggesting possible alterations in binding affinity. The phylogenetic analysis showed Turkish sequences distributed throughout the tree, revealing multiple entrances to Turkey.

SARS CoV-2 (Delta Variant) Infection Kinetics and Immunopathogenesis in Domestic Cats

Continued emergence of SARS-CoV-2 variants highlights the critical need for adaptable and translational animal models for acute COVID-19. Limitations to current animal models for SARS CoV-2 (e.g., transgenic mice, non-human primates, ferrets) include subclinical to mild lower respiratory disease, divergence from clinical COVID-19 disease course, and/or the need for host genetic modifications to permit infection. We therefore established a feline model to study COVID-19 disease progression and utilized this model to evaluate infection kinetics and immunopathology of the rapidly circulating Delta variant (B.1.617.2) of SARS-CoV-2. In this study, specific-pathogen-free domestic cats (n = 24) were inoculated intranasally and/or intratracheally with SARS CoV-2 (B.1.617.2). Infected cats developed severe clinical respiratory disease and pulmonary lesions at 4- and 12-days post-infection (dpi), even at 1/10 the dose of previously studied wild-type SARS-CoV-2. Infectious virus was isolated from nasal secretions of delta-variant infected cats in high amounts at multiple timepoints, and viral antigen was co-localized in ACE2-expressing cells of the lungs (pneumocytes, vascular endothelium, peribronchial glandular epithelium) and strongly associated with severe pulmonary inflammation and vasculitis that were more pronounced than in wild-type SARS-CoV-2 infection. RNA sequencing of infected feline lung tissues identified upregulation of multiple gene pathways associated with cytokine receptor interactions, chemokine signaling, and viral protein–cytokine interactions during acute infection with SARS-CoV-2. Weighted correlation network analysis (WGCNA) of differentially expressed genes identified several distinct clusters of dysregulated hub genes that are significantly correlated with both clinical signs and lesions during acute infection. Collectively, the results of these studies help to delineate the role of domestic cats in disease transmission and response to variant emergence, establish a flexible translational model to develop strategies to prevent the spread of SARS-CoV-2, and identify potential targets for downstream therapeutic development.

Prevalence and circulation patterns of SARS-CoV-2 variants in European sewage mirror clinical data of 54 European cities

For community-level monitoring, the European Commission under the EU Sewage Sentinel System recommends wastewater-based SARS-CoV-2 surveillance. Tracking SARS-CoV-2 variants in a community is pivotal for appropriate public health response. Genome sequencing of SARS-CoV-2 in wastewater samples for tracking variants is challenging, often resulting in low coverage genome sequences, thereby impeding the detection of the SARS-CoV-2 mutations. Therefore, we aimed at high-coverage SARS-CoV-2 genome sequences from sewage samples which we successfully accomplished. This first pan-European surveillance compared the mutation profiles associated with the variants of concerns: B.1.1.7, P.1, B.1.351 and B.1.617.2 across 20 European countries, including 54 municipalities. The results highlight that SARS-CoV-2 variants detected in the wastewater samples mirror the variants profiles reported in clinical data. This study demonstrated that >98% coverage of SARS-CoV-2 genomic sequences is possible and can be used to track SARS-CoV-2 mutations in wastewater to support identifying variants circulating in a city at the community level.

Sequence Analysis, Structure Prediction of Receptor Proteins and In Silico Study of Potential Inhibitors for Management of Life Threatening COVID-19

Background:

Treatment of the Covid-19 pandemic caused by the highly contagious and pathogenic SARS-CoV-2 is a global menace. Day by day, this pandemic is getting worse. Doctors, scientists and researchers across the world are urgently scrambling for a cure for novel corona virus and continuously working at break neck speed to develop vaccines or drugs. But to date, there are no specific drugs or vaccines available in the market to cope up with the virus.

Objective:

The present study helps us to elucidate 3D structures of SARS-CoV-2 proteins and also to identify natural compounds as potential inhibitors against COVID-19.

Methods:

The 3D structures of the proteins were constructed using Modeller 9.16 modeling tool. Modelled proteins were validated with PROCHECK by Ramachandran plot analysis. In this study, a small library of natural compounds (fifty compounds) was docked to the hACE2 binding site of the modelled surface glycoprotein of SARS-CoV-2 using AutoDock Vina to repurpose these inhibitors against SARS-CoV-2. Conceptual density functional theory calculations of the best eight compounds had been performed by Gaussian-09. Geometry optimizations for these molecules were done at M06-2X/ def2-TZVP level of theory. ADME parameters, pharmacokinetic properties and drug likeness of the compounds were analyzed using swissADME website.

Results:

In this study, we analysed the sequences of surface glycoprotein, nucleocapsid phosphoprotein and envelope protein obtained from different parts of the globe. We modelled all the different sequences of surface glycoprotein and envelop protein in order to derive 3D structure of a molecular target, which is essential for the development of therapeutics. Different electronic properties of the inhibitors have been calculated using DFT through M06-2X functional with def2-TZVP basis set. Docking result at the hACE2 binding site of all modelled surface glycoproteins of SARSCoV- 2 showed that all the eight inhibitors (actinomycin D, avellanin C, ichangin, kanglemycin A, obacunone, ursolic acid, ansamiotocin P-3 and isomitomycin A) studied here were many folds better compared to hydroxychloroquine which has been found to be effective to treat patients suffering from COVID-19. All the inhibitors meet most of the criteria of drug likeness assessment.

Conclusion:

We expect that eight compounds (actinomycin D, avellanin C, ichangin, kanglemycin A, obacunone, ursolic acid, ansamiotocin P-3 and isomitomycin A) can be used as potential inhibitors against SARS-CoV-2.

Prediction of the Effects of Nonsynonymous Variants on SARS-CoV-2 Proteins

Background: SARS-CoV-2 virus is a highly transmissible pathogen that causes COVID-19. The outbreak originated in Wuhan, China in December 2019. A number of nonsynonymous mutations located at different SARS-CoV-2 proteins have been reported by multiple studies. However, there are limited computational studies on the biological impacts of these mutations on the structure and function of the proteins.   Methods: In our study nonsynonymous mutations of the SARS-CoV-2 genome and their frequencies were identified from 30,229 sequences. Subsequently, the effects of the top 10 nonsynonymous mutations of different SARS-CoV-2 proteins were analyzed using bioinformatics tools including co-mutation analysis, prediction of the protein structure stability and flexibility analysis, and prediction of the protein functions.   Results: A total of 231 nonsynonymous mutations were identified from 30,229 SARS-CoV-2 genome sequences. The top 10 nonsynonymous mutations affecting nine amino acid residues were ORF1a nsp5 P108S, ORF1b nsp12 P323L and A423V, S protein N501Y and D614G, ORF3a Q57H, N protein P151L, R203K and G204R. Many nonsynonymous mutations showed a high concurrence ratio, suggesting these mutations may evolve together and interact functionally. Our result showed that ORF1a nsp5 P108S, ORF3a Q57H and N protein P151L mutations may be deleterious to the function of SARS-CoV-2 proteins. In addition, ORF1a nsp5 P108S and S protein D614G may destabilize the protein structures while S protein D614G may have a more open conformation compared to the wild type.   Conclusion: The biological consequences of these nonsynonymous mutations of SARS-CoV-2 proteins should be further validated by in vivo and in vitro experimental studies in the future.

Prediction of the effects of the top 10 nonsynonymous variants from 30229 SARS-CoV-2 strains on their proteins

Background: SARS-CoV-2 virus is a highly transmissible pathogen that causes COVID-19. The outbreak originated in Wuhan, China in December 2019. A number of nonsynonymous mutations located at different SARS-CoV-2 proteins have been reported by multiple studies. However, there are limited computational studies on the biological impacts of these mutations on the structure and function of the proteins.   Methods: In our study nonsynonymous mutations of the SARS-CoV-2 genome and their frequencies were identified from 30,229 sequences. Subsequently, the effects of the top 10 highest frequency nonsynonymous mutations of different SARS-CoV-2 proteins were analyzed using bioinformatics tools including co-mutation analysis, prediction of the protein structure stability and flexibility analysis, and prediction of the protein functions.   Results: A total of 231 nonsynonymous mutations were identified from 30,229 SARS-CoV-2 genome sequences. The top 10 nonsynonymous mutations affecting nine amino acid residues were ORF1a nsp5 P108S, ORF1b nsp12 P323L and A423V, S protein N501Y and D614G, ORF3a Q57H, N protein P151L, R203K and G204R. Many nonsynonymous mutations showed a high concurrence ratio, suggesting these mutations may evolve together and interact functionally. Our result showed that ORF1a nsp5 P108S, ORF3a Q57H and N protein P151L mutations may be deleterious to the function of SARS-CoV-2 proteins. In addition, ORF1a nsp5 P108S and S protein D614G may destabilize the protein structures while S protein D614G may have a more open conformation compared to the wild type.   Conclusion: The biological consequences of these nonsynonymous mutations of SARS-CoV-2 proteins should be further validated by in vivo and in vitro experimental studies in the future.

Immunoinformatics Study of SARS-CoV-2 Nucleocapsid Phosphoprotein Identifies Promising Epitopes with Mutational Implications

The SARS-CoV-2 is rapidly evolving and new mutations are being reported from different parts of the world. In this study, we investigated the variations occurring in the nucleocapsid phosphoprotein (N-protein) of SARS-CoV-2 from India. We used several in silico prediction tools to characterise N-protein including IEDB webserver for B cell epitope prediction, Vaxijen 2.0 and AllergenFP v.1.0 for antigenicity and allergenicity prediction of epitopes, CLUSTAL Omega for mutation identification and PONDR webserver for disorder prediction, PROVEAN score for protein function and iMutantsuite for protein stability prediction. Our results show that 81 mutations have occurred in this protein among Indian SARS-CoV-2 isolates. Subsequently, we characterized the N-protein epitopes to identify seven most promising peptides. We mapped these mutations with seven N-protein epitopes to identify the loss of antigenicity in two of them, suggesting that the mutations occurring in the SARS-CoV-2 genome contribute to the alteration in the properties of epitopes. Altogether, our data strongly indicates that N-protein is gaining several mutations in its B cell epitope regions that might alter protein function.

Lipopeptides against COVID-19 RNA-dependent RNA polymerase using molecular docking

Background

Coronavirus disease 2019 (COVID-19) is caused by a novel virus that is responsible for the largest pandemic in recent times. Although numerous studies have explored methods to cope with COVID-19 and targeted drugs and vaccines have been developed, the spread of disease remains rapid due to the high infectivity and mutation capability of SARS-CoV-2, the causative virus of COVID-19. Therefore, there is an urgent necessity to seek more efficient treatments and approaches to combat the disease.

Methods

In this study, molecular docking was used to predict the binding of different lipopeptides, which exhibit significant biological functions, to the RNA-dependent RNA polymerase (also known as nsp12) of SARS-CoV-2, the central component of coronaviral replication and transcription machinery.

Results

The results showed that seven lipopeptides bound to nsp12 at the same location as the FDA-approved drug remdesivir, with higher affinities. Notably, iron-chelating ferrocin A (ferrocin A–iron complex [FAC]) bound to nsp12 most tightly, releasing up to 9.1 kcal mol⁻¹ of free energy. Protein-ligand interaction analysis revealed that FAC formed four hydrogen bonds, two hydrophobic interactions, and three salt bridges with nsp12. These active amino acids are mainly distributed in the fingers and thumb subdomains of nsp12 and are highly conserved.

Conclusions

Our findings suggest that the abovementioned lipopeptides can tightly bind to nsp12, and thus represent promising drug candidates for anti-coronaviral treatments with the potential to fight SARS-CoV-2.

Emerging genetic diversity of SARS-CoV-2 RNA dependent RNA polymerase (RdRp) alters its B-cell epitopes

The RNA dependent RNA polymerase (RdRp) plays crucial role in virus life cycle by replicating the viral genome. The SARS-CoV-2 is an RNA virus that rapidly spread worldwide and acquired mutations. This study was carried out to identify mutations in RdRp as the SARS-CoV-2 spread in India. We compared 50217 RdRp sequences reported from India with the first reported RdRp sequence from Wuhan, China to identify 223 mutations acquired among Indian isolates. Our protein modelling study revealed that several mutants can potentially alter stability and flexibility of RdRp. We predicted the potential B cell epitopes contributed by RdRp and identified thirty-six linear continuous and twenty-five discontinuous epitopes. Among 223 RdRp mutants, 44% of them localises in the B cell epitopes region. Altogether, this study highlights the need to identify and characterize the variations in RdRp to understand the impact of these mutations on SARS-CoV-2.

Impact of animal saliva on the performance of rapid antigen tests for detection of SARS-CoV-2 (wildtype and variants B.1.1.7 and B.1.351)

SARS-CoV-2 infects several animal species and SARS-CoV-2 variants of concern (VOCs) may even show (as in humans) enhanced inter- and intra-species transmission rates. We correlated sensitivity data of SARS-CoV-2 rapid antigen tests (RATs) to viral RNA genome equivalents analyzed by real-time reverse transcriptase-polymerase chain reaction (RT-PCR). Further, we checked their suitability for testing animals by assessing saliva and VOC effects. Viral loads up to 2 logs (RNA copy number) under the hypothetical SARS-CoV-2 infectivity threshold were detected by most analyzed RATs. However, while saliva from various animal species showed generally no adverse effects on the RATs' analytical sensitivities, the detection of VOCs B.1.1.7 and B.1.351 was in some RATs inferior to non-VOC viruses.

In Vitro Rapid Antigen Test Performance with the SARS-CoV-2 Variants of Concern B.1.1.7 (Alpha), B.1.351 (Beta), P.1 (Gamma), and B.1.617.2 (Delta)

Rapid antigen tests (RATs) are an integral part of SARS-CoV-2 containment strategies. As emerging variants of concern (VOCs) displace the initially circulating strains, it is crucial that RATs do not fail to detect these new variants. In this study, four RATs for nasal swab testing were investigated using cultured strains of B.1.1 (non-VOC), B.1.1.7 (Alpha), B.1.351 (Beta), P.1 (Gamma), and B.1.617.2 (Delta). Based on dilution series in cell culture medium and pooled saliva, the limit of detection of these RATs was determined in a laboratory setting. Further investigations on cross-reactivity were conducted using recombinant N-protein from seasonal human coronaviruses (hCoVs). RATs evaluated showed an overall comparable performance with cultured strains of the non-VOC B.1.1 and the VOCs Alpha, Beta, Gamma, and Delta. No cross-reactivity was detected with recombinant N-protein of the hCoV strains HKU1, OC43, NL63, and 229E. A continuous evaluation of SARS-CoV-2 RAT performance is required, especially with regard to evolving mutations. Moreover, cross-reactivity and interference with pathogens and other substances on the test performance of RATs should be consistently investigated to ensure suitability in the context of SARS-CoV-2 containment.

Detection of the new SARS-CoV-2 variants of concern B.1.1.7 and B.1.351 in five SARS-CoV-2 rapid antigen tests (RATs), Germany, March 2021

SARS-CoV-2 variants of concern (VOC) should not escape molecular surveillance. We investigated if SARS-CoV-2 rapid antigen tests (RATs) could detect B.1.1.7 and B.1.351 VOCs in certain laboratory conditions. Infectious cell culture supernatants containing B.1.1.7, B.1.351 or non-VOC SARS-CoV-2 were respectively diluted both in DMEM and saliva. Dilutions were analysed with Roche, Siemens, Abbott, nal von minden and RapiGEN RATs. While further studies with appropriate real-life clinical samples are warranted, all RATs detected B.1.1.7 and B.1.351, generally comparable to non-VOC strain.