Global variation in SARS-CoV-2 proteome and its implication in pre-lockdown emergence and dissemination of 5 dominant SARS-CoV-2 clades

Patro, L. Ponoop Prasad; Sathyaseelan, Chakkarai; Uttamrao, Patil Pranita; Rathinavelan, Thenmalarchelvi

doi:10.1016/j.meegid.2021.104973

Cited by 13 publications

(18 citation statements)

References 44 publications

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“…In our results, some COVID-19 mutations associated with mild disease were also found, such as nsp14:I164ILV, ORF8:L84S, nsp4:F308Y, nsp6:L37F, ORF3a:G196V, N:P13L, nsp4:M324I, and N:G204R. These mutations tend to be present in low-risk patients with different combinations, and some have been reported to be associated with mild disease or disease transmissibility [ 55 , 60 ].…”

Section: Discussionsupporting

confidence: 52%

“…D614G is a hotspot mutation that appeared as early as the Alpha variant, and although the D614G mutation does not directly correlate with disease severity, other COVID-19 variants containing this mutation may accelerate infection due to the ability to facilitate viral entry into cells and further aggravate the disease [ 54 , 59 ]. ORF3a:Q57H and nsp2:T85I first appeared in the Beta variants and our results suggest that they may be associated with severe outcomes of SARS-CoV-2 infection [ 60 ]. Studies have shown that SNP:C241T mutation is associated with lower viral replication efficiency [ 61 ] and it can be observed in our results that mild patients with SNP:C241T mutation tend to be combined with less other severe mutation features (e.g., nsp2:T85I, ORF3a:Q57H, and V1176F), which suggests that this gene mutation may be indirectly associated with mild COVID-19.…”

Section: Discussionmentioning

confidence: 99%

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Identifying COVID-19 Severity-Related SARS-CoV-2 Mutation Using a Machine Learning Method

Huang

Chen

Guo

et al. 2022

Life

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SARS-CoV-2 shows great evolutionary capacity through a high frequency of genomic variation during transmission. Evolved SARS-CoV-2 often demonstrates resistance to previous vaccines and can cause poor clinical status in patients. Mutations in the SARS-CoV-2 genome involve mutations in structural and nonstructural proteins, and some of these proteins such as spike proteins have been shown to be directly associated with the clinical status of patients with severe COVID-19 pneumonia. In this study, we collected genome-wide mutation information of virulent strains and the severity of COVID-19 pneumonia in patients varying depending on their clinical status. Important protein mutations and untranslated region mutations were extracted using machine learning methods. First, through Boruta and four ranking algorithms (least absolute shrinkage and selection operator, light gradient boosting machine, max-relevance and min-redundancy, and Monte Carlo feature selection), mutations that were highly correlated with the clinical status of the patients were screened out and sorted in four feature lists. Some mutations such as D614G and V1176F were shown to be associated with viral infectivity. Moreover, previously unreported mutations such as A320V of nsp14 and I164ILV of nsp14 were also identified, which suggests their potential roles. We then applied the incremental feature selection method to each feature list to construct efficient classifiers, which can be directly used to distinguish the clinical status of COVID-19 patients. Meanwhile, four sets of quantitative rules were set up, which can help us to more intuitively understand the role of each mutation in differentiating the clinical status of COVID-19 patients. Identified key mutations linked to virologic properties will help better understand the mechanisms of infection and will aid in the development of antiviral treatments.

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Section: Discussionsupporting

confidence: 52%

Section: Discussionmentioning

confidence: 99%

Identifying COVID-19 Severity-Related SARS-CoV-2 Mutation Using a Machine Learning Method

Huang

Chen

Guo

et al. 2022

Life

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“…146 Notably, the increased transmissibility and pathogenicity of some SARS-CoV-2 variants are closely related to Nsp2 mutations, such as T85I of Nsp2 in the B.1.526/B.1.427/B.1.429 variant. 147 – 149 The presumed explanation is that mutations interfere with the interaction between Nsp2 and host proteins, 141 ultimately affecting virulence. The immunogenicity of Nsp2 can be applied to the development of inactive or live attenuated virus vaccine.…”

Section: Nonstructural Proteins Of Sras-cov-2mentioning

confidence: 99%

Structural biology of SARS-CoV-2: open the door for novel therapies

Zheng

Zeng

et al. 2022

Sig Transduct Target Ther

198

149

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Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is the causative agent of the pandemic disease COVID-19, which is so far without efficacious treatment. The discovery of therapy reagents for treating COVID-19 are urgently needed, and the structures of the potential drug-target proteins in the viral life cycle are particularly important. SARS-CoV-2, a member of the Orthocoronavirinae subfamily containing the largest RNA genome, encodes 29 proteins including nonstructural, structural and accessory proteins which are involved in viral adsorption, entry and uncoating, nucleic acid replication and transcription, assembly and release, etc. These proteins individually act as a partner of the replication machinery or involved in forming the complexes with host cellular factors to participate in the essential physiological activities. This review summarizes the representative structures and typically potential therapy agents that target SARS-CoV-2 or some critical proteins for viral pathogenesis, providing insights into the mechanisms underlying viral infection, prevention of infection, and treatment. Indeed, these studies open the door for COVID therapies, leading to ways to prevent and treat COVID-19, especially, treatment of the disease caused by the viral variants are imperative.

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“…For this, the gene sequences corresponding to the uORFs were translated using the reference sequences (36) with the help of in-house scripts. The amino acid mutation analyses were done as discussed elsewhere (9,10). The mutations were categorized as highly recurring (HR, occurring with ≥10% percentage frequency), moderately recurring (MR, occurring with 1%-10% percentage frequency), and low recurring (LR, occurring below 1% percentage frequency but should have occurred at least three times) based on their recurrence in the 775,392 viral proteomes.…”

Section: Determination Of Sars-cov-2 Uorf Sequence Conservationmentioning

confidence: 99%

“…Indeed, there are reports (7,8) about the reduced efficacy of the vaccines against the new variants (4). Reports indicate that the number of mutations in the spike protein has increased to 1.4-fold in a time span of 6 months (9,10). This is indicative of challenges in using the existing spike protein antigen-based vaccines (11) when new variants emerge.…”

Section: Introductionmentioning

confidence: 99%

Revelation of Potent Epitopes Present in Unannotated ORF Antigens of SARS-CoV-2 for Epitope-Based Polyvalent Vaccine Design Using Immunoinformatics Approach

et al. 2021

Self Cite

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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) kills thousands of people worldwide every day, thus necessitating rapid development of countermeasures. Immunoinformatics analyses carried out here in search of immunodominant regions in recently identified SARS-CoV-2 unannotated open reading frames (uORFs) have identified eight linear B-cell, one conformational B-cell, 10 CD4+ T-cell, and 12 CD8+ T-cell promising epitopes. Among them, ORF9b B-cell and T-cell epitopes are the most promising followed by M.ext and ORF3c epitopes. ORF9b40-48 (CD8+ T-cell epitope) is found to be highly immunogenic and antigenic with the highest allele coverage. Furthermore, it has overlap with four potent CD4+ T-cell epitopes. Structure-based B-cell epitope prediction has identified ORF9b61-68 to be immunodominant, which partially overlaps with one of the linear B-cell epitopes (ORF9b65-69). ORF3c CD4+ T-cell epitopes (ORF3c2-16, ORF3c3-17, and ORF3c4-18) and linear B-cell epitope (ORF3c14-22) have also been identified as the candidate epitopes. Similarly, M.ext and 7a.iORF1 (overlap with M and ORF7a) proteins have promising immunogenic regions. By considering the level of antigen expression, four ORF9b and five M.ext epitopes are finally shortlisted as potent epitopes. Mutation analysis has further revealed that the shortlisted potent uORF epitopes are resistant to recurrent mutations. Additionally, four N-protein (expressed by canonical ORF) epitopes are found to be potent. Thus, SARS-CoV-2 uORF B-cell and T-cell epitopes identified here along with canonical ORF epitopes may aid in the design of a promising epitope-based polyvalent vaccine (when connected through appropriate linkers) against SARS-CoV-2. Such a vaccine can act as a bulwark against SARS-CoV-2, especially in the scenario of emergence of variants with recurring mutations in the spike protein.

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Global variation in SARS-CoV-2 proteome and its implication in pre-lockdown emergence and dissemination of 5 dominant SARS-CoV-2 clades

Cited by 13 publications

References 44 publications

Identifying COVID-19 Severity-Related SARS-CoV-2 Mutation Using a Machine Learning Method

Identifying COVID-19 Severity-Related SARS-CoV-2 Mutation Using a Machine Learning Method

Structural biology of SARS-CoV-2: open the door for novel therapies

Revelation of Potent Epitopes Present in Unannotated ORF Antigens of SARS-CoV-2 for Epitope-Based Polyvalent Vaccine Design Using Immunoinformatics Approach

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