Evaluating the transmission feasibility of SARS-CoV-2 Omicron (B.1.1.529) variant to 143 mammalian hosts: insights from S protein RBD and host ACE2 interaction studies.

In comparison to previously known severe respiratory syndrome coronavirus 2 (SARS-CoV-2) variants, the newly emerged Omicron (B.1.1.529) variant shows higher infectivity in humans. Exceptionally high infectivity of this variant raises concern of its possible transmission via other intermediate hosts. The SARS-CoV-2 infectivity is established via the association of spike (S) protein receptor binding domain (RBD) with host angiotensin I converting enzyme 2 (hACE2) receptor. In the course of this study, we investigated the interaction between Omicron S protein RBD with the ACE2 receptor of 143 mammalian hosts including human by protein-protein interaction analysis. The goal of this study was to forecast the likelihood that the virus may infect other mammalian species that coexist with or are close to humans in the household, rural, agricultural, or zoological environments. The Omicron RBD was found to interact with higher binding affinity with the ACE2 receptor of 122 mammalian hosts via different amino acid residues from the human ACE2 (hACE2). The rat (Rattus rattus) ACE2 was found to show the strongest interaction with Omicron RBD with a binding affinity of -1393.6 kcal/mol. These distinct strong binding affinity of RBD of Omicron with host ACE2 indicates a greater potential of new host transmissibility and infection via intermediate hosts. Though expected but the phylogenetic position of the mammalian species may not dictate the Omicron RBD binding to the host ACE2 receptor suggesting an involvement of multiple factors in guiding host divergence of the variant.

To diagnose histopathological alterations in respiratory system through radiological analysis

Histopathological alteration in the respiratory system of COVID-19 patient is mainly caused due to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). HRCT is a highly diagnostic tool to detect COVID-19, as chest computerized tomography (CT) describes pre and post effect of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on the respiratory system by radiological findings such as Ground-glass opacity, Pleural effusion, bilateral consolidation, and Interlobular septal thickening. [ FROM AUTHOR] Copyright of Professional Medical Journal is the property of Professional Medical Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Analyzing the interaction of human ACE2 and RBD of spike protein of SARS-CoV-2 in perspective of Omicron variant.

The newly identified Omicron (B.1.1.529) variant of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has steered concerns across the world due to the possession of a large number of mutations leading to high infectivity and vaccine escape potential. The Omicron variant houses 32 mutations in spike (S) protein alone. The viral infectivity is determined mainly by the ability of S protein Receptor Binding Domain (RBD) to bind to the human Angiotensin I Converting Enzyme 2 (hACE2) receptor. In this paper, the interaction of the RBDs of SARS-CoV-2 variants with hACE2 was analyzed by using protein-protein docking and compared with the novel Omicron variant. Our findings reveal that the Omicron RBD interacts strongly with hACE2 receptor via unique amino acid residues as compared to the Wuhan and many other variants. However, the interacting residues of RBD are found to be the same in Lamda (C.37) variant. This unique binding of Omicron RBD with hACE2 suggests an increased potential of infectivity and vaccine evasion potential of the new variant. The evolutionary drive of the SARS-CoV-2 may not be exclusively driven by RBD variants but surely provides for the platform for emergence of new variants.

Differential mutation profile of SARS-CoV-2 proteins across deceased and asymptomatic patients.

BACKGROUND: The SARS-CoV-2 infection has spread at an alarming rate with many places showing multiple peaks in incidence. Present study analyzes a total of 332 SARS-CoV-2 genome sequences from 114 asymptomatic and 218 deceased patients from twenty-one different countries to assess the mutation profile therein in order to establish the correlation between the clinical status and the observed mutations. METHODS: The mining of mutations was carried out using the GISAID CoVSurver (www.gisaid.org/epiflu-applications/covsurver-mutations-app) with the reference sequence 'hCoV-19/Wuhan/WIV04/2019' present in NCBI with Accession number NC-045512.2. The impact of the mutations on SARS-CoV-2 proteins mutation was predicted using PredictSNP1(loschmidt.chemi.muni.cz/predictsnp1) which is a meta-server integrating six predictor tools: SIFT, PhD-SNP, PolyPhen-1, PolyPhen-2, MAPP and SNAP. The iStable integrated server (predictor.nchu.edu.tw/iStable) was used to predict shifts in the protein stability due to mutations. RESULTS: A total of 372 variants were observed in the 332 SARS-CoV-2 sequences with several variants present in multiple patients accounting for a total of 1596 incidences. Asymptomatic and deceased specific mutants constituted 32% and 62% of the repertoire respectively indicating their partial exclusivity. However, the most prevalent mutations were those present in both. Though some parts of the genome are more variable than others but there was clear difference between incidence and prevalence. Non-structural protein 3 (NSP3) with 68 variants had a total of only 105 incidences whereas Spike protein had 346 incidences with just 66 variants. Amongst the Deleterious variants, NSP3 had the highest incidence of 25 followed by NSP2 (16), ORF3a (14) and N (14). Spike protein had just 7 Deleterious variants out of 66. CONCLUSION: Deceased patients have more Deleterious than Neutral variants as compared to the asymptomatic ones. Further, it appears that the Deleterious variants which decrease protein stability are more significant in pathogenicity of SARS-CoV-2.

Phylo-geo-network and haplogroup analysis of 611 novel coronavirus (SARS-CoV-2) genomes from India.

The novel coronavirus (SARS-CoV-2) from Wuhan China discovered in December 2019 has since developed into a global epidemic. Presently, we constructed and analyzed the phylo-geo-network of SARS-CoV-2 genomes from across India to understand the viral evolution in the country. A total of 611 full-length genomes from different states of India were extracted from the EpiCov repository of GISAID initiative on 6 June, 2020. Their alignment with the reference sequence (Wuhan, NCBI accession number NC_045512.2) uncovered 270 parsimony informative sites. Furthermore, 339 genomes were divided into 51 haplogroups. The network revealed the core haplogroup as that of reference sequence NC_045512.2 (Haplogroup A1) with 157 identical sequences present across 16 states. Remaining haplogroups had <10 identical sequences across a maximum of three states. Some states with fewer samples had more haplogroups. Forty-one haplogroups were localized exclusively to any one state. The two most common lineages are B6 and B1 (Pangolin) whereas clade A2a (Covidex) appears to be the most predominant in India. Because the pandemic is still emerging, the observations need to be monitored.

Mutational analysis and assessment of its impact on proteins of SARS-CoV-2 genomes from India.

Mutational status of SARS-CoV-2 genomes from India along with their impact on proteins was ascertained through multiple tools including MEGA, Genome Detective, SIFT, PROVEAN and ws-SNPs&GO. Excluding gaps and ambiguous sequences, 493 variable sites (152 parsimony informative and 341 singleton) were observed. NSP3 had the highest incidence of 101 sites followed by S protein (74), NSP12b (43) and ORF3a (31). Average mutations per sample for males and females was 2.56 and 2.88 respectively. Non-uniform geographical distribution of mutations suggests that sequences in some regions are mutating faster than others. There were 281 mutations (198 Neutral and 83 Disease) affecting amino acid sequence. NSP13 has a maximum of 14 Disease variants followed by S protein and ORF3a with 13 each. Disease mutations in genomes from asymptomatic people was mere 11% but those from deceased patients was at 38% indicating contribution of these mutations to the pathophysiology of the SARS-CoV-2.