Structural and Phylogenetic Analysis of SARS-CoV-2 Spike Glycoprotein from the Most Widespread Variants

The increase in SARS-CoV-2 lineages during 2020-2022 in a state in the Brazilian Northeast is associated with a number of cases

SARS-CoV-2 has caused a high number of deaths in several countries. In Brazil, there were 37 million confirmed cases of COVID-19 and 700,000 deaths caused by the disease. The population size and heterogeneity of the Brazilian population should be considered in epidemiological surveillance due to the varied tropism of the virus. As such, municipalities and states must be factored in for their unique specificities, such as socioeconomic conditions and population distribution. Here, we investigate the spatiotemporal dispersion of emerging SARS-CoV-2 lineages and their dynamics in each microregion from Sergipe state, northeastern Brazil, in the first 3 years of the pandemic. We analyzed 586 genomes sequenced between March 2020 and November 2022 extracted from the GISAID database. Phylogenetic analyses were carried out for each data set to reconstruct evolutionary history. Finally, the existence of a correlation between the number of lineages and infection cases by SARS-CoV-2 was evaluated. Aracaju, the largest city in northeastern Brazil, had the highest number of samples sequenced. This represented 54.6% (320) of the genomes, and consequently, the largest number of lineages identified. Studies also analyzed the relationship between mean lineage distributions and mean monthly infections, daily cases, daily deaths, and hospitalizations of vaccinated and unvaccinated patients. For this, a correlation matrix was created. Results revealed that the increase in the average number of SARS-CoV-2 variants was related to the average number of SARS-CoV-2 cases in both unvaccinated and vaccinated individuals. Thus, our data indicate that it is necessary to maintain epidemiological surveillance, especially in capital cities, since they have a high rate of circulation of resident and non-resident inhabitants, which contributes to the dynamics of the virus.

Anomaly Detection Models for SARS-CoV-2 Surveillance Based on Genome k-mers

Since COVID-19 has brought great challenges to global public health governance, developing methods that track the evolution of the virus over the course of an epidemic or pandemic is useful for public health. This paper uses anomaly detection models to analyze SARS-CoV-2 virus genome k-mers to predict possible new critical variants in the collected samples. We used the sample data from Argentina, China and Portugal obtained from the Global Initiative on Sharing All Influenza Data (GISAID) to conduct multiple rounds of evaluation on several anomaly detection models, to verify the feasibility of this virus early warning and surveillance idea and find appropriate anomaly detection models for actual epidemic surveillance. Through multiple rounds of model testing, we found that the LUNAR (learnable unified neighborhood-based anomaly ranking) and LUNAR+LUNAR stacking model performed well in new critical variants detection. The results of simulated dynamic detection validate the feasibility of this approach, which can help efficiently monitor samples in local areas.

Mutational Analysis of Circulating Omicron SARS-CoV-2 Lineages in the Al-Baha Region of Saudi Arabia

Purpose

Omicron (B.1.1.529) is one of the highly mutated variants of concern of SARS-CoV-2. Lineages of Omicron bear a remarkable degree of mutations leading to enhanced pathogenicity and upward transmission trajectory. Mutating Omicron lineages may trigger a fresh COVID-19 wave at any time in any region. We aimed at the whole-genome sequencing of SARS-CoV-2 to determine variants/subvariants and significant mutations which can foster virus evolution, monitoring of disease spread, and outbreak management.

Methods

We used Illumina-NovaSeq 6000 for SARS-CoV-2 genome sequencing, MEGA 10.2 and nextstrain tools for phylogeny; CD-HIT program (version 4.8.1) and MUSCLE program for clustering and alignment. At the same time, UCSF Chimera was employed for protein visualization.

Results

Predominant Omicron pango lineages in Al-Baha were BA.5.2/B22 (n=4, 57%), and other lineages were BA.2.12/21L (n=1, 14.28%), BV.1/22B (n=1, 14.28%) and BA.5.2.18/22B (n=1, 14.28%). 22B nextstrain clade was predominant, while only one lineage showed 21L. BA.5.2/22B, BA.5.2/22B harbored a maximum of n=24 mutations in the spike region. Twelve crucial RBD mutations: D405N, R408S, K417N, N440K, L452R, S477N, T478K, E484A, F486V, Q498R, N501Y, and Y505H were identified except the lineage BA.5.2/22B in which F486V mutation was not observed. Critical deletions S106 in membrane protein NSP6, E31in nucleocapsid, and L24 in spike region were observed in all the lineages. Furthermore, we identified common mutations of Omicron variants of SARS-CoV-2 in therapeutic hot spot spike region: T19I, D405N, R408S, K417N, N440K, L452R, S477N, T478K, E484A, F486V, Q498R, N501Y, Y505H, D614G, A653V, H655Y, N679K, P681H, N764K, D796Y, Q954H, N969K, D1146D, L452R, F486V, N679K and D796Y. The effect of RBD-targeted mutations on neutralizing (NAbs) binding was considerable.

Conclusion

The outcome of this first report on SARS-CoV-2 variants identification and mutation in the Al-Baha region could be used to lay down the policies to manage and impede the regional outbreak of COVID-19 effectively.

Comparative Binding Ability of Human Monoclonal Antibodies against Omicron Variants of SARS-CoV-2: An In Silico Investigation

Mutation(s) in the spike protein is the major characteristic trait of newly emerged SARS-CoV-2 variants such as Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Delta (B.1.617.2), and Delta-plus. Omicron (B.1.1.529) is the latest addition and it has been characterized by high transmissibility and the ability to escape host immunity. Recently developed vaccines and repurposed drugs exert limited action on Omicron strains and hence new therapeutics are immediately needed. Herein, we have explored the efficiency of twelve therapeutic monoclonal antibodies (mAbs) targeting the RBD region of the spike glycoprotein against all the Omicron variants bearing a mutation in spike protein through molecular docking and molecular dynamics simulation. Our in silico evidence reveals that adintivimab, beludivimab, and regadanivimab are the most potent mAbs to form strong biophysical interactions and neutralize most of the Omicron variants. Considering the efficacy of mAbs, we incorporated CDRH3 of beludavimab within the framework of adintrevimab, which displayed a more intense binding affinity towards all of the Omicron variants viz. BA.1, BA.2, BA.2.12.1, BA.4, and BA.5. Furthermore, the cDNA of chimeric mAb was cloned in silico within pET30ax for recombinant production. In conclusion, the present study represents the candidature of human mAbs (beludavimab and adintrevimab) and the therapeutic potential of designed chimeric mAb for treating Omicron-infected patients.

SARS-CoV-2 S Glycoprotein Stabilization Strategies

The SARS-CoV-2 pandemic has again shown that structural biology plays an important role in understanding biological mechanisms and exploiting structural data for therapeutic interventions. Notably, previous work on SARS-related glycoproteins has paved the way for the rapid structural determination of the SARS-CoV-2 S glycoprotein, which is the main target for neutralizing antibodies. Therefore, all vaccine approaches aimed to employ S as an immunogen to induce neutralizing antibodies. Like all enveloped virus glycoproteins, SARS-CoV-2 S native prefusion trimers are in a metastable conformation, which primes the glycoprotein for the entry process via membrane fusion. S-mediated entry is associated with major conformational changes in S, which can expose many off-target epitopes that deviate vaccination approaches from the major aim of inducing neutralizing antibodies, which mainly target the native prefusion trimer conformation. Here, we review the viral glycoprotein stabilization methods developed prior to SARS-CoV-2, and applied to SARS-CoV-2 S, in order to stabilize S in the prefusion conformation. The importance of structure-based approaches is highlighted by the benefits of employing stabilized S trimers versus non-stabilized S in vaccines with respect to their protective efficacy.

SARS-CoV-2: Searching for the Missing Variants

Structural and phylogenetic analysis of the spike glycoprotein highlighted that the last variants, annotated as omicron, have about 30 mutations compared to the initial version reported in China, while the delta variant, supposed to be the omicron ancestor, shows only 7 mutations. Moreover, the five omicron variants were isolated between November 2021 and January 2022, and the last variant BA.2.75, unofficially named centaurus, was isolated in May 2022. It appears that, since the isolation of the delta variant (October 2020) to the omicron BA.1 (November 2021), there was an interval of one year, whereas the five omicron variants were isolated in three months, and after a successive four months period, the BA.2.75 variant was isolated. So, what is the temporal and phylogenetic correlation among all these variants? The analysis of common mutations among delta and the omicron variants revealed: (i) a phylogenetic correlation among these variants; (ii) the existence of BA.1 and BA.2 omicron variants a few months before being isolated; (iii) at least three possible intermediate variants during the evolution of omicron; (iv) the evolution of the BA.2.12.1, BA.4 and BA.5 variants from omicron BA.2; (v) the centaurus variant evolution from omicron BA.2.12.1.