SARS-CoV-2 variants and spike mutations involved in second wave of COVID-19 pandemic in India

Molecular characterization, phylogenetic and variation analyses of SARS-CoV-2 strains in India

In the wake of the havoc caused by the COVID-19 pandemic, it is imperative to use the available genomic sequence data to gain insight into the mutational and genomic diversity of SARS-CoV-2. Here we have performed comparative phylogenetic, mutational and genetic diversity analysis on 1962 SARS-CoV-2 genome sequences from seven worst hit Indian states during the third Covid-19 wave, to determine the SARS-CoV-2 strains and mutations in circulation during the third wave and the transmission pattern and disease epidemiology across the states and gain valuable insight into the viral evolution. 6083 Single nucleotide polymorphisms (SNPs) were discovered in the analysis with 93 SNPs common to all states. The genetic relatedness among the statewise multilocus genotypes was visualized by plotting a minimum spanning tree based on Bruvo's distance framework. The phylogenetic tree based on Nei's genetic distance showed distinct clades. The AMOVA results indicated that large proportion of the total genetic variation is distributed within the samples, rather than between the samples within each population and between the populations. Our findings provide insight into the SARS-CoV-2 variants and mutations which dominated the third COVID-19 wave in India and thus provide a basis to monitor and further assess these variants and their sub lineages and mutations for their clinical impact and reaction to existing and newly designed drugs and vaccines. The genetic diversity analysis helps in comprehending the viral transmission scenarios across the Indian states so as to enable the State government and researchers in developing state specific prevention measures for future.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13337-024-00878-7.

Machine learning-based approach KEVOLVE efficiently identifies SARS-CoV-2 variant-specific genomic signatures

Machine learning was shown to be effective at identifying distinctive genomic signatures among viral sequences. These signatures are defined as pervasive motifs in the viral genome that allow discrimination between species or variants. In the context of SARS-CoV-2, the identification of these signatures can assist in taxonomic and phylogenetic studies, improve in the recognition and definition of emerging variants, and aid in the characterization of functional properties of polymorphic gene products. In this paper, we assess KEVOLVE, an approach based on a genetic algorithm with a machine-learning kernel, to identify multiple genomic signatures based on minimal sets of k-mers. In a comparative study, in which we analyzed large SARS-CoV-2 genome dataset, KEVOLVE was more effective at identifying variant-discriminative signatures than several gold-standard statistical tools. Subsequently, these signatures were characterized using a new extension of KEVOLVE (KANALYZER) to highlight variations of the discriminative signatures among different classes of variants, their genomic location, and the mutations involved. The majority of identified signatures were associated with known mutations among the different variants, in terms of functional and pathological impact based on available literature. Here we showed that KEVOLVE is a robust machine learning approach to identify discriminative signatures among SARS-CoV-2 variants, which are frequently also biologically relevant, while bypassing multiple sequence alignments. The source code of the method and additional resources are available at: https://github.com/bioinfoUQAM/KEVOLVE.

Characterization of SARS-CoV-2 Variants in Military and Civilian Personnel of an Air Force Airport during Three Pandemic Waves in Italy

We investigated SARS-CoV-2 variants circulating, from November 2020 to March 2022, among military and civilian personnel at an Air Force airport in Italy in order to classify viral isolates in a potential hotspot for virus spread. Positive samples were subjected to Next-Generation Sequencing (NGS) of the whole viral genome and Sanger sequencing of the spike coding region. Phylogenetic analysis classified viral isolates and traced their evolutionary relationships. Clusters were identified using 70% cut-off. Sequencing methods yielded comparable results in terms of variant classification. In 2020 and 2021, we identified several variants, including B.1.258 (4/67), B.1.177 (9/67), Alpha (B.1.1.7, 9/67), Gamma (P.1.1, 4/67), and Delta (4/67). In 2022, only Omicron and its sub-lineage variants were observed (37/67). SARS-CoV-2 isolates were screened to detect naturally occurring resistance in genomic regions, the target of new therapies, comparing them to the Wuhan Hu-1 reference strain. Interestingly, 2/30 non-Omicron isolates carried the G15S 3CLpro substitution responsible for reduced susceptibility to protease inhibitors. On the other hand, Omicron isolates carried unusual substitutions A1803V, D1809N, and A949T on PLpro, and the D216N on 3CLpro. Finally, the P323L substitution on RdRp coding regions was not associated with the mutational pattern related to polymerase inhibitor resistance. This study highlights the importance of continuous genomic surveillance to monitor SARS-CoV-2 evolution in the general population, as well as in restricted communities.

Alpha to Omicron (Variants of Concern): Mutation Journey, Vaccines, and Therapy

Coronavirus disease 2019 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) initially emerged in December 2019 and has subsequently expanded globally, leading to the ongoing pandemic. The extensive spread of various SARS-CoV-2 variants possesses a serious public health threat. An extensive literature search along with deep analysis was performed to describe and evaluate the characteristics of SARS-CoV-2 variants of concern in relation to the effectiveness of the current vaccines and therapeutics. The obtained results showed that several significant mutations have evolved during the COVID-19 pandemic. The developed variants and their various structural mutations can compromise the effectiveness of several vaccines, escape the neutralizing antibodies, and limit the efficiency of available therapeutics. Furthermore, deep analysis of the available data enables the prediction of the future impact of virus mutations on the ongoing pandemic along with the selection of appropriate vaccines and therapeutics.

Nanotechnology-Based RNA Vaccines: Fundamentals, Advantages and Challenges

Over the past decades, many drugs based on the use of nanotechnology and nucleic acids have been developed. However, until recently, most of them remained at the stage of pre-clinical development and testing and did not find their way to the clinic. In our opinion, the main reason for this situation lies in the enormous complexity of the development and industrial production of such formulations leading to their high cost. The development of nanotechnology-based drugs requires the participation of scientists from many and completely different specialties including Pharmaceutical Sciences, Medicine, Engineering, Drug Delivery, Chemistry, Molecular Biology, Physiology and so on. Nevertheless, emergence of coronavirus and new vaccines based on nanotechnology has shown the high efficiency of this approach. Effective development of vaccines based on the use of nucleic acids and nanomedicine requires an understanding of a wide range of principles including mechanisms of immune responses, nucleic acid functions, nanotechnology and vaccinations. In this regard, the purpose of the current review is to recall the basic principles of the work of the immune system, vaccination, nanotechnology and drug delivery in terms of the development and production of vaccines based on both nanotechnology and the use of nucleic acids.

Neutralizing Antibody Responses Elicited by Inactivated Whole Virus and Genetic Vaccines against Dominant SARS-CoV-2 Variants during the Four Epidemic Peaks of COVID-19 in Colombia

Several SARS-CoV-2 variants of concern (VOC) and interest (VOI) co-circulate in Colombia, and determining the neutralizing antibody (nAb) responses is useful to improve the efficacy of COVID-19 vaccination programs. Thus, nAb responses against SARS-CoV-2 isolates from the lineages B.1.111, P.1 (Gamma), B.1.621 (Mu), AY.25.1 (Delta), and BA.1 (Omicron), were evaluated in serum samples from immunologically naïve individuals between 9 and 13 weeks after receiving complete regimens of CoronaVac, BNT162b2, ChAdOx1, or Ad26.COV2.S, using microneutralization assays. An overall reduction of the nAb responses against Mu, Delta, and Omicron, relative to B.1.111 and Gamma was observed in sera from vaccinated individuals with BNT162b2, ChAdOx1, and Ad26.COV2.S. The seropositivity rate elicited by all the vaccines against B.1.111 and Gamma was 100%, while for Mu, Delta, and Omicron ranged between 32 to 87%, 65 to 96%, and 41 to 96%, respectively, depending on the vaccine tested. The significant reductions in the nAb responses against the last three dominant SARS-CoV-2 lineages in Colombia indicate that booster doses should be administered following complete vaccination schemes to increase the nAb titers against emerging SARS-CoV-2 lineages.