Genomic surveillance of SARS-CoV-2 in Russia: insights from the VGARus platform

Abstract

Introduction. In response to the COVID-19 pandemic in the Russian Federation, comprehensive response measures were taken. One of these measures was the development of a viral genome aggregation platform (VGARus) to monitor virus variability. The aim of this paper is to describe the role of the VGARus platform in tracking genetic variation in SARS-CoV-2. Materials and methods. VGARus utilizes sequencing data and bioinformatics tools to monitor genetic variations in SARS-CoV-2. The viral genomes were aligned using NextClade, which also translated them into amino acids and identified mutations. The viral variability over time was analyzed by counting the number of amino acid changes compared to the reference sequence. Results. The analysis of data within VGARus enabled the identification of new virus variants, contributing to improved diagnostic tests and vaccine development. The platform allowed for the prediction of epidemiologic trends, facilitating a rapid response to changes in the epidemiologic situation. For example, using VGARus, an increase in COVID-19 incidence was accurately predicted in the summer of 2022 and early 2023, which were associated with the emergence of Omicron subvariants BA.5 and XBB. Data from the platform helps validate the effectiveness of primers and DNA probes to ensure high diagnostic accuracy and reduce the risk of false negatives. Conclusion. VGARus demonstrates the growing role of genomic surveillance in combating COVID-19 and improving preparedness for future infectious disease outbreaks. The platform is a powerful tool for generating evidence-based solutions to combat a pandemic and mitigate its health, economic and societal impacts. It provides the ability to promptly obtain information on the epidemiologic situation in a particular region of the Russian Federation, use genomic data for phylogenetic analysis, compare the mutational spectrum of SARS-CoV-2 sequences with foreign samples. VGARus data allow for both retrospective analysis and predictive hypotheses. For example, we can clearly see the dynamics of the change of different virus variants: sequences belonging to the Alpha, Beta, Delta, Omicron lineages and many less common ones, clearly form the upsurges of morbidity, the interaction of which is reflected in the epidemiological picture. It is also currently being expanded to monitor other pathogens, increasing its public health relevance.