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.

Relevance. It is known that the immune response to the administration of immunobiological drugs is variable and depends on the individual characteristics of the organism. Host immunogenetic factors have a significant impact on the effectiveness of vaccination. In this study, the frequencies of alleles of the HLA class I (HLA-A, B, C) and class II genes (HLA-DRB1, DPB1, DQB1) were studied in groups of participants with different levels of antibodies (anti-HBs) after vaccination against viral hepatitis B. Aims of the work was to determine the possible relationship between alleles of HLA genes and the intensity of post-vaccination immunity against hepatitis B. Materials and methods. The study included 271 apparently healthy adults who were divided into 3 groups depending on the specific concentration of post-vaccination antibodies (anti-HBs) using ELISA. All calculations were made relative to the groups anti-HBs >100 mIU/ml (n=82), 10-100 mIU/ml (n=98) (protective antibody level) and anti-HBs <10 mIU/ml (n = 91). To type alleles of the HLA class I (HLA-A, B, C) and class II (HLA-DRB1, DPB1, DQB1) genes, we used a panel we developed for whole-genome next-generation sequencing (NGS). Statistical analysis was performed using Pearson's χ² goodness-of-fit test using the FDR multiple correction method with an initial target of p < 0.05. Results. When typing the six genes studied, the total number of alleles identified at least once was 189 variants that were distinct from each other. We identified 3 alleles (B*38:01:01, DQB1*06:03:01 and DRB1*13:01:01), which were significantly more common (FDR p < 0.05) in the group with a protective level of anti-HBsS. Also in this group there was an increased frequency of occurrence of alleles A*26:01:01, A*32:01:01, C*12:03:01, DPB1*04:01:01 and haplotypes DQB1*06:03:01 -DRB1*13:01:01 and B*38:01:01-C*12:03:01. In the group of seronegative patients, alleles A*02:01:01, A*03:01:01, B*44:02:01, B*44:27:01, C*07:04:01, DPB1*04 were more common :01:01, DQB1*05:01:01, DRB1*01:01:01 and DRB1*16:01:01. It was shown that the identified associations were more significant in the group of individuals with a concentration of post-vaccination anti-HBs above 100 mIU/ml. Conclusion. The results obtained indicate that the HLA alleles we identified may influence the level of anti-HBsS production, and that the genetic factor may, to a greater extent, determine whether the antibody level exceeds 100 mIU/ml. defined as an anti-HBS level of 10 mIU/ ml. The development of an integrated approach to the organization of vaccine prevention, including the determination of genetic markers, will improve the quality of immunization of the population. Information about the association of HLA gene alleles can be used to develop predictive scenarios for the development of the hepatitis B epidemic process.

Lower respiratory tract infections caused by the respiratory syncytial virus (RSV) pose a major global public health challenge. The use of next-generation sequencing technologies enables detailed monitoring of viral genetic variability, which is crucial for evaluating the efficacy of immunoprophylactic measures. In this study, whole-genome sequencing of RSV was performed on 106 samples collected in the Russian Federation between September 2021 and April 2025. Three NGS platforms were employed: Illumina MiSeq, Oxford Nanopore Technologies MinION, and Qitan Tech QNome-3841. Using discrete phylogeographic methods, we estimated a minimum of 45 introduction events into Russia for RSV-A and 39 for RSV-B among the genomes included in the analysis. Most events were represented by a single Russian genome. These results indicate recurrent introductions of RSV into Russia from abroad. Given the limited genomic sampling available, most of these introductions were not associated with detectable transmission within the country.

Background: The diagnosis of infectious diseases currently relies predominantly on polymerase chain reaction (PCR) assays. However, the range of pathogens that can be detected simultaneously using these methods is limited, and their effective use depends on an a priori etiological hypothesis. Multiplex PCR-based targeted next-generation sequencing (mp-tNGS) is considered a promising complementary approach for expanded viral testing. This study aimed to develop an in-house mp-tNGS method, perform an initial evaluation of its analytical sensitivity, and explore its performance using clinical respiratory specimens. Methods: The method comprised a panel targeting 28 viruses and bioinformatics pipelines for mp-tNGS data processing. Analytical sensitivity was evaluated using positive control samples (PCSs) containing encapsulated RNA or DNA. Performance with clinical specimens was explored using 910 nasopharyngeal and oropharyngeal swab specimens, which were divided into three groups based on the results of prior PCR testing. Results: Of the 28 viral targets, 23 underwent experimental analytical evaluation, whereas five were assessed in silico only. For 19 of the 23 PCSs tested, the estimated limit of detection (LoD) ranged from 6.3 × 10² to 9.4 × 10³ copies/mL. In the group of 216 PCR-positive specimens, PCR and mp-tNGS results were fully concordant in 139 cases; in 28 specimens, mp-tNGS additionally detected other viruses. Among 394 PCR-negative specimens, mp-tNGS detected viruses in 81. In the group of 300 hospital-derived specimens, mp-tNGS detected at least one viral target in 131 specimens, including additional viral detections and coinfections not identified during the initial testing. A substantial proportion of the additional findings involved Epstein–Barr virus (EBV) and cytomegalovirus (CMV), warranting cautious clinical interpretation. Conclusions: The developed mp-tNGS approach demonstrated the potential to simultaneously detect a broad range of known viruses, provide viral typing, and identify coinfections. The method may be used as an adjunctive tool to broaden the laboratory diagnosis of respiratory infections; however, further optimization, validation, and standardization of criteria for result interpretation are required.