Effective Approaches to Study the Genetic Variability of SARS-CoV-2.

Significant efforts are being made in many countries around the world to respond to the COVID-19 pandemic by developing diagnostic reagent kits, identifying infected people, determining treatment methods, and finally producing effective vaccines. However, novel coronavirus variants may potentially reduce the effectiveness of all these efforts, demonstrating increased transmissibility and abated response to therapy or vaccines, as well as the possibility of false negative results in diagnostic procedures based on nucleic acid amplification methods. Since the end of 2020, several variants of concern have been discovered around the world. When information about a new, potentially more dangerous strain of pathogen appears, it is crucial to determine the moment of its emergence in a region. Eventually, that permits taking timely measures and minimizing new risks associated with the spreading of the virus. Therefore, numerous nations have made tremendous efforts to identify and trace these virus variants, which necessitates serious technological processes to sequence a large number of viral genomes. Here, we report on our experience as one of the primary laboratories involved in monitoring SARS-CoV-2 variants in Russia. We discuss the various approaches used, describe effective protocols, and outline a potential technique combining several methods to increase the ability to trace genetic variants while minimizing financial and labor costs.

Utilizing the VirIdAl Pipeline to Search for Viruses in the Metagenomic Data of Bat Samples.

According to various estimates, only a small percentage of existing viruses have been discovered, naturally much less being represented in the genomic databases. High-throughput sequencing technologies develop rapidly, empowering large-scale screening of various biological samples for the presence of pathogen-associated nucleotide sequences, but many organisms are yet to be attributed specific loci for identification. This problem particularly impedes viral screening, due to vast heterogeneity in viral genomes. In this paper, we present a new bioinformatic pipeline, VirIdAl, for detecting and identifying viral pathogens in sequencing data. We also demonstrate the utility of the new software by applying it to viral screening of the feces of bats collected in the Moscow region, which revealed a significant variety of viruses associated with bats, insects, plants, and protozoa. The presence of alpha and beta coronavirus reads, including the MERS-like bat virus, deserves a special mention, as it once again indicates that bats are indeed reservoirs for many viral pathogens. In addition, it was shown that alignment-based methods were unable to identify the taxon for a large proportion of reads, and we additionally applied other approaches, showing that they can further reveal the presence of viral agents in sequencing data. However, the incompleteness of viral databases remains a significant problem in the studies of viral diversity, and therefore necessitates the use of combined approaches, including those based on machine learning methods.