ArticleMicroorganisms2023
Unlocking the Viral Universe: Metagenomic Analysis of Bat Samples Using Next-Generation Sequencing.
Article in Microorganisms, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Editorial for the Special Issue "Advances in Viral Metagenomics".Microorganisms · 2026Article
- The effect of taxonomic, host-dependent features and sample bias on virus host prediction using machine learning and short sequence k-mers.Scientific reports · 2025Article
- Genetic diversity and cross-species transmissibility of bat-associated picornaviruses from Spain.Virology journal · 2024Article
- Enhancing Clinical Utility: Utilization of International Standards and Guidelines for Metagenomic Sequencing in Infectious Disease Diagnosis.International journal of molecular sciences · 2024Review
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Next-generation sequencing technologies have revolutionized the field of virology by enabling the reading of complete viral genomes, extensive metagenomic studies, and the identification of novel viral pathogens. Although metagenomic sequencing has the advantage of not requiring specific probes or primers, it faces significant challenges in analyzing data and identifying novel viruses. Traditional bioinformatics tools for sequence identification mainly depend on homology-based strategies, which may not allow the detection of a virus significantly different from known variants due to the extensive genetic diversity and rapid evolution of viruses. In this work, we performed metagenomic analysis of bat feces from different Russian cities and identified a wide range of viral pathogens. We then selected sequences with minimal homology to a known picornavirus and used "Switching Mechanism at the 5' end of RNA Template" technology to obtain a longer genome fragment, allowing for more reliable identification. This study emphasizes the importance of integrating advanced computational methods with experimental strategies for identifying unknown viruses to better understand the viral universe.
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Registered trials
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