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Discovery and characterization of novel DNA viruses in Apis mellifera : expanding the honey bee virome through metagenomic analysis.

Dominika KadlečkováMartina SalakovaTomáš ErbanRuth Tachezy
Published in: mSystems (2024)
To date, many viruses have been discovered to infect honey bees. In this study, we used high-throughput sequencing to expand the known virome of the honey bee, Apis mellifera , by identifying several novel DNA viruses. While the majority of previously identified bee viruses are RNA, our study reveals nine new genomes from the Parvoviridae family, tentatively named Bee densoviruses 1 to 9. In addition, we characterized a large DNA virus, Apis mellifera filamentous-like virus (AmFLV), which shares limited protein identities with the known Apis mellifera filamentous virus. The complete sequence of AmFLV, obtained by a combination of laboratory techniques and bioinformatics, spans 152,678 bp. Linear dsDNA genome encodes for 112 proteins, of which 49 are annotated. Another large virus we discovered is Apis mellifera nudivirus, which belongs to a group of Alphanudivirus . The virus has a length of 129,467 bp and a circular dsDNA genome, and has 106 protein encoding genes. The virus contains most of the core genes of the family Nudiviridae . This research demonstrates the effectiveness of viral binning in identifying viruses in honey bee virology, showcasing its initial application in this field.IMPORTANCEHoney bees contribute significantly to food security by providing pollination services. Understanding the virome of honey bees is crucial for the health and conservation of bee populations and also for the stability of the ecosystems and economies for which they are indispensable. This study unveils previously unknown DNA viruses in the honey bee virome, expanding our knowledge of potential threats to bee health. The use of the viral binning approach we employed in this study offers a promising method to uncovering and understanding the vast viral diversity in these essential pollinators.
Keyphrases
  • healthcare
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  • genome wide
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  • small molecule
  • genetic diversity
  • high throughput
  • social media