Location: Bee Research Laboratory
Project Number: 8042-21000-291-003-I
Project Type: Interagency Reimbursable Agreement
Start Date: Apr 1, 2018
End Date: Mar 31, 2022
Honey bees are subject to great pressure from pests and pathogens, affecting pollination and the production of hive products. To address the urgent need to develop more effective ways to control bee disease, a newly developed reverse genetic system for the key virus, Deformed wing virus (DWV), will be combined with high throughput genomic sequencing data and honey bee transcriptome information. These tools will be used to exploit natural defenses against viral infection and to determine the relative virulence of different virus strains. The key objectives will be to 1) exploit antiviral RNA interference (RNAi), a mechanism which plays a major role in insect defenses against RNA viruses and 2) develop alternative ways for DWV control based on cross-protection or infection exclusion phenomena, in which infection with mild or attenuated virus variant provides protection against infection with a more severe variant of the same virus.
The approaches for this project will be to 1) combine RNA sequence data with pathology data and experimental infectious clones to Identify the key virulent strains of DWV circulating in US honey bees. The analysis will involve NGS RNA-Sequence honey bee datasets to identify virulent and mild DWV and/or VDV1 strains, 2) develop and optimize the efficient induction of anti-DWV RNAi by externally introduced dsRNA formulations, designed using novel insights into the interactions between honey bees, DWV, and varroa and 3) generate attenuated protective DWV variants to determine their ability to provide cross-protection against virulent DWV strains. Specifically, full-length clones of DWV will be modified to knock out DWV assess infection in honey bees. An additional set of clones will be modified to alter virulence proteins in the DWV genome, thereby generating attenuated clones. After inoculation of bees in controlled laboratory conditions, the expression of honey bee RNAi pathway components will be quantified in order to identify potential regulators, and the replication and inhibition of viral strains will be assessed. Based on these experimental results each viral strain will be assessed alone and in viral combinations to determine how viruses evade bee responses (measured by the viral load in experimental samples) and how viral strains interact.