Project Number: 6050-21000-016-021-T
Project Type: Trust Fund Cooperative Agreement
Start Date: Dec 15, 2021
End Date: Dec 31, 2022
Honey bee viral ecology has direct implications to the practical use of a critical agricultural pollinator. Past work has highlighted our limited understanding of the diversity of viral family groups within honey bee colonies across the world (Gallbraith et al., 2018) and within the U.S. (Glenny et al., 2017). Similarly, the study of how viral diversity and changes across season and between beekeeping operations is nascent as is our understanding of how it impacts colony health and survival (Glenny et al., 2017). Characterizing how viral diversity within and between honey bee populations, particularly those bred for specific resistance traits, and its interactions with other colony factors is a key component of effective disease prevention and keeping healthy bees. The effort of understanding how viral diversity affects honey bee health is more relevant and a topic of broad interest today. Our own experiences with the current pandemic resulting from a novel virus and affiliated strains have brought the need to understand such threats to the forefront of public consciousness. For honey bees, the spread of novel viral variants is particularly relevant for Deformed Wing Virus (DWV), as a newer variant (DWV-B) has also quickly spread through the United States in the past 10 years (Ryabob et al., 2017). In addition, the impact of more recently discovered viruses is largely unexplored (Ray et al., 2020; McMenamin & Flenniken, 2018), especially with respect to how honey bee genotype may influence the proliferation of these novel viruses. Honey bee genotype becomes even more relevant when we consider dynamics of honey bee colony infestation with Varroa destructor, the parasitic mite that in addition to its own impact on colony health, seems to enhance viral infection and derived colony losses (Dainat et al., 2011; Traynor et al., 2020). Since Varroa is a relatively new parasite of the Western honey bee (Apis mellifera), Varroa infestation has led to the proliferation of viruses (Ryabov et al., 2014), particularly DWV and may lead to differential strain diversity in mite susceptible versus mite resistant or mite tolerant populations (Locke et al., 2014; Thaduri et al., 2018). Honey bee lines bred for a variety of hygienic and tolerance traits may provide a solution to not only combat Varroa, but also to reduce impacts of viral infection on colony health and productivity (Locke et al., 2014, Emsen et al., 2015, Thaduri et al, 2018). Specifically, lines bred to achieve reduced prevalence of Varroa may inherently mitigate potential negative effects of associated viruses through control of Varroa, which directly vectors some viruses and indirectly increases the effect of infections of other viruses. Varroa resistant honey bee lines therefore provide a unique opportunity where host-virus relationships can be explored and contrasted with the more general, mite susceptible honey bee population.
Our aim is to characterize viral diversity across U.S. beekeeping operations. In 2020, 320 colonies across five geographic locations and commercial beekeeping operations (OR, MI, CA, ND, MN) were sampled as part of a previously funded NDAA project. This effort was part of a monitoring program for one of the breeding lines, Hilo bees (https://www.hilobees.com/), developed in collaboration with the USDA-ARS-HBBGPRL. In the proposed, we focus on the late season sampling period (August) which has been previously identified as a peak period in viral diversity (see Glenny et al., 2017). Ultimately six colonies from each of our Varroa resistant line (Hilo) and a control population will be sampled and grouped by end-of-season survival across the five regions resulting in a total of 120 colony samples (6 colonies x 2 lines x 2 survival states x 5 regions). These 120 colony samples is approximately a third of the total number of colonies in the study and will provide a strong overall evaluation of viral genotypes across operations. Virus profiles will be derived for each of the 120 colonies through uniformly homogenized pools of 10 individual workers to be processed via whole transcriptome sequencing. Each sample will be processed to enhance viral representation by extracting virion-protected/encapsidated nuclease treated Ribonucleic Acid (RNA) and omitting polyA selection and ribosomal Ribonucleic Acid (rRNA) removal steps (see Daughenbaugh et al., 2020). Resulting viral reads will be used for meta-genomic assembly to arrive at viral genomes where possible (Glenny et al., 2017; Valles & Rivers, 2019). Genomes and contigs will be compared to existing reference genomes to establish viral taxonomy (Glenny et al., 2017; Valles & Rivers, 2019). Reads will then be mapped back to final, curated genomes and contigs to get proportional representation. In this way our approach would culminate on per colony virus profiles and their relative abundance. Resulting data can then be directly applied to characterize regional variation and identify differences in virus profiles between Varroa resistant and control colonies. Additional work will examine variation of virus profiles over the course of a four-year span (2017-2020). The approach will focus to one geographic region (ND) where samples have been consistently collected for paired groups of Varroa resistant (Hilo) and control colonies in the same beekeeping operation. Samples will be collected for 6 colonies from Hilo and control lines and grouped by end-of-year survival state for each year sampled for a total of 72 colony samples (6 colonies x 2 lines x 2 states x 3 additional years). Sequencing approach and assemblies will be conducted in parallel with the regional analysis, but the time course will allow assessments of rates of stability for virus profiles of the colonies. Work for both regional and time course objectives will include follow-up validation at the individual level using quantitative real-time polymerase chain reaction (qRT-PCR) methods previously employed at the USDA-ARS-HBBGPRL. This final effort would increase resolution for those viral genomes identified as critical.