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Omics Insights into the Effects of Highbush Blueberry and Cranberry Crop Agroecosystems on Honey Bee Health and Physiology

ABSTRACT: Honey bees (Apis mellifera) are essential pollinators in agricultural systems, particularly in fruit-producing agroecosystems such as highbush blueberry and cranberry. However, their health is increasingly compromised by multiple interacting stressors, including pesticide exposure, pathogen infections, and changing nutritional landscapes. To test the hypothesis that distinct agricultural ecosystems, with different combinations of agrochemical exposure, pathogen loads, and floral resources, elicit ecosystem specific, tissue level molecular responses in honey bees, we conducted an integrated multiomics analysis. We combined RNA sequencing, quantitative proteomics, and gut microbiome profiling across three key tissues: head, abdomen, and gut collected from bees in blueberry and cranberry agroecosystems over two field seasons. In parallel, we quantified pesticide residues and pathogen and parasite loads (e.g., Nosema spp., Varroa destructor, and several viruses). Notably, our weighted gene co-expression network analysis (WGCNA) revealed tissue specific coregulated protein modules with ecosystem associated patterns. Bees from blueberry agroecosystems exhibited elevated expression of modules in oxidative phosphorylation, and translation, while those from cranberry agroecosystems showed increased activity in immune pathways and endoplasmic reticulum associated protein processing, indicating potential as robust markers for ecosystem induced physiological adaptation. To further explore the molecular mechanisms underlying different ecosystems, we also conducted the integrative analysis of proteomics, transcriptomics and gut microbiome metagenomics. Gut microbiota composition also differed significantly, with key genera (e.g., Gilliamella, Snodgrassella, Bartonella) correlating with host metabolic and immune modules. These findings underscore the complex, environment-dependent impacts of agroecosystem conditions on bee health. Our study provides a systems level understanding of how combined pesticide, pathogen, and parasitic stressors, mediated by diet and microbiome, shape molecular phenotypes in honey bees, informing strategies for pollinator protection in managed landscapes.

INSTRUMENT(S): timsTOF Pro

ORGANISM(S): Apis Mellifera (ncbitaxon:7460)

SUBMITTER: Leonard J. Foster

PROVIDER: MSV000097590 | MassIVE | Thu Apr 10 11:38:00 BST 2025

SECONDARY ACCESSION(S): PXD062819

REPOSITORIES: MassIVE

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Project description:Purpose: Parts of Europe and the United States have witnessed dramatic losses in commercially managed honey bees over the past decade to what is considered an unsustainable extent. The large-scale loss of honey bees has considerable implications for the agricultural economy because honey bees are one of the leading pollinators of numerous crops. Honey bee declines have been associated with several interactive factors. Poor nutrition and viral infection are two environmental stressors that pose heightened dangers to honey bee health. Methods: We used RNA-sequencing to examine how monofloral diets (Rockrose and Chestnut) and Israeli acute paralysis virus inoculation influence gene expression patterns in honey bees. Results: We found a considerable nutritional response, with almost 2,000 transcripts changing with diet quality. The majority of these genes were over-represented for nutrient signaling (insulin resistance) and immune response (Notch signaling and JaK-STAT pathways). Somewhat unexpectedly, the transcriptomic response to viral infection was fairly limited. We only found 43 transcripts to be differentially expressed, some with known immune functions (argonaute-2), transcriptional regulation, and muscle contraction. We created contrasts to determine if any protective mechanisms of good diet were due to direct effects on immune function (resistance) or indirect effects on energy availability (tolerance). A similar number of resistance and tolerance candidate differentially expressed genes were found, suggesting both processes may play significant roles in dietary buffering from pathogen infection. We also compared the virus main effect in our study (polyandrous colonies) to that obtained in a previous study (single-drone colonies) and verified significant overlap in differential expression despite visualization methods showing differences in the noisiness levels between these two datasets. Conclusions: Through transcriptional contrasts and functional enrichment analysis, we add to evidence of feedbacks between diet and disease in honey bees. We also show that comparing results derived from polyandrous colonies (which are typically more natural) and single-drone colonies (which usually yield more signal) may allow researchers to identify transcriptomic patterns in honey bees that are concurrently less artificial and less noisy. Altogether, we hope this work underlines possible merits of using data visualization techniques and multiple datasets when interpreting RNA-sequencing studies.

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Omics Insights into the Effects of Highbush Blueberry and Cranberry Crop Agroecosystems on Honey Bee Health and Physiology

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