Evidence map›Paper›PMID 40913400›Full record

ArticleProteomics2026

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

Huan Zhong, Yuming Shi, Aleksandra Kozlova, Renata Moravcova, Jason C Rogalski, Aidan Jamieson, Lance Lansing, Kyung-Mee Moon, Xiaojing Yuan, Amanda S Gregoris and 16 more

Abstract read
In one paragraph

Article in Proteomics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

26 authors.

Huan ZhongDepartment of Biochemistry and Molecular Biology, Michael Smith Laboratories, Life Sciences Institute, University of British Columbia, Vancouver, British Columbia, Canada.
Yuming ShiDepartment of Biochemistry and Molecular Biology, Michael Smith Laboratories, Life Sciences Institute, University of British Columbia, Vancouver, British Columbia, Canada.
Aleksandra KozlovaNational Research University Higher School of Economics, Moscow, Russian Federation.
Renata MoravcovaProteomics and Metabolomics Core Facility, Life Sciences Institute, University of British Columbia, Vancouver, British Columbia, Canada.
Jason C RogalskiProteomics and Metabolomics Core Facility, Life Sciences Institute, University of British Columbia, Vancouver, British Columbia, Canada.
Aidan JamiesonDepartment of Biology, York University, Toronto, Ontario, Canada.
Lance LansingAgriculture and Agri-Food Canada, Lethbridge Research and Development Centre, Lethbridge, Alberta, Canada.
Kyung-Mee MoonDepartment of Biochemistry and Molecular Biology, Michael Smith Laboratories, Life Sciences Institute, University of British Columbia, Vancouver, British Columbia, Canada.
Xiaojing YuanProteomics and Metabolomics Core Facility, Life Sciences Institute, University of British Columbia, Vancouver, British Columbia, Canada.
Amanda S GregorisAgriculture and Agri-Food Canada, Beaverlodge Research Farm, Beaverlodge, Alberta, Canada.
Heather HigoDepartment of Biochemistry and Molecular Biology, Michael Smith Laboratories, Life Sciences Institute, University of British Columbia, Vancouver, British Columbia, Canada.
Julia CommonDepartment of Biochemistry and Molecular Biology, Michael Smith Laboratories, Life Sciences Institute, University of British Columbia, Vancouver, British Columbia, Canada.
Ida M ConflittiDepartment of Biology, York University, Toronto, Ontario, Canada.
Mateus PepinelliSchool of Natural Sciences, Laurentian University, Sudbury, Ontario, Canada.
Lan TranAgriculture and Agri-Food Canada, Beaverlodge Research Farm, Beaverlodge, Alberta, Canada.
Morgan CunninghamAgriculture and Agri-Food Canada, Beaverlodge Research Farm, Beaverlodge, Alberta, Canada.
Hosna JabbariDepartment of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada.
Syed Abbas BukhariDepartment of Biology, York University, Toronto, Ontario, Canada.
Sarah K FrenchDepartment of Biology, York University, Toronto, Ontario, Canada.
Rodrigo Ortega PoloAgriculture and Agri-Food Canada, Lethbridge Research and Development Centre, Lethbridge, Alberta, Canada.
Shelley E HooverDepartment of Biological Sciences, University of Lethbridge, Lethbridge, Alberta, Canada.
Stephen F PernalAgriculture and Agri-Food Canada, Beaverlodge Research Farm, Beaverlodge, Alberta, Canada.
Pierre GiovenazzoDépartement de Biologie, Université Laval, Ville de Québec, Québec, Canada.
M Marta GuarnaAgriculture and Agri-Food Canada, Beaverlodge Research Farm, Beaverlodge, Alberta, Canada.
Amro ZayedDepartment of Biology, York University, Toronto, Ontario, Canada.
Leonard J FosterDepartment of Biochemistry and Molecular Biology, Michael Smith Laboratories, Life Sciences Institute, University of British Columbia, Vancouver, British Columbia, Canada.ORCID https://orcid.org/0000-0001-8551-4817

Funding

Genome Canada LSARP #16420Government of Canada through Agriculture and Agri-Food Canada (AAFC) Genomics Research and Development Initiative (GRDI) AAFC J-002368Life Sciences Institute, and Genome BC 374PROOntario Genomics Institute OGI-185
6 · The paper itself

Abstract

Honey bees (Apis mellifera) are vital pollinators in fruit-producing agroecosystems like highbush blueberry (HBB) and cranberry (CRA). However, their health is threatened by multiple interacting stressors, including pesticides, pathogens, and nutritional changes. We tested 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 multi-omics analysis using RNA-sequencing (RNA-seq), proteomics, and gut microbiome profiling across three key tissue types (head, abdomen, and gut) of honey bees collected from two agroecosystems over two field seasons. Quantification was performed for pesticide residues, pathogen loads (Nosema spp., Varroa destructor, and multiple viruses), and gut microbiota. Weighted gene co-expression network analysis (WGCNA) revealed tissue-specific protein modules with ecosystem-associated patterns, which differed from RNA co-expression networks. Microbiome composition also varied, with key genera like Gilliamella, Snodgrassella, and Bartonella correlating with metabolic modules. These findings underscore the complex, environment-dependent impacts of agroecosystem conditions on bee health. Our study provides a system-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. SUMMARY: This study provides a comprehensive multi-omics analysis of honey bees foraging in blueberry and cranberry agroecosystems, offering novel insights into the molecular mechanisms underlying pollinator health in managed crop environments. By integrating transcriptomic, proteomic, and microbiome profiling across key tissues-head, abdomen, and gut-we reveal how environmental stressors, including pesticide exposure, pathogen infections, and parasitic infestations (e.g., Varroa destructor), differentially impact bee physiology and microbiome composition. Our findings highlight tissue-specific responses to these stressors, with distinct metabolic pathway alterations observed in each tissue. Proteomic and transcriptomic analyses uncovered dysregulated pathways linked to oxidative phosphorylation and protein synthesis, while microbiome analysis revealed crop-dependent shifts in gut bacterial communities, suggesting potential roles in pesticide detoxification and immune modulation. Notably, we identified key molecular biomarkers associated with stress adaptation, which may serve as early indicators of colony health deterioration. This research underscores the need for a system-level approach to understanding pollinator stress in agricultural landscapes. By elucidating the interactions between diet, pesticide residues, pathogen loads, and molecular stress responses, our study provides a foundation for targeted conservation strategies aimed at mitigating environmental risks and improving pollination sustainability in agroecosystems.

Indexed as

Blueberry PlantsVaccinium macrocarponAgroecologyAnimalsBeesCrops, AgriculturalGastrointestinal MicrobiomeMultiomicsProteomicsApis melliferamicrobiomemulti‐omicsproteomicstranscriptomics

Identifiers

PMID40913400
PMCPMC13419346

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.