bioRxivMicrobiologyPreprint
Global distribution of honeybee gut microbiome and pesticide-driven adaptations in opportunistic microbial species
Nelli VardazaryaniD, Lusine AduntsiD, Inga L. BazukyaniD, Magdalina K. ZakharyaniD, Honglian LiuiD, Chrats MelkonianiD, Lilit NersisyaniD
Abstract
Honeybees (Apis mellifera) rely on a specialized gut microbiome shaped by climate, flora, agrochemicals, and dietary supplements. Yet, how these factors alter microbiome composition and function remains unclear. We integrated 16S rRNA and shotgun metagenomics data from eight published studies across six regions, alongside newly generated 16S data from Armenia, to assess how environmental and agrochemical factors influence the honeybee gut microbiome. We also introduced a novel co-abundance and functional analysis pipeline to identify treatment-affected bacterial networks and associated pathways. We observed a stable core of six to twelve phylotypes in amplicon and metagenomic datasets respectively. However, we note significant geographic variation in relative abundances, likely reflecting differences in diet, climate, and local flora. Armenian data revealed distinct seasonal shifts, particularly elevated Commensalibacter in autumn and minor urban-rural differences. Pesticide treatments elicited varying responses: oxalic acid drove pronounced beta-diversity shifts; neonicotinoids had subtler effects, both primarily impacting opportunistic pathogens; and glyphosate disrupted core taxa with stronger effects in newly emerged bees under prolonged exposure. Co-abundance network analysis highlighted that the pesticide-associated community was enriched in adaptive pathways, including potential glyphosate degradation by Pseudomonas, biofilm formation, and aromatic amino acid synthesis. These findings reaffirm the stability of the honeybee core microbiome yet underscore that environmental and anthropogenic stressors induce distinct compositional and functional shifts. We emphasize the need for longitudinal metagenomic approaches that enable high-resolution functional profiling and co-abundance network analysis to clarify how these microbiome shifts impact bee health and colony sustainability.
- organism: human
- assay: metagenomics
- research focus: clustering
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- approach: machine learning (classical)
- Citations
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