bioRxiv Science⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2025.03.26.645508

A non-destructive approach to assess the gut microbiome of honey bee (Apis mellifera) queens using fecal samples

Motta, E. V. S.·Seong, J.·Bozkus, M.·Shepherd, T. F.·Rangel, J.
View original source ↗Export metadata ↓

Abstract

Fecal sampling is a widely used, non-invasive method for assessing gut microbiomes across various organisms. However, its suitability for studying the gut microbiome of honey bee (Apis mellifera) queens has not been tested. In this study, we evaluated whether fecal microbiomes accurately reflect gut microbiomes in honey bee queens, offering a potential non-destructive approach for microbiome research. We successfully obtained fecal and gut samples from 21 out of 26 queens. Bacterial communities were analyzed using 16S rRNA amplicon sequencing and qPCR. Our results indicate that queen fecal microbiomes closely resemble gut microbiomes, with no significant differences in alpha diversity and only minor differences in specific bacterial taxa. Beta diversity analyses revealed that within-pair microbiomes (i.e., gut vs. feces from the same queen) were significantly more similar than between-pair comparisons. Additionally, qPCR analyses revealed a strong positive correlation between bacterial abundances in fecal and gut samples, further supporting the use of feces as a proxy for gut microbiome composition. While promising, fecal collection from queens can sometimes be challenging. In our study, we were unable to collect feces from five queens, and these individuals lacked stored fecal material upon inspection of dissected guts. Nonetheless, our findings suggest that fecal sampling can be a useful, non-invasive method for studying honey bee queen microbiomes, enabling longitudinal assessments without compromising colony stability. ImportanceThe gut microbiome plays important roles in honey bee health, including protection against pathogens and stimulation of host physiological pathways. Because gut microbiome analysis involves destructive dissections, most research has focused on workers, given that colonies can have tens of thousands of individuals. This has left a significant gap in microbiome studies of other colony members, such as queens. Given that a queen is the sole reproductive female, her gut microbiome cannot be sampled without compromising colony integrity. In this study, we demonstrate that fecal sampling from honey bee queens provides a reliable, non-destructive alternative for assessing the composition of their gut microbiomes. We found that queen fecal microbiomes closely resemble their gut microbiomes in both taxonomic diversity and composition. This approach enables longitudinal monitoring of queen microbiomes without disrupting colony integrity, offering a valuable tool for honey bee research.

Source connections

Explore related subjects

microbiologyPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Motta, E. V. S., Seong, J., Bozkus, M., Shepherd, T. F., Rangel, J.. 2025-03-26. A non-destructive approach to assess the gut microbiome of honey bee (Apis mellifera) queens using fecal samples. https://doi.org/10.1101/2025.03.26.645508

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Rapid and largely reversible shifts in the canine fecal metabolome during dietary change

Diet can rapidly change the fecal metabolome, but less is known about recovery after the original diet is restored. We used untargeted UPLC-MS metabolomics to analyze 72 fecal samples from nine Pumi dogs during an owner-managed switch from dry food to raw food and back to dry food. Diet phase accounted for a large proportion of variation in both ionization modes. More than 13,000 LC-MS features changed at the first sampling point after the switch to raw food, with a similarly large response after return to dry food. Among features significant in both comparisons, more than 99% changed in opposite directions. At the final sampling point, no positive-mode (ESI+) features and only 13 negative-mode (ESI-) features differed from the second dry-food baseline under the same threshold. BARF-associated patterns persisted in analyses excluding individual dogs and in pedigree-adjusted candidate models, although individual feature effects depended on normalization. Putative metabolites from several biochemical classes differed in their response and recovery. The fecal metabolome therefore changed rapidly and returned largely toward baseline, with differences among dogs.

microbiology↗
bioRxiv2026

Taxonomic and functional concordance between full-length ONT 16S and ONT shotgun metagenomics in the canine gut microbiome

Background: Full-length Oxford Nanopore Technologies (ONT) 16S rRNA sequencing provides a scalable view of microbial community composition and can support phylogeny-based functional prediction, but it is not equivalent to shotgun metagenomics. We asked which biological conclusions are preserved when the same canine fecal specimens are profiled by full-length ONT 16S and ONT whole-genome shotgun (WGS) sequencing, and how their agreement depends on analytical scale, reference representation and classifier. Methods: Ninety-seven fecal specimens from 51 dogs were profiled with both assays from the same DNA extract. Functional profiles predicted from NanoASV/NanoPredict with PICRUSt2 were compared with WGS-supported KEGG Ortholog (KO) profiles generated by Kadath. Taxonomy was benchmarked in a source-genome-matched RefSeq universe and in a host-specific DogMAG universe using minitax and Kraken2. Agreement was evaluated at whole-profile, feature-abundance, detection, between-sample structure and biological-inference scales. Age-associated transfer was assessed with dog-aware continuous mixed models, grouped signed-score analyses and paired/dog-blocked PERMANOVA. Results: Functional whole-profile concordance was high: median within-sample CLR Spearman correlations ranged from 0.781 to 0.860 across developmental strata, while between-sample functional structure remained significant by Mantel (rho=0.543) and Procrustes (r=0.693; both p=0.001). Feature-wise transfer was substantially weaker (median KO-wise CLR Spearman=0.318). Continuous age-associated KO slopes showed substantial cross-assay concordance (Spearman=0.727; signed-score Spearman=0.753; direction agreement=77.9%), although 1,290/5,258 eligible KOs retained significant assay-by-age interactions. Taxonomically, exact genus/species abundance agreement was much lower than agreement in between-sample ecological structure. Host-specific DogMAG improved species-level median Spearman from 0.261 to 0.656 for minitax SpeciesEstimate and from 0.181 to 0.512 for Kraken2. The classifier effect was independent of reference choice: under both RefSeq and DogMAG, minitax yielded stronger 16S-WGS concordance than Kraken2, with all eight prespecified RefSeq paired genus/species endpoints and all 10 DogMAG primary paired endpoints significant after BH correction. The same ordering extended to developmental inference, with DogMAG genus/species age-slope concordance of 0.795/0.799 for SpeciesEstimate versus 0.693/0.702 for Kraken2. Taxonomic Aitchison PERMANOVA detected age-associated structure in every assay/reference/classifier/rank combination, whereas age-by-assay interactions were consistently significant but small (R2 approximately 1.1 to 2.2%). Stricter NanoASV identity thresholds removed substantial 16S abundance without improving species-level agreement. Conclusions: The extent of cross-assay agreement depends on the level of analysis. Full-length ONT 16S preserves broad functional organization, ecological structure and much of the direction of age-associated change, but exact fine-rank composition, individual-feature abundance and effect magnitude remain assay dependent. Host-specific reference representation substantially narrows the taxonomic gap, and classifier choice exerts an additional independent effect: within the same matched reference set, minitax consistently yields stronger 16S-WGS concordance than Kraken2 across abundance, detection, ecological-distance and developmental-inference endpoints. Full-length ONT 16S is therefore well suited to broad ecological screening and hypothesis generation, whereas WGS remains preferable when conclusions depend on quantitative fine-rank composition, directly supported gene content or precise feature-level effect estimates.

microbiology↗
bioRxiv2026

Matrix-controlled emergence of biofilm architecture shapes antimicrobial survival

Biofilms are structured microbial communities whose extracellular matrix is widely regarded as a basis of their protection against antimicrobial compounds. Yet how matrix production by individual bacteria gives rise to collective architecture and antimicrobial protection remains poorly understood. Here, we systematically varied expression of the master biofilm regulator csgD in Salmonella enterica and found that increasing matrix production reorganizes biofilms from dense, isotropic packings into sparse, nematically aligned communities by altering cell-cell interactions. By combining experimentally measured biofilm architectures with reaction-diffusion modeling, we show that these structural changes produce distinct patterns of antimicrobial killing, ranging from preferential killing near the liquid-biofilm interface to more uniform killing throughout the community. Consequently, increasing matrix production unexpectedly reduces antimicrobial survival by shifting the biofilm into different transport regimes, while strain-specific physiological differences further modulate antimicrobial depletion. Rather than acting as a passive barrier, EPS therefore shapes antimicrobial susceptibility by reorganizing biofilm architecture and its transport properties. EPS thus provides a physical link between molecular regulation, collective architecture and antimicrobial survival, providing a quantitative framework for understanding how cellular matrix production generates emergent biofilm function.

microbiology↗