Metagenomic analysis of the honey bee queen microbiome reveals low bacterial diversity and Caudoviricetes phages
Bibliographic record
Abstract
Abstract In eusocial insects, the health of the queens – the colony founders and sole reproductive females – is a primary determinant for colony success. Queen failure in the honey bee Apis mellifera , for example, is a major concern of beekeepers that annually suffer with colony losses, necessitating a greater knowledge of queen health. Several studies on the microbiome of honey bees have characterized its diversity and shown its importance for the health of worker bees, the female non-reproductive caste. However, the microbiome of workers differs from that of queens, which in comparison is still poorly studied. Thus, direct investigations of the queen microbiome are required to understand colony-level microbiome assembly, functional roles, and evolution. Here we used metagenomics to comprehensively characterize the honey bee queen microbiome. Comparing samples from different geographic locations and breeder sources, we show that the microbiome of queens is mostly shaped by the environment experienced since early life, and is predicted to play roles in breakdown of the diet, and protection from pathogens and xenobiotics. We also reveal the microbiome of queens comprises only four core bacterial species, Apilactobacillus kunkeei , Lactobacillus apis, Bombella apis and Commensalibacter sp. Interestingly, in addition to bacteria, we show that bacteriophages infect the queen microbiome, for which Lactobacillaceae are predicted to be the main reservoirs. Together, our results provide the basis to understand the honey bee colony microbiome assemblage, can guide improvements in queen rearing processes, and highlight the importance of bacteriophages for queen microbiome health and microbiome homeostasis in eusocial insects. Importance The queen caste plays a central role for colony success in eusocial insects, as queens lay eggs, and regulate colony behavior and development. Queen failure can cause colonies to collapse, which is one of the major concerns of beekeepers. Thus, understanding of the biology behind the queen’s health is a pressing issue. Previous studies have shown the bee microbiome plays an important role in worker bee health, but little is known about the queen microbiome and its function in vivo . Here, we characterized the queen microbiome identifying for the first time present species and their putative functions. We show that the queen microbiome have predicted nutritional and protective roles in queen association, and comprises only four consistently present bacterial species. Additionally, we bring to attention the spread of phages in the queen microbiome, which increased in abundance in failing queens and may impact the fate of the colony.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".