Comparative genomics reveals that metabolism underlies evolution of entomopathogenicity in bee-loving Ascosphaera spp. fungi
Bibliographic record
Abstract
Ascosphaera (Eurotiomycetes: Onygenales) is a diverse genus of fungi that is exclusively found in association with bee nests and comprises both saprophytic and entomopathogenic species. To date, most genomic analyses have been focused on the honeybee pathogen A. apis, and we lack a genomic understanding of how pathogenesis evolved more broadly in the genus. To address this gap we sequenced the genomes of the leaf-cutting bee pathogen A. aggregata as well as three commensal species: A. pollenicola, A. atra and A. acerosa. De novo annotation and comparison of the assembled genomes was carried out, including the previously published genome of A. apis. To identify candidate virulence genes in the pathogenic species, we performed secondary metabolite-oriented analyses and clustering of biosynthetic gene clusters (BGCs). Additionally, we captured single copy orthologs to infer their phylogeny and created codon-aware alignments to determine orthologs under selective pressure in our pathogenic species. Our results show several shared BGCs between A. apis, A. aggregata and A. pollenicola, with antifungal resistance related genes present in the bee pathogens and commensals. Genes involved in metabolism and protein processing exhibit signatures of enrichment and positive selection under a fitted branch-site model. Additional known virulence genes in A. pollenicola, A. acerosa and A. atra are identified, supporting previous hypotheses that these commensals may be opportunistic pathogens. Finally, we discuss the importance of such genes in other fungal pathogens, suggesting a common route to evolution of pathogenicity in Ascosphaera.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".