Metagenomic Sequencing of Diamondback Moth Gut Microbiome Unveils Key Holobiont Adaptations for Herbivory
Bibliographic record
Abstract
Herbivore specialists adapt to feed on a specific group of host plants by evolving various mechanisms to respond to plant defences. Insects also possess complex gut microbiotas but their potential role in adaptation is poorly understood. Our previous study of the genome of diamondback moth, Plutella xylostella, revealed an intrinsic capacity to detoxify plant defence compounds, which is an important factor in its success as a pest. Here we expand on that work with a complete taxonomic and functional profile of the P. xylostella gut microbiota obtained by metagenomic sequencing. Gene enrichment in the metagenome, accompanied by functional identification, revealed an important role of specific gut bacteria in the breakdown of plant cell walls, detoxification of plant phenolics, and synthesis of amino acids. Microbes participating in these pathways mainly belonged to three highly abundant bacteria: Enterobacter cloacae, Enterobacter asburiae, and Carnobacterium maltaromaticum. Results show that while the gut microbial community may be complex, a small number of functionally active species can be disproportionally important. The presence of specific enzymes in the microbiota community, such as supporting amino acid synthesis, digestion and detoxification functions, demonstrates the beneficial interactions between P. xylostella and its gut microbiota. These interactions can be potential targets for manipulation to provide novel pest management approaches.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".