A link between host plant adaptation and pesticide resistance in the polyphagous spider mite <i>Tetranychus urticae</i>
Bibliographic record
Abstract
Plants produce a wide range of allelochemicals to defend against herbivore attack, and generalist herbivores have evolved mechanisms to avoid, sequester, or detoxify a broad spectrum of natural defense compounds. Successful arthropod pests have also developed resistance to diverse classes of pesticides and this adaptation is of critical importance to agriculture. To test whether mechanisms to overcome plant defenses predispose the development of pesticide resistance, we examined adaptation of the generalist two-spotted spider mite, Tetranychus urticae, to host plant transfer and pesticides. T. urticae is an extreme polyphagous pest with more than 1,100 documented hosts and has an extraordinary ability to develop pesticide resistance. When mites from a pesticide-susceptible strain propagated on bean were adapted to a challenging host (tomato), transcriptional responses increased over time with ~7.5% of genes differentially expressed after five generations. Whereas many genes with altered expression belonged to known detoxification families (like P450 monooxygenases), new gene families not previously associated with detoxification in other herbivores showed a striking response, including ring-splitting dioxygenase genes acquired by horizontal gene transfer. Strikingly, transcriptional profiles of tomato-adapted mites resembled those of multipesticide-resistant strains, and adaptation to tomato decreased the susceptibility to unrelated pesticide classes. Our findings suggest key roles for both an expanded environmental response gene repertoire and transcriptional regulation in the life history of generalist herbivores. They also support a model whereby selection for the ability to mount a broad response to the diverse defense chemistry of plants predisposes the evolution of pesticide resistance in generalists.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".