Characterization of Insecticide Response-Associated Transcripts in the Colorado Potato Beetle: Relevance of Selected Cytochrome P450s and Clothianidin
Bibliographic record
Abstract
The Colorado potato beetle (Leptinotarsa decemlineata (Say)) is known for its capacity to cause significant damages to potato crops worldwide. Multiple approaches have been considered to limit its spread including the use of a diverse arsenal of insecticides. Unfortunately, this insect frequently develops resistance towards these compounds. Investigating the molecular bases underlying the response of L. decemlineata against insecticides is of strong interest to ultimately devise novel and targeted approaches aimed at this pest. This work aimed to characterize, via qRT-PCR, the expression status of targets with relevance to insecticide response, including ones coding for cytochrome P450s, glutathione s-transferases, and cuticular proteins, in L. decemlineata exposed to four insecticides; chlorantraniliprole, clothianidin, imidacloprid, and spinosad. Modulation of levels associated with transcripts coding for selected cytochrome P450s was reported in insects treated with three of the four insecticides studied. Clothianidin treatment yielded the most variations in transcript levels, leading to significant changes in transcripts coding for CYP4c1, CYP4g15, CYP6a13, CYP9e2, GST, and GST-1-Like. Injection of dsRNA targeting CYP4c1 and CYP9e2 was associated with a substantial decrease in expression levels and was, in the case of the latter target, linked to a greater susceptibility of L. decemlineata towards this neonicotinoid, supporting a potential role for this target in clothianidin response. Overall, this data further highlights the differential expression of transcripts with potential relevance in insecticide response, as well as generating specific targets that warrant investigation as novel dsRNA-based approaches are developed against this insect pest.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".