Spinosad‐associated modulation of select cytochrome P450s and glutathione S‐transferases in the Colorado potato beetle, <i>Leptinotarsa decemlineata</i>
Bibliographic record
Abstract
The Colorado potato beetle (Leptinotarsa decemlineata (Say)) is an insect pest that threatens potato crops. Multiple options exist to limit the impact of this pest even though insecticides remain a primary option for its control. Insecticide resistance has been reported in Colorado potato beetles and a better understanding of the molecular players underlying such process is of utmost importance to optimize the tools used to mitigate the impact of this insect. Resistance against the insecticide spinosad has been reported in this insect and this work thus aims at exploring the expression of targets previously associated with insecticide response in Colorado potato beetles exposed to this compound. Amplification and quantification of transcripts coding for cytochrome P450s and glutathione S-transferases were conducted via qRT-PCR in insects treated with varying doses of spinosad and for different time duration. This approach notably revealed differential expression of CYP6a23 and CYP12a5 in insects exposed to low doses of spinosad for 4 h as well as modulation of CYP6a13, CYP6d4, GST, GST1, and GST1-Like in insects treated with high doses of spinosad for the same duration. RNAi-based targeting of CYP4g15 and CYP6a23 was associated with marked reduction of transcript expression 7 days following dsRNA injection and reduction of the former had a marked impact on insect viability. In general, results presented here provide novel information regarding the expression of transcripts relevant to spinosad response in Colorado potato beetles and reveal a novel target to consider in the development of RNAi-based strategies aimed at this potato pest.
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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".