<i>In vitro</i> and <i>in vivo</i> application of RNA interference for targeting genes involved in peritrophic matrix synthesis in a lepidopteran system
Bibliographic record
Abstract
The midgut of most insects is lined with a semipermeable acellular tube, the peritrophic matrix (PM), composed of chitin and proteins. Although various genes encoding PM proteins have been characterized, our understanding of their roles in PM structure and function is very limited. One promising approach for obtaining functional information is RNA interference, which has been used to reduce the levels of specific mRNAs using double-stranded RNAs administered to larvae by either injection or feeding. Although this method is well documented in dipterans and coleopterans, reports of its success in lepidopterans are varied. In the current study, the silencing midgut genes encoding PM proteins (insect intestinal mucin 1, insect intestinal mucin 4, PM protein 1) and the chitin biosynthetic or modifying enzymes (chitin synthase-B and chitin deacetylase 1) in a noctuid lepidopteran, Mamestra configurata, was examined in vitro and in vivo. In vitro studies in primary midgut epithelial cell preparations revealed an acute and rapid silencing (by 24 h) for the gene encoding chitin deacetylase 1 and a slower rate of silencing (by 72 h) for the gene encoding PM protein 1. Genes encoding insect intestinal mucins were slightly silenced by 72 h, whereas no silencing was detected for the gene encoding chitin synthase-B. In vivo experiments focused on chitin deacetylase 1, as the gene was silenced to the greatest extent in vitro. Continuous feeding of neonates and fourth instar larvae with double-stranded RNA resulted in silencing of chitin deacetylase 1 by 24 and 36 h, respectively. Feeding a single dose to neonates also resulted in silencing by 24 h. The current study demonstrates that genes encoding PM proteins can be silenced and outlines conditions for RNA interference by per os feeding in lepidopterans.
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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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".