Nematode neuropeptides as transgenic nematicides
Bibliographic record
Abstract
Plant parasitic nematodes (PPNs) seriously threaten global food security. Conventionally an integrated approach to PPN management has relied heavily on carbamate, organophosphate and fumigant nematicides which are now being withdrawn over environmental health and safety concerns. This progressive withdrawal has left a significant shortcoming in our ability to manage these economically important parasites, and highlights the need for novel and robust control methods. Nematodes can assimilate exogenous peptides through retrograde transport along the chemosensory amphid neurons. Peptides can accumulate within cells of the central nerve ring and can elicit physiological effects when released to interact with receptors on adjoining cells. We have profiled bioactive neuropeptides from the neuropeptide-like protein (NLP) family of PPNs as novel nematicides, and have identified numerous discrete NLPs that negatively impact chemosensation, host invasion and stylet thrusting of the root knot nematode Meloidogyne incognita and the potato cyst nematode Globodera pallida. Transgenic secretion of these peptides from the rhizobacterium, Bacillus subtilis, and the terrestrial microalgae Chlamydomonas reinhardtii reduce tomato infection levels by up to 90% when compared with controls. These data pave the way for the exploitation of nematode neuropeptides as a novel class of plant protective nematicide, using novel non-food transgenic delivery systems which could be deployed on farmer-preferred cultivars.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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 | 0.001 |
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 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".