Disease resistance through impairment of α-SNAP–NSF interaction and vesicular trafficking by soybean <i>Rhg1</i>
Bibliographic record
Abstract
α-SNAP [soluble NSF (N-ethylmaleimide-sensitive factor) attachment protein] and NSF proteins are conserved across eukaryotes and sustain cellular vesicle trafficking by mediating disassembly and reuse of SNARE protein complexes, which facilitate fusion of vesicles to target membranes. However, certain haplotypes of the Rhg1 (resistance to Heterodera glycines 1) locus of soybean possess multiple repeat copies of an α-SNAP gene (Glyma.18G022500) that encodes atypical amino acids at a highly conserved functional site. These Rhg1 loci mediate resistance to soybean cyst nematode (SCN; H. glycines), the most economically damaging pathogen of soybeans worldwide. Rhg1 is widely used in agriculture, but the mechanisms of Rhg1 disease resistance have remained unclear. In the present study, we found that the resistance-type Rhg1 α-SNAP is defective in interaction with NSF. Elevated in planta expression of resistance-type Rhg1 α-SNAPs depleted the abundance of SNARE-recycling 20S complexes, disrupted vesicle trafficking, induced elevated abundance of NSF, and caused cytotoxicity. Soybean, due to ancient genome duplication events, carries other loci that encode canonical (wild-type) α-SNAPs. Expression of these α-SNAPs counteracted the cytotoxicity of resistance-type Rhg1 α-SNAPs. For successful growth and reproduction, SCN dramatically reprograms a set of plant root cells and must sustain this sedentary feeding site for 2-4 weeks. Immunoblots and electron microscopy immunolocalization revealed that resistance-type α-SNAPs specifically hyperaccumulate relative to wild-type α-SNAPs at the nematode feeding site, promoting the demise of this biotrophic interface. The paradigm of disease resistance through a dysfunctional variant of an essential gene may be applicable to other plant-pathogen interactions.
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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".