The Deubiquitinating Enzyme AMSH1 Contributes to Plant Immunity Through Regulating the Stability of BDA1
Bibliographic record
Abstract
Plants utilize plasma membrane localized receptors like kinases (RLKs) or receptor-like proteins (RLPs) to recognize pathogens and activate pattern-triggered immunity (PTI) responses. A gain-of-function mutation in the Arabidopsis RLP SNC2 (SUPPRESSOR OF NPR1-1, CONSTITUTIVE 2) leads to constitutive activation of defense responses in snc2-1D mutant plants. Transcription factors, SYSTEMIC ACQUIRED RESISTANCE DEFICIENT 1 (SARD1) and CALMODULIN-BINDING PROTEIN 60g (CBP60g), define two parallel pathways downstream of SNC2. The autoimmunity of snc2-1D was partially affected by single mutations in SARD1 or CBP60g but completely suppressed by the sard1 cbp60g double mutant. From a suppressor screen using sard1-1 snc2-1D, we identified a deubiquitinating enzyme ASSOCIATED MOLECULE WITH THE SH3 DOMAIN OF STAM 1 (AMSH1) as a key component in SNC2-mediated plant immunity. A loss-of-function mutation in AMSH1 can suppress the autoimmune responses of sard1-1 snc2-1D. In eukaryotes, selective protein degradation often occurs through the ubiquitination/deubiquitination system. The deubiquitinating enzymes that remove ubiquitin from target proteins play essential roles in controlling the level of target protein ubiquitination and degradation. As loss of AMSH1 results in decreased BDA1 abundance and BDA1 is a transmembrane protein required for SNC2-mediated immunity, AMSH1 likely contributes to immunity regulation through controlling BDA1 stability.
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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".