AtCDC48A is involved in the turnover of an NLR immune receptor
Bibliographic record
Abstract
Summary Plants rely on different immune receptors to recognize pathogens and defend against pathogen attacks. Nucleotide‐binding domain and leucine‐rich repeat ( NLR ) proteins play a major role as intracellular immune receptors. Their homeostasis must be maintained at optimal levels in order to effectively recognize pathogens without causing autoimmunity. Previous studies have shown that the activity of the ubiquitin‐proteasome system is essential to prevent excessive accumulation of NLR proteins such as Suppressor of NPR1, Constitutive 1 (SNC1). Attenuation of the ubiquitin E3 ligase SCF CPR1 (Constitutive expressor of Pathogenesis Related genes 1) or the E4 protein MUSE3 (Mutant, SNC1‐Enhancing 3) leads to NLR accumulation and autoimmunity. In the current study, we report the identification of AtCDC48A as a negative regulator of NLR‐mediated immunity. Plants carrying Atcdc48A‐4 , a partial loss‐of‐function allele of AtCDC48A , exhibit dwarf morphology and enhanced disease resistance to the oomycete pathogen Hyaloperonospora arabidopsidis ( H.a .) Noco2. The SNC1 level is increased in Atcdc48A‐4 plants and AtCDC48A interacts with MUSE3 in co‐immunoprecipitation experiments, supporting a role for AtCDC48A in NLR turnover. While Arabidopsis contains four other paralogs of AtCDC48A, knockout mutants of these genes do not show obvious immunity‐related phenotypes, suggesting functional divergence within this family. As an AAA‐ATPase, AtCDC48A likely serves to process the poly‐ubiquitinated NLR substrate for final protein degradation by the 26S proteasome.
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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 | 0.001 | 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 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".