The Evolutionarily Conserved E3 Ubiquitin Ligase AtCHIP Contributes to Plant Immunity
Bibliographic record
Abstract
Plants possess a sophisticated immune system to recognize and respond to microbial threats in their environment. The level of immune signaling must be tightly regulated so that immune responses can be quickly activated in the presence of pathogens, while avoiding autoimmunity. HSP90s, along with their diverse array of co-chaperones, forms chaperone complexes that have been shown to play both positive and negative roles in regulating the accumulation of immune receptors and regulators. In this study, we examined the role of AtCHIP, an evolutionarily conserved E3 ligase that was known to interact with chaperones including HSP90s in multicellular organisms including fruit fly, Caenorhabditis elegans, plants and human. Atchip knockout mutants display enhanced disease susceptibility to a virulent oomycete pathogen, and overexpression of AtCHIP causes enhanced disease resistance at low temperature. Although CHIP was reported to target HSP90 for ubiquitination and degradation, accumulation of HSP90.3 was not affected in Atchip plants. In addition, protein accumulation of nucleotide-binding, leucine-rich repeat domain immune receptor (NLR) SNC1 is not altered in Atchip mutant. Thus, while AtCHIP plays a role in immunity, it does not seem to regulate the turnover of HSP90 or SNC1. Further investigation is needed in order to determine the exact mechanism behind AtCHIP's role in regulating plant immune responses.
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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".