The <i>Arabidopsis</i> ZED1 pseudokinase is required for ZAR1-mediated immunity induced by the <i>Pseudomonas syringae</i> type III effector HopZ1a
Bibliographic record
Abstract
Plant and animal pathogenic bacteria can suppress host immunity by injecting type III secreted effector (T3SE) proteins into host cells. However, T3SEs can also elicit host immunity if the host has evolved a means to recognize the presence or activity of specific T3SEs. The diverse YopJ/HopZ/AvrRxv T3SE superfamily, which is found in both animal and plant pathogens, provides examples of T3SEs playing this dual role. The T3SE HopZ1a is an acetyltransferase carried by the phytopathogen Pseudomonas syringae that elicits effector-triggered immunity (ETI) when recognized in Arabidopsis thaliana by the nucleotide-binding leucine-rich repeat (NB-LRR) protein ZAR1. However, recognition of HopZ1a does not require any known ETI-related genes. Using a forward genetics approach, we identify a unique ETI-associated gene that is essential for ZAR1-mediated immunity. The hopZ-ETI-deficient1 (zed1) mutant is specifically impaired in the recognition of HopZ1a, but not the recognition of other unrelated T3SEs or in pattern recognition receptor (PRR)-triggered immunity. ZED1 directly interacts with both HopZ1a and ZAR1 and is acetylated on threonines 125 and 177 by HopZ1a. ZED1 is a nonfunctional kinase that forms part of small genomic cluster of kinases in Arabidopsis. We hypothesize that ZED1 acts as a decoy to lure HopZ1a to the ZAR1-resistance complex, resulting in ETI activation.
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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 | 0.001 |
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 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".