A complete MAPK cascade, a calmodulin, and a protein phosphatase act downstream of CRK receptor kinases and regulate <i>Arabidopsis</i> innate immunity
Bibliographic record
Abstract
Abstract Mitogen-activated protein kinase (MAPK) cascades are critical signal transduction modules in stress responses, but how their composition and mode of activation induces a stress response is poorly understood. We showed in Arabidopsis that CRK21, a cysteine-rich receptor-like protein kinase (CRK), phosphorylates MAPK kinase kinase 20 (MKKK20) and thus directly activates a novel MAPK cascade, consisting of MKKK20, the MAPK kinase MKK3, and the MAPK MPK6. Furthermore, the protein phosphatase PP2C76 and the calmodulin CaM7 were identified as negative and positive modulators of the cascade, respectively. Loss-of-function in components of the MAPK cascade or in CaM7 led to susceptibility to the bacterial pathogen Pseudomonas syringae and the fungal pathogen Botrytis cinerea . In contrast, loss-of-function of PP2C76 as well as transient overexpression of the genes in the MAPK cascade and CaM7 conferred resistance to the pathogens. Moreover, seven additional CRKs interacted with MKKK20 in vivo , and four of these were highly expressed after inoculation with P. syringae . In summary, our findings demonstrate that the novel CRK21-MKKK20-MKK3-MPK6 signaling pathway functions in immunity to fungal and bacterial pathogens and that CRKs may function in directly activating MKKKs.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".