Selective regulation of the chitin‐induced defense response by the <scp>A</scp>rabidopsis receptor‐like cytoplasmic kinase <scp>PBL</scp>27
Bibliographic record
Abstract
Recognition of microbe-associated molecular patterns (MAMPs) initiates pattern-triggered immunity in host plants. Pattern recognition receptors (PRRs) and receptor-like cytoplasmic kinases (RLCKs) are the major components required for sensing and transduction of these molecular patterns. However, the regulation of RLCKs by PRRs and their specificity remain obscure. In this study we show that PBL27, an Arabidopsis ortholog of OsRLCK185, is an immediate downstream component of the chitin receptor CERK1 and contributes to the regulation of chitin-induced immunity in Arabidopsis. Knockout of PBL27 resulted in the suppression of several chitin-induced defense responses, including the activation of MPK3/6 and callose deposition as well as in disease resistance against fungal and bacterial infections. On the other hand, the contribution of PBL27 to flg22 signaling appears to be very limited, suggesting that PBL27 selectively regulates defense signaling downstream of specific PRR complexes. In vitro phosphorylation experiments showed that CERK1 preferentially phosphorylated PBL27 in comparison to BIK1, whereas phosphorylation of PBL27 by BAK1 was very low compared with that of BIK1. Thus, the substrate specificity of the signaling receptor-like kinases, CERK1 and BAK1, may determine the preference of downstream RLCKs.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".