Recognition of the Pseudomonas syringae type III effector HopF1r by the Arabidopsis NLR ZAR1
Bibliographic record
Abstract
The plant pathogen Pseudomonas syringae uses the needle-like type III secretion system (T3SS) to inject virulence factors known as type III secreted effector proteins (T3SEs) directly into the plant cell. T3SEs disrupt plant immune pathways, allowing for successful colonization. However, plants have evolved resistance (R) genes that encode for nucleotide-binding leucine-rich repeat (NLR) proteins that detect the presence of some effectors, and subsequently trigger an immune response that suppresses pathogen growth. Recognition of effectors by NLRs often involves monitoring another host protein for effector-induced molecular perturbations; upon detection of these modifications, an immune response is triggered. For example, the NLR ZAR1 senses effector-mediated perturbations of associated kinases to detect at least 6 families of T3SEs. The effector HopF2a/HopF1r from P. syringae pv. aceris M302273PT has been found to trigger immunity in Arabidopsis. The objective of my research was 1) to identify other potential genetic requirements for HopF2a/HopF1r recognition in Arabidopsis, and 2) to understand how these components are involved in the HopF2a/HopF1r recognition mechanism. In this thesis, I demonstrate that recognition of HopF2a/HopF1r requires the R gene ZAR1, as well as the kinases ZRK3 and PBL27. The results of this project provide insight into how a single NLR is able to recognize several unrelated effectors by associating with different members of a diverse family of kinases, providing plants with the potential to defend themselves against a wide variety of pathogens.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 | 0.000 |
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".