The type III effector HopF2 <i> <sub>Pto</sub> </i> targets <i>Arabidopsis</i> RIN4 protein to promote <i>Pseudomonas syringae</i> virulence
Bibliographic record
Abstract
Plant immunity can be induced by two major classes of pathogen-associated molecules. Pathogen- or microbe-associated molecular patterns (PAMPs or MAMPs) are conserved molecular components of microbes that serve as "non-self" features to induce PAMP-triggered immunity (PTI). Pathogen effector proteins used to promote virulence can also be recognized as "non-self" features or induce a "modified-self" state that can induce effector-triggered immunity (ETI). The Arabidopsis protein RIN4 plays an important role in both branches of plant immunity. Three unrelated type III secretion effector (TTSE) proteins from the phytopathogen Pseudomonas syringae, AvrRpm1, AvrRpt2, and AvrB, target RIN4, resulting in ETI that effectively restricts pathogen growth. However, no pathogenic advantage has been demonstrated for RIN4 manipulation by these TTSEs. Here, we show that the TTSE HopF2(Pto) also targets Arabidopsis RIN4. Transgenic plants conditionally expressing HopF2(Pto) were compromised for AvrRpt2-induced RIN4 modification and associated ETI. HopF2(Pto) interfered with AvrRpt2-induced RIN4 modification in vitro but not with AvrRpt2 activation, suggestive of RIN4 targeting by HopF2(Pto). In support of this hypothesis, HopF2 (Pto) interacted with RIN4 in vitro and in vivo. Unlike AvrRpm1, AvrRpt2, and AvrB, HopF2(Pto) did not induce ETI and instead promoted P. syringae growth in Arabidopsis. This virulence activity was not observed in plants genetically lacking RIN4. These data provide evidence that RIN4 is a major virulence target of HopF2(Pto) and that a pathogenic advantage can be conveyed by TTSEs that target RIN4.
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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) | 0.001 | 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".