A screen for mutants deficient in coronatine-mediated suppression of root immunity identifies <i>Arabidopsis</i> SDA1 as a novel integrator of immunity and phytohormone signaling
Bibliographic record
Abstract
Abstract Despite the importance of the root immune system in the interaction with rhizosphere microbes, the majority of genetic screens for immunity regulators have been performed in leaves. A previous screen identified 27 hsm ( h ormone-mediated s uppression of M AMP-triggered immunity) mutants that are impaired in jasmonic acid (JA)-mediated suppression of pattern-triggered immunity (PTI) in roots. Here we characterized 16 of the hsm mutants that retain JA sensitivity and are potential negative regulators of root immunity. We found that the majority of hsm mutants show enhanced resistance to Fusarium , a root fungal pathogen; however, only a subset are more resistant to a foliar pathogen. Surprisingly, 12 of 16 hsm mutants are also impaired in abscisic acid (ABA)-mediated suppression of PTI, suggesting a largely shared pathway between JA- and ABA-mediated immune suppression in roots. Although all hsm mutants are insensitive to JA-mediated suppression of root immunity, hsm4 shows hypersensitivity to JA-mediated root growth inhibition and JA-induced gene expression. Consistently, hsm4 is more resistant to leaf pathogens, suggesting that HSM4 is a negative regulator of both root and leaf immunity. Hsm4 was mapped to a mutation in a conserved ARM-repeat protein homologous to yeast SDA1, which has been reported to regulate 60S ribosome biogenesis. As translational reprogramming is a critical layer of immune regulation, this work suggests that AtSDA1 is a novel negative translational regulator of immunity. Additionally, a comprehensive characterization of all 16 hsm mutants provides a genetic toolkit to identify novel mechanisms that regulate root immunity.
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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 | 0.000 |
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 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".