Arabidopsis ETHYLENE RESPONSE FACTOR 8 (ERF8) has dual functions in ABA signaling and immunity
Bibliographic record
Abstract
BACKGROUND: ETHYLENE RESPONSE FACTOR (ERF) 8 is a member of one of the largest transcription factor families in plants, the APETALA2/ETHYLENE RESPONSIVE FACTOR (AP2/ERF) superfamily. Members of this superfamily have been implicated in a wide variety of processes such as development and environmental stress responses. RESULTS: In this study we demonstrated that ERF8 is involved in both ABA and immune signaling. ERF8 overexpression induced programmed cell death (PCD) in Arabidopsis and Nicotiana benthamiana. This PCD was salicylic acid (SA)-independent, suggesting that ERF8 acts downstream or independent of SA. ERF8-induced PCD was abolished by mutations within the ERF-associated amphiphilic repression (EAR) motif, indicating ERF8 induces cell death through its transcriptional repression activity. Two immunity-related mitogen-activated protein kinases, MITOGEN-ACTIVATED PROTEIN KINASE 4 (MPK4) and MPK11, were identified as ERF8-interacting proteins and directly phosphorylated ERF8 in vitro. Four putative MPK phosphorylation sites were identified in ERF8, one of which (Ser103) was determined to be the predominantly phosphorylated residue in vitro, while mutation of all four putative phosphorylation sites partially suppressed ERF8-induced cell death in N. benthamiana. Genome-wide transcriptomic analysis and pathogen growth assays confirmed a positive role of ERF8 in mediating immunity, as ERF8 knockdown or overexpression lines conferred compromised or enhanced resistance against the hemibiotrophic bacterial pathogen Pseudomonas syringae, respectively. CONCLUSIONS: Together these data reveal that the ABA-inducible transcriptional repressor ERF8 has dual roles in ABA signaling and pathogen defense, and further highlight the complex influence of ABA on plant-microbe interactions.
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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 | 0.000 |
| 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".