The C-Terminal Domains SnRK2 Box and ABA Box Have a Role in Sugarcane SnRK2s Auto-Activation and Activity
Bibliographic record
Abstract
Resistance to drought stress is fundamental to plant survival and development. Abscisic acid (ABA) is one of the major hormones involved in different types of abiotic and biotic stress responses. ABA intracellular signaling has been extensively explored in Arabidopsis thaliana and occurs via a phosphorylation cascade mediated by three related protein kinases, denominated SnRK2s (SNF1-related protein kinases). However, the role of ABA signaling and the biochemistry of SnRK2 in crop plants remains underexplored. Considering the importance of the ABA hormone in abiotic stress tolerance, here we investigated the regulatory mechanism of sugarcane SnRK2s - known as SAPKs (Stress/ABA-activated Protein Kinases). The crystal structure of ScSAPK10 revealed the characteristic SnRK2 family architecture, in which the regulatory SnRK2-box interacts with the kinase domain αC helix. To study sugarcane SnRK2 regulation, we produced a series of mutants for the protein regulatory domains SnRK2-box and ABA-box. Mutations in ScSAPK8 SnRK2-box aimed at perturbing its interaction with the protein kinase domain reduced protein kinase activity in vitro. On the other hand, mutations to ScSAPK ABA-box did not impact protein kinase activity but did alter the protein autophosphorylation pattern. Taken together, our results demonstrate that both SnRK2- and ABA-boxes might play a role in sugarcane SnRK2 function.
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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) | 0.002 | 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".