Mechanistic insights into phosphoactivation of SLAC1 in guard cell signaling
Bibliographic record
Abstract
Stomata in leaves regulate gas (carbon dioxide and water vapor) exchange and water transpiration between plants and the atmosphere. SLow Anion Channel 1 (SLAC1) mediates anion efflux from guard cells and plays a crucial role in controlling stomatal aperture. It serves as a central hub for multiple signaling pathways in response to environmental stimuli, with its activity regulated through phosphorylation via various plant protein kinases. However, the molecular mechanism underlying SLAC1 phosphoactivation has remained elusive. Through a combination of protein sequence analyses, AlphaFold-based modeling and electrophysiological studies, we unveiled that the highly conserved motifs on the N- and C-terminal segments of SLAC1 form a cytosolic regulatory domain (CRD) that interacts with the transmembrane domain(TMD), thereby maintaining the channel in an autoinhibited state. Mutations in these conserved motifs destabilize the CRD, releasing autoinhibition in SLAC1 and enabling its transition into an activated state. Our further studies demonstrated that SLAC1 activation undergoes an autoinhibition-release process and subsequent structural changes in the pore helices. These findings provide mechanistic insights into the activation mechanism of SLAC1 and shed light on understanding how SLAC1 controls stomatal closure in response to environmental stimuli.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".