LIKE SEX4 1 Acts as a β-Amylase-Binding Scaffold on Starch Granules during Starch Degradation
Bibliographic record
Abstract
In Arabidopsis (Arabidopsis thaliana) leaves, starch is synthesized during the day and degraded at night to fuel growth and metabolism. Starch is degraded primarily by β-amylases, liberating maltose, but this activity is preceded by glucan phosphorylation and is accompanied by dephosphorylation. A glucan phosphatase family member, LIKE SEX4 1 (LSF1), binds starch and is required for normal starch degradation, but its exact role is unclear. Here, we show that LSF1 does not dephosphorylate glucans. The recombinant dual specificity phosphatase (DSP) domain of LSF1 had no detectable phosphatase activity. Furthermore, a variant of LSF1 mutated in the catalytic cysteine of the DSP domain complemented the starch-excess phenotype of the lsf1 mutant. By contrast, a variant of LSF1 with mutations in the carbohydrate binding module did not complement lsf1. Thus, glucan binding, but not phosphatase activity, is required for the function of LSF1 in starch degradation. LSF1 interacts with the β-amylases BAM1 and BAM3, and the BAM1-LSF1 complex shows amylolytic but not glucan phosphatase activity. Nighttime maltose levels are reduced in lsf1, and genetic analysis indicated that the starch-excess phenotype of lsf1 is dependent on bam1 and bam3. We propose that LSF1 binds β-amylases at the starch granule surface, thereby promoting starch degradation.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".