The Scw1 RNA-Binding Domain Protein Regulates Septation and Cell-Wall Structure in Fission Yeast
Bibliographic record
Abstract
Loss of the nonessential RNA-binding domain protein, Scw1, increases resistance to cell-wall-degrading enzymes in fission yeast. Surprisingly, scw1 null mutations also suppress the lethality of mutations (cdc11-136, cdc7-24, cdc14-118, sid1-239, sid2-250, sid3-106, sid4-A1, and mob1-1) at all levels of the sid pathway. This pathway forms part of the septation initiation network (SIN), which regulates the onset of septum formation and ensures the proper coupling of mitosis to cytokinesis. In contrast, scw1(-) mutations do not suppress ts alleles of the rng genes, cdc12 or cdc15. These mutations also prevent the formation of a septum and in addition block assembly and/or function of the contractile acto-myosin ring. sid mutants exhibit a hyper-sensitivity to cell-wall-degrading enzymes that is suppressed by loss of Scw1. Furthermore, scw1(-)-mediated rescue of sid mutants is abolished in the presence of calcofluor white, a compound that interferes with cell-wall synthesis. These data suggest that Scw1 acts in opposition to the SIN as a negative regulator of cell-wall/septum deposition. Unlike components of the SIN, Scw1 is predominantly a cytoplasmic protein and is not localized to the spindle pole body.
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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) | 0.001 | 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".