Cross-Recognition of the ssgBp Promoter, Which Controls the Expression of the Sporulation–Specific Cell Division Gene ssgB, by Nine SigB Homologues in Streptomyces coelicolor A3(2)
Bibliographic record
Abstract
In their natural environment, bacteria are exposed to various stresses. The stress-response sigma factor SigB of gram-positive Bacillus subtilis is the best-characterized example. Unlike Bacillus subtilis, the gram-positive bacterium Streptomyces coelicolor A3(2) contains nine SigB homologues (SigBFGHIKLMN) with a major role in differentiation and response to osmotic stress. We previously constructed a two-plasmid system to identify promoters recognized by these sigma factors. Interestingly, almost all identified promoters were recognized by two or more SigB homologues. However, no specific sequences characteristic for these recognition groups were found. To examine this cross-recognition in vivo in S. coelicolor A3 (2), one of these promoters was cho-sen, which drives the expression of the sporulation-specific gene ssgB. The ssgBp promoter was inserted into a luciferase reporter plasmid and conjugated to S. coelicolor M145 and nine mutant strains containing deleted individual sigB homologous genes. Luciferase reporter activity indi-cated differential activity of this promoter in these mutant strains, suggesting overlapping pro-moter recognition by these SigB homologues. To determine which nucleotides in the ̶ 10 re-gion are responsible for the selection of a specific SigB homologue, several mutant promoters with altered last three nucleotides in this region were prepared and tested in the two-plasmid system. Some mutant promoters were specifically recognized by some SigB homologues. Mutant promoters were inserted into a luciferase reporter plasmid and conjugated to S. coelicolor A3(2) and these nine mutant strains. Luciferase reporter activity indicated differential activity of these ssgBp mutant promoters, indicating overlapping promoter recognition by these SigB homologues in S. coelicolor A3(2).
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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 | 0.001 |
| 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".