Streptomyces: A Screening Tool for Bacterial Cell Division Inhibitors
Bibliographic record
Abstract
Cell division is essential for spore formation but not for viability in the filamentous streptomycetes bacteria. Failure to complete cell division instead blocks spore formation, a phenotype that can be visualized by the absence of gray (in Streptomyces coelicolor) and green (in Streptomyces venezuelae) spore-associated pigmentation. Despite the lack of essentiality, the streptomycetes divisome is similar to that of other prokaryotes. Therefore, the chemical inhibitors of sporulation in model streptomycetes may interfere with the cell division in rod-shaped bacteria as well. To test this, we investigated 196 compounds that inhibit sporulation in S. coelicolor. We show that 19 of these compounds cause filamentous growth in Bacillus subtilis, consistent with impaired cell division. One of the compounds is a DNA-damaging agent and inhibits cell division by activating the SOS response. The remaining 18 act independently of known stress responses and may therefore act on the divisome or on divisome positioning and stability. Three of the compounds (Fil-1, Fil-2, and Fil-3) confer distinct cell division defects on B. subtilis. They also block B. subtilis sporulation, which is mechanistically unrelated to the sporulation pathway of streptomycetes but is also dependent on the divisome. We discuss ways in which these differing phenotypes can be used in screens for cell division inhibitors.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".