Discovery of Novel Cell Wall-Active Compounds Using P <sub> <i>ywaC</i> </sub> , a Sensitive Reporter of Cell Wall Stress, in the Model Gram-Positive Bacterium Bacillus subtilis
Bibliographic record
Abstract
The emergence of antibiotic resistance in recent years has radically reduced the clinical efficacy of many antibacterial treatments and now poses a significant threat to public health. One of the earliest studied well-validated targets for antimicrobial discovery is the bacterial cell wall. The essential nature of this pathway, its conservation among bacterial pathogens, and its absence in human biology have made cell wall synthesis an attractive pathway for new antibiotic drug discovery. Herein, we describe a highly sensitive screening methodology for identifying chemical agents that perturb cell wall synthesis, using the model of the Gram-positive bacterium Bacillus subtilis. We report on a cell-based pilot screen of 26,000 small molecules to look for cell wall-active chemicals in real time using an autonomous luminescence gene cluster driven by the promoter of ywaC, which encodes a guanosine tetra(penta)phosphate synthetase that is expressed under cell wall stress. The promoter-reporter system was generally much more sensitive than growth inhibition testing and responded almost exclusively to cell wall-active antibiotics. Follow-up testing of the compounds from the pilot screen with secondary assays to verify the mechanism of action led to the discovery of 9 novel cell wall-active compounds.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".