Broadening the Spectrum of β-Lactam Antibiotics through Inhibition of Signal Peptidase Type I
Bibliographic record
Abstract
The resistance of methicillin-resistant Staphylococcus aureus (MRSA) to all β-lactam classes limits treatment options for serious infections involving this organism. Our goal is to discover new agents that restore the activity of β-lactams against MRSA, an approach that has led to the discovery of two classes of natural product antibiotics, a cyclic depsipeptide (krisynomycin) and a lipoglycopeptide (actinocarbasin), which potentiate the activity of imipenem against MRSA strain COL. We report here that these imipenem synergists are inhibitors of the bacterial type I signal peptidase SpsB, a serine protease that is required for the secretion of proteins that are exported through the Sec and Tat systems. A synthetic derivative of actinocarbasin, M131, synergized with imipenem both in vitro and in vivo with potent efficacy. The in vitro activity of M131 extends to clinical isolates of MRSA but not to a methicillin-sensitive strain. Synergy is restricted to β-lactam antibiotics and is not observed with other antibiotic classes. We propose that the SpsB inhibitors synergize with β-lactams by preventing the signal peptidase-mediated secretion of proteins required for β-lactam resistance. Combinations of SpsB inhibitors and β-lactams may expand the utility of these widely prescribed antibiotics to treat MRSA infections, analogous to β-lactamase inhibitors which restored the utility of this antibiotic class for the treatment of resistant Gram-negative infections.
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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".