An unusual class of anthracyclines potentiate Gram-positive antibiotics in intrinsically resistant Gram-negative bacteria
Bibliographic record
Abstract
OBJECTIVES: An orthogonal approach taken towards novel antibacterial drug discovery involves the identification of small molecules that potentiate or enhance the activity of existing antibacterial agents. This study aimed to identify natural-product rifampicin adjuvants in the intrinsically resistant organism Escherichia coli. METHODS: E. coli BW25113 was screened against 1120 actinomycete fermentation extracts in the presence of subinhibitory (2 mg/L) concentrations of rifampicin. The active molecule exhibiting the greatest rifampicin potentiation was isolated using activity-guided methods and identified using mass and NMR spectroscopy. Susceptibility testing and biochemical assays were used to determine the mechanism of antibiotic potentiation. RESULTS: The anthracycline Antibiotic 301A(1) was isolated from the fermentation broth of a strain of Streptomyces (WAC450); the molecule was shown to be highly synergistic with rifampicin (fractional inhibitory concentration index = 0.156) and moderately synergistic with linezolid (FIC index = 0.25) in both E. coli and Acinetobacter baumannii. Activity was associated with inhibition of efflux and the synergistic phenotype was lost when tested against E. coli harbouring mutations within the rpoB gene. Structure-activity relationship studies revealed that other anthracyclines do not synergize with rifampicin and removal of the sugar moiety of Antibiotic 301A(1) abolishes activity. CONCLUSIONS: Screening only a subsection of our natural product library identified a small-molecule antibiotic adjuvant capable of sensitizing Gram-negative bacteria to antibiotics to which they are ordinarily intrinsically resistant. This result demonstrates the great potential of this approach in expanding antibiotic effectiveness in the face of the growing challenge of resistance in Gram-negatives.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".