In vitro evaluation of the potential for resistance development to ceragenin CSA-13
Bibliographic record
Abstract
OBJECTIVES: Though most bacteria remain susceptible to endogenous antimicrobial peptides, specific resistance mechanisms are known. As mimics of antimicrobial peptides, ceragenins were expected to retain antibacterial activity against Gram-positive and -negative bacteria, even after prolonged exposure. Serial passaging of bacteria to a lead ceragenin, CSA-13, was performed with representative pathogenic bacteria. Ciprofloxacin, vancomycin and colistin were used as comparators. The mechanisms of resistance in Gram-negative bacteria were elucidated. METHODS: Susceptible strains of Staphylococcus aureus, Pseudomonas aeruginosa and Acinetobacter baumannii were serially exposed to CSA-13 and comparators for 30 passages. MIC values were monitored. Alterations in the Gram-negative bacterial membrane composition were characterized via mass spectrometry and the susceptibility of antimicrobial-peptide-resistant mutants to CSA-13 was evaluated. RESULTS: S. aureus became highly resistant to ciprofloxacin after <20 passages. After 30 passages, the MIC values of vancomycin and CSA-13 for S. aureus increased 9- and 3-fold, respectively. The Gram-negative organisms became highly resistant to ciprofloxacin after <20 passages. MIC values of colistin for P. aeruginosa and A. baumannii increased to ≥100 mg/L after 20 passages. MIC values of CSA-13 increased to ∼20-30 mg/L and plateaued over the course of the experiment. Bacteria resistant to CSA-13 displayed lipid A modifications that are found in organisms resistant to antimicrobial peptides. CONCLUSIONS: CSA-13 retained potent antibacterial activity against S. aureus over the course of 30 serial passages. Resistance generated in Gram-negative bacteria correlates with modifications to the outer membranes of these organisms and was not stable outside of the presence of the antimicrobial.
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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) | 0.000 | 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".