Efficacy of aspergillomarasmine A/meropenem combinations with and without avibactam against bacterial strains producing multiple β-lactamases
Bibliographic record
Abstract
ABSTRACT The effectiveness of β-lactam antibiotics is increasingly threatened by resistant bacteria that harbor hydrolytic β-lactamase enzymes. Depending on the class of β-lactamase present, β-lactam hydrolysis can occur through one of two general molecular mechanisms. Metallo-β-lactamases (MBLs) require active site Zn 2+ ions, whereas serine-β-lactamases (SBLs) deploy a catalytic serine residue. The result in both cases is drug inactivation via the opening of the β-lactam warhead of the antibiotic. MBLs confer resistance to most β-lactams and are non-susceptible to SBL inhibitors, including recently approved diazabicyclooctanes, such as avibactam; consequently, these enzymes represent a growing threat to public health. Aspergillomarasmine A (AMA), a fungal natural product, can rescue the activity of the β-lactam antibiotic meropenem against MBL-expressing bacterial strains. However, the effectiveness of this β-lactam/β-lactamase inhibitor combination against bacteria producing multiple β-lactamases remains unknown. We systematically investigated the efficacy of AMA/meropenem combination therapy with and without avibactam against 10 Escherichia coli and 10 Klebsiella pneumoniae laboratory strains tandemly expressing single MBL and SBL enzymes. Cell-based assays demonstrated that laboratory strains producing NDM-1 and KPC-2 carbapenemases were resistant to the AMA/meropenem combination but became drug-susceptible upon adding avibactam. We also probed these combinations against 30 clinical isolates expressing multiple β-lactamases. E. coli , Enterobacter cloacae, and K. pneumoniae clinical isolates were more susceptible to AMA, avibactam, and meropenem than Pseudomonas aeruginosa and Acinetobacter baumannii isolates. Overall, the results demonstrate that a triple combination of AMA/avibactam/meropenem has potential for empirical treatment of infections caused by multiple β-lactamase-producing bacteria, especially Enterobacterales.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.001 | 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 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".