Cefepime-Taniborbactam and Ceftibuten-Ledaborbactam Maintain Activity Against KPC Variants that Lead to Ceftazidime-Avibactam Resistance
Bibliographic record
Abstract
Abstract Klebsiella pneumoniae carbapenemases (KPCs) are widespread β-lactamases that are a major cause of clinical non-susceptibility of Gram-negative bacteria to carbapenems and other β-lactam antibiotics. Ceftazidime combined with the β-lactamase inhibitor avibactam (CAZ-AVI) has been effective for treating infections by KPC-producing bacteria, but emergent KPC variants confer resistance to the combination. Taniborbactam and ledaborbactam are bicyclic boronate β-lactamase inhibitors under development with cefepime and ceftibuten, respectively, to treat carbapenem-resistant bacterial infections. Here, we assessed the effects of clinically important KPC-2 and KPC-3 variants (V240G, D179Y, D179Y T243M) on the antibacterial activity of cefepime-taniborbactam (FEP-TAN) and ceftibuten-ledaborbactam (CTB-LED) and examined catalytic activity and inhibition of these variants. FEP-TAN and CTB-LED were highly active against CAZ-AVI-resistant engineered E. coli strains expressing these variants. Purified KPC variants catalyzed more efficient CAZ hydrolysis than wild-type enzymes, and D179Y-containing KPC-3 variants additionally catalyzed more efficient FEP hydrolysis than wild-type KPC-3. All KPC variants poorly hydrolyzed CTB, and D179Y-containing variants demonstrated significantly higher affinity for CAZ than FEP or CTB. Second-order rate constants ( k 2 / K ) for inhibition of D179Y-containing KPC-2 variants were significantly reduced relative to wild-type KPC-2, with AVI most impacted. K 2 / K was less affected for D179Y-containing KPC-3 variants, and reflected robust inhibition by TAN, LED and AVI. Together, the findings illustrate a biochemical basis for greater FEP-TAN and CTB-LED antibacterial activity in KPC variant expression backgrounds relative to CAZ-AVI, whereby the boronate inhibitors have sufficient inhibitory activity, whilst FEP and CTB are poorer substrates and bind to the variant enzymes with reduced affinity compared to CAZ.
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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 | 0.000 |
| 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) | 0.001 | 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".