Cryo-EM characterization of the anydromuropeptide permease AmpG central to bacterial fitness and β-lactam antibiotic resistance
Bibliographic record
Abstract
Bacteria invest significant resources into the continuous creation and tailoring of their essential protective peptidoglycan (PG) cell wall. Several soluble PG biosynthesis products in the periplasm are transported to the cytosol for recycling, leading to enhanced bacterial fitness. GlcNAc-1,6-anhydroMurNAc and peptide variants are transported by the essential major facilitator superfamily importer AmpG in Gram-negative pathogens including Escherichia coli, Klebsiella pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa. Accumulation of GlcNAc-1,6-anhydroMurNAc-pentapeptides also results from β-lactam antibiotic induced cell wall damage. In some species, these products upregulate the β-lactamase AmpC, which hydrolyzes β-lactams to allow for bacterial survival and drug-resistant infections. Here, we have used cryo-electron microscopy and chemical synthesis of substrates in an integrated structural, biochemical, and cellular analysis of AmpG. We show how AmpG accommodates the large GlcNAc-1,6-anhydroMurNAc peptides, including a unique hydrophobic vestibule to the substrate binding cavity, and characterize residues involved in binding that inform the mechanism of proton-mediated transport. AmpG is an MFS importer of bacterial cell wall fragments. Here, authors present a cryoEM structure and supporting mutagenesis to illuminate AmpG’s essential role in bacterial fitness and derepression of broad-spectrum β-lactam antibiotic resistance.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".