Substrate Specificity and Kinetic Characterization of Peptidoglycan O-Acetyltransferase B from Neisseria gonorrhoeae
Bibliographic record
Abstract
The O-acetylation of the essential cell wall polymer peptidoglycan is a major virulence factor identified in many bacteria, both Gram-positive and Gram-negative, including Staphylococcus aureus, Bacillus anthracis, Neisseria gonorrhoeae, and Neisseria meningitidis. With Gram-negative bacteria, the translocation of acetyl groups from the cytoplasm is performed by an integral membrane protein, PatA, for its transfer to peptidoglycan by O-acetyltransferase PatB, whereas a single bimodal membrane protein, OatA, appears to catalyze both reactions of the process in Gram-positive bacteria. Only phenotypic evidence existed in support of these pathways because no in vitro biochemical assay was available for their analysis, which reflected the complexities of investigating integral membrane proteins that act on a totally insoluble and heterogeneous substrate, such as peptidoglycan. In this study, we present the first biochemical and kinetic analysis of a peptidoglycan O-acetyltransferase using PatB from N. gonorrhoeae as the model system. The enzyme has specificity for muropeptides that possess tri- and tetrapeptide stems on muramyl residues. With chitooligosaccharides as substrates, rates of reaction increase with increasing degrees of polymerization to 5/6. This information will be valuable for the identification and development of peptidoglycan O-acetyltransferase inhibitors that could represent potential leads to novel classes of antibiotics.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 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".