Synthesis of defined mono-de-<i>N</i>-acetylated β-(1→6)-<i>N</i>-acetyl-<scp>d</scp>-glucosamine oligosaccharides to characterize PgaB hydrolase activity
Bibliographic record
Abstract
Many clinically-relevant biofilm-forming bacterial strains produce partially de-N-acetylated poly-β-(1→6)-N-acetyl-d-glucosamine (dPNAG) as an exopolysaccharide. In Gram-negative bacteria, the periplasmic protein PgaB is responsible for partial de-N-acetylation of PNAG prior to its export to the extracellular space. In addition to de-N-acetylase activity found in the N-terminal domain, PgaB contains a C-terminal hydrolase domain that can disrupt dPNAG-dependent biofilms and hydrolyzes dPNAG but not fully acetylated PNAG. The role of this C-terminal domain in biofilm formation has yet to be determined in vivo. Further characterization of the enzyme's hydrolase activity has been hampered by a lack of specific dPNAG oligosaccharides. Here, we report the synthesis of a defined mono de-N-acetylated dPNAG penta- and hepta-saccharide. Using mass spectrometry analysis and a fluorescence-based thin-layer chromatography (TLC) assay, we found that our defined dPNAG oligosaccharides are hydrolase substrates. In addition to the expected cleavage site, two residues to the reducing side of the de-N-acetylated residue, minor cleavage products on the non-reducing side of the de-N-acetylation site were observed. These findings provide quantitative data to support how PNAG is processed in Gram-negative bacteria.
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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".