Poly-β-(1→6)-N-acetyl-D-glucosamine mediates surface attachment, biofilm formation, and biocide resistance in Cutibacterium acnes
Bibliographic record
Abstract
Background The commensal skin bacterium Cutibacterium acnes plays a role in the pathogenesis of acne vulgaris and also causes opportunistic infections of implanted medical devices due to its ability to form biofilms on biomaterial surfaces. Poly-β-(1→6)-N-acetyl-D-glucosamine (PNAG) is an extracellular polysaccharide that mediates biofilm formation and biocide resistance in a wide range of bacterial pathogens. The objective of this study was to determine whether C. acnes produces PNAG, and whether PNAG contributes to C. acnes biofilm formation and biocide resistance in vitro. Methods PNAG was detected on the surface of C. acnes cells by fluorescence confocal microscopy using the antigen-specific human IgG1 monoclonal antibody F598. PNAG was detected in C. acnes biofilms by measuring the ability of the PNAG-specific glycosidase dispersin B to inhibit biofilm formation and sensitize biofilms to biocide killing. Results Monoclonal antibody F598 bound to the surface of C. acnes cells. Dispersin B inhibited attachment of C. acnes cells to polystyrene rods, inhibited biofilm formation by C. acnes in glass and polypropylene tubes, and sensitized C. acnes biofilms to killing by benzoyl peroxide and tetracycline. Conclusion C. acnes produces PNAG, and PNAG contributes to C. acnes biofilm formation and biocide resistance in vitro. PNAG may play a role in C. acnes skin colonization, biocide resistance, and virulence in vivo.
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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) | 0.001 | 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 | 0.001 |
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".