Alginate as an auxiliary bacterial membrane: binding of membrane‐active peptides by polysaccharides*
Bibliographic record
Abstract
The chronicity of Pseudomonas aeruginosa infections in cystic fibrosis (CF) patients is characterized by overproduction of the exopolysaccharide alginate, in which biofilm bacteria are embedded. Alginate apparently contributes to the antibiotic resistance of bacteria in this form by acting as a diffusion barrier to positively charged antimicrobial agents. We have been investigating cationic antimicrobial peptides (CAPs) (prototypic sequence: KKAAAXAAAAAXAAWAAXAAAKKKK-NH(2), where X is any of the 20 commonly occurring amino acids) that were originally designed as transmembrane mimetic peptides. Peptides of this group above a specific hydrophobicity threshold insert spontaneously into membranes and have antibacterial activity at micromolar concentrations. While investigating the molecular basis of biofilm resistance to peptides, we found that the anionic alginate polysaccharide induces conformational changes in the most hydrophobic of these peptides typically associated with insertion of such peptides into membrane environments [Chan et al., J. Biol. Chem. (2004) vol. 279, pp. 38749-38754]. Through a combination of experiments measuring release of the fluorescent dye calcein from phospholipid vesicles, peptide interactions with vesicles in the presence and absence of alginate, and affinity of peptides for alginate as a function of net peptide core hydrophobicity, we show here that alginate offers a microenvironment that provides a protective mechanism for the encased bacteria by both binding and promoting the self-association of the CAPs. The overall results indicate that hydrophilic alginate polymers contain a significant hydrophobic compartment, and behave as an 'auxiliary membrane' for bacteria, thus identifying a unique protective role for biofilm exopolysaccharide matrices.
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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 | 0.001 | 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".