Marine Bacteria, A Source for Alginolytic Enzyme to Disrupt Pseudomonas aeruginosa Biofilms
Bibliographic record
Abstract
Pseudomonas aeruginosa biofilms are typically associated with the chronic lung infection of cystic fibrosis (CF) patients and represent a major challenge for treatment. This opportunistic bacterial pathogen secretes alginate, a polysaccharide that is one of the main components of its biofilm. Targeting this major biofilm component has emerged as a tempting therapeutic strategy for tackling biofilm-associated bacterial infections. The enormous potential in genetic diversity of the marine microbial community make it a valuable resource for mining activities responsible for a broad range of metabolic processes, including the alginolytic activity responsible for degrading alginate. A collection of 36 bacterial isolates were purified from marine water based on their alginolytic activity. These isolates were identified based on their 16S rRNA gene sequences. Pseudoalteromonas sp. 1400 showed the highest alginolytic activity and was further confirmed to produce the enzyme alginate lyase. The purified alginate lyase (AlyP1400) produced by Pseudoalteromonas sp. 1400 showed a band of 23 KDa on a protein electrophoresis gel and exhibited a bifunctional lyase activity for both poly-mannuronic acid and poly-glucuronic acid degradation. A tryptic digestion of this gel band analyzed by liquid chromatography-tandem mass spectrometry confirmed high similarity to the alginate lyases in polysaccharide lyase family 18. The purified alginate lyase showed a maximum relative activity at 30 °C at a slightly acidic condition. It decreased the sodium alginate viscosity by over 90% and reduced the P. aeruginosa (strain PA14) biofilms by 69% after 24 h of incubation. The combined activity of AlyP1400 with carbenicillin or ciprofloxacin reduced the P. aeruginosa biofilm thickness, biovolume and surface area in a flow cell system. The present data revealed that AlyP1400 combined with conventional antibiotics helped to disrupt the biofilms produced by P. aeruginosa and can be used as a promising combinational therapeutic strategy.
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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) | 0.000 | 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".