Effects of growth conditions on biofilm formation by<i>Actinobacillus pleuropneumoniae</i>
Bibliographic record
Abstract
Biofilm formation is an important virulence trait of many bacterial pathogens. It has been reported in the literature that only two of the reference strains of the swine pathogen Actinobacillus pleuropneumoniae, representing serotypes 5b and 11, were able to form biofilm in vitro. In this study, we compared biofilm formation by the serotype 1 reference strain S4074 of A. pleuropneumoniae grown in five different culture media. We observed that strain S4074 of A. pleuropneumoniae is able to form biofilms after growth in one of the culture conditions tested brain heart infusion (BHI medium, supplier B). Confocal laser scanning microscopy using a fluorescent probe specific to the poly-N-acetylglucosamine (PGA) polysaccharide further confirmed biofilm formation. In accordance, biofilm formation was susceptible to dispersin B, a PGA hydrolase. Transcriptional profiles of A. pleuropneumoniae S4074 following growth in BHI-B, which allowed a robust biofilm formation, and in BHI-A, in which only a slight biofilm formation was observed, were compared. Genes such as tadC, tadD, genes with homology to autotransporter adhesins as well as genes pgaABC involved in PGA biosynthesis and genes involved in zinc transport were up-regulated after growth in BHI-B. Interestingly, biofilm formation was inhibited by zinc, which was found to be more present in BHI-A (no or slight biofilm) than in BHI-B. We also observed biofilm formation in reference strains representing serotypes 3, 4, 5a, 12 and 14 as well as in 20 of the 37 fresh field isolates tested. Our data indicate that A. pleuropneumoniae has the ability to form biofilms under appropriate growth conditions and transition from a biofilm-positive to a biofilm-negative phenotype was reversible.
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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 | 0.001 |
| 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".