Coagulase-negative staphylococci species affect biofilm formation of other coagulase-negative and coagulase-positive staphylococci
Bibliographic record
Abstract
Coagulase-negative staphylococci (CNS) are considered to be commensal bacteria in humans and animals, but are now also recognized as etiological agents in several infections, including bovine mastitis. Biofilm formation appears to be an important factor in CNS pathogenicity. Furthermore, some researchers have proposed that CNS colonization of the intramammary environment has a protective effect against other pathogens. The mechanisms behind the protective effect of CNS have yet to be characterized. The aim of this study was to evaluate the effect of CNS isolates with a weak-biofilm phenotype on the biofilm formation of other staphylococcal isolates. We selected 10 CNS with a weak-biofilm phenotype and 30 staphylococcal isolates with a strong-biofilm phenotype for this study. We measured biofilm production by individual isolates using a standard polystyrene microtiter plate assay and compared the findings with biofilm produced in mixed cultures. We confirmed the results using confocal microscopy and a microfluidic system with low shear force. Four of the CNS isolates with a weak-biofilm phenotype (Staphylococcus chromogenes C and E and Staphylococcus simulans F and H) significantly reduced biofilm formation in approximately 80% of the staphylococcal species tested, including coagulase-positive Staphylococcus aureus. The 4 Staph. chromogenes and Staph. simulans isolates were also able to disperse pre-established biofilms, but to a lesser extent. We also performed a deferred antagonism assay and recorded the number of colony-forming units in the mixed-biofilm assays on differential or selective agar plates. Overall, CNS with a weak-biofilm phenotype did not inhibit the growth of isolates with a strong-biofilm phenotype. These results suggest that some CNS isolates can negatively affect the ability of other staphylococcal isolates and species to form biofilms via a mechanism that does not involve growth inhibition.
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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 | 0.001 |
| 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".