Genome Comparison and Phylogenetic Analysis of Mastitis-Related Staphylococci with a Focus on Adhesion, Biofilm, and Regulatory-Related Genes
Bibliographic record
Abstract
Abstract Bovine mastitis is the costliest diseases on dairy farms and is caused by different Staphylococcus species. However, staphylococci associated with clinical mastitis infections are different from subclinical ones, indicating a complex mechanism related to bovine mastitis pathogenesis. Here, we performed genomic analyses to determine the prevalence of adhesion, biofilm, and regulatory genes in 478 staphylococcal spp. associated with clinical and subclinical mastitis deposited in public databases. The most prevalent adhesin genes were the ebpS, atl, pls, sasH and sasF genes found in both clinical and subclinical isolates. However, the ebpS gene is absent in subclinical isolates of Staphylococcus arlettae, S. succinus, S. sciuri, S. equorun, S. galinarum, and S. saprophyticus. In constrast, the coa, eap, emp, efb, and vWbp genes were present more frequently in clinical mastitis isolates and highly correlated with the presence of the icaABCD and icaR biofilm genes. We also revealed that many adhesins, biofilm, and associated regulatory genes were potentially horizontally disseminated between clinical and subclinical isolates. Taken together, our results indicate that several adhesins, biofilm, and regulatory-related genes have been overlooked in previous studies and that these virulence factors may arise in staphylococcal species not generally associated with clinical mastitis by horizontal gene transfer.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.001 | 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".