Comparative genomics study of Staphylococcus aureus isolated from cattle and humans reveals virulence patterns exclusively associated with bovine clinical mastitis strains
Bibliographic record
Abstract
Staphylococcus aureus causes nosocomial and intramammary infections in humans and cattle, respectively. A large number of virulence factors are thought to play important roles in the pathogenesis of this bacterium. Currently, genome-wide and data-analysis studies are being used to better understand its epidemiology. In this study, we conducted a genome wide comparison and phylogenomic analyses of S. aureus to find specific virulence patterns associated with clinical and subclinical mastitis strains in cattle and compare them with those of human origin. The presence/absence of key virulence factors such as adhesin, biofilm, antimicrobial resistance, and toxin genes, as well as the phylogeny and sequence type of the isolates were evaluated. A total of 248 genomes (27 clinical mastitis, 43 subclinical mastitis, 21 milk, 53 skin-related abscesses, 49 skin infections, and 55 pus from cellulitis) isolated from 32 countries were evaluated. We found that the cflA, fnbA, ebpS, spa, sdrC, coa, emp, vWF, atl, sasH, sasA, and sasF adhesion genes, as well as the aur, hglA, hglB, and hglC toxin genes were highly associated in clinical mastitis strains. The strains had diverse genetic origins (72 protein A and 48 sequence types with ST97, ST8 and ST152 being frequent in isolates from clinical mastitis, abscess, and skin infection, respectively). Further, our phylogenomic analyses suggested that zoonotic and/or zooanthroponotic transmission may have occurred. These findings contribute to a better understanding of S. aureus epidemiology and the relationships between adhesion mechanisms, biofilm formation, antimicrobial resistance, and toxins and could aid in the development of improved vaccines and strain genotyping methods.
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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 | 0.001 | 0.001 |
| 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".