Genomic comparisons of Streptococcus suis serotype 9 strains recovered from diseased pigs in Spain and Canada
Bibliographic record
Abstract
Streptococcus suis is one of the most important bacterial pathogens in the porcine industry and also a zoonotic agent. Serotype 9 is becoming one of the most prevalent serotypes within the S. suis population in certain European countries. In the present study, serotype 9 strains isolated from a country where infection due to this serotype is endemic (Spain), were compared to those recovered from Canada, where this serotype is rarely isolated from diseased pigs. For comparison purposes, strains from Brazil and the only strain isolated from a human case, in Thailand, were also incorporated. Firstly, sequence types (STs) were obtained followed by detection of putative virulence factors. Phylogenetic trees were constructed using the non-recombinant single nucleotide polymorphisms from core genomes of tested strains. Most Spanish strains were either ST123 or ST125, whereas Canadian strains were highly heterogeneous. However, the distribution of putative virulence factors was similar in both groups of strains. The fact that ST16 strains harbored more putative virulence genes and shared greater similarity with the genome of human serotype 2 strains suggests that they present a higher zoonotic and virulence potential than those from Canada and Spain. More than 80% of the strains included in this study carried genes associated with resistance to tetracycline, lincosamides and macrolides. Serotype 9 strains may be nearly 400 years old and have evolved in parallel into 2 lineages. The rapid population expansion of dominant lineage 1 occurred within the last 40 years probably due to the rapid development of the porcine industry.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 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".