Genomic comparison of two Streptococcus suis serotype 1 strains recovered from porcine and human disease cases
Bibliographic record
Abstract
Streptococcus suis is a zoonotic pathogen that causes invasive infections in humans and pigs. Although S. suis serotype 2 strains are most prevalent worldwide, other serotypes are also occasionally detected. Herein, we investigated the genomes of two S. suis serotype 1 strains belonging to the clonal complex 1, which were recovered from a human patient and an asymptomatic pig, respectively. The genomes differed in pathotype, virulence-associated gene (VAG) profile, minimum core genome (MCG) typing, and antimicrobial resistance gene content. The porcine serotype 1 strain was sequence type (ST) 237 and MCG1, whereas the human serotype 1 strain was ST105 and MCG ungroupable. Both strains were susceptible to several antibiotics consisting of β-lactams, fluoroquinolones, and chloramphenicol. Resistance to tetracycline, macrolides, and clindamycin was observed, which was attributed to the genes tet(O) and erm(B). Analysis of 99 VAG revealed Hhly3, NisK, NisR, salK/salR, srtG, virB4, and virD4 were absent in both serotype 1. However, the porcine strain lacked sadP (Streptococcal adhesin P), whereas the human strain harbored sadP1. Phylogenetic analysis revealed that human S. suis ST105 strains from Vietnam were genetically the closest to the human serotype 1 strain, whereas porcine S. suis ST11 strains from China and Thailand were genetically the closest to the porcine strain.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".