Genomic differences between sequence types 1 and 104 of Streptococcus suis Serotype 2
Bibliographic record
Abstract
Streptococcus suis is a zoonotic pathogen that can cause invasive infections in humans who are in close contact with infected pigs or contaminated pork-derived products. S. suis serotype 2 sequence type (ST) 1 strains are mostly associated with meningitis, whereas ST104 strains are mostly recovered from sepsis cases in humans. No data are available for comparison of the ST1 and ST104 strains at the genomic level, particularly concerning virulence-associated genes. Thus, genomic comparison of both STs was performed in this study.An ST1 isolate (ID26154) from the cerebrospinal fluid of a patient with meningitis and an ST104 isolate (ID24525) from the blood of a patient with sepsis were subjected to shotgun pyrosequencing using the 454 GS Junior System. Genomic comparison was conducted between the ST1 isolate and the ST104 isolate using the Artemis Comparison Tool (ACT) to identify the region of differences (RDs) between ST1 and ST104.Fifty-eight RDs were unique to the ST104 genome and were mainly involved in metabolism and cell functional activities, cell wall anchored proteins, bacteriophages and mobile genetic elements, ABC-type transporters, two-component signal transductions, and lantibiotic proteins. Some virulence genes mostly found in ST1 strains were also present in the ST104 genome. Whole-genome comparison is a powerful tool for identifying genomic region differences between different STs of S. suis serotype 2, leading to the identification of the molecular basis of virulence involved in the pathogenesis of the infection.
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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 | 0.001 |
| 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".