Comparative Genomic Analysis of Streptococcus dysgalactiae subspecies dysgalactiae Isolated From Bovine Mastitis in China
Bibliographic record
Abstract
(SDSD) is one of the most prevalent pathogens causing bovine mastitis worldwide. However, there is a lack of comprehensive information regarding genetic diversity, complete profiles of virulence factors (VFs), and antimicrobial resistance (AMR) genes for SDSD associated with bovine mastitis in China. In this study, a total of 674 milk samples, including samples from 509 clinical and 165 subclinical mastitis cases, were collected from 17 herds in 7 provinces in China from November 2016 to June 2019. All SDSD isolates were included in phylogenetic analysis based on 16S rRNA and multi-locus sequence typing (MLST). In addition, whole genome sequencing was performed on 12 representative SDSD isolates to screen for VFs and AMR genes and to define pan-, core and accessory genomes. The prevalence of SDSD from mastitis milk samples was 7.57% (51/674). According to phylogenetic analysis based on 16S rRNA, 51 SDSD isolates were divided into 4 clusters, whereas based on MLST, 51 SDSD isolates were identified as 11 sequence types, including 6 registered STs and 5 novel STs (ST521, ST523, ST526, ST527, ST529) that belonged to 2 distinct clonal complexes (CCs) and 4 singletons. Based on WGS information, 108 VFs genes in 12 isolates were determined in 11 categories. In addition, 23 AMR genes were identified in 11 categories. Pan-, core and accessory genomes were composed of 2,663, 1,633 and 699 genes, respectively. These results provided a comprehensive profiles of SDSD virulence and resistance genes as well as phylogenetic relationships among mastitis associated SDSD in North China.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".