Comparative genome analysis of <i>Pasteurella multocida</i> strains of porcine origin
Bibliographic record
Abstract
Pasteurella multocida causes acute/chronic pasteurellosis in porcine, resulting in considerable economic losses globally. The draft genomes of two Indian strains NIVEDIPm17 (serogroup D) and NIVEDIPm36 (serogroup A) were sequenced. A total of 2182–2284 coding sequences (CDSs) were predicted along with 5–6 rRNA and 45–46 tRNA genes in the genomes. Multilocus sequence analysis and LPS genotyping showed the presence of ST50: genotype 07 and ST74: genotype 06 in NIVEDIPm17 and NIVEDIPm36, respectively. Pangenome analysis of 61 strains showed the presence of 1653 core genes, 167 soft core genes, 750 shell genes, and 1820 cloud genes. Analysis of virulence-associated genes in 61 genomes indicated the presence of nanB, exbB, exbD, ptfA, ompA, ompH, fur, plpB, fimA, sodA, sodC, tonB, and omp87 in all strains. The 61 genomes contained genes encoding tetracycline (54%), streptomycin (48%), sulphonamide (28%), tigecycline (25%), chloramphenicol (21%), amikacin (7%), cephalosporin (5%), and trimethoprim (5%) resistance. Multilocus sequence type revealed that ST50 was the most common (34%), followed by ST74 (26%), ST13 (24%), ST287 (5%), ST09 (5%), ST122 (3%), and ST07 (2%). Single-nucleotide polymorphism and core genome-based phylogenetic analysis clustered the strains into three major clusters. In conclusion, we described the various virulence factors, mobile genetic elements, and antimicrobial resistance genes in the pangenome of P. multocida of porcine origin, besides the rare presence of LPS genotype 7 in serogroup D.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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".