Genetic Diversity and Evolution of Salmonella enterica Serovar Enteritidis Strains with Different Phage Types
Bibliographic record
Abstract
Phage typing has been used for the epidemiological surveillance of Salmonella enterica serovar Enteritidis for over 2 decades. However, knowledge of the genetic and evolutionary relationships between phage types is very limited, making differences difficult to interpret. Here, single nucleotide polymorphisms (SNPs) identified from whole-genome comparisons were used to determine the relationships between some S. Enteritidis phage types (PTs) commonly associated with food-borne outbreaks in the United States. Emphasis was placed on the predominant phage types PT8, PT13a, and PT13 in North America. With >89,400 bp surveyed across 98 S. Enteritidis isolates representing 14 distinct phage types, 55 informative SNPs were discovered within 23 chromosomally anchored loci. To maximize the discriminatory and evolutionary partitioning of these highly homogeneous strains, sequences comprising informative SNPs were concatenated into a single combined data matrix and subjected to phylogenetic analysis. The resultant phylogeny allocated most S. Enteritidis isolates into two distinct clades (clades I and II) and four subclades. Synapomorphic (shared and derived) sets of SNPs capable of distinguishing individual clades/subclades were identified. However, individual phage types appeared to be evolutionarily disjunct when mapped to this phylogeny, suggesting that phage typing may not be valid for making phylogenetic inferences. Furthermore, the set of SNPs identified here represents useful genetic markers for strain differentiation of more clonal S. Enteritidis strains and provides core genotypic markers for future development of a SNP typing scheme with S. Enteritidis.
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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 | 0.000 | 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".