Comparative Genomic Analysis of Escherichia coli O157:H7 Isolated from Super-Shedder and Low-Shedder Cattle
Bibliographic record
Abstract
Cattle are the primary reservoir of the foodborne pathogen Escherichia coli O157:H7, with the concentration and frequency of E. coli O157:H7 shedding varying substantially among individual hosts. The term ''super-shedder" has been applied to cattle that shed ≥10(4) cfu E. coli O157:H7/g of feces. Super-shedders have been reported to be responsible for the majority of E. coli O157:H7 shed into the environment. The objective of this study was to determine if there are phenotypic and/or genotypic differences between E. coli O157:H7 isolates obtained from super-shedder compared to low-shedder cattle. From a total of 784 isolates, four were selected from low-shedder steers and six isolates from super-shedder steers (4.01-8.45 log cfu/g feces) for whole genome sequencing. Isolates were phage and clade typed, screened for substrate utilization, pH sensitivity, virulence gene profiles and Stx bacteriophage insertion (SBI) sites. A range of 89-2473 total single nucleotide polymorphisms (SNPs) were identified when sequenced strains were compared to E. coli O157:H7 strain Sakai. More non-synonymous SNP mutations were observed in low-shedder isolates. Pan-genomic and SNPs comparisons did not identify genetic segregation between super-shedder or low-shedder isolates. All super-shedder isolates and 3 of 4 of low-shedder isolates were typed as phage type 14a, SBI cluster 3 and SNP clade 2. Super-shedder isolates displayed increased utilization of galactitol, thymidine and 3-O-β-D-galactopyranosyl-D-arabinose when compared to low-shedder isolates, but no differences in SNPs were observed in genes encoding for proteins involved in the metabolism of these substrates. While genetic traits specific to super-shedder isolates were not identified in this study, differences in the level of gene expression or genes of unknown function may still contribute to some strains of E. coli O157:H7 reaching high densities within bovine feces.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".