Differing Populations of Endemic Bacteriophages in Cattle Shedding High and Low Numbers of Escherichia coli O157:H7 Bacteria in Feces
Bibliographic record
Abstract
The objectives of this study were to identify endemic bacteriophages (phages) in the feedlot environment and determine relationships of these phages to Escherichia coli O157:H7 from cattle shedding high and low numbers of naturally occurring E. coli O157:H7. Angus crossbred steers were purchased from a southern Alberta (Canada) feedlot where cattle excreting ≥ 10(4) CFU · g(-1) of E. coli O157:H7 in feces at a single time point were identified as supershedders (SS; n = 6), and cattle excreting <10(4) CFU · g(-1) of feces were identified as low shedders (LS; n = 5). Fecal pats or fecal grabs were collected daily from individual cattle for 5 weeks. E. coli O157:H7 in feces was detected by immunomagnetic separation and enumerated by direct plating, and phages were isolated using short- and overnight-enrichment methods. The total prevalence of E. coli O157:H7 isolated from feces was 14.4% and did not differ between LS and SS (P = 0.972). The total prevalence of phages was higher in the LS group (20.9%) than in the SS group (8.3%; P = 0.01). Based on genome size estimated by pulsed-field gel electrophoresis and morphology determined by transmission electron microscopy, T4- and O1-like phages of Myoviridae and T1-like phage of Siphoviridae were isolated. Compared to T1- and O1-like phages, T4-like phages exhibited a broad host range and strong lytic capability when targeting E. coli O157:H7. Moreover, the T4-like phages were more frequently isolated from feces of LS than SS, suggesting that endemic phages may impact the shedding dynamics of E. coli O157:H7 in cattle.
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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 | 0.000 |
| 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) | 0.000 | 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".