Feces of feedlot cattle contain a diversity of bacteriophages that lyse non-O157 Shiga toxin-producing <i>Escherichia coli</i>
Bibliographic record
Abstract
This study aimed to isolate and characterize bacteriophages that lyse non-O157 Shiga toxin-producing Escherichia coli (STEC) from cattle feces. Of 37 non-O157 STEC-infecting phages isolated, those targeting O26 (AXO26A, AYO26A, AYO26B), O103 (AXO103A, AYO103A), O111 (AXO111A, AYO111A), O121 (AXO121A, AXO121B), and O145 (AYO145A, AYO145B) were further characterized. Transmission electron microscopy showed that the 11 isolates belonged to 3 families and 6 genera: the families Myoviridae (types rV5, T4, ViI, O1), Siphoviridae (type T5), and Podoviridae (type T7). Genome size of the phages as determined by pulsed-field gel electrophoresis ranged from 38 to 177 kb. Excluding phages AXO26A, AYO103A, AYO145A, and AYO145B, all other phages were capable of lysing more than 1 clinically important strain from serogroups of O26, O91, O103, O111, O113, O121, and O128, but none exhibited infectivity across all serogroups. Moreover, phages AYO26A, AXO121A, and AXO121B were also able to lyse 4 common phage types of STEC O157:H7. Our findings show that a diversity of non-O157 STEC-infecting phages are harbored in bovine feces. Phages AYO26A, AYO26B, AXO103A, AXO111A, AYO111A, AXO121A, and AXO121B exhibited a broad host range against a number of serogroups of STEC and have potential for the biocontrol of STEC in the environment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 teacher head, 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".