Characterization and genome analysis of a broad host range lytic phage vB_SenS_TUMS_E19 against <i>Salmonella enterica</i> and its efficiency evaluation in the liquid egg
Bibliographic record
Abstract
Salmonella enterica serovars are zoonotic bacterial that cause foodborne enteritis. Due to bacteria’s antibiotic resistance, using bacteriophages for biocontrol and treatment is a new therapeutic approach. In this study, we isolated, characterized, and analyzed the genome of vB_SenS_TUMS_E19 (E19), a broad host range Salmonella bacteriophage, and evaluated the influence of E19 on liquid eggs infected with Salmonella enterica serovar Enteritidis. Transmission electron microscopy showed that the isolated bacteriophage had a siphovirus morphotype. E19 showed rapid adsorption (92% in 5 min), a short latent period (18 min), a large burst size (156 PFU per cell), and a broad host range against different Salmonella enterica serovars. Whole-genome sequencing analysis indicated that the isolated phage had a 42 813 bp long genome with 49.8% G + C content. Neither tRNA genes nor those associated with antibiotic resistance, virulence factors, or lysogenic formation were detected in the genome. The efficacy of E19 was evaluated in liquid eggs inoculated with S. Enteritidis at 4 and 25 °C, and results showed that it could effectively eradicate S. Enteritidis in just 30 min and prevented its growth up to 72 h. Our findings indicate that E19 can be an alternative to a preservative to control Salmonella in food samples and help prevent and treat salmonellosis.
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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 | 0.000 |
| 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) | 0.000 | 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".