Salmonella Enteritidis Bacteriophages Isolated from Kenyan Poultry Farms Demonstrate Time-Dependent Stability in Environments Mimicking the Chicken Gastrointestinal Tract
Bibliographic record
Abstract
Multi-drug resistant (MDR) Salmonella enterica Enteritidis is one of the major causes of foodborne illnesses worldwide. This non-typhoidal Salmonella (NTS) serovar is mainly transmitted to humans through poultry products. Bacteriophages (phages) offer an alternative to antibiotics for reducing the incidence of MDR NTS in poultry farms. Phages that survive the harsh environment of the chicken gastrointestinal tract (cGIT), which have low pH, high temperatures, and several enzymes, may have a higher therapeutic or prophylactic potential. In this study, we analysed the stability of 10 different S. Enteritidis phages isolated from Kenyan poultry farms in different pH-adjusted media, incubation temperatures, as well as simulated gastric and intestinal fluids (SGF and SIF, respectively). Furthermore, their ability to persist in water sources available in Kenya, including river, borehole, rain and tap water, was assessed. All phages were relatively stable for 12 h at pHs ranging from 5 to 9 and at temperatures ranging from 25 °C to 42 °C. At pH 3, a loss in viral titre of up to three logs was observed after 3 h of incubation. In SGF, phages were stable for 20 min, after which they started losing infectivity. Phages were relatively stable in SIF for up to 2 h. The efficacy of phages to control Salmonella growth was highly reduced in pH 2- and pH 3-adjusted media and in SGF at pH 2.5, but less affected in SIF at pH 8. River water had the most significant detrimental effect on phages, while the other tested waters had a limited impact on the phages. Our data suggest that these phages may be administered to chickens through drinking water and may survive cGIT to prevent salmonellosis in poultry.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.027 | 0.001 |
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".