Rapid and Accurate Detection of Bacteriophage Activity against<i>Escherichia coli</i>O157:H7 by Propidium Monoazide Real-Time PCR
Bibliographic record
Abstract
Conventional methods to determine the efficacy of bacteriophage (phage) for biocontrol of E. coli require several days, due to the need to culture bacteria. Furthermore, cell surface-attached phage particles may lyse bacterial cells during experiments, leading to an overestimation of phage activity. DNA-based real-time quantitative polymerase chain reaction (qPCR) is a fast, sensitive, and highly specific means of enumerating pathogens. However, qPCR may underestimate phage activity due to its inability to distinguish viable from nonviable cells. In this study, we evaluated the suitability of propidium monoazide (PMA), a microbial membrane-impermeable dye that inhibits amplification of extracellular DNA and DNA within dead or membrane-compromised cells as a means of using qPCR to identify only intact E. coli cells that survive phage exposure. Escherichia coli O157:H7 strain R508N and 4 phages (T5-like, T1-like, T4-like, and O1-like) were studied. Results compared PMA-qPCR and direct plating and confirmed that PMA could successfully inhibit amplification of DNA from compromised/damaged cells E. coli O157:H7. Compared to PMA-qPCR, direct plating overestimated (P < 0.01) phage efficacy as cell surface-attached phage particles lysed E. coli O157:H7 during the plating process. Treatment of samples with PMA in combination with qPCR can therefore be considered beneficial when assessing the efficacy of bacteriophage for biocontrol of E. coli O157:H7.
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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 | 0.001 | 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".