Bacteriophage Isolation, Purification, and Characterization Techniques Against Ubiquitous Opportunistic Pathogens
Bibliographic record
Abstract
Healthcare-associated infection with "ESKAPE" pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species) is a global health crisis due to their extensive intrinsic antibiotic resistance and the ability to quickly acquire resistance determinants. Alternative treatment options are required to combat this crisis, and one possibility is the use of bacteriophages, or viruses that strictly infect the pathogenic bacteria. Currently, there is a renaissance in research and development into the use of phages to target multi-, extensively, and pan-resistant bacterial infections in humans, known as phage therapy. Using A. baumannii as an example, this article describes the isolation and purification of bacteriophages from sewage and soil samples, as well as general methods used in phage research such as precipitation of phages using polyethylene glycol, host range analysis, single-cell burst size determination, DNA extraction, and restriction fragment length polymorphism analysis. © 2022 National Research Council Canada. Current Protocols © 2022 Wiley Periodicals LLC. Reproduced with the permission of the Minister of Innovation, Science, and Industry. Basic Protocol 1: Isolation of bacteriophages against A. baumannii from sewage samples Alternate Protocol 1: Isolation of bacteriophages against A. baumannii from soil samples Support Protocol 1: Titering a bacteriophage stock Basic Protocol 2: Purification of phage to an axenic working stock Support Protocol 2: Liquid propagation of bacteriophage Basic Protocol 3: Host range analysis using the spot plate method Basic Protocol 4: Single burst size analysis Alternate Protocol 2: One-step growth curve Basic Protocol 5: Precipitation of bacteriophage using PEG 6000 Basic Protocol 6: DNA extraction from dsDNA bacteriophages Basic Protocol 7: Restriction fragment length polymorphism analysis of novel phage genomes.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.004 |
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".