Standardization of the Agar Plate Method for Bacteriophage Production
The growing threat of antimicrobial resistance (AMR), exacerbated by the COVID-19 pandemic, highlights the urgent need for alternative treatments such as bacteriophage (phage) therapy. Phage therapy offers a targeted approach to combat bacterial infections, particularly those resistant to convention...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-12-01
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| Series: | Antibiotics |
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| Online Access: | https://www.mdpi.com/2079-6382/14/1/2 |
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| author | Su Jin Jo Young Min Lee Kevin Cho Seon Young Park Hyemin Kwon Sib Sankar Giri Sung Bin Lee Won Joon Jung Jae Hong Park Mae Hyun Hwang Da Sol Park Eun Jae Park Sang Wha Kim Jin Woo Jun Sang Guen Kim Ji Hyung Kim Se Chang Park |
| author_facet | Su Jin Jo Young Min Lee Kevin Cho Seon Young Park Hyemin Kwon Sib Sankar Giri Sung Bin Lee Won Joon Jung Jae Hong Park Mae Hyun Hwang Da Sol Park Eun Jae Park Sang Wha Kim Jin Woo Jun Sang Guen Kim Ji Hyung Kim Se Chang Park |
| author_sort | Su Jin Jo |
| collection | DOAJ |
| description | The growing threat of antimicrobial resistance (AMR), exacerbated by the COVID-19 pandemic, highlights the urgent need for alternative treatments such as bacteriophage (phage) therapy. Phage therapy offers a targeted approach to combat bacterial infections, particularly those resistant to conventional antibiotics. This study aimed to standardize an agar plate method for high-mix, low-volume phage production, suitable for personalized phage therapy. Plaque assays were conducted with the double-layer agar method, and plaque sizes were precisely measured using image analysis tools. Regression models developed with Minitab software established correlations between plaque size and phage production, optimizing production while minimizing resistance development. The resulting Plaque Size Calculation (PSC) model accurately correlated plaque size with inoculum concentration and phage yield, establishing specific plaque-forming unit (PFU) thresholds for optimal production. Using phages targeting pathogens such as <i>Escherichia</i>, <i>Salmonella</i>, <i>Staphylococcus</i>, <i>Pseudomonas</i>, <i>Chryseobacterium</i>, <i>Vibrio</i>, <i>Erwinia</i>, and <i>Aeromonas</i> confirmed the model’s accuracy across various conditions. The model’s validation showed a strong inverse correlation between plaque size and minimum-lawn cell clearing PFUs (MCPs; R² = 98.91%) and identified an optimal inoculum density that maximizes yield while minimizing the evolution of resistant mutants. These results highlight that the PSC model offers a standardized and scalable method for efficient phage production, which is crucial for personalized therapy and AMR management. Furthermore, its adaptability across different conditions and phages positions it as a potential standard tool for rapid and precise phage screening and propagation in both clinical and industrial settings. |
| format | Article |
| id | doaj-art-b706ce9eaee346f0b0074bac498c2407 |
| institution | Kabale University |
| issn | 2079-6382 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Antibiotics |
| spelling | doaj-art-b706ce9eaee346f0b0074bac498c24072025-01-24T13:18:28ZengMDPI AGAntibiotics2079-63822024-12-01141210.3390/antibiotics14010002Standardization of the Agar Plate Method for Bacteriophage ProductionSu Jin Jo0Young Min Lee1Kevin Cho2Seon Young Park3Hyemin Kwon4Sib Sankar Giri5Sung Bin Lee6Won Joon Jung7Jae Hong Park8Mae Hyun Hwang9Da Sol Park10Eun Jae Park11Sang Wha Kim12Jin Woo Jun13Sang Guen Kim14Ji Hyung Kim15Se Chang Park16Laboratory of Aquatic Biomedicine, College of Veterinary Medicine and Research Institute for Veterinary Science, Seoul National University, Seoul 08826, Republic of KoreaLaboratory of Aquatic Biomedicine, College of Veterinary Medicine and Research Institute for Veterinary Science, Seoul National University, Seoul 08826, Republic of KoreaLaboratory of Aquatic Biomedicine, College of Veterinary Medicine and Research Institute for Veterinary Science, Seoul National University, Seoul 08826, Republic of KoreaLaboratory of Aquatic Biomedicine, College of Veterinary Medicine and Research Institute for Veterinary Science, Seoul National University, Seoul 08826, Republic of KoreaDepartment of Microbiology and Molecular Biology, College of Bioscience and Biotechnology, Chungnam National University, Daejeon 34134, Republic of KoreaLaboratory of Aquatic Biomedicine, College of Veterinary Medicine and Research Institute for Veterinary Science, Seoul National University, Seoul 08826, Republic of KoreaLaboratory of Aquatic Biomedicine, College of Veterinary Medicine and Research Institute for Veterinary Science, Seoul National University, Seoul 08826, Republic of KoreaLaboratory of Aquatic Biomedicine, College of Veterinary Medicine and Research Institute for Veterinary Science, Seoul National University, Seoul 08826, Republic of KoreaLaboratory of Aquatic Biomedicine, College of Veterinary Medicine and Research Institute for Veterinary Science, Seoul National University, Seoul 08826, Republic of KoreaLaboratory of Aquatic Biomedicine, College of Veterinary Medicine and Research Institute for Veterinary Science, Seoul National University, Seoul 08826, Republic of KoreaLaboratory of Aquatic Biomedicine, College of Veterinary Medicine and Research Institute for Veterinary Science, Seoul National University, Seoul 08826, Republic of KoreaLaboratory of Aquatic Biomedicine, College of Veterinary Medicine and Research Institute for Veterinary Science, Seoul National University, Seoul 08826, Republic of KoreaLaboratory of Aquatic Biomedicine, College of Veterinary Medicine and Research Institute for Veterinary Science, Seoul National University, Seoul 08826, Republic of KoreaDepartment of Aquaculture, Korea National College of Agriculture and Fisheries, Jeonju 54874, Republic of KoreaLaboratory of Phage and Microbial Resistance, Department of Biological Sciences, Kyonggi University, Suwon 16227, Republic of KoreaDepartment of Food Science and Biotechnology, College of Bionano Technology, Gachon University, Seongnam 13120, Republic of KoreaLaboratory of Aquatic Biomedicine, College of Veterinary Medicine and Research Institute for Veterinary Science, Seoul National University, Seoul 08826, Republic of KoreaThe growing threat of antimicrobial resistance (AMR), exacerbated by the COVID-19 pandemic, highlights the urgent need for alternative treatments such as bacteriophage (phage) therapy. Phage therapy offers a targeted approach to combat bacterial infections, particularly those resistant to conventional antibiotics. This study aimed to standardize an agar plate method for high-mix, low-volume phage production, suitable for personalized phage therapy. Plaque assays were conducted with the double-layer agar method, and plaque sizes were precisely measured using image analysis tools. Regression models developed with Minitab software established correlations between plaque size and phage production, optimizing production while minimizing resistance development. The resulting Plaque Size Calculation (PSC) model accurately correlated plaque size with inoculum concentration and phage yield, establishing specific plaque-forming unit (PFU) thresholds for optimal production. Using phages targeting pathogens such as <i>Escherichia</i>, <i>Salmonella</i>, <i>Staphylococcus</i>, <i>Pseudomonas</i>, <i>Chryseobacterium</i>, <i>Vibrio</i>, <i>Erwinia</i>, and <i>Aeromonas</i> confirmed the model’s accuracy across various conditions. The model’s validation showed a strong inverse correlation between plaque size and minimum-lawn cell clearing PFUs (MCPs; R² = 98.91%) and identified an optimal inoculum density that maximizes yield while minimizing the evolution of resistant mutants. These results highlight that the PSC model offers a standardized and scalable method for efficient phage production, which is crucial for personalized therapy and AMR management. Furthermore, its adaptability across different conditions and phages positions it as a potential standard tool for rapid and precise phage screening and propagation in both clinical and industrial settings.https://www.mdpi.com/2079-6382/14/1/2bacteriophageagar plate methodstandardizationpersonalize therapy |
| spellingShingle | Su Jin Jo Young Min Lee Kevin Cho Seon Young Park Hyemin Kwon Sib Sankar Giri Sung Bin Lee Won Joon Jung Jae Hong Park Mae Hyun Hwang Da Sol Park Eun Jae Park Sang Wha Kim Jin Woo Jun Sang Guen Kim Ji Hyung Kim Se Chang Park Standardization of the Agar Plate Method for Bacteriophage Production Antibiotics bacteriophage agar plate method standardization personalize therapy |
| title | Standardization of the Agar Plate Method for Bacteriophage Production |
| title_full | Standardization of the Agar Plate Method for Bacteriophage Production |
| title_fullStr | Standardization of the Agar Plate Method for Bacteriophage Production |
| title_full_unstemmed | Standardization of the Agar Plate Method for Bacteriophage Production |
| title_short | Standardization of the Agar Plate Method for Bacteriophage Production |
| title_sort | standardization of the agar plate method for bacteriophage production |
| topic | bacteriophage agar plate method standardization personalize therapy |
| url | https://www.mdpi.com/2079-6382/14/1/2 |
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