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Research progress on bacteriophage-based biosensors for foodborne pathogens detection
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Hao HU1, 2, Li-Li ZHANG1, 2, Xiang-Mu YANG1, 3, Shao-Wen GUO1, 4, Jing WANG1, 5, Ran WANG1, 2, 5, He-Ye WANG1, *
Journal of Food Safety & Quality | 2025, 16(12) : 116 - 125
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Journal of Food Safety & Quality | 2025, 16(12): 116-125
Highlight: Analysis and Monitoring of Toxic and Harmful Substances in Food
Research progress on bacteriophage-based biosensors for foodborne pathogens detection
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Hao HU1, 2, Li-Li ZHANG1, 2, Xiang-Mu YANG1, 3, Shao-Wen GUO1, 4, Jing WANG1, 5, Ran WANG1, 2, 5, He-Ye WANG1, *
Affiliations
  • 1 Jiangsu Key Laboratory for Food Quality and Safety-State Key Laboratory Cultivation Base, Ministry of Science and Technology, Institute of Food Safety and Nutrition, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China
  • 2 College of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China
  • 3 College of Veterinary Medicine, Yangzhou University, Yangzhou 225009, China
  • 4 College of Animal Science and Technology, Guangxi University, Nanning 530004, China
  • 5 College of Veterinary Medicine, Nanjing Agricultural University, Nanjing 210095, China
Published: 2025-06-25 doi: 10.19812/j.cnki.jfsq11-5956/ts.20250324001
Outline
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Foodborne pathogens contamination is a major global challenge in the field of food safety. Traditional detection methods are limited by issues such as time-consuming processes and complex operational requirements. In recent years, bacteriophage-based biosensors have emerged as a promising research focus for the detection of foodborne pathogens due to their high specificity, sensitivity, and rapid detection capabilities. Bacteriophages, acting as biological recognition elements, can specifically bind to target bacteria and achieve rapid detection through signal transduction methods such as optical, electrochemical and magnetic signals. This review systematically summarized the research progress in bacteriophage-based biosensors for foodborne pathogenic bacteria detection, with a particular focus on the design principles, technical advantages and application prospects of optical biosensors, electrochemical biosensors, magnetic biosensors, and multimodal/multifunctional integrated sensors. These sensors show great potential for applications in food safety, environmental monitoring and clinical diagnostics. In the future, as bacteriophage resources become more abundant and with the advancement and integration of bioinformatics and artificial intelligence technologies, bacteriophage-based biosensors are expected to enable the development of more efficient detection tools and large-scale applications. These advancements will provide robust technical support for food safety, environmental monitoring and clinical diagnostics, holding significant research and societal value.

foodborne pathogens  /  bacteriophage  /  biosensors  /  rapid detection  /  food safety
Hao HU, Li-Li ZHANG, Xiang-Mu YANG, Shao-Wen GUO, Jing WANG, Ran WANG, He-Ye WANG. Research progress on bacteriophage-based biosensors for foodborne pathogens detection[J]. Journal of Food Safety & Quality, 2025 , 16 (12) : 116 -125 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20250324001
Year 2025 volume 16 Issue 12
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Article Info
doi: 10.19812/j.cnki.jfsq11-5956/ts.20250324001
  • Receive Date:2025-03-24
  • Online Date:2026-01-13
  • Published:2025-06-25
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  • Received:2025-03-24
Funding
Affiliations
    1 Jiangsu Key Laboratory for Food Quality and Safety-State Key Laboratory Cultivation Base, Ministry of Science and Technology, Institute of Food Safety and Nutrition, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China
    2 College of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China
    3 College of Veterinary Medicine, Yangzhou University, Yangzhou 225009, China
    4 College of Animal Science and Technology, Guangxi University, Nanning 530004, China
    5 College of Veterinary Medicine, Nanjing Agricultural University, Nanjing 210095, China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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