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Phage-based magnetic capture method as an aid for real-time recombinase polymerase amplification detection of Salmonella spp. in milk

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  • معلومة اضافية
    • بيانات النشر:
      Elsevier, 2024.
    • الموضوع:
      2024
    • Collection:
      LCC:Dairy processing. Dairy products
    • نبذة مختصرة :
      ABSTRACT: Salmonella is a major cause of foodborne diseases worldwide. Conventional rapid assays for detecting Salmonella in real samples often encounter severe matrix interference or detect a limited number of species of a genus, resulting in inaccurate detection. In this study, we developed a method that combined phage-based magnetic capture with real-time recombinase polymerase amplification (RPA) for the rapid, highly sensitive, and specific detection of Salmonella in milk with an ultra-low detection limit. The Felix O-1 phage-conjugated magnetic beads (O-1 pMBs) synthesized in this method showed excellent capture ability for Salmonella spp. and ideal specificity for non-Salmonella strains. After O-1 pMBs-based magnetic separation, the limit of detection of the real-time RPA assay was 50 cfu/mL in milk samples, which was significantly increased by a magnitude of 3 to 4 orders. The method exhibited a high sensitivity (compatibility) of 100% (14/14) for all tested Salmonella serotype strains and an ideal specificity (exclusivity) of 100% (7/7) for the tested non-Salmonella strains. The entire detection process, including Salmonella capture, DNA extraction, and real-time RPA detection, was completed within 1.5 h. Furthermore, milk samples spiked with 10 cfu/25 mL of Salmonella were detected positive after being cultured in buffered peptone water for only 3 h. Therefore, the proposed method could be an alternative for the rapid and accurate detection of Salmonella.
    • File Description:
      electronic resource
    • ISSN:
      0022-0302
    • Relation:
      http://www.sciencedirect.com/science/article/pii/S0022030224007781; https://doaj.org/toc/0022-0302
    • الرقم المعرف:
      10.3168/jds.2023-24237
    • الرقم المعرف:
      edsdoj.9dcdde62f08b42cd989966c7d344e3a5