4.7 Article

Dual-mode of magnetic assisted Au@Ag SERS tags and cationic conjugated UCNPs for qualitative and quantitative analysis of multiple foodborne pathogens

期刊

SENSORS AND ACTUATORS B-CHEMICAL
卷 344, 期 -, 页码 -

出版社

ELSEVIER SCIENCE SA
DOI: 10.1016/j.snb.2021.130305

关键词

Surface-enhanced Raman scattering; Upconversion nanoparticles; Bacteria; Chemometrics algorithm; Milk

资金

  1. Jiangsu Agricultural Science and Technology Innovation Fund [CX(20)2005]
  2. Jiangsu Provincial Key Research and Development Program [BE2020379]

向作者/读者索取更多资源

A new dual-mode optical-nano-sensor was developed to effectively isolate, discriminate, and inactivate multiple foodborne pathogens by utilizing magnetic SERS tags and functionalized upconversion nanoparticles. This sensor can rapidly and simply detect and kill bacteria in contaminated food, contributing to food safety monitoring.
A new dual-mode optical-nano-sensor was designed to effectively isolate, discriminate and inactivate multiple foodborne pathogens through the combined effort of magnetic SERS tags and functionalized upconversion nanoparticles. The positively charged quaternary ammonium salt (QAS) functionalized upconversion nanoparticles (UCNPs@QAS) were used as a fluorescent probe for the analysis of total bacteria count and inactivation of bacteria, and 4-mercaptophenylboronic acid (4-MPBA) modified magnetic Au@Ag NPs (MAu@Ag@MPBA) were applied as a SERS tag for isolation and classification of bacteria. Various types of bacteria can be captured by UCNPs@QAS through electrostatic interactions and by MAu@Ag@MPBA via the reversible recognition interaction of a boronic acid group of 4-MPBA and peptidoglycan from bacteria simultaneously. And then the formed complex structural assemblies were isolated rapidly from the sample matrix by employing the magnetic force for fast and simple dual-model optical detection. In addition, the novel biosensor was successfully applied to discriminate and detect Escherichia coli, Salmonella, Staphylococcus aureus, and their mixture in contaminated milk with the classification rate of 97.2-100 %. The proposed multi-functional nano-platform was able to sensitively capture, detect, and kill foodborne pathogens in a complex system, which could be deployed successfully towards the monitoring of food safety.

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