Magnetic plasmonic particles for SERS-based bacteria sensing: A review
Chaoguang Wang,
Marco M. Meloni,
Xuezhong Wu,
Ming Zhuo,
Taigang He,
Junfeng Wang,
Chongwen Wang,
Peitao Dong
Affiliations
Chaoguang Wang
College of Mechatronics Engineering and Automation, National University of Defense Technology, Changsha 410073, China
Marco M. Meloni
Molecular and Clinical Sciences Research Institute, St George’s, University of London, London SW17 0RE, UK
Xuezhong Wu
College of Mechatronics Engineering and Automation, National University of Defense Technology, Changsha 410073, China
Ming Zhuo
College of Mechatronics Engineering and Automation, National University of Defense Technology, Changsha 410073, China
Taigang He
Molecular and Clinical Sciences Research Institute, St George’s, University of London, London SW17 0RE, UK
Junfeng Wang
College of Mechatronics Engineering and Automation, National University of Defense Technology, Changsha 410073, China
Chongwen Wang
Key Laboratory of New Molecular diagnosis technologies for infectious diseases, Institute of Radiation Medicine, Academy of military medical sciences, Beijing 100850, China
Peitao Dong
College of Mechatronics Engineering and Automation, National University of Defense Technology, Changsha 410073, China
This review describes recent advances in the use of magnetic-plasmonic particles (MPPs) for bacteria detection by Surface-Enhanced Raman Scattering (SERS). Pathogenic bacteria pollution has always been a major threat to human health and safety. SERS spectroscopy has emerged as a powerful and promising technique for sensitive and selective detection of pathogen bacteria. MPPs are considered as a versatile SERS platform for their excellent plasmonic properties and good magnetic responsiveness. Improved preparation method and typical characterization technique of MPPs are introduced, focusing on the thin and continuous metallic shell covering process. Consequently, the SERS-based sensing methods for bacteria identification were discussed, including the label-free and label-based methods. Finally, an overview of the current state of the field and our perspective on future development directions are given.
