Detection and discrimination of pathogenic bacteria with nanomaterials-based optical biosensors: A review

被引:49
作者
Lin, Xiaodong [1 ]
Zhao, Minyang [2 ]
Peng, Tao [1 ]
Zhang, Pan [3 ]
Shen, Ren [3 ]
Jia, Yanwei [1 ,3 ]
机构
[1] Zhuhai UM Sci & Technol Res Inst, Zhuhai, Peoples R China
[2] Sun Yat Sen Univ, Affiliated Hosp 1, Precis Med Inst, Guangzhou, Peoples R China
[3] Univ Macau, Inst Microelect, State Key Lab Analog & Mixed Signal VLSI, Macau, Peoples R China
关键词
Nanomaterials (NMs); Optical biosensors; Pathogenic bacteria; Bacterial detection; Bacterial discrimination; COLORIMETRIC SENSOR ARRAY; GRAM-NEGATIVE BACTERIA; CARBON DOTS; QUANTUM DOTS; ULTRASENSITIVE DETECTION; GOLD NANOPARTICLES; FLUORESCENT IMMUNOASSAY; SALMONELLA-TYPHIMURIUM; STAPHYLOCOCCUS-AUREUS; SILVER NANOPARTICLES;
D O I
10.1016/j.foodchem.2023.136578
中图分类号
O69 [应用化学];
学科分类号
081704 ;
摘要
Pathogenic bacteria can pose a great threat to food safety and human health. It is therefore imperative to develop a rapid, portable, and sensitive determination and discrimination method for pathogenic bacteria. Over the past few years, various nanomaterials (NMs) have been employed as desirable nanoprobes because they possess extraordinary properties that can be used for optical signal enabled detection and identification of bacteria. By means of modification, NMs can, depending on different mechanisms, sense targets directly or indirectly, which then provides an essential support for the detection and differentiation of pathogenic bacteria. In this review, recent application of NMs-based optical biosensors for food safety bacterial detection and discrimination is performed, mainly in but not limited to noble metal NMs, fluorescent NMs, and point-of-care testing (POCT). This review also focuses on future trends in bacterial detection and discrimination, and machine learning in performing intelligent rapid detection and multiple accurate identification of bacteria.
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页数:13
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