Rapid and ultra-sensitive detection of foodborne pathogens by using miniaturized microfluidic devices: a review. Issue 37 (7th September 2016) - Jiang, Yuqian; Zou, Shan; Cao, Xudong
Abstract : Identification and quantification of foodborne pathogens are becoming increasingly important to public health and food safety since the majority of foodborne illnesses and deaths are caused by pathogenic bacteria. Abstract : Identification and quantification of foodborne pathogens are becoming increasingly important to public health and food safety since the majority of foodborne illnesses and deaths are caused by pathogenic bacteria. Conventional methods for foodborne pathogen detection are time-consuming and laborious due to the requirement of a series of processes including cell enrichment, isolation and morphological identification. Therefore the demand for rapid, sensitive, inexpensive and convenient approaches to detect foodborne pathogenic bacteria has emerged in recent years. Among the new approaches, microfluidic chip-based detection has generated growing interest because of the miniaturized size, improved sensitivity and reduced detection time of the devices. In addition, the applications of nanomaterials and magnetic microbeads have further facilitated target recognition and signal transduction processes in microfluidic pathogen detection. The lab-on-a-chip technique has developed into an alternative to conventional methods to detect foodborne pathogens owing to its potentials to offer desired sensitivity and to respond in a short test time. Most recently, smartphones and 3-D printing technologies are attracting growing attention for enhanced detection performances. This paper reviews the most recent developments and trends in miniaturized microfluidic devices based on different recognition principles and signal amplification methods to detect foodborne pathogens. In particular, emphasis will be put on those that offer both rapid detection result turn-around and ultra-low detection limit of 10 2 to 10 3 cells per mL or even single-cell detection.