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A fluorescence sensing array based on photonic crystals and RAA for sensitive and high-throughput detection of Salmonella in foods.
- Source :
-
LWT - Food Science & Technology . Oct2023, Vol. 188, pN.PAG-N.PAG. 1p. - Publication Year :
- 2023
-
Abstract
- Salmonella can cause serious foodborne diseases, which is a major concern for global public health. The sensitive and fast analysis of Salmonella is of importance for food safety. Herein, we developed a fluorescence sensing array based on photonic crystals (PCs) and recombinase-aided amplification (RAA) for high-throughput and high-sensitive analysis of Salmonella in foods. In this assay, RAA was employed for powerful amplification of the target DNA of Salmonella , and the generated dsDNA amplicon was embedded with nucleic acid dye SYBR Green I (SGI), emitting fluorescence. Furthermore, the fluorescence signal was physically enhanced by PCs array; meanwhile, the high-throughput and sensitive detection was realized by microplate reader. Because of the isothermal reaction and lyophilized regent of RAA, the proposed array possessed gentle operation and stable amplification performance. Besides, a small volume of loading samples with 2 μL was required on the PCs array for powerful fluorescence enhancement. Due to the synergistic signal amplification effect of RAA and photonic crystals, a low limit of detection (LOD) of 10 CFU/mL was achieved. Besides, the proposed array exhibited excellent performance with 100% accuracy in 20 spiked food samples. Therefore, the proposed method with the advantages of sensitivity and high throughput showed great application potential. • A fluorescent biosensor based on RAA and PCs was engineered for sensitive detection of Salmonella. • RAA with SYBR Green I has rapid, isothermal and cheap features without need of complex instruments. • PC array was employed to achieve rapid, simultaneous and high-throughput detection. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00236438
- Volume :
- 188
- Database :
- Academic Search Index
- Journal :
- LWT - Food Science & Technology
- Publication Type :
- Academic Journal
- Accession number :
- 173489148
- Full Text :
- https://doi.org/10.1016/j.lwt.2023.115333