A fluorescent dual aptasensor for the rapid and sensitive onsite detection of E. coli O157:H7 and its validation in various food matrices

The speedy analysis of food products remains a keen area of concern; thus, rapid, highly efficient and robust on-site detection platforms are essential. Globally, Escherichia coli O157:H7 is the most common organism associated with food borne illness. The present study focuses on the development of...

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Veröffentlicht in:New journal of chemistry 2018, Vol.42 (13), p.187-1817
Hauptverfasser: Renuka, R. M, Achuth, J, Chandan, H. R, Venkataramana, M, Kadirvelu, K
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Sprache:eng
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Zusammenfassung:The speedy analysis of food products remains a keen area of concern; thus, rapid, highly efficient and robust on-site detection platforms are essential. Globally, Escherichia coli O157:H7 is the most common organism associated with food borne illness. The present study focuses on the development of a rapid onsite E. coli O157:H7 detection platform. Accordingly, target specific ssDNA aptamers are generated using whole cell-SELEX, where the highly reactive aptamers (EcoR1 and EcoR2) with the lowest dissociation constants ( K d ) are further biotin tagged (EcoR1) and fluorescent labelled (EcoR2). Subsequently, the biotin-labelled aptamers are immobilized onto silane-glutaraldehyde-functionalized glass slides, which act as capturing ligands, and the QD-labelled aptamers act as revealing probes. The detection limit of the platform is found to be 10 2 CFU mL −1 within 15 min, and no cross-reactivity towards other related pathogens is observed. The developed assay is further evaluated in complex food matrices to determine the presence of E. coli O157:H7, where the results are found to be consistent with those of the conventional methods with a recovery percentage ranging from 76% to 91%. In conclusion, the developed method is promising for application in real-time food sample monitoring. The speedy analysis of food products remains a keen area of concern; thus, rapid, highly efficient and robust on-site detection platforms are essential.
ISSN:1144-0546
1369-9261
DOI:10.1039/c8nj00997j