Two-stage label-free aptasensing platform for rapid detection of Cronobacter sakazakii in powdered infant formula

[Display omitted] •A two-stage label-free aptasensing platform was established to detect C. sakazakii.•This is the first report of an aptamer against C. sakazakii.•This assay can detect C. sakazakii in PIF at a 7.1×103 CFU/mL detection limit.•This assay requires only 30min or less to complete after...

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Bibliographic Details
Published in:Sensors and actuators. B, Chemical Chemical, 2017-02, Vol.239, p.94-99
Main Authors: Kim, Hong-Seok, Kim, Young-Ji, Chon, Jung-Whan, Kim, Dong-Hyeon, Yim, Jin-Hyeok, Kim, Hyunsook, Seo, Kun-Ho
Format: Article
Language:English
Subjects:
Actuators
Aptamer
Bacteria
Color
Cronobacter sakazakii
Gold nanoparticles
Infants
Nanoparticles
Optimization
Pathogens
Platforms
Powdered infant formula
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Summary:[Display omitted] •A two-stage label-free aptasensing platform was established to detect C. sakazakii.•This is the first report of an aptamer against C. sakazakii.•This assay can detect C. sakazakii in PIF at a 7.1×103 CFU/mL detection limit.•This assay requires only 30min or less to complete after sample enrichment.•This platform may be applicable for detecting other bacteria in real-world samples. Cronobacter sakazakii constitutes one of the most life-threatening foodborne pathogens in neonates, and is typically acquired via contaminated powdered infant formula. In this study, we developed a sensitive and convenient two-stage label-free aptasensing platform for colorimetric detection of C. sakazakii in powdered infant formula. In this system, C. sakazakii depletes aptamers from the test solution, and the reduction of aptamers induces aggregation of gold nanoparticles in salt, a process accompanied by a color change from red to purple. Under optimal conditions, C. sakazakii present in PIF at a concentration as low as 7.1×103 CFU mL−1 could be visually detected within 30min, with a linear range between 7.1×103 and 7.1×107 CFU mL−1. This novel assay provides new opportunities to detect bacteria in real-world samples.
ISSN:0925-4005
1873-3077
DOI:10.1016/j.snb.2016.07.173