Journal article
10-minute assay for detecting Escherichia coli O157:H7 in ground beef samples using piezoelectric-excited millimeter-size cantilever sensors
Journal of food protection, v 70(7), pp 1670-1677
Jul 2007
PMID: 17685341
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
We detected Escherichia coli O157:H7 (EC) at approximately 10 cells per ml in spiked ground beef samples in 10 min using piezoelectric-excited millimeter-size cantilever (PEMC) sensors. The composite PEMC sensors have a sensing area of 2 mm2 and are prepared by immobilizing a polyclonal antibody specific to EC on the sensing surface. Ground beef (2.5 g) was spiked with EC at 10 to 10,000 cells per ml in phosphate-buffered saline (PBS). One milliliter of supernatant was removed from the blended samples and used to perform the detection experiments. The total resonant frequency change obtained for the inoculated samples was 138 +/- 9, 735 +/- 23, 2,603 +/- 51, and 7,184 +/- 606 Hz, corresponding to EC concentrations of 10, 100, 1,000, and 10,000 cells per ml, respectively. EC was detected in the sample solution within the first 10 min. The responses of the sensor to positive, negative, and buffer controls were 36 +/- 6, 27 +/- 2, and 2 +/- 7 Hz, respectively. Verification of EC attachment was confirmed by low-pH buffer release (PBS-HCl, pH 2.2), microscopy, and second antibody EC binding postdetection. The results indicate that PEMC sensors can reliably detect EC at less than 10 cells per ml in 10 min without sample preparation and with label-free reagents.
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Details
- Title
- 10-minute assay for detecting Escherichia coli O157:H7 in ground beef samples using piezoelectric-excited millimeter-size cantilever sensors
- Creators
- David Maraldo - Drexel UniversityRaj Mutharasan - Drexel University
- Publication Details
- Journal of food protection, v 70(7), pp 1670-1677
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Chemical and Biological Engineering
- Web of Science ID
- WOS:000247849900017
- Scopus ID
- 2-s2.0-34447558536
- Other Identifier
- 991019170974004721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Biotechnology & Applied Microbiology
- Food Science & Technology