Detecting low concentration bacterial cells in complex media using a microchip-based flow cytometer

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DOIResolve DOI: http://doi.org/10.1016/j.snb.2014.06.046
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TypeArticle
Journal titleSensors and Actuators, B: Chemical
ISSN0925-4005
Volume202
Pages10511057; # of pages: 7
SubjectBacteria detection; Microcytometer; Real-world samples; Food safety
AbstractRapid detection of pathogenic bacteria in real-world samples, in which low concentration target bacteria usually coexist with a large quantity of interfering particles, is very important in many areas related to public health. In this study, we present our recent efforts in detecting low concentration bacteria in complex media that contain interfering particles and background noise using a microchip-based flow cytometer (i.e., microcytometer). To achieve this goal, low concentration 1.00 μm YG fluorescent beads, model particles for bacteria, were first detected in the presence of both a great number of polystyrene beads and fluorescence background noise using a microcytometer developed in this study. The microcytometer was further used to detect low concentrations of FITC labeled bacteria E. coli DH5α in the presence of a large quantity of interfering beads and FITC fluorescence background noise. We show that the FITC labeled E. coli DH5α cells at concentrations as low as 431 cells/mL were detected by the microcytometer with efficiencies of over 86% in complex media that contained high concentration (i.e., 4.89 × 10 7 particles/mL) blank interfering beads (d = 4.50 μm) with 0.5 μM FITC fluorescein as fluorescence background. This translates to detection of one target bacterial cell from approximately 1 × 105 interfering particles. Unlike other reports, this is the first report that studied detection of low concentration bacteria by a microcytometer in complex sample media. The outstanding detection performances of the microcytometer demonstrated by this study strongly suggest that microcytometers are indeed very promising candidate for detection of pathogenic bacteria in real-world samples.
Publication date
LanguageEnglish
AffiliationInformation and Communication Technologies; National Research Council Canada
Peer reviewedYes
NPARC number21272794
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Record identifier51ef70c7-5c01-4d5a-b68d-2f768ccbff06
Record created2014-12-03
Record modified2016-05-09
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