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Lateral flow assay-based bacterial detection using engineered cell wall binding domains of a phage endolysin

The development of a cost-effective and efficient bacterial detection assay is essential for diagnostic fields, particularly in resource-poor settings. Although antibodies have been widely used for bacterial capture, the production of soluble antibodies is still expensive and time-consuming. Here, w...

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Bibliographic Details
Published in:Biosensors & bioelectronics 2017-10, Vol.96, p.173-177
Main Authors: Kong, Minsuk, Shin, Joong Ho, Heu, Sunggi, Park, Je-Kyun, Ryu, Sangryeol
Format: Article
Language:English
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Summary:The development of a cost-effective and efficient bacterial detection assay is essential for diagnostic fields, particularly in resource-poor settings. Although antibodies have been widely used for bacterial capture, the production of soluble antibodies is still expensive and time-consuming. Here, we developed a nitrocellulose-based lateral flow assay using cell wall binding domains (CBDs) from phage as a recognition element and colloidal gold nanoparticles as a colorimetric signal for the detection of a model pathogenic bacterium, Bacillus cereus (B. cereus). To improve conjugation efficiency and detection sensitivity, cysteine-glutathione-S-transferase-tagged CBDs and maltose-binding protein-tagged CBDs were produced in Escherichia coli (E. coli) and incorporated in our assays. The sensitivity of the strip to detect B. cereus was 1×104 CFU/mL and the overall assay time was 20min. The assay showed superior results compared to the antibody-based approach, and did not show any significant cross-reactivity. This proof of concept study indicates that the lateral flow assay using engineered CBDs hold considerable promise as simple, rapid, and cost-effective biosensors for whole cell detection. •The cell wall binding domain (CBD) of endolysin was tested for whole cell detection.•A lateral flow assay using CBD as a recognition element was developed.•The assay showed promising results for whole cell detection.
ISSN:0956-5663
1873-4235
DOI:10.1016/j.bios.2017.05.010