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Issue 45, 2016
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One-pot bioinspired synthesis of all-inclusive protein–protein nanoflowers for point-of-care bioassay: detection of E. coli O157:H7 from milk

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Abstract

Protein–protein conjugates play a vital role in bioassays with their inherent functions of biological recognition and signal amplification. Herein, a one-pot green method for synthesis of all-inclusive protein–protein nanoflowers has been developed. The protein–protein nanoflowers integrate both essential functions of biological recognition and signal amplification, and they were used as ideal signal labels for the sensitive point-of-care detection of Escherichia coli O157:H7. Especially noteworthy, the prepared Con A–invertase–CaHPO4 hybrid nanoflowers simultaneously loaded sufficient invertase and enhanced the activity of the immobilized invertase, which fits well with the requirements of signal labels for bioassays. Due to the conversion of sucrose to glucose by invertase, Con A–invertase–CaHPO4 hybrid nanoflowers were successfully used for the reliable point-of-care detection of food pathogens by a personal glucose meter. The presented approach successfully resolved the bottleneck in preparing protein–protein conjugate-based signal labels for bioassays using enzyme-based signal amplification strategies, which holds great promise to develop on-demand protein–protein conjugates for a variety of applications extending from biosensors and biomedicine to energy, environmental monitoring and remediation.

Graphical abstract: One-pot bioinspired synthesis of all-inclusive protein–protein nanoflowers for point-of-care bioassay: detection of E. coli O157:H7 from milk

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Publication details

The article was received on 30 Aug 2016, accepted on 18 Oct 2016 and first published on 19 Oct 2016


Article type: Paper
DOI: 10.1039/C6NR06870G
Citation: Nanoscale, 2016,8, 18980-18986
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    One-pot bioinspired synthesis of all-inclusive protein–protein nanoflowers for point-of-care bioassay: detection of E. coli O157:H7 from milk

    R. Ye, C. Zhu, Y. Song, J. Song, S. Fu, Q. Lu, X. Yang, M. Zhu, D. Du, H. Li and Y. Lin, Nanoscale, 2016, 8, 18980
    DOI: 10.1039/C6NR06870G

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