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A novel fluorescence method for the rapid and effective detection of Listeria monocytogenes using aptamer-conjugated magnetic nanoparticles and aggregation-induced emission dots

Abstract

Fluorescent-based assays have been regarded as promising tools for specific, sensitive, rapid and effective detection of Listeria monocytogenes (L. monocytogenes). Nevertheless, the aggregation-caused quenching (ACQ) of emissions is always a big restriction in application for this strategy while the aggregation-induced emission (AIE) material avoids the shortcomings of traditional fluorescent materials perfectly. Herein, we propose an approach to achieve the desired detection performance using aptamer together with antibody-based dual recognition units containing magnetic enrichment and AIE characteristic. Aptamer-coupled magnetic beads are putted into use for the specific capture of L. monocytogenes. As the material of fluorescent signal readout, IgG-TPE-OH@BSA NPs are facile synthesized through 1-(4-Hydroxyphenyl)-1,2,2-triphenylethene (TPE-OH) encapsulated in bovine serum albumin (BSA) microspheres and conjugated rabbit Immunoglobulin G (IgG) antibodies on the surface. In the detection system, the fluorescence intensity of the IgG-TPE-OH@BSA NPs in the supernatant was monitored to avoid the fluorescence interference by the deposit after magnetic separation. The range on detection of L. monocytogenes is 10-106 cfu·mL-1, and the detection limit is as low as 102 cfu·mL-1 with good selectivity. On analyzing spiked samples, the recoveries ranged from 95.37 to 101.90 % without pre-enrichment. Overall, the detection method is rapid, sensitive, specific and efficient.

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Supplementary files

Article information


Submitted
25 Feb 2020
Accepted
25 Mar 2020
First published
25 Mar 2020

Analyst, 2020, Accepted Manuscript
Article type
Paper

A novel fluorescence method for the rapid and effective detection of Listeria monocytogenes using aptamer-conjugated magnetic nanoparticles and aggregation-induced emission dots

Y. Guo, C. Zhao, Y. Liu, H. Nie, X. Guo, X. Song, K. Xu, J. Li and J. Wang, Analyst, 2020, Accepted Manuscript , DOI: 10.1039/D0AN00397B

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