Issue 13, 2023

Label-free colorimetric apta-assay for detection of Escherichia coli based on gold nanoparticles with peroxidase-like amplification

Abstract

In this work, aptamers against E. coli with better performance were obtained via cell systematic evolution of ligands by exponential enrichment (cell-SELEX) and dissociation constants (Kd) of aptamers were estimated to range from 133.87 to 199.44 nM. Furthermore, the selected aptamer was employed for label-free colorimetric detection of E. coli using gold nanoparticles (AuNPs) with peroxidase-like activity to catalyze the oxidation of tetramethylbenzidine (TMB) by hydrogen peroxide (H2O2) to produce color development. This colorimetric apta-assay started with an aptamer–bacteria binding step, and the concentration of residual aptamers after binding depended on the amount of target bacteria. Then, the amount of separated residual aptamers determined the degree of cetyltrimethylammonium bromide (CTAB)-inhibited catalytic activity of AuNPs, which resulted in a color change from dark blue to light blue. Owing to the excellent peroxidase activity of AuNPs, they could emit strong visible color intensity in less than 1 minute to improve visual detection sensitivity. Under optimized conditions, the sensitivity of detection was 5 × 103 CFU mL−1 visually and 75 CFU mL−1 using the UV-vis spectrum with a linear range from 5 × 102 to 1 × 106 CFU mL−1. And it had shown a good recovery rate in real samples of water, juice and milk compared with classical counting methods.

Graphical abstract: Label-free colorimetric apta-assay for detection of Escherichia coli based on gold nanoparticles with peroxidase-like amplification

Supplementary files

Article information

Article type
Paper
Submitted
05 Nov 2022
Accepted
03 Mar 2023
First published
03 Mar 2023

Anal. Methods, 2023,15, 1661-1667

Label-free colorimetric apta-assay for detection of Escherichia coli based on gold nanoparticles with peroxidase-like amplification

M. Liu, F. Zhang, S. Dou, J. Sun, F. Vriesekoop, F. Li, Y. Guo and X. Sun, Anal. Methods, 2023, 15, 1661 DOI: 10.1039/D2AY01822E

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