Issue 14, 2023

Quantitative and qualitative analysis of ochratoxin-A using fluorescent CQDs@DNA-based nanoarchitecture assembly to monitor food safety and quality

Abstract

Ochratoxin A (OTA), a mycotoxin formed by various fungi, such as Aspergillus and Penicillium species, is dangerous to human health. Thus, to circumvent the risk of OTA ingestion, the recognition and quantification of OTA levels are of great significance. A perusal of the literature has revealed that the integration of DNA/Carbon Quantum Dot (CQD)-based hybrid systems may exhibit the unique electronic and optical properties of nanomaterials/nanoarchitecture and consequent recognition properties. Herein, we developed the CQDs@DNA-based hybrid nanoarchitecture system for the selective detection of OTA, which exhibits modulation in the emission spectrum after interaction with OTA, with a significant binding constant (Ka = 3.5 × 105 M−1), a limit of detection of 14 nM, limit of quantification of 47 nM and working range of 1–10 μM. The mechanism for sensing the OTA has been corroborated using fluorescence, UV-visible absorption spectroscopy, and FTIR techniques, demonstrating the binding mode of CQD@DNA hybrid nano-architecture assembly with OTA. Further, we demonstrated the sensing ability of developed CQDs@DNA-based nanoarchitecture assembly towards the quantification of OTA in real food monitoring analysis for real-time applications, which makes this developed nanoarchitecture assembly the potential candidate to conveniently monitor food safety and quality for human health.

Graphical abstract: Quantitative and qualitative analysis of ochratoxin-A using fluorescent CQDs@DNA-based nanoarchitecture assembly to monitor food safety and quality

Supplementary files

Article information

Article type
Paper
Submitted
09 Feb 2023
Accepted
12 Mar 2023
First published
13 Mar 2023

Anal. Methods, 2023,15, 1826-1835

Quantitative and qualitative analysis of ochratoxin-A using fluorescent CQDs@DNA-based nanoarchitecture assembly to monitor food safety and quality

A. Singh, G. Singh, N. Kaur and N. Singh, Anal. Methods, 2023, 15, 1826 DOI: 10.1039/D3AY00209H

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