Metal–Organic Framework-Based Cascade Catalysis-Enabled Fluorescent ELISA with Higher Enzymatic Stability for Zearalenone Detection in Maize

The enzyme-linked immunosorbent assay (ELISA) stands as one of the most frequently employed rapid detection techniques for both chemical and biological contaminants. Horseradish peroxidase (HRP) and hydrogen peroxide (H<sub>2</sub>O<sub>2</sub>), serving as signal generators, play indispensable roles throughout the entire ELISA process. However, HRP and H<sub>2</sub>O<sub>2</sub> exhibit high sensitivity to elevated temperatures, hindering the broader utilization and transportation of ELISA. Hereby, being inspired by the cascade catalysis of glucose by glucose oxidase (GOx) and HRP as well as the advantageous properties of metal-organic frameworks (MOFs), we developed a cascade catalysis-based competitive fluorescent ELISA (CCF-ELISA) for mycotoxin detection in maize using zearalenone (ZEN) as a model. The results revealed the remarkable protective effects of MOFs on enzymatic activities. Based on upon characteristics, the built CCF-ELISA enabled the detection of ZEN with a half-maximal inhibitory concentration of 0.54 ng/mL and allowed a detection range from 0.19 to 1.51 ng/mL. When applied to naturally contaminated maize samples, the outcomes obtained from the CCF-ELISA showed a high level of comparability with high-performance liquid chromatography-tandem mass spectrometry, demonstrating the promising potential of the developed CCF-ELISA in the rapid detection for food security.

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Publication Details

Journal
Journal of Agricultural and Food Chemistry
Published
2024-12-20
DOI
https://doi.org/10.1021/acs.jafc.4c07146
Citations
15
Primary Topic
Advanced biosensing and bioanalysis techniques
Type
article
Field-Weighted Citation Impact
3.51

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article

Metal–Organic Framework-Based Cascade Catalysis-Enabled Fluorescent ELISA with Higher Enzymatic Stability for Zearalenone Detection in Maize

Zhanhui Wang, Chaochao Chen, Yantong Pan, Jianzhong Shen et al.
15 citations
Journal of Agricultural and Food Chemistry
Advanced biosensing and bioanalysis techniques
3.51
article

Metal–Organic Framework-Based Cascade Catalysis-Enabled Fluorescent ELISA with Higher Enzymatic Stability for Zearalenone Detection in Maize

Zhanhui Wang, Chaochao Chen, Yantong Pan, Jianzhong Shen, Liang Luo
article en
15 citations

Abstract

The enzyme-linked immunosorbent assay (ELISA) stands as one of the most frequently employed rapid detection techniques for both chemical and biological contaminants. Horseradish peroxidase (HRP) and hydrogen peroxide (H<sub>2</sub>O<sub>2</sub>), serving as signal generators, play indispensable roles throughout the entire ELISA process. However, HRP and H<sub>2</sub>O<sub>2</sub> exhibit high sensitivity to elevated temperatures, hindering the broader utilization and transportation of ELISA. Hereby, being inspired by the cascade catalysis of glucose by glucose oxidase (GOx) and HRP as well as the advantageous properties of metal-organic frameworks (MOFs), we developed a cascade catalysis-based competitive fluorescent ELISA (CCF-ELISA) for mycotoxin detection in maize using zearalenone (ZEN) as a model. The results revealed the remarkable protective effects of MOFs on enzymatic activities. Based on upon characteristics, the built CCF-ELISA enabled the detection of ZEN with a half-maximal inhibitory concentration of 0.54 ng/mL and allowed a detection range from 0.19 to 1.51 ng/mL. When applied to naturally contaminated maize samples, the outcomes obtained from the CCF-ELISA showed a high level of comparability with high-performance liquid chromatography-tandem mass spectrometry, demonstrating the promising potential of the developed CCF-ELISA in the rapid detection for food security.

Journal of Agricultural and Food ChemistryVol. 73(1)
China Institute of Veterinary Drug Control (CN), Sanya University (CN), China Agricultural University (CN)
National Postdoctoral Program for Innovative Talents, National Key Research and Development Program of China
Openalex Percentile: Top 6%
Advanced biosensing and bioanalysis techniques
3.51
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