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Detection of Inosine Monophosphate (IMP) in Meat Using Double-Enzyme Sensor

  • Guangxian Wang
  • Jianfei Sun
  • Yao Yao
  • Xingshuang An
  • Hui Zhang
  • Guanglei Chu
  • Shui Jiang
  • Yemin GuoEmail author
  • Xia Sun
  • Yuan Liu
Article

Abstract

Inosine monophosphate (IMP) was considered to be an important component of meat flavor and an important indicator for evaluating the quality of meat products. This paper developed a novel dual-enzyme biosensor for the quantitative detection of inosinic acid to assess meat quality. Using the conductivity of MXene materials and the ability of Au@Pt nanoflowers to catalyze the oxidation of H2O2, a dual-enzyme biosensor was assembled and prepared for sensitive and rapid detection of IMP. The MXene-Ti3C2Tx material had 2D nanostructure similar to that of graphene, as well as metal conductivity and good biocompatibility. MXene was used as a carrier for 5′-nucleotidase and xanthine oxidase, with good biological environment and stable microenvironment. Bimetallic nanoflowers with a core-shell structure had better ability to catalyze H2O2 than the single metal. The double-enzyme hydrolyzed IMP to produce the H2O2. The Au@Pt nanoflowers of the sensor can catalyze the decomposition of H2O2, which causes electron transfer to produce current change. Therefore, the content of IMP is indirectly obtained by monitoring the current change. The results showed that the linear range of the double-enzyme biosensor was 0.04~17 g L−1, the correlation coefficient was 0.9964, and the detection limit was 2.73 ng mL−1. The biosensor had great reproducibility and stability. Compared with high-performance liquid chromatography, biosensors could quickly and accurately detect the content of inosine monophosphate in meat, and provided a better method to detect the quality index of meat products.

Keywords

Transition metal carbide Au@Pt nanoflowers Enzyme biosensor Inosine monophosphate 

Notes

Funding Information

This work was supported by the National Natural Science Foundation of China (No. 31772068, 31701681, 31872909), Special Project of Independent Innovation of Shandong Province (2018CXGC0214), Shandong Provincial Natural Science Foundation (ZR2017BC001, ZR2018ZC0126, ZR2018BC055).

Compliance with Ethical Standards

Ethical Approval

This article does not contain any studies with human participants performed by any of the authors.

Informed Consent

Not applicable.

Conflict of Interest

Guangxian Wang declares that there is no conflict of interest. Jianfei Sun declares that there is no conflict of interest. Yao Yao declares that there is no conflict of interest. Xingshuang An declares that there is no conflict of interest. Hui Zhang declares that there is no conflict of interest. Guanglei Chu declares that there is no conflict of interest. Shui Jiang declares that there is no conflict of interest. Yemin Guo declares that there is no conflict of interest. Xia Sun declares that there is no conflict of interest. Yuan Liu declares that there is no conflict of interest.

Novelty Statement

A novel enzyme biosensor was developed to assess meat quality and freshness. Using the conductivity of MXene materials and the catalytic activity of Au@Pt nanoflowers, the enzyme biosensor was assembled and prepared for ultra-sensitive and rapid detection of IMP. The MXene-Ti3C2TX material had a 2D nanostructure similar to graphene, as well as metal conductivity and good biocompatibility. Used as a carrier for related enzymes, MXene provided a good biological environment and a stable microenvironment, while the bimetallic nanoflowers with a core-shell structure had higher catalytic activity than a single noble metal. The by-product hydrogen peroxide was produced by the double-enzyme catalysis process used, the current signal of the catalytic oxidation of hydrogen peroxide by Au@Pt nanoflowers was monitored at the biosensor as the detection target, and the qualitative and quantitative detection of IMP was achieved.

Supplementary material

12161_2019_1652_MOESM1_ESM.doc (12 kb)
ESM 1 (DOC 58 kb)

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Agricultural Engineering and Food ScienceShandong University of TechnologyZiboChina
  2. 2.Department of Food Science and Technology, School of Agriculture and BiologyShanghai Jiao Tong UniversityShanghaiChina

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