A colorimetric biosensor based on enzyme-catalysis-induced production of inorganic nanoparticles for sensitive detection of glucose in white grape wine

Huang Dai; Yuqing Li; Qi Zhang; Yingchun Fu; Yanbin Li

doi:10.1039/c8ra06347h

A colorimetric biosensor based on enzyme-catalysis-induced production of inorganic nanoparticles for sensitive detection of glucose in white grape wine

RSC Adv. 2018 Oct 3;8(59):33960-33967. doi: 10.1039/c8ra06347h. eCollection 2018 Sep 28.

Authors

Huang Dai¹, Yuqing Li¹, Qi Zhang¹, Yingchun Fu¹, Yanbin Li^{1

2}

Affiliations

¹ College of Biosystems Engineering and Food Science, Zhejiang University Hangzhou 310058 China yanbinli@zju.edu.cn +86 571 88982530 +86 571 88982536.
² Department of Biological and Agricultural Engineering, University of Arkansas Fayetteville AR 72701 USA.

Abstract

Sensitive and selective colorimetric sensors have come into a high demand due to their simplicity, rapidity, precision and use of common laboratory instruments. In this study, as a new colorimetric nanoprobe, enzyme-catalysis-induced production of Prussian blue nanoparticles (PBNPs) was employed to develop a colorimetric biosensor which was simple and inexpensive for the rapid detection of glucose in wine. Briefly, glucose as the detection target was added into a solution of glucose oxidase (GOx), FeCl₃ and K₃Fe(CN)₆, which turned the solution color from light-yellow to blue within 10 min. Thus, it could be probed by UV-vis spectroscopy. Unlike common colorimetric methods based on a sole color change mechanism, this method has two paths to generate PBNPs. Because both K₃Fe(CN)₆ and O₂ are involved in the turnover of GOx catalysis, they generate K₄Fe(CN)₆ and H₂O₂ that reduces Fe³⁺, respectively, and both paths finally produce PBNPs. This dual-path method enhances the yield of PBNPs and the detection performance. Under optimized conditions, the method presented a linear detection range of 4 μM to 0.5 mM (r ² = 0.998) and a limit of detection of 3.29 μM, which is comparable to or better than analogues, as well as excellent selectivity. This method also worked well in white grape wine samples with detection results varying within 1% to those obtained by the standard HPLC method. The proposed biosensing method is rapid, simple, low-cost, sensitive and selective, therefore, it is a promising method for daily detection of glucose in food in households and markets.