Enzyme‐based detection of epoxides using colorimetric assay integrated with smartphone imaging.
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| Title: | Enzyme‐based detection of epoxides using colorimetric assay integrated with smartphone imaging. |
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| Authors: | Gul, Ijaz1 (AUTHOR), Bogale, Tadesse Fantaye1 (AUTHOR), Deng, Jiao1 (AUTHOR), Chen, Yong1 (AUTHOR), Fang, Ruiqin1,2 (AUTHOR), Feng, Juan1,2 (AUTHOR), Tang, Lixia1,2 (AUTHOR) lixiatang@uestc.edu.cn |
| Source: | Biotechnology & Applied Biochemistry. Jul/Aug2020, Vol. 67 Issue 4, p685-692. 8p. |
| Subjects: | Image analysis software, Epoxy compounds, Chromatographic analysis, Environmental sampling, Gas analysis |
| Abstract: | Epoxides are widely used chemicals, the determination of which is of paramount importance. Herein, we present an enzyme‐based approach for noninstrumental detection of epoxides in standard solution and environmental samples. Halohydrin dehalogenase (HheC) as a biological recognition element and epichlorohydrin as a model analyte were evaluated for sensing. The detection is based on the color change of the pH indicator dye bromothymol blue caused by the HheC‐catalyzed ring‐opening of the epoxide substrate. The color change is then exploited for the determination of epoxide using a smartphone as an image acquisition and data processing device, eliminating the need for computer‐based image analysis software. The color parameters were systematically evaluated to determine the optimum quantitative analytical parameter. Under optimal conditions, the proposed enzyme‐based detection system showed a linear range of 0.13–2 mM with a detection limit of 0.07 mM and an assay time of 8 Min. In addition, the repeatability expressed as relative standard deviation was found to be below 5% (n = 6). Validation with gas chromatographic analyses showed that the proposed enzyme‐based epoxide detection could be an alternative way in the quantitative determination of epoxides, and particularly useful in resource‐limited settings. [ABSTRACT FROM AUTHOR] |
| Copyright of Biotechnology & Applied Biochemistry is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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