Issue 14, 2017

The colorimetric assay of diamine oxidase activity with high sensitivity based on calixarene derivative-capped gold nanoparticles

Abstract

Diamine oxidase (DAO) is involved in regulating ingested or endogenous histamine, several types of human cancer, and the cell mass during embryonic development. Furthermore, DAO is a potential indicator of intestinal mucosa damage in inflammatory and neoplastic diseases or after chemotherapy. Therefore, developing a biosensor is urgently needed to assay DAO activity. In this work, a simple but sensitive colorimetric biosensor is developed for DAO assay and inhibitor screening. The biosensor is based on host-guest interactions between the amine group on the terminal of 1,6-hexanediamine (HMD) and p-sulfonatocalix[6]arene (pSC6). These interactions may aggregate pSC6 modified gold nanoparticles (AuNPs) and induce the corresponding color change of the test solution. Specifically, AuNP aggregation is affected because coordination reactivity does not exist between oxidized HMD and pSC6 during HMD oxidation by DAO. Therefore, a simple colorimetric method with high sensitivity for the assay of DAO activity is proposed. A linear relationship is presented under optimized experimental conditions in a range of 0.15 mU mL−1 to 4.5 mU mL−1 with the lowest detection limit of 0.062 mU mL−1. Moreover, the inhibition effect of guanidine on DAO activity is tested with the IC50 value of 2.4 μM using the proposed biosensor. Therefore, this biosensor has great potential not only for the detection of DAO activity but also for inhibitor screening in future.

Graphical abstract: The colorimetric assay of diamine oxidase activity with high sensitivity based on calixarene derivative-capped gold nanoparticles

Article information

Article type
Paper
Submitted
24 Jan 2017
Accepted
04 Mar 2017
First published
06 Mar 2017

Anal. Methods, 2017,9, 2153-2158

The colorimetric assay of diamine oxidase activity with high sensitivity based on calixarene derivative-capped gold nanoparticles

B. Wu, F. Zou, X. Wang, K. Koh, K. Wang and H. Chen, Anal. Methods, 2017, 9, 2153 DOI: 10.1039/C7AY00227K

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