Published October 16, 2017 | Version v1
Journal article

A redox-modulated fluorescent strategy for the highly sensitive detection of metabolites by using graphene quantum dots

Description

In this paper, a redox-modulated fluorescent strategy based on the transformation of Fe2+/Fe3+ couple and enzymatic reaction for rapid monitoring glucose and uric acid using graphene quantum dots (GQDs) as fluorescent probe was developed. Hydrogen peroxide (H2O2) can be produced by the enzymatic reaction of a series of metabolites, such as glucose and uric acid. In the presence of hydrogen peroxide, Fe2+ can be oxidized and converted to Fe3+, which have a significant quenching difference in the fluorescence of graphene quantum dots (GQDs). Thus, a sensitive and label-free biosensor for the detection of uric acid and glucose was developed. Under the optimized experimental conditions, the fluorescence intensity was linearly correlated with the concentration of uric acid and glucose in the range of 0.1–45 μmolL-1 and 0.1–30 μmolL-1 with a detection limit of 0.026 μmolL−1and 0.021 μmolL−1, respectively. The proposed method was applied to the determination of uric acid and glucose in human serum samples with satisfactory results, which had potential application to detect metabolites associated with H2O2 release. - Highlights: • GQDs with a fluorescence emission peak of 535 nm were used to detect uric acid and glucose. • The fluorescent strategy is based on the transformation of Fe2+/Fe3+ couple and enzymatic reaction. • The method was simple, low cost and had a higher sensitivity and better selectivity. • Uric acid and glucose in real samples were detected with satisfactory results. • The method had potential application to detect metabolites associated with H2O2 release.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.aca.2017.07.031

Additional details

Identifiers

DOI
10.1016/j.aca.2017.07.031;
PII
S0003-2670(17)30835-8;

Publishing Information

Journal Title
Analytica Chimica Acta
Journal Volume
990
Journal Page Range
p. 150-156
ISSN
0003-2670
CODEN
ACACAM

Optional Information

Copyright
Copyright (c) 2017 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.