Enzyme Multilayers on Graphene-Based FETs for Biosensing Applications

Publication year: 2018
Authors: Bliem C. a, Piccinini E. b, Knoll W. a, Azzaroni O. b
Affiliations:

a - AIT Austrian Institute of Technology GmbH, Biosensor Technologies, Vienna, Austria
b - INIFTA Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas (INIFTA)—Departamento de Química, Facultad de Ciencias Exactas, Universidad Nacional de La Plata—CONICET, La Plata, Argentina

Published in: Methods in Enzymology, 2018, Vol. 609, p. 23-46
doi: 10.1016/bs.mie.2018.06.001

Electrochemical sensors represent a powerful tool for real-time measurement of a variety of analytes of much significance to different areas, ranging from clinical diagnostics to food technology. Point-of-care devices which can be used at patient bedside or for online monitoring of critical parameters are of great importance in clinical daily routine. In this work, portable, low-cost electrochemical sensors for a fast and reliable detection of the clinically relevant analyte urea have been developed. The intrinsic pH sensitivity of reduced graphene oxide (rGO)-based field-effect transistors (FETs) was exploited to monitor the enzymatic hydrolysis of urea. The functionalization of the sensor platform using the layer-by-layer technique is especially advantageous for the immobilization of the biorecognition element provided that this approach preserves the enzyme integrity as well as the rGO surface. The great selectivity of the enzyme (urease) combined with the high sensitivity of rGO-based FETs result in the construction of urea biosensors with a limit of detection (LOD) of 1 μM and a linear range up to 1 mM. Quantification of Cu2 + with a LOD down to 10 nM was performed by taking advantage of the specific inhibition of urease in the presence of heavy metals. These versatile biosensors offer great possibilities for further development of highly sensitive enzyme-based FETs for real-time, label-free detection of a wide variety of clinically relevant analytes.


MP-SPR keywords: adsorbed mass, adsorption, enzyme immobilization, layer-by-layer, reduced graphene oxide surface