Authors:	Reiner-Rozman, Ciril
Title:	Graphene-based field effect transistors for the biosensing of toxins
Online publication date:	26-Aug-2016
Year of first publication:	2016
Language:	english
Abstract:	A biosensor setup was designed for the detection of aflatoxin B1 based on field effect transistors (FET) using reduced Graphene-Oxide (rGO) as transducer. The dependence of the detection signal to the ion strength of the buffer solution was studied and results were superimposed with the Debye-length theory, demonstrating the applicable ion strengths for the shown type of biosensor. Furthermore characterization of pH responses and the binding of bovine serum album as a standard test for the biosensor have been tested. As the next step, binding of aflatoxin B1 was characterized, measuring basic kinetic parameters according to the Langmuir binding theory for the description of the equilibrium surface coverage as a function of the bulk (analyte) concentration in aqueous solution. The obtained binding coefficient for aflatoxin B1 are found to be in the same magnitude as described in literature values. Furthermore the main aim of this project was the detection of aflatoxin B1 from real-life corn samples using anti-fouling layers for the protection of the rGO and the diminishment of unspecific surface potential and charge changes. Therefor a sensor array was used, implying a FET with the target aflatoxin B1-antibody and a FET with a non-targeted antibody (bovine serum albumin) for comparison of the response signals. For the realization, reduced graphene oxide (rGO) was synthesized using a wet-chemical method and then used for the fabrication of 50 µm channel-width field effect transistors. A passivation coating of 20 nm Ta2O5 was sputtered on the semiconductor (rGO) without pin-holes. Then, using a silane as linking molecule, the target antibodies (aflatoxin B1) were applied on the passivated surface just before measurement in liquid-gated configuration. The passivation prohibits binding of non-specific molecules from the food samples on the graphene surface, but still the surface potential is changed when flushing these food samples over the FET channel. Therefor a negative control FET is connected serially to the FET with the target antibodies and this negative control is performed using non-target antibodies (anti-bovine serum albumin). The signals of both FETs are then compared and the difference in signal area is giving a read-out for the aflatoxin B1 binding on the target antibodies. A comparison of the integrated areas obtained by the response signals of the FETs during contaminated corn injections yields the final biosensor read-out. The limit of detection (LOD) in real-life samples was found to be around 10 nM, being two magnitudes higher than for measurements in buffer, but still below the maximum toxin concentration instructed by the EU food-stuffs regulatory. Calibration curves of the system were performed using a titration of 5 different contaminated corn food samples and one certified blank corn sample. The detection signals were then measured by the integration of the separate response signals and the difference of the target FET and the negative control. The presented approach shows promising results for the development of a novel biosensor due to the low assay time (around 2 minutes), small device size, possible real-time read-out and it’s cost-efficiency. The work on aflatoxin B1 detection was performed in the framework of an industrial project in cooperation with Romer Labs®, Tulln, Austria. Additionally to the sought experimental data on toxin detection in this phd-thesis from real-life samples a liquid-velocity sensor was accomplished and described, the use of impedance spectroscopy for FETs demonstrated and a novel characterization technique using surface electrochemical microscopy (SECM) for the assessment of the applicability of graphene surfaces for biosensors was developed.
DDC:	500 Naturwissenschaften 500 Natural sciences and mathematics
Institution:	Johannes Gutenberg-Universität Mainz
Department:	FB 10 Biologie
Place:	Mainz
ROR:	https://ror.org/023b0x485
DOI:	http://doi.org/10.25358/openscience-4610
URN:	urn:nbn:de:hebis:77-diss-1000006380
Version:	Original work
Publication type:	Dissertation
License:	In Copyright
Information on rights of use:	https://rightsstatements.org/vocab/InC/1.0/
Extent:	VI, 125, XXXIII Seiten
Appears in collections:	JGU-Publikationen