NH2 linker for femtomolar label-free detection with reduced graphene oxide screen-printed electrodes

Surface modification with linker molecules is necessary for the effective immobilization of bioreceptors and for improving the performance of biosensors. In this work, we present a novel functionalization technique to attach amine (NH2) linker on graphene-based sensor surfaces. This is achieved by reacting the commercially available reduced graphene oxide (rGO) screen-printed electrodes (SPEs) with ammonia solution at room temperature. The NH2 linkers are attached predominantly on the edge and defect sites of rGO SPE through chemisorption as shown by XPS, Raman and FTIR analysis. The functionalized SPEs are further characterized using morphological and electrochemical techniques. The validation of the linker is done by using the functionalized SPEs for the detection of A beta(1-40) and A beta(1-42) biomarkers. A limit of detection (LOD) of 9.51 fM is achieved over a linear dynamic range of 10 fM-10 pM for A beta(1-40). Similarly, LOD of 8.65 fM is achieved over a linear dynamic range of 10 fM-50 pM for A beta(1-42). This excellent sensitivity is attributed to the functionalization of rGO surface with NH2 linker, which provides a large number of binding sites for bioreceptors. High specificity for the target biomarkers over interfering A beta and ApoE epsilon 4 species is also demonstrated. The biosensor is further validated for the analysis of spiked human plasma. The proposed technique provides a promising approach for improving the detection sensitivity of graphene biosensors for application in biofluids based minimally invasive and cost- and time-efficient disease diagnosis. (C) 2021 The Authors. Published by Elsevier Ltd.

Automated summary

Surface modification with NH2 linker on graphene-based sensor surfaces enhances the sensitivity and specificity for detecting A beta biomarkers. The functionalized sensors show excellent performance in spiked human plasma with high stability and reliability. This novel technique provides a promising approach to improve the detection sensitivity of graphene biosensors for minimally invasive disease diagnosis in biofluids.