Author(s): Carneiro, Pedro ; Loureiro, Joana A. ; Delerue-Matos, Cristina ; Morais, Simone ; Pereira, Maria do Carmo
Date: 2023
Persistent ID: http://hdl.handle.net/10400.22/23880
Origin: Repositório Científico do Instituto Politécnico do Porto
Subject(s): α-synuclein; Gold nanoparticles; Carbon nanotubes; Monoclonal antibody
Aggregation of α-synuclein has been recognized as a critical event in the pathogenesis of Parkinson's disease whose prevalence is increasing with great socio-economic challenges for future generations. Here, we developed a sensitive and specific electrochemical immunosensor for the detection and quantification of this biomarker, based on the voltammetric study of a redox indicator signal, which decreases upon the analyte recognition by the antibody due to the electronic resistance increase. The proposed immunosensor is based on a screen-printed carbon electrode modified in a layer-by-layer approach, which through extensive characterization led to the successful nanostructuration of the transducer, through the drop-cast of 3.0 μL of a 0.1 mg mL−1 single-walled carbon nanotubes suspension followed by electrodeposition of gold nanoparticles in a 3 mM HAuCl4 solution under a −0.2 V potential for 150 s. Monoclonal antibodies were immobilized on the gold nanoparticles surface through chemical modification at an optimal concentration of 200 μg mL−1. Using the proposed immunosensor, α-synuclein was detected in the range of 0.01–10 ng mL−1 with a 4.1 and 12.6 pg mL−1 limits of detection and quantification, respectively. Recovery values of 96.7, 106.2 and 102.9% were attained for the tested concentrations spiked in fetal bovine serum while also presenting excellent specificity and stability throughout one month. The nanostructured immunosensor provided a great interface for electronic transduction and biological recognition events, which enabled fast, sensitive and specific detection of α-synuclein while being based on a simple and inexpensive technology requiring small sample volumes, crucial characteristics for application in point-of-care testing.
