4.7 Article

Modified screen printed electrode for development of a highly sensitive label-free impedimetric immunosensor to detect amyloid beta peptides

期刊

ANALYTICA CHIMICA ACTA
卷 892, 期 -, 页码 69-76

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.aca.2015.08.036

关键词

Amyloid beta (A beta); Immunosensor; Electrochemical impedance spectroscopy (EIS); Screen-printed electrode (SPE); Disposable electrochemical printed (DEP) chip

资金

  1. Japan Society for the Promotion of Science (JSPS)

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Alzheimer's disease (AD) is a fatal neurodegenerative disease affecting approximately 26 million people world-wide, and the number is increasing as life expectancy increases. Since the only reliable diagnosis for the pathology is histochemical post-mortem examination, there is a rather urgent need for reliable, sensitive and quick detection techniques. Amyloid beta, being one of the established and widely accepted biomarkers of AD is a target biomolecule. Herein, we present fabrication of a labelless impedimetric amyloid beta immunosensor on carbon DEP (disposable electrochemical printed) chip. Three types of amyloid beta impedimetric immunosensors were fabricated in a systematic step-wise manner in order to understand the effects that each surface modification chemistry had on detection sensitivity. We found that compared to a bare electrode, surface modification through formation of SAM of AuNPs increased sensitivity by approximately three orders of magnitude (LoD from 2.04 mu M to 2.65 nM). A further modification using protein G, which helps orientate antibodies to an optimum position for interaction with antigen, lowered the LoD further to 0.57 nM. We have demonstrated that the presence of one of the most abundance proteins in biological fluids, bovine serum albumin (BSA), did not interfere with the sensitivity of the sensor. Since the DEP chips are disposable and the detection platform label-free, the developed sensor is relatively fast and cheap. These methods could easily be applied for detection of other antigens, with selection of the detection platform based on the desired for sensitivity. (C) 2015 Elsevier B.V. All rights reserved.

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