Determination of p53 biomarker using an electrochemical immunoassay based on layer-by-layer films with NiFe2O4 nanoparticles

Author(s)

Ibanez-Redin, Gisela ; Joshi, Nirav ; do Nascimento, Gustavo Freitas ; Wilson, Deivy ; Melendez, Matias E. ; Carvalho, Andre L. ; Reis, Rui Manuel ; Goncalves, Debora ; Oliveira, Osvaldo N., Jr.

• Document type: Journal article
• Source: Microchimica Acta; v. 187, n. 11, p. 10-pg., 2020-10-21.

Abstract

A disposable electrochemical immunosensors is presented suitable to detect cancer biomarker p53 using screen-printed carbon electrodes modified with a layer-by-layer (LbL) matrix of carboxylated NiFe(2)O(4)nanoparticles and polyethyleneimine, onto which anti-p53 antibodies were adsorbed. Under optimized conditions, the immunosensors exhibited high surface coverage and high concentration of immobilized antibodies, which allowed for detection of p53 in a wide dynamic range from 1.0 to 10 x 10(3) pg mL(-1), with a limit of detection of 5.0 fg mL(-1)at a working potential of 100 mV vs. Ag/AgCl. The immunosensors also exhibited good selectivity with negligible interference upon incubation in complex matrices containing high concentrations of proteins (i.e., fetal bovine serum and cell lysate). The immunosensor performance is among the best reported in the literature for determination of p53, with the additional advantage of being disposable and operating with low-volume solutions. Graphical abstract Schematic representation of immunosensor fabrication depicting the immobilization of specific antibodies against p53 protein onto the surfaces of disposable printed electrodes modified with films of polyethyleneimine and different concentrations of carboxylated magnetic nanoparticles. (AU)

• FAPESP's process: 14/23546-1 - Enhanced sensitive and selective sensors made with p-NiO nanowire/n-ZnO Nanowire heterostructures
• Grantee: Niravkumar Jitendrabhai Joshi
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• FAPESP's process: 18/22214-6 - Towards a convergence of technologies: from sensing and biosensing to information visualization and machine learning for data analysis in clinical diagnosis
• Grantee: Osvaldo Novais de Oliveira Junior
• Support Opportunities: Research Projects - Thematic Grants