Liposome-amplified photoelectrochemical immunoassay for highly sensitive monitoring of disease biomarkers based on a split-type strategy.

Biosens Bioelectron

Key Laboratory of Analysis and Detection for Food Safety (Ministry of Education&Fujian Province), Institute of Nanomedicine and Nanobiosensing, Department of Chemistry, Fuzhou University, Fuzhou 350108, PR China.

Published: January 2018

Liposomes are an excellent candidate component for biosensors to transduce and amplify detection signals due to their outstanding ability in encapsulating signal marker compounds. However, the use of liposomes for photoelectrochemical (PEC) signal transduction has not yet been achieved due the lack of appropriate sensing strategy. Herein, we report on a novel liposomes-amplified PEC immunoassay (LAPIA) method for sensitive HIV-p24 antigen (p24) detection based on a split-type strategy. Initially, liposomes were encapsulated with alkaline phosphatase (ALP) in their hydrophilic chamber and conjugated with secondary antibody on the surface to form the ALP-encapsulated liposomes (ALP-Ls) based PEC signal label. Sandwiched immunoassay based on the ALP-Ls label was then carried out in microwell plate. Upon addition of tween 20, the ALP molecules were released and catalyzed the hydrolysis of ascorbic acid 2-phosphate (AA-p) to produce ascorbic acid (AA). The latter then donated electron to the graphene/g-CN nanohybrids based photoelectrode, arousing an increased photocurrent signal. The separation of immunoreaction step and PEC signal excitation (i.e. split-type) not only enabled the realization of liposomes based amplification strategy, but also could eliminate the PEC-caused biomolecules damage. The developed PEC method possessed a wide calibration range from 1.0pgmL to 50ngmL and a low detection limit of 0.63pgmL. Its practicability was demonstrated by assaying human serum samples. Moreover, the universality of the liposomes-amplified PEC sensing strategy was also demonstrated by developing it into a sensitive microRNA detection method.

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http://dx.doi.org/10.1016/j.bios.2017.07.067DOI Listing

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