journal article·2021-10

A novel Ag/Zn bimetallic MOF as a superior sensitive biosensing platform for HCV-RNA electrochemical detection

Said M. El-Sheikh, Diaa I. Osman, Omnia I. Ali, Wafaa Gh Shousha, Madiha A. Shoeib, Sherif M. Shawky, Sheta M. Sheta

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Abstract

Abstract A new label-free electrochemical biosensor was progressed for direct detection of unamplified HCV nucleic acid based on silver/zinc bimetallic metal–organic framework (Ag/Zn-MOF). Several physico-chemical techniques were used to confirm the structure and morphology. The prepared bimetallic-MOF was cast on the glassy carbon electrode (GCE) and treated with the capture probe of HCV. Then, treated with bovine serum albumin (BSA) to passivate the surface, which is ready for hybridization process once the HCV target nucleic acid was added. Cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) were used as an evidence for the successful stepwise formation of the desired biosensor. In addition, a differential pulse voltammetry (DPV) measurement was used in the presence of glucose as an electrochemical catalytic indicator. The results confirmed that the bimetallic MOF's catalytic activity stimulated glucose oxidation to gluconolactone, resulting in electrochemical signal amplification. The proposed HCV electrochemical biosensor has several advantages ease of use; low cost; high selectivity and sensitivity; a linear detection ranges from 1 fM to 100 nM; and ultra-low detection limit (0.64 fM). To date, this is the first electrochemical HCV-biosensor report based on bimetallic-MOF. Consequently, this assay opens the door for designing more electrochemical biosensors regarding the electrical and catalytic activity of bimetallic-MOF.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Advanced biosensing and bioanalysis techniques · Metal-Organic Frameworks: Synthesis and Applications · Electrochemical sensors and biosensors

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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