Phenolic Tyrosinase Substrate with a Formal Potential Lower than That of Phenol to Obtain a Sensitive Electrochemical Immunosensor

Abstract

The high and selective catalytic activities of tyrosinase (Tyr) have frequently led to its application in sensitive biosensors. However, in affinity-based biosensors, the use of Tyr as a catalytic label is less common compared to horseradish peroxidase and alkaline phosphatase owing to the fact that phenolic Tyr substrates have yet to be investigated in detail. Herein, four phenolic compounds that have lower formal potentials than phenol were examined for their applicability as Tyr substrates, and three reducing agents were examined as potential strong reducing agents for electrochemical−chemical (EC) redox cycling involving an electrode, a Tyr product, and a reducing agent. The combination of 4methoxyphenol (MP) and ammonia-borane (AB) allows for (i) a high electrochemical signal level owing to rapid EC redox cycling and (ii) a low electrochemical background level owing to the slow oxidation of AB at a low applied potential and no reaction between MP and AB. When this combination was applied to an electrochemical immunosensor for parathyroid hormone (PTH) detection, a detection limit of 2 pg/mL was obtained. This detection limit is significantly lower than that obtained when a combination of phenol and AB was employed (300 pg/mL). It was also found that the developed immunosensor works well in PTH detection in clinical serum samples. This new phenolic substrate could therefore pave the way for Tyr to be more commonly used as a catalytic label in affinitybased biosensors.

Overview on the Development of Electrochemical Immunosensors by the Signal Amplification of Enzyme- or Nanozyme-Based Catalysis Plus Redox Cycling

“…Finally, the developed method was capable of determining CEA in a linear range of 1.0 pg/mL~0.1 μg/mL with a detection limit of 100 fg/mL. To further investigate the detailed information of tyrosinase as a catalytic label in immunoassay, Park et al compared the applicability of four para -substituted phenolic compounds as tyrosinase substrates and three reducing agents for EC redox cycling ( Figure 10 B) [ 140 ]. In this work, 4-methoxyphenol and ammonia-borane (H 3 N−BH 3 , AB) were selected as the tyrosinase substrate and the reducing agent.…”

“…( B ) Schematic illustration of an electrochemical immunosensor using Tyr (tyrosinase) as a catalytic label and 4-methoxyphenol as a reducing agent. Reprinted with permission from reference [ 140 ]. Copyright 2016 American Chemical Society.…”

Optical Bioassays Based on the Signal Amplification of Redox Cycling

“…Therefore, redox cycling can be simply coupled with other signal amplification methods, such as enzymes or nanocatalyst-driven chemical reactions and nanomaterial-based containers [ 14 , 15 ]. For example, electrochemical biosensors, by integrating redox cycling and enzyme catalysis, have been developed to show high sensitivity and signal-to-noise ratio [ 16 , 17 , 18 ]. Chemical–chemical redox cycling reactions have been successfully deployed in photoelectrochemical biosensors for the ultrasensitive detection of various biomarkers [ 19 , 20 ].…”

A compact, low-cost, and binary sensing (BiSense) platform for noise-free and self-validated impedimetric detection of COVID-19 infected patients

“…Several researchers have attempted to develop new multichannel potentiostats, but they are neither low-cost enough to be used for low-cost POCT (e.g., for detection of COVID-19 outside of a laboratory) nor sensitive and noise-free enough to meet the high sensitivity needs of ultrasensitive electrochemical biosensors ( Alam et al, 2021 ; Park et al, 2022 ; Ramfos et al, 2013 ; Vinoth et al, 2021 ; Wu et al, 2018 ). The output signals of these readers whether square wave, cyclic voltammetry, or impedance ( Pellitero et al, 2021 ), deals with curve-shaped data that needs further data analysis and curve-fitting approaches to obtain the biosensor data, adding to the complexity of the reader ( Abdullah et al, 2019 ; Bianchi et al, 2019 ; Hoilett et al, 2020 ; Pruna et al, 2018 ; Wu et al, 2018 ).…”