Technological advances in electrochemical biosensors for the detection of disease biomarkers

Abstract

With an increasing focus on health in contemporary society, interest in the diagnosis, treatment, and prevention of diseases has grown rapidly. Accordingly, the demand for biosensors for the early diagnosis of disease is increasing. However, the measurement range of existing electrochemical sensors is relatively high, which is not suitable for early disease diagnosis, requiring the detection of small amounts of biocomponents. Various attempts have been made to overcome this and amplify the signal, including binding with various labeling molecules, such as DNA, enzymes, nanoparticles, and carbon materials. Efforts are also being made to increase the sensitivity of electrochemical sensors, and the combination of nanomaterials, materials, and biotechnology offers the potential to increase sensitivity in a variety of ways. Recent studies suggest that electrochemical sensors can be a powerful tool in providing comprehensive insights into the targeting and detection of disease-associated biomarkers. Significant advances in nanomaterial and biomolecule approaches for improved sensitivity have resulted in the development of electrochemical biosensors capable of detecting multiple biomarkers in real time in clinically relevant samples. In this review, we have discussed the recent studies on electrochemical sensors for detection of diseases such as diabetes, degenerative diseases, and cancer. Further, we have highlighted new technologies to improve sensitivity using various materials, including DNA, enzymes, nanoparticles, and carbon materials.

Keywords: Biomarkers; Disease diagnosis; Early diagnosis; Electrochemical biosensors; Nanomaterials.

Fig. 1

a shows the limits of the detection (LOD) trend studied for the last 10 years by dividing the electrochemical sensor into three major diseases: b diabetes, c neurodegenerative disease, and d cancer. Representative of 56 data of this review in the field of electrochemical biosensors over the disease detection. The number of the published papers on neurodegenerative diseases, interleukins and cytokines according to Chemical Abstracts Service (CAS) data e

Fig. 2

Schematic illustration of basic principle (a) and measurement methods (b) of electrochemical sensors

Fig. 3

a Representative of key advances in the field of electrochemical glucose biosensors over the past decade. Reproduced with permission from ref. [18]. Copyright (2020) ACS. b Schematic illustration depicting the deintercalation of CaGe2 or CaSi2 Zintl phases. c Cyclic voltammograms, Chronoamperometry curves of the glucose oxidase-based electrochemical glucose biosensor and Chronoamperometry curves of the various electrode configurations. b and c reproduced with permission from ref. [19]. Copyright (2021) Wiley

Fig. 4

a Schematic illustration of water oxidation-coupled, FeOOH/Mo: BiVO4-based photoelectrochemical sensing platform for detecting Alzheimer’s tau proteins of femtomolar levels. b Detection limits of AD biomarker-targeting sensing platforms reported so far. a and b Reproduced with permission from Ref. [35]. Copyright (2020) Elsevier. c Scheme 1. A schematic illustration of the electrochemical detection of Ab (1–40/1–42) by using a gelsolin-Au-Th bioconjugate as a probe. Reprinted with permission from Ref. [31]. Copyright (2014) Wiley. d Cyclic voltammetry from anhydrous acetonitrile containing 0.1 M LiClO₄ solution and 0.1 M 3-thiophene-3-acetic acid, Pyrrole-2-carboxylic acid, Pyrrole-3-carboxylic acid on gold disc. Nyquist plots of modified electrode. Reproduced with permission from Ref. [32]. Copyright (2020) Elsevier

Fig. 5

a Schematic illustration of the fabrication process of the immunosensing interface, DPV responses of electrochemical immunoassay and the calibration plot between the DPV peak current and the logarithm values of CYFRA21-1 concentrations. Reproduced with permission from Ref. [59]. Copyright (2016) Springer. b Schematic illustration of the AuNS modified LSG-based aptasensor. Cyclic voltammograms of bare LSG electrode, Nyquist plots for bare LSG. Reproduced from with permission Ref. [55]. Copyright (2021) Elsevier

Fig. 6

a Schematic of the principle of the CRISPR/Cas9-triggered ESDR based on a 3D GR/AuPtPd nanoflower biosensor. Reproduced with permission from Ref. [12]. Copyright (2021) Elsevier. b Schematic representation of a preparation of mesoporous Au electrode (MPGE) via electrodeposition of gold (III)-containing polymeric (block) micelles.  Reprinted with permission from Ref. [93]. Copyright (2020) Elsevier. c Gel electrophoresis analyses of the translational biosensing event between a target miR-196b and a target probe via Klenow fragment-assisted dual amplification for the detection of target miR-196b using a native gel and 7 M urea denaturing gel. M indicates the DNA markers for 10–300 bp. Each lane: 100 nM. Reproduced with permission from Ref. [94]. Copyright (2021) Elsevier

Fig. 7

a A schematic representation of the fabrication of the Chit/ChOx/Ti3C2Tx/GCE, and a possible reaction mechanism of cholesterol at the modified GCE. Reproduced with permission from Ref. [109]. Copyright (2021) Elsevier. b “Signal-on” electrochemical exosomes aptasensor using CD63-incorporated GOx/HRP DFs as sensing interface and specific recognition element. c “Signal-off” electrochemical dual-aptamer biosensor for thrombin detection using Apt15 as capture probe and Apt29-incorporated GOx/HRP DFs as amplified labels. b and c Reproduced with permission from Ref. [105]. Copyright (2021) Elsevier

Fig. 8

a Construction of the electrochemical biosensor of EMT. Detection of E-cadherin at different protein levels and with different number of cells. Reproduced with permission from Ref. [113]. Copyright (2020) Springer. b Immunosensor preparation mechanism diagram. The immunosensor response to DPV signals for detecting different concentrations of PCT. Reproduced with permission from Ref. [112]. Copyright (2021) Elsevier

Fig. 9

a Schematic representation of the SPCE electrochemical DNA biosensor. DPV curves after hybridization, The calibration plot of peak current versus the logarithm of the concentration of target lncRNA MALAT1. Reproduced with permission from Ref. [15]. Copyright (2021) Springer. b Schematic representation of the fabrication and working of Tyr/ZnO-rGO/ITO biosensing platform. DPV response of Tyr/ZnO-rGO/ITO bioelectrodes towards different DA concentrations. Calibration curve plotted between DPV response current and exposed DA concentrations. Hanes plot to determine the Michaelis–Menten constant (Km) associated with enzyme activity. Comparison of responses between ZnO-rGO/ITO and Tyr/ZnO-rGO/ITO electrodes towards different DA concentrations. Reproduced with permission from Ref. [128]. Copyright (2020) Elsevier

Fig. 10

a Representative examples of wearable biosensors. Reproduced with permission from Ref. [134]. Copyright (2019) Springer. b Representative of epidermal biosensors for real-time monitoring of sweat. Reproduced with permission from Ref. [134]. Copyright (2019) Springer. c Schematic representation of microneedle sensor for L-Dopa detection and portable wireless electroanalyzer enabled with wireless data transmission to the smart device. Reproduced with permission from Ref. [140]. Copyright (2019) ACS. d Mechanical match, biocompatibility and biointegration of the implanted CNT fiber. Reproduced with permission from Ref. [144]. Copyright (2020) Springer