Electrochemical and surface plasmon insulin assays on clinical samples

Abstract

Diabetes is a complex immune disorder that requires extensive medical care beyond glycemic control. Recently, the prevalence of diabetes, particularly type 1 diabetes (T1D), has significantly increased from 5% to 10%, and this has affected the health-associated complication incidences in children and adults. The 2012 statistics by the American Diabetes Association reported that 29.1 million Americans (9.3% of the population) had diabetes, and 86 million Americans (age ≥20 years, an increase from 79 million in 2010) had prediabetes. Personalized glucometers allow diabetes management by easy monitoring of the high millimolar blood glucose levels. In contrast, non-glucose diabetes biomarkers, which have gained considerable attention for early prediction and provide insights about diabetes metabolic pathways, are difficult to measure because of their ultra-low levels in blood. Similarly, insulin pumps, sensors, and insulin monitoring systems are of considerable biomedical significance due to their ever-increasing need for managing diabetic, prediabetic, and pancreatic disorders. Our laboratory focuses on developing electrochemical immunosensors and surface plasmon microarrays for minimally invasive insulin measurements in clinical sample matrices. By utilizing antibodies or aptamers as the insulin-selective biorecognition elements in combination with nanomaterials, we demonstrated a series of selective and clinically sensitive electrochemical and surface plasmon immunoassays. This review provides an overview of different electrochemical and surface plasmon immunoassays for insulin. Considering the paramount importance of diabetes diagnosis, treatment, and management and insulin pumps and monitoring devices with focus on both T1D (insulin-deficient condition) and type 2 diabetes (insulin-resistant condition), this review on insulin bioassays is timely and significant.

Fig. 1

Schematic representation of a typical insulin (PDB: 3V19) biosensor. In our work, we used different transduction methods, such as cyclic voltammetry (CV), square wave voltammetry (SWV), amperometry, electrochemical impedance spectroscopy (EIS), quartz crystal microbalance (QCM), and surface plasmon resonance (SPR) microarray imager.

Fig. 2

(a) Electrochemical methods showing (i) a representative cyclic voltammogram, (ii) a square wave voltammogram, (iii) an amperometric i-t curve at an applied constant potential, and (iv) the Nyquist plot representation of a faradaic impedance spectrum for a diffusion controlled interfacial charge-transfer process between an electrode and electrolyte interface containing a dissolved redox probe. (b) Schematic of oscillation frequency decrease monitored in real-time upon addition of a mass onto a gold disk infused quartz crystal measured by QCM. (c) Surface plasmon resonance monitoring of an antigen-antibody interaction with binding kinetics in a microarray format.

Fig. 3

(a) Representative electrochemical mass sensor designed for insulin detection based on quartz crystal microbalance followed by faradaic impedance signals. (b) A: oscillation frequency change, and B: increase in charge-transfer resistance for a 2-fold diluted serum insulin captured onto polyacrylic acid functionalized MNPs (100 nm hydrodynamic diameter) and bound onto the surface immobilized insulin antibody. Reproduced with permission from Ref. , The Royal Society of Chemistry.

Fig. 4

(a) Representative voltammetric MWNT/Py/Ab_insulin immunosensor designed to monitor current signals, and (b) A: square wave voltammograms for measuring 2-fold diluted serum insulin concentration captured onto MNPs (increasing concentration from a to f), and B: the calibration plot of sensor response. T1D and T2D denote type 1 and type 2 diabetes patient serum samples and the designed voltammetric sensor correlated with the standard ELISA method. Reprinted with permission from Ref. . Copyright 2015 American Chemical Society.

Fig. 5

(a) Cyclic voltammograms in Fe(CN)₆^3−/4− mixture for PGE/MWNT/Py/Ab_insulin/BSA electrodes treated with 0 (insulin unspiked 50% serum), 5, 25, 50, and 200 pM insulin spiked serum samples (a-e) captured onto MNPs; and (b) the corresponding increase in peak separation (ΔE_p) values for the insulin concentration dependent binding of serum insulin-MNPs onto the surface insulin antibody on PGE/MWNT/Py/Ab_insulin/BSA electrodes. Scan rate 0.1 Vs⁻¹. Reprinted with permission from Ref. . Copyright 2015 American Chemical Society.

Fig. 6

(a) Amperometric flow-injection immunosensor designed for insulin detection in 20-fold diluted human serum, and (b) current signals with insulin concentration presented with a patient sample data validating the applicability of such sensors for patient serum samples. Reprinted with permission from Ref. , The Royal Society of Chemistry.

Fig. 7

(a) SPRi microarray immunosensor developed for insulin detection in human serum, and (b) SPRi responses inferring the serum matrix effect and the performance of direct vs. sandwiched 50% serum insulin immunoassay. Reprinted with permission from Ref. Copyright 2016 American Chemical Society.

Fig. 8

(a) Dual SPRi microarray imager developed for insulin and HbA1c detection in an unprocessed whole blood diluted 20-times in buffer, and (b) the respective difference images, line profiles, and real-time SPRi responses (from left to right) for various concentrations of insulin and HbA1c. Reproduced with permission from Ref. Copyright 2017 American Chemical Society.