H.O.S.T.: Hemoglobin microbubble-based Oxidative stress Sensing Technology.

In this work, we discuss the development of H.O.S.T., a novel hemoglobin microbubble-based electrochemical biosensor for label-free detection of Hydrogen peroxide (H2O2) towards oxidative stress and cancer diagnostic applications. The novelty of the constructed sensor lies in the use of a sonochemically prepared hemoglobin microbubble capture probe, which allowed for an extended dynamic range, lower detection limit, and enhanced resolution compared to the native hemoglobin based H2O2 biosensors. The size of the prepared particles Hemoglobin microbubbles was characterized using Coulter Counter analysis and was found to be 4.4 microns, and the morphology of these spherical microbubbles was shown using Brightfield microscopy. The binding chemistry of the sensor stack elements of HbMbs' and P.A.N.H.S. crosslinker was characterized using Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy and UV-Vis Spectroscopy. The electrochemical biosensor calibration (R2 > 0.95) was done using Electrochemical Impedance Spectroscopy, Cyclic Voltammetry, and Square Wave Voltammetry. The electrochemical biosensor calibration (R2 > 0.95) was done using Electrochemical Impedance Spectroscopy, Cyclic Voltammetry, and Square Wave Voltammetry. The specificity of the sensor for H2O2 was analyzed using cross-reactivity studies using ascorbic acid and glucose as interferents (p < 0.0001 for the highest non-specific dose versus the lowest specific dose). The developed sensor showed good agreement in performance with a commercially available kit for H2O2 detection using Bland Altman Analysis (mean bias = 0.37 for E.I.S. and - 24.26 for CV). The diagnostic potential of the biosensor was further tested in cancerous (N.G.P.) and non-cancerous (H.E.K.) cell lysate for H2O2 detection (p = 0.0064 for E.I.S. and p = 0.0062 for CV). The Michaelis Menten constant calculated from the linear portion of the sensor was found to be [Formula: see text] of 19.44 µM indicating that our biosensor has a higher affinity to Hydrogen peroxide than other available enzymatic sensors, it is attributed to the unique design of the hemoglobin polymers in microbubble.

Inflammatory Stimuli Responsive Non-Faradaic, Ultrasensitive Combinatorial Electrochemical Urine Biosensor.

In this work, we propose a novel diagnostic biosensor that can enable stratification of disease states based on severity and hence allow for clear and actionable diagnoses. The scheme can potentially boost current Point-Of-Care (POC) biosensors for diseases that require time-critical stratification. Here, two key inflammatory biomarkers­Interleukin-8 and Interleukin-6­have been explored as proof of concept, and a four-class stratification of inflammatory disease severity is discussed. Our method is superior to traditional lab techniques as it is faster (<4 minutes turn-around time) and can work with any combination of disease biomarkers to categorize diseases by subtypes and severity. At its core, the biosensor relies on electrochemical impedance spectroscopy to transduce subtle inflammatory stimuli at the input for IL-8 and IL-6 for a limit of detection (LOD) of 1 pg/mL each. The biosensing scheme utilizes a two-stage random forest machine learning model for 4-state output disease classification with a 98.437% accuracy. This scheme can potentially boost the diagnostic power of current electrochemical biosensors for better precision therapy and improved patient outcomes.

Label-Free Protein Glycosylation Analysis Using NanoMonitor-An Ultrasensitive Electrochemical Biosensor.

Glycans (oligosaccharide chains attached to glycoproteins) are a promising class of biomarkers, found in body fluids such as serum, saliva, urine, etc., that can be used for the diagnosis of disease conditions. Subtle changes in glycans resulting from altered glycosylation machinery have been reported during various diseases, including carcinogenesis. In this article, we detail protocols for the rapid, label-free analysis of glycans using a previously developed highly sensitive and selective electrochemical impedance spectroscopy-based biosensing diagnostic platform called "NanoMonitor." The glycosensor operation is based on the specific affinity capture of the target glycans on the sensor surface by glycan-binding proteins known as lectins. This glycan-lectin binding activity modulates the impedance of the electrical double layer at the buffer-electrode interface. Protocols for the preparation of glycoprotein samples and glycosylation analysis using NanoMonitor and lectin-based ELISA are described here. The data obtained using these protocols show that NanoMonitor is capable of distinguishing between glycoform variants of the glycoprotein fetuin and glycoproteins derived from cultured human pancreatic cancer cells with high sensitivity (orders of magnitude higher than lectin-based ELISA) and selectivity. The results obtained indicate that NanoMonitor protocols can be further developed to enable use of NanoMonitor as a handheld electronic biosensor device for routine multiplexed detection of glycan biomarkers from clinical samples. © 2021 Wiley Periodicals LLC. Basic Protocol 1: Preparing the NanoMonitor surface for glycan biosensing Support Protocol: Synthesis of glycoform variants of fetuin Basic Protocol 2: Performing Electrochemical Impedance Spectroscopy (EIS) for analyzing glycoprotein structures.