Novel Sensitive Electrochemical Immunosensor Development for the Selective Detection of HopQ H. pylori Bacteria Biomarker

Abstract

Helicobacter pylori (<i>H. pylori</i>) is a highly contagious pathogenic bacterium that can cause gastrointestinal ulcers and may gradually lead to gastric cancer. <i>H. pylori</i> expresses the outer membrane HopQ protein at the earliest stages of infection. Therefore, HopQ is a highly reliable candidate as a biomarker for <i>H. pylori</i> detection in saliva samples. In this work, an <i>H. pylori</i> immunosensor is based on detecting HopQ as an <i>H. pylori</i> biomarker in saliva. The immunosensor was developed by surface modification of screen-printed carbon electrodes (SPCE) with MWCNT-COOH decorated with gold nanoparticles (AuNP) followed by HopQ capture antibody grafting on SPCE/MWCNT/AuNP surface using EDC/S-NHS chemistry. The sensor performance was investigated utilizing various methods, such as cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and scanning electron microscope (SEM) coupled with energy-dispersive X-ray spectroscopy (EDX). <i>H. pylori</i> detection performance in spiked saliva samples was evaluated by square wave voltammetry (SWV). The sensor is suitable for HopQ detection with excellent sensitivity and linearity in the 10 pg/mL-100 ng/mL range, with a 2.0 pg/mL limit of detection (LOD) and an 8.6 pg/mL limit of quantification (LOQ). The sensor was tested in saliva at 10 ng/mL, and recovery of 107.6% was obtained by SWV. From Hill's model, the dissociation constant Kd for HopQ/HopQ antibody interaction is estimated to be 4.60 × 10^-10 mg/mL. The fabricated platform shows high selectivity, good stability, reproducibility, and cost-effectiveness for <i>H. pylori</i> early detection due to the proper choice of biomarker, the nanocomposite material utilization to boost the SPCE electrical performance, and the intrinsic selectivity of the antibody-antigen approach. Additionally, we provide insight into possible future aspects that researchers are recommended to focus on.