Advances in Helicobacter pylori detection technology: From pathology-based to multi-omic based methods

Abstract

Traditional detection methods for Helicobacter pylori (H. pylori) infection are complex and time-consuming, which hinders their large-scale application. In recent years, advances in multi-omics techniques have expanded the detection targets for H. pylori. Simultaneously, the development of technologies such as CRISPR/Cas systems, biosensors and artificial intelligence image recognition systems has also promoted the development of detection technology. Therefore, systematic summary and in-depth description of the latest technology will facilitate the advancement of H. pylori detection. In this paper, the existing H. pylori detection methods are divided into four categories according to detection targets: pathological detection, metabolic detection, proteomic detection and nucleic acid detection. The working principles and application characteristics are reviewed, and their advantages and limitations are compared. This article is not exhaustive, but it also discusses potential techniques that could inspire the development of faster, more accurate, and more convenient detection systems for H. pylori infection.