Untargeted metabolomic profiling for identifying systemic signatures of helicobacter pylori infection in a guinea pig model (dataset)

Abstract

Infections caused by the Gram-negative bacterium Helicobacter pylori (H. pylori) can lead to gastritis, gastric or duodenal ulcers, and even gastric cancer in humans. Investigating quantitative changes in soluble biomarkers associated with H. pylori infection offers a promising method for monitoring the progression of the infection, inflammatory response and potentially systemic consequences. This study aimed to identify, using an experimental model of H. pylori infection in guinea pigs, the specific metabolomic biomarkers in the serum of H. pylori-infected (32) versus uninfected (32) animals. The H. pylori status was confirmed through histological, molecular, and serological examinations. Metabolomic profiling was conducted using UPLC-QTOF/MS methods. The metabolomic biomarkers significantly associated with H. pylori infection were selected based on volcano plots and traditional univariate receiver operating characteristics (ROC). This study identified 12 unique metabolites significantly differentiating H. pylori-infected guinea pigs from uninfected ones. In summary, the metabolomic profiling of serum samples, in combination with ROC characteristics of the data, enhances the monitoring of H. pylori infection and related inflammatory responses in guinea pigs experimentally infected with these bacteria, with potential applications in humans for prediction the infection course and its systemic effects.