Pathogen-microbiome Interaction During Helicobacter Pylori Infection

Pathogen-microbiome Interaction in Human Response and Disease-outcome During Infection and Colonization With Helicobacter Pylori

Helicobacter pylori affects the gut microbiome in ways that are only partially understood. In which patients H. pylori causes severe disease and in whom it merely colonizes, possibly even with beneficial effects, is not understood. The investigators are pursuing the hypothesis that changes in the gut microbiome that can be easily measured in stool have such predictive value.

Helicobacter pylori colonizes the stomach of about half of the world's population, including about 20-30% of adults in Germany. In some cases, this colonization can lead to chronic inflammation of the gastric mucosa, which can lead to various serious diseases such as ulcer disease and gastric cancer. It has been reported several times in the literature that Helicobacter pylori infection negatively affects the human intestinal flora and can lead to microbial imbalance (dysbiosis). Recent studies, mostly from mouse models, reveal new roles and interactions of the microbiome: host immune response may influence bacterial activity; bacterial metabolites may determine microbiome functions. Differences in the microbiome were also found between Helicobacter pylori-infected patients and were associated with treatment success. On the other hand, beneficial microbial symbiosis may prevent intestinal inflammation. The reasons for these differences in the microbiome of Helicobacter pylori-infected patients, which may also contribute to treatment failure, remain to be investigated. Therefore, this project aims to investigate how Helicobacter pylori affects the bacteria and fungi of the human gastrointestinal microbiome and how the suspected microbial imbalance may influence treatment success. In this project, The investigators aim to answer the question of how these newly discovered mechanisms alter the course of human H. pylori infection. The investigators will analyze H. pylori itself in colonized patients and asymptomatic individuals (whole genome sequencing), determine the immune response of the carrier (RNA expression in lymphocytes), and composition of the gut microbiome (DNA sequencing) and activity (RNA expression in the bacteria/fungi and identification of metabolites). Using bioinformatics approaches, particularly machine learning, The investigators will determine the parameters that predict disease progression and eradication success. The results will provide important decision support for H. pylori-infected patients.

Inclusion Criteria:

Patients: -

• Male and female patients aged ≥ 18 years.
• Specimens from patients undergoing tissue sampling, stool, and blood to rule out Helicobacter pylori infection
• Written informed consent from patients.

Volunteer subjects: -

• Male and female (non-pregnant) volunteers between the ages of 18-65 years.
• Written informed consent from volunteers.
• No acute medical conditions
• No regular medication use, and no antibiotic use in the last 4 weeks.

Exclusion Criteria:

Patients: -

• Minor patients
• Patients not capable of giving consent
• Samples without sufficient residual material after standard diagnostic procedures
• Samples from patients who have not given consent for testing

Volunteer subjects: -

• Subjects not capable of giving consent
• Subjects with acute illnesses
• Subjects older than 65 or younger than 18 years of age.
• Pregnant women