BLACKSBURG, Va., August 31, 2013 – Researchers at the Virginia Bioinformatics Institute (VBI) have developed a new large animal model to study immune system interactions with the stomach bacterium Helicobacter pylori. The researchers describe their pig model in Infection and Immunity.
H. pylori is found in over half the world’s population. While most people do not develop disease, some experience chronic inflammation of the stomach, or gastritis, which can lead to development of ulcers or cancer. In addition to its role as a pathogen, H. pylori has beneficial effects. Researchers have found that H. pylori can prevent certain chronic inflammatory and metabolic diseases, while the absence of the bacterium may contribute to obesity and type II diabetes.
Recently, scientists found H. pylori inside human immune cells. When pathogens reside within host cells, the immune system typically recruits a specific type of T cells, called CD8+ cytotoxic T cells, to help clear the infection by destroying infected cells. Researchers have found higher numbers of cytotoxic T cells in patients with H. pylori-associated gastritis, indicating that these cells may contribute to the development of gastric lesions.
To study immune responses in H. pylori-mediated disease, researchers at VBI’s Nutritional Immunology and Molecular Medicine Laboratory (NIMML) developed a pig model that closely mimics the human gastric environment. When pigs were infected with H. pylori, the researchers observed an increase in another type of immune cells called pro-inflammatory CD4+ T helper cells, followed by an increase in CD8+ cytotoxic T cells. This finding was somewhat unexpected because scientists did not observe an increase in CD8+ T cells in mouse and gerbil models of H. pylori infection. However, the rise in CD8+ T cells in pigs mirrors the recent findings in human clinical studies.
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Although the immune system recruits CD8+ cytotoxic T cells to fight bacterial infection, the NIMML researchers found that these cells contribute to tissue damage rather than bacterial clearance. Their findings will help scientists better understand the complex interactions of H. pylori and its host.
NIMML researchers within MIEP are using results from the pig model and other experimental data to develop a computational model of H. pylori infection. Such modeling efforts aim to develop faster, more efficient ways to predict initiation, progression and outcomes of infection.
An abstract is available at http://www.ncbi.nlm.nih.gov/pubmed/23897614
MIEP is funded by the National Institute of Allergy and Infectious Diseases, part of the National Institutes of Health, under Contract No. HHSN272201000056C. PI: Josep Bassaganya-Riera.
About the Nutritional Immunology and Molecular Medicine Laboratory:
The Nutritional Immunology and Molecular Medicine Laboratory (NIMML) conducts translational research aimed at developing novel therapeutic and prophylactic approaches for modulating immune and inflammatory responses. The Laboratory has over 20 researchers and combines computational modeling, bioinformatics approaches, pre-clinical experimentation and human clinical studies to better understand the mechanisms of immune regulation at mucosal surfaces and ultimately accelerate the development of novel treatments for infectious and immune-mediated diseases. In addition, the NIMML team leads the NIAID-funded Center for Modeling Immunity to Enteric Pathogens (MIEP).
About the Virginia Bioinformatics Institute
The Virginia Bioinformatics Institute at Virginia Tech is a premier bioinformatics, computational biology and systems biology research facility that uses transdisciplinary approaches to science, combining information technology, biology and medicine. These approaches are used to interpret and apply vast amounts of biological data generated from basic research to some of today’s key challenges in the biomedical, environmental and agricultural sciences. With more than 240 highly trained multidisciplinary, international personnel, research at the institute involves collaboration in diverse disciplines such as mathematics, computer science, biology, plant pathology, biochemistry, systems biology, computational immunology, statistics, economics, synthetic biology and medicine. The large amounts of data generated by this approach are analyzed and interpreted to create new knowledge that is disseminated to the world’s scientific, governmental and wider communities.
September 12, 2013