New Pig Model will Study Ulcer Immune Response
Monday, September 30, 2013
Researchers at the Virginia Bioinformatics Institute (VBI) have
developed a new pig model to study how the immune system interacts with
the stomach bacterium Helicobacter pylori, the leading cause of peptic
"The results from our new pig model closely mimic
what has been reported in clinical settings, which will allow us to
comprehensively and systematically investigate human immune responses to
H. pylori,” said Raquel Hontecillas, co-director of the Nutritional
Immunology and Molecular Medicine Laboratory and the Center for Modeling
Immunity to Enteric Pathogens.
The discovery in the October
edition of the journal Infection and Immunity may inform changes in the
ways doctors treat patients. An estimated 4 million Americans have sores
in the stomach lining known as peptic ulcers, according to the American
When bacteria reside within host
cells, the immune system typically recruits a type of white blood cell
called T cells — in this case, CD8+ cytotoxic T cells — to destroy the
However, the researchers found that these cells may contribute to tissue damage.
In patients with H. pylori-associated gastritis, higher numbers of
cytotoxic T cells are present, indicating that these cells may
contribute to the development of gastric lesions.
To study immune
responses in H. pylori-mediated disease, researchers at the Virginia
Bioinformatics Institute’s Nutritional Immunology and Molecular Medicine
Laboratory 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, according to the study.
Researchers within the
Center for Modeling Immunity to Enteric Pathogens 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.