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New Software Models Immune Responses

Researchers with the Virginia Bioinformatics Institute at Virginia Tech have released an upgrade to the institute's ENteric Immunity SImulator (ENISI) software, which models immune responses to beneficial and harmful bacteria that enter the gastrointestinal tract of mice, pigs, and humans.

ENISI allows users to create enteric systems such as the gut-associated mucosal immune system in silico, providing a better glimpse of how the immune system responds to pathogens that invade the bacteria-rich environment of the gut.

ENISI was initially designed by the Center for Modeling Immunity to Enteric Pathogens (MIEP) to model inflammatory bowel disease. The upgrade allows investigators to simulate immune responses in a mouse infected with Helicobacter pylori. The MIEP team plans to expand the software to simulate infection with enteroaggregative Escherichia coli and other enteric pathogens, such as Clostridium difficile and Cryptosporidium parvum. Future upgrades will allow users to run simulations via the ENISI website and eventually be able to visualize in silico cells or lesions forming in real time, rather than only seeing the outcomes of such interactions.

"ENISI is unique because it's specific to the gut, simulating each individual cell rather than creating broad mathematical models," said Kate Wendelsdorf, a Ph.D. student in the genetics, bioinformatics, and computational biology program at Virginia Tech. "Thus, it's more faithful to a living system and allows us to simulate a million individual cells, more than any other simulator. It's a powerful tool for understanding interactions between gut pathogens and the mucosal immune system."

Researchers can manipulate cells and immune processes in ENISI to determine if, for example, blocking a specific immune pathway or adding a drug can inhibit pathogen invasion and infection. The computer-generated models can, in turn, help researchers design better experiments to test the simulations in laboratory settings or in live animals. Therefore, it may be possible to test the efficacy of a novel vaccine or immune therapeutic in an ENISI model of disease, confirm the results in an animal model, and then use those results to explore the mechanisms of therapeutic efficacy in additional studies.

This feature will help immunologists and infectious disease experts immensely in understanding pathology, diagnosis, and treatment.

"ENISI is based on an interaction-based modeling approach that represents individual cells and their interactions with other cells, pathogens, and the environment. The algorithmic/procedural representation of individual agents and their interactions with other agents via an abstract interaction network is central to the modeling process. The use of high-performance computing facilitates scaling to 106 cells; we expect this number to grow 100-fold over the next two years. Such a representation yields a fundamentally different approach to understanding novel immunological processes," said Madhav Marathe, the center's modeling lead.

"ENISI runs on high-performance computers: hundreds or thousands of servers working together to produce an answer. The program shows the power of trans-disciplinary science, bringing together a team of software developers, computer scientists, immunologists, and physicists to solve problems that they wouldn't have been able to tackle on their own," said Keith Bisset, modeling expert and a key developer of the ENISI software.

A Center for Modeling Immunity to Enteric Pathogens paper entitled, "Enteric Immunity Simulator: A tool for in silico study of gut immunopathologies," has been accepted in the IEEE Bioinformatics and Biomedicine (BIBM) International conference proceedings. Preliminary ENISI modeling results that simulate bacterial-induced colitis will be presented at the conference in Atlanta in November (

"One of our goals is to develop user-friendly and interactive modeling tools that engage and inform the immunology and infectious disease communities, thereby enabling paradigm-shifting scientific discovery," said Josep Bassaganya-Riera, the center's principal investigator. "The release of the upgraded ENISI software by the MIEP team is a major step in allowing powerful computer simulations to uncover novel mechanisms of immunoregulation underlying immune responses to gut pathogens. The ultimate goal of such powerful simulations is to accelerate the discovery of novel drug targets and biomarkers for enteric infectious diseases. The fully integrated computational modeling, bioinformatics and immunology experimentation efforts within the MIEP program enable the generation of mechanistic evidence in silico and efficient validation in vivo," and Bassaganya-Riera, who is also director of the Nutritional Immunology and Molecular Medicine Laboratory at Virginia Bioinformatics Institute.

For more information about ENISI, visit the Center for Modeling Immunity to Enteric Pathogens at

The center is funded by the National Institute of Allergy and Infectious Diseases under the Modeling Immunity for Biodefense program.

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, 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.

Tiffany Trent | Newswise Science News
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