BLACKSBURG, Va., Dec. 16, 2011 – Virginia Bioinformatics Institute (VBI) researchers led by Dr. Bassaganya-Riera, Professor of Immunology at VBI and Director of the Nutritional Immunology and Molecular Medicine Laboratory (NIMML), returned from the Modeling Immunity for Biodefense (MIB) annual meeting galvanized to launch into Year Two of the Center for Modeling Immunity for Enteric Pathogens (MIEP) program. The MIB annual meeting also included other modeling centers such as the Center for Computational Immunology at Duke, the Program for Research on Immune Modeling and Experimentation at Mount Sinai/Yale, and the Center for Biodefense Immune Modeling at Rochester.
The meeting, held at the National Institutes of Health in Bethesda on November 2-3, 2011 focused on achievements for the first part of the program and goals for the next phase of the MIEP program. Among the greatest achievements for MIEP were developing a computational model of CD4+ T cell differentiation using the Complex Pathway Simulator (COPASI) software; launching an enhanced version of CellPublisher, a unique platform that shows cell interactions via a Google maps-like interface and a high level of integration between modeling and experimental efforts; and deploying ENteric Immunity SImulator (ENISI), a newly developed interaction-based modeling software.
“The COPASI framework is very user-friendly and capable of providing a solid foundation for model implementation and sharing. I have no doubt that the computational models developed by MIEP will be extremely valuable to the study of immunity to enteric pathogens. The MIEP Center has made significant progress in characterizing mechanisms of immunoregulation at the gut mucosa while establishing fully integrated, novel and improved capabilities at the interface of immunology, bioinformatics, and modeling,” said Dr. Bassaganya-Riera.
For the second phase of the program, Dr. Bassaganya-Riera’s NIMML team will use the modeling process to generate novel hypotheses about mechanisms of immunoregulation and help guide the design of immunology experiments. These new experiments in animal models and human blood samples will help refine and validate our predictive computational models. The knowledge gained promises to lead to improved, broad-based and host-targeted therapeutics to counteract deadly gut pathogens and the inflammation they often cause.
“The NIMML investigated the role of peroxisome proliferator-activated receptor γ (PPAR γ) on CD4+ T cell differentiation during infection with enteric pathogens. This provides an excellent framework for the development of novel mathematical models of immunity. In addition, PPAR γ represents a valuable target for developing new therapeutics for enteric infections,” said Dr. Raquel Hontecillas, the MIEP Immunology Lead and Assistant Professor at VBI.
About the Nutritional Immunology and Molecular Medicine Laboratory (NIMML)
The Nutritional Immunology and Molecular Medicine Laboratory (http://www.nimml.org) conducts translational research aimed at developing novel therapeutic and prophylactic approaches for modulating immune and inflammatory responses. The Laboratory combines computational modeling, bioinformatics approaches, immunology experimentation, and pre-clinical and clinical studies to better understand the mechanisms of immune regulation at mucosal surfaces and ultimately accelerate the development of novel treatments for inflammatory, infectious and immune-mediated diseases.
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 250 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.