A new program at the National Institute of Allergy and Infectious Diseases (NIAID), one of the National Institutes of Health (NIH), aims to better understand the complex biochemical networks that regulate the interactions between infectious organisms and the human or animal cells they infect. The Program in Systems Immunology and Infectious Disease Modeling (PSIIM) will employ a powerful new approach called computational systems biology to develop a deeper understanding of how pathogens cause disease and how the immune system responds to them.
"Understanding the daunting complexity of biological systems is the greatest challenge and at the cutting-edge of science in the 21st century," says NIH Director Elias A. Zerhouni, M.D. "The creation of this program will strengthen the intramural research program here on the NIH campus."
The wealth of information gleaned about the human genome in recent years has identified many of the genes, proteins and other molecules involved in various biological systems. But understanding how these pieces work together to produce the complex physiological and pathological behavior of cells and organisms is not well understood. The goal of the PSIIM, which is a component of NIAID's Division of Intramural Research (DIR) under the leadership of immunologist Ronald N. Germain, M.D., Ph.D., is to create a way to ask how whole systems of molecules, cells and tissues interact during an immune response or when confronted with an infectious agent.
"The idea of the PSIIM," says NIAID Director Anthony S. Fauci, M.D., "is to use systems biology to allow scientists to ask very big questions they may not have been able to fully address even a few years ago--such as how infectious organisms invade human cells, how the toxins they produce cause cell and tissue destruction and how these pathogens evade or manipulate the immune response."
"Once we understand these interactions, we can make strategic decisions about how to interfere with infectious disease pathology or how to direct immune responses to better fight infections," says DIR Director Kathryn C. Zoon, Ph.D., adding that these new insights can serve as the starting point for the design of new drugs to treat diseases or the development of new vaccines.
By creating computer models of complex molecular interaction networks, PSIIM investigators will be able to simulate the biology of cells, tissues and, eventually, organisms. The program will also use state-of-the-art experimental approaches to determine how closely these simulations predict real behavior. As the models improve, scientists should gain the ability to predict how drugs and other interventions will affect a cell or organism and whether such treatments will be tolerated by the host while they fight the infectious agent. Although most of the studies will be conducted with less dangerous pathogens, special facilities in the new C. W. Bill Young Center for Biodefense and Emerging Infectious Diseases at NIH will enable PSIIM scientists to examine such questions with microbes that cause diseases such as anthrax, virulent forms of influenza, tularemia and plague. The program will encourage collaboration between NIAID researchers and other scientists from both inside and outside NIH in efforts to better understand infectious diseases and the immune system.
The cornerstone of the PSIIM research project is a software package called Simmune, which enables biologists to model many types of biological systems. Created by NIAID scientist Martin Meier-Schellersheim, Ph.D., and his colleagues, the software allows a scientist to use a simple graphical interface to easily define the interactions between individual molecules in a large network, or the behaviors of cells in response to external signals. Once a scientist inputs quantitative information obtained by laboratory measurements, Simmune can then simulate the behavior of the whole signaling network or of an entire cell. The software does this by automatically creating a mathematical model involving special equations and then solving these equations for the specific conditions the user entered into the program.
Before Simmune, making such mathematical models by hand often took months and required extensive expertise in applied mathematics. In addition, making changes to an existing model was very time-consuming, which limited the complexity of what could be modeled. "With Simmune, we are trying to empower a broad range of biological experts, allowing them to easily make and modify detailed quantitative models of the biological systems they have studied in the lab for years. The hope is that these models will provide a deeper understanding of how complex behaviors arise, leading to new insights into disease," says Dr. Germain. "One of the great advantages of Simmune is that it gives biologists a way to do the difficult mathematics needed for such modeling without having to actually be involved with the mathematics."
In the first stringent test of the new software, Drs. Meier-Schellersheim, Germain and their colleagues demonstrated that Simmune can accurately predict cell function in both time and space. In an article to be published July 21 by the journal PLoS Computational Biology, they describe how they used the software to model a complicated cell-biological behavior known as chemosensing--a fundamental biological process whereby cells sense and respond to external signals, such as inflammatory chemicals involved in an immune response. Using Simmune, the NIAID team modeled what happens in a stimulated cell to the distribution of a membrane-associated molecule known as a phospholipid. The concentration of the phospholipid changes during chemosensing mainly due to the action of two enzymes that synthesize or break down this molecule. Scientists had thought that the destructive biochemical reaction that helps produce high and low concentrations of the phospholipid in different parts of the cell was regulated through some unknown mechanism acting throughout the cell. But a new model developed with Simmune predicted that the enhanced concentration of phospholipid at the "front" end of the cell (facing the source of chemical signals) resulted from a combination of two known mechanisms--a very rapid local inhibitory activity and the slower movement of another molecule to a distant part of the cell. The NIAID researchers, who tested their predictions in the laboratory, found that the experimental data matched very closely what they had predicted with Simmune.
The real power of the software, Dr. Meier-Schellersheim adds, is that it can do this same sort of modeling in nearly any cell-based biological system. "This is a tool that can simulate signaling and cellular processes in general," he says, "whatever system or process you are interested in." Because of the general utility of the approach, PSIIM is planning to collaborate extensively with scientists in other NIH institutes and centers, such as the National Cancer Institute's Center for Cancer Research, to help support research in areas such as cancer biology that are outside of the field of immunity and infectious diseases.
NIAID is a component of the National Institutes of Health. NIAID supports basic and applied research to prevent, diagnose and treat infectious diseases such as HIV/AIDS and other sexually transmitted infections, influenza, tuberculosis, malaria and illness from potential agents of bioterrorism. NIAID also supports research on basic immunology, transplantation and immune-related disorders, including autoimmune diseases, asthma and allergies.
The National Institutes of Health (NIH)--The Nation's Medical Research Agency--includes 27 Institutes and Centers and is a component of the U. S. Department of Health and Human Services. It is the primary federal agency for conducting and supporting basic, clinical and translational medical research, and it investigates the causes, treatments and cures for both common and rare diseases. For more information about NIH and its programs, visit http://www.nih.gov.
Reference: M Meier-Schellersheim et al. Key role of local regulation in chemosensing revealed by a new molecular interaction-based modeling method. PLoS Computational Biology DOI: 10.1371/journal.pcbi.0020082.eor (2006).
News releases, fact sheets and other NIAID-related materials are available on the NIAID Web site at http://www.niaid.nih.gov.
Last reviewed: By John M. Grohol, Psy.D. on 21 Feb 2009
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