New NIAID Program Aims to Model Immune Responses
and Key Infectious Diseases
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.
News releases, fact sheets and other NIAID-related materials are available on the NIAID Web site at http://www.niaid.nih.gov.
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 www.nih.gov. |