Shown here are mouse intestinal epithelial cells. MIT and MGH researchers have modeled how such cells respond to tumor necrosis factor Credit: The Journal of Cell Biology
Biological systems, including cells,
tissues, and organs, can function properly only when their parts are working in
harmony. These systems are often dauntingly complex: Inside a single cell,
thousands of proteins interact with each other to determine how the cell will
develop and respond to its environment.
To understand this great complexity, a
growing number of biologists and bioengineers are turning to computational
models. This approach, known as systems biology, has been used successfully to
model the behavior of cells grown in laboratory dishes. However, until now, no
one has used it to model the behavior of cells inside a living animal.
Signaling, researchers from MIT and Massachusetts General Hospital
report that they have created a new computational model that describes how
intestinal cells in mice respond to a natural chemical called tumor necrosis
The work demonstrates that systems
biology offers a way to get a handle on the complexity of living systems and
raises the possibility that it could be used to model cancer and other complex
diseases, says Douglas Lauffenburger, head of MIT’s Department of Biological
Engineering and a senior author of the paper.
“You’re not likely to explain most
diseases in terms of one genetic deficit or one molecular impairment,”
Lauffenburger says. “You need to understand how many molecular components,
working in concert, give rise to how cells and tissues are formed—either
properly or improperly.”
Systems biology, a field that has grown in the past 10 years, focuses on
analyzing how the components of a biological system interact to produce the
behavior of that system.
“The beauty of systems biology is
that it doesn’t ignore the biological complexity of what’s going on,” says
Kevin Haigis, an assistant professor of pathology at MGH and Harvard Medical
School and a senior
author of the Science Signaling
“Biologists are trained to be
reductionists,” adds Haigis, who was a postdoctoral associate at MIT
before moving to MGH. “I don’t think people have failed to realize the
complexity of how biology works, but people are accustomed to trying to reduce
complexity to make things more understandable.”
In contrast, the systems biology
approach tries to capture that complexity through computer modeling of many
variables. Inputs to the model might be the amounts of certain proteins found
inside cells, and outputs would be the cells’ resulting behaviors.
While at MIT, Haigis worked in the lab
of Tyler Jacks, director of the David H. Koch Institute for Integrative Cancer
Research at MIT, studying the role of the cancer-causing gene Ras in the mouse
colon. He teamed up with Lauffenburger and others to computationally model Ras’
behavior in cell culture.
After Haigis moved to MGH, he and
Lauffenburger decided to bring this computational approach to studying living
animals because they believed that studies done in cultured cells could miss
some of the critical factors that come into play in living systems, such as the
location of a cell within a living tissue and the influence of cells that
In the new paper, the researchers tackled the complex interactions that produce
inflammation in the mouse intestine. The intestine contains many types of cells,
but they focused on epithelial cells (which line the intestinal tube) and their
response to TNF.
Previous work has shown that TNF plays a
central role in intestinal inflammation, and provokes one of two possible
responses in the intestinal epithelial cells: cell death or cell proliferation.
Chronic inflammation can lead to inflammatory bowel disease and potentially
In this study, the researchers got the
data they needed to develop their computational model by treating normal mice
with TNF, then determining whether the cells proliferated or died. They found
that cell fate depended on the cells’ location in the intestine—cells in the
ileum proliferated, while those in the duodenum died.
The multi-faceted result would likely
not have been seen in a lab dish. “In cell culture, you would have gotten
one or the other,” Lauffenburger says.
They also correlated the diverse
outcomes with the activities of more than a dozen proteins found in the cells,
allowing them to determine how the outcomes depended on quantitative
combination of key signaling pathways, and furthermore, to predict how the
outcomes would be affected by drug treatment. The researchers then tested the
model’s predictions in an additional cohort of mice, and found that they were accurate.
Jason Papin, assistant professor of biomedical engineering at the Univ. of Virginia, says that the team’s biggest
accomplishment is demonstrating that systems biology modeling can be done in
living animals (in vivo). “You
always want to move to an in vivo
setting, if possible, but it’s technically more difficult,” says Papin,
who was not involved with this research.
The researchers are now trying to figure
out in more detail what factors in the intestinal cells’ environment influence
the cells to behave the way they do. They are also studying how genetic
mutations might alter the cells’ responses.
They also plan to begin a study of
neurological diseases such as Alzheimer’s disease. Cancer is another disease
that lends itself to this kind of modeling, says Jacks, who was not part of
this study. Cancer is an extremely complicated disease that usually involves
derangement of many cell signaling pathways involved in cell division, DNA
repair and stress response.
“We expect that our ability to
predict which targets, which drugs and which patients to bring together in the
context of cancer treatment will require a deeper understanding of the complex
signaling pathways that exist in cancer,” says Jacks. “This approach
will help us get there.”