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Mathematical Modeling Predicts Cellular Communication

Date:
October 15, 2003
Source:
Public Library Of Science
Summary:
From the moment its life begins, the fate of a multicellular organism depends on how well its cells communicate. Proteins act as molecular switchboard operators to keep the lines of communication open and the flow of cellular messages on track. But charting the protein interactions, signaling pathways, and other elements that regulate these networks is no small feat.

From the moment its life begins, the fate of a multicellular organism depends on how well its cells communicate. Proteins act as molecular switchboard operators to keep the lines of communication open and the flow of cellular messages on track. But charting the protein interactions, signaling pathways, and other elements that regulate these networks is no small feat. There are many players that interact in complicated ways. Furthermore, these efforts have been hampered by the lack of quantitative data--measurements of signal duration, amplitude, and fluctuation--on these regulatory pathways.

In a tour de force combination of mathematical modeling and precise quantitative measurements, Marc Kirschner, of Harvard Medical School, and Reinhart Heinrich, of Humboldt University, Berlin, and colleagues focused their efforts on a well-studied signaling pathway--the Wnt pathway, which plays a role both in various stages of embryonic development and in carcinogenesis. Like most signaling pathways, Wnt is highly conserved. Consequently, developing tools that elucidate the Wnt pathway will not only provide insights into this important pathway but have implications for understanding communication pathways in animals from jellyfish to humans.

In order to develop their model model, the authors needed to know the concentrations of the various signaling components. What they found surprised them. When they measured the concentrations of the principal scaffold proteins (which bring other components in a pathway together by providing an interaction surface), axin and APC, they found that these two proteins were present in dramatically different concentrations, with axin at very low levels relative to the other signaling components and APC at similar concentrations to other signaling components. With this information in hand, and after a series of refinements based on additional experiments, they were able to develop a model that could not only simulate the behavior of the main players in the pathway--both in the absence and presence of a Wnt signal--but which also suggested why the two scaffold proteins are present in different concentrations: the low level of axin here may help the pathways retain their modularity, preventing the Wnt pathway from interfering with the other pathways.

These findings demonstrate that modeling can offer powerful new insights into the workings of complex signaling systems, cutting through the static to pick up important signals even in those pathways that are well understood. The results have important implications for developmental biology and human disease: The Wnt pathway is often activated during carcinogenesis--and mutations in several of these signaling proteins have been linked to colon cancer--suggesting that cancer can develop when signals in the Wnt circuitry somehow get crossed. By predicting how quantitative factors may influence the behavior of signaling networks, mathematical models such as this could shed light on the role that breakdowns in cellular communication play in carcinogenesis. The researchers argue that future attempts to characterize these complex networks must incorporate quantification measurements, and their modeling efforts suggest ways to do that.

###

Link: http://www.plos.org/downloads/plbi-01-01-lee-salic-kruger.pdf.


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The above story is based on materials provided by Public Library Of Science. Note: Materials may be edited for content and length.


Cite This Page:

Public Library Of Science. "Mathematical Modeling Predicts Cellular Communication." ScienceDaily. ScienceDaily, 15 October 2003. <www.sciencedaily.com/releases/2003/10/031015031202.htm>.
Public Library Of Science. (2003, October 15). Mathematical Modeling Predicts Cellular Communication. ScienceDaily. Retrieved July 31, 2014 from www.sciencedaily.com/releases/2003/10/031015031202.htm
Public Library Of Science. "Mathematical Modeling Predicts Cellular Communication." ScienceDaily. www.sciencedaily.com/releases/2003/10/031015031202.htm (accessed July 31, 2014).

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