University of Pennsylvania Scientists Uncover Inherent Properties of Cell Signaling Pathways

            PHILADELPHIA -- Using an innovative approach based on synthetic biology and mathematical modeling, University of Pennsylvania researchers have explored the workings of a crucial cell-signaling pathway known as the mitogen-activated protein kinase, or MAPK, cascade.

By creating and manipulating a synthetic version of the signaling module, they were able to demonstrate that this pathway can inherently support a surprising variety of cell signals and responses.  Their work, in collaboration with researchers at Boston University and the Howard Hughes Medical Institute, is in the Jan. 7 issue of the journal Cell.

The enzymatic pathways within a cell that carry information from the outside world to the nucleus are enormously complex, with myriad branches and feedback loops.  They give the cell the ability to respond to its environment in various ways, such as by dividing or even self-destructing.  Such complexity makes studying an individual signaling module in situ difficult because this top-down approach only reveals how the natural module operates within the specific context of that cell. 

The Penn researchers instead took a bottom-up approach by synthetically constructing a MAPK cascade, known as a versatile signaling module capable of eliciting various responses, so its inherent capabilities could be studied in isolation.

“We wanted to take a signaling module that is broadly used by cells,” said Casim A. Sarkar, “and ask the question, What are the inherent properties of this module?” Sarkar is an assistant professor of bioengineering in Penn’s School of Engineering and Applied Science and co-author of the study. 

Using yeast as a host organism, the researchers constructed an insulated mammalian MAPK cascade consisting of the kinases Raf-MEK-ERK, and then subjected the module to various perturbations, including simply changing the relative concentrations of the three enzymes that make up the cascade. 

“We could not only analyze the basic version of the cascade but also understand how well-defined perturbations influenced its signal-processing characteristics,” Sarkar said. 

The experimenters also developed a mechanistic computational model capable of exploring a wide range of other possible perturbations and accurately predicting signaling responses.

Sarkar and his colleagues found that the MAPK cascade, even reduced to its basic three kinases and separated from its highly interconnected native cell environment, could still generate a broad array of signaling responses.  Pathways such as the MAPK cascade can act as “switches,” processing graded inputs from the surroundings and ultimately triggering a binary response in the cell -- to divide or not to divide, for example. 

“Perhaps the most surprising observation was that this switch-like input-output behavior could be significantly modulated by only adjusting the relative concentrations of the three core kinases,” Sarkar said.  “Without invoking feedback or any of the other connections that might exist in the native context, this behavior could be tuned.”

Aside from demonstrating that the MAPK cascade is, as Sarkar described, “a very flexible and tunable platform for generating a broad array of cellular responses,” the researchers have proven the potential of this new combination of a bottom-up synthetic biology approach with computational modeling for gaining a better understanding of these cellular signaling mechanisms.  

It was “the marriage of the synthetic biology and modeling approaches that gave us mechanistic insight.  Both were necessary to achieve this,” Sarkar said. 

Such insights into the intricacies of cell signaling can ultimately lead to the development and design of more effective drugs in, for example, diseases such as cancer where these pathways go awry, as well as to new cell-based therapies and devices. 

“Bioengineers are interested not only in understanding how cells make decisions, but also in rationally manipulating them to create new tissues, biosensors and biological computers.  The design rules elucidated by our work may also be useful for such applications,” Sarkar said.