Team applies new theory to learn how and why cells differentiate
Jun 16, 2014 An overview of the stem cell gene network gives a sense of the complex process involved in cell differentiation, as transcription factors and protein complexes influence and loop back upon each other. Rice University researchers found that stem cell differentiation can be defined as a many-body problem as they developed a theoretical system to analyze large gene networks. Credit: Bin Zhang/Rice University
How does a stem cell decide what path to take? In a way, it's up to the wisdom of the crowd.
The DNA in a pluripotent stem cell is bombarded with waves of proteins whose ebb and flow nudge the cell toward becoming blood, bone, skin or organs. A new theory by scientists at Rice University shows the cell's journey is neither a simple step-by-step process nor all random.
Theoretical biologist Peter Wolynes and postdoctoral fellow Bin Zhang set out to create a mathematical tool to analyze large, realistic gene networks. As a bonus, their open-access study to be published this week by the Proceedings of the National Academy of Sciences helped them understand that the process by which stem cells differentiate is a many-body problem.
"Many-body" refers to physical systems that involve interactions between large numbers of particles. Scientists assume these many bodies conspire to have a function in every system, but the "problem" is figuring out just what that function is. In the new work, these bodies consist not only of the thousands of proteins expressed by embryonic stem cells but also DNA binding sites that lead to feedback loops and other "attractors" that prompt the cell to move from one steady state to the next until it reaches a final configuration.
To test their tool, the researchers looked at the roles of eight key proteins and how they rise and fall in number, bind and unbind to DNA and degrade during stem cell differentiation. Though the interactions may not always follow a precise path, their general pattern inevitably leads to the desired result for the same reason a strand of amino acids will inevitably fold into the proper protein: because the landscape dictates that it be so.
Wolynes called the new work a "stylized," simplified model meant to give a general but accurate overview of how cell networks function. It's based on a theory he formed in 2003 with Masaki Sasai of Nagoya University but now takes into account the fact that not one but many genes can be responsible for even a single decision in a cellular process.
"This is what Bin figured out, that one could generalize our 2003 model to be much more realistic about how several different proteins bind to DNA in order to turn it on or off," Wolynes said.
A rigorous theoretical approach to determine the transition pathways and rates between steady states was also important, Zhang said. "This is crucial for understanding the mechanism of how stem cell differentiation occurs," he said.
Wolynes said that because the stem cell is stochasticthat is, its fate is not pre-determined"we had to ask why a gene doesn't constantly flip randomly from one state to another state. This paper for the first time describes how we can, for a pretty complicated circuit, figure out there are only certain periods during which the flipping can occur, following a well-defined transition pathway."
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Team applies new theory to learn how and why cells differentiate