Scientists experiment with three proteins that impact preadipocytes contribute to fat cell determination

May 17, 2017

"The three target proteins of this initial model are the most commonly studied, but their mutual relationships in relation to the creation of fat cells are still not well-known, so we are putting their roles together to see how they contribute to fat cell determination for the first time, as far as we know, in the literature," Coskun said.

The mathematical equations in which these three protein levels were manipulated resulted in a model that helped define the conditions under which pre-fat cells would remain dormant, start copying themselves or turn into fat cells. Two-parameter bifurcation curves are used for interpretation of model outcomes, which itself is a novel approach in terms of mathematical terminology.

The main parameters driving this model were two substances that affect the target proteins: a protein called IkB, which inhibits the inflammatory NF-kB protein, and the concentration of a chemical stimulant, called a mitogen, that stimulates production of cyclin D.

According to the model, if the level of IkB is high and the level of the cyclin D stimulant is low, the pre-fat cells remain dormant. The model then shows what is called a "curve of uncertainty," which predicts the circumstances that are required for preadipocytes to either remain dormant or proliferate in their current state. The region of uncertainty then determines the conditions for coexistence of a pair of these three states: differentiation and quiescence, or proliferation and differentiation.

The researchers also conducted preliminary experiments to test the model's outcomes by exposing mouse cells to TNF-alpha, a mitogen that stimulates cyclin D. They found that the concentrations of the proteins in those cells generally behaved as the model suggested they would. In addition, previous research reports of similar experiments also support the model's outcomes, Coskun said.

He noted that more experiments are needed to further test the model, which also could be expanded to add more proteins to the equations.

Source : Ohio State University