An important model for biological pattern formation is the bacterium E. coli, in which specific Min proteins oscillate rhythmically back and forth between the cell poles, guiding symmetric cell division. To investigate the robustness of the pattern formation, the researchers genetically engineered E. coli to enable them to control the gene expression, and thus the cellular concentrations, of the proteins MinD and MinE independently of each other. After that, they studied the pattern formation in various protein concentrations and used methods from statistical physics to analyze the data.
Buffer through conformational changes
“Our investigations revealed that the oscillations are impressively robust even at changes in concentration exceeding one order of magnitude,” says Henrik Weyer, one of the lead authors of the study. “Moreover, the wavelength of the oscillations remained remarkably constant.” In spite of this, the bacterium seems to be very economical with its resources and to produce only so much of each protein as is necessary to trigger and maintain the oscillations.
From these results, the researchers developed a theoretical model based on biochemical reactions, which is able to explain all experimental observations. Crucially, the model incorporates conformational changes to the MinE protein. “The latent state forms a reservoir that switches to the active state and back again as required and maintains the stability of the pattern formation,” says Frey. These findings were possible only through a combination of biophysical modeling and cell-physiological methods, emphasizes the biophysicist, who is also a member of the ORIGINS Excellence Cluster. “Our results furnish important insights into the principles of dynamic pattern formation and could also lead to exciting new findings for other biological questions.”
Publication: Ziyuan Ren, Henrik Weyer, Laeschkir Würthner, Dongyang Li, Cindy Sou, Daniel Villarreal, Erwin Frey, Suckjoon Jun: "Robust and resource-optimal dynamic pattern formation of Min proteins in vivo". Nature Physics
Contact:
Prof. Dr. Erwin Frey
Ludwig-Maximilians-Universität München / ORIGINS Excellence Cluster
email: frey(at)lmu.de
