Criticality and Adaptivity in Enzymatic Networks.
The contrast between the stochasticity of biochemical networks and the regularity of cellular behavior suggests that biological networks generate robust behavior from noisy constituents. Identifying the mechanisms that confer this ability on biological networks is essential to understanding cells. Here we show that queueing for a limited shared resource in broad classes of enzymatic networks in certain conditions leads to a critical state characterized by strong and long-ranged correlations between molecular species. An enzymatic network reaches this critical state when the input flux of its substrate is balanced by the maximum processing capacity of the network. We then consider enzymatic networks with adaptation, when the limiting resource (enzyme or cofactor) is produced in proportion to the demand for it. We show that the critical state becomes an attractor for these networks, which points toward the onset of self-organized criticality. We suggest that the adaptive queueing motif that leads to significant correlations between multiple species may be widespread in biological systems.
BioCircuits Institute, University of California, San Diego, La Jolla, California.
Paul J
PJ
Steiner
BioCircuits Institute, University of California, San Diego, La Jolla, California; Department of Mathematics, University of California, San Diego, La Jolla, California. Electronic address: williams@math.ucsd.edu.
Ruth J
RJ
Williams
BioCircuits Institute, University of California, San Diego, La Jolla, California; Molecular Biology Section, Division of Biological Sciences, University of California, San Diego, La Jolla, California; Department of Bioengineering, University of California, San Diego, La Jolla, California; San Diego Center for Systems Biology, University of California, San Diego, La Jolla, California. Electronic address: hasty@ucsd.edu.
Jeff
J
Hasty
BioCircuits Institute, University of California, San Diego, La Jolla, California; San Diego Center for Systems Biology, University of California, San Diego, La Jolla, California. Electronic address: ltsimring@ucsd.edu.
Lev S
LS
Tsimring
D000465:Algorithms; D003198:Computer Simulation; D004798:Enzymes / Q000737:chemistry / Q000378:metabolism*; D008958:Models, Molecular; D013269:Stochastic Processes
D004798:Enzymes