title: Intrinsic fluctuations, robustness, and tunability in signaling cycles.
abstract: Covalent modification cycles (e.g., phosphorylation-dephosphorylation) underlie most cellular signaling and control processes. Low molecular copy number, arising from compartmental segregation and slow diffusion between compartments, potentially renders these cycles vulnerable to intrinsic chemical fluctuations. How can a cell operate reliably in the presence of this inherent stochasticity? How do changes in extrinsic parameters lead to variability of response? Can cells exploit these parameters to tune cycles to different ranges of stimuli? We study the dynamics of an isolated phosphorylation cycle. Our model shows that the cycle transmits information reliably if it is tuned to an optimal parameter range, despite intrinsic fluctuations and even for small input signal amplitudes. At the same time, the cycle is sensitive to changes in the concentration and activity of kinases and phosphatases. This sensitivity can lead to significant cell-to-cell response variability. It also provides a mechanism to tune the cycle to transmit signals in various amplitude ranges. Our results show that signaling cycles possess a surprising combination of robustness and tunability. This combination makes them ubiquitous in eukaryotic signaling, optimizing signaling in the presence of fluctuations using their inherent flexibility. On the other hand, cycles tuned to suppress intrinsic fluctuations can be vulnerable to changes in the number and activity of kinases and phosphatases. Such trade-offs in robustness to intrinsic and extrinsic fluctuations can influence the evolution of signaling cascades, making them the weakest links in cellular circuits.
authors.affiliation: Computation and Neural Systems Option, California Institute of Technology, Pasadena, California, USA.
authors.forename: Joseph
authors.initials: J
authors.lastname: Levine
authors.forename: Hao Yuan
authors.initials: HY
authors.lastname: Kueh
authors.forename: Leonid
authors.initials: L
authors.lastname: Mirny
mesh_terms: D001683:Biological Clocks / Q000502:physiology*; D003198:Computer Simulation; D005246:Feedback / Q000502:physiology*; D008954:Models, Biological; D015233:Models, Statistical; D009991:Oscillometry / Q000379:methods*; D010766:Phosphorylation; D010770:Phosphotransferases / Q000378:metabolism*; D015398:Signal Transduction / Q000502:physiology*; D013269:Stochastic Processes
chemical_list: D010770:Phosphotransferases