Stochastic sequestration dynamics can act as intrinsic noise filter in signaling network motifs



The relation between design principles of signaling network motifs and their robustness against intrinsic noise still remains illusive. In this talk, I will summarize our recent investigation on the role of cascading for coping with intrinsic noise due to stochasticity in molecular reactions. We use stochastic modeling approaches to quantify fluctuations in the terminal kinase of phosphorylation-dephosphorylation cascade motifs and demonstrate that cascading highly affects these fluctuations. We show that this purely stochastic effect can be explained by time-varying sequestration of upstream kinase molecules. In particular, we discuss conditions on time scales and parameter regimes which lead to a reduction of output fluctuations. Our results are put into biological context by adapting rate parameters of our modeling approach to biologically feasible ranges for general binding-unbinding and phosphorylation-dephosphorylation mechanisms. Overall, this study reveals a novel role of stochastic sequestration for dynamic noise filtering in ubiquitous signaling motifs.