Decomposing Noise in Biochemical Signaling Systems Highlights the Role of Protein Degradation

Abstract

Stochasticity is an essential aspect of biochemical processes at the cellular level. We now know that living cells take advantage of stochasticity in some cases and counteract stochastic effects in others. Here we propose a method that allows us to calculate contributions of individual reactions to the total variability of a system's output. We demonstrate that reactions differ significantly in their relative impact on the total noise and we illustrate the importance of protein degradation on the overall variability for a range of molecular processes and signaling systems. With our flexible and generally applicable noise decomposition method, we are able to shed new, to our knowledge, light on the sources and propagation of noise in biochemical reaction networks; in particular, we are able to show how regulated protein degradation can be employed to reduce the noise in biochemical systems.

Steady-state EB cap size fluctuations are determined by stochastic microtubule growth and maturation

“…In the linear noise approximation (33) (LNA) we can write an instantaneous velocity as vðtÞ = v g + ξ v ðtÞ, where ξ v ðtÞ is a Gaussian white-noise term accounting for the stochasticity of the microtubule growth (30,32). The power in the noise term is proportional to the sum of the rates of the two Poisson processes of association and dissociation (11):…”

“…Intrinsic network noise has been extensively studied for gene expression and other biochemical networks (29)(30)(31)(32)(33)(34). The specific properties of the noise were often found to be of functional importance.…”

Information processing by simple molecular motifs and susceptibility to noise

“…The model represented in figure 5 was considered with different rates of dephosphorylation ( parameter v) and degradation of the active protein ( parameter m), which were previously shown to be the reactions that make the largest relative contributions to the variability in the abundance of the active protein [23]. For this system, we proceed as before and estimate the MI for the three noise scenarios between the three molecular species at steady state.…”

“…We consider the model used by Komorowski et al [23] to describe gene expression and activation of the protein product via reversible phosphorylation, where the kinase and phosphatase are assumed to be abundant and at constant activity levels.…”

“…In particular, we shall focus on noise and its impact on information processing in signal transduction [16,[22][23][24]. The concept of 'noisy channels' has been central to information theory since its conception [1], but in a molecular context, as outlined above, we are not necessarily able to separate between the channel and the transmitted message.…”