Superstability of the yeast cell-cycle dynamics: Ensuring causality in the presence of biochemical stochasticity

Abstract

Gene regulatory dynamics is governed by molecular processes and therefore exhibits an inherent stochasticity. However, for the survival of an organism it is a strict necessity that this intrinsic noise does not prevent robust functioning of the system. It is still an open question how dynamical stability is achieved in biological systems despite the omnipresent fluctuations. In this paper we investigate the cell-cycle of the budding yeast Saccharomyces cerevisiae as an example of a wellstudied organism.We study a genetic network model of eleven genes that coordinate the cell-cycle dynamics using a modeling framework which generalizes the concept of discrete threshold dynamics. By allowing for fluctuations in the transcription/translation times, we introduce noise in the model, accounting for the effects of biochemical stochasticity. We study the dynamical attractor of the cell cycle and find a remarkable robustness against fluctuations of this kind. We identify mechanisms that ensure reliability in spite of fluctuations: 'Catcher' states and persistence of activity levels contribute significantly to the stability of the yeast cell cycle despite the inherent stochasticity.

Boolean network models of cellular regulation: prospects and limitations

“…On the other hand, phases with multiple flips among the nodes can in principle desynchronize the system. With noisy Boolean networks at hand, we are now able to make a double check, which indeed has been done (Braunewell & Bornholdt 2006) by reformulating the model by Li et al (2004) in terms of noisy Boolean nets. The result of this test is that the correct control sequence emerges from the network, even in the presence of strong noise.…”

Transcriptional Control of the Plant Cell Cycle

“…Recent studies of the budding and fission yeast cell cycle (Bähler 2005) and of factors that contribute to robustness of the cell cycle (Li et al 2004;Jensen et al 2006;Braunewell and Bornholdt 2007), lead me to propose a different view of the relation between the distinct regulatory mechanisms that in concert mediate cell cycle control. Such studies reveal that these mechanisms are coupled by regulatory interactions, for example: cell cycle phase-specific expression of individual cyclins conditions high-level CDK activity at specific times, which in turn controls the activity of the proteasome that regulates the stability of cell cycle transcription factors.…”

Cellular Automata on Graphs: Topological Properties of ER Graphs Evolved towards Low-Entropy Dynamics

“…Such analyses can elucidate dynamic properties also relevant for regulatory dynamics of biological networks, which have been successfully modeled with CA approaches (see, e.g., [61,62]). From this perspective, our framework provides a means to comprehensively study the sensitivity of a system to topological perturbations and associated rule space modifications.…”