A yeast cell cycle model integrating stress, signaling, and physiology.

The cell division cycle in eukaryotic cells is a series of highly coordinated molecular interactions that ensure that cell growth, duplication of genetic material, and actual cell division are precisely orchestrated to give rise to two viable progeny cells. Moreover, the cell cycle machinery is responsible for incorporating information about external cues or internal processes that the cell must keep track of to ensure a coordinated, timely progression of all related processes. This is most pronounced in multicellular organisms, but also a cardinal feature in model organisms such as baker's yeast. The complex and integrative behavior is difficult to grasp and requires mathematical modeling to fully understand the quantitative interplay of the single components within the entire system. Here, we present a self-oscillating mathematical model of the yeast cell cycle that comprises all major cyclins and their main regulators. Furthermore, it accounts for the regulation of the cell cycle machinery by a series of external stimuli such as mating pheromones and changes in osmotic pressure or nutrient quality. We demonstrate how the external perturbations modify the dynamics of cell cycle components and how the cell cycle resumes after adaptation to or relief from stress.

Signaling pathways in context.

The last decade has seen a rise in the development of methods and models to analyze cellular networks on all levels. The applications of this knowledge are, however, often confined to specifics of the network in concrete conditions and leveraging it is hampered by the lack of information about this context and its implications on the system. While not all cellular networks have been deciphered yet, even for well-studied networks their versatility in different contexts is barely considered. Here, we focus on challenges and potentials when integrating signaling networks into their encompassing structures. We highlight three different consequences of this process: a) its fundamental importance for whole-cell and large-scale models, b) significant changes in contextual behavior imposed on entire systems by genetic variations, and c) species-specific conservation or divergence of signaling motifs can give important clues on how to handle cellular context. While important studies have been conducted on these topics to some extent, an increased focus on developing and exploiting solutions for integrative contextualization should turn out as a fruitful path for both theoretical and experimental research.

Interaction Dynamics Determine Signaling and Output Pathway Responses.

The understanding of interaction dynamics in signaling pathways can shed light on pathway architecture and provide insights into targets for intervention. Here, we explored the relevance of kinetic rate constants of a key upstream osmosensor in the yeast high-osmolarity glycerol-mitogen-activated protein kinase (HOG-MAPK) pathway to signaling output responses. We created mutant pairs of the Sln1-Ypd1 complex interface that caused major compensating changes in the association (kon) and dissociation (koff) rate constants (kinetic perturbations) but only moderate changes in the overall complex affinity (Kd). Yeast cells carrying a Sln1-Ypd1 mutant pair with moderate increases in kon and koff displayed a lower threshold of HOG pathway activation than wild-type cells. Mutants with higher kon and koff rates gave rise to higher basal signaling and gene expression but impaired osmoadaptation. Thus, the kon and koff rates of the components in the Sln1 osmosensor determine proper signaling dynamics and osmoadaptation.

Information processing in the adaptation of Saccharomyces cerevisiae to osmotic stress: an analysis of the phosphorelay system.

Cellular signaling is key for organisms to survive immediate stresses from fluctuating environments as well as relaying important information about external stimuli. Effective mechanisms have evolved to ensure appropriate responses for an optimal adaptation process. For them to be functional despite the noise that occurs in biochemical transmission, the cell needs to be able to infer reliably what was sensed in the first place. For example Saccharomyces cerevisiae are able to adjust their response to osmotic shock depending on the severity of the shock and initiate responses that lead to near perfect adaptation of the cell. We investigate the Sln1-Ypd1-Ssk1-phosphorelay as a module in the high-osmolarity glycerol pathway by incorporating a stochastic model. Within this framework, we can imitate the noisy perception of the cell and interpret the phosphorelay as an information transmitting channel in the sense of C.E. Shannon's "Information Theory". We refer to the channel capacity as a measure to quantify and investigate the transmission properties of this system, enabling us to draw conclusions on viable parameter sets for modeling the system.