In mammals, the circadian pacemaker, which controls daily rhythms, is located in the suprachiasmatic nucleus (SCN). Circadian oscillations are generated in individual SCN neurons by a molecular regulatory network. Cells oscillate with periods ranging from 20 to 28 h, but at the tissue level, SCN neurons display significant synchrony, suggesting a robust intercellular coupling in which neurotransmitters are assumed to play a crucial role. We present a dynamical model for the coupling of a population of circadian oscillators in the SCN. The cellular oscillator, a three-variable model, describes the core negative feedback loop of the circadian clock. The coupling mechanism is incorporated through the global level of neurotransmitter concentration. Global coupling is efficient to synchronize a population of 10,000 cells. Synchronized cells can be entrained by a 24-h light-dark cycle. Simulations of the interaction between two populations representing two regions of the SCN show that the driven population can be phase-leading. Experimentally testable predictions are: 1), phases of individual cells are governed by their intrinsic periods; and 2), efficient synchronization is achieved when the average neurotransmitter concentration would dampen individual oscillators. However, due to the global neurotransmitter oscillation, cells are effectively synchronized.

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Cellular signalling networks integrate environmental stimuli with the information on cellular status. These networks must be robust against stochastic fluctuations in stimuli as well as in the amounts of signalling components. Here, we challenge the yeast HOG signal-transduction pathway with systematic perturbations in components' expression levels under various external conditions in search for nodes of fragility. We observe a substantially higher frequency of fragile nodes in this signal-transduction pathway than that has been observed for other cellular processes. These fragilities disperse without any clear pattern over biochemical functions or location in pathway topology and they are largely independent of pathway activation by external stimuli. However, the strongest toxicities are caused by pathway hyperactivation. In silico analysis highlights the impact of model structure on in silico robustness, and suggests complex formation and scaffolding as important contributors to the observed fragility patterns. Thus, in vivo robustness data can be used to discriminate and improve mathematical models.

A complex signalling network governs the response of Saccharomyces cerevisiae to an array of environmental stimuli and stresses. In the present article, we provide an overview of the main signalling system and discuss the mechanisms by which yeast integrates and separates signals from these sources. We apply our classification scheme to a simple semi-quantitative model of the HOG (high-osmolarity glycerol)/FG (filamentous growth)/PH (pheromone) MAPK (mitogen-activated protein kinase) signalling network by perturbing its signal integration mechanisms under combinatorial stimuli of osmotic stress, starvation and pheromone exposure in silico. Our findings include that the Hog1 MAPK might act as a timer for filamentous differentiation, not allowing morphological differentiation before osmo-adaptation is sufficiently completed. We also see that a mutually exclusive decision-making between pheromone and osmo-response might not be taken on the MAPK level and transcriptional regulation of MAPK targets. We conclude that signal integration mechanisms in a wider network including the cell cycle have to be taken into account for which our framework might provide focal points of study.

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