Dynamic properties of signaling pathways control their behavior and function. We undertook an iterative computational and experimental investigation of the dynamic properties of tumor necrosis factor (TNF)␣-mediated activation of the transcription factor NF-B. Surprisingly, we found that the temporal profile of the NF-B activity is invariant to the TNF␣ dose. We reverse engineered a computational model of the signaling pathway to identify mechanisms that impart this important response characteristic, thus predicting that the IKK activity profile must transiently peak at all TNF␣ doses to generate the observed NF-B dynamics. Experimental confirmation of this prediction emphasizes the importance of mechanisms that rapidly down-regulate IKK following TNF␣ activation. A refined computational model further revealed signaling characteristics that ensure robust TNF␣-mediated cell-cell communication over considerable distances, allowing for fidelity of cellular inflammatory responses in infected tissue.The transcription factor NF-B 3 is a key mediator of physiologic processes such as inflammation and adaptive immunity and has been implicated in numerous pathologic states such as cancer, rheumatoid arthritis, and sepsis (1). Consequently, understanding the mechanisms of NF-B activation and regulation is of prime importance. One major activator of NF-B is the potent inflammatory cytokine TNF␣. TNF␣ binds to and trimerizes its receptor, TNFR1, which leads to a receptorassociated signalosome that activates the kinase IKK (2). IKK phosphorylates IB proteins, which normally sequester NF-B in the cytoplasm; phosphorylated IBs are rapidly polyubiquitinated and proteasomally degraded, releasing free NF-B, which translocates to the nucleus and modulates gene expression (2).Detailed biochemical and genetic analyses over the past 25 years have helped elucidate the components that connect TNF␣ to NF-B. However, relatively little is known about how these molecular players act together as a signaling system, whose complex dynamics control the time-variable activity of NF-B and subsequent gene expression (3-6).Recently, it has become apparent that analysis of the systems properties of complex biochemical pathways can benefit from an integrated approach combining systematic experimental perturbations with an associated computational analysis of molecular interactions (5, 7, 8, 10 -13). This type of analysis applied to TNF␣-induced NF-B activity demonstrated that the ␣, ␤, and ⑀ isoforms of IB cooperate to produce a biphasic NF-B response (5). Varying the duration of the TNF␣ stimulus had no effect on the duration of the initial response, thus ensuring expression of some NF-B-regulated genes even in response to very short stimuli (5). This analysis, however, did not address the question of how other types of signaling inputs are processed.In this study, we analyze in detail a different type of inputs, constant stimulations at different TNF␣ doses, and experimentally and computationally analyze the resulting pathway characteristics. Surp...

The complex transition from a single-cell to a multicellular life form during the formation of a fruiting body by the amoeba Dictyostelium discoideum is accompanied by a pulsatile collective signaling process that instigates chemotaxis of the constituent cells. Although the cells used for the analysis of this phenomenon are normally genetically identical (isogenic), it is not clear whether they are equally responsive to the waves of the signaling stimulus, nor is it clear how responses across the population influence collective cell behavior. Here, we found that isogenic Dictyostelium cells displayed differing sensitivities to the chemoattractant cyclic adenosine monophosphate (cAMP). Furthermore, the resulting signaling responses could be explained by a model in which cells are refractory to further stimulation for 5 to 6 min after the initial input and the signaling output is amplified, with the amplification threshold varying across the cells in the population. This pathway structure could explain intracellular amplification of the chemoattractant gradient during cell migration. The new model predicts that diverse cell responsiveness can facilitate collective cell behavior, specifically due to the presence of a small number of cells in the population with increased responsiveness that aid in propagating the initial cAMP signaling wave across the cell population.

SUMMARY Signal transduction networks can display complex dynamic behavior such as oscillations in the activity of key components [1-6], but it is often unclear if such dynamic complexity is actually important for the network's regulatory functions [7, 8]. Here we found that the mitogen-activated protein kinase (MAPK) Fus3, a key regulator of the yeast mating pheromone response undergoes sustained oscillations in its phosphorylation/activation state during continuous pheromone exposure. These MAPK activity oscillations led to corresponding oscillations in mating gene expression. Oscillations in MAPK activity and gene expression required the negative regulator of G-protein signaling Sst2, and partially required the MAPK phosphatase Msg5. Peaks in Fus3 activation correlated with periodic rounds of cell morphogenesis, with each peak preceding the formation of an additional mating projection. Preventing projection formation did not eliminate MAPK oscillation, but preventing MAPK oscillation blocked the formation of additional projections. A mathematical model was developed that reproduced several features of the observed oscillatory dynamics. These observations demonstrate a role for MAPK activity oscillation in driving a periodic downstream response, and explain how the pheromone signaling pathway, previously thought to desensitize after 1-3 hours, controls morphology changes that continue for a much longer time.

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Motivation-Progress in systems biology depends on developing scalable informatics tools to predictively model, visualize, and flexibly store information about complex biological systems. Scalability of these tools, as well as their ability to integrate within larger frameworks of evolving tools, is critical to address the multi-scale and size complexity of biological systems.