Ca(2+) is a ubiquitous intracellular messenger that regulates diverse cellular activities. Extracellular stimuli often evoke sequences of intracellular Ca(2+) spikes, and spike frequency may encode stimulus intensity. However, the timing of spikes within a cell is random because each interspike interval has a large stochastic component. In human embryonic kidney (HEK) 293 cells and rat primary hepatocytes, we found that the average interspike interval also varied between individual cells. To evaluate how individual cells reliably encoded stimuli when Ca(2+) spikes exhibited such unpredictability, we combined Ca(2+) imaging of single cells with mathematical analyses of the Ca(2+) spikes evoked by receptors that stimulate formation of inositol 1,4,5-trisphosphate (IP3). This analysis revealed that signal-to-noise ratios were improved by slow recovery from feedback inhibition of Ca(2+) spiking operating at the whole-cell level and that they were robust against perturbations of the signaling pathway. Despite variability in the frequency of Ca(2+) spikes between cells, steps in stimulus intensity caused the stochastic period of the interspike interval to change by the same factor in all cells. These fold changes reliably encoded changes in stimulus intensity, and they resulted in an exponential dependence of average interspike interval on stimulation strength. We conclude that Ca(2+) spikes enable reliable signaling in a cell population despite randomness and cell-to-cell variability, because global feedback reduces noise, and changes in stimulus intensity are represented by fold changes in the stochastic period of the interspike interval.

The dynamin-related Eps15-homology domain-containing protein 2 (EHD2) is a membrane remodeling ATPase that regulates the dynamics of caveolae. Here, we established an electron paramagnetic resonance (EPR) approach to characterize structural features of membrane-bound EHD2. We show that residues at the tip of the helical domain can insert into the membrane and may create membrane curvature by a wedging mechanism. Using EPR and X-ray crystallography, we found that the N-terminus is folded into a hydrophobic pocket of the GTPase domain in solution and can be released into the membrane. Cryo electron microscopy demonstrated that the N-terminus is not essential for oligomerization of EHD2 into a membrane-anchored scaffold. Instead, we found a function of the N-terminus in regulating targeting and stable association of EHD2 to caveolae. Our data uncover an unexpected, membrane-induced regulatory switch in EHD2 and demonstrate the versatility of EPR to study structure and function of dynamin superfamily proteins.

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Cellular signaling systems precisely transmit information in the presence of molecular noise while retaining flexibility to accommodate the needs of individual cells. To understand design principles underlying such versatile signaling, we analyzed the response of the tumor suppressor p53 to varying levels of DNA damage in hundreds of individual cells and observed a switch between distinct signaling modes characterized by isolated pulses and sustained oscillations of p53 accumulation. Guided by dynamic systems theory we show that this requires an excitable network structure comprising positive feedback and provide experimental evidence for its molecular identity. The resulting data-driven model reproduced all features of measured signaling responses and is sufficient to explain their heterogeneity in individual cells. We present evidence that heterogeneity in the levels of the feedback regulator Wip1 sets cell-specific thresholds for p53 activation, providing means to modulate its response through interacting signaling pathways. Our results demonstrate how excitable signaling networks can provide high specificity, sensitivity and robustness while retaining unique possibilities to adjust their function to the physiology of individual cells.To ensure reliable information processing, cellular signaling systems need to faithfully sense inputs in noisy environments while maintaining the flexibility to adjust their function to different physiologies. A commonly observed strategy to enable robust signal detection is the pulsed activation of signaling pathways in a digital-like response 1 . To understand how pulsatile dynamics can mediate robust yet versatile signal processing, it is necessary to identify the design principles that enable molecular networks to switch between different dynamic states and the mechanisms that allow modulation of their activity.A well-known example of a pulsatile signaling pathway in mammalian cells is the tumor suppressor p53. As a central hub of the cellular stress response, p53 maintains genomic integrity in proliferating cells and during tissue homeostasis 2 . In healthy cells, p53 levels are low due to poly-ubiquitination by the E3-ligase Mdm2 and subsequent proteasomal degradation 3,4 . Upon stress, p53 is activated by kinases that serve as primary damage sensors. One particularly dangerous insult is DNA damage in the form of double strand breaks (DSB), which may cause genomic rearrangements such as translocations, deletions and chromosome fusions. The primary sensor for DSBs is the PI3K-like kinase ataxia telangiectasia mutated (ATM) 5 , which gets phosphorylated and activated within minutes after damage induction 6 . Active ATM then stabilizes p53 by at least two distinct mechanisms: it phosphorylates Mdm2, which induces its auto-ubiquitination and subsequent degradation 7 , and p53, which interferes with Mdm2 binding 8,9 . As a consequence, p53 accumulates in the nucleus, where it acts as a transcription factor activating the expression of hundreds of target genes 10 .A key feature ...

Important biological processes like cell signalling and gene expression have noisy components and are very complex at the same time. Mathematical analysis of such systems has often been limited to the study of isolated subsystems, or approximations are used that are difficult to justify. Here we extend a recently published method (Thurley and Falcke, PNAS 2011) which is formulated in observable system configurations instead of molecular transitions. This reduces the number of system states by several orders of magnitude and avoids fitting of kinetic parameters. The method is applied to signalling. is a ubiquitous second messenger transmitting information by stochastic sequences of concentration spikes, which arise by coupling of subcellular release events (puffs). We derive analytical expressions for a mechanistic model, based on recent data from live cell imaging, and calculate spike statistics in dependence on cellular parameters like stimulus strength or number of channels. The new approach substantiates a generic model, which is a very convenient way to simulate spike sequences with correct spiking statistics.