A Minimal Model of Signaling Network Elucidates Cell-to-Cell Stochastic Variability in Apoptosis

Signaling networks are designed to sense an environmental stimulus and adapt to it. We propose and study a minimal model of signaling network that can sense and respond to external stimuli of varying strength in an adaptive manner. The structure of this minimal network is derived based on some simple assumptions on its differential response to external stimuli. We employ stochastic differential equations and probability distributions obtained from stochastic simulations to characterize differential signaling response in our minimal network model. We show that the proposed minimal signaling network displays two distinct types of response as the strength of the stimulus is decreased. The signaling network has a deterministic part that undergoes rapid activation by a strong stimulus in which case cell-to-cell fluctuations can be ignored. As the strength of the stimulus decreases, the stochastic part of the network begins dominating the signaling response where slow activation is observed with characteristic large cell-to-cell stochastic variability. Interestingly, this proposed stochastic signaling network can capture some of the essential signaling behaviors of a complex apoptotic cell death signaling network that has been studied through experiments and large-scale computer simulations. Thus we claim that the proposed signaling network is an appropriate minimal model of apoptosis signaling. Elucidating the fundamental design principles of complex cellular signaling pathways such as apoptosis signaling remains a challenging task. We demonstrate how our proposed minimal model can help elucidate the effect of a specific apoptotic inhibitor Bcl-2 on apoptotic signaling in a cell-type independent manner. We also discuss the implications of our study in elucidating the adaptive strategy of cell death signaling pathways.Comment: 9 pages, 6 figure

Essential versus accessory aspects of cell death: recommendations of the NCCD 2015

Cells exposed to extreme physicochemical or mechanical stimuli die in an uncontrollable manner, as a result of their immediate structural breakdown. Such an unavoidable variant of cellular demise is generally referred to as ‘accidental cell death’ (ACD). In most settings, however, cell death is initiated by a genetically encoded apparatus, correlating with the fact that its course can be altered by pharmacologic or genetic interventions. ‘Regulated cell death’ (RCD) can occur as part of physiologic programs or can be activated once adaptive responses to perturbations of the extracellular or intracellular microenvironment fail. The biochemical phenomena that accompany RCD may be harnessed to classify it into a few subtypes, which often (but not always) exhibit stereotyped morphologic features. Nonetheless, efficiently inhibiting the processes that are commonly thought to cause RCD, such as the activation of executioner caspases in the course of apoptosis, does not exert true cytoprotective effects in the mammalian system, but simply alters the kinetics of cellular demise as it shifts its morphologic and biochemical correlates. Conversely, bona fide cytoprotection can be achieved by inhibiting the transduction of lethal signals in the early phases of the process, when adaptive responses are still operational. Thus, the mechanisms that truly execute RCD may be less understood, less inhibitable and perhaps more homogeneous than previously thought. Here, the Nomenclature Committee on Cell Death formulates a set of recommendations to help scientists and researchers to discriminate between essential and accessory aspects of cell death

Ultrahigh specificity in a network of computationally designed protein-interaction pairs

Protein networks in all organisms comprise homologous interacting pairs. In these networks, some proteins are specific, interacting with one or a few binding partners, whereas others are multispecific and bind a range of targets. We describe an algorithm that starts from an interacting pair and designs dozens of new pairs with diverse backbone conformations at the binding site as well as new binding orientations and sequences. Applied to a high-affinity bacterial pair, the algorithm results in 18 new ones, with cognate affinities from pico- to micromolar. Three pairs exhibit 3-5 orders of magnitude switch in specificity relative to the wild type, whereas others are multispecific, collectively forming a protein-interaction network. Crystallographic analysis confirms design accuracy, including in new backbones and polar interactions. Preorganized polar interaction networks are responsible for high specificity, thus defining design principles that can be applied to program synthetic cellular interaction networks of desired affinity and specificity

Tuning hardness in calcite by incorporation of amino acids

Structural biominerals are inorganic/organic composites that exhibit remarkable mechanical properties. However, the structure–property relationships of even the simplest building unit—mineral single crystals containing embedded macromolecules—remain poorly understood. Here, by means of a model biomineral made from calcite single crystals containing glycine (0–7 mol%) or aspartic acid (0–4 mol%), we elucidate the origin of the superior hardness of biogenic calcite. We analysed lattice distortions in these model crystals by using X-ray diffraction and molecular dynamics simulations, and by means of solid-state nuclear magnetic resonance show that the amino acids are incorporated as individual molecules. We also demonstrate that nanoindentation hardness increased with amino acid content, reaching values equivalent to their biogenic counterparts. A dislocation pinning model reveals that the enhanced hardness is determined by the force required to cut covalent bonds in the molecules

Exploring the Contextual Sensitivity of Factors that Determine Cell-to-Cell Variability in Receptor-Mediated Apoptosis

Stochastic fluctuations in gene expression give rise to cell-to-cell variability in protein levels which can potentially cause variability in cellular phenotype. For TRAIL (TNF-related apoptosis-inducing ligand) variability manifests itself as dramatic differences in the time between ligand exposure and the sudden activation of the effector caspases that kill cells. However, the contribution of individual proteins to phenotypic variability has not been explored in detail. In this paper we use feature-based sensitivity analysis as a means to estimate the impact of variation in key apoptosis regulators on variability in the dynamics of cell death. We use Monte Carlo sampling from measured protein concentration distributions in combination with a previously validated ordinary differential equation model of apoptosis to simulate the dynamics of receptor-mediated apoptosis. We find that variation in the concentrations of some proteins matters much more than variation in others and that precisely which proteins matter depends both on the concentrations of other proteins and on whether correlations in protein levels are taken into account. A prediction from simulation that we confirm experimentally is that variability in fate is sensitive to even small increases in the levels of Bcl-2. We also show that sensitivity to Bcl-2 levels is itself sensitive to the levels of interacting proteins. The contextual dependency is implicit in the mathematical formulation of sensitivity, but our data show that it is also important for biologically relevant parameter values. Our work provides a conceptual and practical means to study and understand the impact of cell-to-cell variability in protein expression levels on cell fate using deterministic models and sampling from parameter distributions

Human Cell Chips: Adapting DNA Microarray Spotting Technology to Cell-Based Imaging Assays

Here we describe human spotted cell chips, a technology for determining cellular state across arrays of cells subjected to chemical or genetic perturbation. Cells are grown and treated under standard tissue culture conditions before being fixed and printed onto replicate glass slides, effectively decoupling the experimental conditions from the assay technique. Each slide is then probed using immunofluorescence or other optical reporter and assayed by automated microscopy. We show potential applications of the cell chip by assaying HeLa and A549 samples for changes in target protein abundance (of the dsRNA-activated protein kinase PKR), subcellular localization (nuclear translocation of NFκB) and activation state (phosphorylation of STAT1 and of the p38 and JNK stress kinases) in response to treatment by several chemical effectors (anisomycin, TNFα, and interferon), and we demonstrate scalability by printing a chip with ∼4,700 discrete samples of HeLa cells. Coupling this technology to high-throughput methods for culturing and treating cell lines could enable researchers to examine the impact of exogenous effectors on the same population of experimentally treated cells across multiple reporter targets potentially representing a variety of molecular systems, thus producing a highly multiplexed dataset with minimized experimental variance and at reduced reagent cost compared to alternative techniques. The ability to prepare and store chips also allows researchers to follow up on observations gleaned from initial screens with maximal repeatability

Contrasting effects of nitric oxide and corticotropin- releasing factor within the dorsal periaqueductal gray on defensive behavior and nociception in mice

The anxiogenic and antinociceptive effects produced by glutamate N-methyl-D-aspartate receptor activation within the dorsal periaqueductal gray (dPAG) matter have been related to nitric oxide (NO) production, since injection of NO synthase (NOS) inhibitors reverses these effects. dPAG corticotropin-releasing factor receptor (CRFr) activation also induces anxiety-like behavior and antinociception, which, in turn, are selectively blocked by local infusion of the CRF type 1 receptor (CRFr1) antagonist, NBI 27914 [5-chloro-4-(N-(cyclopropyl)methyl-N-propylamino)-2-methyl-6-(2,4,6-trichlorophenyl)aminopyridine]. Here, we determined whether i) the blockade of the dPAG by CRFr1 attenuates the anxiogenic/antinociceptive effects induced by local infusion of the NO donor, NOC-9 [6-(2-hydroxy-1-methyl-2-nitrosohydrazino)-N-methyl-1-hexanamine], and ii) the anxiogenic/antinociceptive effects induced by intra-dPAG CRF are prevented by local infusion of N(ω)-propyl-L-arginine (NPLA), a neuronal NOS inhibitor, in mice. Male Swiss mice (12 weeks old, 25-35 g, N = 8-14/group) were stereotaxically implanted with a 7-mm cannula aimed at the dPAG. Intra-dPAG NOC-9 (75 nmol) produced defensive-like behavior (jumping and running) and antinociception (assessed by the formalin test). Both effects were reversed by prior local infusion of NBI 27914 (2 nmol). Conversely, intra-dPAG NPLA (0.4 nmol) did not modify the anxiogenic/antinociceptive effects of CRF (150 pmol). These results suggest that CRFr1 plays an important role in the defensive behavior and antinociception produced by NO within the dPAG. In contrast, the anxiogenic and antinociceptive effects produced by intra-dPAG CRF are not related to NO synthesis in this limbic midbrain structure

Intergenerational trauma in the occupied Palestinian territories:Effect on children and promotion of healing

Addressing a gap in the trauma recovery literature, the current study seeks to deepen understanding and encourage discussion of intergenerational trauma for Palestinian children living under military occupation. Differing definitions of intergenerational trauma and the plethora of terms used to describe children's traumatic experiences are explored. A historico-political and social context analysis is applied to understanding the creation and maintenance of intergenerational trauma in the occupied Palestinian territories. The cumulative impact of historical and collective trauma and loss, and daily humiliation on children's symptoms are analyzed using a developmental trauma framework. Effective healing of intergenerational trauma is then set within cultural beliefs and the formation of identity. Finally, a framework for shaping future research isproposed.<br/

Modeling the TNFα-Induced Apoptosis Pathway in Hepatocytes

The proinflammatory cytokine TNFα fails to provoke cell death in isolated hepatocytes but has been implicated in hepatocyte apoptosis during liver diseases associated with chronic inflammation. Recently, we showed that TNFα is able to sensitize primary murine hepatocytes cultured on collagen to Fas ligand-induced apoptosis and presented a mathematical model of the sensitizing effect. Here, we analyze how TNFα induces apoptosis in combination with the transcriptional inhibitor actinomycin D (ActD). Accumulation of reactive oxygen species (ROS) in response to TNFR activation turns out to be critical for sustained activation of JNK which then triggers mitochondrial pathway-dependent apoptosis. In addition, the amount of JNK is strongly upregulated in a ROS-dependent way. In contrast to TNFα plus cycloheximide no cFLIP degradation is observed suggesting a different apoptosis pathway in which the Itch-mediated cFLIP degradation and predominantly caspase-8 activation is not involved. Time-resolved data of the respective pro- and antiapoptotic factors are obtained and subjected to mathematical modeling. On the basis of these data we developed a mathematical model which reproduces the complex interplay regulating the phosphorylation status of JNK and generation of ROS. This model was fully integrated with our model of TNFα/Fas ligand sensitizing as well as with a published NF-κB-model. The resulting comprehensive model delivers insight in the dynamical interplay between the TNFα and FasL pathways, NF-κB and ROS and gives an example for successful model integration