Cell shape and negative links in regulatory motifs together control spatial information flow in signaling networks

Mechanical and Systems Biology of Cancer

Mechanics and biochemical signaling are both often deregulated in cancer, leading toincreased cell invasiveness, proliferation, and survival. The dynamics and interactions of cytoskeletal components control basic mechanical properties, such as cell tension, stiffness, and engagement with the extracellular environment, which can lead to extracellular matrix remodeling. Intracellular mechanics can alter signaling and transcription factors, impacting cell decision making. Additionally, signaling from soluble and mechanical factors in the extracellular environment, such as substrate stiffness and ligand density, can modulate cytoskeletal dynamics. Computational models closely integrated with experimental support, incorporating cancer-specific parameters, can provide quantitative assessments and serve as predictive tools toward dissecting the feedback between signaling and mechanics and across multiple scales and domains in tumor progression.

The effect of cell geometry on polarization in budding yeast

The localization (or polarization) of proteins on the membrane during the mating of budding yeast (Saccharomyces cerevisiae) is an important model system for understanding simple pattern formation within cells. While there are many existing mathematical models of polarization, for both budding and mating, there are still many aspects of this process that are not well understood. In this paper we set out to elucidate the effect that the geometry of the cell can have on the dynamics of certain models of polarization. Specifically, we look at several spatial stochastic models of Cdc42 polarization that have been adapted from published models, on a variety of tip-shaped geometries, to replicate the shape change that occurs during the growth of the mating projection. We show here that there is a complex interplay between the dynamics of polarization and the shape of the cell. Our results show that while models of polarization can generate a stable polarization cap, its localization at the tip of mating projections is unstable, with the polarization cap drifting away from the tip of the projection in a geometry dependent manner. We also compare predictions from our computational results to experiments that observe cells with projections of varying lengths, and track the stability of the polarization cap. Lastly, we examine one model of actin polarization and show that it is unlikely, at least for the models studied here, that actin dynamics and vesicle traffic are able to overcome this effect of geometry.

Spatial modeling of the membrane-cytosolic interface in protein kinase signal transduction

The spatial architecture of signaling pathways and the interaction with cell size and morphology are complex, but little understood. With the advances of single cell imaging and single cell biology, it becomes crucial to understand intracellular processes in time and space. Activation of cell surface receptors often triggers a signaling cascade including the activation of membrane-attached and cytosolic signaling components, which eventually transmit the signal to the cell nucleus. Signaling proteins can form steep gradients in the cytosol, which cause strong cell size dependence. We show that the kinetics at the membrane-cytosolic interface and the ratio of cell membrane area to the enclosed cytosolic volume change the behavior of signaling cascades significantly. We suggest an estimate of average concentration for arbitrary cell shapes depending on the cell volume and cell surface area. The normalized variance, known from image analysis, is suggested as an alternative measure to quantify the deviation from the average concentration. A mathematical analysis of signal transduction in time and space is presented, providing analytical solutions for different spatial arrangements of linear signaling cascades. Quantification of signaling time scales reveals that signal propagation is faster at the membrane than at the nucleus, while this time difference decreases with the number of signaling components in the cytosol. Our investigations are complemented by numerical simulations of non-linear cascades with feedback and asymmetric cell shapes. We conclude that intracellular signal propagation is highly dependent on cell geometry and, thereby, conveys information on cell size and shape to the nucleus.

Basal Ganglia Neuromodulation Over Multiple Temporal and Structural Scales-Simulations of Direct Pathway MSNs Investigate the Fast Onset of Dopaminergic Effects and Predict the Role of Kv4.2

The basal ganglia are involved in the motivational and habitual control of motor and cognitive behaviors. Striatum, the largest basal ganglia input stage, integrates cortical and thalamic inputs in functionally segregated cortico-basal ganglia-thalamic loops, and in addition the basal ganglia output nuclei control targets in the brainstem. Striatal function depends on the balance between the direct pathway medium spiny neurons (D1-MSNs) that express D1 dopamine receptors and the indirect pathway MSNs that express D2 dopamine receptors. The striatal microstructure is also divided into striosomes and matrix compartments, based on the differential expression of several proteins. Dopaminergic afferents from the midbrain and local cholinergic interneurons play crucial roles for basal ganglia function, and striatal signaling via the striosomes in turn regulates the midbrain dopaminergic system directly and via the lateral habenula. Consequently, abnormal functions of the basal ganglia neuromodulatory system underlie many neurological and psychiatric disorders. Neuromodulation acts on multiple structural levels, ranging from the subcellular level to behavior, both in health and disease. For example, neuromodulation affects membrane excitability and controls synaptic plasticity and thus learning in the basal ganglia. However, it is not clear on what time scales these different effects are implemented. Phosphorylation of ion channels and the resulting membrane effects are typically studied over minutes while it has been shown that neuromodulation can affect behavior within a few hundred milliseconds. So how do these seemingly contradictory effects fit together? Here we first briefly review neuromodulation of the basal ganglia, with a focus on dopamine. We furthermore use biophysically detailed multi-compartmental models to integrate experimental data regarding dopaminergic effects on individual membrane conductances with the aim to explain the resulting cellular level dopaminergic effects. In particular we predict dopaminergic effects on Kv4.2 in D1-MSNs. Finally, we also explore dynamical aspects of the onset of neuromodulation effects in multi-scale computational models combining biochemical signaling cascades and multi-compartmental neuron models.

Phosphodiesterase Diversity and Signal Processing Within cAMP Signaling Networks

A large number of neuromodulators activate G-protein coupled receptors (GPCRs) and mediate their cellular actions via the regulation of intracellular cAMP, the small highly diffusible second messenger. In fact, in the same neuron several different GPCRs can regulate cAMP with seemingly identical timecourses that give rise to distinct signaling outcomes, suggesting that cAMP does not have equivalent access to all its downstream effectors and may exist within defined intracellular pools or domains. cAMP compartmentalization is the process that allows the neuron to differentially interpret these various intracellular cAMP signals into cellular response. The molecular mechanisms that give rise to cAMP compartmentalization are not fully understood, but it is thought that phosphodiesterases (PDEs), the enzymes that degrade cAMP, significantly contribute to this process. PDEs, as the sole mechanism of signal termination for cAMP, hold great promise as therapeutic targets for pathologies that are due to the dysregulation of intracellular cAMP signaling. Due to their diverse catalytic activity, regulation and localization each PDE subtype expressed in a given neuron may have a distinct role on downstream signaling.

Detection of phasic dopamine by D1 and D2 striatal medium spiny neurons

KEY POINTS

Brief dopamine events are critical actors of reward-mediated learning in the striatum; the intracellular cAMP-protein kinase A (PKA) response of striatal medium spiny neurons to such events was studied dynamically using a combination of biosensor imaging in mouse brain slices and in silico simulations. Both D1 and D2 medium spiny neurons can sense brief dopamine transients in the sub-micromolar range. While dopamine transients profoundly change cAMP levels in both types of medium spiny neurons, the PKA-dependent phosphorylation level remains unaffected in D2 neurons. At the level of PKA-dependent phosphorylation, D2 unresponsiveness depends on protein phosphatase-1 (PP1) inhibition by DARPP-32. Simulations suggest that D2 medium spiny neurons could detect transient dips in dopamine level.

ABSTRACT

The phasic release of dopamine in the striatum determines various aspects of reward and action selection, but the dynamics of the dopamine effect on intracellular signalling remains poorly understood. We used genetically encoded FRET biosensors in striatal brain slices to quantify the effect of transient dopamine on cAMP or PKA-dependent phosphorylation levels, and computational modelling to further explore the dynamics of this signalling pathway. Medium-sized spiny neurons (MSNs), which express either D1 or D2 dopamine receptors, responded to dopamine by an increase or a decrease in cAMP, respectively. Transient dopamine showed similar sub-micromolar efficacies on cAMP in both D1 and D2 MSNs, thus challenging the commonly accepted notion that dopamine efficacy is much higher on D2 than on D1 receptors. However, in D2 MSNs, the large decrease in cAMP level triggered by transient dopamine did not translate to a decrease in PKA-dependent phosphorylation level, owing to the efficient inhibition of protein phosphatase 1 by DARPP-32. Simulations further suggested that D2 MSNs can also operate in a 'tone-sensing' mode, allowing them to detect transient dips in basal dopamine. Overall, our results show that D2 MSNs may sense much more complex patterns of dopamine than previously thought.

Cell shape information is transduced through tension-independent mechanisms

The shape of a cell within tissues can represent the history of chemical and physical signals that it encounters, but can information from cell shape regulate cellular phenotype independently? Using optimal control theory to constrain reaction-diffusion schemes that are dependent on different surface-to-volume relationships, we find that information from cell shape can be resolved from mechanical signals. We used microfabricated 3-D biomimetic chips to validate predictions that shape-sensing occurs in a tension-independent manner through integrin β₃ signaling pathway in human kidney podocytes and smooth muscle cells. Differential proteomics and functional ablation assays indicate that integrin β₃ is critical in transduction of shape signals through ezrin–radixin–moesin (ERM) family. We used experimentally determined diffusion coefficients and experimentally validated simulations to show that shape sensing is an emergent cellular property enabled by multiple molecular characteristics of integrin β₃. We conclude that 3-D cell shape information, transduced through tension-independent mechanisms, can regulate phenotype.

It is not known whether the shape of a cell can regulate cellular phenotype independently. Here, the authors show that culturing kidney podocytes or smooth muscle cells on 3-D biomimetic surfaces results in phenotypic changes and that cell shape is sensed by integrin β₃ in a tension-independent manner.

cAMP Signals in Drosophila Motor Neurons Are Confined to Single Synaptic Boutons

The second messenger cyclic AMP (cAMP) plays an important role in synaptic plasticity. Although there is evidence for local control of synaptic transmission and plasticity, it is less clear whether a similar spatial confinement of cAMP signaling exists. Here, we suggest a possible biophysical basis for the site-specific regulation of synaptic plasticity by cAMP, a highly diffusible small molecule that transforms the physiology of synapses in a local and specific manner. By exploiting the octopaminergic system of Drosophila, which mediates structural synaptic plasticity via a cAMP-dependent pathway, we demonstrate the existence of local cAMP signaling compartments of micrometer dimensions within single motor neurons. In addition, we provide evidence that heterogeneous octopamine receptor localization, coupled with local differences in phosphodiesterase activity, underlies the observed differences in cAMP signaling in the axon, cell body, and boutons.

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Boutons, axon, and cell body are independent cAMP signaling compartments

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Receptors and PDEs are responsible for the compartmentalization of cAMP

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cAMP does not propagate from the bouton to the cell body

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Local cAMP increases provides a basis for site-specific control of synaptic plasticity

Systems biology of cellular membranes: a convergence with biophysics

Systems biology and systems medicine have played an important role in the last two decades in shaping our understanding of biological processes. While systems biology is synonymous with network maps and '-omics' approaches, it is not often associated with mechanical processes. Here, we make the case for considering the mechanical and geometrical aspects of biological membranes as a key step in pushing the frontiers of systems biology of cellular membranes forward. We begin by introducing the basic components of cellular membranes, and highlight their dynamical aspects. We then survey the functions of the plasma membrane and the endomembrane system in signaling, and discuss the role and origin of membrane curvature in these diverse cellular processes. We further give an overview of the experimental and modeling approaches to study membrane phenomena. We close with a perspective on the converging futures of systems biology and membrane biophysics, invoking the need to include physical variables such as location and geometry in the study of cellular membranes. WIREs Syst Biol Med 2017, 9:e1386. doi: 10.1002/wsbm.1386 For further resources related to this article, please visit the WIREs website.

Applying Pattern Recognition to High-Resolution Images to Determine Cellular Signaling Status

Two frequently used tools to acquire high- resolution images of cells are scanning electron microscopy (SEM) and atomic force microscopy (AFM). The former provides a nanometer resolution view of cellular features rapidly and with high throughput, while the latter enables visualizing hydrated and living cells. In current practice, these images are viewed by eye to determine cellular status, e.g., activated versus resting. Automatic and quantitative data analysis is lacking. This paper develops an algorithm of pattern recognition that works very effectively for AFM and SEM images. Using rat basophilic leukemia cells, our approach creates a support vector machine to automatically classify resting and activated cells. Ten-fold cross-validation with cells that are known to be activated or resting gives a good estimate of the generalized classification results. The pattern recognition of AFM images achieves 100% accuracy, while SEM reaches 95.4% for our images as well as images published in prior literature. This outcome suggests that our methodology could become an important and frequently used tool for researchers utilizing AFM and SEM for structural characterization as well as determining cellular signaling status and function.

Biophysics of Biochemical Signaling in Dendritic Spines: Implications in Synaptic Plasticity

Dendritic spines are mushroom-shaped postsynaptic compartments that host biochemical signal cascades important for synaptic plasticity and, ultimately, learning and memory. Signaling events in spines involve a signaling network composed of hundreds of signaling proteins interacting with each other extensively. Synaptic plasticity is typically induced by Ca²⁺ elevation in spines, which activates a variety of signaling pathways. This leads to changes in the actin cytoskeleton and membrane dynamics, which in turn causes structural and functional changes of the spine. Recent studies have demonstrated that the activities of these proteins have a variety of spatiotemporal patterns, which orchestrate signaling activity in different subcellular compartments at different timescales. The diffusion and the decay kinetics of signaling molecules play important roles in determining the degree of their spatial spreading, and thereby the degree of the spine specificity of the signaling pathway.

Stability analysis in spatial modeling of cell signaling

Advances in high-resolution microscopy and other techniques have emphasized the spatio-temporal nature of information transfer through signal transduction pathways. The compartmentalization of signaling molecules and the existence of microdomains are now widely acknowledged as key features in biochemical signaling. To complement experimental observations of spatio-temporal dynamics, mathematical modeling has emerged as a powerful tool. Using modeling, one can not only recapitulate experimentally observed dynamics of signaling molecules, but also gain an understanding of the underlying mechanisms in order to generate experimentally testable predictions. Reaction-diffusion systems are commonly used to this end; however, the analysis of coupled nonlinear systems of partial differential equations, generated by considering large reaction networks is often challenging. Here, we aim to provide an introductory tutorial for the application of reaction-diffusion models to the spatio-temporal dynamics of signaling pathways. In particular, we outline the steps for stability analysis of such models, with a focus on biochemical signal transduction. WIREs Syst Biol Med 2018, 10:e1395. doi: 10.1002/wsbm.1395 This article is categorized under: Biological Mechanisms > Cell Signaling Analytical and Computational Methods > Dynamical Methods Models of Systems Properties and Processes > Mechanistic Models.

Modeling and simulation of biological systems using SPICE language

The article deals with BB-SPICE (SPICE for Biochemical and Biological Systems), an extension of the famous Simulation Program with Integrated Circuit Emphasis (SPICE). BB-SPICE environment is composed of three modules: a new textual and compact description formalism for biological systems, a converter that handles this description and generates the SPICE netlist of the equivalent electronic circuit and NGSPICE which is an open-source SPICE simulator. In addition, the environment provides back and forth interfaces with SBML (System Biology Markup Language), a very common description language used in systems biology. BB-SPICE has been developed in order to bridge the gap between the simulation of biological systems on the one hand and electronics circuits on the other hand. Thus, it is suitable for applications at the interface between both domains, such as development of design tools for synthetic biology and for the virtual prototyping of biosensors and lab-on-chip. Simulation results obtained with BB-SPICE and COPASI (an open-source software used for the simulation of biochemical systems) have been compared on a benchmark of models commonly used in systems biology. Results are in accordance from a quantitative viewpoint but BB-SPICE outclasses COPASI by 1 to 3 orders of magnitude regarding the computation time. Moreover, as our software is based on NGSPICE, it could take profit of incoming updates such as the GPU implementation, of the coupling with powerful analysis and verification tools or of the integration in design automation tools (synthetic biology).

Mathematical modeling of gonadotropin-releasing hormone signaling

Gonadotropin-releasing hormone (GnRH) acts via G-protein coupled receptors on pituitary gonadotropes to control reproduction. These are G_q-coupled receptors that mediate acute effects of GnRH on the exocytotic secretion of luteinizing hormone (LH) and follicle-stimulating hormone (FSH), as well as the chronic regulation of their synthesis. GnRH is secreted in short pulses and GnRH effects on its target cells are dependent upon the dynamics of these pulses. Here we overview GnRH receptors and their signaling network, placing emphasis on pulsatile signaling, and how mechanistic mathematical models and an information theoretic approach have helped further this field.

Shaping mitochondrial dynamics: The role of cAMP signalling

In recent years, our idea of mitochondria evolved from "mere" energy and metabolite producers to key regulators of many cellular functions. In order to preserve and protect their functional status, these organelles engage a number of dynamic processes that allow them to decrease accumulated burden and maintain their homeostasis. Indeed, mitochondria can unite (fusion), divide (fission), position themselves strategically in the cell (motility/trafficking) and if irreversibly damaged or dysfunctional eliminated (mitophagy). These dynamic processes can be controlled both by mitochondrial and cellular signalling pathways, hence allowing mitochondria to tune their function to the cellular needs. Among the regulatory mechanisms, reversible phosphorylation downstream the cyclic AMP (cAMP) signalling cascade was shown to deeply influence mitochondrial dynamics. This review explores the emerging evidence suggesting that cAMP is a key player in the orchestration of mitochondrial fusion/fission, motility and mitophagy, extending the repertoire of this second messenger, which is now recognised as a major regulator of mitochondrial homeostasis.

[Physiopathology of cAMP/PKA signaling in neurons]

Cyclic adenosine monophosphate (cAMP) and the cyclic-AMP dependent protein kinase (PKA) regulate a plethora of cellular functions in virtually all eukaryotic cells. In neurons, the cAMP/PKA signaling cascade controls a number of biological properties such as axonal growth, synaptic transmission, regulation of excitability or long term changes in the nucleus. Genetically-encoded optical biosensors for cAMP or PKA considerably improved our understanding of these processes by providing a real-time measurement in living neurons. In this review, we describe the recent progresses made in the creation of biosensors for cAMP or PKA activity. These biosensors revealed profound differences in the amplitude of the cAMP signal evoked by neuromodulators between various neuronal preparations. These responses can be resolved at the level of individual neurons, also revealing differences related to the neuronal type. At the subcellular level, biosensors reported different signal dynamics in domains like dendrites, cell body, nucleus and axon. Combining this imaging approach with pharmacology or genetical models points at phosphodiesterases and phosphatases as critical regulatory proteins. Biosensor imaging will certainly help understand the mechanism of action of current drugs as well as help in devising novel therapeutic strategies for neuropsychiatric diseases.

Genetically encoded biosensors for visualizing live-cell biochemical activity at super-resolution

Compartmentalized biochemical activities are essential to all cellular processes, but there is no generalizable method to visualize dynamic protein activities in living cells at a resolution commensurate with their compartmentalization. Here we introduce a new class of fluorescent biosensors that detect biochemical activities in living cells at a resolution up to three-fold better than the diffraction limit. Utilizing specific, binding-induced changes in protein fluorescence dynamics, these biosensors translate kinase activities or protein-protein interactions into changes in fluorescence fluctuations, which are quantifiable through stochastic optical fluctuation imaging. A Protein Kinase A (PKA) biosensor allowed us to resolve minute PKA activity microdomains on the plasma membrane of living cells and uncover the role of clustered anchoring proteins in organizing these activity microdomains. Together, these findings suggest that biochemical activities of the cell are spatially organized into an activity architecture, whose structural and functional characteristics can be revealed by these new biosensors.

The Horizon of Materiobiology: A Perspective on Material-Guided Cell Behaviors and Tissue Engineering

Although the biological functions of cell and tissue can be regulated by biochemical factors (e.g., growth factors, hormones), the biophysical effects of materials on the regulation of biological activity are receiving more attention. In this Review, we systematically summarize the recent progress on how biomaterials with controllable properties (e.g., compositional/degradable dynamics, mechanical properties, 2D topography, and 3D geometry) can regulate cell behaviors (e.g., cell adhesion, spreading, proliferation, cell alignment, and the differentiation or self-maintenance of stem cells) and tissue/organ functions. How the biophysical features of materials influence tissue/organ regeneration have been elucidated. Current challenges and a perspective on the development of novel materials that can modulate specific biological functions are discussed. The interdependent relationship between biomaterials and biology leads us to propose the concept of "materiobiology", which is a scientific discipline that studies the biological effects of the properties of biomaterials on biological functions at cell, tissue, organ, and the whole organism levels. This Review highlights that it is more important to develop ECM-mimicking biomaterials having a self-regenerative capacity to stimulate tissue regeneration, instead of attempting to recreate the complexity of living tissues or tissue constructs ex vivo. The principles of materiobiology may benefit the development of novel biomaterials providing combinative bioactive cues to activate the migration of stem cells from endogenous reservoirs (i.e., cell niches), stimulate robust and scalable self-healing mechanisms, and unlock the body's innate powers of regeneration.

AKAP-mediated feedback control of cAMP gradients in developing hippocampal neurons

Cyclic AMP (cAMP) and protein kinase A (PKA), classical examples of spatially compartmentalized signaling molecules, are critical axon determinants that regulate neuronal polarity and axon formation, yet little is known about micro-compartmentalization of cAMP and PKA signaling and its role in developing neurons. Here, we revealed that cAMP forms a gradient in developing hippocampal neurons, with higher cAMP levels in more distal regions of the axon compared to other regions of the cell. Interestingly, this cAMP gradient changed according to the developmental stage and depended on proper anchoring of PKA by A-kinase anchoring proteins (AKAPs). Disrupting PKA anchoring to AKAPs increased the cAMP gradient in early-stage neurons and led to enhanced axon elongation. Our results provide new evidence for a local negative feedback loop, assembled by AKAPs, for the precise control of a growth-stage-dependent cAMP gradient to ensure proper axon growth.

Crawling and turning in a minimal reaction-diffusion cell motility model: Coupling cell shape and biochemistry

We study a minimal model of a crawling eukaryotic cell with a chemical polarity controlled by a reaction-diffusion mechanism describing Rho GTPase dynamics. The size, shape, and speed of the cell emerge from the combination of the chemical polarity, which controls the locations where actin polymerization occurs, and the physical properties of the cell, including its membrane tension. We find in our model both highly persistent trajectories, in which the cell crawls in a straight line, and turning trajectories, where the cell transitions from crawling in a line to crawling in a circle. We discuss the controlling variables for this turning instability and argue that turning arises from a coupling between the reaction-diffusion mechanism and the shape of the cell. This emphasizes the surprising features that can arise from simple links between cell mechanics and biochemistry. Our results suggest that similar instabilities may be present in a broad class of biochemical descriptions of cell polarity.

5D imaging approaches reveal the formation of distinct intracellular cAMP spatial gradients

Cyclic AMP (cAMP) is a ubiquitous second messenger known to differentially regulate many cellular functions. Several lines of evidence suggest that the distribution of cAMP within cells is not uniform. However, to date, no studies have measured the kinetics of 3D cAMP distributions within cells. This is largely due to the low signal-to-noise ratio of FRET-based probes. We previously reported that hyperspectral imaging improves the signal-to-noise ratio of FRET measurements. Here we utilized hyperspectral imaging approaches to measure FRET signals in five dimensions (5D) - three spatial (x, y, z), wavelength (λ), and time (t) - allowing us to visualize cAMP gradients in pulmonary endothelial cells. cAMP levels were measured using a FRET-based sensor (H188) comprised of a cAMP binding domain sandwiched between FRET donor and acceptor - Turquoise and Venus fluorescent proteins. We observed cAMP gradients in response to 0.1 or 1 μM isoproterenol, 0.1 or 1 μM PGE1, or 50 μM forskolin. Forskolin- and isoproterenol-induced cAMP gradients formed from the apical (high cAMP) to basolateral (low cAMP) face of cells. In contrast, PGE1-induced cAMP gradients originated from both the basolateral and apical faces of cells. Data suggest that 2D (x,y) studies of cAMP compartmentalization may lead to erroneous conclusions about the existence of cAMP gradients, and that 3D (x,y,z) studies are required to assess mechanisms of signaling specificity. Results demonstrate that 5D imaging technologies are powerful tools for measuring biochemical processes in discrete subcellular domains. This work was supported by NIH P01HL066299, R01HL058506, S10RR027535, AHA 16PRE27130004 and the Abraham Mitchell Cancer Research Fund.

Cross-regulation of Phosphodiesterase 1 and Phosphodiesterase 2 Activities Controls Dopamine-mediated Striatal α-Amino-3-hydroxy-5-methyl-4-isoxazolepropionic Acid (AMPA) Receptor Trafficking

Dopamine, a key striatal neuromodulator, increases synaptic strength by promoting surface insertion and/or retention of AMPA receptors (AMPARs). This process is mediated by the phosphorylation of the GluA1 subunit of AMPAR by cyclic nucleotide-dependent kinases, making cyclic nucleotide phosphodiesterases (PDEs) potential regulators of synaptic strength. In this study, we examined the role of phosphodiesterase 2 (PDE2), a medium spiny neuron-enriched and cGMP-activated PDE, in AMPAR trafficking. We found that inhibiting PDE2 resulted in enhancement of dopamine-induced surface GluA1 expression in dopamine receptor 1-expressing medium spiny neurons. Using pharmacological and genetic approaches, we found that inhibition of PDE1 resulted in a decrease in surface AMPAR levels because of the allosteric activation of PDE2. The cross-regulation of PDE1 and PDE2 activities results in counterintuitive control of surface AMPAR expression, making it possible to regulate the directionality and magnitude of AMPAR trafficking.

Paradoxical signaling regulates structural plasticity in dendritic spines

Transient spine enlargement (3- to 5-min timescale) is an important event associated with the structural plasticity of dendritic spines. Many of the molecular mechanisms associated with transient spine enlargement have been identified experimentally. Here, we use a systems biology approach to construct a mathematical model of biochemical signaling and actin-mediated transient spine expansion in response to calcium influx caused by NMDA receptor activation. We have identified that a key feature of this signaling network is the paradoxical signaling loop. Paradoxical components act bifunctionally in signaling networks, and their role is to control both the activation and the inhibition of a desired response function (protein activity or spine volume). Using ordinary differential equation (ODE)-based modeling, we show that the dynamics of different regulators of transient spine expansion, including calmodulin-dependent protein kinase II (CaMKII), RhoA, and Cdc42, and the spine volume can be described using paradoxical signaling loops. Our model is able to capture the experimentally observed dynamics of transient spine volume. Furthermore, we show that actin remodeling events provide a robustness to spine volume dynamics. We also generate experimentally testable predictions about the role of different components and parameters of the network on spine dynamics.

Dendritic diameter influences the rate and magnitude of hippocampal cAMP and PKA transients during β-adrenergic receptor activation

In the hippocampus, cyclic-adenosine monophosphate (cAMP) and cAMP-dependent protein kinase (PKA) form a critical signaling cascade required for long-lasting synaptic plasticity, learning and memory. Plasticity and memory are known to occur following pathway-specific changes in synaptic strength that are thought to result from spatially and temporally coordinated intracellular signaling events. To better understand how cAMP and PKA dynamically operate within the structural complexity of hippocampal neurons, we used live two-photon imaging and genetically-encoded fluorescent biosensors to monitor cAMP levels or PKA activity in CA1 neurons of acute hippocampal slices. Stimulation of β-adrenergic receptors (isoproterenol) or combined activation of adenylyl cyclase (forskolin) and inhibition of phosphodiesterase (IBMX) produced cAMP transients with greater amplitude and rapid on-rates in intermediate and distal dendrites compared to somata and proximal dendrites. In contrast, isoproterenol produced greater PKA activity in somata and proximal dendrites compared to intermediate and distal dendrites, and the on-rate of PKA activity did not differ between compartments. Computational models show that our observed compartmental difference in cAMP can be reproduced by a uniform distribution of PDE4 and a variable density of adenylyl cyclase that scales with compartment size to compensate for changes in surface to volume ratios. However, reproducing our observed compartmental difference in PKA activity required enrichment of protein phosphatase in small compartments; neither reduced PKA subunits nor increased PKA substrates were sufficient. Together, our imaging and computational results show that compartment diameter interacts with rate-limiting components like adenylyl cyclase, phosphodiesterase and protein phosphatase to shape the spatial and temporal components of cAMP and PKA signaling in CA1 neurons and suggests that small neuronal compartments are most sensitive to cAMP signals whereas large neuronal compartments accommodate a greater dynamic range in PKA activity.

A Computational Modeling and Simulation Approach to Investigate Mechanisms of Subcellular cAMP Compartmentation

Subcellular compartmentation of the ubiquitous second messenger cAMP has been widely proposed as a mechanism to explain unique receptor-dependent functional responses. How exactly compartmentation is achieved, however, has remained a mystery for more than 40 years. In this study, we developed computational and mathematical models to represent a subcellular sarcomeric space in a cardiac myocyte with varying detail. We then used these models to predict the contributions of various mechanisms that establish subcellular cAMP microdomains. We used the models to test the hypothesis that phosphodiesterases act as functional barriers to diffusion, creating discrete cAMP signaling domains. We also used the models to predict the effect of a range of experimentally measured diffusion rates on cAMP compartmentation. Finally, we modeled the anatomical structures in a cardiac myocyte diad, to predict the effects of anatomical diffusion barriers on cAMP compartmentation. When we incorporated experimentally informed model parameters to reconstruct an in silico subcellular sarcomeric space with spatially distinct cAMP production sites linked to caveloar domains, the models predict that under realistic conditions phosphodiesterases alone were insufficient to generate significant cAMP gradients. This prediction persisted even when combined with slow cAMP diffusion. When we additionally considered the effects of anatomic barriers to diffusion that are expected in the cardiac myocyte dyadic space, cAMP compartmentation did occur, but only when diffusion was slow. Our model simulations suggest that additional mechanisms likely contribute to cAMP gradients occurring in submicroscopic domains. The difference between the physiological and pathological effects resulting from the production of cAMP may be a function of appropriate compartmentation of cAMP signaling. Therefore, understanding the contribution of factors that are responsible for coordinating the spatial and temporal distribution of cAMP at the subcellular level could be important for developing new strategies for the prevention or treatment of unfavorable responses associated with different disease states.

Subcellular compartmentation of the ubiquitous second messenger cAMP has been widely proposed as a mechanism to explain how this one signaling molecule produces unique receptor-dependent functional responses. But, how exactly compartmentation occurs, is unknown. This is because there has been no way to measure the regulation and movement of cAMP in cells with intact subcellular structures. In this study, we applied novel computational approaches to predict whether PDE activity alone or in conjunction with restricted diffusion is sufficient to produce cAMP gradients in submicroscopic signaling domains. We also used the models to test the effect of a range of experimentally measured diffusion rates on cAMP compartmentation. Our simulations suggest that PDE activity alone is not sufficient to explain compartmentation, but if diffusion of cAMP is limited by potential factors such as molecular crowding, PKA buffering, and anatomical barriers, then compartmentation is predicted to occur.

Memory of cell shape biases stochastic fate decision-making despite mitotic rounding

Cell shape influences function, and the current model suggests that such shape effect is transient. However, cells dynamically change their shapes, thus, the critical question is whether shape information remains influential on future cell function even after the original shape is lost. We address this question by integrating experimental and computational approaches. Quantitative live imaging of asymmetric cell-fate decision-making and their live shape manipulation demonstrates that cellular eccentricity of progenitor cell indeed biases stochastic fate decisions of daughter cells despite mitotic rounding. Modelling and simulation indicates that polarized localization of Delta protein instructs by the progenitor eccentricity is an origin of the bias. Simulation with varying parameters predicts that diffusion rate and abundance of Delta molecules quantitatively influence the bias. These predictions are experimentally validated by physical and genetic methods, showing that cells exploit a mechanism reported herein to influence their future fates based on their past shape despite dynamic shape changes.

Cell shape influences function but during mitotic cell rounding the original shape is lost. Here the authors show that the cellular eccentricity of progenitor cell biases stochastic fate-decisions using a combination of quantitative live imaging, genetic manipulations and computational simulations.

A computational method for the coupled solution of reaction-diffusion equations on evolving domains and manifolds: Application to a model of cell migration and chemotaxis

In this paper, we devise a moving mesh finite element method for the approximate solution of coupled bulk-surface reaction-diffusion equations on an evolving two dimensional domain. Fundamental to the success of the method is the robust generation of bulk and surface meshes. For this purpose, we use a novel moving mesh partial differential equation (MMPDE) approach. The developed method is applied to model problems with known analytical solutions; these experiments indicate second-order spatial and temporal accuracy. Coupled bulk-surface problems occur frequently in many areas; in particular, in the modelling of eukaryotic cell migration and chemotaxis. We apply the method to a model of the two-way interaction of a migrating cell in a chemotactic field, where the bulk region corresponds to the extracellular region and the surface to the cell membrane.

Control of βAR- and N-methyl-D-aspartate (NMDA) Receptor-Dependent cAMP Dynamics in Hippocampal Neurons

Norepinephrine, a neuromodulator that activates β-adrenergic receptors (βARs), facilitates learning and memory as well as the induction of synaptic plasticity in the hippocampus. Several forms of long-term potentiation (LTP) at the Schaffer collateral CA1 synapse require stimulation of both βARs and N-methyl-D-aspartate receptors (NMDARs). To understand the mechanisms mediating the interactions between βAR and NMDAR signaling pathways, we combined FRET imaging of cAMP in hippocampal neuron cultures with spatial mechanistic modeling of signaling pathways in the CA1 pyramidal neuron. Previous work implied that cAMP is synergistically produced in the presence of the βAR agonist isoproterenol and intracellular calcium. In contrast, we show that when application of isoproterenol precedes application of NMDA by several minutes, as is typical of βAR-facilitated LTP experiments, the average amplitude of the cAMP response to NMDA is attenuated compared with the response to NMDA alone. Models simulations suggest that, although the negative feedback loop formed by cAMP, cAMP-dependent protein kinase (PKA), and type 4 phosphodiesterase may be involved in attenuating the cAMP response to NMDA, it is insufficient to explain the range of experimental observations. Instead, attenuation of the cAMP response requires mechanisms upstream of adenylyl cyclase. Our model demonstrates that Gs-to-Gi switching due to PKA phosphorylation of βARs as well as Gi inhibition of type 1 adenylyl cyclase may underlie the experimental observations. This suggests that signaling by β-adrenergic receptors depends on temporal pattern of stimulation, and that switching may represent a novel mechanism for recruiting kinases involved in synaptic plasticity and memory.

Noradrenaline is a stress related molecule that facilitates learning and memory when released in the hippocampus. The facilitation of memory is related to modulation of synaptic plasticity, but the mechanisms underlying this modulation are not well understood. We utilize a combination of live cell imaging and computational modeling to discover how noradrenergic receptor stimulation interacts with other molecules, such as calcium, required for synaptic plasticity and memory storage. Though prior work has shown that noradrenergic receptors and calcium interact synergistically to elevate intracellular second messengers when combined simultaneously, our results demonstrate that prior stimulation of noradrenergic receptors inhibits the elevation of intracellular second messengers. Our results further demonstrate that the inhibition may be caused by the noradrenergic receptor switching signaling pathways, thereby recruiting a different set of memory kinases. This switching represents a novel mechanism for recruiting molecules involved in synaptic plasticity and memory.

Unbiased Rare Event Sampling in Spatial Stochastic Systems Biology Models Using a Weighted Ensemble of Trajectories

The long-term goal of connecting scales in biological simulation can be facilitated by scale-agnostic methods. We demonstrate that the weighted ensemble (WE) strategy, initially developed for molecular simulations, applies effectively to spatially resolved cell-scale simulations. The WE approach runs an ensemble of parallel trajectories with assigned weights and uses a statistical resampling strategy of replicating and pruning trajectories to focus computational effort on difficult-to-sample regions. The method can also generate unbiased estimates of non-equilibrium and equilibrium observables, sometimes with significantly less aggregate computing time than would be possible using standard parallelization. Here, we use WE to orchestrate particle-based kinetic Monte Carlo simulations, which include spatial geometry (e.g., of organelles, plasma membrane) and biochemical interactions among mobile molecular species. We study a series of models exhibiting spatial, temporal and biochemical complexity and show that although WE has important limitations, it can achieve performance significantly exceeding standard parallel simulation—by orders of magnitude for some observables.

Stochastic simulations (simulations where randomness plays a role) of even simple biological systems are often so computationally intensive that it is impossible, in practice, to simulate them exhaustively and gather good statistics about the likelihood of different outcomes. The difficulty is compounded for the observation of rare events in these simulations; unfortunately, rare events, such as state transitions and barrier crossings, are often those of particular interest. Using the weighted ensemble (WE) method, we are able to enhance the characterization of rare events in cell biology simulations, but in such a way that the statistics for these events remain unbiased. The histogram of outcomes that WE produces has the same shape as a naive one, but the resolution of events in the tails of the histogram is greatly improved. This improved resolution in rare event statistics can be used to infer unbiased estimates of long timescale dynamics from short simulations, and we show that using a weighted ensemble can result in a reduction in total simulation time needed to sample certain events of interest in spatial, stochastic models of biological systems.

Mechanisms Restricting Diffusion of Intracellular cAMP

Although numerous receptors stimulate cAMP production in a wide array of cells, many elicit distinct, highly localized responses, implying that the subcellular distribution of cAMP is not uniform. One often used explanation is that phosphodiesterases, which breakdown cAMP, act as functional barriers limiting diffusion. However, several studies refute the notion that this is sufficient, suggesting that phosphodiesterase-independent movement of cAMP must occur at rates slower than free diffusion. But, until now this has never been demonstrated. Using Raster Image Correlation Spectroscopy (RICS), we measured the diffusion coefficient of a fluorescently-labeled cAMP derivative (φ450-cAMP) as well as other fluorescent molecules in order to investigate the role that molecular size, cell morphology, and buffering by protein kinase A (PKA) play in restricting cAMP mobility in different cell types. Our results demonstrate that cytosolic movement of cAMP is indeed much slower than the rate of free diffusion and that interactions with PKA, especially type II PKA associated with mitochondria, play a significant role. These findings have important implications with respect to cAMP signaling in all cells.

Development of computational models of cAMP signaling

Despite the growing evidence defining the cAMP signaling network as a master regulator of cellular function in a number of tissues, regulatory feedback loops, signal compartmentalization, as well as cross-talk with other signaling pathways make understanding the emergent properties of cAMP cellular action a daunting task. Dynamical models of signaling that combine quantitative rigor with molecular details can contribute valuable mechanistic insight into the complexity of intracellular cAMP signaling by complementing and guiding experimental efforts. In this chapter, we review the development of cAMP computational models. We describe how features of the cAMP network can be represented and review the types of experimental data useful in modeling cAMP signaling. We also compile a list of published cAMP models that can aid in the development of novel dynamical models of cAMP signaling.

Dendritic spine geometry can localize GTPase signaling in neurons

Dendritic spines are the postsynaptic terminals of most excitatory synapses in the mammalian brain. Learning and memory are associated with long-lasting structural remodeling of dendritic spines through an actin-mediated process regulated by the Rho-family GTPases RhoA, Rac, and Cdc42. These GTPases undergo sustained activation after synaptic stimulation, but whereas Rho activity can spread from the stimulated spine, Cdc42 activity remains localized to the stimulated spine. Because Cdc42 itself diffuses rapidly in and out of the spine, the basis for the retention of Cdc42 activity in the stimulated spine long after synaptic stimulation has ceased is unclear. Here we model the spread of Cdc42 activation at dendritic spines by means of reaction-diffusion equations solved on spine-like geometries. Excitable behavior arising from positive feedback in Cdc42 activation leads to spreading waves of Cdc42 activity. However, because of the very narrow neck of the dendritic spine, wave propagation is halted through a phenomenon we term geometrical wave-pinning. We show that this can account for the localization of Cdc42 activity in the stimulated spine, and, of interest, retention is enhanced by high diffusivity of Cdc42. Our findings are broadly applicable to other instances of signaling in extreme geometries, including filopodia and primary cilia.

Rite of passage: a bZIP transcription factor must transit the cell apex to become competent

In the filamentous fungus Aspergillus nidulans BrlA triggers the central developmental pathway that controls the transition from vegetative growth to asexual reproduction. Upstream regulators including the bZIP transcription factor FlbB activate the expression of brlA. Previous work has established that FlbB localizes to both the apex of the hypha, where it interacts with and is anchored by FlbE, and to nuclei, with highest levels in the nucleus closest to the apex and successively lower levels in nuclei further away from the apex. In this issue, Herrero-Garcia et al. dissect the roles of these two FlbB pools and the mechanisms underlying their localization and activity. Using a photoactivatable tag, they demonstrate that FlbB moves from the tip into the apical nucleus. Through a series of deletion constructs, they show that import of FlbB into the nucleus requires a bipartite NLS, that FlbB localization at the tip requires actin and that the FlbB tip-high gradient appears to be mass action dependent as the gradient is lost with FlbB constitutive upregulation. They show that while the pool of FlbB at the apex is required for triggering asexual development, the tip high nuclear gradient is not required.

Early Signaling in Primary T Cells Activated by Antigen Presenting Cells Is Associated with a Deep and Transient Lamellal Actin Network

Cellular signaling transduction critically depends on molecular interactions that are in turn governed by dynamic subcellular distributions of the signaling system components. Comprehensive insight into signal transduction requires an understanding of such distributions and cellular structures driving them. To investigate the activation of primary murine T cells by antigen presenting cells (APC) we have imaged more than 60 signaling intermediates during T cell stimulation with microscopy across resolution limits. A substantial number of signaling intermediates associated with a transient, wide, and actin-associated lamellum extending from an interdigitated T cell:APC interface several micrometers into the T cell, as characterized in detail here. By mapping the more than 60 signaling intermediates onto the spatiotemporal features of cell biological structures, the lamellum and other ones previously described, we also define distinct spatial and temporal characteristics of T cell signal initiation, amplification, and core signaling in the activation of primary T cells by APCs. These characteristics differ substantially from ones seen when T cells are activated using common reductionist approaches.

Analogous synaptic plasticity profiles emerge from disparate channel combinations

An open question within the Bienenstock-Cooper-Munro theory for synaptic modification concerns the specific mechanism that is responsible for regulating the sliding modification threshold (SMT). In this conductance-based modeling study on hippocampal pyramidal neurons, we quantitatively assessed the impact of seven ion channels (R- and T-type calcium, fast sodium, delayed rectifier, A-type, and small-conductance calcium-activated (SK) potassium and HCN) and two receptors (AMPAR and NMDAR) on a calcium-dependent Bienenstock-Cooper-Munro-like plasticity rule. Our analysis with R- and T-type calcium channels revealed that differences in their activation-inactivation profiles resulted in differential impacts on how they altered the SMT. Further, we found that the impact of SK channels on the SMT critically depended on the voltage dependence and kinetics of the calcium sources with which they interacted. Next, we considered interactions among all the seven channels and the two receptors through global sensitivity analysis on 11 model parameters. We constructed 20,000 models through uniform randomization of these parameters and found 360 valid models based on experimental constraints on their plasticity profiles. Analyzing these 360 models, we found that similar plasticity profiles could emerge with several nonunique parametric combinations and that parameters exhibited weak pairwise correlations. Finally, we used seven sets of virtual knock-outs on these 360 models and found that the impact of different channels on the SMT was variable and differential. These results suggest that there are several nonunique routes to regulate the SMT, and call for a systematic analysis of the variability and state dependence of the mechanisms underlying metaplasticity during behavior and pathology.

Diverse array-designed modes of combination therapies in Fangjiomics

In line with the complexity of disease networks, diverse combination therapies have been demonstrated potential in the treatment of different patients with complex diseases in a personal combination profile. However, the identification of rational, compatible and effective drug combinations remains an ongoing challenge. Based on a holistic theory integrated with reductionism, Fangjiomics systematically develops multiple modes of array-designed combination therapies. We define diverse "magic shotgun" vertical, horizontal, focusing, siege and dynamic arrays according to different spatiotemporal distributions of hits on targets, pathways and networks. Through these multiple adaptive modes for treating complex diseases, Fangjiomics may help to identify rational drug combinations with synergistic or additive efficacy but reduced adverse side effects that reverse complex diseases by reconstructing or rewiring multiple targets, pathways and networks. Such a novel paradigm for combination therapies may allow us to achieve more precise treatments by developing phenotype-driven quantitative multi-scale modeling for rational drug combinations.

Good practices for building dynamical models in systems biology

Dynamic models can offer deep understanding of information processing mechanisms in physiology, cell signaling, and biological regulation when they are appropriately detailed. Here, we describe some of the key aspects of the model-building process, including proper parameterization and error analysis, as well as common mistakes, such as model-tweaking and oversimplification, which can decrease the value of the models.

3D computational reconstruction of tissues with hollow spherical morphologies using single-cell gene expression data

Single-cell gene expression analysis has contributed to a better understanding of the transcriptional heterogeneity in a variety of model systems, including those used in research in developmental, cancer and stem cell biology. Nowadays, technological advances facilitate the generation of large gene expression data sets in high-throughput format. Strategies are needed to pertinently visualize this information in a tissue structure-related context, so as to improve data analysis and aid the drawing of meaningful conclusions. Here we describe an approach that uses spatial properties of the tissue source to enable the reconstruction of hollow sphere-shaped tissues and organs from single-cell gene expression data in 3D space. To demonstrate our method, we used cells of the mouse otocyst and the renal vesicle as examples. This protocol presents a straightforward computational expression analysis workflow, and it is implemented on the MATLAB and R statistical computing and graphics software platforms. Hands-on time for typical experiments can be <1 h using a standard desktop PC or Mac.

Dendritic geometry shapes neuronal cAMP signalling to the nucleus

Neurons have complex dendritic trees, receiving numerous inputs at various distances from the cell body. Yet the rules of molecular signal propagation from dendrites to nuclei are unknown. DARPP-32 is a phosphorylation-regulated signalling hub in striatal output neurons. We combine diffusion-reaction modelling and live imaging to investigate cAMP-activated DARPP-32 signalling to the nucleus. The model predicts maximal effects on the nucleus of cAMP production in secondary dendrites, due to segmental decrease of dendrite diameter. Variations in branching, perikaryon size or spines have less pronounced effects. Biosensor kinase activity measurement following cAMP or dopamine uncaging confirms these predictions. Histone 3 phosphorylation, regulated by this pathway, is best stimulated by cAMP released in secondary-like dendrites. Thus, unexpectedly, the efficacy of diffusion-based signalling from dendrites to nucleus is not inversely proportional to the distance. We suggest a general mechanism by which dendritic geometry counterbalances the effect of dendritic distance for signalling to the nucleus.

Methodologies for the modeling and simulation of biochemical networks, illustrated for signal transduction pathways: a primer

Biochemical networks depict the chemical interactions that take place among elements of living cells. They aim to elucidate how cellular behavior and functional properties of the cell emerge from the relationships between its components, i.e. molecules. Biochemical networks are largely characterized by dynamic behavior, and exhibit high degrees of complexity. Hence, the interest in such networks is growing and they have been the target of several recent modeling efforts. Signal transduction pathways (STPs) constitute a class of biochemical networks that receive, process, and respond to stimuli from the environment, as well as stimuli that are internal to the organism. An STP consists of a chain of intracellular signaling processes that ultimately result in generating different cellular responses. This primer presents the methodologies used for the modeling and simulation of biochemical networks, illustrated for STPs. These methodologies range from qualitative to quantitative, and include structural as well as dynamic analysis techniques. We describe the different methodologies, outline their underlying assumptions, and provide an assessment of their advantages and disadvantages. Moreover, publicly and/or commercially available implementations of these methodologies are listed as appropriate. In particular, this primer aims to provide a clear introduction and comprehensive coverage of biochemical modeling and simulation methodologies for the non-expert, with specific focus on relevant literature of STPs.

Polarized cellular patterns of endocannabinoid production and detection shape cannabinoid signaling in neurons

Neurons display important differences in plasma membrane composition between somatodendritic and axonal compartments, potentially leading to currently unexplored consequences in G-protein-coupled-receptor signaling. Here, by using highly-resolved biosensor imaging to measure local changes in basal levels of key signaling components, we explored features of type-1 cannabinoid receptor (CB1R) signaling in individual axons and dendrites of cultured rat hippocampal neurons. Activation of endogenous CB1Rs led to rapid, Gi/o-protein- and cAMP-mediated decrease of cyclic-AMP-dependent protein kinase (PKA) activity in the somatodendritic compartment. In axons, PKA inhibition was significantly stronger, in line with axonally-polarized distribution of CB1Rs. Conversely, inverse agonist AM281 produced marked rapid increase of basal PKA activation in somata and dendrites, but not in axons, removing constitutive activation of CB1Rs generated by local production of the endocannabinoid 2-arachidonoylglycerol (2-AG). Interestingly, somatodendritic 2-AG levels differently modified signaling responses to CB1R activation by Δ(9)-THC, the psychoactive compound of marijuana, and by the synthetic cannabinoids WIN55,212-2 and CP55,940. These highly contrasted differences in sub-neuronal signaling responses warrant caution in extrapolating pharmacological profiles, which are typically obtained in non-polarized cells, to predict in vivo responses of axonal (i.e., presynaptic) GPCRs. Therefore, our results suggest that enhanced comprehension of GPCR signaling constraints imposed by neuronal cell biology may improve the understanding of neuropharmacological action.

Macromolecular transport in synapse to nucleus communication

Local signaling events at synapses or axon terminals must be communicated to the nucleus to elicit transcriptional responses. The lengths of neuronal processes pose a significant challenge for such intracellular communication. This challenge is met by mechanisms ranging from rapid signals encoded in calcium waves to slower macromolecular signaling complexes carried by molecular motors. Here we summarize recent findings on macromolecular signaling from the synapse to the nucleus, in comparison to those employed in injury signaling along axons. A number of common themes emerge, including combinatorial signal encoding by post-translational mechanisms such as differential phosphorylation and proteolysis, and conserved roles for importins in coordinating signaling complexes. Neurons may integrate ionic flux with motor-transported signals as a temporal code for synaptic plasticity signaling.

Visualization of cyclic nucleotide dynamics in neurons

The second messengers cyclic adenosine monophosphate (cAMP) and cyclic guanosine monophosphate (cGMP) transduce many neuromodulatory signals from hormones and neurotransmitters into specific functional outputs. Their production, degradation and signaling are spatiotemporally regulated to achieve high specificity in signal transduction. The development of genetically encodable fluorescent biosensors has provided researchers with useful tools to study these versatile second messengers and their downstream effectors with unparalleled spatial and temporal resolution in cultured cells and living animals. In this review, we introduce the general design of these fluorescent biosensors and describe several of them in more detail. Then we discuss a few examples of using cyclic nucleotide fluorescent biosensors to study regulation of neuronal function and finish with a discussion of advances in the field. Although there has been significant progress made in understanding how the specific signaling of cyclic nucleotide second messengers is achieved, the mechanistic details in complex cell types like neurons are only just beginning to surface. Current and future fluorescent protein reporters will be essential to elucidate the role of cyclic nucleotide signaling dynamics in the functions of individual neurons and their networks.

cAMP signaling microdomains and their observation by optical methods

The second messenger cyclic AMP (cAMP) is a major intracellular mediator of many hormones and neurotransmitters and regulates a myriad of cell functions, including synaptic plasticity in neurons. Whereas cAMP can freely diffuse in the cytosol, a growing body of evidence suggests the formation of cAMP gradients and microdomains near the sites of cAMP production, where cAMP signals remain apparently confined. The mechanisms responsible for the formation of such microdomains are subject of intensive investigation. The development of optical methods based on fluorescence resonance energy transfer (FRET), which allow a direct observation of cAMP signaling with high temporal and spatial resolution, is playing a fundamental role in elucidating the nature of such microdomains. Here, we will review the optical methods used for monitoring cAMP and protein kinase A (PKA) signaling in living cells, providing some examples of their application in neurons, and will discuss the major hypotheses on the formation of cAMP/PKA microdomains.

Cancer stem cells: a systems biology view of their role in prognosis and therapy

Evidence has accumulated that characterizes highly tumorigenic cancer cells residing in heterogeneous populations. The accepted term for such a subpopulation is cancer stem cells (CSCs). While many questions still remain about their precise role in the origin, progression, and drug resistance of tumors, it is clear they exist. In this review, a current understanding of the nature of CSC, their potential usefulness in prognosis, and the need to target them will be discussed. In particular, separate studies now suggest that the CSC is plastic in its phenotype, toggling between tumorigenic and nontumorigenic states depending on both intrinsic and extrinsic conditions. Because of this, a static view of gene and protein levels defined by correlations may not be sufficient to either predict disease progression or aid in the discovery and development of drugs to molecular targets leading to cures. Quantitative dynamic modeling, a bottom up systems biology approach whereby signal transduction pathways are described by differential equations, may offer a novel means to overcome the challenges of oncology today. In conclusion, the complexity of CSCs can be captured in mathematical models that may be useful for selecting molecular targets, defining drug action, and predicting sensitivity or resistance pathways for improved patient outcomes.

A nuclear circularity-based classifier for diagnostic distinction of desmoplastic from spindle cell melanoma in digitized histological images

Context:

Distinction of spindle cell melanoma (SM) and desmoplastic melanoma (DM) is clinically important due to differences in metastatic rate and prognosis; however, histological distinction is not always straightforward. During a routine review of cases, we noted differences in nuclear circularity between SM and DM.

Aim:

The primary aim in our study was to determine whether these differences in nuclear circularity, when assessed using a basic ImageJ-based threshold extraction, can serve as a diagnostic classifier to distinguish DM from SM.

Settings and Design:

Our retrospective analysis of an established patient cohort (SM n = 9, DM n = 9) was employed to determine discriminatory power.

Subjects and Methods:

Regions of interest (total n = 108; 6 images per case) were selected from scanned H and E-stained histological sections, and nuclear circularity was extracted and quantified by computational image analysis using open source tools (plugins for ImageJ).

Statistical Analysis:

Using analysis of variance, t-tests, and Fisher's exact tests, we compared extracted quantitative shape measures; statistical significance was defined as P < 0.05.

Results:

Classifying circularity values into four shape categories (spindled, elongated, oval, round) demonstrated significant differences in the spindled and round categories. Paradoxically, DM contained more spindled nuclei than SM (P = 0.011) and SM contained more round nuclei than DM (P = 0.026). Performance assessment using a combined shape-classification of the round and spindled fractions showed 88.9% accuracy and a Youden index of 0.77.

Conclusions:

Spindle cell melanoma and DM differ significantly in their nuclear morphology with respect to fractions of round and spindled nuclei. Our study demonstrates that quantifying nuclear circularity can be used as an adjunct diagnostic tool for distinction of DM and SM.