The chemical organization of signaling interactions

MOTIVATION: Cellular chemical signaling pathways form complex networks that are beginning to be studied at the level of chemical kinetics and databases of reactions. Chemical reaction details are traditionally represented as lists of reactions and rates. This does not map readily to the block diagram representation familiar to biologists, and obscures the functional organization of signaling networks. This study examines motifs in signaling chemistry and reports common features that may help to formalize such a mapping between pathway block diagrams and the chemistry. The same motifs may facilitate data representation and provide functional abstraction of the chemistry. RESULTS: I classified 74 interactions between 25 signaling pathways in terms of shared chemical motifs. All interactions in this dataset consist of a few communicating molecules from one set of pathways, and a replicating set of reactions and molecules from another. Each unique combination of interacting pathways duplicates the chemical reaction scheme of this replicating set, but involves different rate constants. Signaling pathways can therefore be described in an object-oriented manner as sets of core reactions with well-defined interfaces between pathways. This generalization lends itself to designing simulators and databases for signaling networks. AVAILABILITY: Software and example models are freely available from http://www.ncbs.res.in/~bhalla/examples/EGFR_example.html.     

The region-specific activities of lipid rafts during axon growth and guidance

The generation and control of cell polarity is a fundamental mechanism for directed migration of the cell. In developing neurons, the axonal growth cone recognizes environmental molecular cues and migrates toward its correct target, thereby forming neuronal networks. The spatial information provided by environmental cues directs axon growth and guidance through generating polarity of intracellular signals and cytoskeletal organization in the growth cone. This polarization process is dependent on lipid rafts, specialized microdomains in the cell membrane. Lipid rafts in specific regions of the growth cone are involved in axon growth and guidance. For example, forward migration of the growth cone requires raft membranes in its leading front. Recent experiments have suggested that lipid rafts function as a platform for localized signaling downstream of adhesion molecules and guidance receptors. The rafts assemble into an active membrane domain that captures and reorganizes the cytoskeletal machinery. In this way, the spatial control of signaling through raft membranes plays a critical role in translating extracellular information into polarized motility of the growth cone.     

A density-dependent switch drives stochastic clustering and polarization of signaling molecules

Positive feedback plays a key role in the ability of signaling molecules to form highly localized clusters in the membrane or cytosol of cells. Such clustering can occur in the absence of localizing mechanisms such as pre-existing spatial cues, diffusional barriers, or molecular cross-linking. What prevents positive feedback from amplifying inevitable biological noise when an un-clustered “off” state is desired? And, what limits the spread of clusters when an “on” state is desired? Here, we show that a minimal positive feedback circuit provides the general principle for both suppressing and amplifying noise: below a critical density of signaling molecules, clustering switches off; above this threshold, highly localized clusters are recurrently generated. Clustering occurs only in the stochastic regime, suggesting that finite sizes of molecular populations cannot be ignored in signal transduction networks. The emergence of a dominant cluster for finite numbers of molecules is partly a phenomenon of random sampling, analogous to the fixation or loss of neutral mutations in finite populations. We refer to our model as the “neutral drift polarity model.” Regulating the density of signaling molecules provides a simple mechanism for a positive feedback circuit to robustly switch between clustered and un-clustered states. The intrinsic ability of positive feedback both to create and suppress clustering is a general mechanism that could operate within diverse biological networks to create dynamic spatial organization.     

Understand the Functions of Scaffold Proteins in Cell Signaling by a Mesoscopic Simulation Method

Scaffold proteins are central players in regulating the spatial-temporal organization of many important signaling pathways in cells. They offer physical platforms to downstream signaling proteins so that their transient interactions in a crowded and heterogeneous environment of cytosol can be greatly facilitated. However, most scaffold proteins tend to simultaneously bind more than one signaling molecule, which leads to the spatial assembly of multimeric protein complexes. The kinetics of these protein oligomerizations are difficult to quantify by traditional experimental approaches. To understand the functions of scaffold proteins in cell signaling, we developed a, to our knowledge, new hybrid simulation algorithm in which both spatial organization and binding kinetics of proteins were implemented. We applied this new technique to a simple network system that contains three molecules. One molecule in the network is a scaffold protein, whereas the other two are its binding targets in the downstream signaling pathway. Each of the three molecules in the system contains two binding motifs that can interact with each other and are connected by a flexible linker. By applying the new simulation method to the model, we show that the scaffold proteins will promote not only thermodynamics but also kinetics of cell signaling given the premise that the interaction between the two signaling molecules is transient. Moreover, by changing the flexibility of the linker between two binding motifs, our results suggest that the conformational fluctuations in a scaffold protein play a positive role in recruiting downstream signaling molecules. In summary, this study showcases the capability of computational simulation in understanding the general principles of scaffold protein functions.     

Cell type specificity of signaling: view from membrane receptors distribution and their downstream transduction networks

Studies on cell signaling pay more attention to spatial dynamics and how such diverse organization can relate to high order of cellular capabilities. To overview the specificity of cell signaling, we integrated human receptome data with proteome spatial expression profiles to systematically investigate the specificity of receptors and receptor-triggered transduction networks across 62 normal cell types and 14 cancer types. Six percent receptors showed cell-type-specific expression, and 4% signaling networks presented enriched cell-specific proteins induced by the receptors. We introduced a concept of "response context" to annotate the cell-type dependent signaling networks. We found that most cells respond similarly to the same stimulus, as the "response contexts" presented high functional similarity. Despite this, the subtle spatial diversity can be observed from the difference in network architectures. The architecture of the signaling networks in nerve cells displayed less completeness than that in glandular cells, which indicated cellular-context dependent signaling patterns are elaborately spatially organized. Likewise, in cancer cells most signaling networks were generally dysfunctional and less complete than that in normal cells. However, glioma emerged hyper-activated transduction mechanism in malignant state. Receptor ATP6AP2 and TNFRSF21 induced rennin-angiotensin and apoptosis signaling were found likely to explain the glioma-specific mechanism. This work represents an effort to decipher context-specific signaling network from spatial dimension. Our results indicated that although a majority of cells engage general signaling response with subtle differences, the spatial dynamics of cell signaling can not only deepen our insights into different signaling mechanisms, but also help understand cell signaling in disease.     

Spatial Control of Biochemical Modification Cascades and Pathways

Information transmission in cells occurs through complex networks of proteins and genes and is relayed through cascades of biochemical modifications, which are typically studied through ordinary differential equations. However, it is becoming increasingly clear that spatial factors can strongly influence chemical information transmission in cells. In this article, we systematically disentangle the effects of space in signaling cascades. This is done by examining the effects of localization/compartmentalization and diffusion of enzymes and substrates in multiple variants of chemical modification cascades. This includes situations where the modified form of species at one stage 1) acts as an enzyme for the next stage; 2) acts as a substrate for the next stage; and 3) is involved in phosphotransfer. Our analysis reveals the multiple effects of space in signal transduction cascades. Although in some cases space plays a modulatory effect (itself of interest), in other cases, spatial regulation and control can profoundly affect the nature of information processing as a result of the subtle interplay between the patterns of localization of species, diffusion, and the nature of the modification cascades. Our results provide a platform for disentangling the role of space and spatial control in multiple cellular contexts and a basis for engineering spatial control in signaling cascades through localization/compartmentalization.     

Using plasma membrane nanoclusters to build better signaling circuits

Cellular signaling pathways do not simply transmit data; they integrate and process signals to operate as switches, oscillators, logic gates, memory modules and many other types of control system. These complex processing capabilities enable cells to respond appropriately to the myriad of external cues that direct growth and development. The idea that crosstalk and feedback loops are used as control systems in biological signaling networks is well established. Signaling networks are also subject to exquisite spatial regulation, yet how spatial control modulates signal outputs is less well understood. Here, we explore the spatial organization of two different signal transduction circuits: receptor tyrosine kinase activation of the mitogen-activated protein kinase module; and glycosylphosphatidylinositol-anchored receptor activation of phospholipase C. With regards to these pathways, recent results have refocused attention on the crucial role of lipid rafts and plasma membrane nanodomains in signal transmission. We identify common design principals that highlight how the spatial organization of signal transduction circuits can be used as a fundamental control mechanism to modulate system outputs in vivo.     

Protein interaction networks in medicine and disease

The physical interaction of proteins is subject to intense investigation that has revealed that proteins are assembled into large densely connected networks. In this review, we will examine how signaling pathways can be combined to form higher order protein interaction networks. By using network graph theory, these interaction networks can be further analyzed for global organization, which has revealed unique aspects of the relationships between protein networks and complex biological phenotypes. Moreover, several studies have shown that the structure and dynamics of protein networks are disturbed in complex diseases such as cancer progression. These relationships suggest a novel paradigm for treatment of complex multigenic disease where the protein interaction network is the target of therapy more so than individual molecules within the network.     

Insights into the organization of biochemical regulatory networks using graph theory analyses

Graph theory has been a valuable mathematical modeling tool to gain insights into the topological organization of biochemical networks. There are two types of insights that may be obtained by graph theory analyses. The first provides an overview of the global organization of biochemical networks; the second uses prior knowledge to place results from multivariate experiments, such as microarray data sets, in the context of known pathways and networks to infer regulation. Using graph analyses, biochemical networks are found to be scale-free and small-world, indicating that these networks contain hubs, which are proteins that interact with many other molecules. These hubs may interact with many different types of proteins at the same time and location or at different times and locations, resulting in diverse biological responses. Groups of components in networks are organized in recurring patterns termed network motifs such as feedback and feed-forward loops. Graph analysis revealed that negative feedback loops are less common and are present mostly in proximity to the membrane, whereas positive feedback loops are highly nested in an architecture that promotes dynamical stability. Cell signaling networks have multiple pathways from some input receptors and few from others. Such topology is reminiscent of a classification system. Signaling networks display a bow-tie structure indicative of funneling information from extracellular signals and then dispatching information from a few specific central intracellular signaling nexuses. These insights show that graph theory is a valuable tool for gaining an understanding of global regulatory features of biochemical networks.     

Bacterial intelligence: imitation games,time-sharing,and long-range quantum coherence

Bacteria are far more intelligent than we can think of. They adopt different survival strategies to make their life comfortable. Researches on bacterial communication to date suggest that bacteria can communicate with each other using chemical signaling molecules as well as using ion channel mediated electrical signaling. Though in past few decades the scopes of chemical signaling have been investigated extensively, those of electrical signaling have received less attention. In this article, we present a novel perspective on time-sharing behavior, which maintains the biofilm growth under reduced nutrient supply between two distant biofilms through electrical signaling based on the experimental evidence reported by Liu et al., in 2017. In addition, following the recent work by Humphries et al. Cell 168(1):200–209, in 2017, we highlight the consequences of long range electrical signaling within biofilm communities through spatially propagating waves of potassium. Furthermore, we address the possibility of two-way cellular communication between artificial and natural cells through chemical signaling being inspired by recent experimental observation (Lentini et al. 2017) where the efficiency of artificial cells in imitating the natural cells is estimated through cellular Turing test. These three spectacular observations lead us to envisage and devise new classical and quantum views of these complex biochemical networks that have never been realized previously.     

Signal transfer by Eph receptors

The Eph receptors are a unique family of receptor tyrosine kinases that enforce cellular position in tissues through mainly repulsive signals generated upon cell-cell contact. Together, Eph receptors and their membrane-anchored ligands. the ephrins, are key molecules for establishing tissue organization through signaling pathways that control axonal projection, cell migration, and the maintenance of cellular boundaries. Through their SH2 (Src Homology 2) and PDZ (postsynaptic density protein, disks large, zona occludens) domains, several signaling molecules have been demonstrated to interact with the activated cytoplasmic domain of Eph receptors by using the yeast two-hybrid system and in vitro biochemical assays. Most proteins found to interact with Eph receptors are well-known regulators of cytoskeletal organization and cell adhesion, and also cell proliferation. Promoting growth, however, does not appear to be a primary role of Eph receptors. Explaining which signaling interactions identified for the Eph receptors have physiological significance, how Eph receptor signaling cascades are propagated, and characterizing the intrinsic signaling properties of the ephrins are all exciting questions currently being investigated.     

Semisynthesis of unnatural amino acid mutants of paxillin: protein probes for cell migration studies

Caged phosphopeptides and phosphoproteins are valuable tools for dissecting the dynamic role of phosphorylation in complex signaling networks with temporal and spatial control. Demonstrating the broad scope of phosphoamino acid caging for studying signaling events, we report here the semisynthesis of a photolabile precursor to the cellular migration protein paxillin, which is a complex, multidomain phosphoprotein. This semisynthetic construct provides a powerful probe for investigating the influence that phosphorylation of paxillin at a single site has on cellular migration. The 61-kDa paxillin construct was assembled using native chemical ligation to install a caged phosphotyrosine residue at position 31 of the 557-residue protein, and the probe includes all other binding and localization determinants in the paxillin macromolecule, which are essential for creating a native environment to investigate phosphorylation. Following semisynthesis, paxillin variants were characterized through detailed biochemical analyses and by quantitative uncaging studies.     

From large networks to small molecules

Large-scale analysis of genetic and physical interaction networks has begun to reveal the global organization of the cell. Cellular phenotypes observed at the macroscopic level depend on the collective characteristics of protein and genetic interaction networks, which exhibit scale-free properties and are highly resistant to perturbation of a single node. The nascent field of chemical genetics promises a host of small-molecule probes to explore these emerging networks. Although the robust nature of cellular networks usually resists the action of single agents, they may be susceptible to rationally designed combinations of small molecules able to collectively shift network behavior.     

Chemical genetic strategies to delineate MAP kinase signaling pathways using protein-fragment complementation assays (PCA)

Signal transduction pathways mediated by MAP kinases are among the most studied. Direct analysis of MAP kinase pathways has been difficult because some details of MAP kinase signaling cannot be studied in vitro. Here, we describe a strategy for directly analyzing MAP kinase signaling pathways in living cells using protein-fragment complementation assays (PCA) based on intensely fluorescent proteins. The assays allow for spatial and temporal analysis of protein complexes including those that form upstream and downstream from MAPKs as well as complexes of MAPKs with regulator and effector proteins. We describe high-content assays, high-throughput quantitative microscopic methods to follow temporal changes in complex subcellular location and quantity. Spatial and temporal changes in response to perturbations (chemical, siRNA, and hormones) allow for delineation of MAPK signaling networks and a general and high-throughput approach to identify small molecules that act directly or indirectly on MAPK pathways.     

Junctional signaling microdomains: bridging the gap between the neuronal cell surface and Ca2+ stores

Growing evidence suggests that plasma membranes are locally differentiated into microdomains that are important interaction sites for organization of signaling molecules. These signaling microdomains create local conditions that enhance molecular interactions, excluding others, thereby ensuring speed, spatial localization, and specificity of signal transduction. With the special emphasis on InsP(3) and Ca(2+) signaling pathways, we will discuss here the evolving concept of signaling microdomains that provide a key framework for understanding the differential regulation of many cellular target proteins.     

Coupled Stochastic Spatial and Non-Spatial Simulations of ErbB1 Signaling Pathways Demonstrate the Importance of Spatial Organization in Signal Transduction

Background

The ErbB family of receptors activates intracellular signaling pathways that control cellular proliferation, growth, differentiation and apoptosis. Given these central roles, it is not surprising that overexpression of the ErbB receptors is often associated with carcinogenesis. Therefore, extensive laboratory studies have been devoted to understanding the signaling events associated with ErbB activation.

Methodology/Principal Findings

Systems biology has contributed significantly to our current understanding of ErbB signaling networks. However, although computational models have grown in complexity over the years, little work has been done to consider the spatial-temporal dynamics of receptor interactions and to evaluate how spatial organization of membrane receptors influences signaling transduction. Herein, we explore the impact of spatial organization of the epidermal growth factor receptor (ErbB1/EGFR) on the initiation of downstream signaling. We describe the development of an algorithm that couples a spatial stochastic model of membrane receptors with a nonspatial stochastic model of the reactions and interactions in the cytosol. This novel algorithm provides a computationally efficient method to evaluate the effects of spatial heterogeneity on the coupling of receptors to cytosolic signaling partners.

Conclusions/Significance

Mathematical models of signal transduction rarely consider the contributions of spatial organization due to high computational costs. A hybrid stochastic approach simplifies analyses of the spatio-temporal aspects of cell signaling and, as an example, demonstrates that receptor clustering contributes significantly to the efficiency of signal propagation from ligand-engaged growth factor receptors.     

Chemoreceptors in Caulobacter crescentus: trimers of receptor dimers in a partially ordered hexagonally packed array

Chemoreceptor arrays are macromolecular complexes that form extended assemblies primarily at the poles of bacterial cells and mediate chemotaxis signal transduction, ultimately controlling cellular motility. We have used cryo-electron tomography to determine the spatial distribution and molecular architecture of signaling molecules that comprise chemoreceptor arrays in wild-type Caulobacter crescentus cells. We demonstrate that chemoreceptors are organized as trimers of receptor dimers, forming partially ordered hexagonally packed arrays of signaling complexes in the cytoplasmic membrane. This novel organization at the threshold between order and disorder suggests how chemoreceptors and associated molecules are arranged in signaling assemblies to respond dynamically in the activation and adaptation steps of bacterial chemotaxis.     

Markov Random Field Modeling of the Spatial Distribution of Proteins on Cell Membranes

Cell membranes display a range of receptors that bind ligands and activate signaling pathways. Signaling is characterized by dramatic changes in membrane molecular topography, including the co-clustering of receptors with signaling molecules and the segregation of other signaling molecules away from receptors. Electron microscopy of immunogold-labeled membranes is a critical technique to generate topographical information at the 5–10 nm resolution needed to understand how signaling complexes assemble and function. However, due to experimental limitations, only two molecular species can usually be labeled at a time. A formidable challenge is to integrate experimental data across multiple experiments where there are from 10 to 100 different proteins and lipids of interest and only the positions of two species can be observed simultaneously. As a solution, we propose the use of Markov random field (MRF) modeling to reconstruct the distribution of multiple cell membrane constituents from pair-wise data sets. MRFs are a powerful mathematical formalism for modeling correlations between states associated with neighboring sites in spatial lattices. The presence or absence of a protein of a specific type at a point on the cell membrane is a state. Since only two protein types can be observed, i.e., those bound to particles, and the rest cannot be observed, the problem is one of deducing the conditional distribution of a MRF with unobservable (hidden) states. Here, we develop a multiscale MRF model and use mathematical programming techniques to infer the conditional distribution of a MRF for proteins of three types from observations showing the spatial relationships between only two types. Application to synthesized data shows that the spatial distributions of three proteins can be reliably estimated. Application to experimental data provides the first maps of the spatial relationship between groups of three different signaling molecules. The work is an important step toward a more complete understanding of membrane spatial organization and dynamics during signaling.     

低分子数下的生命

瞬时分子信号发生在微区,这些区域通常处于一种非均一非平衡状态。在这个过程中,参与的分了数很少,通常有很大的波动。于是,了解各种分子成分的空间组织结构对理解细胞信号通路非常必要。我们利用蒙特卡洛电脑仿真的方法,结合现实的三维几何构形,来研究亚细胞结构以及神经元和突触的生理学。