Phosphatase Specificity and Pathway Insulation in Signaling Networks

Phosphatases play an important role in cellular signaling networks by regulating the phosphorylation state of proteins. Phosphatases are classically considered to be promiscuous, acting on tens to hundreds of different substrates. We recently demonstrated that a shared phosphatase can couple the responses of two proteins to incoming signals, even if those two substrates are from otherwise isolated areas of the network. This finding raises a potential paradox: if phosphatases are indeed highly promiscuous, how do cells insulate themselves against unwanted crosstalk? Here, we use mathematical models to explore three possible insulation mechanisms. One approach involves evolving phosphatase K_M values that are large enough to prevent saturation by the phosphatase’s substrates. Although this is an effective method for generating isolation, the phosphatase becomes a highly inefficient enzyme, which prevents the system from achieving switch-like responses and can result in slow response kinetics. We also explore the idea that substrate degradation can serve as an effective phosphatase. Assuming that degradation is unsaturatable, this mechanism could insulate substrates from crosstalk, but it would also preclude ultrasensitive responses and would require very high substrate turnover to achieve rapid dephosphorylation kinetics. Finally, we show that adaptor subunits, such as those found on phosphatases like PP2A, can provide effective insulation against phosphatase crosstalk, but only if their binding to substrates is uncoupled from their binding to the catalytic core. Analysis of the interaction network of PP2A’s adaptor domains reveals that although its adaptors may isolate subsets of targets from one another, there is still a strong potential for phosphatase crosstalk within those subsets. Understanding how phosphatase crosstalk and the insulation mechanisms described here impact the function and evolution of signaling networks represents a major challenge for experimental and computational systems biology.     

Protein kinases display minimal interpositional dependence on substrate sequence: potential implications for the evolution of signalling networks

Characterization of in vitro substrates of protein kinases by peptide library screening provides a wealth of information on the substrate specificity of kinases for amino acids at particular positions relative to the site of phosphorylation, but provides no information concerning interdependence among positions. High-throughput techniques have recently made it feasible to identify large numbers of in vivo kinase substrates. We used data from experiments on the kinases ATM/ATR and CDK1, and curated CK2 substrates to evaluate the prevalence of interactions between substrate positions within a motif and the utility of these interactions in predicting kinase substrates. Among these data, evidence of interpositional sequence dependencies is strikingly rare, and what dependency exists does little to aid in the prediction of novel kinase substrates. Significant increases in the ability of models to predict kinase-substrate specificity beyond position-independent models must come largely from inclusion of elements of biological and cellular context, rather than further analysis of substrate sequences alone. Our results suggest that, evolutionarily, kinase substrate fitness exists in a smooth energetic landscape. Taken with results from others indicating that phosphopeptide-binding domains do exhibit interpositional dependence, our data suggest that incorporation of new substrate molecules into phospho-signalling networks may be rate-limited by the evolution of suitability for binding by phosphopeptide-binding domains.     

Mechanical Cell–Cell Communication in Fibrous Networks: The Importance of Network Geometry

Cells contracting in extracellular matrix (ECM) can transmit stress over long distances, communicating their position and orientation to cells many tens of micrometres away. Such phenomena are not observed when cells are seeded on substrates with linear elastic properties, such as polyacrylamide (PA) gel. The ability for fibrous substrates to support far reaching stress and strain fields has implications for many physiological processes, while the mechanical properties of ECM are central to several pathological processes, including tumour invasion and fibrosis. Theoretical models have investigated the properties of ECM in a variety of network geometries. However, the effects of network architecture on mechanical cell–cell communication have received little attention. This work investigates the effects of geometry on network mechanics, and thus the ability for cells to communicate mechanically through different networks. Cell-derived displacement fields are quantified for various network geometries while controlling for network topology, cross-link density and micromechanical properties. We find that the heterogeneity of response, fibre alignment, and substrate displacement fields are sensitive to network choice. Further, we show that certain geometries support mechanical communication over longer distances than others. As such, we predict that the choice of network geometry is important in fundamental modelling of cell–cell interactions in fibrous substrates, as well as in experimental settings, where mechanical signalling at the cellular scale plays an important role. This work thus informs the construction of theoretical models for substrate mechanics and experimental explorations of mechanical cell–cell communication.     

The potential for signal integration and processing in interacting MAP kinase cascades

The cellular response to environmental stimuli requires biochemical information processing through which sensory inputs and cellular status are integrated and translated into appropriate responses by way of interacting networks of enzymes. One such network, the mitogen-activated protein (MAP) kinase cascade is a highly conserved signal transduction module that propagates signals from cell surface receptors to various cytosolic and nuclear targets by way of a phosphorylation cascade. We have investigated the potential for signal processing within a network of interacting feed-forward kinase cascades typified by the MAP kinase cascade. A genetic algorithm was used to search for sets of kinetic parameters demonstrating representative key input-output patterns of interest. We discuss two of the networks identified in our study, one implementing the exclusive-or function (XOR) and another implementing what we refer to as an in-band detector (IBD) or two-sided threshold. These examples confirm the potential for logic and amplitude-dependent signal processing in interacting MAP kinase cascades demonstrating limited cross-talk. Specifically, the XOR function allows the network to respond to either one, but not both signals simultaneously, while the IBD permits the network to respond exclusively to signals within a given range of strength, and to suppress signals below as well as above this range. The solution to the XOR problem is interesting in that it requires only two interacting pathways, crosstalk at only one layer, and no feedback or explicit inhibition. These types of responses are not only biologically relevant but constitute signal processing modules that can be combined to create other logical functions and that, in contrast to amplification, cannot be achieved with a single cascade or with two non-interacting cascades. Our computational results revealed surprising similarities between experimental data describing the JNK/MKK4/MKK7 pathway and the solution for the IBD that evolved from the genetic algorithm. The evolved IBD not only exhibited the required non-monotonic signal strength-response, but also demonstrated transient and sustained responses that properly reflected the input signal strength, dependence on both of the MAPKKs for signaling, phosphorylation site preferences by each of the MAPKKs, and both activation and inhibition resulting from the overexpression of one of the MAPKKs.     

Sho1 and Pbs2 act as coscaffolds linking components in the yeast high osmolarity MAP kinase pathway

Scaffold proteins mediate efficient and specific signaling in several mitogen-activated protein (MAP) kinase cascades. In the yeast high osmolarity response pathway, the MAP kinase kinase Pbs2 is thought to function as a scaffold, since it binds the osmosensor Sho1, the upstream MAP kinase kinase kinase Ste11, and the downstream MAP kinase Hog1. Nonetheless, previous work has shown that Ste11 can be activated even when Pbs2 is deleted, resulting in inappropriate crosstalk to the mating pathway. We have found a region in the C terminus of Sho1 that binds Ste11 independently of Pbs2 and is required for crosstalk. These data support a model in which Sho1 has at least two separable interaction regions: one that binds Ste11 and mediates its activation, and one that binds Pbs2, directing Ste11 to act on Pbs2. Thus, a network of interactions provided by both Sho1 and Pbs2 appears to direct pathway information flow.     

Crosstalk between cAMP-PKA and MAP kinase pathways is a key regulatory design necessary to regulate FLO11 expression

Signal transduction pathways crosstalk with one another and play a central role in regulation of cellular events. Crosstalk brings complexity to the system, and hence, a systematic analysis of these crosstalks helps in relating the signaling network structure to its function. Here, we present a modular steady state approach to quantify the network comprising of cAMP-PKA and MAP kinase pathways involved in the regulation of FLO11, a gene which is required for pseudohyphae growth in Saccharomyces cerevisiae under nitrogen starvation. These two pathways crosstalk by converging on the same target, i.e., FLO11 and through Ras2p, an upstream activator of both cAMP and MAPK pathway. Analysis of crosstalk at the gene level revealed that cAMP-PKA and MAPK pathways are indispensable to FLO11 expression. The dose response was highly sensitive and primarily controlled by cAMP-PKA pathway. We demonstrate that the highly sensitive response in the cAMP-PKA pathway was due to crosstalk and inhibitor ultrsensitivity, key regulatory designs present at the downstream of cAMP-PKA pathway. The analysis of the role of Ras2p in the crosstalk between the cAMP-PKA and MAPK pathways indicated that crosstalk essentially helped in amplification of the Gpa2p signal, another upstream activator of the cAMP-PKA pathway. However, the effect of crosstalk due to Ras2p on FLO11 expression was minimal under normal activation levels of Ras2p. Whereas, the crosstalk itself can bring about FLO11 expression under the hyperactivated Ras2p conditions thereby eliminating the requirement for the other activator Gpa2p. We also observed the presence of system level properties such as amplification, inhibitor ultrasensitvity and bistability, which can be attributed to the regulatory design present in the FLO11 expression system. These system level properties might help the organism to respond to varying nutritional status.     

Substrate specificity of protein kinase C. Use of synthetic peptides corresponding to physiological sites as probes for substrate recognition requirements

Although the Ca2+/phospholipid-dependent protein kinase, protein kinase C, has a broad substrate specificity in vitro, the enzyme appears considerably less promiscuous in vivo. To date only a handful of proteins have been identified as physiological substrates for this protein kinase. In order to determine the basis for this selectivity for substrates in intact cells, we have probed the substrate primary sequence requirements of protein kinase C using synthetic peptides corresponding to sites of phosphorylation from four of the known physiological substrates. We have also identified the acetylated N-terminal serine of chick muscle lactate dehydrogenase as an in vitro site of phosphorylation for this protein kinase. These comparative studies have demonstrated that, in vivo, the enzyme exhibits a preference for one basic residue C-terminal to the phosphorylatable residue, as in the sequence: Ser/Thr-Xaa-Lys/Arg, where Xaa is usually an uncharged residue. Additional basic residues, both N and C-terminal to the target amino acid, enhance the Vmax and Km parameters of phosphorylation. None of the peptides based on physiological phosphorylation sites of protein kinase C was an efficient substrate of cAMP-dependent protein kinase, emphasizing the distinct site-recognition selectivities of these two pleiotropic protein kinases. The favorable kinetic parameters of several of the synthetic peptides, coupled with their selectivity for phosphorylation by protein kinase C, will facilitate the assay of this enzyme in the presence of other protein kinases in tissue and cell extracts.     

Split Histidine Kinases Enable Ultrasensitivity and Bistability in Two-Component Signaling Networks

Bacteria sense and respond to their environment through signaling cascades generally referred to as two-component signaling networks. These networks comprise histidine kinases and their cognate response regulators. Histidine kinases have a number of biochemical activities: ATP binding, autophosphorylation, the ability to act as a phosphodonor for their response regulators, and in many cases the ability to catalyze the hydrolytic dephosphorylation of their response regulator. Here, we explore the functional role of “split kinases” where the ATP binding and phosphotransfer activities of a conventional histidine kinase are split onto two distinct proteins that form a complex. We find that this unusual configuration can enable ultrasensitivity and bistability in the signal-response relationship of the resulting system. These dynamics are displayed under a wide parameter range but only when specific biochemical requirements are met. We experimentally show that one of these requirements, namely segregation of the phosphatase activity predominantly onto the free form of one of the proteins making up the split kinase, is met in Rhodobacter sphaeroides. These findings indicate split kinases as a bacterial alternative for enabling ultrasensitivity and bistability in signaling networks. Genomic analyses reveal that up 1.7% of all identified histidine kinases have the potential to be split and bifunctional.     

Protein-tyrosine phosphorylation in Bacillus subtilis

In recent years bacterial protein-tyrosine kinases have been found to phosphorylate a growing number of protein substrates, including RNA polymerase sigma factors, UDP-glucose dehydrogenases and single-stranded DNA-binding proteins. The activity of these protein substrates was affected by tyrosine phosphorylation, indicating that this post-translational modification could regulate physiological processes ranging from stress response and exopolysaccharide synthesis to DNA metabolism. Some interesting work in this field was done in Bacillus subtilis, and we here present the current state of knowledge on protein-tyrosine phosphorylation in this gram-positive model organism. With its two kinases, two kinase modulators, three phosphatases and at least four different tyrosine-phosphorylated substrates, B. subtilis is the bacterium with the highest number of presently known participants in the global network of protein-tyrosine phosphorylation. We discuss the approaches currently used to chart this network: ranging from studies of substrate specificity and the physiological role of tyrosine phosphorylation of individual enzymes to the global approaches at the level of systems biology.     

Adaptive mutations that prevent crosstalk enable the expansion of paralogous signaling protein families

Orthologous proteins often harbor numerous substitutions, but whether these differences result from neutral or adaptive processes is usually unclear. To tackle this challenge, we examined the divergent evolution of a model bacterial signaling pathway comprising the kinase PhoR and its cognate substrate PhoB. We show that the specificity-determining residues of these proteins are typically under purifying selection but have, in α-proteobacteria, undergone a burst of diversification followed by extended stasis. By reversing mutations that accumulated in an α-proteobacterial PhoR, we demonstrate that these substitutions were adaptive, enabling PhoR to avoid crosstalk with a paralogous pathway that arose specifically in α-proteobacteria. Our findings demonstrate that duplication and the subsequent need to avoid crosstalk strongly influence signaling protein evolution. These results provide a concrete example of how system-wide insulation can be achieved postduplication through a surprisingly limited number of mutations. Our work may help explain the apparent ease with which paralogous protein families expanded in all organisms.     

Evolution of enzymes in metabolism: a network perspective

Several models have been proposed to explain the origin and evolution of enzymes in metabolic pathways. Initially, the retro-evolution model proposed that, as enzymes at the end of pathways depleted their substrates in the primordial soup, there was a pressure for earlier enzymes in pathways to be created, using the later ones as initial template, in order to replenish the pools of depleted metabolites. Later, the recruitment model proposed that initial templates from other pathways could be used as long as those enzymes were similar in chemistry or substrate specificity. These two models have dominated recent studies of enzyme evolution. These studies are constrained by either the small scale of the study or the artificial restrictions imposed by pathway definitions. Here, a network approach is used to study enzyme evolution in fully sequenced genomes, thus removing both constraints. We find that homologous pairs of enzymes are roughly twice as likely to have evolved from enzymes that are less than three steps away from each other in the reaction network than pairs of non-homologous enzymes. These results, together with the conservation of the type of chemical reaction catalyzed by evolutionarily related enzymes, suggest that functional blocks of similar chemistry have evolved within metabolic networks. One possible explanation for these observations is that this local evolution phenomenon is likely to cause less global physiological disruptions in metabolism than evolution of enzymes from other enzymes that are distant from them in the metabolic network.     

Characterization of human neutrophil ecto-protein kinase activity released by kinase substrates.

Although most studies of protein phosphorylation have focused on intracellular protein kinases, evidence for protein kinase activity on the surface of several types of cells has been described. Evidence was recently provided for the existence of ecto-protein kinase activity on the surface of human neutrophils. Evidence for three distinct ecto-protein kinase activities was detected, one that phosphorylates endogenous surface proteins, one that phosphorylates exogenous substrates in a cAMP-independent manner and is released in the presence of substrate, and a low level of activity of one that phosphorylates exogenous Kemptide in a cAMP-dependent manner. To begin to elucidate its role in neutrophil function, we have characterized several properties of the releasable ecto-protein kinase activity on human neutrophils. This enzyme activity was inhibited by impermeant stilbene disulfonic acids, which are known to alter neutrophil function, as well as by impermeant sulfhydryl reactive agents. Enzyme activity was detectable at physiologic concentrations of Mg2+, but was higher in the presence of Mn2+. Protein kinase activity was strongly inhibited by heparin, whereas trifluoperazine, cAMP, and cGMP had little effect on kinase activity. Protein kinase activity was selectively removed from the cell surface by incubation with the ecto-kinase substrates casein and phosvitin, but the enzyme was not released by phosphatidylinositol-specific phospholipase C. Repeated exposure of neutrophils to substrate depleted ecto-protein kinase activity from the cell surface, but activity was rapidly restored by incubation in buffer lacking substrate. The released protein kinase had a Km for ATP of approximately 0.5 microM and a pH maximum between 7.0 and 7.5. At least four ecto-protein kinase substrates were detected in serum; vitronectin was identified as one of these substrates by immunoprecipitation studies. Although the exact role of ecto-protein kinase activity in neutrophil function remains undefined, the identification of vitronectin as a serum substrate suggests that it interacts with a physiologically important substrate.     

Inferring general relations between network characteristics from specific network ensembles

Different network models have been suggested for the topology underlying complex interactions in natural systems. These models are aimed at replicating specific statistical features encountered in real-world networks. However, it is rarely considered to which degree the results obtained for one particular network class can be extrapolated to real-world networks. We address this issue by comparing different classical and more recently developed network models with respect to their ability to generate networks with large structural variability. In particular, we consider the statistical constraints which the respective construction scheme imposes on the generated networks. After having identified the most variable networks, we address the issue of which constraints are common to all network classes and are thus suitable candidates for being generic statistical laws of complex networks. In fact, we find that generic, not model-related dependencies between different network characteristics do exist. This makes it possible to infer global features from local ones using regression models trained on networks with high generalization power. Our results confirm and extend previous findings regarding the synchronization properties of neural networks. Our method seems especially relevant for large networks, which are difficult to map completely, like the neural networks in the brain. The structure of such large networks cannot be fully sampled with the present technology. Our approach provides a method to estimate global properties of under-sampled networks in good approximation. Finally, we demonstrate on three different data sets (C. elegans neuronal network, R. prowazekii metabolic network, and a network of synonyms extracted from Roget's Thesaurus) that real-world networks have statistical relations compatible with those obtained using regression models.     

MCAM: multiple clustering analysis methodology for deriving hypotheses and insights from high-throughput proteomic datasets

Advances in proteomic technologies continue to substantially accelerate capability for generating experimental data on protein levels, states, and activities in biological samples. For example, studies on receptor tyrosine kinase signaling networks can now capture the phosphorylation state of hundreds to thousands of proteins across multiple conditions. However, little is known about the function of many of these protein modifications, or the enzymes responsible for modifying them. To address this challenge, we have developed an approach that enhances the power of clustering techniques to infer functional and regulatory meaning of protein states in cell signaling networks. We have created a new computational framework for applying clustering to biological data in order to overcome the typical dependence on specific a priori assumptions and expert knowledge concerning the technical aspects of clustering. Multiple clustering analysis methodology ('MCAM') employs an array of diverse data transformations, distance metrics, set sizes, and clustering algorithms, in a combinatorial fashion, to create a suite of clustering sets. These sets are then evaluated based on their ability to produce biological insights through statistical enrichment of metadata relating to knowledge concerning protein functions, kinase substrates, and sequence motifs. We applied MCAM to a set of dynamic phosphorylation measurements of the ERRB network to explore the relationships between algorithmic parameters and the biological meaning that could be inferred and report on interesting biological predictions. Further, we applied MCAM to multiple phosphoproteomic datasets for the ERBB network, which allowed us to compare independent and incomplete overlapping measurements of phosphorylation sites in the network. We report specific and global differences of the ERBB network stimulated with different ligands and with changes in HER2 expression. Overall, we offer MCAM as a broadly-applicable approach for analysis of proteomic data which may help increase the current understanding of molecular networks in a variety of biological problems.     

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.     

Systems‐level interactions between insulin–EGF networks amplify mitogenic signaling

Crosstalk mechanisms have not been studied as thoroughly as individual signaling pathways. We exploit experimental and computational approaches to reveal how a concordant interplay between the insulin and epidermal growth factor (EGF) signaling networks can potentiate mitogenic signaling. In HEK293 cells, insulin is a poor activator of the Ras/ERK (extracellular signal‐regulated kinase) cascade, yet it enhances ERK activation by low EGF doses. We find that major crosstalk mechanisms that amplify ERK signaling are localized upstream of Ras and at the Ras/Raf level. Computational modeling unveils how critical network nodes, the adaptor proteins GAB1 and insulin receptor substrate (IRS), Src kinase, and phosphatase SHP2, convert insulin‐induced increase in the phosphatidylinositol‐3,4,5‐triphosphate (PIP₃) concentration into enhanced Ras/ERK activity. The model predicts and experiments confirm that insulin‐induced amplification of mitogenic signaling is abolished by disrupting PIP₃‐mediated positive feedback via GAB1 and IRS. We demonstrate that GAB1 behaves as a non‐linear amplifier of mitogenic responses and insulin endows EGF signaling with robustness to GAB1 suppression. Our results show the feasibility of using computational models to identify key target combinations and predict complex cellular responses to a mixture of external cues.     

Plasticity of the MAPK Signaling Network in Response to Mechanical Stress

Cells display versatile responses to mechanical inputs and recent studies have identified the mitogen-activated protein kinase (MAPK) cascades mediating the biological effects observed upon mechanical stimulation. Although, MAPK pathways can act insulated from each other, several mechanisms facilitate the crosstalk between the components of these cascades. Yet, the combinatorial complexity of potential molecular interactions between these elements have prevented the understanding of their concerted functions. To analyze the plasticity of the MAPK signaling network in response to mechanical stress we performed a non-saturating epistatic screen in resting and stretched conditions employing as readout a JNK responsive dJun-FRET biosensor. By knocking down MAPKs, and JNK pathway regulators, singly or in pairs in Drosophila S2R+ cells, we have uncovered unexpected regulatory links between JNK cascade kinases, Rho GTPases, MAPKs and the JNK phosphatase Puc. These relationships have been integrated in a system network model at equilibrium accounting for all experimentally validated interactions. This model allows predicting the global reaction of the network to its modulation in response to mechanical stress. It also highlights its context-dependent sensitivity.     

QIKS – Quantitative identification of kinase substrates

Signaling networks regulate cellular responses to external stimuli through post‐translational modifications such as protein phosphorylation. Phosphoproteomics facilitate the large‐scale identification of kinase substrates. Yet, the characterization of critical connections within these networks and the identification of respective kinases remain the major analytical challenge. To address this problem, we present a novel approach for the identification of direct kinase substrates using chemical genetics in combination with quantitative phosphoproteomics. Quantitative identification of kinase substrates (QIKS) is a novel‐screening platform developed for the proteome‐wide substrate‐analysis of specific kinases. Here, we aimed to identify substrates of mitogen‐activated protein kinase/Erk kinase (Mek1), an essential kinase in the mitogen‐activated protein kinase cascade. An ATP analog‐sensitive mutant of Mek1 (Mek1‐as) was incubated with a cell extract from Mek1 deficient cells. Phosphorylated proteins were analyzed by LC‐MS/MS of IMAC‐enriched phosphopeptides, labeled differentially for relative quantification. The identification of extracellular regulated kinase 1/2 as the sole cytoplasmic substrates of MEK1 validates the applicability of this approach and suggests that QIKS could be used to identify substrates of a wide variety of kinases.