Spatio-temporal modeling of signaling protein recruitment to EGFR

Phase separation enhances probability of receptor signalling and drug targeting

The probability of a given receptor tyrosine kinase (RTK) triggering a defined cellular outcome is low because of the promiscuous nature of signalling, the randomness of molecular diffusion through the cell, and the ongoing nonfunctional submembrane signalling activity or noise. Signal transduction is therefore a 'numbers game', where enough cell surface receptors and effector proteins must initially be engaged to guarantee formation of a functional signalling complex against a background of redundant events. The presence of intracellular liquid-liquid phase separation (LLPS) at the plasma membrane provides a mechanism through which the probabilistic nature of signalling can be weighted in favour of the required, discrete cellular outcome and mutual exclusivity in signal initiation.

Modeling the Cluster Size Distribution of Vascular Endothelial Growth Factor (VEGF) Receptors

We previously developed a method of defining receptor clusters in the membrane based on mutual distance and applied it to a set of transmission microscopy images of vascular endothelial growth factor receptors. An optimal length parameter was identified, resulting in cluster identification and a procedure that assigned a geometric shape to each cluster. We showed that the observed particle distribution results were consistent with the random placement of receptors within the clusters and, to a lesser extent, the random placement of the clusters on the cell membrane. Here, we develop and validate a stochastic model of clustering, based on a hypothesis of preexisting domains that have a high affinity for receptors. The proximate objective is to clarify the mechanism behind cluster formation and to estimate the effect on signaling. Receptor-enriched domains may significantly impact signaling pathways that rely on ligand-induced dimerization of receptors. We define a simple statistical model, based on the preexisting domain hypothesis, to predict the probability distribution of cluster sizes. The process yielded sets of parameter values that can readily be used in dynamical calculations as the estimates of the quantitative characteristics of the clustering domains.

Subcellular Dynamic Immunopatterning of Cytosolic Protein Complexes on Microstructured Polymer Substrates

Analysis of protein–protein interactions in living cells by protein micropatterning is currently limited to the spatial arrangement of transmembrane proteins and their corresponding downstream molecules. Here, we present a robust and straightforward method for dynamic immunopatterning of cytosolic protein complexes by use of an artificial transmembrane bait construct in combination with microstructured antibody arrays on cyclic olefin polymer substrates. As a proof, the method was used to characterize Grb2-mediated signaling pathways downstream of the epidermal growth factor receptor (EGFR). Ternary protein complexes (Shc1:Grb2:SOS1 and Grb2:Gab1:PI3K) were identified, and we found that EGFR downstream signaling is based on constitutively bound (Grb2:SOS1 and Grb2:Gab1) as well as on agonist-dependent protein associations with transient interaction properties (Grb2:Shc1 and Grb2:PI3K). Spatiotemporal analysis further revealed significant differences in stability and exchange kinetics of protein interactions. Furthermore, we could show that this approach is well suited to study the efficacy and specificity of SH2 and SH3 protein domain inhibitors in a live cell context. Altogether, this method represents a significant enhancement of quantitative subcellular micropatterning approaches as an alternative to standard biochemical analyses.

EGFR transactivates RON to drive oncogenic crosstalk

Crosstalk between different receptor tyrosine kinases (RTKs) is thought to drive oncogenic signaling and allow therapeutic escape. EGFR and RON are two such RTKs from different subfamilies, which engage in crosstalk through unknown mechanisms. We combined high-resolution imaging with biochemical and mutational studies to ask how EGFR and RON communicate. EGF stimulation promotes EGFR-dependent phosphorylation of RON, but ligand stimulation of RON does not trigger EGFR phosphorylation – arguing that crosstalk is unidirectional. Nanoscale imaging reveals association of EGFR and RON in common plasma membrane microdomains. Two-color single particle tracking captured formation of complexes between RON and EGF-bound EGFR. Our results further show that RON is a substrate for EGFR kinase, and that transactivation of RON requires formation of a signaling competent EGFR dimer. These results support a role for direct EGFR/RON interactions in propagating crosstalk, such that EGF-stimulated EGFR phosphorylates RON to activate RON-directed signaling.

Receptor/Raft Ratio Is a Determinant for LRP6 Phosphorylation and WNT/β-Catenin Signaling

Microdomains or lipid rafts greatly affect the distribution of proteins and peptides in the membrane and play a vital role in the formation and activation of receptor/protein complexes. A prominent example for the decisive impact of lipid rafts on signaling is LRP6, whose localization to the same lipid rafts domain as the kinase CK1γ is crucial for its successful phosphorylation and the subsequent activation of the signalosome, hence WNT/β-catenin signaling. However, according to various experimental measurements, approximately 25 to 35 % of the cell plasma membrane is covered by nanoscopic raft domains with diameters ranging between 10 to 200 nm. Extrapolating/Translating these values to the membrane of a “normal sized” cell yields a raft abundance, that, by far, outnumbers the membrane-associated pathway components of most individual signaling pathway, such as receptor and kinases. To analyze whether and how the quantitative ratio between receptor and rafts affects LRP6 phosphorylation and WNT/β-catenin pathway activation, we present a computational modeling study, that for the first time employs realistic raft numbers in a compartment-based pathway model. Our simulation experiments indicate, that for receptor/raft ratios smaller than 1, i.e., when the number of raft compartments clearly exceeds the number of pathway specific membrane proteins, we observe significant decrease in LRP6 phosphorylation and downstream pathway activity. Our results suggest that pathway specific targeting and sorting mechanism are required to significantly narrow down the receptor/raft ratio and to enable the formation of the LRP6 signalosome, hence signaling.

Deviating from the Beaten Track: New Twists in Brassinosteroid Receptor Function

A key feature of plants is their plastic development tailored to the environmental conditions. To integrate environmental signals with genetic growth regulatory programs, plants rely on a number of hormonal pathways, which are intimately connected at multiple levels. Brassinosteroids (BRs), a class of plant sterol hormones, are perceived by cell surface receptors and trigger responses instrumental in tailoring developmental programs to environmental cues. Arguably, BR signalling is one of the best-characterized plant signalling pathways, and the molecular composition of the core signal transduction cascade seems clear. However, BR research continues to reveal new twists to re-shape our view on this key signalling circuit. Here, exciting novel findings pointing to the plasma membrane as a key site for BR signalling modulation and integration with other pathways are reviewed and new inputs into the BR signalling pathway and emerging “non-canonical” functions of the BR receptor complex are highlighted. Together, this new evidence underscores the complexity of plant signalling integration and serves as a reminder that highly-interconnected signalling pathways frequently comprise non-linear aspects which are difficult to convey in classical conceptual models.

Multisite EGFR phosphorylation is regulated by adaptor protein abundances and dimer lifetimes

Differential epidermal growth factor receptor (EGFR) phosphorylation is thought to couple receptor activation to distinct signaling pathways. However, the molecular mechanisms responsible for biased signaling are unresolved due to a lack of insight into the phosphorylation patterns of full-length EGFR. We extended a single-molecule pull-down technique previously used to study protein-protein interactions to allow for robust measurement of receptor phosphorylation. We found that EGFR is predominantly phosphorylated at multiple sites, yet phosphorylation at specific tyrosines is variable and only a subset of receptors share phosphorylation at the same site, even with saturating ligand concentrations. We found distinct populations of receptors as soon as 1 min after ligand stimulation, indicating early diversification of function. To understand this heterogeneity, we developed a mathematical model. The model predicted that variations in phosphorylation are dependent on the abundances of signaling partners, while phosphorylation levels are dependent on dimer lifetimes. The predictions were confirmed in studies of cell lines with different expression levels of signaling partners, and in experiments comparing low- and high-affinity ligands and oncogenic EGFR mutants. These results reveal how ligand-regulated receptor dimerization dynamics and adaptor protein concentrations play critical roles in EGFR signaling.

A compact synthetic pathway rewires cancer signaling to therapeutic effector release

An important goal in synthetic biology is to engineer biochemical pathways to address unsolved biomedical problems. One long-standing problem in molecular medicine is the specific identification and ablation of cancer cells. Here, we describe a method, named Rewiring of Aberrant Signaling to Effector Release (RASER), in which oncogenic ErbB receptor activity, instead of being targeted for inhibition as in existing treatments, is co-opted to trigger therapeutic programs. RASER integrates ErbB activity to specifically link oncogenic states to the execution of desired outputs. A complete mathematical model of RASER and modularity in design enable rational optimization and output programming. Using RASER, we induced apoptosis and CRISPR-Cas9-mediated transcription of endogenous genes specifically in ErbB-hyperactive cancer cells. Delivery of apoptotic RASER by adeno-associated virus selectively ablated ErbB-hyperactive cancer cells while sparing ErbB-normal cells. RASER thus provides a new strategy for oncogene-specific cancer detection and treatment.

In silico prediction of ErbB signal activation from receptor expression profiles through a data analytics pipeline

The ErbB signalling pathway has been studied extensively owing to its role in normal physiology and its dysregulation in cancer. Reverse engineering by mathematical models use the reductionist approach to characterize the network components. For an emergent, system-level view of the network, we propose a data analytics pipeline that can learn from the data generated by reverse engineering and use it to re-engineer the system with an agent-based approach. Data from a kinetic model that estimates the parameters by fitting to experiments on cell lines, were encoded into rules, for the interactions of the molecular species (agents) involved in biochemical reactions. The agent model, a digital representation of the cell line system, tracks the activation of ErbB1-3 receptors on binding with ligands, resulting in their dimerization, phosphorylation, trafficking and stimulation of downstream signalling through P13-Akt and Erk pathways. The analytics pipeline has been used to mechanistically link HER expression profile to receptor dimerization and activation of downstream signalling pathways. When applied to drug studies, the efficacy of a drug can be investigated in silico. The anti-tumour activity of Pertuzumab, a monoclonal antibody that inhibits HER2 dimerization, was simulated by blocking 80% of the cellular HER2 available, to observe the effect on signal activation.

Receptor Tyrosine Kinase Ubiquitination and De-Ubiquitination in Signal Transduction and Receptor Trafficking

Receptor tyrosine kinases (RTKs) are membrane-based sensors that enable rapid communication between cells and their environment. Evidence is now emerging that interdependent regulatory mechanisms, such as membrane trafficking, ubiquitination, proteolysis and gene expression, have substantial effects on RTK signal transduction and cellular responses. Different RTKs exhibit both basal and ligand-stimulated ubiquitination, linked to trafficking through different intracellular compartments including the secretory pathway, plasma membrane, endosomes and lysosomes. The ubiquitin ligase superfamily comprising the E1, E2 and E3 enzymes are increasingly implicated in this post-translational modification by adding mono- and polyubiquitin tags to RTKs. Conversely, removal of these ubiquitin tags by proteases called de-ubiquitinases (DUBs) enables RTK recycling for another round of ligand sensing and signal transduction. The endocytosis of basal and activated RTKs from the plasma membrane is closely linked to controlled proteolysis after trafficking and delivery to late endosomes and lysosomes. Proteolytic RTK fragments can also have the capacity to move to compartments such as the nucleus and regulate gene expression. Such mechanistic diversity now provides new opportunities for modulating RTK-regulated cellular responses in health and disease states.

VEGFR1 promotes cell migration and proliferation through PLCγ and PI3K pathways

The ability to control vascular endothelial growth factor (VEGF) signaling offers promising therapeutic potential for vascular diseases and cancer. Despite this promise, VEGF-targeted therapies are not clinically effective for many pathologies, such as breast cancer. VEGFR1 has recently emerged as a predictive biomarker for anti-VEGF efficacy, implying a functional VEGFR1 role beyond its classically defined decoy receptor status. Here we introduce a computational approach that accurately predicts cellular responses elicited via VEGFR1 signaling. Aligned with our model prediction, we show empirically that VEGFR1 promotes macrophage migration through PLCγ and PI3K pathways and promotes macrophage proliferation through a PLCγ pathway. These results provide new insight into the basic function of VEGFR1 signaling while offering a computational platform to quantify signaling of any receptor.

Dynamic modeling of folliculogenesis signaling pathways in the presence of miRNAs expression

Background

TEK signaling plays a very important role in folliculogenesis. It activates Ras/ERK/MYC, PI3K/AKT/mTORC1 and ovarian steroidogenesis activation pathways. These are the main pathways for cell growth, differentiation, migration, adhesion, proliferation, survival and protein synthesis.

Results

TEK signaling on each of the two important pathways where levels of pERK, pMYC, pAkt, pMCL1 and pEIF4EBP1 are increased in dominant follicles and pMYC is decreased in dominant follicles. Over activation of ERK and MYC which are the main cell growth and proliferation and over activation of Akt, MCl1, mTORC1 and EIF4EBP1 which are the main cell survival and protein synthesis factors act as promoting factors for folliculogenesis. In case of over expression of hsa-miR-30d-3p and hsa-miR-451a, MYC activity level is considerably increased in subordinate follicles. Our simulation results show that in the presence of has-miR-548v and bta-miR-22-3p, downstream factors of pathways are inhibited.

Conclusions

Our work offers insight into the design of natural biological procedures and makes predictions that can guide further experimental studies on folliculogenesis pathways. Moreover, it defines a simple signal processing unit that may be useful for engineering synthetic biology and genes circuits to carry out cell-based computation.

Electronic supplementary material

The online version of this article (doi:10.1186/s13048-017-0371-y) contains supplementary material, which is available to authorized users.

Src homology 2 domains enhance tyrosine phosphorylation in vivo by protecting binding sites in their target proteins from dephosphorylation

Phosphotyrosine (pTyr)-dependent signaling is critical for many cellular processes. It is highly dynamic, as signal output depends not only on phosphorylation and dephosphorylation rates but also on the rates of binding and dissociation of effectors containing phosphotyrosine-dependent binding modules such as Src homology 2 (SH2) and phosphotyrosine-binding (PTB) domains. Previous in vitro studies suggested that binding of SH2 and PTB domains can enhance protein phosphorylation by protecting the sites bound by these domains from phosphatase-mediated dephosphorylation. To test whether this occurs in vivo, we used the binding of growth factor receptor bound 2 (GRB2) to phosphorylated epidermal growth factor receptor (EGFR) as a model system. We analyzed the effects of SH2 domain overexpression on protein tyrosine phosphorylation by quantitative Western and far-Western blotting, mass spectrometry, and computational modeling. We found that SH2 overexpression results in a significant, dose-dependent increase in EGFR tyrosine phosphorylation, particularly of sites corresponding to the binding specificity of the overexpressed SH2 domain. Computational models using experimentally determined EGFR phosphorylation and dephosphorylation rates, and pTyr-EGFR and GRB2 concentrations, recapitulated the experimental findings. Surprisingly, both modeling and biochemical analyses suggested that SH2 domain overexpression does not result in a major decrease in the number of unbound phosphorylated SH2 domain-binding sites. Our results suggest that signaling via SH2 domain binding is buffered over a relatively wide range of effector concentrations and that SH2 domain proteins with overlapping binding specificities are unlikely to compete with one another for phosphosites in vivo.

Quantifying the Interaction between EGFR Dimers and Grb2 in Live Cells

Adaptor proteins are a class of cytoplasmic proteins that bind to phosphorylated residues in receptor tyrosine kinases and trigger signaling cascades that control critically important cellular processes, such as cell survival, growth, differentiation, and motility. Here, we seek to characterize the interaction between epidermal growth factor receptor (EGFR) and the cytoplasmic adaptor protein growth factor receptor-bound protein 2 (Grb2) in a cellular context. To do so, we explore the utility of a highly biologically relevant model system, mammalian cells under reversible osmotic stress, and a recently introduced Förster resonance energy transfer microscopy method, fully quantified spectral imaging. We present a method that allows us to quantify the stoichiometry and the association constant of the EGFR-Grb2 binding interaction in the plasma membrane, in the presence and absence of activating ligand. The method that we introduce can have broad utility in membrane protein research, as it can be applied to different membrane protein-cytoplasmic protein pairs.

Plant immune and growth receptors share common signalling components but localise to distinct plasma membrane nanodomains

Cell surface receptors govern a multitude of signalling pathways in multicellular organisms. In plants, prominent examples are the receptor kinases FLS2 and BRI1, which activate immunity and steroid-mediated growth, respectively. Intriguingly, despite inducing distinct signalling outputs, both receptors employ common downstream signalling components, which exist in plasma membrane (PM)-localised protein complexes. An important question is thus how these receptor complexes maintain signalling specificity. Live-cell imaging revealed that FLS2 and BRI1 form PM nanoclusters. Using single-particle tracking we could discriminate both cluster populations and we observed spatiotemporal separation between immune and growth signalling platforms. This finding was confirmed by visualising FLS2 and BRI1 within distinct PM nanodomains marked by specific remorin proteins and differential co-localisation with the cytoskeleton. Our results thus suggest that signalling specificity between these pathways may be explained by the spatial separation of FLS2 and BRI1 with their associated signalling components within dedicated PM nanodomains.

Plant immune and growth receptors share common signalling components but localise to distinct plasma membrane nanodomains

Cell surface receptors govern a multitude of signalling pathways in multicellular organisms. In plants, prominent examples are the receptor kinases FLS2 and BRI1, which activate immunity and steroid-mediated growth, respectively. Intriguingly, despite inducing distinct signalling outputs, both receptors employ common downstream signalling components, which exist in plasma membrane (PM)-localised protein complexes. An important question is thus how these receptor complexes maintain signalling specificity. Live-cell imaging revealed that FLS2 and BRI1 form PM nanoclusters. Using single-particle tracking we could discriminate both cluster populations and we observed spatiotemporal separation between immune and growth signalling platforms. This finding was confirmed by visualising FLS2 and BRI1 within distinct PM nanodomains marked by specific remorin proteins and differential co-localisation with the cytoskeleton. Our results thus suggest that signalling specificity between these pathways may be explained by the spatial separation of FLS2 and BRI1 with their associated signalling components within dedicated PM nanodomains.

DOI:http://dx.doi.org/10.7554/eLife.25114.001

Unlike most animals, plants cannot move away if their environment changes for the worse. Instead, a plant must sense these changes and respond appropriately, for example by changing how much it grows. Disease-causing microbes in the immediate environment represent another potential threat to plants. To detect these microbes, plant cells have proteins called “pattern recognition receptors” in their surface membranes that sense certain molecules from the microbes (similar receptors are found in animals too). When a receptor protein recognises one such microbial molecule, it becomes activated and forms a complex with other proteins referred to as co-receptors. The protein complex then sends a signal into the cell to trigger an immune response.

Plants also use similar receptor proteins to sense their own signalling molecules and regulate their growth and development. These growth-related receptors rely on many of the same co-receptors and signalling components as the immunity-related receptors. This posed the question: how can plant cells use the same proteins to trigger different responses to different signals?

Bücherl et al. have now used high-resolution microscopy and the model plant Arabidopsis thaliana to show that the plant’s immune receptors and growth receptors are found in separate clusters at the plant cell’s surface membrane. These clusters are only a few hundred nanometres wide, and they also contained other signalling components that are needed to quickly relay the signals into the plant cell.

Bücherl et al. suggest that, by organizing their receptors into these physically distinct clusters, plant cells can use similar proteins to sense different signals and respond in then different ways. This idea will need to be tested in future studies. Further work is also needed to understand how these clusters of signalling proteins are assembled and inserted at specific locations within the surface membrane of a plant cell.

DOI:http://dx.doi.org/10.7554/eLife.25114.002

Agent-based re-engineering of ErbB signaling: a modeling pipeline for integrative systems biology

Motivation

Experiments in systems biology are generally supported by a computational model which quantitatively estimates the parameters of the system by finding the best fit to the experiment. Mathematical models have proved to be successful in reverse engineering the system. The data generated is interpreted to understand the dynamics of the underlying phenomena. The question we have sought to answer is that - is it possible to use an agent-based approach to re-engineer a biological process, making use of the available knowledge from experimental and modelling efforts? Can the bottom-up approach benefit from the top-down exercise so as to create an integrated modelling formalism for systems biology? We propose a modelling pipeline that learns from the data given by reverse engineering, and uses it for re-engineering the system, to carry out in-silico experiments.

Results

A mathematical model that quantitatively predicts co-expression of EGFR-HER2 receptors in activation and trafficking has been taken for this study. The pipeline architecture takes cues from the population model that gives the rates of biochemical reactions, to formulate knowledge-based rules for the particle model. Agent-based simulations using these rules, support the existing facts on EGFR-HER2 dynamics. We conclude that, re-engineering models, built using the results of reverse engineering, opens up the possibility of harnessing the power pack of data which now lies scattered in literature. Virtual experiments could then become more realistic when empowered with the findings of empirical cell biology and modelling studies.

Availability and Implementation

Implemented on the Agent Modelling Framework developed in-house. C ++ code templates available in Supplementary material .

Contact

liz.csir@gmail.com.

Supplementary information

Supplementary data are available at Bioinformatics online.

Ligand-induced growth and compaction of CD36 nanoclusters enriched in Fyn induces Fyn signaling

Nanoclustering is an emerging organizational principle for membrane-associated proteins. The functional consequences of nanoclustering for receptor signaling remain largely unknown. Here, we applied quantitative multi-channel high- and super-resolution imaging to analyze the endothelial cell surface receptor CD36, the clustering of which upon binding to multivalent ligands, such as the anti-angiogenic factor thrombospondin-1 (TSP-1), is thought to be crucial for signaling. We found that a substantial fraction of unligated CD36 exists in nanoclusters, which not only promote TSP-1 binding but are also enriched with the downstream effector Fyn. Exposure to multivalent ligands (TSP-1 or anti-CD36 IgM) that result in larger and denser CD36 clusters activates Fyn. Conversely, pharmacological perturbations that prevent the enhancement of CD36 clustering by TSP-1 abrogate Fyn activation. In both cases, there is no detectable change in Fyn enrichment at CD36 nanoclusters. These observations reveal a crucial role for the basal organization of a receptor into nanoclusters that are enriched with the signal-transducing downstream effectors of that receptor, such that enhancement of clustering by multivalent ligands is necessary and sufficient to activate the downstream effector without the need for its de novo recruitment.

Time-resolved multimodal analysis of Src Homology 2 (SH2) domain binding in signaling by receptor tyrosine kinases

While the affinities and specificities of SH2 domain-phosphotyrosine interactions have been well characterized, spatio-temporal changes in phosphosite availability in response to signals, and their impact on recruitment of SH2-containing proteins in vivo, are not well understood. To address this issue, we used three complementary experimental approaches to monitor phosphorylation and SH2 binding in human A431 cells stimulated with epidermal growth factor (EGF): 1) phospho-specific mass spectrometry; 2) far-Western blotting; and 3) live cell single-molecule imaging of SH2 membrane recruitment. Far-Western and MS analyses identified both well-established and previously undocumented EGF-dependent tyrosine phosphorylation and binding events, as well as dynamic changes in binding patterns over time. In comparing SH2 binding site phosphorylation with SH2 domain membrane recruitment in living cells, we found in vivo binding to be much slower. Delayed SH2 domain recruitment correlated with clustering of SH2 domain binding sites on the membrane, consistent with membrane retention via SH2 rebinding.

DOI:http://dx.doi.org/10.7554/eLife.11835.001

Individual cells in a multicellular organism must receive signals from the environment and from other cells, and adjust their behavior accordingly. Such signals may cause a cell to grow and multiply, move, or even die. Often these signals are received by receptor proteins, which span the cell membrane and thus provide a way for signals from outside the cell to cause changes inside the cell.

The tyrosine kinases are one such group of membrane receptors. When a signal binds to a tyrosine kinase, the receptor is activated and it can add chemical tags called phosphates to the part of itself, or a neighboring protein, that is inside the cell. These phosphates provide binding sites for other types of proteins, many of which contain a section called a SH2 domain. This transmits the signal and leads to further changes in the cell. However, there are over a hundred different SH2 domain-containing proteins in human cells and we do not have a clear picture of what exactly happens when receptor tyrosine kinases are activated.

Jadwin, Oh et al. have now looked at how the number of SH2 domain binding sites changes over time after a signal is received. The experiments used three different experimental approaches to study a tyrosine kinase called the Epidermal Growth Factor (EGF) receptor, which is often over-active in human cancers. Jadwin, Oh et al. found that the timing of the changes in the number of SH2 domain binding sites on EGF varied widely. The different methods provided different perspectives on exactly when the changes happen, for example, directly observing the binding of SH2 domains to the membrane of living cells under the microscope showed that binding was much slower than expected from other methods that used purified proteins in solutions. This might be due to the receptors taking a relatively long time to form clusters at the membrane after they receive a signal.

Further experiments suggested that what happens when EGF is activated may depend not only on the number of SH2 domain binding sites made, but also the timing and the physical arrangement of those sites. A long-term goal for further studies is to understand how various types of signals can lead to different outcomes in the cell.

DOI:http://dx.doi.org/10.7554/eLife.11835.002

Use of mechanistic models to integrate and analyze multiple proteomic datasets

Proteins in cell signaling networks tend to interact promiscuously through low-affinity interactions. Consequently, evaluating the physiological importance of mapped interactions can be difficult. Attempts to do so have tended to focus on single, measurable physicochemical factors, such as affinity or abundance. For example, interaction importance has been assessed on the basis of the relative affinities of binding partners for a protein of interest, such as a receptor. However, multiple factors can be expected to simultaneously influence the recruitment of proteins to a receptor (and the potential of these proteins to contribute to receptor signaling), including affinity, abundance, and competition, which is a network property. Here, we demonstrate that measurements of protein copy numbers and binding affinities can be integrated within the framework of a mechanistic, computational model that accounts for mass action and competition. We use cell line-specific models to rank the relative importance of protein-protein interactions in the epidermal growth factor receptor (EGFR) signaling network for 11 different cell lines. Each model accounts for experimentally characterized interactions of six autophosphorylation sites in EGFR with proteins containing a Src homology 2 and/or phosphotyrosine-binding domain. We measure importance as the predicted maximal extent of recruitment of a protein to EGFR following ligand-stimulated activation of EGFR signaling. We find that interactions ranked highly by this metric include experimentally detected interactions. Proteins with high importance rank in multiple cell lines include proteins with recognized, well-characterized roles in EGFR signaling, such as GRB2 and SHC1, as well as a protein with a less well-defined role, YES1. Our results reveal potential cell line-specific differences in recruitment.

Inhibition of Receptor Dimerization as a Novel Negative Feedback Mechanism of EGFR Signaling

Dimerization of the epidermal growth factor receptor (EGFR) is crucial for initiating signal transduction. We employed raster image correlation spectroscopy to continuously monitor the EGFR monomer-dimer equilibrium in living cells. EGFR dimer formation upon addition of EGF showed oscillatory behavior with a periodicity of about 2.5 min, suggesting the presence of a negative feedback loop to monomerize the receptor. We demonstrated that monomerization of EGFR relies on phospholipase Cγ, protein kinase C, and protein kinase D (PKD), while being independent of Ca2+ signaling and endocytosis. Phosphorylation of the juxtamembrane threonine residues of EGFR (T654/T669) by PKD was identified as the factor that shifts the monomer-dimer equilibrium of ligand bound EGFR towards the monomeric state. The dimerization state of the receptor correlated with the activity of an extracellular signal-regulated kinase, downstream of the EGFR. Based on these observations, we propose a novel, negative feedback mechanism that regulates EGFR signaling via receptor monomerization.

NetworkViewer: visualizing biochemical reaction networks with embedded rendering of molecular interaction rules

Background

Network representations of cell-biological signaling processes frequently contain large numbers of interacting molecular and multi-molecular components that can exist in, and switch between, multiple biochemical and/or structural states. In addition, the interaction categories (associations, dissociations and transformations) in such networks cannot satisfactorily be mapped onto simple arrows connecting pairs of components since their specifications involve information such as reaction rates and conditions with regard to the states of the interacting components. This leads to the challenge of having to reconcile competing objectives: providing a high-level overview without omitting relevant information, and showing interaction specifics while not overwhelming users with too much detail displayed simultaneously. This problem is typically addressed by splitting the information required to understand a reaction network model into several categories that are rendered separately through combinations of visualizations and/or textual and tabular elements, requiring modelers to consult several sources to obtain comprehensive insights into the underlying assumptions of the model.

Results

We report the development of an application, the Simmune NetworkViewer, that visualizes biochemical reaction networks using iconographic representations of protein interactions and the conditions under which the interactions take place using the same symbols that were used to specify the underlying model with the Simmune Modeler. This approach not only provides a coherent model representation but, moreover, following the principle of “overview first, zoom and filter, then details-on-demand,” can generate an overview visualization of the global network and, upon user request, presents more detailed views of local sub-networks and the underlying reaction rules for selected interactions. This visual integration of information would be difficult to achieve with static network representations or approaches that use scripted model specifications without offering simple but detailed symbolic representations of molecular interactions, their conditions and consequences in terms of biochemical modifications.

Conclusions

The Simmune NetworkViewer provides concise, yet comprehensive visualizations of reaction networks created in the Simmune framework. In the near future, by adopting the upcoming SBML standard for encoding multi-component, multi-state molecular complexes and their interactions as input, the NetworkViewer will, moreover, be able to offer such visualization for any rule-based model that can be exported to that standard.

Recruitment of the adaptor protein Grb2 to EGFR tetramers

Adaptor protein Grb2 binds phosphotyrosines in the epidermal growth factor (EGF) receptor (EGFR) and thereby links receptor activation to intracellular signaling cascades. Here, we investigated how recruitment of Grb2 to EGFR is affected by the spatial organization and quaternary state of activated EGFR. We used the techniques of image correlation spectroscopy (ICS) and lifetime-detected Förster resonance energy transfer (also known as FLIM-based FRET or FLIM–FRET) to measure ligand-induced receptor clustering and Grb2 binding to activated EGFR in BaF/3 cells. BaF/3 cells were stably transfected with fluorescently labeled forms of Grb2 (Grb2–mRFP) and EGFR (EGFR–eGFP). Following stimulation of the cells with EGF, we detected nanometer-scale association of Grb2–mRFP with EGFR–eGFP clusters, which contained, on average, 4 ± 1 copies of EGFR–eGFP per cluster. In contrast, the pool of EGFR–eGFP without Grb2–mRFP had an average cluster size of 1 ± 0.3 EGFR molecules per punctum. In the absence of EGF, there was no association between EGFR–eGFP and Grb2–mRFP. To interpret these data, we extended our recently developed model for EGFR activation, which considers EGFR oligomerization up to tetramers, to include recruitment of Grb2 to phosphorylated EGFR. The extended model, with adjustment of one new parameter (the ratio of the Grb2 and EGFR copy numbers), is consistent with a cluster size distribution where 2% of EGFR monomers, 5% of EGFR dimers, <1% of EGFR trimers, and 94% of EGFR tetramers are associated with Grb2. Together, our experimental and modeling results further implicate tetrameric EGFR as the key signaling unit and call into question the widely held view that dimeric EGFR is the predominant signaling unit.

Dynamic transition states of ErbB1 phosphorylation predicted by spatial stochastic modeling

ErbB1 overexpression is strongly linked to carcinogenesis, motivating better understanding of erbB1 dimerization and activation. Recent single-particle-tracking data have provided improved measures of dimer lifetimes and strong evidence that transient receptor coconfinement promotes repeated interactions between erbB1 monomers. Here, spatial stochastic simulations explore the potential impact of these parameters on erbB1 phosphorylation kinetics. This rule-based mathematical model incorporates structural evidence for conformational flux of the erbB1 extracellular domains, as well as asymmetrical orientation of erbB1 cytoplasmic kinase domains during dimerization. The asymmetric dimer model considers the theoretical consequences of restricted transactivation of erbB1 receptors within a dimer, where the N-lobe of one monomer docks with the C-lobe of the second monomer and triggers its catalytic activity. The dynamic nature of the erbB1 phosphorylation state is shown by monitoring activation states of individual monomers as they diffuse, bind, and rebind after ligand addition. The model reveals the complex interplay between interacting liganded and nonliganded species and the influence of their distribution and abundance within features of the membrane landscape.

Model-based analysis of HER activation in cells co-expressing EGFR, HER2 and HER3

The HER/ErbB family of receptor tyrosine kinases drives critical responses in normal physiology and cancer, and the expression levels of the various HER receptors are critical determinants of clinical outcomes. HER activation is driven by the formation of various dimer complexes between members of this receptor family. The HER dimer types can have differential effects on downstream signaling and phenotypic outcomes. We constructed an integrated mathematical model of HER activation, and trafficking to quantitatively link receptor expression levels to dimerization and activation. We parameterized the model with a comprehensive set of HER phosphorylation and abundance data collected in a panel of human mammary epithelial cells expressing varying levels of EGFR/HER1, HER2 and HER3. Although parameter estimation yielded multiple solutions, predictions for dimer phosphorylation were in agreement with each other. We validated the model using experiments where pertuzumab was used to block HER2 dimerization. We used the model to predict HER dimerization and activation patterns in a panel of human mammary epithelial cells lines with known HER expression levels in response to stimulations with ligands EGF and HRG. Simulations over the range of expression levels seen in various cell lines indicate that: i) EGFR phosphorylation is driven by HER1-HER1 and HER1-HER2 dimers, and not HER1-HER3 dimers, ii) HER1-HER2 and HER2-HER3 dimers both contribute significantly to HER2 activation with the EGFR expression level determining the relative importance of these species, and iii) the HER2-HER3 dimer is largely responsible for HER3 activation. The model can be used to predict phosphorylated dimer levels for any given HER expression profile. This information in turn can be used to quantify the potencies of the various HER dimers, and can potentially inform personalized therapeutic approaches.

A family of cell surface molecules called the HER receptor family plays important roles in normal physiology and cancer. This family has four members, HER1-4. These receptors convert signals received from the extracellular environment into cell decisions such as growth and survival – a process termed signal transduction. In particular, HER2 and HER3 are over-expressed in a number of tumors, and their expression levels are associated with abnormal growth and poor clinical prognosis. A key step in HER-mediated signal transduction is the formation of dimer complexes between members of this family. Different dimer types have different potencies for activating normal and aberrant responses. Prediction of the dimerization pattern for a given HER expression level may pave the way for personalized therapeutic approaches targeting specific dimers. Towards this end, we constructed a mathematical model for HER dimerization and activation. We determined unknown model parameters by analyzing HER activation data collected in a panel of human mammary epithelial cells that express different levels of the HER molecules. The model enables us to quantitatively link HER expression levels to receptor dimerization and activation. Further, the model can be used to support additional quantitative investigations into the basic biology of HER-mediated signal transduction.

Visualization of BRI1 and BAK1(SERK3) membrane receptor heterooligomers during brassinosteroid signaling

The leucine-rich repeat receptor-like kinase BRASSINOSTEROID-INSENSITIVE1 (BRI1) is the main ligand-perceiving receptor for brassinosteroids (BRs) in Arabidopsis (Arabidopsis thaliana). Binding of BRs to the ectodomain of plasma membrane (PM)-located BRI1 receptors initiates an intracellular signal transduction cascade that influences various aspects of plant growth and development. Even though the major components of BR signaling have been revealed and the PM was identified as the main site of BRI1 signaling activity, the very first steps of signal transmission are still elusive. Recently, it was shown that the initiation of BR signal transduction requires the interaction of BRI1 with its SOMATIC EMBRYOGENESIS RECEPTOR-LIKE KINASE (SERK) coreceptors. In addition, the resolved structure of the BRI1 ectodomain suggested that BRI1-ASSOCIATED KINASE1 [BAK1](SERK3) may constitute a component of the ligand-perceiving receptor complex. Therefore, we investigated the spatial correlation between BRI1 and BAK1(SERK3) in the natural habitat of both leucine-rich repeat receptor-like kinases using comparative colocalization analysis and fluorescence lifetime imaging microscopy. We show that activation of BR signaling by exogenous ligand application resulted in both elevated colocalization between BRI1 and BAK1(SERK3) and an about 50% increase of receptor heterooligomerization in the PM of live Arabidopsis root epidermal cells. However, large populations of BRI1 and BAK1(SERK3) colocalized independently of BRs. Moreover, we could visualize that approximately 7% of the BRI1 PM pool constitutively heterooligomerizes with BAK1(SERK3) in live root cells. We propose that only small populations of PM-located BRI1 and BAK1(SERK3) receptors participate in active BR signaling and that the initiation of downstream signal transduction involves preassembled BRI1-BAK1(SERK3) heterooligomers.

Exploring higher-order EGFR oligomerisation and phosphorylation--a combined experimental and theoretical approach

The epidermal growth factor receptor (EGFR) kinase is generally considered to be activated by either ligand-induced dimerisation or a ligand-induced conformational change within pre-formed dimers. Ligand-induced higher-order EGFR oligomerisation or clustering has been reported but it is not clear how EGFR oligomers, as distinct from EGFR dimers, influence signaling outputs. To address this question, we combined measures of receptor clustering (microscopy; image correlation spectroscopy) and phosphorylation (Western blots) with modelling of mass-action chemical kinetics. A stable BaF/3 cell-line that contains a high proportion (>90%) of inactive dimers of EGFR-eGFP but no secreted ligand and no other detectable ErbB receptors was used as the model cell system. EGF at concentrations of greater than 1 nM was found to cluster EGFR-eGFP dimers into higher-order complexes and cause parallel increases in EGFR phosphorylation. The kinetics of EGFR clustering and phosphorylation were both rapid, plateauing within 2 minutes after stimulation with 30 nM EGF. A rule-based model was formulated to interpret the data. This model took into account ligand binding, ligand-induced conformational changes in the cytosolic tail, monomer-dimer-trimer-tetramer transitions via ectodomain- and kinase-mediated interactions, and phosphorylation. The model predicts that cyclic EGFR tetramers are the predominant phosphorylated species, in which activated receptor dimers adopt a cyclic side-by-side orientation, and that receptor kinase activation is stabilised by the intramolecular interactions responsible for cyclic tetramerization.

Analytical solution of steady-state equations for chemical reaction networks with bilinear rate laws

True steady states are a rare occurrence in living organisms, yet their knowledge is essential for quasi-steady-state approximations, multistability analysis, and other important tools in the investigation of chemical reaction networks (CRN) used to describe molecular processes on the cellular level. Here, we present an approach that can provide closed form steady-state solutions to complex systems, resulting from CRN with binary reactions and mass-action rate laws. We map the nonlinear algebraic problem of finding steady states onto a linear problem in a higher-dimensional space. We show that the linearized version of the steady-state equations obeys the linear conservation laws of the original CRN. We identify two classes of problems for which complete, minimally parameterized solutions may be obtained using only the machinery of linear systems and a judicious choice of the variables used as free parameters. We exemplify our method, providing explicit formulae, on CRN describing signal initiation of two important types of RTK receptor-ligand systems, VEGF and EGF-ErbB1.

Studying the role of lipid rafts on protein receptor bindings with cellular automata

It is widely accepted that lipid rafts promote receptor clustering and thereby facilitate signaling transduction. The role of lipid rafts in inducing and promoting receptor accumulation within the cell membrane has been explored by several computational and experimental studies. However, it remains unclear whether lipid rafts influence the recruitment and binding of proteins from the cytosol as well. To provide an answer to this question a spatial membrane model has been developed based on cellular automata. Our results indicate that lipid rafts indeed influence protein receptor bindings. In particular processes with slow dissociation and binding kinetics are promoted by lipid rafts, whereas fast binding processes are slightly hampered. However, the impact depends on a variety of parameters, such as the size and mobility of the lipid rafts, the induced slow down of receptors within rafts, and also the dissociation and binding kinetics of the cytosolic proteins. Thus, for any individual signaling pathway the influence of lipid rafts on protein binding might be different. To facilitate analyzing this influence given a specific pathway, our approach has been generalized into LiRaM, a modeling and simulation tool for lipid rafts models.

The impact of high density receptor clusters on VEGF signaling

Vascular endothelial growth factor (VEGF) signaling is involved in the process of blood vessel development and maintenance. Signaling is initiated by binding of the bivalent VEGF ligand to the membrane-bound receptors (VEGFR), which in turn stimulates receptor dimerization. Herein, we discuss experimental evidence that VEGF receptors localize in caveloae and other regions of the plasma membrane, and for other receptors, it has been shown that receptor clustering has an impact on dimerization and thus also on signaling. Overall, receptor clustering is part of a complex ecosystem of interactions and how receptor clustering impacts dimerization is not well understood. To address these questions, we have formulated the simplest possible model. We have postulated the existence of a single high affinity region in the cell membrane, which acts as a transient trap for receptors. We have defined an ODE model by introducing high- and low-density receptor variables and introduce the corresponding reactions from a realistic model of VEGF signal initiation. Finally, we use the model to investigate the relation between the degree of VEGFR concentration, ligand availability, and signaling. In conclusion, our simulation results provide a deeper understanding of the role of receptor clustering in cell signaling.

Ligand binding induces a conformational change in epidermal growth factor receptor dimers

The activation of the epidermal growth factor receptor (EGFR) kinase requires ligand binding to the extracellular domain (ECD). Previous reports demonstrate that the EGFR-ECD can be crystallized in two conformations - a tethered monomer or, in the presence of ligand, an untethered back-to-back dimer. We use Biosensor analysis to demonstrate that even in the monomeric state different C-terminal extensions of both truncated (EGFR(1-501))-ECD and full-length EGFR(1-621)-ECD can change the conformation of the ligand-binding site. The binding of a monoclonal antibody mAb806, which recognizes the dimer interface, to the truncated EGFR(1-501)-Fc fusion protein is reduced in the presence of ligand, consistent with a change in conformation. On the cell surface, the presence of erythroblastosis B2 (erbB2) increases the binding of mAb806 to the EGFR. The conformation of the erbB2: EGFR heterodimer interface changes when the cells are treated with epidermal growth factor (EGF). We propose that ligand induces kinase-inactive, pre-formed EGFR dimers and heterodimers to change conformation leading to kinase-active tetramers, where kinase activation occurs via an asymmetric interaction between EGFR dimers.

Mathematical simulation of membrane protein clustering for efficient signal transduction

Initiation and propagation of cell signaling depend on productive interactions among signaling proteins at the plasma membrane. These diffusion-limited interactions can be influenced by features of the membrane that introduce barriers, such as cytoskeletal corrals, or microdomains that transiently confine both transmembrane receptors and membrane-tethered peripheral proteins. Membrane topographical features can lead to clustering of receptors and other membrane components, even under very dynamic conditions. This review considers the experimental and mathematical evidence that protein clustering impacts cell signaling in complex ways. Simulation approaches used to consider these stochastic processes are discussed.

Modeling of tumor progression in NSCLC and intrinsic resistance to TKI in loss of PTEN expression

EGFR signaling plays a very important role in NSCLC. It activates Ras/ERK, PI3K/Akt and STAT activation pathways. These are the main pathways for cell proliferation and survival. We have developed two mathematical models to relate to the different EGFR signaling in NSCLC and normal cells in the presence or absence of EGFR and PTEN mutations. The dynamics of downstream signaling pathways vary in the disease state and activation of some factors can be indicative of drug resistance. Our simulation denotes the effect of EGFR mutations and increased expression of certain factors in NSCLC EGFR signaling on each of the three pathways where levels of pERK, pSTAT and pAkt are increased. Over activation of ERK, Akt and STAT3 which are the main cell proliferation and survival factors act as promoting factors for tumor progression in NSCLC. In case of loss of PTEN, Akt activity level is considerably increased. Our simulation results show that in the presence of erlotinib, downstream factors i.e. pAkt, pSTAT3 and pERK are inhibited. However, in case of loss of PTEN expression in the presence of erlotinib, pAkt level would not decrease which demonstrates that these cells are resistant to erlotinib.

Comprehensive binary interaction mapping of SH2 domains via fluorescence polarization reveals novel functional diversification of ErbB receptors

First-generation interaction maps of Src homology 2 (SH2) domains with receptor tyrosine kinase (RTK) phosphosites have previously been generated using protein microarray (PM) technologies. Here, we developed a large-scale fluorescence polarization (FP) methodology that was able to characterize interactions between SH2 domains and ErbB receptor phosphosites with higher fidelity and sensitivity than was previously achieved with PMs. We used the FP assay to query the interaction of synthetic phosphopeptides corresponding to 89 ErbB receptor intracellular tyrosine sites against 93 human SH2 domains and 2 phosphotyrosine binding (PTB) domains. From 358,944 polarization measurements, the affinities for 1,405 unique biological interactions were determined, 83% of which are novel. In contrast to data from previous reports, our analyses suggested that ErbB2 was not more promiscuous than the other ErbB receptors. Our results showed that each receptor displays unique preferences in the affinity and location of recruited SH2 domains that may contribute to differences in downstream signaling potential. ErbB1 was enriched versus the other receptors for recruitment of domains from RAS GEFs whereas ErbB2 was enriched for recruitment of domains from tyrosine and phosphatidyl inositol phosphatases. ErbB3, the kinase inactive ErbB receptor family member, was predictably enriched for recruitment of domains from phosphatidyl inositol kinases and surprisingly, was enriched for recruitment of domains from tyrosine kinases, cytoskeletal regulatory proteins, and RHO GEFs but depleted for recruitment of domains from phosphatidyl inositol phosphatases. Many novel interactions were also observed with phosphopeptides corresponding to ErbB receptor tyrosines not previously reported to be phosphorylated by mass spectrometry, suggesting the existence of many biologically relevant RTK sites that may be phosphorylated but below the detection threshold of standard mass spectrometry procedures. This dataset represents a rich source of testable hypotheses regarding the biological mechanisms of ErbB receptors.

Regulation from within: the cytoskeleton in transmembrane signaling

There is mounting evidence that the plasma membrane is highly dynamic and organized in a complex manner. The cortical cytoskeleton is proving to be a particularly important regulator of plasmalemmal organization, modulating the mobility of proteins and lipids in the membrane, facilitating their segregation, and influencing their clustering. This organization plays a critical role in receptor-mediated signaling, especially in the case of immunoreceptors, which require lateral clustering for their activation. Based on recent developments, we discuss the structures and mechanisms whereby the cortical cytoskeleton regulates membrane dynamics and organization, and how the nonuniform distribution of immunoreceptors and their self-association may affect activation and signaling.

Fast rebinding increases dwell time of Src homology 2 (SH2)-containing proteins near the plasma membrane

Receptor tyrosine kinases (RTKs) control a host of biological functions by phosphorylating tyrosine residues of intracellular proteins upon extracellular ligand binding. The phosphotyrosines (p-Tyr) then recruit a subset of ∼100 Src homology 2 (SH2) domain-containing proteins to the cell membrane. The in vivo kinetics of this process are not well understood. Here we use total internal reflection (TIR) microscopy and single-molecule imaging to monitor interactions between SH2 modules and p-Tyr sites near the cell membrane. We found that the dwell time of SH2 modules within the TIR illumination field is significantly longer than predictions based on chemical dissociation rate constants, suggesting that SH2 modules quickly rebind to nearby p-Tyr sites after dissociation. We also found that, consistent with the rebinding model, the effective diffusion constant is negatively correlated with the respective dwell time for different SH2 domains and the dwell time is positively correlated with the local density of RTK phosphorylation. These results suggest a mechanism whereby signal output can be regulated through the spatial organization of multiple binding sites, which will prompt reevaluation of many aspects of RTK signaling, such as signaling specificity, mechanisms of spatial control, and noise suppression.

Cross-suppression of EGFR ligands amphiregulin and epiregulin and de-repression of FGFR3 signalling contribute to cetuximab resistance in wild-type KRAS tumour cells

BACKGROUND

In addition to the mutational status of KRAS, the epidermal growth factor receptor (EGFR) ligands amphiregulin (AREG) and epiregulin (EREG) might function as bona fide biomarkers of cetuximab (Ctx) sensitivity for most EGFR-driven carcinomas.

METHODS

Lentivirus-delivered small hairpin RNAs were employed to specifically reduce AREG or EREG gene expression in wild-type KRAS A431 squamous cell carcinoma cells. Colony-forming assays were used to monitor the impact of AREG and EREG knockdown on Ctx efficacy. Amphiregulin and EREG protein expression levels were assessed by quantitative ELISA in parental A431 cells and in pooled populations of A431 cells adapted to grow in the presence of Ctx. A phosphoproteomic platform was used to measure the relative level of phosphorylation of 42 distinct receptor tyrosine kinases before and after the acquisition of resistance to Ctx.

RESULTS

Stable gene silencing of either ligand was found to notably reduce the expression of the other ligand. Parental A431 cells with normal expression levels of AREG/EREG exhibited significantly increased growth inhibition in response to Ctx, compared with derivatives that are engineered to produce minimal AREG/EREG. The parental A431 cells acutely treated with Ctx exhibited reduced basal expression levels of AREG/EREG. Pooled populations of Ctx-resistant A431 cells expressed significantly lower levels of AREG/EREG and were insensitive to the downregulatory effects of Ctx. Phosphoproteomic screen identified a remarkable hyperactivation of FGFR3 in Ctx-resistant A431 cells, which gained sensitivity to the cytotoxic and apoptotic effects of the FGFR3 TK inhibitor PD173074. The A431 parental cells acutely treated with Ctx rapidly activated FGFR3 and their concomitant exposure to Ctx and PD173074 resulted in synergistic apoptosis.

CONCLUSION

Cross-suppression of AREG/EREG expression may explain the tight co-expression of AREG and EREG, as well as their tendency to be more highly expressed than other EGFR ligands to determine Ctx efficacy. The positive selection for Ctx-resistant tumour cells exhibiting AREG/EREG cross-suppression may have an important role in the emergence of Ctx resistance. As de-repression of FGFR3 activity rapidly replaces the loss of EGFR-ligand signalling in terms of cell proliferation and survival, combinations of Ctx and FGFR3-targeted drugs may be a valuable strategy to enhance the efficacy of single Ctx while preventing or delaying acquired resistance to Ctx.

Structural systems biology and multiscale signaling models

We review current advances in experimental as well as computational modeling and simulation approaches to structural systems biology, whose overall aim is to build quantitative models of signaling networks while retaining the crucial elements of molecular specificity. We briefly discuss the current and emerging experimental and computational methods, particularly focusing on hybrid and multiscale methods, and highlight several applications in cell signaling with quantitative and predictive capabilities. The scope of such models range from delineating protein-protein interactions to describing clinical implications.

An adaptive coarse graining method for signal transduction in three dimensions

The spatio-temporal landscape of the plasma membrane regulates activation and signal transduction of membrane bound receptors by restricting their two-dimensional mobility and by inducing receptor clustering. This regulation also extends to complex formation between receptors and adaptor proteins, which are the intermediate signaling molecules involved in cellular signaling that relay the received cues from cell surface to cytoplasm and eventually to the nucleus. Although their investigation poses challenging technical difficulties, there is a crucial need to understand the impact of the receptor diffusivity, clustering, and spatial heterogeneity, and of receptor-adaptor protein complex formation on the cellular signal transduction patterns. Building upon our earlier studies, we have developed an adaptive coarse-grained Monte Carlo method that can be used to investigate the role of diffusion, clustering and membrane corralling on receptor association and receptor-adaptor protein complex formation dynamics in three dimensions. The new Monte Carlo lattice based approach allowed us to introduce spatial resolution on the 2-D plasma membrane and to model the cytoplasm in three-dimensions. Being a multi-resolution approach, our new method makes it possible to represent various parts of the cellular system at different levels of detail and enabled us to utilize the locally homogeneous assumption when justified (e.g., cytoplasmic region away from the cell membrane) and avoid its use when high spatial resolution is needed (e.g., cell membrane and cytoplasmic region near the membrane) while keeping the required computational complexity manageable. Our results have shown that diffusion has a significant impact on receptor-receptor dimerization and receptor-adaptor protein complex formation kinetics. We have observed an "adaptor protein hopping" mechanism where the receptor binding proteins may hop between receptors to form short-lived transient complexes. This increased residence time of the adaptor proteins near cell membrane and their ability to frequently change signaling partners may explain the increase in signaling efficiency when receptors are clustered. We also hypothesize that the adaptor protein hopping mechanism can cause concurrent or sequential activation of multiple signaling pathways, thus leading to crosstalk between diverse biological functions.

Time-resolved in silico modeling of fine-tuned cAMP signaling in platelets: feedback loops, titrated phosphorylations and pharmacological modulation

Background

Hemostasis is a critical and active function of the blood mediated by platelets. Therefore, the prevention of pathological platelet aggregation is of great importance as well as of pharmaceutical and medical interest. Endogenous platelet inhibition is predominantly based on cyclic nucleotides (cAMP, cGMP) elevation and subsequent cyclic nucleotide-dependent protein kinase (PKA, PKG) activation. In turn, platelet phosphodiesterases (PDEs) and protein phosphatases counterbalance their activity. This main inhibitory pathway in human platelets is crucial for countervailing unwanted platelet activation. Consequently, the regulators of cyclic nucleotide signaling are of particular interest to pharmacology and therapeutics of atherothrombosis. Modeling of pharmacodynamics allows understanding this intricate signaling and supports the precise description of these pivotal targets for pharmacological modulation.

Results

We modeled dynamically concentration-dependent responses of pathway effectors (inhibitors, activators, drug combinations) to cyclic nucleotide signaling as well as to downstream signaling events and verified resulting model predictions by experimental data. Experiments with various cAMP affecting compounds including anti-platelet drugs and their combinations revealed a high fidelity, fine-tuned cAMP signaling in platelets without cross-talk to the cGMP pathway. The model and the data provide evidence for two independent feedback loops: PKA, which is activated by elevated cAMP levels in the platelet, subsequently inhibits adenylyl cyclase (AC) but as well activates PDE3. By multi-experiment fitting, we established a comprehensive dynamic model with one predictive, optimized and validated set of parameters. Different pharmacological conditions (inhibition, activation, drug combinations, permanent and transient perturbations) are successfully tested and simulated, including statistical validation and sensitivity analysis. Downstream cyclic nucleotide signaling events target different phosphorylation sites for cAMP- and cGMP-dependent protein kinases (PKA, PKG) in the vasodilator-stimulated phosphoprotein (VASP). VASP phosphorylation as well as cAMP levels resulting from different drug strengths and combined stimulants were quantitatively modeled. These predictions were again experimentally validated. High sensitivity of the signaling pathway at low concentrations is involved in a fine-tuned balance as well as stable activation of this inhibitory cyclic nucleotide pathway.

Conclusions

On the basis of experimental data, literature mining and database screening we established a dynamic in silico model of cyclic nucleotide signaling and probed its signaling sensitivity. Thoroughly validated, it successfully predicts drug combination effects on platelet function, including synergism, antagonism and regulatory loops.

Quantification of the brassinosteroid insensitive1 receptor in planta

In plants, green fluorescent protein (GFP) is routinely used to determine the subcellular location of fusion proteins. Here, we show that confocal imaging can be employed to approximate the number of GFP-labeled protein molecules present in living Arabidopsis (Arabidopsis thaliana) root cells. The technique involves calibration with soluble GFP to provide a usable protein concentration range within the confocal volume of the microscope. As a proof of principle, we quantified the Brassinosteroid Insensitive1 (BRI1) receptor fused to GFP, under control of its own promoter. The number of BRI1-GFP molecules per root epidermal cell ranges from 22,000 in the meristem and 130,000 in the elongation zone to 80,000 in the maturation zone, indicating that up to 6-fold differences in BRI1 receptor content exist. In contrast, when taking into account differences in cell size, BRI1-GFP receptor density in the plasma membrane is kept constant at 12 receptors μm⁻² in all cells throughout the meristem and elongation zone. Only the quiescent center and columella cells deviate from this pattern and have 5 to 6 receptors μm⁻². Remarkably, root cell sensitivity toward brassinosteroids appears to coincide with uniform meristem receptor density.

Spatio-temporal dependence of the signaling response in immune-receptor trafficking networks regulated by cell density: a theoretical model

Cell signaling processes involve receptor trafficking through highly connected networks of interacting components. The binding of surface receptors to their specific ligands is a key factor for the control and triggering of signaling pathways. In most experimental systems, ligand concentration and cell density vary within a wide range of values. Dependence of the signal response on cell density is related with the extracellular volume available per cell. This dependence has previously been studied using non-spatial models which assume that signaling components are well mixed and uniformly distributed in a single compartment. In this paper, a mathematical model that shows the influence exerted by cell density on the spatio-temporal evolution of ligands, cell surface receptors, and intracellular signaling molecules is developed. To this end, partial differential equations were used to model ligand and receptor trafficking dynamics through the different domains of the whole system. This enabled us to analyze several interesting features involved with these systems, namely: a) how the perturbation caused by the signaling response propagates through the system; b) receptor internalization dynamics and how cell density affects the robustness of dose-response curves upon variation of the binding affinity; and c) that enhanced correlations between ligand input and system response are obtained under conditions that result in larger perturbations of the equilibrium . Finally, the results are compared with those obtained by considering that the above components are well mixed in a single compartment.

Macroscopic law of conservation revealed in the population dynamics of Toll-like receptor signaling

Stimulating the receptors of a single cell generates stochastic intracellular signaling. The fluctuating response has been attributed to the low abundance of signaling molecules and the spatio-temporal effects of diffusion and crowding. At population level, however, cells are able to execute well-defined deterministic biological processes such as growth, division, differentiation and immune response. These data reflect biology as a system possessing microscopic and macroscopic dynamics. This commentary discusses the average population response of the Toll-like receptor (TLR) 3 and 4 signaling. Without requiring detailed experimental data, linear response equations together with the fundamental law of information conservation have been used to decipher novel network features such as unknown intermediates, processes and cross-talk mechanisms. For single cell response, however, such simplicity seems far from reality. Thus, as observed in any other complex systems, biology can be considered to possess order and disorder, inheriting a mixture of predictable population level and unpredictable single cell outcomes.

Dishevelled interacts with the DIX domain polymerization interface of Axin to interfere with its function in down-regulating β-catenin

Wnt/β-catenin signaling controls numerous steps in normal animal development and can also cause cancer if inappropriately activated. In the absence of Wnt, β-catenin is targeted continuously for proteasomal degradation by the Axin destruction complex, whose activity is blocked upon Wnt stimulation by Dishevelled, which recruits Axin to the plasma membrane and assembles it into a signalosome. This key event during Wnt signal transduction depends on dynamic head-to-tail polymerization by the DIX domain of Dishevelled. Here, we use rescue assays in Drosophila tissues and functional assays in human cells to show that polymerization-blocking mutations in the DIX domain of Axin disable its effector function in down-regulating Armadillo/β-catenin and its response to Dishevelled during Wnt signaling. Intriguingly, NMR spectroscopy revealed that the purified DIX domains of the two proteins interact with each other directly through their polymerization interfaces, whereby the same residues mediate both homo- and heterotypic interactions. This result implies that Dishevelled has the potential to act as a "natural" dominant-negative, binding to the polymerization interface of Axin's DIX domain to interfere with its self-assembly, thereby blocking its effector function.