Signaling complexes: biophysical constraints on intracellular communication

Proteomics of membrane receptors and signaling

Receptors represent an abundant class of integral membrane proteins that transmit information on various types of signals within the cell. Assemblages of receptors and their interacting proteins (receptor complexes) have emerged as important units of signal transduction for various types of receptors including G protein coupled, ligand-gated ion channel, and receptor tyrosine kinase. This review aims to summarize the major approaches and findings of receptor proteomics. Isolation and characterization of receptor complexes from cells has become common using the methods of immunoaffinity-, ligand-, and tag-based chromatography followed by MS for the analysis of enriched receptor preparations. In addition, tools such as stable isotope labeling have contributed to understanding quantitative properties and PTMs to receptors and their interacting proteins. As data from studies on receptor-protein interactions considerably expands, complementary approaches such as bioinformatics and computational biology will undoubtedly play a significant role in defining cellular and network functions for various types of receptor complexes. Findings from receptor proteomics may also shed light on the mechanism of action for pharmacological drugs and can be of value in understanding molecular pathologies of disease states.

Three-state kinetic mechanism for scaffold-mediated signal transduction

Signaling events in eukaryotic cells are often guided by a scaffolding protein. Scaffold proteins assemble multiple proteins into a spatially localized signaling complex and exert numerous physical effects on signaling pathways. To study these effects, we consider a minimal, three-state kinetic model of scaffold-mediated kinase activation. We first introduce and apply a path summation technique to obtain approximate solutions to a single molecule master equation that governs protein kinase activation. We then consider exact numerical solutions. We comment on when this approximation is appropriate and then use this analysis to illustrate the competition of processes occurring at many time scales that are involved in signal transduction in the presence of a scaffold protein. We find that our minimal model captures how scaffold concentration can influence the times over which signaling is distributed in kinase cascades. For a range of scaffold concentrations, scaffolds allow for signaling to be distributed over multiple decades. The findings are consistent with recent experiments and simulation data. These results provide a framework and offer a mechanism for understanding how scaffold proteins can influence the shape of the waiting time distribution of kinase activation and effectively broaden the times over which protein kinases are activated in the course of cell signaling.

Increasing the efficiency of bacterial transcription simulations: when to exclude the genome without loss of accuracy

Background

Simulating the major molecular events inside an Escherichia coli cell can lead to a very large number of reactions that compose its overall behaviour. Not only should the model be accurate, but it is imperative for the experimenter to create an efficient model to obtain the results in a timely fashion. Here, we show that for many parameter regimes, the effect of the host cell genome on the transcription of a gene from a plasmid-borne promoter is negligible, allowing one to simulate the system more efficiently by removing the computational load associated with representing the presence of the rest of the genome. The key parameter is the on-rate of RNAP binding to the promoter (k_on), and we compare the total number of transcripts produced from a plasmid vector generated as a function of this rate constant, for two versions of our gene expression model, one incorporating the host cell genome and one excluding it. By sweeping parameters, we identify the k_on range for which the difference between the genome and no-genome models drops below 5%, over a wide range of doubling times, mRNA degradation rates, plasmid copy numbers, and gene lengths.

Results

We assess the effect of the simulating the presence of the genome over a four-dimensional parameter space, considering: 24 min <= bacterial doubling time <= 100 min; 10 <= plasmid copy number <= 1000; 2 min <= mRNA half-life <= 14 min; and 10 bp <= gene length <= 10000 bp. A simple MATLAB user interface generates an interpolated k_on threshold for any point in this range; this rate can be compared to the ones used in other transcription studies to assess the need for including the genome.

Conclusion

Exclusion of the genome is shown to yield less than 5% difference in transcript numbers over wide ranges of values, and computational speed is improved by two to 24 times by excluding explicit representation of the genome.

GPCR-Kir channel signaling complexes: defining rules of engagement

Ion channels and G protein-coupled receptors (GPCRs) are integral transmembrane proteins vital to a multitude of cell signaling and physiological functions. Members of these large protein families are known to interact directly with various intracellular protein partners in a dynamic and isoform-dependent manner, ultimately shaping their life cycle and signal output. The family of G protein-gated inwardly rectifying potassium channels (Kir3 or GIRK) expressed in brain, heart, and endocrine tissues were recently shown to stably associate with several different GPCRs, forming the basis of a macromolecular ion channel-GPCR signaling complex. The molecular determinants that mediate and maintain GPCR-Kir3 channel complexes are currently not well understood. Recent findings and emerging hypotheses on the assembly and stability of multiprotein GPCR-Kir channel signaling complexes are discussed, highlighting distinct mechanisms used by different Kir channel families. These protein-protein interaction processes are crucial in determining both the synaptic response times and the extent of GPCR "cross-talk" in Kir3-mediated inhibitory synaptic transmission.

Proteomic approaches to the analysis of multiprotein signaling complexes

Signal transduction is one of the most active fields in modern biomedical research. Increasing evidence has shown that signaling proteins associate with each other in characteristic ways to form large signaling complexes. These diverse structures operate to boost signaling efficiency, ensure specificity and increase sensitivity of the biochemical circuitry. Traditional methods of protein analysis are inadequate to fully characterize and understand these structures, which are intricate, contain many components and are highly dynamic. Instead, proteomics technologies are currently being applied to investigate the nature and composition of multimeric signaling complexes. This review presents commonly used and potential proteomic methods of analyzing diverse protein complexes along with a discussion and a brief evaluation of alternative approaches. Challenges associated with proteomic analysis of signaling complexes are also discussed.

Intracellular complexes of the beta2 subunit of the nicotinic acetylcholine receptor in brain identified by proteomics

Nicotine acetylcholine receptors (nAChRs) comprise a family of ligand-gated channels widely expressed in the mammalian brain. The beta2 subunit is an abundant protein subunit critically involved in the cognitive and behavioral properties of nicotine as well as in the mechanisms of nicotine addiction. In this work, we used matrix-assisted laser desorption ionization time-of-flight tandem mass spectrometry (MALDI-TOF-TOF MS/MS) to uncover protein interactions of the intracellular loop of the beta2 subunit and components of immunoprecipitated beta2-nAChR complexes from mouse brain. Using the beta2-knockout mouse to exclude nonspecific binding to the beta2 antibody, we identify 21 nAChR-interacting proteins (NIPs) expressed in brain. Western blot analysis confirmed the association between the beta2 subunit and candidate NIPs. Based on their functional profiles, the hypothesis is suggested that the identified NIPs can regulate the trafficking and signaling of the beta2-nAChR. Interactions of the beta2 subunit with NIPs such as G protein alpha, G protein-regulated inducer of neurite outgrowth 1, and G protein-activated K(+) channel 1 suggest a link between nAChRs and cellular G protein pathways. These findings reveal intracellular interactions of the beta2 subunit and may contribute to the understanding of the mechanisms of nAChR signaling and trafficking in neurons.

Clustering of membrane raft proteins by the actin cytoskeleton

Cell membranes are laterally organized into functionally discrete domains that include the cholesterol-dependent membrane "rafts." However, how membrane domains are established and maintained remains unresolved and controversial but often requires the actin cytoskeleton. In this study, we used fluorescence resonance energy transfer to measure the role of the actin cytoskeleton in the co-clustering of membrane raft-associated fluorescent proteins (FPs) and FPs targeted to the nonraft membrane fraction. By fitting the fluorescence resonance energy transfer data to an isothermal binding equation, we observed a specific co-clustering of raft-associated donor and acceptor probes that was sensitive to latrunculin B (Lat B), which disrupts the actin cytoskeleton. Conversely, treating with jasplakinolide to enhance actin polymerization increased co-clustering of the raft-associated FPs over that of the nonraft probes. We also observed by immunoblotting experiments that the actin-dependent co-clustering coincided with regulation of the raft-associated Src family kinase Lck. Specifically, Lat B decreased the phosphorylation of the C-terminal regulatory tyrosine of Lck (Tyr505), and combining the Lat B with filipin further decreased the Tyr505 phosphorylation. Furthermore, the Lat B-dependent changes in Lck regulation required CD45 because no significant changes occurred in treated T cells lacking CD45 expression. These data define a role for the actin cytoskeleton in promoting co-clustering of raft-associated proteins and show that this property is important toward regulating raft-associated signaling proteins such as Lck.

A proteomic approach to receptor signaling: Molecular mechanisms and therapeutic implications derived from discovery of the dopamine D2 receptor signalplex

Recent research in cell signaling has shown that the assembly of G protein coupled receptors into signaling complexes or signalplexes represents the primary mechanism by which receptor-mediated signaling is established and maintained. In this review, we summarize the current state of knowledge regarding protein interactions that comprise the dopamine D2 receptor signalplex within the brain. Studies based on conventional and advanced two-hybrid methodologies, as well as bioinformatic and computational analysis of sequence information from completed genomes have demonstrated interactions between dopamine D2 receptors and a cohort of dopamine receptor interacting proteins (DRIPs). DRIP interactions appear to regulate key aspects of receptor function including the signaling and membrane trafficking of dopamine D2 receptors. Disruptions or modifications of the signalplex, using membrane permeant competing peptide or dominant negative approaches, may represent promising new strategies for the selective targeting of the dopamine D2 receptor in cells and in native tissue. DRIP interactions provide a novel platform for understanding the mechanisms of dopamine receptor signaling, and for the potential development of novel treatments for brain disease.

Scaffold proteins confer diverse regulatory properties to protein kinase cascades

The assembly of multiple signaling proteins into a complex by a scaffold protein guides many cellular decisions. Despite recent advances, the overarching principles that govern scaffold function are not well understood. We carried out a computational study using kinetic Monte Carlo simulations to understand how spatial localization of kinases on a scaffold may regulate signaling under different physiological conditions. Our studies identify regulatory properties of scaffold proteins that allow them to both amplify and attenuate incoming signals in different biological contexts. These properties are not caused by the well established prozone or combinatorial inhibition effect. These results bring coherence to seemingly paradoxical observations and suggest that cells have evolved design rules that enable scaffold proteins to regulate widely disparate cellular functions.

Monitoring protein interactions in the living cell through the fluorescence decays of the cyan fluorescent protein

Using fluorescence lifetime microspectroscopy and imaging techniques, we have studied the fluorescence of cyan fluorescent protein (CFP) transiently expressed in HEK-293 cells, in the presence or absence of its fluorescence resonance energy transfer (FRET) partner, yellow fluorescent protein (YFP). When the two proteins are attached through a 27-amino-acid linker, a 33 % average efficiency of intramolecular energy transfer is accurately determined inside the cell. Additionally, we observe a systematic quenching of the CFP fluorescence with increasing levels of protein expression. This quenching cannot be accounted for by formation of the previously described dimer of GFP-related proteins, since its magnitude is unchanged when the fluorescent proteins carry the mutation A206K shown to dissociate this dimer in vitro. Even when the intracellular protein concentration largely exceeds the in vitro dissociation constant of the dimer, self-association remains undetectable, either between free proteins or intramolecularly within the CFP-YFP construct. Instead, the detailed concentration effects are satisfactorily accounted for by a model of intermolecular, concentration-dependent energy transfer, arising from molecular proximity and crowding. In the case of CFP alone, we suggest that self-quenching could result from a pseudo-homo FRET mechanism between different, spectrally shifted emissive forms of the protein. These phenomena require careful consideration in intracellular FRET studies.

Structure and dynamics of crystalline protein layers bound to supported lipid bilayers

We study proteins at the surface of bilayer membranes using streptavidin and avidin bound to biotinylated lipids in a supported lipid bilayer (SLB) at the solid-liquid interface. Using X-ray reflectivity and simultaneous fluorescence microscopy, we characterize the structure and fluidity of protein layers with varied relative surface coverages of crystalline and noncrystalline protein. With continuous bleaching, we measure a 10-15% decrease in the fluidity of the SLB after the full protein layer is formed. We propose that this reduction in lipid mobility is due to a small fraction (0.04) of immobilized lipids bound to the protein layer that create obstacles to membrane diffusion. Our X-ray reflectivity data show a 40 A thick layer of protein, and we resolve an 8 A layer separating the protein layer from the bilayer. We suggest that the separation provided by this water layer allows the underlying lipid bilayer to retain its fluidity and stability.

The use of a generalized born model for the analysis of protein conformational transitions: a comparative study with explicit solvent simulations for chemotaxis Y protein (CheY)

To investigate whether implicit solvent models are appropriate for mechanistic studies of conformational transition in proteins, a recently developed generalized Born model (GBSW) was applied to a small signaling protein, chemotaxis protein Y (CheY), with different combinations of the phosphorylation state and conformation of the system; the results were compared to explicit solvent simulations using a stochastic boundary condition. The subtle but distinct conformational transitions involved in CheY activation makes the system ideally suited for comparing implicit and explicit solvent models because these conformational transitions are potentially accessible in both types of simulations. The structural and dynamical properties analyzed include not only those localized to the active site region but also throughout the protein, such as sidechain methyl group order parameters, backbone hydrogen bonding lifetime and occupancy as well as principal components of the trajectories. Overall, many properties were well reproduced by the GBSW simulations when compared with the explicit solvent calculations, although a number of observations consistently point to the suggestion that the current parameterization of the GBSW model tends to overestimate hydrogen-bonding interactions involving both charged groups and (charge-neutral) backbone atoms. This deficiency led to overstabilization of certain secondary structural motifs and more importantly, qualitatively different behaviors for the active site groups (Thr 87, Ala 88, the beta4-alpha4 loop) in response to phosphorylation, when compared with explicit solvent simulations. The current study highlights the value of carrying out both explicit and implicit solvent simulations for complementary mechanistic insights in the analysis of conformational transition in biomolecules.

Toward a mathematical model of the assembly and disassembly of membrane microdomains: comparison with experimental models

We study a model system in which lipid bilayers are created using variable (precisely known) proportions of phosphatidylcholine and cholesterol. The model membranes exhibit cholesterol-enriched microdomains that are analogous to the so-called "lipid rafts" that form in living cells. After briefly presenting some experimental results, we formulate and solve a novel mathematical model based on the Smoluchowski equations for coagulation and fragmentation. We present a comparison between the distribution of lipid-raft areas observed in experimental lipid bilayers, and that distribution predicted by the theoretical model. Excellent agreement between the experiments and theory is obtained, with minimal parameter fitting.

Extracting biochemical parameters for cellular modeling: A mean-field approach

Recent developments in molecular biology have made it feasible to carry out experimental verification of mathematical models for biochemical processes, offering the eventual prospect of creating a detailed, validated picture of gene expression. A persistent difficulty with this long-term goal is the incompleteness of the kinetic information available in the literature: Many rate constants cannot or have not yet been measured. Here, we present a method of filling in missing parameters using an approach conceptually analogous to mean-field approaches in statistical mechanics: When studying a particular gene, we extract key parameters by considering the averaged effect of all other genes in the system, analogously to considering the averaged magnetic field in a physical spin model. This methodology has been applied to account for the effect of the presence of the Escherichia coli genome on the availability of key enzymes involved in gene expression (RNA polymerases and ribosomes), yielding the number of free enzymes as a function of cellular growth rate. These conclusions have been obtained by deriving genome-wide averages and matching them to bulk literature values of E. coli K-12 and B/r. Average rate constants have been found for RNA polymerases and ribosomes binding to promoter and ribosome-binding sites, respectively; these results suggest that cells vary not only their production rates of RNA polymerase and ribosomes under different growth-rate conditions but also change their global level of transcriptional/translational activation and repression, thus altering the average binding rate constants for these enzymes. To test the mean-field method, the results from the genome-wide averages have been applied to the induced lac operon, where our derived on-rate for binding of RNA polymerase to the promoter is in good agreement with previous experimental results.

The Multi-PDZ domain protein MUPP1 as a lipid raft-associated scaffolding protein controlling the acrosome reaction in mammalian spermatozoa

The success of acrosomal exocytosis, a complex process with a variety of interrelated steps, relies on the coordinated interaction of participating signaling molecules. Since scaffolding proteins are known to spatially organize sequential signaling pathways, we examined whether the Multi-PDZ domain protein MUPP1, recently identified in mammalian spermatozoa, is functionally active in controlling acrosomal secretion in mammalian sperm cells. To address this question, permeabilized mouse sperm were loaded with inhibitory antibodies against MUPP1 as well as with a photosensitive Ca(2+) chelator which allows a controlled release of acrosomal Ca(2+). The results revealed that MUPP1 controls initial tethering and docking of the acrosomal vesicle, whereas syntaxin 2, a t-SNARE protein also expressed in the acrosomal cap of mammalian spermatozoa, appears to take part in the final process of acrosomal fusion. Interestingly, using immunogold electron microscopy, it was found that MUPP1 is detectable in the region of the periacrosomal membrane. Furthermore, in isolated detergent-insoluble glycolipid-enriched membrane domains from epididymal spermatozoa, MUPP1 was found to show a striking association with the Triton X-100 insoluble membrane fraction, which did not change significantly upon sperm capacitation or partial chemical extraction of cholesterol. This evidence points to a role of MUPP1 as a membrane raft-associated molecular organizer, and suggests that mammalian spermatozoa may use a scaffolding protein and distinct membrane subdomains to spatially organize components involved in the process of acrosomal exocytosis.

Transient directed motions of GABA(A) receptors in growth cones detected by a speed correlation index

Single-molecule tracking of membrane proteins has become an important tool for investigating dynamic processes in live cells, such as cell signaling, membrane compartmentation or trafficking. The extraction of relevant parameters, such as interaction times between molecular partners or confinement-zone sizes, from the trajectories of single molecules requires appropriate statistical methods. Here we report a new tool, the speed correlation index, designed to detect transient periods of directed motion within trajectories of diffusing molecules. The ability to detect such events in a wide range of biologically relevant parameter values (speed, diffusion coefficient, and durations of the directed period) was first established on simulated data. The method was next applied to analyze the trajectories of quantum-dot-labeled GABA(A) receptors in nerve growth cones. The use of the speed correlation index revealed that the receptors had a "conveyor belt" type of motion due to temporary interactions ( approximately 4.0 s) between the receptors and the microtubules, leading to an average directed motion (velocity approximately 0.3 mum s(-1)) in the growth-cone membrane. Our observations point to the possibility of a cytoskeleton-dependent redistribution of the sensing molecules in the membrane, which could play a role in the modulation of the cell response to external signals.

On the origins of a crowded cytoplasm

Contemporary cells show a highly crowded macromolecular content, the processes which originated this state being largely unknown. We propose that a driving force leading to the crowded cellular state could be the increase in growth rate produced by an enhanced cytoplasmic protein concentration. Briefly, in a diluted scenario, an increase in protein concentration has two opposing effects on growth rate. The favorable effect is the increase in the activity per unit volume of the component proteins and the disadvantageous effect is the concomitant increase in the protein mass per unit volume which has to be produced. In this work we show that the first effect is quantitatively more important, resulting in an overall increase in growth rate. This result was obtained with a model of E. coli and using nonmechanistic physiological arguments. The proposed driving force operates even at low protein concentrations, where the nonspecific interactions of macromolecular crowding are not significant, and could be as ancient as the first protocells. Experimental measurement of this cytoplasmic protein concentration effect in present organisms is hindered by the prevailing nonspecific interactions, product of long-term evolution. However, chemical/biochemical systems, built up to mimic properties of living cells, could be an adequate tool to test this effect.

A finite element framework for studying the mechanical response of macromolecules: application to the gating of the mechanosensitive channel MscL

The gating pathways of mechanosensitive channels of large conductance (MscL) in two bacteria (Mycobacterium tuberculosis and Escherichia coli) are studied using the finite element method. The phenomenological model treats transmembrane helices as elastic rods and the lipid membrane as an elastic sheet of finite thickness; the model is inspired by the crystal structure of MscL. The interactions between various continuum components are derived from molecular-mechanics energy calculations using the CHARMM all-atom force field. Both bacterial MscLs open fully upon in-plane tension in the membrane and the variation of pore diameter with membrane tension is found to be essentially linear. The estimated gating tension is close to the experimental value. The structural variations along the gating pathway are consistent with previous analyses based on structural models with experimental constraints and biased atomistic molecular-dynamics simulations. Upon membrane bending, neither MscL opens substantially, although there is notable and nonmonotonic variation in the pore radius. This emphasizes that the gating behavior of MscL depends critically on the form of the mechanical perturbation and reinforces the idea that the crucial gating parameter is lateral tension in the membrane rather than the curvature of the membrane. Compared to popular all-atom-based techniques such as targeted or steered molecular-dynamics simulations, the finite element method-based continuum-mechanics framework offers a unique alternative to bridge detailed intermolecular interactions and biological processes occurring at large spatial scales and long timescales. It is envisioned that such a hierarchical multiscale framework will find great value in the study of a variety of biological processes involving complex mechanical deformations such as muscle contraction and mechanotransduction.

Rearrangement of lipid ordered phases upon protein adsorption due to multiple site binding

This study involves the interactions of proteins with Langmuir monolayers of a metal-chelating lipid, where adsorption is driven by a strong specific interaction between histidines on the proteins and divalent metal ions loaded into the lipid headgroups. A comparison of the structural rearrangement of the lipid film upon adsorption of myoglobin and a synthetic peptide, each of which have multiple histidines, with that upon the adsorption of lysozyme, which has only one histidine, suggests that the lipid rearrangement in the former case is due to the multiplicity of binding sites. The kinetics and manner of rearrangement change with the binding energy and film pressure.

Stochastic dynamics of macromolecular-assembly networks

The formation and regulation of macromolecular complexes provides the backbone of most cellular processes, including gene regulation and signal transduction. The inherent complexity of assembling macromolecular structures makes current computational methods strongly limited for understanding how the physical interactions between cellular components give rise to systemic properties of cells. Here, we present a stochastic approach to study the dynamics of networks formed by macromolecular complexes in terms of the molecular interactions of their components. Exploiting key thermodynamic concepts, this approach makes it possible to both estimate reaction rates and incorporate the resulting assembly dynamics into the stochastic kinetics of cellular networks. As prototype systems, we consider the lac operon and phage lambda induction switches, which rely on the formation of DNA loops by proteins and on the integration of these protein-DNA complexes into intracellular networks. This cross-scale approach offers an effective starting point to move forward from network diagrams, such as those of protein-protein and DNA-protein interaction networks, to the actual dynamics of cellular processes.

Cell-signalling dynamics in time and space

The specificity of cellular responses to receptor stimulation is encoded by the spatial and temporal dynamics of downstream signalling networks. Temporal dynamics are coupled to spatial gradients of signalling activities, which guide pivotal intracellular processes and tightly regulate signal propagation across a cell. Computational models provide insights into the complex relationships between the stimuli and the cellular responses, and reveal the mechanisms that are responsible for signal amplification, noise reduction and generation of discontinuous bistable dynamics or oscillations.

Synthetic multivalent ligands as probes of signal transduction

Cell-surface receptors acquire information from the extracellular environment and coordinate intracellular responses. Many receptors do not operate as individual entities, but rather as part of dimeric or oligomeric complexes. Coupling the functions of multiple receptors may endow signaling pathways with the sensitivity and malleability required to govern cellular responses. Moreover, multireceptor signaling complexes may provide a means of spatially segregating otherwise degenerate signaling cascades. Understanding the mechanisms, extent, and consequences of receptor co-localization and interreceptor communication is critical; chemical synthesis can provide compounds to address the role of receptor assembly in signal transduction. Multivalent ligands can be generated that possess a variety of sizes, shapes, valencies, orientations, and densities of binding elements. This Review focuses on the use of synthetic multivalent ligands to characterize receptor function.

Subcellular localization of protein kinase C delta and epsilon affects transcriptional and post-transcriptional processes in four-cell mouse embryos

During mouse preimplantation development, two isozymes of protein kinase C (PKC), delta and epsilon, transiently localize to nuclei at the early four-cell stage. In order to study their functions at this stage, we altered the subcellular localization of these isozymes (ratio of nuclear to cytoplasmic concentrations) with peptides that specifically activate or inhibit translocation of each isozyme. The effects of altering nuclear concentration of each isozyme on transcription (5-bromouridine 5'-triphosphate (BrUTP) incorporation), amount and distribution of small nuclear ribonucleoproteins (snRNPs), nucleolar dynamics (immunocytochemistry for Smith antigen (Sm) protein) and the activity of embryonic alkaline phosphatase (EAP; histochemistry) were examined. We found that nuclear concentration of PKC epsilon correlated with total mRNA transcription. Higher nuclear concentrations of both PKC delta and epsilon decreased storage of snRNPs in Cajal bodies and decreased the number of nucleoli, but did not affect the nucleoplasmic concentration of snRNPs. Inhibiting translocation of PKC delta out of the nucleus at the early four-cell stage decreased cytoplasmic EAP activity, whereas inhibiting translocation of PKC epsilon increased EAP activity slightly. These results indicate that translocation of PKC delta and epsilon in and out of nuclei at the early four-cell stage in mice can affect transcription or message processing, and that sequestration of these PKC in nuclei can also affect the activity of a cytoplasmic protein (EAP).

Spatial modeling of dimerization reaction dynamics in the plasma membrane: Monte Carlo vs. continuum differential equations

Bimolecular reactions in the plasma membrane, such as receptor dimerization, are a key signaling step for many signaling systems. For receptors to dimerize, they must first diffuse until a collision happens, upon which a dimerization reaction may occur. Therefore, study of the dynamics of cell signaling on the membrane may require the use of a spatial modeling framework. Despite the availability of spatial simulation methods, e.g., stochastic spatial Monte Carlo (MC) simulation and partial differential equation (PDE) based approaches, many biological models invoke well-mixed assumptions without completely evaluating the importance of spatial organization. Whether one is to utilize a spatial or non-spatial simulation framework is therefore an important decision. In order to evaluate the importance of spatial effects a priori, i.e., without performing simulations, we have assessed the applicability of a dimensionless number, known as second Damköhler number (Da), defined here as the ratio of time scales of collision and reaction, for 2-dimensional bimolecular reactions. Our study shows that dimerization reactions in the plasma membrane with Da approximately >0.1 (tested in the receptor density range of 10(2)-10(5)/microm(2)) require spatial modeling. We also evaluated the effective reaction rate constants of MC and simple deterministic PDEs. Our simulations show that the effective reaction rate constant decreases with time due to time dependent changes in the spatial distribution of receptors. As a result, the effective reaction rate constant of simple PDEs can differ from that of MC by up to two orders of magnitude. Furthermore, we show that the fluctuations in the number of copies of signaling proteins (noise) may also depend on the diffusion properties of the system. Finally, we used the spatial MC model to explore the effect of plasma membrane heterogeneities, such as receptor localization and reduced diffusivity, on the dimerization rate. Interestingly, our simulations show that localization of epidermal growth factor receptor (EGFR) can cause the diffusion limited dimerization rate to be up to two orders of magnitude higher at higher average receptor densities reported for cancer cells, as compared to a normal cell.

Building signaling complexes at the membrane

Cell membranes, the plasma membrane in particular, serve as the hub of various cellular signaling networks. In response to receptor activation, many cytosolic proteins are reversibly recruited to membranes to form dynamic signaling complexes. Membranes provide a unique microenvironment in which the formation of signaling complexes can be exquisitely modulated by the fine interplay between protein-protein and lipid-protein interactions.

Trading the micro-world of combinatorial complexity for the macro-world of protein interaction domains

Membrane receptors and proteins involved in signal transduction display numerous binding domains and operate as molecular scaffolds generating a variety of parallel reactions and protein complexes. The resulting combinatorial explosion of the number of feasible chemical species and, hence, different states of a network greatly impedes mechanistic modeling of signaling systems. Here we present novel general principles and identify kinetic requirements that allow us to replace a mechanistic picture of all possible micro-states and transitions by a macro-description of states of separate binding sites of network proteins. This domain-oriented approach dramatically reduces computational models of cellular signaling networks by dissecting mechanistic trajectories into the dynamics of macro- and meso-variables. We specify the conditions when the temporal dynamics of micro-states can be exactly or approximately expressed in terms of the product of the relative concentrations of separate domains. We prove that our macro-modeling approach equally applies to signaling systems with low population levels, analyzed by stochastic rather than deterministic equations. Thus, our results greatly facilitate quantitative analysis and computational modeling of multi-protein signaling networks.

Preface: the cellular communications maze

Inter- and intracellular ionic and molecular communications are indispensable to the preservation of life and all organic functions. The cell constantly responds to a myriad of extracellular ionic and molecular signals, and cell behavior in single-cell or multicellular organisms is coordinated by these signals moving into, inside, or between the cells. The signals pass through the cell's phospholipidic plasma membrane by diffusion and, mostly, via protein transporters: gates, receptors, and/or ion pumps imbedded in the membrane. Each signaling pathway is a complex cause and effect chain of events involving intricate networks of interactions. For example, the extracellular signals, which are monitored by the cell's membrane cognate receptors, form ligand-receptor complexes. These are typically amplified by interaction with a coupling protein, mostly a G protein, and are diversified via intracellular signal transductions, either directly or via the activation of intracellular second messengers. The present volume focuses on signal-induced interactions that trigger specific responses of the effector system. Highlighting the cellular communication framework and the major parameters encountered in these complex interactive phenomena may help to familiarize the uninitiated with the complex phenomena involved in sustaining life.

Adaptational assistance in clusters of bacterial chemoreceptors

Sensory adaptation of low-abundance chemoreceptors in Escherichia coli requires assistance from high-abundance receptors, because only high-abundance receptors carry the carboxyl-terminal pentapeptide sequence NWETF that enhances adaptational covalent modification. Using membrane vesicles containing both high-abundance receptor Tar and low-abundance receptor Trg, we observed effective assistance in vitro for all three adaptational modifications: methylation, demethylation and deamidation. These results demonstrated that adaptational assistance involves not only the previously documented assistance for methylation but also assistance for the two CheB-catalysed reactions. We determined rates of assisted methylation and demethylation at many ratios of assisting to assisted receptor. Analysis by a model of assistance indicated one Tar dimer could assist seven Trg dimers in methylation or five in demethylation, defining assistance neighbourhoods. These neighbourhoods were larger than a trimer of homodimers, required only receptors and were minimally affected by formation of signalling complexes. Time courses of assisted Trg methylation in membranes with low amounts of Tar showed that assisting receptors did not diffuse beyond initial neighbourhoods for at least two hours. Taken together, these observations indicate that chemoreceptors can form stable neighbourhoods larger than trimers in the absence of other chemotaxis proteins. Such interactions are likely to occur in natural receptor clusters in vivo.

Monitoring the formation of dynamic G-protein-coupled receptor-protein complexes in living cells

GPCRs (G-protein-coupled receptors) play an extremely important role in transducing extracellular signals across the cell membrane with high specificity and sensitivity. They are central to many of the body's endocrine and neurotransmitter pathways, and are consequently a major drug target. It is now clear that GPCRs interact with a range of proteins, including other GPCRs. Identifying and elucidating the function of such interactions will significantly enhance our understanding of cellular function, with the promise of new and improved pharmaceuticals. Biophysical techniques involving resonance energy transfer, namely FRET (fluorescence resonance energy transfer) and BRET (bioluminescence resonance energy transfer), now enable us to monitor the formation of dynamic GPCR-protein complexes in living cells, in real time. Their use has firmly established the concept of GPCR oligomerization, as well as demonstrating GPCR interactions with GPCR kinases, beta-arrestins, adenylate cyclase and a subunit of an inwardly rectifying K+ channel. The present review examines recent technological advances and experimental applications of FRET and BRET, discussing particularly how they have been adapted to extract an ever-increasing amount of information about the nature, specificity, stoichiometry, kinetics and agonist-dependency of GPCR-protein interactions.

The evolution of Ca2+ signalling in photosynthetic eukaryotes

It is likely that cytosolic Ca2+ elevations have played a part in eukaryotic signal transduction for about the last 2 Gyr, being mediated by a group of molecules which are collectively known as the [Ca2+]cyt signalling toolkit. Different eukaryotes often display strikingly similar [Ca2+]cyt signalling elevations, which may reflect conservation of toolkit components (homology) or similar constraints acting on different toolkits (homoplasy). Certain toolkit components, which are presumably ancestral, are shared by plants and animals, but some components are unique to photosynthetic organisms. We propose that the structure of modern plant [Ca2+]cyt signalling toolkits may be explained by their modular adaptation from earlier pathways.

Physical landscapes in biological membranes: physico-chemical terrains for spatio-temporal control of biomolecular interactions and behaviour

The evolving complexities of biological membranes are discussed from the point of view of potential roles of the physical constitution of the membrane. These include features of the surface and dipole potentials and membrane 'rafts'. These properties are outlined; they emphasize that protein-lipid and specific lipid environments are influential parameters in how biomolecular interactions may take place with and within membranes. Several fluorescence detection technologies directed towards measurement of these properties are also outlined that permit high-resolution experimental determination of intermolecular interactions with membranes by measuring small changes of these potentials. These point to the possibility that the membrane dipole potential in particular is enormously influential in determining the behaviour of receptor and signalling systems within membrane rafts, and offers the means of a novel mechanism for biological control.

Rapid hop diffusion of a G-protein-coupled receptor in the plasma membrane as revealed by single-molecule techniques

Diffusion of a G-protein coupled receptor, mu-opioid receptor (muOR), in the plasma membrane was tracked by single-fluorescent molecule video imaging and high-speed single-particle tracking. At variance with a previous publication, where gold-tagged muOR was found to be totally confined within a domain, which in turn underwent very slow diffusion itself, we found that muOR undergoes rapid hop diffusion over membrane compartments (210-nm and 730-nm nested double compartments in the case of normal rat kidney cell line), which are likely delimited by the actin-based membrane-skeleton "fence or corrals" and its associated transmembrane protein "pickets", at a rate comparable to that for transferrin receptor (every 45 and 760 ms on average, respectively), suggesting that the fence and picket models may also be applicable to G-protein coupled receptors. Further, we found that strong confinement of gold-labeled muOR could be induced by the prolonged on-ice preincubation of the gold probe with the cells, showing that this procedure should be avoided in future single-particle tracking experiments. Based on the dense, long trajectories of muOR obtained by high-speed single-particle tracking, the membrane compartments apposed and adjoined to each other could be defined that are delimited by rather straight boundaries, consistent with the involvement of actin filaments in membrane compartmentalization.

The pathobiology of the septin gene family

Septins are an evolutionarily conserved group of GTP-binding and filament-forming proteins that belong to the large superclass of P-loop GTPases. While originally discovered in yeast as cell division cycle mutants with cytokinesis defects, they are now known to have diverse cellular roles which include polarity determination, cytoskeletal reorganization, membrane dynamics, vesicle trafficking, and exocytosis. Septin proteins form homo- and hetero-oligomeric polymers which can assemble into higher-order filaments. They are also known to interact with components of the cytoskeleton, ie actin and tubulin. The precise role of GTP binding is not clear but a current model suggests that it is associated with conformational changes which alter binding to other proteins. There are at least 12 human septin genes, and although information on expression patterns is limited, most undergo complex alternative splicing with some degree of tissue specificity. Nevertheless, an increasing body of data implicates the septin family in the pathogenesis of diverse disease states including neoplasia, neurodegenerative conditions, and infections. Here the known biochemical properties of mammalian septins are reviewed in the light of the data from yeast and other model organisms. The data implicating septins in human disease are considered and a model linking these data is proposed. It is posited that septins can act as regulatable scaffolds where the stoichiometry of septin associations, modifications, GTP status, and the interactions with other proteins allow the regulation of key cellular processes including polarity determination. Derangements of such septin scaffolds thus explain the role of septins in disease states.

Simulating complex intracellular processes using object-oriented computational modelling

The aim of this paper is to give an overview of computer modelling and simulation in cellular biology, in particular as applied to complex biochemical processes within the cell. This is illustrated by the use of the techniques of object-oriented modelling, where the computer is used to construct abstractions of objects in the domain being modelled, and these objects then interact within the computer to simulate the system and allow emergent properties to be observed. The paper also discusses the role of computer simulation in understanding complexity in biological systems, and the kinds of information which can be obtained about biology via simulation.

Monte Carlo simulations of receptor dynamics: insights into cell signaling

Many receptor-level processes involve the diffusion and reaction of receptors with other membrane-localized molecules. Monte Carlo simulation is a powerful technique that allows us to track the motions and discrete reactions of individual receptors, thus simulating receptor dynamics and the early events of signal transduction. In this paper, we discuss simulations of two receptor processes, receptor dimerization and G-protein activation. Our first set of simulations demonstrates how receptor dimerization can create clusters of receptors via partner switching and the relevance of this clustering for receptor cross-talk and integrin signaling. Our second set of simulations investigates the activation and desensitization of G-protein coupled receptors when either a single agonist or both an agonist and an antagonist are present. For G-protein coupled receptor systems in the presence of an agonist alone, the dissociation rate constant of agonist is predicted to affect the ratio of G-protein activation to receptor phosphorylation. Similarly, this ratio is affected by the antagonist dissociation rate constant when both agonist and antagonist are present. The relationship of simulation predictions to experimental findings and potential applications of our findings are also discussed.

Distributed subunit interactions in CheA contribute to dimer stability: a sedimentation equilibrium study

The structural domains of the Escherichia coli CheA protein resemble 'beads on a string', since the N-terminal phosphate-accepting (P) domain is joined to the CheY/CheB-binding (B) domain through a flexible linker, and the B domain is in turn joined to the C-terminal dimerization/catalytic/regulatory domains by a second intervening linker. Dimerization occurs primarily via interactions between two dimerization domains, which is required for CheA trans-autophosphorylation. In this study, sedimentation equilibrium was used to demonstrate significant subunit interactions at secondary sites in the two naturally occurring (full-length and short) forms of CheA (CheA(1-654) or CheA(L), and CheA(98-654) or CheA(S)) by contrasting the dimerization of CheA(L) and CheA(S) to CheA(T), an engineered form that lacked the P domain entirely. The estimated dimer dissociation constant (K(1,2)) for CheA(T) (3.1 microM) was weaker than K(1,2) for CheA(L) (0.49 microM), which was attributed to the P domain-catalytic domain interactions that were present in CheA(L) but not CheA(T). In contrast, CheA(S) dimerization was unexpectedly stronger (K(1,2) approximately 20 nM), which arose through interactions between two P domain remnants in the CheA(S) dimer. This conclusion was supported by the results of sedimentation equilibrium experiments conducted with P domains and P domain remnants expressed in the absence of the dimerization/catalytic/regulatory domains. The P domain remnant had a measurable tendency to self-associate; the full-length P domain did not. Hydrophobic forces probably drive this interaction, since hydrophobic amino acids buried in the intact P domain are solvent-exposed in CheA(S). Also, the nascent N-terminus of CheA(S) bound to the phosphatase (CheZ) more effectively, a conclusion based on the demonstrably greater ability of the P domain remnant to co-sediment CheZ, compared to the intact P domain.

Stochastic model of protein-protein interaction: why signaling proteins need to be colocalized

Colocalization of proteins that are part of the same signal transduction pathway via compartmentalization, scaffold, or anchor proteins is an essential aspect of the signal transduction system in eukaryotic cells. If interaction must occur via free diffusion, then the spatial separation between the sources of the two interacting proteins and their degradation rates become primary determinants of the time required for interaction. To understand the role of such colocalization, we create a mathematical model of the diffusion based protein-protein interaction process. We assume that mRNAs, which serve as the sources of these proteins, are located at different positions in the cytoplasm. For large cells such as Drosophila oocytes we show that if the source mRNAs were at random locations in the cell rather than colocalized, the average rate of interactions would be extremely small, which suggests that localization is needed to facilitate protein interactions and not just to prevent cross-talk between different signaling modules.

Learning and evolution in bacterial taxis: an operational amplifier circuit modeling the computational dynamics of the prokaryotic ‘two component system’ protein network

Adaptive behavior in unicellular organisms (i.e., bacteria) depends on highly organized networks of proteins governing purposefully the myriad of molecular processes occurring within the cellular system. For instance, bacteria are able to explore the environment within which they develop by utilizing the motility of their flagellar system as well as a sophisticated biochemical navigation system that samples the environmental conditions surrounding the cell, searching for nutrients or moving away from toxic substances or dangerous physical conditions. In this paper we discuss how proteins of the intervening signal transduction network could be modeled as artificial neurons, simulating the dynamical aspects of the bacterial taxis. The model is based on the assumption that, in some important aspects, proteins can be considered as processing elements or McCulloch-Pitts artificial neurons that transfer and process information from the bacterium's membrane surface to the flagellar motor. This simulation of bacterial taxis has been carried out on a hardware realization of a McCulloch-Pitts artificial neuron using an operational amplifier. Based on the behavior of the operational amplifier we produce a model of the interaction between CheY and FliM, elements of the prokaryotic two component system controlling chemotaxis, as well as a simulation of learning and evolution processes in bacterial taxis. On the one side, our simulation results indicate that, computationally, these protein 'switches' are similar to McCulloch-Pitts artificial neurons, suggesting a bridge between evolution and learning in dynamical systems at cellular and molecular levels and the evolutive hardware approach. On the other side, important protein 'tactilizing' properties are not tapped by the model, and this suggests further complexity steps to explore in the approach to biological molecular computing.

The BglF sensor recruits the BglG transcription regulator to the membrane and releases it on stimulation

The Escherichia coli BglF protein is a sugar-sensor that controls the activity of the transcriptional antiterminator BglG by reversibly phosphorylating it, depending on beta-glucoside availability. BglF is a membrane-bound protein, whereas BglG is a soluble protein, and they are both present in the cell in minute amounts. How do BglF and BglG find each other to initiate signal transduction efficiently? Using bacterial two-hybrid systems and the Far-Western technique, we demonstrated unequivocally that BglG binds to BglF and to its active site-containing domain in vivo and in vitro. Measurements by surface plasmon resonance corroborated that the affinity between these proteins is high enough to enable their stable binding. To visualize the subcellular localization of BglG, we used fluorescence microscopy. In cells lacking BglF, the BglG-GFP fusion protein was evenly distributed throughout the cytoplasm. In contrast, in cells producing BglF, BglG-GFP was localized to the membrane. On addition of beta-glucoside, BglG-GFP was released from the membrane, becoming evenly distributed throughout the cell. Using mutant proteins and genetic backgrounds that impede phosphorylation of the Bgl proteins, we demonstrated that BglG-BglF binding and recruitment of BglG to the membrane sensor requires phosphorylation but does not depend on the individual phosphorylation sites of the Bgl proteins. We suggest a mechanism for rapid response to environmental changes by preassembly of signaling complexes, which contain transcription regulators recruited by their cognate sensors-kinases, under nonstimulating conditions, and release of the regulators to the cytoplasm on stimulation. This mechanism might be applicable to signaling cascades in prokaryotes and eukaryotes.

Specificity is complex and time consuming: mutual exclusivity in tyrosine kinase-mediated signaling

Most fundamental cellular processes are transduced through tyrosine kinase (TK)-mediated pathways. For transduction without corruption, the protein-protein interactions involved have to be mutually exclusive. Many of these proteins bind via homologous domains whose binding characteristics suggest that their innate specificity is not sufficiently high to account for the integrity of signal transduction. Stimulation of TK-mediated signals is often accompanied by recruitment of a precise, multimolecular protein complex that is itself capable of imposing specificity. Furthermore, this complex provides protection against phosphatase activity, controlling the longevity of the active signaling complex, and thus influencing outcomes in subsequent downstream events.

Four-dimensional organization of protein kinase signaling cascades: the roles of diffusion, endocytosis and molecular motors

Extracellular signals received by membrane receptors are processed, encoded and transferred to the nucleus via phosphorylation and spatial relocation of protein members of multiple component pathways, such as mitogen activated protein kinase (MAPK) cascades. The receptor-induced membrane recruitment of the cytoplasmic protein SOS results in the activation of the Ras/MAPK cascade. It has been suggested that the membrane recruitment of signaling proteins causes an increase in the diffusion-limited rates. We have recently shown that this increase is too small to be responsible for enhanced signal transduction. Instead we demonstrate that the function of membrane localization is to increase the number (or average lifetime) of complexes between signaling partners. A hallmark of signaling pathways is the spatial separation of activation and deactivation mechanisms; e.g. a protein can be phosphorylated at the cell surface by a membrane-bound kinase and dephosphorylated in the cytosol by a cytosolic phosphatase. Given the measured values of protein diffusion coefficients and of phosphatase and kinase activities, the spatial separation is shown to result in precipitous phospho-protein gradients. When information transfer is hampered by slow protein diffusion and rapid dephosphorylation, phospho-protein trafficking within endocytic vesicles may be an efficient way to deliver messages to physiologically relevant locations. The proposed mechanism explains recent observations that various inhibitors of endocytosis can inhibit MAPK activation. Additional mechanisms facilitating the relay of signals from cell-surface receptors to the nucleus can involve the assembly of protein kinases on a scaffolding protein and active transport of signaling complexes by molecular motors. We also discuss long-range signaling within a cell, such as survival signaling in neurons. We hypothesize that ligand-independent waves of receptor activation or/and traveling waves of phosphorylated kinases emerge to spread the signals over long distances.

On the role of self-recognition in T cell responses to foreign antigen

The key role of the thymus in shaping the peripheral T cell receptor (TCR) repertoire has been appreciated for nearly a quarter of a century. For most of that time, a single model has dominated thinking about the physiological role of the positive selection process mediated by TCR recognition of self-peptides and major histocompatibility complex (MHC) molecules. This developmental filter was believed to populate secondary lymphoid tissues with T cells bearing receptors best able to recognize unknown foreign peptides associated with the particular allelic forms of the MHC molecules present in an individual. More recently, self-recognition has been suggested to regulate the viability of naïve T cells. Here we focus on new results indicating that a critical contribution of positive selection to host defense is insuring that each peripheral T cell can use self-recognition to (i) enhance TCR signaling sensitivity upon foreign antigen recognition and (ii) augment the clonal expansion that accompanies limiting foreign antigen display at early points in an infectious process. We also detail new insights into the intracellular signaling circuitry that underlies the effective discrimination between low- and high-quality ligands of the TCR and speculate on how this design might facilitate an additional contribution of self-recognition to T cell activation in the presence of foreign stimuli.

G protein-coupled receptors form stable complexes with inwardly rectifying potassium channels and adenylyl cyclase

A large number of studies have demonstrated co-purification or co-immunoprecipitation of receptors with G proteins. We have begun to look for the presence of effector molecules in these receptor complexes. Co-expression of different channel and receptor permutations in COS-7 and HEK 293 cells in combination with co-immunoprecipitation experiments established that the dopamine D(2) and D(4), and beta(2)-adrenergic receptors (beta(2)-AR) form stable complexes with Kir3 channels. The D(4)/Kir3 and D(2) receptor/Kir3 interaction does not occur when the channel and receptor are expressed separately and mixed prior to immunoprecipitation, indicating that the interaction is not an artifact of the experimental protocol and reflects a biosynthetic event. The observed complexes are stable in that they are not disrupted by receptor activation or modulation of G protein alpha subunit function. However, using a peptide that binds Gbetagamma (betaARKct), we show that Gbetagamma is critical for dopamine receptor-Kir3 complex formation, but not for maintenance of the complex. We also provide evidence that Kir3 channels and another effector, adenylyl cyclase, are stably associated with the beta(2)-adrenergic receptor and can be co-immunoprecipitated by anti-receptor antibodies. Using bioluminescence resonance energy transfer, we have shown that in living cells under physiological conditions, beta(2)AR interacts directly with Kir3.1/3.4 and Kir3.1/3.2c heterotetramers as well as with adenylyl cyclase. All of these interactions are stable in the presence of receptor agonists, suggesting that these signaling complexes persist during signal transduction. In addition, we provide evidence that the receptor-effector complexes are also found in vivo. The observation that several G protein-coupled receptors form stable complexes with their effectors suggests that this arrangement might be a general feature of G protein-coupled signal transduction.