A new concept to reveal protein dynamics based on energy dissipation

Protein dynamics is essential for its function, especially for intramolecular signal transduction. In this work we propose a new concept, energy dissipation model, to systematically reveal protein dynamics upon effector binding and energy perturbation. The concept is applied to better understand the intramolecular signal transduction during allostery of enzymes. The E. coli allosteric enzyme, aspartokinase III, is used as a model system and special molecular dynamics simulations are designed and carried out. Computational results indicate that the number of residues affected by external energy perturbation (i.e. caused by a ligand binding) during the energy dissipation process shows a sigmoid pattern. Using the two-state Boltzmann equation, we define two parameters, the half response time and the dissipation rate constant, which can be used to well characterize the energy dissipation process. For the allostery of aspartokinase III, the residue response time indicates that besides the ACT2 signal transduction pathway, there is another pathway between the regulatory site and the catalytic site, which is suggested to be the β15-αK loop of ACT1. We further introduce the term "protein dynamical modules" based on the residue response time. Different from the protein structural modules which merely provide information about the structural stability of proteins, protein dynamical modules could reveal protein characteristics from the perspective of dynamics. Finally, the energy dissipation model is applied to investigate E. coli aspartokinase III mutations to better understand the desensitization of product feedback inhibition via allostery. In conclusion, the new concept proposed in this paper gives a novel holistic view of protein dynamics, a key question in biology with high impacts for both biotechnology and biomedicine.     

Mean-field Boolean network model of a signal transduction network

In this paper we provide a mean-field Boolean network model for a signal transduction network of a generic fibroblast cell. The network consists of several main signaling pathways, including the receptor tyrosine kinase, the G-protein coupled receptor, and the Integrin signaling pathway. The network consists of 130 nodes, each representing a signaling molecule (mainly proteins). Nodes are governed by Boolean dynamics including canalizing functions as well as totalistic Boolean functions that depend only on the overall fraction of active nodes. We categorize the Boolean functions into several different classes. Using a mean-field approach we generate a mathematical formula for the probability of a node becoming active at any time step. The model is shown to be a good match for the actual network. This is done by iterating both the actual network and the model and comparing the results numerically. Using the Boolean model it is shown that the system is stable under a variety of parameter combinations. It is also shown that this model is suitable for assessing the dynamics of the network under protein mutations. Analytical results support the numerical observations that in the long-run at most half of the nodes of the network are active.     

Module dynamics of the GnRH signal transduction network

We analyse computational modules of a frequency decoding signal transduction network. The gonadotropin releasing hormone (GnRH) signal transduction network mediates the biosynthesis and release of the gonadotropins, luteinizing hormone (LH) and follicle stimulating hormone (FSH). The pulsatile pattern of GnRH production by the hypothalamus has a critical influence on the release and synthesis of gonadotropins in the pituitary. In humans, slower pulses lead to the expression of the beta-subunit of the LH protein and cause anovulation and amenorrhea. Higher frequency pulses lead to expression of the alpha subunit and a hypogonadal state. The frequency sensitivity is a consequence of the structure of the GnRH signal transduction network. We analyse individual components of this network, organized into three network architectures, and describe the frequency-decoding capabilities of each of these modules. We find that these modules are comparable to simple circuit elements, some of which integrate and others which perform as frequency sensitive filters. We propose that the cell computes by exploiting variation in the time scales of protein activation (phosphorylation) and gene expression.     

The MAP kinase cascade. Discovery of a new signal transduction pathway

Using biochemical techniques similar to those used by Krebs and Fischer in elucidating the cAMP kinase cascade, a protein kinase cascade has been found that represents a new pathway for signal transduction. This pathway is activated in almost all cells that have been examined by many different growth and differentiations factors suggesting control of different cell responses. At this writing, four tiers of growth factor regulated kinases, each tier represented by more than one enzyme, have been reconstitutedin vitro to form the MAP kinase cascade. Preliminary findings suggesting multiple feedback or feedforward regulation of several components in the cascade predict higher complexity than a simple linear pathway.     

Mapping the intramolecular signal transduction of G‐protein coupled receptors

G‐protein coupled receptors (GPCRs), a major gatekeeper of extracellular signals on plasma membrane, are unarguably one of the most important therapeutic targets. Given the recent discoveries of allosteric modulations, an allosteric wiring diagram of intramolecular signal transductions would be of great use to glean the mechanism of receptor regulation. Here, by evaluating betweenness centrality (C_B) of each residue, we calculate maps of information flow in GPCRs and identify key residues for signal transductions and their pathways. Compared with preexisting approaches, the allosteric hotspots that our C_B‐based analysis detects for A_2A adenosine receptor (A_2AAR) and bovine rhodopsin are better correlated with biochemical data. In particular, our analysis outperforms other methods in locating the rotameric microswitches, which are generally deemed critical for mediating orthosteric signaling in class A GPCRs. For A_2AAR, the inter‐residue cross‐correlation map, calculated using equilibrium structural ensemble from molecular dynamics simulations, reveals that strong signals of long‐range transmembrane communications exist only in the agonist‐bound state. A seemingly subtle variation in structure, found in different GPCR subtypes or imparted by agonist bindings or a point mutation at an allosteric site, can lead to a drastic difference in the map of signaling pathways and protein activity. The signaling map of GPCRs provides valuable insights into allosteric modulations as well as reliable identifications of orthosteric signaling pathways. Proteins 2014; 82:727–743. © 2013 Wiley Periodicals, Inc.     

Early steps of the intramolecular signal transduction in rhodopsin explored by molecular dynamics simulations

We present molecular dynamics simulations of bovine rhodopsin in a membrane mimetic environment based on the recently refined X-ray structure of the pigment. The interactions between the protonated Schiff base and the protein moiety are explored both with the chromophore in the dark-adapted 11-cis and in the photoisomerized all-trans form. Comparison of simulations with Glu181 in different protonation states strongly suggests that this loop residue located close to the 11-cis bond bears a negative charge. Restrained molecular dynamics simulations also provide evidence that the protein tightly confines the absolute conformation of the retinal around the C12-C13 bond to a positive helicity. 11-cis to all-trans isomerization leads to an internally strained chromophore, which relaxes after a few nanoseconds by a switching of the ionone ring to an essentially planar all-trans conformation. This structural transition of the retinal induces in turn significant conformational changes of the protein backbone, especially in helix VI. Our results suggest a possible molecular mechanism for the early steps of intramolecular signal transduction in a prototypical G-protein-coupled receptor.     

A systems biology perspective on protein structural dynamics and signal transduction

The functional dynamics of signal transduction through protein interaction networks are determined both by network topology and by the signal processing properties of component proteins. In order to understand the emergent properties of signal transduction networks in terms of information processing, storage and decision making, we not only need to map the so-called 'interactome' but, perhaps more importantly, we also have to understand how the structural dynamics of constituent proteins shape non-linear responses through cooperativity and allostery. Several in silico methods have been developed to identify networks of cooperative residues in proteins and help infer their mode of action. Applying this type of analysis to important classes of modular signal transduction domains should, in principle, allow the function of these proteins to be abstracted in terms of their information processing characteristics, permitting better comprehension of the systemic properties of biological networks.     

Bacterial signal transduction network in a genomic perspective

Bacterial signalling network includes an array of numerous interacting components that monitor environmental and intracellular parameters and effect cellular response to changes in these parameters. The complexity of bacterial signalling systems makes comparative genome analysis a particularly valuable tool for their studies. Comparative studies revealed certain general trends in the organization of diverse signalling systems. These include (i) modular structure of signalling proteins; (ii) common organization of signalling components with the flow of information from N-terminal sensory domains to the C-terminal transmitter or signal output domains (N-to-C flow); (iii) use of common conserved sensory domains by different membrane receptors; (iv) ability of some organisms to respond to one environmental signal by activating several regulatory circuits; (v) abundance of intracellular signalling proteins, typically consisting of a PAS or GAF sensor domains and various output domains; (vi) importance of secondary messengers, cAMP and cyclic diguanylate; and (vii) crosstalk between components of different signalling pathways. Experimental characterization of the novel domains and domain combinations would be needed for achieving a better understanding of the mechanisms of signalling response and the intracellular hierarchy of different signalling pathways.     

A new model for chemotactic signal transduction in Dictyostelium discoideum

Dictyostelium discoideum amoebae were employed to study the refractoriness and adaptation of the rapid (5sec) accumulation of actin in their Triton-insoluble cytoskeletons following stimulation with specific chemoattractants. Amoebae became refractory within 10sec for this response but no adaptation occurred during this period. Amoebae desensitized for one attractant were not desensitized for another and responses to stimulation with a mixture of attractants were approximately additive. The characteristics of these processes are compared to published studies of adaptation in other chemoattractant-induced responses and a new model for the chemotactic signal transduction pathway is formulated. We conclude that intracellular cGMP accumulation may be on a separate branch of the pathway from the actin response.     

Epistasis in a model of molecular signal transduction

Biological functions typically involve complex interacting molecular networks, with numerous feedback and regulation loops. How the properties of the system are affected when one, or several of its parts are modified is a question of fundamental interest, with numerous implications for the way we study and understand biological processes and treat diseases. This question can be rephrased in terms of relating genotypes to phenotypes: to what extent does the effect of a genetic variation at one locus depend on genetic variation at all other loci? Systematic quantitative measurements of epistasis – the deviation from additivity in the effect of alleles at different loci – on a given quantitative trait remain a major challenge. Here, we take a complementary approach of studying theoretically the effect of varying multiple parameters in a validated model of molecular signal transduction. To connect with the genotype/phenotype mapping we interpret parameters of the model as different loci with discrete choices of these parameters as alleles, which allows us to systematically examine the dependence of the signaling output – a quantitative trait – on the set of possible allelic combinations. We show quite generally that quantitative traits behave approximately additively (weak epistasis) when alleles correspond to small changes of parameters; epistasis appears as a result of large differences between alleles. When epistasis is relatively strong, it is concentrated in a sparse subset of loci and in low order (e.g. pair-wise) interactions. We find that focusing on interaction between loci that exhibit strong additive effects is an efficient way of identifying most of the epistasis. Our model study defines a theoretical framework for interpretation of experimental data and provides statistical predictions for the structure of genetic interaction expected for moderately complex biological circuits.     

Brownian dynamics simulations of intramolecular energy transfer

A novel technique for modelling intramolecular energy transfer is presented. Brownian dynamics calculations are used to compute the trajectories of donor and acceptor species, and the instantaneous orientation factor is calculated during each temporal iteration. In this work, several model systems are considered. Trajectories were computed for energy transfer between a flexible donor and a rigidly fixed acceptor. We have considered configurations where the donor is, (1) tethered to a fixed point in space, but free to diffuse rotationally, and (2) constrained to wobble in a cone. The luminescence decay of the donor is ‘measured’, and a non-single-exponential decay is observed for configurations of efficient energy transfer. Luminescence anisotropy measurements of constrained and unconstrained donors reflect the contribution of both energy transfer and rotational diffusion to the shape of the anisotropy decay curve.     

Investigations into the relationship between feedback loops and functional importance of a signal transduction network based on Boolean network modeling

Background  

A number of studies on biological networks have been carried out to unravel the topological characteristics that can explain the functional importance of network nodes. For instance, connectivity, clustering coefficient, and shortest path length were previously proposed for this purpose. However, there is still a pressing need to investigate another topological measure that can better describe the functional importance of network nodes. In this respect, we considered a feedback loop which is ubiquitously found in various biological networks.     

GPCR和CaCC信号传导中的钙信号网络

G蛋白偶联受体(G protein-coupled receptor,GPCR)作为最大的一类人膜蛋白受体家族和最重要的药物靶标而倍受关注,其中钙离子在细胞内信号传导级联放大中起了关键的作用。阐述了GPCR和钙激活的氯离子通道蛋白(calcium-activated chloride channel,CaCC)中的钙信号网络与生理功能以及如何干扰阻断该网络,为药物设计和很多疾病的治疗提供了依据。     

Microtubule dynamics and signal transduction at the immunological synapse: new partners and new connections

EMBO J (2012) 31 21, 4140–4152 doi:10.1038/emboj.2012.242; published online August242012Antigen recognition induces T cells to polarize towards antigen presenting cells (APC) generating an organized cell interface named the immunological synapse. T-cell microtubules (MTs) reorient the MT-organizing centre (MTOC) to the immunological synapse central region, while MT irradiate towards the synapse periphery. Martín-Cófreces et al (2012) describe in this issue that the MT plus-end-binding protein 1 (EB1) interacts with TCR cytosolic regions and mediate the organization of an immunological synapse fully functional to transduce activation signals.The pioneer work of Kupfer and Singer (1989) established that T-cell MTs rearrange in response to specific TCR engagement by APCs, resulting in MTOC orientation to the APC contact site in helper and cytotoxic T cells. MTOC reorientation was shown to be the result of a MT polymerization dynamic process involving MT posttranslational modifications (Kuhn and Poenie, 2002; Serrador et al, 2004). MT reorganization during T-cell antigen recognition is functionally linked to T-cell effector functions, like the polarized secretion of helper cytokines to B cells (Kupfer et al, 1991; Huse et al, 2006), or cytotoxic granules to target cells (Stinchcombe et al, 2006). MTs also transport TCR-carrying endosomes during synapse formation (Das et al, 2004) and TCR signalling complexes at the immunological synapse (Lasserre et al, 2010; Hashimoto-Tane et al, 2011). Altogether, these findings show that the dynamic reorganization of MTs and its related molecular transport are critical for the organization and function of the immunological synapse.Martín-Cófreces et al (2012) present here interesting new insights, unveiling a link between EB1 and the TCR complex. EB1 is one of a series of MT plus-end-associated proteins critical for MT polymerization dynamics (Slep, 2010). The first important finding initially issued from a two-hybrid screening was that EB1 could directly interact with TCR complex cytosolic regions. By GST pull-down and co-immunoprecipitation experiments, the authors narrowed down this interaction to two of the TCR complex subunits, ζ and ɛ, in their ITAM (immuno-receptor tyrosine-based activation motif)-containing regions, and within the C-terminal 82 amino-acid region on EB1. In T cells, EB1–TCR interaction could occur without TCR stimulation, suggesting that EB1 plays a role in TCR dynamics previous to TCR engagement. The authors then investigated EB1 localization and its involvement in synapse organization and function. Live cell imaging showed intense EB1 movement in the synapse area, with MTs growing from the MTOC to the synapse periphery, leading to an apparent concentration of EB1 at the T cell–APC interface. To analyse the relationship between MT dynamics and intracellular transport, the authors followed EB1–GFP and TCRζ–Cherry by total internal reflection fluorescence (TIRF) microscopy in synapses formed on anti-CD3-coated cover slips. They observed transient coincident spots between EB1 and TCRζ+ vesicles, suggesting that growing MTs transport TCRζ-carrying vesicles towards the immunological synapse. Consistently, EB1-silenced cells displayed altered TCRζ vesicle dynamics and TCRζ clustering at the synapse. Likewise, vesicle transport to the synapse of the signalling scaffold molecule LAT and its clustering at the synapse were altered. Finally, they observed transient encounters between TCRζ- and LAT-carrying vesicles inhibited by EB1 silencing. These observations point out to a crucial role of EB1 and MT dynamics in the organization of the immunological synapse.Immunological synapse organization has been related with its capacity to regulate TCR signal transduction. Therefore, Martín-Cófreces et al (2012) investigated how EB1 silencing impacted TCR signalling. EB1-silenced cells were indeed impaired in key TCR signalling events, like LAT tyrosine phosphorylation, which allows LAT interaction with activation effectors, like the phospholipase C (PLC)γ, promoting TCR signal propagation. Consistently, PLCγ activation was impaired in EB1-silenced cells. However, upstream activation events, like tyrosine phosphorylation of TCRζ and of its associated protein tyrosine kinase ZAP70, were not altered. This suggests that MT-dependent LAT vesicle traffic is key for LAT phosphorylation and the generation of TCR signalling complexes.Altogether, Martín-Cófreces'' findings reinforce the idea that polarized vesicle transport via organized MT networks is key to set up the immunological synapse as a signal transduction platform. EB1 interaction with two TCR subunits may link the TCR complex with MTs dynamics. It remains unanswered, however, whether EB1 also interacts with LAT, facilitating the merging at the synapse of distinct TCRζ- and LAT-carrying vesicles.Vesicle traffic on MTs generally occurs via molecular motors from the dynein and kinesin families. The former are associated with minus end-oriented transport, whereas the later mostly ensures plus-end-associated transport. The immunological synapse may use both types of transport. Thus, cytotoxic granule delivery to the synapse may mainly involve dynein-mediated vesicle traffic, since the MTOC translocates very close to the immunological synapse (Stinchcombe et al, 2006). Likewise, centripetal movements of signalling microclusters at the synapse involve dynein (Hashimoto-Tane et al, 2011). Martín-Cófreces et al (2012) show that TCRζ- and LAT-carrying vesicles are transported towards MT plus ends in an EB1-dependent manner. It remains uncertain whether EB1 could play a direct transport role at the immunological synapse, helping the attachment of TCRζ vesicles to growing MT plus ends. Alternatively, EB1 could mediate MT interactions with TCR complexes present at the plasma membrane. Initial TCR clustering at the synapse would help capturing EB1-positive MT plus ends, orienting MTs and MT-mediated traffic of TCRζ- and LAT-carrying vesicles to the synapse by a kinesin-based transport (Figure 1), and promoting TCRζ and LAT encountering and clustering at the synapse. EB1 silencing would perturb MT–plasma membrane interactions impairing this MT orientation and transport loop. MT polymerization kinetic studies on immunological synapses formed by EB1-silenced versus control T cells may help to clarify this mechanism. Although further studies will be necessary to elucidate the detailed mechanism, the work by Martín-Cófreces et al (2012) already highlights the importance of MT dynamics and vesicle traffic in the formation of a functional immunological synapse, raising novel and interesting questions on how the MT network helps to set up complex signal transduction machineries.Open in a separate windowFigure 1Model of the role of EB1 in MT dynamics and TCR signal transduction at the immunological synapse. (A) Initial T cell–APC contact. TCR initial clustering would favour the capture of EB1-containing MT plus ends at the T cell–APC contact. (B) Immune synapse formation. The increase capture of MTs plus ends by TCR clusters would promote the arrival of TCRζ- and LAT-carrying vesicles leading to increase TCR and LAT clustering and encountering at the synapse. Alternatively, EB1 interaction with TCR could also be directly involved in TCRζ vesicle transport to the synapse. In turn, increase TCR clustering would promote additional MT and capture, building an amplification loop for MT dynamics and vesicle transport. (C) Established immunological synapse. A structured MT network would facilitate the continuous arrival of TCRζ- and LAT-carrying vesicles through the MT plus ends at the immunological synapse periphery. Then the centripetal movement of TCR signalling complexes towards the MT minus end at the MTOC close to the synapse centre would bring signalling complexes to signal extinction sites (i.e., endosomes). The right panel in C represents a xy section of the immunological synapse, as it is observed on stimulatory cover slips.     

Identification of conserved protein complexes based on a model of protein network evolution

MOTIVATION: Data on protein-protein interactions (PPIs) are increasing exponentially. To date, large-scale protein interaction networks are available for human and most model species. The arising challenge is to organize these networks into models of cellular machinery. As in other biological domains, a comparative approach provides a powerful basis for addressing this challenge. RESULTS: We develop a probabilistic model for protein complexes that are conserved across two species. The model describes the evolution of conserved protein complexes from an ancestral species by protein interaction attachment and detachment and gene duplication events. We apply our model to search for conserved protein complexes within the PPI networks of yeast and fly, which are the largest networks in public databases. We detect 150 conserved complexes that match well-known complexes in yeast and are coherent in their functional annotations both in yeast and in fly. In comparison with two previous approaches, our model yields higher specificity and sensitivity levels in protein complex detection. AVAILABILITY: The program is available upon request.     

Thresholds in transient dynamics of signal transduction pathways

Transient dynamics of signal transduction pathways play an important role in many biological processes, including cell differentiation, apoptosis, metabolism and DNA damage response. Recent examples of quantitative methods to characterize transient signals include transient metabolic control coefficients and finite time Lyapunov exponents. In our work we compare these quantitative methods to characterize transient phenomena and specifically discuss their predictive power for three examples. We focus on the identification of thresholds that separate different transient dynamic behaviors. Our investigation leads to the following results: The spectrum of the finite-time Lyapunov exponents unambiguously and reliably identifies putative thresholds in transient dynamics. Metabolic control coefficients do not reliably detect all thresholds and suffer from false positives.     

Alteration of EGFR spatiotemporal dynamics suppresses signal transduction

The epidermal growth factor receptor (EGFR), which regulates cell growth and survival, is integral to colon tumorigenesis. Lipid rafts play a role in regulating EGFR signaling, and docosahexaenoic acid (DHA) is known to perturb membrane domain organization through changes in lipid rafts. Therefore, we investigated the mechanistic link between EGFR function and DHA. Membrane incorporation of DHA into immortalized colonocytes altered the lateral organization of EGFR. DHA additionally increased EGFR phosphorylation but paradoxically suppressed downstream signaling. Assessment of the EGFR-Ras-ERK1/2 signaling cascade identified Ras GTP binding as the locus of the DHA-induced disruption of signal transduction. DHA also antagonized EGFR signaling capacity by increasing receptor internalization and degradation. DHA suppressed cell proliferation in an EGFR-dependent manner, but cell proliferation could be partially rescued by expression of constitutively active Ras. Feeding chronically-inflamed, carcinogen-injected C57BL/6 mice a fish oil containing diet enriched in DHA recapitulated the effects on the EGFR signaling axis observed in cell culture and additionally suppressed tumor formation. We conclude that DHA-induced alteration in both the lateral and subcellular localization of EGFR culminates in the suppression of EGFR downstream signal transduction, which has implications for the molecular basis of colon cancer prevention by DHA.