Dynamic receptor team formation can explain the high signal transduction gain in Escherichia coli

The source of high signal cooperativity in bacterial chemosensory arrays

The Escherichia coli chemosensory system consists of large arrays of transmembrane chemoreceptors associated with a dedicated histidine kinase, CheA, and a linker protein, CheW, that couples CheA activity to receptor control. The kinase activity responses to receptor ligand occupancy changes can be highly cooperative, reflecting allosteric coupling of multiple CheA and receptor molecules. Recent structural and functional studies have led to a working model in which receptor core complexes, the minimal units of signaling, are linked into hexagonal arrays through a unique interface 2 interaction between CheW and the P5 domain of CheA. To test this array model, we constructed and characterized CheA and CheW mutants with amino acid replacements at key interface 2 residues. The mutant proteins proved defective in interface 2-specific in vivo cross-linking assays, and formed signaling complexes that were dispersed around the cell membrane rather than clustered at the cell poles as in wild type chemosensory arrays. Interface 2 mutants down-regulated CheA activity in response to attractant stimuli in vivo, but with much less cooperativity than the wild type. Moreover, mutant cells containing fluorophore-tagged receptors exhibited greater basal anisotropy that changed rapidly in response to attractant stimuli, consistent with facile changes in loosely packed receptors. We conclude that interface 2 lesions disrupt important network connections between core complexes, preventing receptors from operating in large, allosteric teams. This work confirms the critical role of interface 2 in organizing the chemosensory array, in directing the clustered array to the cell poles, and in producing its highly cooperative signaling properties.

Excitation and adaptation in bacteria-a model signal transduction system that controls taxis and spatial pattern formation

The machinery for transduction of chemotactic stimuli in the bacterium E. coli is one of the most completely characterized signal transduction systems, and because of its relative simplicity, quantitative analysis of this system is possible. Here we discuss models which reproduce many of the important behaviors of the system. The important characteristics of the signal transduction system are excitation and adaptation, and the latter implies that the transduction system can function as a "derivative sensor" with respect to the ligand concentration in that the DC component of a signal is ultimately ignored if it is not too large. This temporal sensing mechanism provides the bacterium with a memory of its passage through spatially- or temporally-varying signal fields, and adaptation is essential for successful chemotaxis. We also discuss some of the spatial patterns observed in populations and indicate how cell-level behavior can be embedded in population-level descriptions.

A "trimer of dimers"-based model for the chemotactic signal transduction network in bacterial chemotaxis

The network that controls chemotaxis in Escherichia coli is one of the most completely characterized signal transduction systems to date. Receptor clustering accounts for characteristics such as high sensitivity, precise adaptation over a wide dynamic range of ligand concentrations, and robustness to variations in the amounts of intracellular proteins. To gain insights into the structure-function relationship of receptor clusters and understand the mechanism behind the high-performance signaling, we develop and analyze a model for a single trimer of dimers. This new model extends an earlier model (Spiro et al. in Proc. Natl. Acad. Sci. 94:7263-7268, 1997) to incorporate the recent experimental findings that the core structure of receptor clusters is the trimer of receptor dimers. We show that the model can reproduce most of the experimentally-observed behaviors, including excitation, adaptation, high sensitivity, and robustness to parameter variations. In addition, the model makes a number of new predictions as to how the adaptation time varies with the expression level of various proteins involved in signal transduction. Our results provide a more mechanistically-based description of the structure-function relationship for the signaling system, and show the key role of the interaction among dimer members of the trimer in the chemotactic response of cells.

Flower development as an interplay between dynamical physical fields and genetic networks

In this paper we propose a model to describe the mechanisms by which undifferentiated cells attain gene configurations underlying cell fate determination during morphogenesis. Despite the complicated mechanisms that surely intervene in this process, it is clear that the fundamental fact is that cells obtain spatial and temporal information that bias their destiny. Our main hypothesis assumes that there is at least one macroscopic field that breaks the symmetry of space at a given time. This field provides the information required for the process of cell differentiation to occur by being dynamically coupled to a signal transduction mechanism that, in turn, acts directly upon the gene regulatory network (GRN) underlying cell-fate decisions within cells. We illustrate and test our proposal with a GRN model grounded on experimental data for cell fate specification during organ formation in early Arabidopsis thaliana flower development. We show that our model is able to recover the multigene configurations characteristic of sepal, petal, stamen and carpel primordial cells arranged in concentric rings, in a similar pattern to that observed during actual floral organ determination. Such pattern is robust to alterations of the model parameters and simulated failures predict altered spatio-temporal patterns that mimic those described for several mutants. Furthermore, simulated alterations in the physical fields predict a pattern equivalent to that found in Lacandonia schismatica, the only flowering species with central stamens surrounded by carpels.

An agent-based model of signal transduction in bacterial chemotaxis

We report the application of agent-based modeling to examine the signal transduction network and receptor arrays for chemotaxis in Escherichia coli, which are responsible for regulating swimming behavior in response to environmental stimuli. Agent-based modeling is a stochastic and bottom-up approach, where individual components of the modeled system are explicitly represented, and bulk properties emerge from their movement and interactions. We present the Chemoscape model: a collection of agents representing both fixed membrane-embedded and mobile cytoplasmic proteins, each governed by a set of rules representing knowledge or hypotheses about their function. When the agents were placed in a simulated cellular space and then allowed to move and interact stochastically, the model exhibited many properties similar to the biological system including adaptation, high signal gain, and wide dynamic range. We found the agent based modeling approach to be both powerful and intuitive for testing hypotheses about biological properties such as self-assembly, the non-linear dynamics that occur through cooperative protein interactions, and non-uniform distributions of proteins in the cell. We applied the model to explore the role of receptor type, geometry and cooperativity in the signal gain and dynamic range of the chemotactic response to environmental stimuli. The model provided substantial qualitative evidence that the dynamic range of chemotactic response can be traced to both the heterogeneity of receptor types present, and the modulation of their cooperativity by their methylation state.

Spatiotemporal modelling of CheY complexes in Escherichia coli chemotaxis

The chemotaxis pathway of Escherichia coli is one of the best studied and modelled biological signalling pathways. Here we extend existing modelling approaches by explicitly including a description of the formation and subcellular localization of intermediary complexes in the phosphotransfer pathway. The inclusion of these complexes shows that only about 60% of the total output response regulator (CheY) is uncomplexed at any moment and hence free to interact with its target, the flagellar motor. A clear strength of this model is its ability to predict the experimentally observable subcellular localization of CheY throughout a chemotactic response. We have found good agreement between the model output and experimentally determined CheY localization patterns.

In vivo measurement by FRET of pathway activity in bacterial chemotaxis

The two-component pathway in Escherichia coli chemotaxis has become a paradigm for bacterial signal processing. Genetics and biochemistry of the pathway as well as physiological responses have been studied in detail. Despite its relative simplicity, the chemotaxis pathway is renowned for its ability to amplify and integrate weak signals and for its robustness against various kinds of perturbations. All this information inspired multiple attempts at mathematical analysis and computer modeling, but a quantitative understanding of the pathway was hampered by our inability to follow the signal processing in vivo. To address this problem, we developed assays based on fluorescence resonance energy transfer (FRET) and bioluminescence resonance energy transfer (BRET) that enabled us to monitor activity-dependent protein interactions in real time directly in living cells. Here, we describe quantitative applications of these assays in cell populations and on a single-cell level to study the interaction of the phosphorylated response regulator CheY with its phosphatase CheZ. Since this interaction defines the rate of CheY dephosphorylation, which at steady state equals the rate of CheY phosphorylation, it can be used to characterize intracellular kinase activity and thus to analyze properties of the chemotaxis signaling network.

Physical responses of bacterial chemoreceptors

Chemoreceptors of the bacterium Escherichia coli are thought to form trimers of homodimers that undergo conformational changes upon ligand binding and thereby signal a cytoplasmic kinase. We monitored the physical responses of trimers in living cells lacking other chemotaxis proteins by fluorescently tagging receptors and measuring changes in fluorescence anisotropy. These changes were traced to changes in energy transfer between fluorophores on different dimers of a trimer: attractants move these fluorophores farther apart, and repellents move them closer together. These measurements allowed us to define the responses of bare receptor oligomers to ligand binding and compare them to the corresponding response in kinase activity. Receptor responses could be fit by a simple "two-state" model in which receptor dimers are in either active or inactive conformations, from which energy bias and dissociation constants could be estimated. Comparison with responses in kinase-activity indicated that higher-order interactions are dominant in receptor clusters.

Receptor-receptor coupling in bacterial chemotaxis: evidence for strongly coupled clusters

Receptor coupling is believed to explain the high sensitivity of the Escherichia coli chemotaxis network to small changes in levels of chemoattractant. We compare in detail the activity response of coupled two-state receptors for different models of receptor coupling: weakly-coupled extended one-dimensional and two-dimensional lattice models and the Monod-Wyman-Changeux model of isolated strongly-coupled clusters. We identify features in recent data that distinguish between the models. Specifically, researchers have measured the receptor activity response to steps of chemoattractant for a variety of engineered E. coli strains using in vivo fluorescence resonance energy transfer. We find that the fluorescence resonance energy transfer results for wild-type and for a low-activity mutant are inconsistent with the lattice models of receptor coupling, but consistent with the Monod-Wyman-Changeux model of receptor coupling, suggesting that receptors form isolated strongly-coupled clusters.

Chemosensing in Escherichia coli: two regimes of two-state receptors

The chemotaxis network in Escherichia coli is remarkable for its sensitivity to small relative changes in the concentrations of multiple chemical signals. We present a model for signal integration by mixed clusters of interacting two-state chemoreceptors. Our model results compare favorably to the results obtained by Sourjik and Berg with in vivo fluorescence resonance energy transfer. Importantly, we identify two distinct regimes of behavior, depending on the relative energies of the two states of the receptors. In regime I, coupling of receptors leads to high sensitivity, while in regime II, coupling of receptors leads to high cooperativity, i.e., high Hill coefficient. For homogeneous receptors, we predict an observable transition between regime I and regime II with increasing receptor methylation or amidation.

Cooperative signaling among bacterial chemoreceptors

Four chemoreceptors in Escherichia coli mediate responses to chemicals in the environment. The receptors self-associate and localize to the cell poles. This aggregation implies that interactions among receptors are important parameters of signal processing during chemotaxis. We examined this phenomenon using a receptor-coupled in vitro assay of CheA kinase activity. The ability of homogeneous populations of the serine receptor Tsr and the aspartate receptor Tar to stimulate CheA was directly proportional to the ratio of the receptor to total protein in cell membranes up to a fraction of 50%. Membranes containing mixed populations of Tar and Tsr supported an up to 4-fold greater stimulation of CheA than expected on the basis of the contributions of the individual receptors. Peak activity was seen at a Tar:Tsr ratio of 1:4. This synergy was observed only when the two proteins were expressed simultaneously, suggesting that, under our conditions, the fundamental "cooperative receptor unit" is relatively static, even in the absence of CheA and CheW. Finally, we observed that inhibition of receptor-stimulated CheA activity by serine or aspartate required significantly higher concentrations of ligand for membranes containing mixed Tsr and Tar populations than for membranes containing only Tsr (up to 10(2)-fold more serine) or Tar (up to 10(4)-fold more aspartate). Together with recent analyses of the interactions of Tsr and Tar in vivo, our results reveal the emergent properties of mixed receptor populations and emphasize their importance in the integrated signal processing that underlies bacterial chemotaxis.

Large increases in attractant concentration disrupt the polar localization of bacterial chemoreceptors

In bacterial chemotaxis, the chemoreceptors [methyl-accepting chemotaxis proteins (MCPs)] transduce chemotactic signals through the two-component histidine kinase CheA. At low but not high attractant concentrations, chemotactic signals must be amplified. The MCPs are organized into a polar lattice, and this organization has been proposed to be critical for signal amplification. Although evidence in support of this model has emerged, an understanding of how signals are amplified and modulated is lacking. We probed the role of MCP localization under conditions wherein signal amplification must be inhibited. We tested whether a large increase in attractant concentration (a change that should alter receptor occupancy from c. 0% to > 95%) would elicit changes in the chemoreceptor localization. We treated Escherichia coli or Bacillus subtilis with a high level of attractant, exposed cells to the cross-linking agent paraformaldehyde and visualized chemoreceptor location with an anti-MCP antibody. A marked increase in the percentage of cells displaying a diffuse staining pattern was obtained. In contrast, no increase in diffuse MCP staining is observed when cells are treated with a repellent or a low concentration of attractant. For B. subtilis mutants that do not undergo chemotaxis, the addition of a high concentration of attractant has no effect on MCP localization. Our data suggest that interactions between chemoreceptors are decreased when signal amplification is unnecessary.

Collaborative signaling by bacterial chemoreceptors

Motile bacteria seek optimal living habitats by following gradients of attractant and repellent chemicals in their environment. The signaling machinery for these chemotactic behaviors, although assembled from just a few protein components, has extraordinary information-processing capabilities. Escherichia coli, the best-studied model, employs a networked cluster of transmembrane receptors to detect minute chemical stimuli, to integrate multiple and conflicting inputs, and to generate an amplified output signal that controls the cell's flagellar motors. Signal gain arises through cooperative action of chemoreceptors of different types. The signaling-teams within a receptor cluster may be built from trimers of receptor dimers that communicate through shared connections to their partner signaling proteins.

An allosteric model for transmembrane signaling in bacterial chemotaxis

Bacteria are able to sense chemical gradients over a wide range of concentrations. However, calculations based on the known number of receptors do not predict such a range unless receptors interact with one another in a cooperative manner. A number of recent experiments support the notion that this remarkable sensitivity in chemotaxis is mediated by localized interactions or crosstalk between neighboring receptors. A number of simple, elegant models have proposed mechanisms for signal integration within receptor clusters. What is a lacking is a model, based on known molecular mechanisms and our accumulated knowledge of chemotaxis, that integrates data from multiple, heterogeneous sources. To address this question, we propose an allosteric mechanism for transmembrane signaling in bacterial chemotaxis based on the "trimer of dimers" model, where three receptor dimers form a stable complex with CheW and CheA. The mechanism is used to integrate a diverse set of experimental data in a consistent framework. The main predictions are: (1) trimers of receptor dimers form the building blocks for the signaling complexes; (2) receptor methylation increases the stability of the active state and retards the inhibition arising from ligand-bound receptors within the signaling complex; (3) trimer of dimer receptor complexes aggregate into clusters through their mutual interactions with CheA and CheW; (4) cooperativity arises from neighboring interaction within these clusters; and (5) cluster size is determined by the concentration of receptors, CheA, and CheW. The model is able to explain a number of seemingly contradictory experiments in a consistent manner and, in the process, explain how bacteria are able to sense chemical gradients over a wide range of concentrations by demonstrating how signals are integrated within the signaling complex.

Effect of chemoreceptor modification on assembly and activity of the receptor-kinase complex in Escherichia coli

Bacterial chemoreceptors are embedded in the inner cell membrane in tight clusters. We show that changes in receptor methylation that generate large changes in kinase activity have relatively little effect on cluster morphology. Thus, changes in receptor activity do not appear to be mediated by changes in receptor-kinase assembly.