Cellular stoichiometry of the components of the chemotaxis signaling complex

Cellular stoichiometry of the chemotaxis proteins in Bacillus subtilis

The chemoreceptor-CheA kinase-CheW coupling protein complex, with ancillary associated proteins, is at the heart of chemotactic signal transduction in bacteria. The goal of this work was to determine the cellular stoichiometry of the chemotaxis signaling proteins in Bacillus subtilis. Quantitative immunoblotting was used to determine the total number of chemotaxis proteins in a single cell of B. subtilis. Significantly higher levels of chemoreceptors and much lower levels of CheA kinase were measured in B. subtilis than in Escherichia coli. The resulting cellular ratio of chemoreceptor dimers per CheA dimer in B. subtilis is roughly 23.0 ± 4.5 compared to 3.4 ± 0.8 receptor dimers per CheA dimer observed in E. coli, but the ratios of the coupling protein CheW to the CheA dimer are nearly identical in the two organisms. The ratios of CheB to CheR in B. subtilis are also very similar, although the overall levels of modification enzymes are higher. When the potential binding partners of CheD are deleted, the levels of CheD drop significantly. This finding suggests that B. subtilis selectively degrades excess chemotaxis proteins to maintain optimum ratios. Finally, the two cytoplasmic receptors were observed to localize among the other receptors at the cell poles and appear to participate in the chemoreceptor complex. These results suggest that there are many novel features of B. subtilis chemotaxis compared with the mechanism in E. coli, but they are built on a common core.

Lateral density of receptor arrays in the membrane plane influences sensitivity of the E. coli chemotaxis response

In chemotactic bacteria, transmembrane chemoreceptors, CheA and CheW form the core signalling complex of the chemotaxis sensory apparatus. These complexes are organized in extended arrays in the cytoplasmic membrane that allow bacteria to respond to changes in concentration of extracellular ligands via a cooperative, allosteric response that leads to substantial amplification of the signal induced by ligand binding. Here, we have combined cryo-electron tomographic studies of the 3D spatial architecture of chemoreceptor arrays in intact E. coli cells with computational modelling to develop a predictive model for the cooperativity and sensitivity of the chemotaxis response. The predictions were tested experimentally using fluorescence resonance energy transfer (FRET) microscopy. Our results demonstrate that changes in lateral packing densities of the partially ordered, spatially extended chemoreceptor arrays can modulate the bacterial chemotaxis response, and that information about the molecular organization of the arrays derived by cryo-electron tomography of intact cells can be translated into testable, predictive computational models of the chemotaxis response.

Optimal receptor-cluster size determined by intrinsic and extrinsic noise

Biological cells sense external chemical stimuli in their environment using cell-surface receptors. To increase the sensitivity of sensing, receptors often cluster. This process occurs most noticeably in bacterial chemotaxis, a paradigm for sensing and signaling in general. While amplification of weak stimuli is useful in the absence of noise, its usefulness is less clear in the presence of extrinsic input noise and intrinsic signaling noise. Here, exemplified in a bacterial chemotaxis system, we combine the allosteric Monod-Wyman-Changeux model for signal amplification by receptor complexes with calculations of noise to study their interconnectedness. Importantly, we calculate the signal-to-noise ratio, describing the balance of beneficial and detrimental effects of clustering for the cell. Interestingly, we find that there is no advantage for the cell to build receptor complexes for noisy input stimuli in the absence of intrinsic signaling noise. However, with intrinsic noise, an optimal complex size arises in line with estimates of the size of chemoreceptor complexes in bacteria and protein aggregates in lipid rafts of eukaryotic cells.

Bacterial sensor kinases: diversity in the recognition of environmental signals

Bacteria sense and respond to a wide range of physical and chemical signals. Central to sensing and responding to these signals are two-component systems, which have a sensor histidine kinase (SK) and a response regulator (RR) as basic components. Here we review the different molecular mechanisms by which these signals are integrated and modulate the phosphorylation state of SKs. Apart from the basic mechanism, which consists of signal recognition by the SK that leads to an alteration of its autokinase activity and subsequently a change in the RR phosphorylation state, a variety of alternative modes have evolved. The biochemical data available on SKs, particularly their molecular interactions with signals, nucleotides, and their cognate RRs, are also reviewed.

PAS/poly-HAMP signalling in Aer-2, a soluble haem-based sensor

Poly-HAMP domains are widespread in bacterial chemoreceptors, but previous studies have focused on receptors with single HAMP domains. The Pseudomonas aeruginosa chemoreceptor, Aer-2, has an unusual domain architecture consisting of a PAS-sensing domain sandwiched between three N-terminal and two C-terminal HAMP domains, followed by a conserved kinase control module. The structure of the N-terminal HAMP domains was recently solved, making Aer-2 the first protein with resolved poly-HAMP structure. The role of Aer-2 in P. aeruginosa is unclear, but here we show that Aer-2 can interact with the chemotaxis system of Escherichia coli to mediate repellent responses to oxygen, carbon monoxide and nitric oxide. Using this model system to investigate signalling and poly-HAMP function, we determined that the Aer-2 PAS domain binds penta-co-ordinated b-type haem and that reversible signalling requires four of the five HAMP domains. Deleting HAMP 2 and/or 3 resulted in a kinase-off phenotype, whereas deleting HAMP 4 and/or 5 resulted in a kinase-on phenotype. Overall, these data support a model in which ligand-bound Aer-2 PAS and HAMP 2 and 3 act together to relieve inhibition of the kinase control module by HAMP 4 and 5, resulting in the kinase-on state of the Aer-2 receptor.

The photosensor protein Ppr of Rhodocista centenaria is linked to the chemotaxis signalling pathway

Background

Rhodocista centenaria is a phototrophic α-proteobacterium exhibiting a phototactic behaviour visible as colony movement on agar plates directed to red light. As many phototrophic purple bacteria R. centenaria possesses a soluble photoactive yellow protein (Pyp). It exists as a long fusion protein, designated Ppr, consisting of three domains, the Pyp domain, a putative bilin binding domain (Bbd) and a histidine kinase domain (Pph). The Ppr protein is involved in the regulation of polyketide synthesis but it is still unclear, how this is connected to phototaxis and chemotaxis.

Results

To elucidate the possible role of Ppr and Pph in the chemotactic network we studied the interaction with chemotactic proteins in vitro as well as in vivo. Matrix-assisted coelution experiments were performed to study the possible communication of the different putative binding partners. The kinase domain of the Ppr protein was found to interact with the chemotactic linker protein CheW. The formation of this complex was clearly ATP-dependent. Further results indicated that the Pph histidine kinase domain and CheW may form a complex with the chemotactic kinase CheAY suggesting a role of Ppr in the chemotaxis signalling pathway. In addition, when Ppr or Pph were expressed in Escherichia coli, the chemotactic response of the cells was dramatically affected.

Conclusions

The Ppr protein of Rhodocista centenaria directly interacts with the chemotactic protein CheW. This suggests a role of the Ppr protein in the regulation of the chemotactic response in addition to its role in chalcone synthesis.

Fine-tuning of chemotactic response in E. coli determined by high-throughput capillary assay

In E. coli, chemotactic behavior exhibits perfect adaptation that is robust to changes in the intracellular concentration of the chemotactic proteins, such as CheR and CheB. However, the robustness of the perfect adaptation does not explicitly imply a robust chemotactic response. Previous studies on the robustness of the chemotactic response relied on swarming assays, which can be confounded by processes besides chemotaxis, such as cellular growth and depletion of nutrients. Here, using a high-throughput capillary assay that eliminates the effects of growth, we experimentally studied how the chemotactic response depends on the relative concentration of the chemotactic proteins. We simultaneously measured both the chemotactic response of E. coli cells to L: -aspartate and the concentrations of YFP-CheR and CheB-CFP fusion proteins. We found that the chemotactic response is fine-tuned to a specific ratio of [CheR]/[CheB] with a maximum response comparable to the chemotactic response of wild-type behavior. In contrast to adaptation in chemotaxis, that is robust and exact, capillary assays revealed that the chemotactic response in swimming bacteria is fined-tuned to wild-type level of the [CheR]/[CheB] ratio.

Chemoreceptors in signalling complexes: shifted conformation and asymmetric coupling

Bacterial chemotaxis is mediated by signalling complexes of chemoreceptors, histidine kinase CheA and coupling protein CheW. Interactions in complexes profoundly affect the kinase. We investigated effects of these interactions on chemoreceptors by comparing receptors alone and in complexes. Assays of initial rates of methylation indicated that signalling complexes shifted receptor conformation towards the methylation-on, higher-ligand-affinity, kinase-off state, tuning receptors for greater sensitivity. In contrast, transmembrane and conformational signalling within chemoreceptors was essentially unaltered, consistent with other evidence identifying receptor dimers as the fundamental units of such signalling. In signalling complexes, coupling of ligand binding to kinase activity is cooperative and the dynamic range of kinase control expanded > 100-fold by receptor adaptational modification. We observed no cooperativity in influence of ligand on receptor conformation, only on kinase activity. However, receptor modification generated increased dynamic range in a stepwise fashion, partly in coupling ligand to receptor conformation and partly in coupling receptor conformation to kinase activity. Thus, receptors and kinase were not equivalently affected by interactions in signalling complexes or by ligand binding and adaptational modification, indicating asymmetrical coupling between them. This has implications for mechanisms of precise adaptation. Coupling might vary, providing a previously unappreciated locus for sensory control.

Spatial organization of transmembrane receptor signalling

The spatial organization of transmembrane receptors is a critical step in signal transduction and receptor trafficking in cells. Transmembrane receptors engage in lateral homotypic and heterotypic cis-interactions as well as intercellular trans-interactions that result in the formation of signalling foci for the initiation of different signalling networks. Several aspects of ligand-induced receptor clustering and association with signalling proteins are also influenced by the lipid composition of membranes. Thus, lipid microdomains have a function in tuning the activity of many transmembrane receptors by positively or negatively affecting receptor clustering and signal transduction. We review the current knowledge about the functions of clustering of transmembrane receptors and lipid-protein interactions important for the spatial organization of signalling at the membrane.

Spatial organization in bacterial chemotaxis

Spatial organization of signalling is not an exclusive property of eukaryotic cells. Despite the fact that bacterial signalling pathways are generally simpler than those in eukaryotes, there are several well-documented examples of higher-order intracellular signalling structures in bacteria. One of the most prominent and best-characterized structures is formed by proteins that control bacterial chemotaxis. Signals in chemotaxis are processed by ordered arrays, or clusters, of receptors and associated proteins, which amplify and integrate chemotactic stimuli in a highly cooperative manner. Receptor clusters further serve to scaffold protein interactions, enhancing the efficiency and specificity of the pathway reactions and preventing the formation of signalling gradients through the cell body. Moreover, clustering can also ensure spatial separation of multiple chemotaxis systems in one bacterium. Assembly of receptor clusters appears to be a stochastic process, but bacteria evolved mechanisms to ensure optimal cluster distribution along the cell body for partitioning to daughter cells at division.

Mutational analysis of the transmembrane helix 2-HAMP domain connection in the Escherichia coli aspartate chemoreceptor tar

Transmembrane helix 2 (TM2) of the Tar chemoreceptor undergoes an inward piston-like displacement of 1 to 3 Å upon binding aspartate. This signal is transmitted to the kinase-control module via the HAMP domain. Within Tar, the HAMP domain forms a parallel four-helix bundle consisting of a dimer of two amphipathic helices connected by a flexible linker. In the nuclear magnetic resonance structure of an archaeal HAMP domain, residues corresponding to the MLLT sequence between Arg-214 at the end of TM2 and Pro-219 of Tar are an N-terminal helical extension of AS1. We modified this region to test whether it behaves as a continuous helical connection between TM2 and HAMP. First, one to four Gly residues were inserted between Thr-218 and Pro-219. Second, the MLLT sequence was replaced with one to nine Gly residues. Third, the sequence was shortened or extended with residues compatible with helix formation. Cells expressing receptors in which the MLLT sequence was shortened to MLL or in which the MLLT sequence was replaced by four Gly residues performed good aspartate chemotaxis. Other mutant receptors supported diminished aspartate taxis. Most mutant receptors had biased signal outputs and/or abnormal patterns of adaptive methylation. We interpret these results to indicate that a strong, permanent helical connection between TM2 and the HAMP domain is not necessary for normal transmembrane signaling.

Differences in signalling by directly and indirectly binding ligands in bacterial chemotaxis

In chemotaxis of Escherichia coli and other bacteria, extracellular stimuli are perceived by transmembrane receptors that bind their ligands either directly, or indirectly through periplasmic-binding proteins (BPs). As BPs are also involved in ligand uptake, they provide a link between chemotaxis and nutrient utilization by cells. However, signalling by indirectly binding ligands remains much less understood than signalling by directly binding ligands. Here, we compared intracellular responses mediated by both types of ligands and developed a new mathematical model for signalling by indirectly binding ligands. We show that indirect binding allows cells to better control sensitivity to specific ligands in response to their nutrient environment and to coordinate chemotaxis with ligand transport, but at the cost of the dynamic range being much narrower than for directly binding ligands. We further demonstrate that signal integration by the chemosensory complexes does not depend on the type of ligand. Overall, our data suggest that the distinction between signalling by directly and indirectly binding ligands is more physiologically important than the traditional distinction between high- and low-abundance receptors.

Structure of the ternary complex formed by a chemotaxis receptor signaling domain, the CheA histidine kinase, and the coupling protein CheW as determined by pulsed dipolar ESR spectroscopy

The signaling apparatus that controls bacterial chemotaxis is composed of a core complex containing chemoreceptors, the histidine autokinase CheA, and the coupling protein CheW. Site-specific spin labeling and pulsed dipolar ESR spectroscopy (PDS) have been applied to investigate the structure of a soluble ternary complex formed by Thermotoga maritima CheA (TmCheA), CheW, and receptor signaling domains. Thirty-five symmetric spin-label sites (SLSs) were engineered into the five domains of the CheA dimer and CheW to provide distance restraints within the CheA:CheW complex in the absence and presence of a soluble receptor that inhibits kinase activity (Tm14). Additional PDS restraints among spin-labeled CheA, CheW, and an engineered single-chain receptor labeled at six different sites allow docking of the receptor structure relative to the CheA:CheW complex. Disulfide cross-linking between selectively incorporated Cys residues finds two pairs of positions that provide further constraints within the ternary complex: one involving Tm14 and CheW and another involving Tm14 and CheA. The derived structure of the ternary complex indicates a primary site of interaction between CheW and Tm14 that agrees well with previous biochemical and genetic data for transmembrane chemoreceptors. The PDS distance distributions are most consistent with only one CheW directly engaging one dimeric Tm14. The CheA dimerization domain (P3) aligns roughly antiparallel to the receptor-conserved signaling tip but does not interact strongly with it. The angle of the receptor axis with respect to P3 and the CheW-binding P5 domains is bound by two limits differing by approximately 20 degrees . In one limit, Tm14 aligns roughly along P3 and may interact to some extent with the hinge region near the P3 hairpin loop. In the other limit, Tm14 tilts to interact with the P5 domain of the opposite subunit in an interface that mimics that observed with the P5 homologue CheW. The time domain ESR data can be simulated from the model only if orientational variability is introduced for the P5 and, especially, P3 domains. The Tm14 tip also binds beside one of the CheA kinase domains (P4); however, in both bound and unbound states, P4 samples a broad range of distributions that are only minimally affected by Tm14 binding. The CheA P1 domains that contain the substrate histidine are also broadly distributed in space under all conditions. In the context of the hexagonal lattice formed by trimeric transmembrane chemoreceptors, the PDS structure is best accommodated with the P3 domain in the center of a honeycomb edge.

Chemotactic response and adaptation dynamics in Escherichia coli

Adaptation of the chemotaxis sensory pathway of the bacterium Escherichia coli is integral for detecting chemicals over a wide range of background concentrations, ultimately allowing cells to swim towards sources of attractant and away from repellents. Its biochemical mechanism based on methylation and demethylation of chemoreceptors has long been known. Despite the importance of adaptation for cell memory and behavior, the dynamics of adaptation are difficult to reconcile with current models of precise adaptation. Here, we follow time courses of signaling in response to concentration step changes of attractant using in vivo fluorescence resonance energy transfer measurements. Specifically, we use a condensed representation of adaptation time courses for efficient evaluation of different adaptation models. To quantitatively explain the data, we finally develop a dynamic model for signaling and adaptation based on the attractant flow in the experiment, signaling by cooperative receptor complexes, and multiple layers of feedback regulation for adaptation. We experimentally confirm the predicted effects of changing the enzyme-expression level and bypassing the negative feedback for demethylation. Our data analysis suggests significant imprecision in adaptation for large additions. Furthermore, our model predicts highly regulated, ultrafast adaptation in response to removal of attractant, which may be useful for fast reorientation of the cell and noise reduction in adaptation.

Bacterial chemotaxis is a paradigm for sensory systems, and thus has attracted immense interest from biologists and modelers alike. Using this pathway, cells can sense chemical molecules in their environment, and bias their movement towards nutrients and away from toxins. To avoid over- or understimulation of the signaling pathway, receptors adapt to current external conditions by covalent receptor modification, ultimately allowing cells to chemotax over a wide range of background concentrations. While the robustness and precision in adaptation was previously explained, we quantify the dynamics of adaptation, important for cell memory and behavior, as well as noise filtering in the pathway. Specifically, we study the intracellular signaling response and subsequent adaptation to concentration step changes in attractant chemicals. We combine measurements of signaling in living cells with a dynamic model for strongly coupled receptors, even including the effects of concentration flow in the experiment. Using a novel way of summarizing time-dependent data, we derive a new adaptation model, predicting additional layers of feedback regulation. As a consequence, adaptation to sudden exposure of unfavorable conditions is very fast, which may be useful for a quick reorientation and escape of the cell.

Developing stochastic models for spatial inference: bacterial chemotaxis

BACKGROUND

Biological systems are inherently inhomogeneous and spatial effects play a significant role in processes such as pattern formation. At the cellular level proteins are often localised either through static attachment or via a dynamic equilibrium. As well as spatial heterogeneity many cellular processes exhibit stochastic fluctuations and so to make inferences about the location of molecules there is a need for spatial stochastic models. A test case for spatial models has been bacterial chemotaxis which has been studied extensively as a model of signal transduction.

RESULTS

By creating specific models of a cellular system that incorporate the spatial distributions of molecules we have shown how the fit between simulated and experimental data can be used to make inferences about localisation, in the case of bacterial chemotaxis. This method allows the robust comparison of different spatial models through alternative model parameterisations.

CONCLUSIONS

By using detailed statistical analysis we can reliably infer the parameters for the spatial models, and also to evaluate alternative models. The statistical methods employed in this case are particularly powerful as they reduce the need for a large number of simulation replicates. The technique is also particularly useful when only limited molecular level data is available or where molecular data is not quantitative.

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.

Detailed simulations of cell biology with Smoldyn 2.1

Most cellular processes depend on intracellular locations and random collisions of individual protein molecules. To model these processes, we developed algorithms to simulate the diffusion, membrane interactions, and reactions of individual molecules, and implemented these in the Smoldyn program. Compared to the popular MCell and ChemCell simulators, we found that Smoldyn was in many cases more accurate, more computationally efficient, and easier to use. Using Smoldyn, we modeled pheromone response system signaling among yeast cells of opposite mating type. This model showed that secreted Bar1 protease might help a cell identify the fittest mating partner by sharpening the pheromone concentration gradient. This model involved about 200,000 protein molecules, about 7000 cubic microns of volume, and about 75 minutes of simulated time; it took about 10 hours to run. Over the next several years, as faster computers become available, Smoldyn will allow researchers to model and explore systems the size of entire bacterial and smaller eukaryotic cells.

Bacterial chemoreceptors: providing enhanced features to two-component signaling

Bacteria perform chemotaxis utilizing core two-component signaling systems to which have been added enhanced features of signal amplification, sensory adaptation, molecular memory and high sensitivity over a wide dynamic range. Chemoreceptors are central to the enhancements. These transmembrane homodimers associate in trimers and in clusters of signaling complexes containing from a few to thousands of receptors. Receptor homodimers couple ligand occupancy and adaptational modification to transmembrane signaling. Trimers activate and control the histidine kinase. Clusters enable signal amplification, high sensitivity and adaptational assistance. Homodimer signaling initiates with helical piston sliding that is converted to modulation of competing packing modes of adjacent segments of an extended helical coiled coil. In trimers, signaling and coupling may involve switching between compact and expanded forms.

The chemoreceptor dimer is the unit of conformational coupling and transmembrane signaling

Transmembrane chemoreceptors are central components in bacterial chemotaxis. Receptors couple ligand binding and adaptational modification to receptor conformation in processes that create transmembrane signaling. Homodimers, the fundamental receptor structural units, associate in trimers and localize in patches of thousands. To what degree do conformational coupling and transmembrane signaling require higher-order interactions among dimers? To what degree are they altered by such interactions? To what degree are they inherent features of homodimers? We addressed these questions using nanodiscs to create membrane environments in which receptor dimers had few or no potential interaction partners. Receptors with many, few, or no interaction partners were tested for conformational changes and transmembrane signaling in response to ligand occupancy and adaptational modification. Conformation was assayed by measuring initial rates of receptor methylation, a parameter independent of receptor-receptor interactions. Coupling of ligand occupancy and adaptational modification to receptor conformation and thus to transmembrane signaling occurred with essentially the same sensitivity and magnitude in isolated dimers as for dimers with many neighbors. Thus, we conclude that the chemoreceptor dimer is the fundamental unit of conformational coupling and transmembrane signaling. This implies that in signaling complexes, coupling and transmembrane signaling occur through individual dimers and that changes between dimers in a receptor trimer or among trimer-based signaling complexes are subsequent steps in signaling.

Molecular modeling of flexible arm-mediated interactions between bacterial chemoreceptors and their modification enzyme

Sensory adaptation in bacterial chemotaxis is mediated by methylation and demethylation of specific glutamyl residues in the cytoplasmic domain of chemoreceptors. Methylation is catalyzed by methyltransferase CheR. In E. coli and related organisms, methylation sufficiently rapid to be physiologically effective requires a carboxyl terminal pentapeptide sequence on the receptor being modified or, via adaptational assistance, on a neighboring homodimer in a receptor cluster. Pentapeptide-enhanced methylation is thought to be mediated by a approximately 30 residue, potentially disordered sequence that serves as a flexible arm connecting the receptor body and pentapeptide-bound methyltransferase, thus allowing diffusionally restricted enzyme to reach methyl-accepting sites. However, it was not known how many or which sites on the same or neighboring receptors were accessible to the tethered enzyme. We investigated using molecular modeling and found that, in a hexagonal array of trimers of receptor dimers, CheR tethered to a dimer of chemoreceptor Tar by its native 30-residue flexible-arm sequence could reach all methyl-accepting sites on the dimer to which it was tethered plus 48 methyl-accepting sites distributed among nine neighboring dimers, equivalent to the total sites carried by six receptors. This modeling-determined methylation neighborhood of one enzyme-binding dimer and six neighbors corresponds precisely with the experimentally identified neighborhood of seven. Thus, the experimentally observed adaptational assistance can occur by docking of pentapeptide-bound, diffusionally restricted enzyme to methyl-accepting sites on neighboring receptors. Our analysis introduces the notion that physiologically relevant adaptational assistance could occur even if only a subset of sites on a particular receptor are within reach.

Cellular localization of predicted transmembrane and soluble chemoreceptors in Sinorhizobium meliloti

Bacterial chemoreceptors primarily locate in clusters at the cell pole, where they form large sensory complexes which recruit cytoplasmic components of the signaling pathway. The genome of the soil bacterium Sinorhizobium meliloti encodes seven transmembrane and two soluble chemoreceptors. We have investigated the localization of all nine chemoreceptors in vivo using genome-encoded fusions to a variant of the enhanced green fluorescent protein and to monomeric red fluorescent protein. Six of the transmembrane (McpT to McpX and McpZ) and both soluble (McpY and IcpA) receptors localize to the cell pole. Only McpS, encoded from the symbiotic plasmid pSymA, is evenly distributed in the cell. While the synthesis of all polar localized receptors is confined to exponential growth correlating with the motility phase of cells, McpS is only weakly expressed throughout cell culture growth. Therefore, motile S. meliloti cells form one major chemotaxis cluster that harbors all chemoreceptors except for McpS. Colocalization and deletion analysis demonstrated that formation of polar foci by the majority of receptors is dependent on other chemoreceptors and that receptor clusters are stabilized by the presence of the chemotaxis proteins CheA and CheW. The transmembrane McpV and the soluble IcpA localize to the pole independently of CheA and CheW. However, in mutant strains McpV formed delocalized polar caps that spread throughout the cell membrane while IcpA exhibited increased bipolarity. Immunoblotting of fractionated cells revealed that IcpA, which lacks any hydrophobic domains, nevertheless is associated to the cell membrane.

The core signaling proteins of bacterial chemotaxis assemble to form an ultrastable complex

The chemosensory pathway of bacterial chemotaxis forms a polar signaling cluster in which the fundamental signaling units, the ternary complexes, are arrayed in a highly cooperative, repeating lattice. The repeating ternary units are composed of transmembrane receptors, histidine-kinase CheA, and coupling protein CheW, but it is unknown how these three core proteins are interwoven in the assembled ultrasensitive lattice. Here, to further probe the nature of the lattice, we investigate its stability. The findings reveal that once the signaling cluster is assembled, CheA remains associated and active for days in vitro. All three core components are required for this ultrastable CheA binding and for receptor-controlled kinase activity. The stability is disrupted by low ionic strength or high pH, providing strong evidence that electrostatic repulsion between the highly acidic core components can lead to disassembly. We propose that ultrastability arises from the assembled lattice structure that establishes multiple linkages between the core components, thereby conferring thermodynamic or kinetic ultrastability to the bound state. An important, known function of the lattice structure is to facilitate receptor cooperativity, which in turn enhances pathway sensitivity. In the cell, however, the ultrastability of the lattice could lead to uncontrolled growth of the signaling complex until it fills the inner membrane. We hypothesize that such uncontrolled growth is prevented by an unidentified intracellular disassembly system that is lost when complexes are isolated from cells, thereby unmasking the intrinsic complex ultrastability. Possible biological functions of ultrastability are discussed.

Signal amplification in a lattice of coupled protein kinases

The bacterium Escherichia coli detects chemical attractants and repellents by means of a cluster of transmembrane receptors and associated molecules. Experiments have shown that this cluster amplifies the signal about 35-fold and current models attribute this amplification to cooperative interactions between neighbouring receptors. However, when applied to the mixed population of receptors of wild-type E. coli, these models lead to indiscriminate methylation of all receptor types rather than the selective methylation observed experimentally. In this paper, we propose that cooperative interactions occur not between receptors but in the underlying lattice of CheA molecules. In our model, each CheA molecule is stimulated by its neighbours via their flexible P1 domains and modulated by the ligand binding and methylation states of associated receptors. We test this idea with detailed, molecular-based stochastic simulations and show that it gives an accurate reproduction of signalling in this system, including ligand-specific adaptation.

Introducing simulated cellular architecture to the quantitative analysis of fluorescent microscopy

Biological cells are complex and highly dynamic: many macromolecules are organized in loose assemblies, clusters or highly structured complexes, others exist most of the time as freely diffusing monomers. They move between regions and compartments through diffusion and enzyme-mediated transport, within a heavily crowded cytoplasm. To make sense of this complexity, computational models, and, in turn, quantitative in vivo data are needed. An array of fluorescent microscopy methods is available, but due to the inherent noise and complexity inside the cell, they are often hard to interpret. Using the example of fluorescence recovery after photobleaching (FRAP) and the bacterial chemotaxis system, we are here introducing detailed spatial simulations as a new approach in analysing such data.

Self-organization of the Escherichia coli chemotaxis network imaged with super-resolution light microscopy

Photoactivated localization microscopy analysis of chemotaxis receptors in bacteria suggests that the non-random organization of these proteins results from random self-assembly of clusters without direct cytoskeletal involvement or active transport.

The Escherichia coli chemotaxis network is a model system for biological signal processing. In E. coli, transmembrane receptors responsible for signal transduction assemble into large clusters containing several thousand proteins. These sensory clusters have been observed at cell poles and future division sites. Despite extensive study, it remains unclear how chemotaxis clusters form, what controls cluster size and density, and how the cellular location of clusters is robustly maintained in growing and dividing cells. Here, we use photoactivated localization microscopy (PALM) to map the cellular locations of three proteins central to bacterial chemotaxis (the Tar receptor, CheY, and CheW) with a precision of 15 nm. We find that cluster sizes are approximately exponentially distributed, with no characteristic cluster size. One-third of Tar receptors are part of smaller lateral clusters and not of the large polar clusters. Analysis of the relative cellular locations of 1.1 million individual proteins (from 326 cells) suggests that clusters form via stochastic self-assembly. The super-resolution PALM maps of E. coli receptors support the notion that stochastic self-assembly can create and maintain approximately periodic structures in biological membranes, without direct cytoskeletal involvement or active transport.

Cells arrange their components—proteins, lipids, and nucleic acids—in organized and reproducible ways to optimize the activities of these components and, therefore, to improve cell efficiency and survival. Eukaryotic cells have a complex arrangement of subcellular structures such as membrane-bound organelles and cytoskeletal transport systems. However, subcellular organization is also important in prokaryotic cells, including rod-shaped bacteria such as E. coli, most of which lack such well-developed systems of organelles and motor proteins for transporting cellular cargoes. In fact, it has remained somewhat mysterious how bacteria are able to organize and spatially segregate their interiors. The E. coli chemotaxis network, a system important for the bacterial response to environmental cues, is one of the best-understood biological signal transduction pathways and serves as a useful model for studying bacterial spatial organization because its components display a nonrandom, periodic distribution in mature cells. Chemotaxis receptors aggregate and cluster into large sensory complexes that localize to the poles of bacteria. To understand how these clusters form and what controls their size and density, we use ultrahigh-resolution light microscopy, called photoactivated localization microscopy (PALM), to visualize individual chemoreceptors in single E. coli cells. From these high-resolution images, we determined that receptors are not actively distributed or attached to specific locations in cells. Instead, we show that random receptor diffusion and receptor–receptor interactions are sufficient to generate the observed complex, ordered pattern. This simple mechanism, termed stochastic self-assembly, may prove to be widespread in both prokaryotic and eukaryotic cells.

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.

Differential affinity and catalytic activity of CheZ in E. coli chemotaxis

Push–pull networks, in which two antagonistic enzymes control the activity of a messenger protein, are ubiquitous in signal transduction pathways. A classical example is the chemotaxis system of the bacterium Escherichia coli, in which the kinase CheA and the phosphatase CheZ regulate the phosphorylation level of the messenger protein CheY. Recent experiments suggest that both the kinase and the phosphatase are localized at the receptor cluster, and Vaknin and Berg recently demonstrated that the spatial distribution of the phosphatase can markedly affect the dose–response curves. We argue, using mathematical modeling, that the canonical model of the chemotaxis network cannot explain the experimental observations of Vaknin and Berg. We present a new model, in which a small fraction of the phosphatase is localized at the receptor cluster, while the remainder freely diffuses in the cytoplasm; moreover, the phosphatase at the cluster has a higher binding affinity for the messenger protein and a higher catalytic activity than the phosphatase in the cytoplasm. This model is consistent with a large body of experimental data and can explain many of the experimental observations of Vaknin and Berg. More generally, the combination of differential affinity and catalytic activity provides a generic mechanism for amplifying signals that could be exploited in other two-component signaling systems. If this model is correct, then a number of recent modeling studies, which aim to explain the chemotactic gain in terms of the activity of the receptor cluster, should be reconsidered.

In both prokaryotes and eukaryotes, extra- and intracellular signals are often processed by biochemical networks in which two enzymes together control the activity of a messenger protein via opposite modification reactions. A well-known example is the chemotaxis network of Escherichia coli that controls the swimming behavior of the bacterium in response to chemical stimuli. Recent experiments suggest that the two counteracting enzymes in this network are colocalized at the receptor cluster, while experiments by Vaknin and Berg indicate that the spatial distribution of the enzymes by itself can markedly affect the response of the network. We argue using mathematical modeling that the most widely used model of the chemotaxis network is inconsistent with these experimental observations. We then present an alternative model in which part of one enzyme is colocalized with the other enzyme at the receptor cluster, while the remainder freely diffuses in the cytoplasm; moreover, the fraction at the cluster both binds more strongly to the messenger protein and modifies it faster. This model is consistent with a large number of experimental observations and provides a generic mechanism for amplifying signals.

Polar chemoreceptor clustering by coupled trimers of dimers

Receptors of bacterial chemotaxis form clusters at the cell poles, where clusters act as "antennas" to amplify small changes in ligand concentration. It is worthy of note that chemoreceptors cluster at multiple length scales. At the smallest scale, receptors form dimers, which assemble into stable timers of dimers. At a large scale, trimers form large polar clusters composed of thousands of receptors. Although much is known about the signaling properties emerging from receptor clusters, it is unknown how receptors localize at the cell poles and what the determining factors are for cluster size. Here, we present a model of polar receptor clustering based on coupled trimers of dimers, where cluster size is determined as a minimum of the cluster-membrane free energy. This energy has contributions from the cluster-membrane elastic energy, penalizing large clusters due to their high intrinsic curvature, and receptor-receptor coupling that favors large clusters. We find that the reduced cluster-membrane curvature mismatch at the curved cell poles leads to large and robust polar clusters, in line with experimental observation, whereas lateral clusters are efficiently suppressed.

The region preceding the C-terminal NWETF pentapeptide modulates baseline activity and aspartate inhibition of Escherichia coli Tar

The Tar chemoreceptor-CheA-CheW ternary complex of Escherichia coli is a transmembrane allosteric enzyme in which binding of ligands to the periplasmic domain modulates the activity of CheA kinase. Kinase activity is also affected by reversible methylation of four glutamyl residues in the cytoplasmic domain of the receptor. E. coli Tar contains 553 residues. Residues 549-553 comprise the NWETF pentapeptide that binds the CheR methyltransferase and CheB methylesterase. The crystal structure of the similar Tsr chemoreceptor predicts that residues 263-289 and 490-515 of Tar form the most membrane-proximal portion of the extended CD1-CD2 four-helix bundle of the cytoplasmic domain. The last methylation site, Glu-491, is in the C19 heptad, and the N22-19 and C22-19 heptads are present in all classes of bacterial transmembrane chemoreceptors. Residues 516-548 probably serve as a flexible tether for the NWETF pentapeptide. Here, we present a mutational analysis of residues 505-548. The more of this region that is deleted, the less sensitive Tar is to inhibition by aspartate. Tar deleted from residue 505 through the NWETF sequence stimulates CheA in vitro but is not inhibited by aspartate. Thus, interaction of the last two heptads (C21 and C22) of CD2 with the first two heptads (N22 and N21) of CD1 must be important for transmitting an inhibitory signal from the HAMP domain to the four-helix bundle. The R514A, K523A, R529A, R540A, and R542A substitutions, singly or together, increase the level of activation of CheA in vitro, whereas the R505A substitution decreases the level of CheA stimulation by 40% and lowers the aspartate K(i) 7-fold. The R505E substitution completely abolishes stimulation of CheA in vitro. Glu-505 may interact electrostatically with Asp-273 to destabilize the "on" signaling state by loosening the four-helix bundle.

Dependence of bacterial chemotaxis on gradient shape and adaptation rate

Simulation of cellular behavior on multiple scales requires models that are sufficiently detailed to capture central intracellular processes but at the same time enable the simulation of entire cell populations in a computationally cheap way. In this paper we present RapidCell, a hybrid model of chemotactic Escherichia coli that combines the Monod-Wyman-Changeux signal processing by mixed chemoreceptor clusters, the adaptation dynamics described by ordinary differential equations, and a detailed model of cell tumbling. Our model dramatically reduces computational costs and allows the highly efficient simulation of E. coli chemotaxis. We use the model to investigate chemotaxis in different gradients, and suggest a new, constant-activity type of gradient to systematically study chemotactic behavior of virtual bacteria. Using the unique properties of this gradient, we show that optimal chemotaxis is observed in a narrow range of CheA kinase activity, where concentration of the response regulator CheY-P falls into the operating range of flagellar motors. Our simulations also confirm that the CheB phosphorylation feedback improves chemotactic efficiency by shifting the average CheY-P concentration to fit the motor operating range. Our results suggest that in liquid media the variability in adaptation times among cells may be evolutionary favorable to ensure coexistence of subpopulations that will be optimally tactic in different gradients. However, in a porous medium (agar) such variability appears to be less important, because agar structure poses mainly negative selection against subpopulations with low levels of adaptation enzymes. RapidCell is available from the authors upon request.

Modeling the chemotactic response of Escherichia coli to time-varying stimuli

In their natural environment, cells need to extract useful information from complex temporal signals that vary over a wide range of intensities and time scales. Here, we study how such signals are processed by Escherichia coli during chemotaxis by developing a general theoretical model based on receptor adaptation and receptor-receptor cooperativity. Measured responses to various monotonic, oscillatory, and impulsive stimuli are all explained consistently by the underlying adaptation kinetics within this model. For exponential ramp signals, an analytical solution is discovered that reveals a remarkable connection between the dependence of kinase activity on the exponential ramp rate and the receptor methylation rate function. For exponentiated sine-wave signals, spectral analysis shows that the chemotaxis pathway acts as a lowpass filter for the derivative of the signal with the cutoff frequency determined by an intrinsic adaptation time scale. For large step stimuli, we find that the recovery time is determined by the constant maximum methylation rate, which provides a natural explanation for the observed recovery time additivity. Our model provides a quantitative system-level description of the chemotaxis signaling pathway and can be used to predict E. coli chemotaxis responses to arbitrary temporal signals. This model of the receptor system reveals the molecular origin of Weber's law in bacterial chemotaxis. We further identify additional constraints required to account for the related observation that the output of this pathway is constant under exponential ramp stimuli, a feature that we call "logarithmic tracking."

Receptor density balances signal stimulation and attenuation in membrane-assembled complexes of bacterial chemotaxis signaling proteins

All cells possess transmembrane signaling systems that function in the environment of the lipid bilayer. In the Escherichia coli chemotaxis pathway, the binding of attractants to a two-dimensional array of receptors and signaling proteins simultaneously inhibits an associated kinase and stimulates receptor methylation--a slower process that restores kinase activity. These two opposing effects lead to robust adaptation toward stimuli through a physical mechanism that is not understood. Here, we provide evidence of a counterbalancing influence exerted by receptor density on kinase stimulation and receptor methylation. Receptor signaling complexes were reconstituted over a range of defined surface concentrations by using a template-directed assembly method, and the kinase and receptor methylation activities were measured. Kinase activity and methylation rates were both found to vary significantly with surface concentration--yet in opposite ways: samples prepared at high surface densities stimulated kinase activity more effectively than low-density samples, whereas lower surface densities produced greater methylation rates than higher densities. FRET experiments demonstrated that the cooperative change in kinase activity coincided with a change in the arrangement of the membrane-associated receptor domains. The counterbalancing influence of density on receptor methylation and kinase stimulation leads naturally to a model for signal regulation that is compatible with the known logic of the E. coli pathway. Density-dependent mechanisms are likely to be general and may operate when two or more membrane-related processes are influenced differently by the two-dimensional concentration of pathway elements.

Chemoreceptors in Caulobacter crescentus: trimers of receptor dimers in a partially ordered hexagonally packed array

Chemoreceptor arrays are macromolecular complexes that form extended assemblies primarily at the poles of bacterial cells and mediate chemotaxis signal transduction, ultimately controlling cellular motility. We have used cryo-electron tomography to determine the spatial distribution and molecular architecture of signaling molecules that comprise chemoreceptor arrays in wild-type Caulobacter crescentus cells. We demonstrate that chemoreceptors are organized as trimers of receptor dimers, forming partially ordered hexagonally packed arrays of signaling complexes in the cytoplasmic membrane. This novel organization at the threshold between order and disorder suggests how chemoreceptors and associated molecules are arranged in signaling assemblies to respond dynamically in the activation and adaptation steps of bacterial chemotaxis.

Stochastic assembly of chemoreceptor clusters in Escherichia coli

Chemoreceptors and cytoplasmic chemotaxis proteins in Escherichia coli form clusters that play a key role in signal processing. These clusters localize at cell poles and at specific positions along the cell body which correspond to future division sites, but the details of cluster formation and the mechanism of cluster distribution remain unclear. Here, we used fluorescence microscopy to investigate how the numbers and sizes of receptor clusters depend on the expression level of chemotaxis proteins and on the cell length. We show that the average cluster number saturates at high levels of protein expression at approximately 3.7 clusters per cell, well below the number of available positioning sites. Correspondingly, distances between clusters in filamentous cells saturate at an average of 1 mum but, even at saturating expression levels, individual cluster numbers and distances show a broad distribution around the mean. Our data imply a stochastic mode of cluster assembly, where a defined average interval between clusters along the cell body arises from competition between nucleation of new clusters and growth of existing clusters. Upon subsequent anchorage to defined lateral sites, clusters grow with rates that inversely depend on their size, and become polar upon several rounds of cell division.

Protein exchange dynamics at chemoreceptor clusters in Escherichia coli

Signal processing in bacterial chemotaxis relies on large sensory complexes consisting of thousands of protein molecules. These clusters create a scaffold that increases the efficiency of pathway reactions and amplifies and integrates chemotactic signals. The cluster core in Escherichia coli comprises a ternary complex composed of receptors, kinase CheA, and adaptor protein CheW. All other chemotaxis proteins localize to clusters by binding either directly to receptors or to CheA. Here, we used fluorescence recovery after photobleaching (FRAP) to investigate the turnover of chemotaxis proteins at the cluster and their mobility in the cytoplasm. We found that cluster exchange kinetics were protein-specific and took place on several characteristic time scales that correspond to excitation, adaptation, and cell division, respectively. We further applied analytical and numerical data fitting to analyze intracellular protein diffusion and to estimate the rate constants of cluster equilibration in vivo. Our results indicate that the rates of protein turnover at the cluster have evolved to ensure optimal performance of the chemotaxis pathway.

Location and architecture of the Caulobacter crescentus chemoreceptor array

A new method for recording both fluorescence and cryo-EM images of small bacterial cells was developed and used to identify chemoreceptor arrays in cryotomograms of intact Caulobacter crescentus cells. We show that in wild-type cells preserved in a near-native state, the chemoreceptors are hexagonally packed with a lattice spacing of 12 nm, just a few tens of nanometers away from the flagellar motor that they control. The arrays were always found on the convex side of the cell, further demonstrating that Caulobacter cells maintain dorsal/ventral as well as anterior/posterior asymmetry. Placing the known crystal structure of a trimer of receptor dimers at each vertex of the lattice accounts well for the density and agrees with other constraints. Based on this model for the arrangement of receptors, there are between one and two thousand receptors per array.

Model for Protein Concentration Gradients in the Cytoplasm

Intracellular protein concentration gradients are generally thought to be unsustainable at steady-state due to diffusion. Here we show how protein concentration gradients can theoretically be sustained indefinitely through a relatively simple mechanism that couples diffusion to a spatially segregated kinase-phosphatase system. Although it is appreciated that such systems can theoretically give rise to phosphostate gradients, it has been assumed that they do not give rise to gradients in the total protein concentration. Here we show that this assumption does not hold if the two forms of protein have different diffusion coefficients. If, for example, the phosphorylated state binds selectively to a second larger protein or protein complex then a steady state gradient in total protein concentration will be created. We illustrate the principle with an analytical solution to the diffusion-reaction problem and by stochastic individual-based simulations using the Smoldyn program. We argue that protein gradients created in this way need to be considered in experiments using fluorescent probes and could in principle encode spatial information in the cytoplasm.

Relationship between cellular response and behavioral variability in bacterial chemotaxis

Over the last decades, bacterial chemotaxis in Escherichia coli has emerged as a canonical system for the study of signal transduction. A remarkable feature of this system is the coexistence of a robust adaptive behavior observed at the population level with a large fluctuating behavior in single cells [Korobkova E, Emonet T, Vilar JMG, Shimizu TS, Cluzel P (2004) Nature 428:574-578]. Using a unified stochastic model, we demonstrate that this coexistence is not fortuitous but a direct consequence of the architecture of this adaptive system. The methylation and demethylation cycles that regulate the activity of receptor-kinase complexes are ultrasensitive because they operate outside the region of first-order kinetics. As a result, the receptor-kinase that governs cellular behavior exhibits a sigmoidal activation curve. We propose that the steepness of this kinase activation curve simultaneously controls the behavioral variability in nonstimulated individual bacteria and the duration of the adaptive response to small stimuli. We predict that the fluctuating behavior and the chemotactic response of individual cells both peak within the transition region of this sigmoidal curve. Large-scale simulations of digital bacteria suggest that the chemotaxis network is tuned to simultaneously maximize both the random spread of cells in the absence of nutrients and the cellular response to gradients of attractant. This study highlights a fundamental relation from which the behavioral variability of nonstimulated cells is used to infer the timing of the cellular response to small stimuli.

Bacterial chemoreceptors: high-performance signaling in networked arrays

Chemoreceptors are crucial components in the bacterial sensory systems that mediate chemotaxis. Chemotactic responses exhibit exquisite sensitivity, extensive dynamic range and precise adaptation. The mechanisms that mediate these high-performance functions involve not only actions of individual proteins but also interactions among clusters of components, localized in extensive patches of thousands of molecules. Recently, these patches have been imaged in native cells, important features of chemoreceptor structure and on-off switching have been identified, and new insights have been gained into the structural basis and functional consequences of higher order interactions among sensory components. These new data suggest multiple levels of molecular interactions, each of which contribute specific functional features and together create a sophisticated signaling device.

Interaction of CheY with the C-terminal peptide of CheZ

Chemotaxis, a means for motile bacteria to sense the environment and achieve directed swimming, is controlled by flagellar rotation. The primary output of the chemotaxis machinery is the phosphorylated form of the response regulator CheY (P-CheY). The steady-state level of P-CheY dictates the direction of rotation of the flagellar motor. The chemotaxis signal in the form of P-CheY is terminated by the phosphatase CheZ. Efficient dephosphorylation of CheY by CheZ requires two distinct protein-protein interfaces: one involving the strongly conserved C-terminal helix of CheZ (CheZ(C)) tethering the two proteins together and the other constituting an active site for catalytic dephosphorylation. In a previous work (J. Guhaniyogi, V. L. Robinson, and A. M. Stock, J. Mol. Biol. 359:624-645, 2006), we presented high-resolution crystal structures of CheY in complex with the CheZ(C) peptide that revealed alternate binding modes subject to the conformational state of CheY. In this study, we report biochemical and structural data that support the alternate-binding-mode hypothesis and identify key recognition elements in the CheY-CheZ(C) interaction. In addition, we present kinetic studies of the CheZ(C)-associated effect on CheY phosphorylation with its physiologically relevant phosphodonor, the histidine kinase CheA. Our results indicate mechanistic differences in phosphotransfer from the kinase CheA versus that from small-molecule phosphodonors, explaining a modest twofold increase of CheY phosphorylation with the former, observed in this study, relative to a 10-fold increase previously documented with the latter.

Chemotaxis of Escherichia coli to pyrimidines: a new role for the signal transducer tap

Escherichia coli exhibits chemotactic responses to sugars, amino acids, and dipeptides, and the responses are mediated by methyl-accepting chemotaxis proteins (MCPs). Using capillary assays, we demonstrated that Escherichia coli RP437 is attracted to the pyrimidines thymine and uracil and the response was constitutively expressed under all tested growth conditions. All MCP mutants lacking the MCP Tap protein showed no response to pyrimidines, suggesting that Tap, which is known to mediate dipeptide chemotaxis, is required for pyrimidine chemotaxis. In order to confirm the role of Tap in pyrimidine chemotaxis, we constructed chimeric chemoreceptors (Tapsr and Tsrap), in which the periplasmic and cytoplasmic domains of Tap and Tsr were switched. When Tapsr and Tsrap were individually expressed in an E. coli strain lacking all four native MCPs, Tapsr mediated chemotaxis toward pyrimidines and dipeptides, but Tsrap did not complement the chemotaxis defect. The addition of the C-terminal 19 amino acids from Tsr to the C terminus of Tsrap resulted in a functional chemoreceptor that mediated chemotaxis to serine but not pyrimidines or dipeptides. These results indicate that the periplasmic domain of Tap is responsible for detecting pyrimidines and the Tsr signaling domain confers on Tapsr the ability to mediate efficient chemotaxis. A mutant lacking dipeptide binding protein (DBP) was wild type for pyrimidine taxis, indicating that DBP, which is the primary chemoreceptor for dipeptides, is not responsible for detecting pyrimidines. It is not yet known whether Tap detects pyrimidines directly or via an additional chemoreceptor protein.

Chemotaxis in Escherichia coli: a molecular model for robust precise adaptation

The chemotaxis system in the bacterium Escherichia coli is remarkably sensitive to small relative changes in the concentrations of multiple chemical signals over a broad range of ambient concentrations. Interactions among receptors are crucial to this sensitivity as is precise adaptation, the return of chemoreceptor activity to prestimulus levels in a constant chemoeffector environment. Precise adaptation relies on methylation and demethylation of chemoreceptors by the enzymes CheR and CheB, respectively. Experiments indicate that when transiently bound to one receptor, these enzymes act on small assistance neighborhoods (AN) of five to seven receptor homodimers. In this paper, we model a strongly coupled complex of receptors including dynamic CheR and CheB acting on ANs. The model yields sensitive response and precise adaptation over several orders of magnitude of attractant concentrations and accounts for different responses to aspartate and serine. Within the model, we explore how the precision of adaptation is limited by small AN size as well as by CheR and CheB kinetics (including dwell times, saturation, and kinetic differences among modification sites) and how these kinetics contribute to noise in complex activity. The robustness of our dynamic model for precise adaptation is demonstrated by randomly varying biochemical parameters.

Bacteria swim in relatively straight lines and change directions through tumbling. In the process of chemotaxis, a network of receptors and other proteins controls the tumbling frequency to direct an otherwise random walk toward nutrients and away from repellents. Receptor clustering and adaptation to persistent stimuli through covalent modification allow chemotaxis to be sensitive over a large range of ambient concentrations. The individual components of the chemotaxis network are well characterized, and signaling measurements by fluorescence microscopy quantify the network's response, making the system well suited for modeling and analysis. In this paper, we expand upon a previous model based on experiments indicating that the covalent modifications required for adaptation occur through the action of enzymes on groups of neighboring receptors, referred to as assistance neighborhoods. Simulations show that our proposed molecular model of a strongly coupled complex of receptors produces accurate responses to different stimuli and is robust to parameter variation. Within this model, the correct adaptation response is limited by small assistance-neighborhood size as well as enzyme kinetics. We also explore how these kinetics contribute to noise in the chemotactic response.

Subcellular location characteristics of the Pseudomonas aeruginosa GGDEF protein, WspR, indicate that it produces cyclic-di-GMP in response to growth on surfaces

The Pseudomonas aeruginosa Wsp signal transduction system produces cyclic-di-GMP (c-di-GMP), an intracellular messenger that stimulates biofilm formation and suppresses motility. The Wsp system is homologous to chemotaxis systems and includes a membrane-bound receptor protein, WspA, and a response regulator GGDEF protein, WspR, that catalyses c-di-GMP synthesis when phosphorylated. We found that the subcellular distributions of fluorescent protein-tagged WspA and WspR differed markedly from their chemotaxis counterparts. WspA-YFP formed patches in cells whereas WspR-YFP was dispersed when unphosphorylated and formed bright cytoplasmic clusters when phosphorylated. WspR formed clusters in cells of a DeltawspF mutant, a genetic background that causes constitutive phosphorylation of WspR, but was dispersed in cells of a wspA mutant, a genetic background necessary for WspR phosphorylation. In addition, WspR mutated at Asp70, its predicted site of phosphorylation, did not form clusters. C-di-GMP synthesis was not required for cluster formation. WspR-YFP was dispersed in liquid-grown wild-type cells, but formed clusters that sometimes appeared and disappeared over the course of a few minutes in cells grown on an agar surface. Our results suggest that the compartmentalized production of c-di-GMP in response to a stimulus associated with growth on a surface is an important functional characteristic of the Wsp system.

Robust effects of Tsr–CheBp and CheA–CheYp affinity in bacterial chemotaxis

OBJECTIVE

Cell motility and chemotaxis play a role in the virulence of pathogenic bacteria, such as escape from host immune responses. Escherichia coli chemotaxis provides a well-characterized model system for the bacterial chemotaxis network. Two features of E. coli chemotaxis include signal amplification and robustly accurate adaptation. Recent simulation studies with models considering the effects of other receptors have suggested possible mechanisms for signal amplification. Although precise adaptation to aspartate has been explained by conventional kinetic models, the adaptation behavior of models incorporating the effects of other receptors remains unclear.

METHODS

We concentrated on how receptor crosstalk affects minimization of adaptation error and compared models in which the contribution of other receptors varied.

RESULTS

We demonstrated that the model is adaptable to attractant concentrations ranging from 0.1microM to 10mM with a decreased error rate (from 8% to 2%) when the kinetic constant of CheA and phosphorylated CheY dissociation is increased.

CONCLUSION

The results suggest that accurate adaptation is maintained through control of both the interaction of cytoplasmic Che proteins and the activity of the receptor complex.

A native antibody-based mobility-shift technique (NAMOS-assay) to determine the stoichiometry of multiprotein complexes

Characterization of multiprotein complexes (MPCs) is an important step toward an integrative view of protein interaction networks and prerequisite for a molecular understanding of how a certain MPC functions. Here, we present a technique utilizing monoclonal subunit-specific antibodies for an electrophoretic immunoshift assay in Blue Native-gels (NAMOS-assay), which allows the determination of the stoichiometry of MPCs. First, we use the B cell antigen receptor as a model MPC whose stoichiometry is known, confirming the HC(2)LC(2)Igalpha/beta(1) stoichiometry. Second, we demonstrate that the digitonin-extracted T cell antigen receptor (TCR) extracted from T cells has a stoichiometry of alphabetaepsilon(2)gammadeltazeta(2). We then show that the NAMOS-assay does not require purified MPCs, since it can determine the stoichiometry of an MPC in cell lysates. The NAMOS-assay is also compatible with use of epitope tags appended to the protein of interest, as e.g. the widely used HA-tag, and anti-epitope antibodies for the assay. Given its general applicability, this method has a wide potential for MPC research.

Positioning of chemosensory clusters in E. coli and its relation to cell division

Chemotaxis receptors and associated signalling proteins in Escherichia coli form clusters that consist of thousands of molecules and are the largest native protein complexes described to date in bacteria. Clusters are located at the cell poles and laterally along the cell body, and play an important role in signal transduction. Much work has been done to study the structure and function of receptor clusters, but the significance of their positioning and the underlying mechanisms are not understood. Here, we used fluorescence imaging to study cluster distribution and follow cluster dynamics during cell growth. Our data show that lateral clusters localise to specific periodic positions along the cell body, which mark future division sites and are involved in the localisation of the replication machinery. The chemoreceptor cluster positioning is thus intricately related to the overall structure and division of an E. coli cell.

Direct visualization of Escherichia coli chemotaxis receptor arrays using cryo-electron microscopy

Signal transduction in bacterial chemotaxis is initiated by the binding of extracellular ligands to a specialized family of methyl-accepting chemoreceptor proteins. Chemoreceptors cluster at distinct regions of the cell and form stable ternary complexes with the histidine autokinase CheA and the adapter protein CheW. Here we report the direct visualization and spatial organization of chemoreceptor arrays in intact Escherichia coli cells by using cryo-electron tomography and biochemical techniques. In wild-type cells, ternary complexes are arranged as an extended lattice, which may or may not be ordered, with significant variations in the size and specific location among cells in the same population. In the absence of CheA and CheW, chemoreceptors do not form observable clusters and are diffusely localized to the cell pole. At disproportionately high receptor levels, membrane invaginations containing nonfunctional, axially interacting receptor assemblies are formed. However, functional chemoreceptor arrays can be reestablished by increasing cellular levels of CheA and CheW. Our results demonstrate that chemotaxis in E. coli requires the presence of chemoreceptor arrays and that the formation of these arrays requires the scaffolding interactions of the signaling molecules CheA and CheW.

Co-expression of signaling proteins improves robustness of the bacterial chemotaxis pathway

Biological systems are exposed to various perturbations that affect performance of the cellular networks, with stochastic variation in protein levels, or gene expression noise, being one of the major sources of intracellular perturbations. We recently used Escherichia coli chemotaxis as a model to analyze robustness against such noise and demonstrated theoretically and experimentally that a steady-state output of the pathway is robust against concerted variation in the levels of all chemotaxis proteins. However, our model predicted that the pathway topology does not confer much robustness against an uncorrelated variation in the protein levels. To test whether additional robustness features might be missing from our model, we compare here its predictions with an experimentally determined chemotactic performance under varying levels of individual proteins. Our data show that the pathway is indeed even more robust than predicted to two types of perturbations-the variation in the levels of the adaptation enzymes and a correlated expression of CheY and CheZ. Although the design features that are responsible for this higher robustness still remain to be understood, our results stress the importance of a robust design of both native and synthetic signaling networks.