Cellular stoichiometry of the components of the chemotaxis signaling complex

Bacterial Energy Sensor Aer Modulates the Activity of the Chemotaxis Kinase CheA Based on the Redox State of the Flavin Cofactor

Flagellated bacteria modulate their swimming behavior in response to environmental cues through the CheA/CheY signaling pathway. In addition to responding to external chemicals, bacteria also monitor internal conditions that reflect the availability of oxygen, light, and reducing equivalents, in a process termed "energy taxis." In Escherichia coli, the transmembrane receptor Aer is the primary energy sensor for motility. Genetic and physiological data suggest that Aer monitors the electron transport chain through the redox state of its FAD cofactor. However, direct biochemical data correlating FAD redox chemistry with CheA kinase activity have been lacking. Here, we test this hypothesis via functional reconstitution of Aer into nanodiscs. As purified, Aer contains fully oxidized FAD, which can be chemically reduced to the anionic semiquinone (ASQ). Oxidized Aer activates CheA, whereas ASQ Aer reversibly inhibits CheA. Under these conditions, Aer cannot be further reduced to the hydroquinone, in contrast to the proposed Aer signaling model. Pulse ESR spectroscopy of the ASQ corroborates a potential mechanism for signaling in that the resulting distance between the two flavin-binding PAS (Per-Arnt-Sim) domains implies that they tightly sandwich the signal-transducing HAMP domain in the kinase-off state. Aer appears to follow oligomerization patterns observed for related chemoreceptors, as higher loading of Aer dimers into nanodiscs increases kinase activity. These results provide a new methodological platform to study Aer function along with new mechanistic details into its signal transduction process.

Chemotaxis towards autoinducer 2 mediates autoaggregation in Escherichia coli

Bacteria communicate by producing and sensing extracellular signal molecules called autoinducers. Such intercellular signalling, known as quorum sensing, allows bacteria to coordinate and synchronize behavioural responses at high cell densities. Autoinducer 2 (AI-2) is the only known quorum-sensing molecule produced by Escherichia coli but its physiological role remains elusive, although it is known to regulate biofilm formation and virulence in other bacterial species. Here we show that chemotaxis towards self-produced AI-2 can mediate collective behaviour-autoaggregation-of E. coli. Autoaggregation requires motility and is strongly enhanced by chemotaxis to AI-2 at physiological cell densities. These effects are observed regardless whether cell-cell interactions under particular growth conditions are mediated by the major E. coli adhesin (antigen 43) or by curli fibres. Furthermore, AI-2-dependent autoaggregation enhances bacterial stress resistance and promotes biofilm formation.

Direct Correlation between Motile Behavior and Protein Abundance in Single Cells

Understanding how stochastic molecular fluctuations affect cell behavior requires the quantification of both behavior and protein numbers in the same cells. Here, we combine automated microscopy with in situ hydrogel polymerization to measure single-cell protein expression after tracking swimming behavior. We characterized the distribution of non-genetic phenotypic diversity in Escherichia coli motility, which affects single-cell exploration. By expressing fluorescently tagged chemotaxis proteins (CheR and CheB) at different levels, we quantitatively mapped motile phenotype (tumble bias) to protein numbers using thousands of single-cell measurements. Our results disagreed with established models until we incorporated the role of CheB in receptor deamidation and the slow fluctuations in receptor methylation. Beyond refining models, our central finding is that changes in numbers of CheR and CheB affect the population mean tumble bias and its variance independently. Therefore, it is possible to adjust the degree of phenotypic diversity of a population by adjusting the global level of expression of CheR and CheB while keeping their ratio constant, which, as shown in previous studies, confers functional robustness to the system. Since genetic control of protein expression is heritable, our results suggest that non-genetic diversity in motile behavior is selectable, supporting earlier hypotheses that such diversity confers a selective advantage.

Cell-to-cell variations in protein numbers due to random fluctuations at the molecular level lead to cell-to-cell variations in behavior. To maintain predictable responses, signaling networks have evolved robustness against noise, but in some situations phenotypic diversity in a clonal population can be beneficial as a bet hedging or division of labor strategy. Investigating of how random molecular fluctuations affect cell behavior requires to measure biological parameters at different scales. Here, we report a new experiment that allows the measure of both protein numbers and behavior in cells that are free to move in their environment. Using Escherichia coli, a model system for the study of cellular behavior, we investigated the effects variations in the numbers of the chemo-receptor modification enzymes on single-cell swimming behavior. We found that the mean and variance of the behavior can be adjusted independently in the population by adjusting protein expression. This mechanism allows for the genetic selection of phenotypic diversity without disrupting correlations in protein expression that are important for the overall robustness of the chemotaxis system.

Twitching motility and cAMP levels: signal transduction through a single methyl-accepting chemotaxis protein

The Pseudomonas aeruginosa Chp chemosensory system regulates twitching motility, intracellular adenosine 3('') 5(')-cyclic monophosphate (cAMP) levels and is postulated to be involved in directional twitching towards phosphatidylethanolamine (PE). Because PilJ is the only methyl-accepting chemotaxis protein (MCP) identified in the Chp system, we determined the role of PilJ in mediating signal transduction for the distinct outputs of this system. Mutants that lack the periplasmic domain of PilJ (pilJΔ74-273) showed lower levels of cAMP but retained directional twitching towards PE. While initial studies revealed reduced twitching motility by PilJΔ74-273, this was due to decreased cAMP levels. Our data illustrate the importance of the periplasmic domain of PilJ in regulating cAMP. This is the first time a defined domain within PilJ has been identified as having a distinct role in signal transduction.

Information processing in bacteria: memory, computation, and statistical physics: a key issues review

Living systems have to constantly sense their external environment and adjust their internal state in order to survive and reproduce. Biological systems, from as complex as the brain to a single E. coli cell, have to process these data in order to make appropriate decisions. How do biological systems sense external signals? How do they process the information? How do they respond to signals? Through years of intense study by biologists, many key molecular players and their interactions have been identified in different biological machineries that carry out these signaling functions. However, an integrated, quantitative understanding of the whole system is still lacking for most cellular signaling pathways, not to say the more complicated neural circuits. To study signaling processes in biology, the key thing to measure is the input-output relationship. The input is the signal itself, such as chemical concentration, external temperature, light (intensity and frequency), and more complex signals such as the face of a cat. The output can be protein conformational changes and covalent modifications (phosphorylation, methylation, etc), gene expression, cell growth and motility, as well as more complex output such as neuron firing patterns and behaviors of higher animals. Due to the inherent noise in biological systems, the measured input-output dependence is often noisy. These noisy data can be analysed by using powerful tools and concepts from information theory such as mutual information, channel capacity, and the maximum entropy hypothesis. This information theory approach has been successfully used to reveal the underlying correlations between key components of biological networks, to set bounds for network performance, and to understand possible network architecture in generating observed correlations. Although the information theory approach provides a general tool in analysing noisy biological data and may be used to suggest possible network architectures in preserving information, it does not reveal the underlying mechanism that leads to the observed input-output relationship, nor does it tell us much about which information is important for the organism and how biological systems use information to carry out specific functions. To do that, we need to develop models of the biological machineries, e.g. biochemical networks and neural networks, to understand the dynamics of biological information processes. This is a much more difficult task. It requires deep knowledge of the underlying biological network-the main players (nodes) and their interactions (links)-in sufficient detail to build a model with predictive power, as well as quantitative input-output measurements of the system under different perturbations (both genetic variations and different external conditions) to test the model predictions to guide further development of the model. Due to the recent growth of biological knowledge thanks in part to high throughput methods (sequencing, gene expression microarray, etc) and development of quantitative in vivo techniques such as various florescence technology, these requirements are starting to be realized in different biological systems. The possible close interaction between quantitative experimentation and theoretical modeling has made systems biology an attractive field for physicists interested in quantitative biology. In this review, we describe some of the recent work in developing a quantitative predictive model of bacterial chemotaxis, which can be considered as the hydrogen atom of systems biology. Using statistical physics approaches, such as the Ising model and Langevin equation, we study how bacteria, such as E. coli, sense and amplify external signals, how they keep a working memory of the stimuli, and how they use these data to compute the chemical gradient. In particular, we will describe how E. coli cells avoid cross-talk in a heterogeneous receptor cluster to keep a ligand-specific memory. We will also study the thermodynamic costs of adaptation for cells to maintain an accurate memory. The statistical physics based approach described here should be useful in understanding design principles for cellular biochemical circuits in general.

Enhancement of Swimming Speed Leads to a More-Efficient Chemotactic Response to Repellent

Negative chemotaxis refers to the motion of microorganisms away from regions with high concentrations of chemorepellents. In this study, we set controlled gradients of NiCl2, a chemorepellent, in microchannels to quantify the motion of Escherichia coli over a broad range of concentrations. The experimental technique measured the motion of the bacteria in space and time and further related the motion to the local concentration profile of the repellent. Results show that the swimming speed of bacteria increases with an increasing concentration of repellent, which in turn enhances the drift velocity. The contribution of the increased swimming speed to the total drift velocity was in the range of 20 to 40%, with the remaining contribution coming from the modulation of the tumble frequency. A simple model that incorporates receptor dynamics, including adaptation, intracellular signaling, and swimming speed variation, was able to qualitatively capture the observed trend in drift velocity.

SOS System Induction Inhibits the Assembly of Chemoreceptor Signaling Clusters in Salmonella enterica

Swarming, a flagellar-driven multicellular form of motility, is associated with bacterial virulence and increased antibiotic resistance. In this work we demonstrate that activation of the SOS response reversibly inhibits swarming motility by preventing the assembly of chemoreceptor-signaling polar arrays. We also show that an increase in the concentration of the RecA protein, generated by SOS system activation, rather than another function of this genetic network impairs chemoreceptor polar cluster formation. Our data provide evidence that the molecular balance between RecA and CheW proteins is crucial to allow polar cluster formation in Salmonella enterica cells. Thus, activation of the SOS response by the presence of a DNA-injuring compound increases the RecA concentration, thereby disturbing the equilibrium between RecA and CheW and resulting in the cessation of swarming. Nevertheless, when the DNA-damage decreases and the SOS response is no longer activated, basal RecA levels and thus polar cluster assembly are reestablished. These results clearly show that bacterial populations moving over surfaces make use of specific mechanisms to avoid contact with DNA-damaging compounds.

Fundamental constraints on the abundances of chemotaxis proteins

Flagellated bacteria, such as Escherichia coli, perform directed motion in gradients of concentration of attractants and repellents in a process called chemotaxis. The E. coli chemotaxis signaling pathway is a model for signal transduction, but it has unique features. We demonstrate that the need for fast signaling necessitates high abundances of the proteins involved in this pathway. We show that further constraints on the abundances of chemotaxis proteins arise from the requirements of self-assembly both of flagellar motors and of chemoreceptor arrays. All these constraints are specific to chemotaxis, and published data confirm that chemotaxis proteins tend to be more highly expressed than their homologs in other pathways. Employing a chemotaxis pathway model, we show that the gain of the pathway at the level of the response regulator CheY increases with overall chemotaxis protein abundances. This may explain why, at least in one E. coli strain, the abundance of all chemotaxis proteins is higher in media with lower nutrient content. We also demonstrate that the E. coli chemotaxis pathway is particularly robust to abundance variations of the motor protein FliM.

Bacterial chemotaxis: information processing, thermodynamics, and behavior

Escherichia coli has long been used as a model organism due to the extensive experimental characterization of its pathways and molecular components. Take chemotaxis as an example, which allows bacteria to sense and swim in response to chemicals, such as nutrients and toxins. Many of the pathway's remarkable sensing and signaling properties are now concisely summarized in terms of design (or engineering) principles. More recently, new approaches from information theory and stochastic thermodynamics have begun to address how pathways process environmental stimuli and what the limiting factors are. However, to fully capitalize on these theoretical advances, a closer connection with single-cell experiments will be required.

Protein Connectivity in Chemotaxis Receptor Complexes

The chemotaxis sensory system allows bacteria such as Escherichia coli to swim towards nutrients and away from repellents. The underlying pathway is remarkably sensitive in detecting chemical gradients over a wide range of ambient concentrations. Interactions among receptors, which are predominantly clustered at the cell poles, are crucial to this sensitivity. Although it has been suggested that the kinase CheA and the adapter protein CheW are integral for receptor connectivity, the exact coupling mechanism remains unclear. Here, we present a statistical-mechanics approach to model the receptor linkage mechanism itself, building on nanodisc and electron cryotomography experiments. Specifically, we investigate how the sensing behavior of mixed receptor clusters is affected by variations in the expression levels of CheA and CheW at a constant receptor density in the membrane. Our model compares favorably with dose-response curves from in vivo Förster resonance energy transfer (FRET) measurements, demonstrating that the receptor-methylation level has only minor effects on receptor cooperativity. Importantly, our model provides an explanation for the non-intuitive conclusion that the receptor cooperativity decreases with increasing levels of CheA, a core signaling protein associated with the receptors, whereas the receptor cooperativity increases with increasing levels of CheW, a key adapter protein. Finally, we propose an evolutionary advantage as explanation for the recently suggested CheW-only linker structures.

Receptor clusters of the bacterial chemotaxis sensory system act as antennae to amplify tiny changes in concentrations in the chemical environment of the cell, ultimately steering the cell towards nutrients and away from toxins. Despite bacterial chemotaxis being the most widely studied sensory pathway, the exact architecture of the receptor clusters remains speculative, with understanding suffering from a number of paradoxical observations. To address these issues with respect to the protein arrangement in the linkers connecting receptors, we present a statistical-mechanics model that combines insights from electron cryotomography on the linker architecture with results from fluorescence imaging of signaling in living cells. Although the signaling data for different expression levels of key molecular components in the linkers seems contradictory at first, our model reconciles these predictions with structural and biochemical data. Finally, we provide an evolutionary explanation for the observation that some of the incorporated linkers do not seem to transmit signals from the receptors.

Understanding the link between single cell and population scale responses of Escherichia coli in differing ligand gradients

We formulate an agent-based population model of Escherichia coli cells which incorporates a description of the chemotaxis signalling cascade at the single cell scale. The model is used to gain insight into the link between the signalling cascade dynamics and the overall population response to differing chemoattractant gradients. Firstly, we consider how the observed variation in total (phosphorylated and unphosphorylated) signalling protein concentration affects the ability of cells to accumulate in differing chemoattractant gradients. Results reveal that a variation in total cell protein concentration between cells may be a mechanism for the survival of cell colonies across a wide range of differing environments. We then study the response of cells in the presence of two different chemoattractants. In doing so we demonstrate that the population scale response depends not on the absolute concentration of each chemoattractant but on the sensitivity of the chemoreceptors to their respective concentrations. Our results show the clear link between single cell features and the overall environment in which cells reside.

Single-cell E. coli response to an instantaneously applied chemotactic signal

In response to an attractant or repellant, an Escherichia coli cell controls the rotational direction of its flagellar motor by a chemotaxis system. When an E. coli cell senses an attractant, a reduction in the intracellular concentration of a chemotaxis protein, phosphorylated CheY (CheY-P), induces counterclockwise (CCW) rotation of the flagellar motor, and this cellular response is thought to occur in several hundred milliseconds. Here, to measure the signaling process occurring inside a single E. coli cell, including the recognition of an attractant by a receptor cluster, the inactivation of histidine kinase CheA, and the diffusion of CheY and CheY-P molecules, we applied a serine stimulus by instantaneous photorelease from a caged compound and examined the cellular response at a temporal resolution of several hundred microseconds. We quantified the clockwise (CW) and CCW durations immediately after the photorelease of serine as the response time and the duration of the response, respectively. The results showed that the response time depended on the distance between the receptor and motor, indicating that the decreased CheY-P concentration induced by serine propagates through the cytoplasm from the receptor-kinase cluster toward the motor with a timing that is explained by the diffusion of CheY and CheY-P molecules. The response time included 240 ms for enzymatic reactions in addition to the time required for diffusion of the signaling molecule. The measured response time and duration of the response also revealed that the E. coli cell senses a similar serine concentration regardless of whether the serine concentration is increasing or decreasing. These detailed quantitative findings increase our understanding of the signal transduction process that occurs inside cells during bacterial chemotaxis.

Molecular adaptations of Herbaspirillum seropedicae during colonization of the maize rhizosphere

Molecular mechanisms of plant recognition and colonization by diazotrophic bacteria are barely understood. Herbaspirillum seropedicae is a Betaproteobacterium capable of colonizing epiphytically and endophytically commercial grasses, to promote plant growth. In this study, we utilized RNA-seq to compare the transcriptional profiles of planktonic and maize root-attached H. seropedicae SmR1 recovered 1 and 3 days after inoculation. The results indicated that nitrogen metabolism was strongly activated in the rhizosphere and polyhydroxybutyrate storage was mobilized in order to assist the survival of H. seropedicae during the early stages of colonization. Epiphytic cells showed altered transcription levels of several genes associated with polysaccharide biosynthesis, peptidoglycan turnover and outer membrane protein biosynthesis, suggesting reorganization of cell wall envelope components. Specific methyl-accepting chemotaxis proteins and two-component systems were differentially expressed between populations over time, suggesting deployment of an extensive bacterial sensory system for adaptation to the plant environment. An insertion mutation inactivating a methyl-accepting chemosensor induced in planktonic bacteria, decreased chemotaxis towards the plant and attachment to roots. In summary, analysis of mutant strains combined with transcript profiling revealed several molecular adaptations that enable H. seropedicae to sense the plant environment, attach to the root surface and survive during the early stages of maize colonization.

Chemotaxis of Escherichia coli to norepinephrine (NE) requires conversion of NE to 3,4-dihydroxymandelic acid

Norepinephrine (NE), the primary neurotransmitter of the sympathetic nervous system, has been reported to be a chemoattractant for enterohemorrhagic Escherichia coli (EHEC). Here we show that nonpathogenic E. coli K-12 grown in the presence of 2 μM NE is also attracted to NE. Growth with NE induces transcription of genes encoding the tyramine oxidase, TynA, and the aromatic aldehyde dehydrogenase, FeaB, whose respective activities can, in principle, convert NE to 3,4-dihydroxymandelic acid (DHMA). Our results indicate that the apparent attractant response to NE is in fact chemotaxis to DHMA, which was found to be a strong attractant for E. coli. Only strains of E. coli K-12 that produce TynA and FeaB exhibited an attractant response to NE. We demonstrate that DHMA is sensed by the serine chemoreceptor Tsr and that the chemotaxis response requires an intact serine-binding site. The threshold concentration for detection is ≤5 nM DHMA, and the response is inhibited at DHMA concentrations above 50 μM. Cells producing a heterodimeric Tsr receptor containing only one functional serine-binding site still respond like the wild type to low concentrations of DHMA, but their response persists at higher concentrations. We propose that chemotaxis to DHMA generated from NE by bacteria that have already colonized the intestinal epithelium may recruit E. coli and other enteric bacteria that possess a Tsr-like receptor to preferred sites of infection.

Optimal resource allocation in cellular sensing systems

Living cells deploy many resources to sense their environments, including receptors, downstream signaling molecules, time, and fuel. However, it is not known which resources fundamentally limit the precision of sensing, like weak links in a chain, and which can compensate each other, leading to trade-offs between them. We present a theory for the optimal design of the large class of sensing systems in which a receptor drives a push-pull network. The theory identifies three classes of resources that are required for sensing: receptors and their integration time, readout molecules, and energy (fuel turnover). Each resource class sets a fundamental sensing limit, which means that the sensing precision is bounded by the limiting resource class and cannot be enhanced by increasing another class--the different classes cannot compensate each other. This result yields a previously unidentified design principle, namely that of optimal resource allocation in cellular sensing. It states that, in an optimally designed sensing system, each class of resources is equally limiting so that no resource is wasted. We apply our theory to what is arguably the best-characterized sensing system in biology, the chemotaxis network of Escherichia coli. Our analysis reveals that this system obeys the principle of optimal resource allocation, indicating a selective pressure for the efficient design of cellular sensing systems.

Adaptability of non-genetic diversity in bacterial chemotaxis

Bacterial chemotaxis systems are as diverse as the environments that bacteria inhabit, but how much environmental variation can cells tolerate with a single system? Diversification of a single chemotaxis system could serve as an alternative, or even evolutionary stepping-stone, to switching between multiple systems. We hypothesized that mutations in gene regulation could lead to heritable control of chemotactic diversity. By simulating foraging and colonization of E. coli using a single-cell chemotaxis model, we found that different environments selected for different behaviors. The resulting trade-offs show that populations facing diverse environments would ideally diversify behaviors when time for navigation is limited. We show that advantageous diversity can arise from changes in the distribution of protein levels among individuals, which could occur through mutations in gene regulation. We propose experiments to test our prediction that chemotactic diversity in a clonal population could be a selectable trait that enables adaptation to environmental variability.

DOI:http://dx.doi.org/10.7554/eLife.03526.001

Bacterial colonies are generally made up of genetically identical cells. Despite this, a closer look at the members of a bacterial colony shows that these cells can have very different behaviors. For example, some cells may grow more quickly than others, or be more resistant to antibiotics. The mechanisms driving this diversity are only beginning to be identified and understood.

Escherichia coli bacteria can move towards, or away from, certain chemicals in their surrounding environment to help them navigate toward favorable conditions. This behavior is known as chemotaxis. The signals from all of these chemicals are processed in E. coli by just one set of proteins, which control the different behaviors that are needed for the bacteria to follow them. Different numbers of these proteins are found in different—but genetically identical—bacteria, and the number of proteins is linked to how the bacteria perform these behaviors.

It has been suggested that diversity can be beneficial to the overall bacterial population, as it helps the population survive environmental changes. This suggests that the level of diversity in the population should adapt to the level of diversity in the environment. However, it remains unknown how this adaptation occurs.

Frankel et al. developed and combined several models and simulations to investigate whether differences in chemotaxis protein production help an E. coli colony to survive. The models show that in different environments, it can be beneficial for the population as a whole if different cells have different responses to the chemicals present. For example, if a lot of a useful chemical is present, bacteria are more likely to survive by heading straight to the source. If not much chemical is detected, the bacteria may need to move in a more exploratory manner.

Frankel et al. find that different amounts of chemotaxis proteins produce these different behaviors. To survive in a changing environment, it is therefore best for the E. coli colony to contain cells that have different amounts of these proteins. Frankel et al. propose that the variability of chemotaxis protein levels between genetically identical cells can change through mutations in the genes that control how many of the proteins are produced, and predict that such mutations allow populations to adapt to environmental changes.

The environments simulated in the model were much simpler than would be found in the real world, and Frankel et al. describe experiments that are now being performed to confirm and expand on their results. The model could be used in the future to shed light on the behavior of other cells that are genetically identical but exhibit diverse behaviors, from other bacterial species to more complex cancer cells.

DOI:http://dx.doi.org/10.7554/eLife.03526.002

High density and ligand affinity confer ultrasensitive signal detection by a guanylyl cyclase chemoreceptor

Guanylyl cyclases (GCs), which synthesize the messenger cyclic guanosine 3',5'-monophosphate, control several sensory functions, such as phototransduction, chemosensation, and thermosensation, in many species from worms to mammals. The GC chemoreceptor in sea urchin sperm can decode chemoattractant concentrations with single-molecule sensitivity. The molecular and cellular underpinnings of such ultrasensitivity are not known for any eukaryotic chemoreceptor. In this paper, we show that an exquisitely high density of 3 × 10(5) GC chemoreceptors and subnanomolar ligand affinity provide a high ligand-capture efficacy and render sperm perfect absorbers. The GC activity is terminated within 150 ms by dephosphorylation steps of the receptor, which provides a means for precise control of the GC lifetime and which reduces "molecule noise." Compared with other ultrasensitive sensory systems, the 10-fold signal amplification by the GC receptor is surprisingly low. The hallmarks of this signaling mechanism provide a blueprint for chemical sensing in small compartments, such as olfactory cilia, insect antennae, or even synaptic boutons.

Interactions among the three adaptation systems of Bacillus subtilis chemotaxis as revealed by an in vitro receptor-kinase assay

The Bacillus subtilis chemotaxis pathway employs three systems for sensory adaptation: the methylation system, the CheC/CheD/CheYp system, and the CheV system. Little is known in general about how these three adaptation systems contribute to chemotaxis in B. subtilis and whether they interact with one another. To further understand these three adaptation systems, we employed a quantitative in vitro receptor-kinase assay. Using this assay, we were able to determine how CheD and CheV affect receptor-kinase activity as a function of the receptor modification state. CheD was found to increase receptor-kinase activity, where the magnitude of the increase depends on the modification state of the receptor. The principal new findings concern CheV. Little was known about this protein before now. Our data suggest that this protein has two roles depending on the modification state of the receptor, one for sensory adaptation when the receptors are modified (methylated) and the other for signal amplification when they are unmodified (unmethylated). In addition, our data suggest that methylation of site 630 tunes the strength of the CheV adaptation system. Collectively, our results provide new insight regarding the integrated function of the three adaptation systems in B. subtilis.

Exponential signaling gain at the receptor level enhances signal-to-noise ratio in bacterial chemotaxis

Cellular signaling systems show astonishing precision in their response to external stimuli despite strong fluctuations in the molecular components that determine pathway activity. To control the effects of noise on signaling most efficiently, living cells employ compensatory mechanisms that reach from simple negative feedback loops to robustly designed signaling architectures. Here, we report on a novel control mechanism that allows living cells to keep precision in their signaling characteristics – stationary pathway output, response amplitude, and relaxation time – in the presence of strong intracellular perturbations. The concept relies on the surprising fact that for systems showing perfect adaptation an exponential signal amplification at the receptor level suffices to eliminate slowly varying multiplicative noise. To show this mechanism at work in living systems, we quantified the response dynamics of the E. coli chemotaxis network after genetically perturbing the information flux between upstream and downstream signaling components. We give strong evidence that this signaling system results in dynamic invariance of the activated response regulator against multiplicative intracellular noise. We further demonstrate that for environmental conditions, for which precision in chemosensing is crucial, the invariant response behavior results in highest chemotactic efficiency. Our results resolve several puzzling features of the chemotaxis pathway that are widely conserved across prokaryotes but so far could not be attributed any functional role.

New insights into bacterial chemoreceptor array structure and assembly from electron cryotomography

Bacterial chemoreceptors cluster in highly ordered, cooperative, extended arrays with a conserved architecture, but the principles that govern array assembly remain unclear. Here we show images of cellular arrays as well as selected chemoreceptor complexes reconstituted in vitro that reveal new principles of array structure and assembly. First, in every case, receptors clustered in a trimers-of-dimers configuration, suggesting this is a highly favored fundamental building block. Second, these trimers-of-receptor dimers exhibited great versatility in the kinds of contacts they formed with each other and with other components of the signaling pathway, although only one architectural type occurred in native arrays. Third, the membrane, while it likely accelerates the formation of arrays, was neither necessary nor sufficient for lattice formation. Molecular crowding substituted for the stabilizing effect of the membrane and allowed cytoplasmic receptor fragments to form sandwiched lattices that strongly resemble the cytoplasmic chemoreceptor arrays found in some bacterial species. Finally, the effective determinant of array structure seemed to be CheA and CheW, which formed a "superlattice" of alternating CheA-filled and CheA-empty rings that linked receptor trimers-of-dimer units into their native hexagonal lattice. While concomitant overexpression of receptors, CheA, and CheW yielded arrays with native spacing, the CheA occupancy was lower and less ordered, suggesting that temporal and spatial coordination of gene expression driven by a single transcription factor may be vital for full order, or that array overgrowth may trigger a disassembly process. The results described here provide new insights into the assembly intermediates and assembly mechanism of this massive macromolecular complex.

An unorthodox sensory adaptation site in the Escherichia coli serine chemoreceptor

The serine chemoreceptor of Escherichia coli contains four canonical methylation sites for sensory adaptation that lie near intersubunit helix interfaces of the Tsr homodimer. An unexplored fifth methylation site, E502, lies at an intrasubunit helix interface closest to the HAMP domain that controls input-output signaling in methyl-accepting chemotaxis proteins. We analyzed, with in vivo Förster resonance energy transfer (FRET) kinase assays, the serine thresholds and response cooperativities of Tsr receptors with different mutationally imposed modifications at sites 1 to 4 and/or at site 5. Tsr variants carrying E or Q at residue 502, in combination with unmodifiable D and N replacements at adaptation sites 1 to 4, underwent both methylation and demethylation/deamidation, although detection of the latter modifications required elevated intracellular levels of CheB. These Tsr variants could not mediate a chemotactic response to serine spatial gradients, demonstrating that adaptational modifications at E502 alone are not sufficient for Tsr function. Moreover, E502 is not critical for Tsr function, because only two amino acid replacements at this residue abrogated serine chemotaxis: Tsr-E502P had extreme kinase-off output and Tsr-E502I had extreme kinase-on output. These large threshold shifts are probably due to the unique HAMP-proximal location of methylation site 5. However, a methylation-mimicking glutamine at any Tsr modification site raised the serine response threshold, suggesting that all sites influence signaling by the same general mechanism, presumably through changes in packing stability of the methylation helix bundle. These findings are consistent with control of input-output signaling in Tsr through dynamic interplay of the structural stabilities of the HAMP and methylation bundles.

Cell responses only partially shape cell-to-cell variations in protein abundances in Escherichia coli chemotaxis

Cell-to-cell variations in protein abundance in clonal cell populations are ubiquitous in living systems. Because protein composition determines responses in individual cells, it stands to reason that the variations themselves are subject to selective pressures. However, the functional role of these cell-to-cell differences is not well understood. One way to tackle questions regarding relationships between form and function is to perturb the form (e.g., change the protein abundances) and observe the resulting changes in some function. Here, we take on the form-function relationship from the inverse perspective, asking instead what specific constraints on cell-to-cell variations in protein abundance are imposed by a given functional phenotype. We develop a maximum entropy-based approach to posing questions of this type and illustrate the method by application to the well-characterized chemotactic response in Escherichia coli. We find that full determination of observed cell-to-cell variations in protein abundances is not inherent in chemotaxis itself but, in fact, appears to be jointly imposed by the chemotaxis program in conjunction with other factors (e.g., the protein synthesis machinery and/or additional nonchemotactic cell functions, such as cell metabolism). These results illustrate the power of maximum entropy as a tool for the investigation of relationships between biological form and function.

Data-driven quantification of the robustness and sensitivity of cell signaling networks

Robustness and sensitivity of responses generated by cell signaling networks has been associated with survival and evolvability of organisms. However, existing methods analyzing robustness and sensitivity of signaling networks ignore the experimentally observed cell-to-cell variations of protein abundances and cell functions or contain ad hoc assumptions. We propose and apply a data-driven maximum entropy based method to quantify robustness and sensitivity of Escherichia coli (E. coli) chemotaxis signaling network. Our analysis correctly rank orders different models of E. coli chemotaxis based on their robustness and suggests that parameters regulating cell signaling are evolutionary selected to vary in individual cells according to their abilities to perturb cell functions. Furthermore, predictions from our approach regarding distribution of protein abundances and properties of chemotactic responses in individual cells based on cell population averaged data are in excellent agreement with their experimental counterparts. Our approach is general and can be used to evaluate robustness as well as generate predictions of single cell properties based on population averaged experimental data in a wide range of cell signaling systems.

Unraveling adaptation in eukaryotic pathways: lessons from protocells

Eukaryotic adaptation pathways operate within wide-ranging environmental conditions without stimulus saturation. Despite numerous differences in the adaptation mechanisms employed by bacteria and eukaryotes, all require energy consumption. Here, we present two minimal models showing that expenditure of energy by the cell is not essential for adaptation. Both models share important features with large eukaryotic cells: they employ small diffusible molecules and involve receptor subunits resembling highly conserved G-protein cascades. Analyzing the drawbacks of these models helps us understand the benefits of energy consumption, in terms of adjustability of response and adaptation times as well as separation of cell-external sensing and cell-internal signaling. Our work thus sheds new light on the evolution of adaptation mechanisms in complex systems.

Adaptation is a common feature in sensory systems, well familiar to us from light and dark adaptation of our visual system. Biological cells, ranging from bacteria to complex eukaryotes, including single-cell organisms and human sensory receptors, adopt different strategies to fulfill this property. However, all of them require substantial amounts of energy to adapt. Here, we compare the different biological strategies and design two minimal models which allow adaptation without requiring energy consumption. Schemes similar to the ones we proposed in our minimal models could have been adopted by ancient protocells, that have evolved into the pathways we now know and study. Analyzing our models can thus help elucidate the advantages brought to the cells by consumption of energy, including the bypassing of hard-wired cell parameters such as diffusion constants with increased control over time scales.

The sensory histidine kinases TorS and EvgS tend to form clusters in Escherichia coli cells

Microorganisms use multiple two-component sensory systems to detect changes in their environment and elicit physiological responses. Despite their wide spread and importance, the intracellular organization of two-component sensory proteins in bacteria remains little investigated. A notable exception is the well-studied clustering of the chemoreceptor-kinase complexes that mediate chemotaxis behaviour. However, these chemosensory complexes differ fundamentally from other systems, both structurally and functionally. Therefore, studying the organization of typical sensory kinases in bacteria is essential for understanding the general role of receptor clustering in bacterial sensory signalling. Here, by studying mYFP-tagged sensory kinases in Escherichia coli, we show that the tagged TorS and EvgS sensors have a clear tendency for self-association and clustering. These sensors clustered even when expressed at a level of a few hundred copies per cell. Moreover, the mYFP-tagged response regulator TorR showed clear TorS-dependent clustering, indicating that untagged TorS sensors also tend to form clusters. We also provide evidence for the functionality of these tagged sensors. Experiments with truncated TorS or EvgS proteins suggested that clustering of EvgS sensors depends on the cytoplasmic part of the protein, whereas clustering of TorS sensors can be potentially mediated by the periplasmic/transmembrane domain. Overall, these findings support the notion that sensor clustering plays a role in bacterial sensory signalling beyond chemotaxis.

Adaptation dynamics in densely clustered chemoreceptors

In many sensory systems, transmembrane receptors are spatially organized in large clusters. Such arrangement may facilitate signal amplification and the integration of multiple stimuli. However, this organization likely also affects the kinetics of signaling since the cytoplasmic enzymes that modulate the activity of the receptors must localize to the cluster prior to receptor modification. Here we examine how these spatial considerations shape signaling dynamics at rest and in response to stimuli. As a model system, we use the chemotaxis pathway of Escherichia coli, a canonical system for the study of how organisms sense, respond, and adapt to environmental stimuli. In bacterial chemotaxis, adaptation is mediated by two enzymes that localize to the clustered receptors and modulate their activity through methylation-demethylation. Using a novel stochastic simulation, we show that distributive receptor methylation is necessary for successful adaptation to stimulus and also leads to large fluctuations in receptor activity in the steady state. These fluctuations arise from noise in the number of localized enzymes combined with saturated modification kinetics between the localized enzymes and the receptor substrate. An analytical model explains how saturated enzyme kinetics and large fluctuations can coexist with an adapted state robust to variation in the expression levels of the pathway constituents, a key requirement to ensure the functionality of individual cells within a population. This contrasts with the well-mixed covalent modification system studied by Goldbeter and Koshland in which mean activity becomes ultrasensitive to protein abundances when the enzymes operate at saturation. Large fluctuations in receptor activity have been quantified experimentally and may benefit the cell by enhancing its ability to explore empty environments and track shallow nutrient gradients. Here we clarify the mechanistic relationship of these large fluctuations to well-studied aspects of the chemotaxis system, precise adaptation and functional robustness.

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.

Quantitative modeling of bacterial chemotaxis: signal amplification and accurate adaptation

We review the recent developments in understanding the bacterial chemotaxis signaling pathway by using quantitative modeling methods. The models developed are based on structural information of the signaling complex and the dynamics of the underlying biochemical network. We focus on two important functions of the bacterial chemotaxis signaling pathway: signal amplification and adaptation. We describe in detail the structure and the dynamics of the mathematical models and how they compare with existing experiments, emphasizing the predictability of the models. Finally, we outline future directions for developing the modeling approach to better understand the bacterial chemosensory system.

Chemoreceptors of Escherichia coli CFT073 play redundant roles in chemotaxis toward urine

Community-acquired urinary tract infections (UTIs) are commonly caused by uropathogenic Escherichia coli (UPEC). We hypothesize that chemotaxis toward ligands present in urine could direct UPEC into and up the urinary tract. Wild-type E. coli CFT073 and chemoreceptor mutants with tsr, tar, or aer deletions were tested for chemotaxis toward human urine in the capillary tube assay. Wild-type CFT073 was attracted toward urine, and Tsr and Tar were the chemoreceptors mainly responsible for mediating this response. The individual components of urine including L-amino acids, D-amino acids and various organic compounds were also tested in the capillary assay with wild-type CFT073. Our results indicate that CFT073 is attracted toward some L- amino acids and possibly toward some D-amino acids but not other common compounds found in urine such as urea, creatinine and glucuronic acid. In the murine model of UTI, the loss of any two chemoreceptors did not affect the ability of the bacteria to compete with the wild-type strain. Our data suggest that the presence of any strong attractant and its associated chemoreceptor might be sufficient for colonization of the urinary tract and that amino acids are the main chemoattractants for E. coli strain CFT073 in this niche.

mMaple: a photoconvertible fluorescent protein for use in multiple imaging modalities

Recent advances in fluorescence microscopy have extended the spatial resolution to the nanometer scale. Here, we report an engineered photoconvertible fluorescent protein (pcFP) variant, designated as mMaple, that is suited for use in multiple conventional and super-resolution imaging modalities, specifically, widefield and confocal microscopy, structured illumination microscopy (SIM), and single-molecule localization microscopy. We demonstrate the versatility of mMaple by obtaining super-resolution images of protein organization in Escherichia coli and conventional fluorescence images of mammalian cells. Beneficial features of mMaple include high photostability of the green state when expressed in mammalian cells and high steady state intracellular protein concentration of functional protein when expressed in E. coli. mMaple thus enables both fast live-cell ensemble imaging and high precision single molecule localization for a single pcFP-containing construct.

Ligand affinity and kinase activity are independent of bacterial chemotaxis receptor concentration: insight into signaling mechanisms

Binding of attractant to bacterial chemotaxis receptors initiates a transmembrane signal that inhibits the kinase CheA bound ~300 Å distant at the other end of the receptor. Chemoreceptors form large clusters in many bacterial species, and the extent of clustering has been reported to vary with signaling state. To test whether ligand binding regulates kinase activity by modulating a clustering equilibrium, we measured the effects of two-dimensional receptor concentration on kinase activity in proteoliposomes containing the purified Escherichia coli serine receptor reconstituted into vesicles over a range of lipid:protein molar ratios. The IC(50) of kinase inhibition was unchanged despite a 10-fold change in receptor concentration. Such a change in concentration would have produced a measurable shift in the IC(50) if receptor clustering were involved in kinase regulation, based on a simple model in which the receptor oligomerization and ligand binding equilibria are coupled. These results indicate that the primary signal, ligand control of kinase activity, does not involve a change in receptor oligomerization state. In combination with previous work on cytoplasmic fragments assembled on vesicle surfaces [Besschetnova, T. Y., et al. (2008) Proc. Natl. Acad. Sci. U.S.A.105, 12289-12294], this suggests that binding of ligand to chemotaxis receptors inhibits the kinase by inducing a conformational change that expands the membrane area occupied by the receptor cytoplasmic domain, without changing the number of associated receptors in the signaling complex.

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.

CheA-receptor interaction sites in bacterial chemotaxis

In bacterial chemotaxis, transmembrane chemoreceptors, the CheA histidine kinase, and the CheW coupling protein assemble into signaling complexes that allow bacteria to modulate their swimming behavior in response to environmental stimuli. Among the protein-protein interactions in the ternary complex, CheA-CheW and CheW-receptor interactions were studied previously, whereas CheA-receptor interaction has been less investigated. Here, we characterize the CheA-receptor interaction in Thermotoga maritima by NMR spectroscopy and validate the identified receptor binding site of CheA in Escherichia coli chemotaxis. We find that CheA interacts with a chemoreceptor in a manner similar to that of CheW, and the receptor binding site of CheA's regulatory domain is homologous to that of CheW. Collectively, the receptor binding sites in the CheA-CheW complex suggest that conformational changes in CheA are required for assembly of the CheA-CheW-receptor ternary complex and CheA activation.

Molecular architecture of chemoreceptor arrays revealed by cryoelectron tomography of Escherichia coli minicells

The chemoreceptors of Escherichia coli localize to the cell poles and form a highly ordered array in concert with the CheA kinase and the CheW coupling factor. However, a high-resolution structure of the array has been lacking, and the molecular basis of array assembly has thus remained elusive. Here, we use cryoelectron tomography of flagellated E. coli minicells to derive a 3D map of the intact array. Docking of high-resolution structures into the 3D map provides a model of the core signaling complex, in which a CheA/CheW dimer bridges two adjacent receptor trimers via multiple hydrophobic interactions. A further, hitherto unknown, hydrophobic interaction between CheW and the homologous P5 domain of CheA in an adjacent core complex connects the complexes into an extended array. This architecture provides a structural basis for array formation and could explain the high sensitivity and cooperativity of chemotaxis signaling in E. coli.

The energy-speed-accuracy tradeoff in sensory adaptation

Adaptation is the essential process by which an organism becomes better suited to its environment. The benefits of adaptation are well documented, but the cost it incurs remains poorly understood. Here, by analysing a stochastic model of a minimum feedback network underlying many sensory adaptation systems, we show that adaptive processes are necessarily dissipative, and continuous energy consumption is required to stabilize the adapted state. Our study reveals a general relation among energy dissipation rate, adaptation speed and the maximum adaptation accuracy. This energy-speed-accuracy relation is tested in the Escherichia coli chemosensory system, which exhibits near-perfect chemoreceptor adaptation. We identify key requirements for the underlying biochemical network to achieve accurate adaptation with a given energy budget. Moreover, direct measurements confirm the prediction that adaptation slows down as cells gradually de-energize in a nutrient-poor medium without compromising adaptation accuracy. Our work provides a general framework to study cost-performance tradeoffs for cellular regulatory functions and information processing.

Theoretical insights into bacterial chemotaxis

Research into understanding bacterial chemotactic systems has become a paradigm for Systems Biology. Experimental and theoretical researchers have worked hand-in-hand for over 40 years to understand the intricate behavior driving bacterial species, in particular how such small creatures, usually not more than 5 µm in length, detect and respond to small changes in their extracellular environment. In this review we highlight the importance that theoretical modeling has played in providing new insight and understanding into bacterial chemotaxis. We begin with an overview of the bacterial chemotaxis sensory response, before reviewing the role of theoretical modeling in understanding elements of the system on the single cell scale and features underpinning multiscale extensions to population models.

Membrane clustering and the role of rebinding in biochemical signaling

In many cellular signaling pathways, key components form clusters at the cell membrane. Although much work has focused on the mechanisms behind such cluster formation, the implications for downstream signaling remain poorly understood. Here, motivated by recent experiments, we use particle-based simulation to study a covalent modification network in which the activating component is either clustered or randomly distributed on the membrane. We find that whereas clustering reduces the response of a single-modification network, it can enhance the response of a double-modification network. The reduction is a bulk effect: a cluster presents a smaller effective target to a substrate molecule in the bulk. The enhancement, on the other hand, is a local effect: a cluster promotes the rapid rebinding and second activation of singly activated substrate molecules. As such, the enhancement relies on frequent collisions on a short timescale, leading to an optimal ratio of diffusion to association that agrees with typical measured rates. We complement simulation with analytic results at both the mean-field and first-passage distribution levels. Our results emphasize the importance of spatially resolved models, showing that significant effects of spatial correlations persist even in spatially averaged quantities such as response curves.

Bacterial chemoreceptor arrays are hexagonally packed trimers of receptor dimers networked by rings of kinase and coupling proteins

Chemoreceptor arrays are supramolecular transmembrane machines of unknown structure that allow bacteria to sense their surroundings and respond by chemotaxis. We have combined X-ray crystallography of purified proteins with electron cryotomography of native arrays inside cells to reveal the arrangement of the component transmembrane receptors, histidine kinases (CheA) and CheW coupling proteins. Trimers of receptor dimers lie at the vertices of a hexagonal lattice in a "two-facing-two" configuration surrounding a ring of alternating CheA regulatory domains (P5) and CheW couplers. Whereas the CheA kinase domains (P4) project downward below the ring, the CheA dimerization domains (P3) link neighboring rings to form an extended, stable array. This highly interconnected protein architecture underlies the remarkable sensitivity and cooperative nature of transmembrane signaling in bacterial chemotaxis.

The genome sequence of Polymorphum gilvum SL003B-26A1(T) reveals its genetic basis for crude oil degradation and adaptation to the saline soil

Polymorphum gilvum SL003B-26A1^T is the type strain of a novel species in the recently published novel genus Polymorphum isolated from saline soil contaminated with crude oil. It is capable of using crude oil as the sole carbon and energy source and can adapt to saline soil at a temperature of 45°C. The Polymorphum gilvum genome provides a genetic basis for understanding how the strain could degrade crude oil and adapt to a saline environment. Genome analysis revealed the versatility of the strain for emulsifying crude oil, metabolizing aromatic compounds (a characteristic specific to the Polymorphum gilvum genome in comparison with other known genomes of oil-degrading bacteria), as well as possibly metabolizing n-alkanes through the LadA pathway. In addition, COG analysis revealed Polymorphum gilvum SL003B-26A1^T has significantly higher abundances of the proteins responsible for cell motility, lipid transport and metabolism, and secondary metabolite biosynthesis, transport and catabolism than the average levels found in all other genomes sequenced thus far, but lower abundances of the proteins responsible for carbohydrate transport and metabolism, defense mechanisms, and translation than the average levels. These traits support the adaptability of Polymorphum gilvum to a crude oil-contaminated saline environment. The Polymorphum gilvum genome could serve as a platform for further study of oil-degrading microorganisms for bioremediation and microbial-enhanced oil recovery in harsh saline environments.

Responding to chemical gradients: bacterial chemotaxis

Chemotaxis allows bacteria to follow gradients of nutrients and other environmental stimuli. The bacterium Escherichia coli performs chemotaxis via a run-and-tumble strategy in which sensitive temporal comparisons lead to a biased random walk, with longer runs in the preferred gradient direction. The chemotaxis network of E. coli has developed over the years into one of the most thoroughly studied model systems for signal transduction and behavior, yielding general insights into such properties of cellular networks as signal amplification, signal integration, and robustness. Despite its relative simplicity, the operation of the E. coli chemotaxis network is highly refined and evolutionarily optimized at many levels. For example, recent studies revealed that the network adjusts its signaling properties dependent on the extracellular environment, apparently to optimize chemotaxis under particular conditions. The network can even utilize potentially detrimental stochastic fluctuations in protein levels and reaction rates to maximize the chemotactic performance of the population.

Noise characteristics of the Escherichia coli rotary motor

Background

The chemotaxis pathway in the bacterium Escherichia coli allows cells to detect changes in external ligand concentration (e.g. nutrients). The pathway regulates the flagellated rotary motors and hence the cells' swimming behaviour, steering them towards more favourable environments. While the molecular components are well characterised, the motor behaviour measured by tethered cell experiments has been difficult to interpret.

Results

We study the effects of sensing and signalling noise on the motor behaviour. Specifically, we consider fluctuations stemming from ligand concentration, receptor switching between their signalling states, adaptation, modification of proteins by phosphorylation, and motor switching between its two rotational states. We develop a model which includes all signalling steps in the pathway, and discuss a simplified version, which captures the essential features of the full model. We find that the noise characteristics of the motor contain signatures from all these processes, albeit with varying magnitudes.

Conclusions

Our analysis allows us to address how cell-to-cell variation affects motor behaviour and the question of optimal pathway design. A similar comprehensive analysis can be applied to other two-component signalling pathways.

Action at a distance: amino acid substitutions that affect binding of the phosphorylated CheY response regulator and catalysis of dephosphorylation can be far from the CheZ phosphatase active site

Two-component regulatory systems, in which phosphorylation controls the activity of a response regulator protein, provide signal transduction in bacteria. For example, the phosphorylated CheY response regulator (CheYp) controls swimming behavior. In Escherichia coli, the chemotaxis phosphatase CheZ stimulates the dephosphorylation of CheYp. CheYp apparently binds first to the C terminus of CheZ and then binds to the active site where dephosphorylation occurs. The phosphatase activity of the CheZ(2) dimer exhibits a positively cooperative dependence on CheYp concentration, apparently because the binding of the first CheYp to CheZ(2) is inhibited compared to the binding of the second CheYp. Thus, CheZ phosphatase activity is reduced at low CheYp concentrations. The CheZ21IT gain-of-function substitution, located far from either the CheZ active site or C-terminal CheY binding site, enhances CheYp binding and abolishes cooperativity. To further explore mechanisms regulating CheZ activity, we isolated 10 intragenic suppressor mutations of cheZ21IT that restored chemotaxis. The suppressor substitutions were located along the central portion of CheZ and were not allele specific. Five suppressor mutants tested biochemically diminished the binding of CheYp and/or the catalysis of dephosphorylation, even when the suppressor substitutions were distant from the active site. One suppressor mutant also restored cooperativity to CheZ21IT. Consideration of results from this and previous studies suggests that the binding of CheYp to the CheZ active site (not to the C terminus) is rate limiting and leads to cooperative phosphatase activity. Furthermore, amino acid substitutions distant from the active site can affect CheZ catalytic activity and CheYp binding, perhaps via the propagation of structural or dynamic perturbations through a helical bundle.

Protein footprinting in a complex milieu: identifying the interaction surfaces of the chemotaxis adaptor protein CheW

Characterizing protein-protein interactions in a biologically relevant context is important for understanding the mechanisms of signal transduction. Most signal transduction systems are membrane associated and consist of large multiprotein complexes that undergo rapid reorganization--circumstances that present challenges to traditional structure determination methods. To study protein-protein interactions in a biologically relevant complex milieu, we employed a protein footprinting strategy based on isotope-coded affinity tag (ICAT) reagents. ICAT reagents are valuable tools for proteomics. Here, we show their utility in an alternative application--they are ideal for protein footprinting in complex backgrounds because the affinity tag moiety allows for enrichment of alkylated species prior to analysis. We employed a water-soluble ICAT reagent to monitor cysteine accessibility and thereby to identify residues involved in two different protein-protein interactions in the Escherichia coli chemotaxis signaling system. The chemotaxis system is an archetypal transmembrane signaling pathway in which a complex protein superstructure underlies sophisticated sensory performance. The formation of this superstructure depends on the adaptor protein CheW, which mediates a functionally important bridging interaction between transmembrane receptors and histidine kinase. ICAT footprinting was used to map the surfaces of CheW that interact with the large multidomain histidine kinase CheA, as well as with the transmembrane chemoreceptor Tsr in native E. coli membranes. By leveraging the affinity tag, we successfully identified CheW surfaces responsible for CheA-Tsr interaction. The proximity of the CheA and Tsr binding sites on CheW suggests the formation of a composite CheW-Tsr surface for the recruitment of the signaling kinase to the chemoreceptor complex.

Identification of an anchor residue for CheA-CheY interactions in the chemotaxis system of Escherichia coli

Transfer of a phosphoryl group from autophosphorylated CheA (P-CheA) to CheY is an important step in the bacterial chemotaxis signal transduction pathway. This reaction involves CheY (i) binding to the P2 domain of P-CheA and then (ii) acquiring the phosphoryl group from the P1 domain. Crystal structures indicated numerous side chain interactions at the CheY-P2 binding interface. To investigate the individual contributions of the P2 side chains involved in these contacts, we analyzed the effects of eight alanine substitution mutations on CheA-CheY binding interactions. An F214A substitution in P2 caused ∼1,000-fold reduction in CheA-CheY binding affinity, while Ala substitutions at other P2 positions had small effects (E171A, E178A, and I216A) or no detectable effects (H181A, D202A, D207A, and C213A) on binding affinity. These results are discussed in relation to previous in silico predictions of hot-spot and anchor positions at the CheA-CheY interface. We also investigated the consequences of these mutations for chemotaxis signal transduction in living cells. CheA(F214A) was defective in mediating localization of CheY-YFP to the large clusters of signaling proteins that form at the poles of Escherichia coli cells, while the other CheA variants did not differ from wild-type (wt) CheA (CheA(wt)) in this regard. In our set of mutants, only CheA(F214A) exhibited a markedly diminished ability to support chemotaxis in motility agar assays. Surprisingly, however, in FRET assays that monitored receptor-regulated production of phospho-CheY, CheA(F214A) (and each of the other Ala substitution mutants) performed just as well as CheA(wt). Overall, our findings indicate that F214 serves as an anchor residue at the CheA-CheY interface and makes an important contribution to the binding energy in vitro and in vivo; however, loss of this contribution does not have a large negative effect on the overall ability of the signaling pathway to modulate P-CheY levels in response to chemoattractants.

Core unit of chemotaxis signaling complexes

Bacterial chemoreceptors, histidine kinase CheA, and coupling protein CheW form clusters of chemotaxis signaling complexes. In signaling complexes kinase activity is enhanced several hundredfold and placed under receptor control. Activation is necessary to poise enzyme activity such that receptor control has physiologically relevant effects. Thus kinase activation can be considered the underlying core activity of signaling complexes. We defined the minimal physical unit that generates this activity using chemoreceptor Tar from Escherichia coli rendered water soluble by insertion into nanodiscs to (i) measure saturable binding of CheA and CheW to the smallest kinase-activating groups of receptor dimers and (ii) purify and characterize core units of signaling complexes. Purified complexes activated kinase almost as well as signaling complexes formed on arrays of receptors in isolated native membrane. Purified complexes contained two receptor trimers of dimers and two CheW for each CheA dimer, consistent with the approximately 1:1 CheACheW ratio determined by binding measurements. The 2:2:1 stoichiometry implied that CheA dimers, the enzymatically active form, connect two chemoreceptor trimers of dimers by interaction of one CheA protomer and a CheW with each trimer, an organization for which specific molecular interactions have previously been identified. The core unit associates six receptor dimers with a CheA dimer, providing sufficient capacity to account for much of the cooperativity and interdimer influence observed experimentally. We conclude that the 221 organization is the core structural and functional unit of chemotaxis signaling complexes and postulate that hexagonal arrays characteristic of signaling complexes are built from this unit.