Kinetic basis for the stimulatory effect of phosphorylation on the methylesterase activity of CheB

Evidence for Pentapeptide-Dependent and Independent CheB Methylesterases

Many bacteria possess multiple chemosensory pathways that are composed of homologous signaling proteins. These pathways appear to be functionally insulated from each other, but little information is available on the corresponding molecular basis. We report here a novel mechanism that contributes to pathway insulation. We show that, of the four CheB paralogs of Pseudomonas aeruginosa PAO1, only CheB₂ recognizes a pentapeptide at the C-terminal extension of the McpB (Aer2) chemoreceptor (K_D = 93 µM). McpB is the sole chemoreceptor that stimulates the Che2 pathway, and CheB₂ is the methylesterase of this pathway. Pectobacterium atrosepticum SCRI1043 has a single CheB, CheB_Pec, and 19 of its 36 chemoreceptors contain a C-terminal pentapeptide. The deletion of cheB_Pec abolished chemotaxis, but, surprisingly, none of the pentapeptides bound to CheB_Pec. To determine the corresponding structural basis, we solved the 3D structure of CheB_Pec. Its structure aligned well with that of the pentapeptide-dependent enzyme from Salmonella enterica. However, no electron density was observed in the CheB_Pec region corresponding to the pentapeptide-binding site in the Escherichia coli CheB. We hypothesize that this structural disorder is associated with the failure to bind pentapeptides. Combined data show that CheB methylesterases can be divided into pentapeptide-dependent and independent enzymes.

Phenotypic diversity and temporal variability in a bacterial signaling network revealed by single-cell FRET

We present in vivo single-cell FRET measurements in the Escherichia coli chemotaxis system that reveal pervasive signaling variability, both across cells in isogenic populations and within individual cells over time. We quantify cell-to-cell variability of adaptation, ligand response, as well as steady-state output level, and analyze the role of network design in shaping this diversity from gene expression noise. In the absence of changes in gene expression, we find that single cells demonstrate strong temporal fluctuations. We provide evidence that such signaling noise can arise from at least two sources: (i) stochastic activities of adaptation enzymes, and (ii) receptor-kinase dynamics in the absence of adaptation. We demonstrate that under certain conditions, (ii) can generate giant fluctuations that drive signaling activity of the entire cell into a stochastic two-state switching regime. Our findings underscore the importance of molecular noise, arising not only in gene expression but also in protein networks.

Many sophisticated computer programs use random number generators to help solve challenging problems. These problems range from achieving secure communication across the Internet to deciding how best to invest in the stock market. Much research in recent years has found that randomness is also widespread in living cells, where it is often called “noise”. For example, the activity of some genes is so unpredictable to the extent that it appears random. Yet, relatively little is known about how such gene-expression noise propagates up to change how the cell behaves. Many open questions also remain about how cells might exploit these or other fluctuations to achieve complex tasks, like people use random number generators.

Bacteria perform a number of complex tasks. Some bacteria will swim toward chemicals that suggest a potential reward, such as food. Yet they swim away from chemicals that could lead them to harm. This ability is called chemotaxis and it relies on a network of interacting enzymes and other proteins that coordinates a bacterium’s movements with the input from its senses.

Keegstra et al. set out to find sources of noise that might act as random number generators and help the bacterium E. coli to best perform chemotaxis. An improved version of a technique called in vivo Förster resonance energy transfer (or in vivo FRET for short) was used to give a detectable signal when two proteins involved in the chemotaxis network interacted inside a single bacterium. The experiments showed that this protein network amplifies gene-expression noise for some genes while lessening it for others. In addition, the interactions between proteins encoded by genes acted as an extra source of noise, even when gene-expression noise was eliminated.

Keegstra et al. found that the amount of signaling within the chemotaxis network, as measured by in vivo FRET, varied wildly over time. This revealed two sources of noise at the level of protein signaling. One was due to randomness in the activity of the enzymes involved in tuning the cell’s sensitivity to changes in its environment. The other was due to protein interactions within a large complex that acts as the cell’s sensor. Unexpectedly, this second source of noise under some conditions could be so strong that it flipped the output of the cell’s signaling network back and forth between just two states: “on” and “off”.

Together these findings uncover how signaling networks can not only amplify or lessen gene-expression noise, but can themselves become a source of random events. The new knowledge of how such random events interact with a complex trait in a living cell – namely chemotaxis – could aid future antimicrobial strategies, because many bacteria use chemotaxis to help them establish infections. More generally, the new insights about noise in protein networks could help engineers seeking to build synthetic biochemical networks or produce useful compounds in living cells.

Internal sense of direction: sensing and signaling from cytoplasmic chemoreceptors

SUMMARY

Chemoreceptors sense environmental signals and drive chemotactic responses in Bacteria and Archaea. There are two main classes of chemoreceptors: integral inner membrane and soluble cytoplasmic proteins. The latter were identified more recently than integral membrane chemoreceptors and have been studied much less thoroughly. These cytoplasmic chemoreceptors are the subject of this review. Our analysis determined that 14% of bacterial and 43% of archaeal chemoreceptors are cytoplasmic, based on currently sequenced genomes. Cytoplasmic chemoreceptors appear to share the same key structural features as integral membrane chemoreceptors, including the formations of homodimers, trimers of dimers, and 12-nm hexagonal arrays within the cell. Cytoplasmic chemoreceptors exhibit varied subcellular locations, with some localizing to the poles and others appearing both cytoplasmic and polar. Some cytoplasmic chemoreceptors adopt more exotic locations, including the formations of exclusively internal clusters or moving dynamic clusters that coalesce at points of contact with other cells. Cytoplasmic chemoreceptors presumably sense signals within the cytoplasm and bear diverse signal input domains that are mostly N terminal to the domain that defines chemoreceptors, the so-called MA domain. Similar to the case for transmembrane receptors, our analysis suggests that the most common signal input domain is the PAS (Per-Arnt-Sim) domain, but a variety of other N-terminal domains exist. It is also common, however, for cytoplasmic chemoreceptors to have C-terminal domains that may function for signal input. The most common of these is the recently identified chemoreceptor zinc binding (CZB) domain, found in 8% of all cytoplasmic chemoreceptors. The widespread nature and diverse signal input domains suggest that these chemoreceptors can monitor a variety of cytoplasmically based signals, most of which remain to be determined.

Nutrient-sensing mechanisms across evolution

For organisms to coordinate their growth and development with nutrient availability, they must be able to sense nutrient levels in their environment. Here, we review select nutrient-sensing mechanisms in a few diverse organisms. We discuss how these mechanisms reflect the nutrient requirements of specific species and how they have adapted to the emergence of multicellularity in eukaryotes.

Pseudomonas chemotaxis

Pseudomonads sense changes in the concentration of chemicals in their environment and exhibit a behavioral response mediated by flagella or pili coupled with a chemosensory system. The two known chemotaxis pathways, a flagella-mediated pathway and a putative pili-mediated system, are described in this review. Pseudomonas shows chemotaxis response toward a wide range of chemicals, and this review includes a summary of them organized by chemical structure. The assays used to measure positive and negative chemotaxis swimming and twitching Pseudomonas as well as improvements to those assays and new assays are also described. This review demonstrates that there is ample research and intellectual space for future investigators to elucidate the role of chemotaxis in important processes such as pathogenesis, bioremediation, and the bioprotection of plants and animals.

Beyond gene expression: the impact of protein post-translational modifications in bacteria

The post-translational modification (PTM) of proteins plays a critical role in the regulation of a broad range of cellular processes in eukaryotes. Yet their role in governing similar systems in the conventionally presumed 'simpler' forms of life has been largely neglected and, until recently, was thought to occur only rarely, with some modifications assumed to be limited to higher organisms alone. Recent developments in mass spectrometry-based proteomics have provided an unparalleled power to enrich, identify and quantify peptides with PTMs. Additional modifications to biological molecules such as lipids and carbohydrates that are essential for bacterial pathophysiology have only recently been detected on proteins. Here we review bacterial protein PTMs, focusing on phosphorylation, acetylation, proteolytic degradation, methylation and lipidation and the roles they play in bacterial adaptation - thus highlighting the importance of proteomic techniques in a field that is only just in its infancy. This article is part of a Special Issue entitled: Trends in Microbial Proteomics.

In Rhodobacter sphaeroides, chemotactic operon 1 regulates rotation of the flagellar system 2

Rhodobacter sphaeroides is able to assemble two different flagella, the subpolar flagellum (Fla1) and the polar flagella (Fla2). In this work, we report the swimming behavior of R. sphaeroides Fla2(+) cells lacking each of the proteins encoded by chemotactic operon 1. A model proposing how these proteins control Fla2 rotation is presented.

Kinetics of ATP and TNP-ATP binding to the active site of CheA from Thermotoga maritima

The mechanism of nucleotide binding to the active site of Thermotoga maritima CheA was investigated using stopped-flow fluorescence experiments that monitored binding of ATP and TNP-ATP to the catalytic domain (P4) of CheA that had been engineered to include a tryptophan residue as a fluorescent reporter group at the active site (P4(F487W)). Rapid decreases in protein intrinsic fluorescence and increases in TNP-ATP fluorescence were observed during binding reactions, and time courses were analyzed to define the kinetic mechanisms for ATP and TNP-ATP binding. This analysis indicated that binding of ATP(Mg(2+)) to P4(F487W) involves a single reversible step with a k(on) of 0.92 +/- 0.09 microM(-1) s(-1), a k(off) of 1.9 +/- 0.4 s(-1), and a K(d) of 1.5-2.1 microM (all values determined at 4 degrees C). Binding of TNP-ATP(Mg(2+)) to P4(F487W) involves a more complicated mechanism, requiring at least three sequential steps. Computer simulations and nonlinear regression analysis were used to estimate the rate constants of the forward and reverse reactions for each of the three steps in the reaction scheme [Formula: see text] Similar analysis indicated that an alternative reaction scheme, involving a rate-limiting conformational change in P4 prior to TNP-ATP binding, did an equally good job of accounting for all of the kinetics results:[Formula: see text] In both models, steps 2 and 3 have slow reversal rates that contribute to the high affinity of the active site for TNP-ATP (K(d) = 0.015 microM). These results highlight the dramatic effect of the TNP moieties on CheA-nucleotide interactions, and they provide the first detailed information about the kinetic mechanism underlying interaction of a protein histidine kinase with this tight-binding inhibitor.

Dynamic map of protein interactions in the Escherichia coli chemotaxis pathway

Protein-protein interactions play key roles in virtually all cellular processes, often forming complex regulatory networks. A powerful tool to study interactions in vivo is fluorescence resonance energy transfer (FRET), which is based on the distance-dependent energy transfer from an excited donor to an acceptor fluorophore. Here, we used FRET to systematically map all protein interactions in the chemotaxis signaling pathway in Escherichia coli, one of the most studied models of signal transduction, and to determine stimulation-induced changes in the pathway. Our FRET analysis identified 19 positive FRET pairs out of the 28 possible protein combinations, with 9 pairs being responsive to chemotactic stimulation. Six stimulation-dependent and five stimulation-independent interactions were direct, whereas other interactions were apparently mediated by scaffolding proteins. Characterization of stimulation-induced responses revealed an additional regulation through activity dependence of interactions involving the adaptation enzyme CheB, and showed complex rearrangement of chemosensory receptors. Our study illustrates how FRET can be efficiently employed to study dynamic protein networks in vivo.

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.

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.

Robustness analysis of the E.coli chemosensory system to perturbations in chemoattractant concentrations

MOTIVATION

Cells of Escherichia coli sense and move toward chemical attractants. This is done through an intricate sensory system that eventually directs the movements of flagellae which regulate the 'runs' and 'tumbles' of the cells. Under realistic conditions, chemical stimuli often fluctuate due to noise from the environment. The effect of noise on the chemosensory system has been investigated here through the sensitivity coefficients of the concentrations of four key proteins--the phosphorylated forms of CheA, CheB and CheY, and the FliM-CheY-P complex--that govern chemotactic motility. The letter P denotes phosphorylation.

RESULTS

All sensitivities increased with time and then stabilized. However, the four sets of sensitivities differed in their magnitudes and the durations of their transient phases before stabilization. CheA-P was the least sensitive and CheY-P the most sensitive. Moreover, while the sensitivities of CheA-P, CheB-P and CheY-P increased with chemoattractant concentration, that of the FliM complex decreased. These differences have been interpreted in terms of the mechanism of the chemosensory system and they have important implications for practical applications of chemotaxis.

Identification of sensory and signal-transducing domains in two-component signaling systems

The availability of complete genome sequences of diverse bacteria and archaea makes comparative sequence analysis a powerful tool for analyzing signal transduction systems encoded in these genomes. However, most signal transduction proteins consist of two or more individual protein domains, which significantly complicates their functional annotation and makes automated annotation of these proteins in the course of large-scale genome sequencing projects particularly unreliable. This chapter describes certain common-sense protocols for sequence analysis of two-component histidine kinases and response regulators, as well as other components of the prokaryotic signal transduction machinery: Ser/Thr/Tyr protein kinases and protein phosphatases, adenylate and diguanylate cyclases, and c-di-GMP phosphodiesterases. These protocols rely on publicly available computational tools and databases and can be utilized by anyone with Internet access.

Characterization of the Thermotoga maritima chemotaxis methylation system that lacks pentapeptide-dependent methyltransferase CheR:MCP tethering

Sensory adaptation in bacterial chemotaxis is mediated by covalent modifications of specific glutamate and glutamine residues within the cytoplasmic domains of methyl-accepting chemotaxis proteins (MCPs). In Escherichia coli and Salmonella enterica, efficient methylation of MCPs depends on the localization of methyltransferase CheR to MCP clusters through an interaction between the CheR beta-subdomain and a pentapeptide sequence (NWETF or NWESF) at the C-terminus of the MCP. In vitro methylation analyses utilizing S. enterica and Thermotoga maritima CheR proteins and MCPs indicate that MCP methylation in T. maritima occurs independently of a pentapeptide-binding motif. Kinetic and binding measurements demonstrate that despite efficient methylation, the interaction between T. maritima CheR and T. maritima MCPs is of relatively low affinity. Comparative protein sequence analyses of CheR beta-subdomains from organisms having MCPs that contain and/or lack pentapeptide-binding motifs identified key similarities and differences in residue conservation, suggesting the existence of two distinct classes of CheR proteins: pentapeptide-dependent and pentapeptide-independent methyltransferases. Analysis of MCP C-terminal ends showed that only approximately 10% of MCPs contain a putative C-terminal binding motif, the majority of which are restricted to the different proteobacteria classes (alpha, beta, gamma, delta). These findings suggest that tethering of CheR to MCPs is a relatively recent event in evolution and that the pentapeptide-independent methylation system is more common than the well-characterized pentapeptide-dependent methylation system.

Identification of methylation sites in Thermotoga maritima chemotaxis receptors

Adaptation in bacterial chemotaxis involves reversible methylation of specific glutamate residues within the cytoplasmic domains of methyl-accepting chemotaxis proteins. The specific sites of methylation in Salmonella enterica and Escherichia coli chemoreceptors, identified 2 decades ago, established a consensus sequence for methylation by methyltransferase CheR. Here we report the in vitro methylation of chemoreceptors from Thermotoga maritima, a hyperthermophile that has served as a useful source of chemotaxis proteins for structural analysis. Sites of methylation have been identified by liquid chromatography-mass spectrometry/mass spectrometry. Fifteen sites of methylation were identified within the cytoplasmic domains of four different T. maritima chemoreceptors. The results establish a consensus sequence for chemoreceptor methylation sites in T. maritima that is distinct from the previously identified consensus sequence for E. coli and S. enterica. These findings suggest that consensus sequences for posttranslational modifications in one organism may not be directly extrapolated to analogous modifications in other bacteria.

Structural classification of bacterial response regulators: diversity of output domains and domain combinations

CheY-like phosphoacceptor (or receiver [REC]) domain is a common module in a variety of response regulators of the bacterial signal transduction systems. In this work, 4,610 response regulators, encoded in complete genomes of 200 bacterial and archaeal species, were identified and classified by their domain architectures. Previously uncharacterized output domains were analyzed and, in some cases, assigned to known domain families. Transcriptional regulators of the OmpR, NarL, and NtrC families were found to comprise almost 60% of all response regulators; transcriptional regulators with other DNA-binding domains (LytTR, AraC, Spo0A, Fis, YcbB, RpoE, and MerR) account for an additional 6%. The remaining one-third is represented by the stand-alone REC domain (approximately 14%) and its combinations with a variety of enzymatic (GGDEF, EAL, HD-GYP, CheB, CheC, PP2C, and HisK), RNA-binding (ANTAR and CsrA), protein- or ligand-binding (PAS, GAF, TPR, CAP_ED, and HPt) domains, or newly described domains of unknown function. The diversity of domain architectures and the abundance of alternative domain combinations suggest that fusions between the REC domain and various output domains is a widespread evolutionary mechanism that allows bacterial cells to regulate transcription, enzyme activity, and/or protein-protein interactions in response to environmental challenges. The complete list of response regulators encoded in each of the 200 analyzed genomes is available online at http://www.ncbi.nlm.nih.gov/Complete_Genomes/RRcensus.html.

Active site identification through geometry-based and sequence profile-based calculations: burial of catalytic clefts

Electrostatics calculations with proteins that are uniformly charged over volume can aid enzyme/non-enzyme discrimination. For known enzymes, such methods locate active sites to within 5% on the enzyme surface, in 77% of a test set. We now report that removing the dielectric boundary improves active site location to 80%, with optimal discrimination between enzymes and non-enzymes of around 80% specificity and 80% sensitivity. This calculation quantifies burial of solvent-accessible regions. Many of the true enzymes incorrectly assigned as non-enzymes have active sites at subunit boundaries. These are missed in monomer-based calculations. Catalytic and non-catalytic antibodies are studied in this context of active/binding site burial. Whilst catalytic antibodies, on average, have marginally higher active site burial than non-catalytic antibodies, these values are generally smaller than for non-antibody enzymes, possibly contributing to their relatively low turnover. Prediction of active site location improves further when sequence profile-based weights replace the uniform charge distribution, so that a combination of burial and amino acid conservation is assessed. Accuracy rises to 93% of active sites to within 5%, in the test set, for the optimal profile weights scheme. The equivalent value in a separate validation set is 89% to within 5%. Enzyme/non-enzyme and enzyme functional site predictions are made for structural genomics proteins, suggesting that a substantial majority of these are non-enzymes.

Making sense of it all: bacterial chemotaxis

Bacteria must be able to respond to a changing environment, and one way to respond is to move. The transduction of sensory signals alters the concentration of small phosphorylated response regulators that bind to the rotary flagellar motor and cause switching. This simple pathway has provided a paradigm for sensory systems in general. However, the increasing number of sequenced bacterial genomes shows that although the central sensory mechanism seems to be common to all bacteria, there is added complexity in a wide range of species.

Targeting of the chemotaxis methylesterase/deamidase CheB to the polar receptor-kinase cluster in an Escherichia coli cell

Chemotactic adaptation to persisting stimulation involves reversible methylation of the chemoreceptors that form complexes with the histidine kinase CheA at a cell pole. The methyltransferase CheR targets to the C-terminal NWETF sequence of the chemoreceptor. In contrast, localization of the methylesterase CheB is largely unknown, although regulation of its activity via phosphorylation is central to adaptation. In this study, green fluorescent protein was fused to full-length CheB or its various parts: the N-terminal regulatory domain (N), the C-terminal catalytic domain (C) and the linker (L). The full-length and NL fusions and, to a lesser extent, the LC fusion localized to a pole. Deletion of the P2 domain from CheA abolished polar localization of the full-length and NL fusions, but did not affect that of the LC fusion. Pull-down assays demonstrated that the NL fragment, but not the LC fragment, binds to the P2 fragment of CheA. These results indicate that binding of the NL domain to the P2 domain targets CheB to the polar signalling complex. The LC fusion, like the chemoreceptor, partially localized in the absence of CheA, suggesting that the LC domain may interact with its substrate sites, either as part of the protein or as a proteolytic fragment.

Design and diversity in bacterial chemotaxis: a comparative study in Escherichia coli and Bacillus subtilis

Comparable processes in different species often involve homologous genes. One question is whether the network structure, in particular the feedback control structure, is also conserved. The bacterial chemotaxis pathways in E. coli and B. subtilis both regulate the same task, namely, excitation and adaptation to environmental signals. Both pathways employ many orthologous genes. Yet how these orthologs contribute to network function in each organism is different. To investigate this problem, we propose what is to our knowledge the first computational model for B. subtilis chemotaxis and compare it to previously published models for chemotaxis in E. coli. The models reveal that the core control strategy for signal processing is the same in both organisms, though in B. subtilis there are two additional feedback loops that provide an additional layer of regulation and robustness. Furthermore, the network structures are different despite the similarity of the proteins in each organism. These results demonstrate the limitations of pathway inferences based solely on homology and suggest that the control strategy is an evolutionarily conserved property.

Computational modeling reveals some important differences in the networks that regulate chemotaxis in E. coli and B. subtilis, differences that are hard to predict on the basis of sequence homology alone

Allosteric enhancement of adaptational demethylation by a carboxyl-terminal sequence on chemoreceptors

Sensory adaptation in bacterial chemotaxis is mediated by covalent modification of chemoreceptors. Specific glutamyl residues are methylated and demethylated in reactions catalyzed by methyltransferase CheR and methylesterase CheB. In Escherichia coli and Salmonella enterica serovar typhimurium, efficient adaptational modification by either enzyme is dependent on a conserved pentapeptide sequence at the chemoreceptor carboxyl terminus, a position distant from the sites of modification. For CheR-catalyzed methylation, previous work demonstrated that this sequence acts as a high affinity docking site, enhancing methylation by increasing enzyme concentration near methyl-accepting glutamates. We investigated pentapeptide-mediated enhancement of CheB-catalyzed demethylation and found it occurred by a distinctly different mechanism. Assays of binding between CheB and the pentapeptide sequence showed that it was too weak to have a significant effect on local enzyme concentration. Kinetic analyses revealed that interaction of the sequence and the methylesterase enhanced the rate constant of demethylation not the Michaelis constant. This allosteric activation occurred if the sequence was attached to chemoreceptor, but hardly at all if it was present as an isolated peptide. In addition, free peptide inhibited demethylation of the native receptor carrying the pentapeptide sequence at its carboxyl terminus. These observations imply that the allosteric change is transmitted through the protein substrate, not the enzyme.