Chemotactic bacteria such as Escherichia coli can detect and respond to extremely low concentrations of attractants, concentrations of less than 5 nM in the case of aspartate. They also sense gradients of attractants extending over five orders of magnitude in concentration (up to 1 mM aspartate). Here we consider the possibility that this combination of sensitivity and range of response depends on the clustering of chemotactic receptors on the surface of the bacterium. We examine what will happen if ligand binding changes the activity of a receptor, propagating this change in activity to neighbouring receptors in a cluster. Calculations based on these assumptions show that sensitivity to extracellular ligands increases with the extent of spread of activity through an array of receptors, but that the range of concentrations over which the array works is severely diminished. However, a combination of low threshold of response and wide dynamic range can be attained if the cell has both clusters and single receptors on its surface, particularly if the extent of activity spread can adapt to external conditions. A mechanism of this kind can account quantitatively for the sensitivity and response range of E. coli to aspartate.

Coliform bacteria detect chemical attractants by means of a membrane-associated cluster of receptors and signalling molecules. We have used recently determined molecular structures, in conjunction with plastic models generated by three-dimensional printer technology, to predict how the proteins of the complex are arranged in relation to the plasma membrane. The proposed structure is a regular two-dimensional lattice in which the cytoplasmic ends of chemotactic-receptor dimers are inserted into a hexagonal array of CheA and CheW molecules. This structure creates separate compartments for adaptation and downstream signalling, and indicates a possible basis for the spread of activity within the cluster.

Our results display the potential use of computer-based bacteria as experimental objects for exploring subtleties of chemotactic behavior.

Cells in a cloned population of coliform bacteria exhibit a wide range of swimming behaviors--a form of non-genetic individuality. We used computer models to examine the proposition that these variations are due to differences in the number of chemotaxis signaling molecules from one cell to the next. Simulations were run in which the concentrations of seven gene products in the chemotaxis pathway were changed either deterministically or stochastically, with the changes derived from independent normal distributions. Computer models with two adaptation mechanisms were compared with experimental results from observations on individuals drawn from genetically identical populations. The range of swimming behavior predicted for cells with a standard deviation of protein copy number per cell of 10% of the mean was found to match closely the experimental range of the wild-type population. We also make predictions for the swimming behaviors of mutant strains lacking the adaptational mechanism that can be tested experimentally.

Adaptation of the attractant response in Escherichia coli is attributable to the methylation of its transmembrane chemotactic receptors by the methyltransferase CheR. This protein contains two binding domains, one for the sites of methylation themselves and the other for a flexible tether at the C terminus of the receptor. We have explored the theoretical consequences of this binding geometry for a CheR molecule associated with a cluster of chemotactic receptors. Calculations show that the CheR molecule will bind with high net affinity to the receptor lattice, having a high probability of being attached by one or both of its domains at any instant of time. Because of the relatively low affinity of its individual domains and the close proximity of neighboring receptors, it is likely that when one domain unbinds it will reattach to the array before the other domain unbinds. Stochastic simulations show that the enzyme will move through the receptor cluster in a hand-over-hand fashion, like a gibbon swinging through the branches of a tree. We explore the possible consequences of this motion, which we term "molecular brachiation", for chemotactic adaptation and suggest that a similar mechanism may be operative in other large assemblies of protein molecules.

CheZ catalyzes the dephosphorylation of the response regulator CheY in the two-component regulatory system that mediates chemotaxis in Escherichia coli. CheZ is a homodimer with two active sites for dephosphorylation. To gain insight into cellular mechanisms for the precise regulation of intracellular phosphorylated CheY (CheYp) levels, we evaluated the kinetic properties of CheZ. The steady state rate of CheZ-mediated dephosphorylation of CheYp displayed marked sigmoidicity with respect to CheYp concentration and a k cat of 4.9 s ؊1 . In contrast, the gain of function mutant CheZ-I21T with an amino acid substitution far from the active site gave hyperbolic kinetics and required far lower CheYp for half-saturation but had a similar k cat value as the wild type enzyme. Stopped flow fluorescence measurements demonstrated a 6-fold faster CheZ/CheYp association rate for CheZ-I21T (k assoc ‫؍‬ 3. 4 In the two-component regulatory system that mediates chemotaxis in Escherichia coli, the cell continuously regulates the level of phosphorylation of the response regulator CheY in response to an external chemical gradient (1-4). Intracellular levels of phosphorylated CheY (CheYp) 4 in turn directly dictate cell swimming behavior. CheYp binds to the base of the flagellum, thereby changing the direction of flagellar rotation from counterclockwise (causing a forward run) to clockwise (causing a reorienting tumble). Because cells switch rapidly between these two swimming behaviors as they sample their environment (5, 6), it is essential that both phosphorylation and dephosphorylation of CheY occur on a rapid time scale so that the concentration of CheYp at any instant accurately reflects current environmental conditions. Moreover, the highly cooperative relationship between intracellular CheYp concentration and the probability of clockwise rotation (7) underscores the necessity of precise regulation of CheYp levels. CheY is phosphorylated on Asp-57 by its cognate sensor kinase CheA at a rate that is dictated by the rate of autophosphorylation of CheA with ATP, which in turn is a function of the activity state of coupled transmembrane receptors. CheYp is dephosphorylated by the phosphatase CheZ. The ability to perform chemotaxis is very sensitive to intracellular CheZ activity as either a modest increase or decrease of CheZ activity disables chemotaxis (8 -12). Much of the cellular pool of CheZ is associated with the large polar signaling complex (13-15), which also contains receptors, CheA, and the scaffolding protein, CheW. Colocalization of CheZ with the CheA kinase implies some futile cycling of CheY but ensures a uniform concentration of CheYp across the length of the cell (15-17). CheZ is unrelated by amino acid sequence to other known classes of protein phosphatases and has a unique catalytic mechanism based on the introduction of additional catalytic elements into the CheYp active site for CheYp autodephosphorylation activity. CheZ is a homodimer with two CheYp binding sites, each binding site being composed of two ind...

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

A deterministic computer model of the signal transduction pathway mediating bacterial chemotaxis was used to examine the variation in both unstimulated swimming behaviour and adaptation time to stimuli in clonal populations of cells. Copy numbers of proteins in the pathway were computed from a simpli¢ed model of transcription and translation that predicts greater-than-Poissonian statistics. Simulated and experimental individuality data could be brought into good agreement on varying the noise strength of the protein copy number distributions. In the simulations, all the proteins in the pathway are involved to a signi¢cant degree in the appearance of phenotypic diversity, although there is a modest decrease in in£uence with increasing copy number. ß