Modeling chemotaxis reveals the role of reversed phosphotransfer and a bi-functional kinase-phosphatase

Understanding how multiple signals are integrated in living cells to produce a balanced response is a major challenge in biology. Two-component signal transduction pathways, such as bacterial chemotaxis, comprise histidine protein kinases (HPKs) and response regulators (RRs). These are used to sense and respond to changes in the environment. Rhodobacter sphaeroides has a complex chemosensory network with two signaling clusters, each containing a HPK, CheA. Here we demonstrate, using a mathematical model, how the outputs of the two signaling clusters may be integrated. We use our mathematical model supported by experimental data to predict that: (1) the main RR controlling flagellar rotation, CheY6, aided by its specific phosphatase, the bifunctional kinase CheA3, acts as a phosphate sink for the other RRs; and (2) a phosphorelay pathway involving CheB2 connects the cytoplasmic cluster kinase CheA3 with the polar localised kinase CheA2, and allows CheA3-P to phosphorylate non-cognate chemotaxis RRs. These two mechanisms enable the bifunctional kinase/phosphatase activity of CheA3 to integrate and tune the sensory output of each signaling cluster to produce a balanced response. The signal integration mechanisms identified here may be widely used by other bacteria, since like R. sphaeroides, over 50% of chemotactic bacteria have multiple cheA homologues and need to integrate signals from different sources.

Spatiotemporal modelling of CheY complexes in Escherichia coli chemotaxis

The chemotaxis pathway of Escherichia coli is one of the best studied and modelled biological signalling pathways. Here we extend existing modelling approaches by explicitly including a description of the formation and subcellular localization of intermediary complexes in the phosphotransfer pathway. The inclusion of these complexes shows that only about 60% of the total output response regulator (CheY) is uncomplexed at any moment and hence free to interact with its target, the flagellar motor. A clear strength of this model is its ability to predict the experimentally observable subcellular localization of CheY throughout a chemotactic response. We have found good agreement between the model output and experimentally determined CheY localization patterns. (C) 2009 Elsevier Ltd. All rights reserved.

Overview of mathematical approaches used to model bacterial chemotaxis I: the single cell

Mathematical modeling of bacterial chemotaxis systems has been influential and insightful in helping to understand experimental observations. We provide here a comprehensive overview of the range of mathematical approaches used for modeling, within a single bacterium, chemotactic processes caused by changes to external gradients in its environment. Specific areas of the bacterial system which have been studied and modeled are discussed in detail, including the modeling of adaptation in response to attractant gradients, the intracellular phosphorylation cascade, membrane receptor clustering, and spatial modeling of intracellular protein signal transduction. The importance of producing robust models that address adaptation, gain, and sensitivity are also discussed. This review highlights that while mathematical modeling has aided in understanding bacterial chemotaxis on the individual cell scale and guiding experimental design, no single model succeeds in robustly describing all of the basic elements of the cell. We conclude by discussing the importance of this and the future of modeling in this area.

Overview of mathematical approaches used to model bacterial chemotaxis II: bacterial populations

We review the application of mathematical modeling to understanding the behavior of populations of chemotactic bacteria. The application of continuum mathematical models, in particular generalized Keller-Segel models, is discussed along with attempts to incorporate the microscale (individual) behavior on the macroscale, modeling the interaction between different species of bacteria, the interaction of bacteria with their environment, and methods used to obtain experimentally verified parameter values. We allude briefly to the role of modeling pattern formation in understanding collective behavior within bacterial populations. Various aspects of each model are discussed and areas for possible future research are postulated.

A chimeric N-terminal Escherichia coli C-terminal Rhodobacter sphaeroides FliG rotor protein supports bidirectional E coli flagellar rotation and chemotaxis

Flagellate bacteria such as Escherichia coli and Salmonella enterica serovar Typhimurium typically express 5 to 12 flagellar filaments over their cell surface that rotate in clockwise (CW) and counterclockwise directions. These bacteria modulate their swimming direction towards favorable environments by biasing the direction of flagellar rotation in response to various stimuli. In contrast, Rhodobacter sphaeroides expresses a single subpolar flagellum that rotates only CW and responds tactically by a series of biased stops and starts. Rotor protein FliG transiently links the MotAB stators to the rotor, to power rotation and also has an essential function in flagellar export. In this study, we sought to determine whether the FliG protein confers directionality on flagellar motors by testing the functional properties of R. sphaeroides FliG and a chimeric FliG protein, EcRsFliG (N-terminal and central domains of E. coli FliG fused to an R. sphaeroides FliG C terminus), in an E. coli FliG null background. The EcRsFliG chimera supported flagellar synthesis and bidirectional rotation; bacteria swam and tumbled in a manner qualitatively similar to that of the wild type and showed chemotaxis to amino acids. Thus, the FliG C terminus alone does not confer the unidirectional stop-start character of the R. sphaeroides flagellar motor, and its conformation continues to support tactic, switch-protein interactions in a bidirectional motor, despite its evolutionary history in a bacterium with a unidirectional motor.

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. WIREs Syst Biol Med 2012 doi: 10.1002/wsbm.1168 For further resources related to this article, please visit the WIREs website.

Response kinetics in the complex chemotaxis signalling pathway of Rhodobacter sphaeroides

Chemotaxis is one of the best characterised signalling systems in biology. It is the mechanism by which bacteria move towards optimal environments and is implicated in biofilm formation, pathogenesis and symbiosis. The properties of the bacterial chemosensory response have been described in detail for the single chemosensory pathway of Escherichia coli. We have characterised the properties of the chemosensory response of Rhodobacter sphaeroides, an -proteobacterium with multiple chemotaxis pathways, under two growth conditions allowing the effects of protein expression levels and cell architecture to be investigated. Using tethered cell assays we measured the responses of the system to step changes in concentration of the attractant propionate and show that, independently of the growth conditions, R. sphaeroides is chemotactic over at least five orders of magnitude and has a sensing profile following Weber’s law. Mathematical modelling also shows that, like E. coli, R. sphaeroides is capable of showing Fold-Change Detection (FCD). Our results indicate that general features of bacterial chemotaxis such as the range and sensitivity of detection, adaptation times, adherence to Weber’s law and the presence of FCD may be integral features of chemotaxis systems in general, regardless of network complexity, protein expression levels and cellular architecture across different species.

Fold-change detection in a whole-pathway model of Escherichia coli chemotaxis

There has been recent interest in sensory systems that are able to display a response which is proportional to a fold change in stimulus concentration, a feature referred to as fold-change detection (FCD). Here, we demonstrate FCD in a recent whole-pathway mathematical model of Escherichia coli chemotaxis. FCD is shown to hold for each protein in the signalling cascade and to be robust to kinetic rate and protein concentration variation. Using a sensitivity analysis, we find that only variations in the number of receptors within a signalling team lead to the model not exhibiting FCD. We also discuss the ability of a cell with multiple receptor types to display FCD and explain how a particular receptor configuration may be used to elucidate the two experimentally determined regimes of FCD behaviour. All findings are discussed in respect of the experimental literature.

Modelling the movement and survival of the root-feeding clover weevil, Sitona lepidus, in the root-zone of white clover

White clover (Trifolium repens) is an important pasture legume but is often difficult to sustain in a mixed sward because, among other things, of the damage to roots caused by the soil-dwelling larval stages of S. lepidus. Locating the root nodules on the white clover roots is crucial for the survival of the newly hatched larvae. This paper presents a numerical model to simulate the movement of newly hatched S. lepidus larvae towards the root nodules, guided by a chemical signal released by the nodules. The model is based on the diffusion-chemotaxis equation. Experimental observations showed that the average speed of the larvae remained approximately constant, so the diffusion-chernotaxis model was modified so that the larvae respond only to the gradient direction of the chemical signal but not its magnitude. An individual-based lattice Boltzmann method was used to simulate the movement of individual larvae, and the parameters required for the model were estimated from the measurement of larval movement towards nodules in soil scanned using X-ray microtomography. The model was used to investigate the effects of nodule density, the rate of release of chemical signal, the sensitivity of the larvae to the signal, and the random foraging of the larvae on the movement and subsequent survival of the larvae. The simulations showed that the most significant factors for larval survival were nodule density and the sensitivity of the larvae to the signal. The dependence of larval survival rate on nodule density was well fitted by the Michealis-Menten kinetics. (c) 2005 Elsevier B.V All rights reserved.

Modelling the movement and survival of the root-feeding clover weevil, Sitona lepidus, in the root-zone of white clover

White clover (Trifolium repens) is an important pasture legume but is often difficult to sustain in a mixed sward because, among other things, of the damage to roots caused by the soil-dwelling larval stages of S. lepidus. Locating the root nodules on the white clover roots is crucial for the survival of the newly hatched larvae. This paper presents a numerical model to simulate the movement of newly hatched S. lepidus larvae towards the root nodules, guided by a chemical signal released by the nodules. The model is based on the diffusion-chemotaxis equation. Experimental observations showed that the average speed of the larvae remained approximately constant, so the diffusion-chernotaxis model was modified so that the larvae respond only to the gradient direction of the chemical signal but not its magnitude. An individual-based lattice Boltzmann method was used to simulate the movement of individual larvae, and the parameters required for the model were estimated from the measurement of larval movement towards nodules in soil scanned using X-ray microtomography. The model was used to investigate the effects of nodule density, the rate of release of chemical signal, the sensitivity of the larvae to the signal, and the random foraging of the larvae on the movement and subsequent survival of the larvae. The simulations showed that the most significant factors for larval survival were nodule density and the sensitivity of the larvae to the signal. The dependence of larval survival rate on nodule density was well fitted by the Michealis-Menten kinetics. (c) 2005 Elsevier B.V All rights reserved.

Sulfation of genistein alters its antioxidant properties and its effect on platelet aggregation and monocyte and endothelial function

Soy isoflavones have been extensively studied because of their possible benefits to human health. Genistein, the major isoflavone aglycone, has received most attention; however, it undergoes extensive metabolism (e.g. conjugation with sulfuric acid) in the gut and liver, which may affect its biological proper-ties. This study investigated the antioxidant activity and free radical-scavenging properties of genistein, genistein-4'-sulfate and genistein-4'-7-disulfate as well as their effect on platelet aggregation and monocyte and endothelial function. Electron spin resonance spectroscopy (ESR) and spin trapping data and other standard antioxidant assays indicated that genistein is a relatively weak antioxidant compared to quercetin and that its sulfated metabolites are even less effective. Furthermore, genistein-4'-sulfate was less potent than genistem, and genistein-4'-7-disulfate even less potent, at inhibiting collagen-induced platelet aggregation, nitric oxide (NO) production by macrophages, and secretion by primary human endothelial cells of monocyte chemoattractant protein 1 (MCP-1), intercellular adhesion molecule 1 (ICAM-1) and vascular cell adhesion molecule 1 (VCAM-1). The current data suggest that sulfation of genistein, with the associated loss of hydroxyl groups, decreases its antioxidant activity and its effect on platelet aggregation, inflammation, cell adhesion and chemotaxis. (C) 2004 Elsevier B.V All rights reserved.

Sulfation of genistein alters its antioxidant properties and its effect on platelet aggregation and monocyte and endothelial function

Soy isoflavones have been extensively studied because of their possible benefits to human health. Genistein, the major isoflavone aglycone, has received most attention; however, it undergoes extensive metabolism (e.g. conjugation with sulfuric acid) in the gut and liver, which may affect its biological proper-ties. This study investigated the antioxidant activity and free radical-scavenging properties of genistein, genistein-4'-sulfate and genistein-4'-7-disulfate as well as their effect on platelet aggregation and monocyte and endothelial function. Electron spin resonance spectroscopy (ESR) and spin trapping data and other standard antioxidant assays indicated that genistein is a relatively weak antioxidant compared to quercetin and that its sulfated metabolites are even less effective. Furthermore, genistein-4'-sulfate was less potent than genistem, and genistein-4'-7-disulfate even less potent, at inhibiting collagen-induced platelet aggregation, nitric oxide (NO) production by macrophages, and secretion by primary human endothelial cells of monocyte chemoattractant protein 1 (MCP-1), intercellular adhesion molecule 1 (ICAM-1) and vascular cell adhesion molecule 1 (VCAM-1). The current data suggest that sulfation of genistein, with the associated loss of hydroxyl groups, decreases its antioxidant activity and its effect on platelet aggregation, inflammation, cell adhesion and chemotaxis. (C) 2004 Elsevier B.V All rights reserved.

A practical approach for training dynamic recurrent neural networks: use of Apriori information

Presents a technique for incorporating a priori knowledge from a state space system into a neural network training algorithm. The training algorithm considered is that of chemotaxis and the networks being trained are recurrent neural networks. Incorporation of the a priori knowledge ensures that the resultant network has behaviour similar to the system which it is modelling.

The role of flagella, but not fimbriae, in the adherence of Salmonella enterica serotype Enteritidis to chick gut explant

To gain an understanding of the role of fimbriae and flagella in the adherence and colonisation of Salmonella enterica serotype Enteritidis in chickens, an in-vitro gut adherence assay was developed and used to assess the adherence of a wild-type Enteritidis strain and isogenic non-fimbriate and non-flagellate mutant strains. Enteritidis strain S1400/94, a clinical isolate virulent in chickens, was shown to possess genes which encoded type 1, SEF14, SEF17, plasmid-encoded and long polar fimbriae. Mutant strains unable to elaborate these fimbriae were created by allelic exchange. Each fimbrial operon was inactivated by the insertion of an antibiotic resistance gene cassette. In addition, fliC, motAB and cheA loci, which encode the major subunit of the flagellum, the energy-translation system for motility and one of the chemotaxis signalling proteins, respectively, were similarly inactivated. Non-flagellate mutant strains were significantly less adherent than the wild-type strain, whereas mutant strains defective for the elaboration of any of the types of fimbriae adhered as well as the wild-type strain. A flagellate but non-motile (paralysed) mutant strain and a smooth-swimming chemotaxis-deficient mutant strain were shown to be less adherent than the wild-type strain, but that observation depended on the assay conditions used.