Nanoscale organization and dynamics of the siglec CD22 cooperate with the cytoskeleton in restraining BCR signalling.

Receptor organization and dynamics at the cell membrane are important factors of signal transduction regulation. Using super-resolution microscopy and single-particle tracking, we show how the negative coreceptor CD22 works with the cortical cytoskeleton in restraining BCR signalling. In naïve B cells, we found endogenous CD22 to be highly mobile and organized into nanodomains. The landscape of CD22 and its lateral diffusion were perturbed either in the absence of CD45 or when the CD22 lectin domain was mutated. To understand how a relatively low number of CD22 molecules can keep BCR signalling in check, we generated Brownian dynamic simulations and supported them with ex vivo experiments. This combined approach suggests that the inhibitory function of CD22 is influenced by its nanoscale organization and is ensured by its fast diffusion enabling a "global BCR surveillance" at the plasma membrane.

The Normative Orientations of Climate Scientists.

In 1942 Robert K. Merton tried to demonstrate the structure of the normative system of science by specifying the norms that characterized it. The norms were assigned the abbreviation CUDOs: Communism, Universalism, Disinterestedness, and Organized skepticism. Using the results of an on-line survey of climate scientists concerning the norms of science, this paper explores the climate scientists' subscription to these norms. The data suggests that while Merton's CUDOs remain the overall guiding moral principles, they are not fully endorsed or present in the conduct of climate scientists: there is a tendency to withhold results until publication, there is the intention of maintaining property rights, there is external influence defining research and the tendency to assign the significance of authored work according to the status of the author rather than content of the paper. These are contrary to the norms of science as proposed by Robert K. Merton.

Limits of computational biology.

Are we close to a complete inventory of living processes so that we might expect in the near future to reproduce every essential aspect necessary for life? Or are there mechanisms and processes in cells and organisms that are presently inaccessible to us? Here I argue that a close examination of a particularly well-understood system--that of Escherichia coli chemotaxis--shows we are still a long way from a complete description. There is a level of molecular uncertainty, particularly that responsible for fine-tuning and adaptation to myriad external conditions, which we presently cannot resolve or reproduce on a computer. Moreover, the same uncertainty exists for any process in any organism and is especially pronounced and important in higher animals such as humans. Embryonic development, tissue homeostasis, immune recognition, memory formation, and survival in the real world, all depend on vast numbers of subtle variations in cell chemistry most of which are presently unknown or only poorly characterized. Overcoming these limitations will require us to not only accumulate large quantities of highly detailed data but also develop new computational methods able to recapitulate the massively parallel processing of living cells.

The cell as a thermostat: how much does it know?

How does bacterial thermotaxis compare to a simple wall thermostat? Elements with similar function can be found in the two, including a temperature-sensing element, an output switch, and an external control. But they differ in their origins. A thermostat is designed and made by humans and embodies their understanding of seasonal fluctuations in temperature and how these affect room comfort. By contrast, the bacterial system is self-contained and assembles according to information in its genome acquired by evolution. This information is far richer than anything carried by a thermostat and closer to the 'knowledge' that higher animals have about the world.

The chemotactic behavior of computer-based surrogate bacteria.

BACKGROUND: Chemotaxis is the process by which organisms migrate toward nutrients and favorable environments and away from toxins and unfavorable environments. In many species of bacteria, this occurs when extracellular signals are detected by transmembrane receptors and relayed to flagellar motors, which control the cell's swimming behavior. RESULTS: We used a molecularly detailed reaction-kinetics model of the chemotaxis pathway in Escherichia coli coupled to a graphical display based on known swimming parameters to simulate the responses of bacteria to 2D gradients of attractants. The program gives the correct phenotype of over 60 mutants in which chemotaxis-pathway components are deleted or overexpressed and accurately reproduces the responses to pulses and step increases of attractant. In order to match the known sensitivity of bacteria to low concentrations of attractant, we had to introduce a set of "infectivity" reactions based on cooperative interactions between neighboring chemotaxis receptors in the membrane. In order to match the impulse response to a brief stimulus and to achieve an effective accumulation in a gradient, we also had to increase the activities of the adaptational enzymes CheR and CheB at least an order of magnitude greater than published values. Our simulations reveal that cells develop characteristic levels of receptor methylation and swimming behavior at different positions along a gradient. They also predict a distinctive "volcano" profile in some gradients, with peaks of cell density at intermediate concentrations of attractant. CONCLUSIONS: Our results display the potential use of computer-based bacteria as experimental objects for exploring subtleties of chemotactic behavior.

A spatially extended stochastic model of the bacterial chemotaxis signalling pathway.

We have combined two distinct but related stochastic approaches to model the Escherichia coli chemotaxis pathway. Reactions involving cytosolic components of the pathway were assumed to obey the laws of conventional stochastic chemical kinetics, while the clustered membrane receptors were represented in two-dimensional arrays similar to the Ising model. Receptors were assumed to flip between an active and an inactive state with probabilities dependent upon three energy inputs: ligand binding, methylation level due to adaptation, and the activity of neighbouring receptors. Examination of models with different lattice size and geometry showed that the sensitivity to stimuli increases with lattice size and the nearest-neighbour coupling strength up to a critical point, but this amplification was also accompanied by a proportional increase in steady-state noise. Multiple methylation of receptors resulted in diminished signal-to-noise ratio, but showed improved stability to variation in the coupling strength and increased gain. Under the best conditions the simulated output of a coupled lattice of receptors closely matched the time-course and amplitude found experimentally in living bacteria. The model also has some of the properties of a cellular automaton and shows an unexpected emergence of spatial patterns of methylation within the receptor lattice.

Modelling the bacterial chemotaxis receptor complex.

The pathway controlling chemotaxis in Escherichia coli is the simplest and most well understood cell signalling system to date. However, quantitative models based on the available data still fail to reproduce important features of the pathway. Most notably, the observed sensitivity of cells to very small changes in stimulus concentrations cannot be reproduced by conventional models based on the measured concentrations, binding affinities and rate constants of the proteins involved. This discrepancy, together with recent experimental findings, drew our attention to the spatial organization of molecules within the cell and in particular to the clusters of receptors localised at the cell poles. A stochastic simulator for chemical reactions, STOCHSIM, was previously developed to model the chemotaxis pathway at the level of individual molecular interactions. This program has now been extended to incorporate a spatial representation that allows the interaction between molecules in a two-dimensional lattice to be simulated. In silico 'experiments' using this new version of STOCHSIM demonstrate that lateral interactions between clustered receptors can significantly enhance the excitation response. The adaptation reactions may also exploit the proximity of receptor molecules, and a hypothetical mechanism by which this may occur is currently being tested.

Intrinsic activity in cells and the brain.

Motile cells such as bacteria, amoebae, and fibroblasts display a continual level of energy-consuming reactions involving the cytoskeleton and signal pathways, regardless of whether or not they are actually migrating. I draw parallels between these "silent signals" and the intrinsic activity of the human brain, especially that associated with the brain stem. In both cases, it can be argued that the organism continually rehearses possible future actions, so it can act quickly and accurately when suitable cues are received from the environment.

The propagation of allosteric states in large multiprotein complexes.

A statistical view of allostery leads to a more nuanced and physically realistic picture of protein cooperativity. If the conformational state of one protein molecule in a multiprotein complex influences the probability of a particular conformation in a neighbouring protein, then changes can propagate. Given suitable parameters, linear or two-dimensional arrays of allosteric subunits will then behave similar to an Ising model, exhibiting hypersharp responses to external conditions. Predictions based on this concept find good quantitative agreement in a number of experimental systems including switching of the bacterial flagellar motor, amplification of ligand signals in the Escherichia coli chemotaxis receptors, and termination of calcium sparks in cardiac muscle. A similar mechanism could potentially provide a universal mechanism of integration within living cells.

Swimming patterns and dynamics of simulated Escherichia coli bacteria.

A spatially and temporally realistic simulation of Escherichia coli chemotaxis was used to investigate the swimming patterns of wild-type and mutant bacteria within a rectangular arena in response to chemoattractant gradients. Swimming dynamics were analysed during long time series with phase-space trajectories, power spectra and estimations of fractal dimensions (FDs). Cell movement displayed complex trajectories in the phase space owing to interaction of multiple attractors that captured runs and tumbles. Deletion of enzymes responsible for adaptation (CheR and CheB) restricted the pattern of bacterial swimming in the absence of a gradient. In the presence of a gradient, there was a strong increase in trajectories arising from runs and attenuation of those arising from tumbles. Similar dynamics were observed for mutants lacking CheY, which are unable to tumble. The deletion of CheR, CheB and CheY also caused significant shifts in chemotaxis spectral frequencies. Rescaled range analysis and estimation of FD suggest that wild-type bacteria display characteristics of fractional Brownian motion with positive correlation between past and future events. These results reveal an underlying order in bacterial swimming dynamics, which enables a chemotactic search strategy conforming to a fractal walk.

Signal amplification in a lattice of coupled protein kinases.

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

How the "melting" and "freezing" of protein molecules may be used in cell signaling.

The motile response of Escherichia coli bacteria to attractants and repellents is one of the best-understood examples of a signal transduction pathway. A number of recent studies suggest that the receptors in this system undergo major changes in both their degree of structural order and their state of aggregation in the membrane. We discuss the thermodynamic basis for this effect and argue that the "freezing" or "melting" of protein structure may be the language of signaling.

Balls and chains--a mesoscopic approach to tethered protein domains.

Many proteins contain regions of unstructured polypeptide chain that appear to be flexible and to undergo random thermal motion. In some cases the unfolded sequence acts as a flexible tether that restricts the diffusion of a globular protein domain for the purpose of catalysis or self-assembly. In this article, we present a stochastic model for tethered protein domains under various conditions and solve it numerically to deduce the general and dynamic properties of these systems. A critical domain size dependent on the length of the tether is presented, above which a spherical domain tethered to an impenetrable wall by a flexible chain displays a restricted localization between two concentric half-shells. Results suggest that the diffusion of such a spherical domain is effectively reduced in its dimensionality and able to explore the available space with high efficiency. It also becomes clear that the orientation of the ball is not independent of the distance from the tethering point but becomes more constrained as the linking tether is extended. The possible biological significance of these and other results is discussed.

Flexible peptides and cytoplasmic gels.

Recent progress in predicting protein structures has revealed a surprising abundance of proteins that are significantly unfolded under physiological conditions. Unstructured, flexible polypeptides are likely to be functionally important and may cause local cytoplasmic regions to become gel-like.

Simulated diffusion of phosphorylated CheY through the cytoplasm of Escherichia coli.

We describe the use of a computational model to study the effects of cellular architecture and macromolecular crowding on signal transduction in Escherichia coli chemotaxis. A newly developed program, Smoldyn, allows the movement and interaction of a large number of individual molecules in a structured environment to be simulated (S. S. Andrews and D. Bray, Phys. Biol., in press). With Smoldyn, we constructed a three-dimensional model of an E. coli cell and examined the diffusion of CheYp from the cluster of receptors to the flagellar motors under control conditions and in response to attractant and repellent stimuli. Our simulations agree well with experimental observations of cell swimming responses and are consistent with the diffusive behavior expected in wild-type and mutant cells. The high resolution available to us in the new program allows us to calculate the loci of individual CheYp molecules in a cell and the distribution of their lifetimes under different cellular conditions. We find that the time delay between stimulus and response differs for flagellar motors located at different positions in the cell. We explore different possible locations for the phosphatase CheZ and show conditions under which a gradient of CheYp exists in the cell. The introduction of inert blocks into the cytoplasm, representing impenetrable structures such as the nucleoid and large protein complexes, produces a fall in the apparent diffusion coefficient of CheYp and enhances the differences between motors. These and other results are left as predictions for future experiments.

Molecular networks: the top-down view.

Network theory can give a useful overview of how a biological system works. But to make testable predictions, we need the details.

Conformational spread: the propagation of allosteric states in large multiprotein complexes.

The phenomenon of allostery is conventionally described for small symmetrical oligomeric proteins such as hemoglobin. Here we review experimental evidence from a variety of systems-including bacterial chemotaxis receptors, muscle ryanodine receptors, and actin filaments-showing that conformational changes can also propagate through extended lattices of protein molecules. We explore the statistical mechanics of idealized linear and two-dimensional arrays of allosteric proteins and show that, as in the analogous Ising models, arrays of closely packed units can show large-scale integrated behavior. We also discuss proteins that undergo conformational changes driven by the hydrolysis of ATP and give examples in which these changes propagate through linear chains of molecules. We suggest that conformational spread could provide the basis of a solid-state "circuitry" in a living cell, able to integrate biochemical and biophysical events over hundreds of protein molecules.