Noise characteristics of the Escherichia coli rotary motor

The role of disorder in the motion of chiral active particles in the presence of obstacles

The presence of obstacles is intuitively expected to hinder the diffusive transport of active particles. However, for chiral active particles, a low density of obstacles near a surface can enhance their diffusive behavior. Here, we study numerically the role that disorder plays in determining the transport dynamics of chiral active particles on surfaces with obstacles. We consider different densities of regularly spaced obstacles and distinct types of disorder: noise in the dynamics of the particle, quenched noise in the positions of the obstacles as well as obstacle size polydispersity. We show that, depending on the type and strength of the disorder, the presence of obstacles can either enhance or hinder transport, and discuss implications for the control of active transport in disordered media.

State of the art of bacterial chemotaxis

Bacterial chemotaxis is a biased movement of bacteria toward the beneficial chemical gradient or away from a toxic chemical gradient. This movement is achieved by sensing a chemical gradient by chemoreceptors. In most of the chemotaxis studies, Escherichia coli has been used as a model organism. E. coli have about 4-6 flagella on their surfaces, and the motility is achieved by rotating the flagella. Each flagellum has reversible flagellar motors at its base, which rotate the flagella in counterclockwise and clockwise directions to achieve "run" and "tumble." The chemotaxis of bacteria is regulated by a network of interacting proteins. The sensory signal is processed and transmitted to the flagellar motor by cytoplasmic proteins. Bacterial chemotaxis plays an important role in many biological processes such as biofilm formation, quorum sensing, bacterial pathogenesis, and host infection. Bacterial chemotaxis can be applied for bioremediation, horizontal gene transfer, drug delivery, or maybe some other industry in near future. This review contains an overview of bacterial chemotaxis, recent findings of the physiological importance of bacterial chemotaxis in other biological processes, and the application of bacterial chemotaxis.

Maximal information transmission is compatible with ultrasensitive biological pathways

Cells are often considered input-output devices that maximize the transmission of information by converting extracellular stimuli (input) via signaling pathways (communication channel) to cell behavior (output). However, in biological systems outputs might feed back into inputs due to cell motility, and the biological channel can change by mutations during evolution. Here, we show that the conventional channel capacity obtained by optimizing the input distribution for a fixed channel may not reflect the global optimum. In a new approach we analytically identify both input distributions and input-output curves that optimally transmit information, given constraints from noise and the dynamic range of the channel. We find a universal optimal input distribution only depending on the input noise, and we generalize our formalism to multiple outputs (or inputs). Applying our formalism to Escherichia coli chemotaxis, we find that its pathway is compatible with optimal information transmission despite the ultrasensitive rotary motors.

Multiple sources of slow activity fluctuations in a bacterial chemosensory network

Cellular networks are intrinsically subject to stochastic fluctuations, but analysis of the resulting noise remained largely limited to gene expression. The pathway controlling chemotaxis of Escherichia coli provides one example where posttranslational signaling noise has been deduced from cellular behavior. This noise was proposed to result from stochasticity in chemoreceptor methylation, and it is believed to enhance environment exploration by bacteria. Here we combined single-cell FRET measurements with analysis based on the fluctuation-dissipation theorem (FDT) to characterize origins of activity fluctuations within the chemotaxis pathway. We observed surprisingly large methylation-independent thermal fluctuations of receptor activity, which contribute to noise comparably to the energy-consuming methylation dynamics. Interactions between clustered receptors involved in amplification of chemotactic signals are also necessary to produce the observed large activity fluctuations. Our work thus shows that the high response sensitivity of this cellular pathway also increases its susceptibility to noise, from thermal and out-of-equilibrium processes.

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.

Predicting chemical environments of bacteria from receptor signaling

Sensory systems have evolved to respond to input stimuli of certain statistical properties, and to reliably transmit this information through biochemical pathways. Hence, for an experimentally well-characterized sensory system, one ought to be able to extract valuable information about the statistics of the stimuli. Based on dose-response curves from in vivo fluorescence resonance energy transfer (FRET) experiments of the bacterial chemotaxis sensory system, we predict the chemical gradients chemotactic Escherichia coli cells typically encounter in their natural environment. To predict average gradients cells experience, we revaluate the phenomenological Weber's law and its generalizations to the Weber-Fechner law and fold-change detection. To obtain full distributions of gradients we use information theory and simulations, considering limitations of information transmission from both cell-external and internal noise. We identify broad distributions of exponential gradients, which lead to log-normal stimuli and maximal drift velocity. Our results thus provide a first step towards deciphering the chemical nature of complex, experimentally inaccessible cellular microenvironments, such as the human intestine.

Outside the laboratory, bacteria live in complex microenvironments characterized by competition for space and available nutrients. Although often inaccessible by experiments, understanding the spatio-temporal dynamics of bacterial microenvironments is biomedically important. For instance, the chemical environment that symbiotic Escherichia coli encounter in the human gut relates to health of the gastrointestinal tract, gut metabolism, immune response, and tissue homeostasis. Other complex microenvironments include soil and biofilms. Assuming that bacterial sensory systems have evolved to optimally sense typical gradients, we treat signaling data, the signaling pathway with its architecture and reaction rates, and computer simulations of swimming bacteria in different gradients as “prior knowledge” to “reverse engineer” E. coli's habitat. Our identified gradients are exponentially shaped with wide-ranging rate values. These microenvironments most likely stem from local fluctuating nutrient sources and degradation by competing species, in which bacteria have evolved to swim with optimal performance.

Pursuit of food versus pursuit of information in a Markovian perception-action loop model of foraging

Efficient coding, redundancy reduction, and other information theoretic optimization principles have successfully explained the organization of many biological phenomena, from the physiology of sensory receptive fields to the variability of certain DNA sequence ensembles. Here we examine the hypothesis that behavioral strategies that are optimal for survival must necessarily involve efficient information processing, and ask whether there can be circumstances in which deliberately sacrificing some information can lead to higher utility? To this end, we present an analytically tractable model for a particular instance of a perception-action loop: a creature searching for a randomly moving food source confined to a 1D ring world. The model incorporates the statistical structure of the creature's world, the effects of the creature's actions on that structure, and the creature's strategic decision process. The underlying model takes the form of a Markov process on an infinite dimensional state space. To analyze it we construct an exact coarse graining that reduces the model to a Markov process on a finite number of "information states". This mathematical technique allows us to make quantitative comparisons between the performance of an information-theoretically optimal strategy with other candidate search strategies on a food gathering task. We find that 1. Information optimal search does not necessarily optimize utility (expected food gain). 2. The rank ordering of search strategies by information performance does not predict their ordering by expected food obtained. 3. The relative advantage of different strategies depends on the statistical structure of the environment, in particular the variability of motion of the source. We conclude that there is no simple relationship between information and utility. Even in the absence of information processing costs or bandwidth constraints, behavioral optimality does not imply information efficiency, nor is there a simple tradeoff between the two objectives of gaining information about a food source versus obtaining the food itself. For a wide range of values of the food source's movement parameter, the strategy of collecting the most information possible about the unknown source location carries an ineliminable structural cost, leading to a situation in which a foraging creature could actually choose to be less well-informed while simultaneously being, on average, better fed.

Noninvasive inference of the molecular chemotactic response using bacterial trajectories

The quality of sensing and response to external stimuli constitutes a basic element in the selective performance of living organisms. Here we consider the response of Escherichia coli to chemical stimuli. For moderate amplitudes, the bacterial response to generic profiles of sensed chemicals is reconstructed from its response function to an impulse, which then controls the efficiency of bacterial motility. We introduce a method for measuring the impulse response function based on coupling microfluidic experiments and inference methods: The response function is inferred using Bayesian methods from the observed trajectories of bacteria swimming in microfluidically controlled chemical fields. The notable advantages are that the method is based on the bacterial swimming response, it is noninvasive, without any genetic and/or mechanical preparation, and assays the behavior of the whole flagella bundle. We exploit the inference method to measure responses to aspartate and α-methylaspartate--measured previously by other methods--as well as glucose, leucine, and serine. The response to the attractant glucose is shown to be biphasic and perfectly adapted, as for aspartate. The response to the attractant serine is shown to be biphasic yet imperfectly adapted, that is, the response function has a nonzero (positive) integral. The adaptation of the response to the repellent leucine is also imperfect, with the sign of the two phases inverted with respect to serine. The diversity in the bacterial population of the response function and its dependency upon the background concentration are quantified.