Chemoattractant receptors activate, recruit and capture G proteins for wide range chemotaxis

The wide range sensing of extracellular signals is a common feature of various sensory cells. Eukaryotic chemotactic cells driven by GPCRs and their cognate G proteins are one example. This system endows the cells directional motility towards their destination over long distances. There are several mechanisms to achieve the long dynamic range, including negative regulation of the receptors upon ligand interaction and spatial regulation of G proteins, as we found recently. However, these mechanisms are insufficient to explain the 105-fold range of chemotaxis seen in Dictyostelium. Here, we reveal that the receptor-mediated activation, recruitment, and capturing of G proteins mediate chemotactic signaling at the lower, middle and higher concentration ranges, respectively. These multiple mechanisms of G protein dynamics can successfully cover distinct ranges of ligand concentrations, resulting in seamless and broad chemotaxis. Furthermore, single-molecule imaging analysis showed that the activated Gα subunit forms an unconventional complex with the agonist-bound receptor. This complex formation of GPCR-Gα increased the membrane-binding time of individual Gα molecules and therefore resulted in the local accumulation of Gα. Our findings provide an additional chemotactic dynamic range mechanism in which multiple G protein dynamics positively contribute to the production of gradient information

An Information-Theoretic Characterization of the Optimal Gradient Sensing Response of Cells

Many cellular systems rely on the ability to interpret spatial heterogeneities in chemoattractant concentration to direct cell migration. The accuracy of this process is limited by stochastic fluctuations in the concentration of the external signal and in the internal signaling components. Here we use information theory to determine the optimal scheme to detect the location of an external chemoattractant source in the presence of noise. We compute the minimum amount of mutual information needed between the chemoattractant gradient and the internal signal to achieve a prespecified chemotactic accuracy. We show that more accurate chemotaxis requires greater mutual information. We also demonstrate that a priori information can improve chemotaxis efficiency. We compare the optimal signaling schemes with existing experimental measurements and models of eukaryotic gradient sensing. Remarkably, there is good quantitative agreement between the optimal response when no a priori assumption is made about the location of the existing source, and the observed experimental response of unpolarized Dictyostelium discoideum cells. In contrast, the measured response of polarized D. discoideum cells matches closely the optimal scheme, assuming prior knowledge of the external gradient—for example, through prolonged chemotaxis in a given direction. Our results demonstrate that different observed classes of responses in cells (polarized and unpolarized) are optimal under varying information assumptions

Influences of Excluded Volume of Molecules on Signaling Processes on Biomembrane

We investigate the influences of the excluded volume of molecules on biochemical reaction processes on 2-dimensional surfaces using a model of signal transduction processes on biomembranes. We perform simulations of the 2-dimensional cell-based model, which describes the reactions and diffusion of the receptors, signaling proteins, target proteins, and crowders on the cell membrane. The signaling proteins are activated by receptors, and these activated signaling proteins activate target proteins that bind autonomously from the cytoplasm to the membrane, and unbind from the membrane if activated. If the target proteins bind frequently, the volume fraction of molecules on the membrane becomes so large that the excluded volume of the molecules for the reaction and diffusion dynamics cannot be negligible. We find that such excluded volume effects of the molecules induce non-trivial variations of the signal flow, defined as the activation frequency of target proteins, as follows. With an increase in the binding rate of target proteins, the signal flow varies by i) monotonically increasing; ii) increasing then decreasing in a bell-shaped curve; or iii) increasing, decreasing, then increasing in an S-shaped curve. We further demonstrate that the excluded volume of molecules influences the hierarchical molecular distributions throughout the reaction processes. In particular, when the system exhibits a large signal flow, the signaling proteins tend to surround the receptors to form receptor-signaling protein clusters, and the target proteins tend to become distributed around such clusters. To explain these phenomena, we analyze the stochastic model of the local motions of molecules around the receptor.Comment: 31 pages, 10 figure

GPCR and G protein mobility in D. discoideum : a single molecule study

Chemotaxis, the process in which cells detect a concentration gradient of a specific substance, interpret that information, and subsequently initiate movement towards the source is an essential part of many biological phenomena. It___s central to the processes in wound healing, in immune defense and in the formation of a viable embryo. In this thesis I used the well characterized social amoeba Dictyostelium discoideum to investigate, in depth, the dynamics that govern the first steps in the detection of a chemical gradient. D. discoideum detects cyclic adenosine mono-phosphate (cAMP) by a special receptor protein, cAMP receptor 1 (cAR1). Inside the cell this receptor activates a G protein which subsequently initiates a complex signaling cascade. Using fluorescence single-molecule microscopy I investigated the movements of both cAR1 and its associated G protein. During chemotaxis both proteins show striking differences in mobility between the leading and trailing edge of the cell. Those differences are presumably key to our understanding of gradient sensing by cells that have been ignored in models so far.LEI Universiteit LeidenBiological and Molecular Physic

Noise filtering tradeoffs in spatial gradient sensing and cell polarization response

<p>Abstract</p> <p>Background</p> <p>Cells sense chemical spatial gradients and respond by polarizing internal components. This process can be disrupted by gradient noise caused by fluctuations in chemical concentration.</p> <p>Results</p> <p>We investigated how external gradient noise affects spatial sensing and response focusing on noise-filtering and the resultant tradeoffs. First, using a coarse-grained mathematical model of gradient-sensing and cell polarity, we characterized three negative consequences of noise: Inhibition of the extent of polarization, degradation of directional accuracy, and production of a noisy output polarization. Next, we explored filtering strategies and discovered that a combination of positive feedback, multiple signaling stages, and time-averaging produced good results. There was an important tradeoff, however, because filtering resulted in slower polarization. Simulations demonstrated that a two-stage filter-amplifier resulted in a balanced outcome. Then, we analyzed the effect of noise on a mechanistic model of yeast cell polarization in response to gradients of mating pheromone. This analysis showed that yeast cells likely also combine the above three filtering mechanisms into a filter-amplifier structure to achieve impressive spatial-noise tolerance, but with the consequence of a slow response time. Further investigation of the amplifier architecture revealed two positive feedback loops, a fast inner and a slow outer, both of which contributed to noise-tolerant polarization. This model also made specific predictions about how orientation performance depended upon the ratio between the gradient slope (signal) and the noise variance. To test these predictions, we performed microfluidics experiments measuring the ability of yeast cells to orient to shallow gradients of mating pheromone. The results of these experiments agreed well with the modeling predictions, demonstrating that yeast cells can sense gradients shallower than 0.1% μm^-1, approximately a single receptor-ligand molecule difference between front and back, on par with motile eukaryotic cells.</p> <p>Conclusions</p> <p>Spatial noise impedes the extent, accuracy, and smoothness of cell polarization. A combined filtering strategy implemented by a filter-amplifier architecture with slow dynamics was effective. Modeling and experimental data suggest that yeast cells employ these elaborate mechanisms to filter gradient noise resulting in a slow but relatively accurate polarization response.</p

Deciphering Intracellular Signaling Regulating Directed Cell Migration

Directed cell migration is a ubiquitous phenomenon with implications in development, wound healing, immunity, and metastasis. The ability of cells to orient their migration is dependent on the presence of external cues, the components to detect them and the intracellular networks to process them. This dissertation explores how the regulation of core intracellular components can shape directional migration responses and the mechanisms in which cells decode single and multiple external guidance cues. Given the complexity and redundancy in migratory signaling pathways, we develop a new technique to generate an intracellular gradient of protein activity without receptor activation. We demonstrate the utility of this technique by imposing gradients of different values of the active form of one of the core mediators of directed migration, a Rho GTPase, Rac. We find that shallow gradients of Rac alone are sufficient to direct the polarity and movement of cells, recapitulating phenotypes of chemoattractant induced migration and demonstrating synthetic chemotaxis in mammalian cells. These results reveal that cell polarity can be defined starting from a downstream node, Rac. Furthermore, we present a new refined mathematical model of cell chemotaxis and suggest a novel role for an upstream kinase, PI3K, in sensitizing cells to Rac activation. Next, we explore how cells process multiple guidance inputs, chemotaxis and contact inhibition of locomotion (CIL), and the resulting implications for directed cell migration. We find that chemotaxis and CIL do not act independently, as the resulting migration phenotypes when both cues are presented in conjunction are altered when they are presented individually. The balance between these cues is dynamic; modulating the strength of the cues through external inputs or molecular interventions can influence the resulting directed migration outcomes. We further investigate the mechanistic basis of this dependency by enumerating the molecular mediators of these cues and finding where they might crosstalk. In this study, we develop several new techniques at the interface between engineering and the life sciences and present their applications. We anticipate that similar multidisciplinary approaches will help unravel mysteries in directed cell migration and in general biology