Stochastic signal inputs for chemotactic response in Dictyostelium cells revealed by single molecule imaging techniques

Orientation of Cell Polarity by Chemical Gradients

Accurate decoding of spatial chemical landscapes is critical for many cell functions. Eukaryotic cells decode local chemical gradients to orient growth or movement in productive directions. Recent work on yeast model systems, whose gradient sensing pathways display much less complexity than those in animal cells, has suggested new paradigms for how these very small cells successfully exploit information in noisy and dynamic pheromone gradients to identify their mates. Pheromone receptors regulate a polarity circuit centered on the conserved Rho-family GTPase, Cdc42. The polarity circuit contains both positive and negative feedback pathways, allowing spontaneous symmetry breaking and also polarity site disassembly and relocation. Cdc42 orients the actin cytoskeleton, leading to focused vesicle traffic that promotes movement of the polarity site and also reshapes the cortical distribution of receptors at the cell surface. In this article, we review the advances from work on yeasts and compare them with the excitable signaling pathways that have been revealed in chemotactic animal cells. Expected final online publication date for the Annual Review of Biophysics, Volume 51 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Noisy signal propagation and amplification in phenotypic transition cascade of colonic cells

Like genes and proteins, cells can use biochemical networks to sense and process information. The differentiation of the cell state in colonic crypts forms a typical unidirectional phenotypic transitional cascade, in which stem cells differentiate into the transit-amplifying cells (TACs), and TACs continue to differentiate into fully differentiated cells. In order to quantitatively describe the relationship between the noise of each compartment and the amplification of signals, the gain factor is introduced, and the gain-fluctuation relation is obtained by using the linear noise approximation of the master equation. Through the simulation of these theoretical formulas, the characters of noise propagation and amplification are studied. It is found that the transmitted noise is an important part of the total noise in each downstream cell. Therefore, a small number of downstream cells can only cause its small inherent noise, but the total noise may be very large due to the transmitted noise. The influence of the transmitted noise may be the indirect cause of colon cancer. In addition, the total noise of the downstream cells always has a minimum value. As long as a reasonable value of the gain factor is selected, the number of cells in colonic crypts will be controlled within the normal range. This may be a good method to intervene the uncontrollable growth of tumor cells and effectively control the deterioration of colon cancer.

Robustness against additional noise in cellular information transmission

Fluctuations in intracellular reactions (intrinsic noise) reduce the information transmitted from an extracellular input to a cellular response. However, recent studies have demonstrated that the decrease in the transmitted information with respect to extracellular input fluctuations (extrinsic noise) is smaller when the intrinsic noise is larger. Therefore, it has been suggested that robustness against extrinsic noise increases with the level of the intrinsic noise. We call this phenomenon intrinsic noise-induced robustness (INIR). As previous studies on this phenomenon have focused on complex biochemical reactions, the relation between INIR and the input-output of a system is unclear. Moreover, the mechanism of INIR remains elusive. In this paper, we address these questions by analyzing simple models. We first analyze a model in which the input-output relation is linear. We show that the robustness against extrinsic noise increases with the intrinsic noise, confirming the INIR phenomenon. Moreover, the robustness against the extrinsic noise is more strongly dependent on the intrinsic noise when the variance of the intrinsic noise is larger than that of the input distribution. Next, we analyze a threshold model in which the output depends on whether the input exceeds the threshold. When the threshold is equal to the mean of the input, INIR is realized, but when the threshold is much larger than the mean, the threshold model exhibits stochastic resonance, and INIR is not always apparent. The robustness against extrinsic noise and the transmitted information can be traded off against one another in the linear model and the threshold model without stochastic resonance, whereas they can be simultaneously increased in the threshold model with stochastic resonance.

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.

Multi-State Transition Kinetics of Intracellular Signaling Molecules by Single-Molecule Imaging Analysis

The chemotactic signaling of eukaryotic cells is based on a chain of interactions between signaling molecules diffusing on the cell membrane and those shuttling between the membrane and cytoplasm. In this chapter, we describe methods to quantify lateral diffusion and reaction kinetics on the cell membrane. By the direct visualization and statistic analyses of molecular Brownian movement achieved by single-molecule imaging techniques, multiple states of membrane-bound molecules are successfully revealed with state transition kinetics. Using PTEN, a phosphatidylinositol-3,4,5-trisphosphate (PI(3,4,5)P3) 3'-phosphatase, in Dictyostelium discoideum undergoing chemotaxis as a model, each process of the analysis is described in detail. The identified multiple state kinetics provides an essential clue to elucidating the molecular mechanism of chemoattractant-induced dynamic redistribution of the signaling molecule asymmetrically on the cell membrane. Quantitative parameters for molecular reactions and diffusion complement a conventional view of the chemotactic signaling system, where changing a static network of molecules connected by causal relationships into a spatiotemporally dynamic one permits a mathematical description of stochastic migration of the cell along a shallow chemoattractant gradient.

Influences of excluded volume of molecules on signaling processes on the 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 monotonically increasing; increasing then decreasing in a bell-shaped curve; or 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.

Tracking shallow chemical gradients by actin-driven wandering of the polarization site

BACKGROUND

Many cells are remarkably proficient at tracking very shallow chemical gradients, despite considerable noise from stochastic receptor-ligand interactions. Motile cells appear to undergo a biased random walk: spatial noise in receptor activity may determine the instantaneous direction, but because noise is spatially unbiased, it is filtered out by time averaging, resulting in net movement upgradient. How nonmotile cells might filter out noise is unknown.

RESULTS

Using yeast chemotropic mating as a model, we demonstrate that a polarized patch of polarity regulators "wanders" along the cortex during gradient tracking. Computational and experimental findings suggest that actin-directed membrane traffic contributes to wandering by diluting local polarity factors. The pheromone gradient appears to bias wandering via interactions between receptor-activated Gβγ and polarity regulators. Artificially blocking patch wandering impairs gradient tracking.

CONCLUSIONS

We suggest that the polarity patch undergoes an intracellular biased random walk that enables noise filtering by time averaging, allowing nonmotile cells to track shallow gradients.

Lipid rafts generate digital-like signal transduction in cell plasma membranes

Lipid rafts are meso-scale (5-200 nm) cell membrane domains where signaling molecules assemble and function. However, due to their dynamic nature, it has been difficult to unravel the mechanism of signal transduction in lipid rafts. Recent advanced imaging techniques have revealed that signaling molecules are frequently, but transiently, recruited to rafts with the aid of protein-protein, protein-lipid, and/or lipid-lipid interactions. Individual signaling molecules within the raft are activated only for a short period of time. Immobilization of signaling molecules by cytoskeletal actin filaments and scaffold proteins may facilitate more efficient signal transmission from rafts. In this review, current opinions of how the transient nature of molecular interactions in rafts generates digital-like signal transduction in cell membranes, and the benefits this phenomenon provides, are discussed.

Single-molecule imaging of stochastic signaling events in living cells

Environmental changes result in signaling events at cell membranes. To develop the means to understand these events at the molecular level, it is essential to become familiar with the stochastic nature of signaling molecules in living cells. Using total internal reflection fluorescent microscopy (TIRFM), these signaling events can be directly observed at the single-molecule level. This article explains the basis of TIRFM and how it is set up. It then describes how to visualize cell membrane signaling events. It also explains how to prove that detected fluorescence is emitted from single dye molecules and how to analyze the data from TIRFM experiments.

SELECTIVITY IMPROVEMENT IN A MODEL OF OLFACTORY RECEPTOR NEURON WITH ADSORPTION-DESORPTION NOISE

In biological olfactory systems, interaction of odorant molecules with olfactory receptor proteins is driven by Brownian motion. As a result, at chemical equilibrium, the total number of bound receptors changes randomly in time. Here we investigate the role of this effect, known in physics as adsorption-desorption noise, in the discriminating ability of olfactory receptor neurons. For this purpose we developed a computer program, which generates the adsorption-desorption process in a model neuron. We compared the processes resulting from two different odorants with different affinities for the receptor proteins. We took into account the threshold at which spikes are triggered and we calculated the neuronal selectivity due to the differences in the threshold-crossing statistics for the processes resulting from both odorants. We conclude that selectivity of the spiking response of the whole neuron is much greater than that of its receptor proteins in the near-threshold range of odorant concentrations.

Hierarchical organization of noise generates spontaneous signal in Paramecium cell

In many cellular processes, spontaneous activities are often the basis for their functioning. Paramecium cells change their swimming direction under a homogeneous environment, which is induced by a spontaneous signal generation in the membrane electric potential. For such a spontaneous activity, a theoretical model has been proposed by Oosawa (2007) [Biosystems 88, 191-201.], in which intracellular noise is hierarchically organized from thermal fluctuations to spike-like large fluctuations, which induces a signal to change spontaneously the swimming direction. Our analysis of the model shows that the system is a kind of excitable media, in which a spike is induced by a stochastic fluctuation. We show conditions of channels properties to have a spike train.

Single-molecule imaging techniques to visualize chemotactic signaling events on the membrane of living Dictyostelium cells

In this chapter, we describe methods to monitor signaling events at the single-molecule level on the membrane of living cells by using total internal reflection fluorescence microscopy (TIRFM). The techniques provide a powerful tool for elucidating the stochastic properties of signaling molecules involved in chemotaxis of the cellular slime mold Dictyostelium discoideum. Taking cAMP receptor 1 (cAR1) as an example of a target protein for single-molecule imaging, we describe the experimental setup of TIRFM, a method for labeling cAR1 with a fluorescent dye, and a method for investigating the receptor's lateral mobility. We discuss how the developmental progression of cells modulates both cAR1 behavior and the phenotypic variability in cAR1 mobility for different cell populations.

3'-phosphoinositides regulate the coordination of speed and accuracy during chemotaxis

The PI3K/PTEN pathway, as the regulator of 3'-phosphoinositide (3'-PI) dynamics, has emerged as a key regulator of chemoattractant gradient sensing during chemotaxis in Dictyostelium and other cell types. Previous results have shown 3'-PIs to be important for regulating basal cell motility and sensing the direction and strength of the chemoattractant gradient. We examined the chemotaxis of wild-type cells and cells lacking PTEN or PI3K1 and 2 using analytical methods that allowed us to quantitatively discern differences between the genotype's ability to sense and efficiently respond to changes in gradient steepness during chemotaxis. We found that cells are capable of increasing their chemotactic accuracy and speed as they approach a micropipette in a manner that is dependent on the increasing strength of the concentration gradient and 3'-PI signaling. Further, our data show that 3'-PI signaling affects a cell's ability to coordinate speed and direction to increase chemotactic efficiency. Using to our knowledge a new measurement of chemotactic efficiency that reveals the degree of coordination between speed and accuracy, we found that cells also have the capacity to increase their chemotactic efficiency as they approach the micropipette. Like directional accuracy and speed, the increase in chemotactic efficiency of cells with increased gradient strength is sensitive to 3'-PI dysregulation. Our evidence suggests that receptor-driven 3'-PI signaling regulates the ability of a cell to capitalize on stronger directional inputs and minimize the effects of inaccurate turns to increase chemotactic efficiency.

Noise generation, amplification and propagation in chemotactic signaling systems of living cells

Theoretical considerations of stochastic signal transduction in living cells have revealed the gain-fluctuation relation, which provides a theoretical framework to describe quantitatively how noise is generated, amplified and propagated along a signaling cascade in living cells. We chose the chemotactic signaling of bacteria and eukaryotic cells as a typical example of noisy signal transduction and applied the gain-fluctuation relation to these signaling systems in order to analyze the effects of noise on signal transduction. Comparing our theoretical analysis with the experimental results of chemotaxis in bacteria Escherichia coli and eukaryote Dictyostelium discoideum revealed that noise in signal transduction systems limits the cells' chemotactic ability and contributes to their behavioral variability. Based on the kinetic properties of signaling molecules in living cells, the gain-fluctuation relation can quantitatively explain stochastic cellular behaviors.

Chemotaxis: navigating by multiple signaling pathways

During chemotaxis, phosphatidylinositol 3,4,5-trisphosphate (PIP(3)) accumulates at the leading edge of a eukaryotic cell, where it induces the formation of pseudopodia. PIP(3) has been suggested to be the compass of cells navigating in gradients of signaling molecules. Recent observations suggest that chemotaxis is more complex than previously anticipated. Complete inhibition of all PIP(3) signaling has little effect, and alternative pathways have been identified. In addition, selective pseudopod growth and retraction are more important in directing cell movement than is the place where new pseudopodia are formed.

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.

For many cell types, the direction of migration is determined in response to spatial differences in the concentration of chemoattractant, a process known as chemotaxis. Precise chemotaxis—that is, motility with low directional distortion—requires that cells make accurate decisions based on the stochastic fluctuations inherent in cell-surface receptor occupancy. Here, we use rate distortion theory, a branch of information theory, to determine chemotaxis strategies for cells based on this imperfect information about their environment. In engineering, rate distortion theory provides the information processing capabilities required to achieve a desired accuracy. We demonstrate that more accurate chemotaxis requires greater information. We also show that a priori information can improve chemotaxis efficiency. We compare the optimal signaling schemes to existing experimental measurements and models of eukaryotic gradient sensing and demonstrate that different observed types of cellular responses (polarized and unpolarized) are optimal under varying information assumptions. Our results also highlight the constraints that noise places on the performance of cellular systems.