Single-molecule analysis of chemotactic signaling in Dictyostelium cells

Recent Advancements in Imaging Techniques for Individual Extracellular Vesicles

Extracellular vesicles (EVs), secreted from most cells, are small lipid membranes of vesicles of 30 to 1000 nm in diameter and contain nucleic acids, proteins, and intracellular organelles originating from donor cells. EVs play pivotal roles in intercellular communication, particularly in forming niches for cancer cell metastasis. However, EVs derived from donor cells exhibit significant heterogeneity, complicating the investigation of EV subtypes using ensemble averaging methods. In this context, we highlight recent studies that characterize individual EVs using advanced techniques, including single-fluorescent-particle tracking, single-metal-nanoparticle tracking, single-non-label-particle tracking, super-resolution microscopy, and atomic force microscopy. These techniques have facilitated high-throughput analyses of the properties of individual EV particles such as their sizes, compositions, and physical properties. Finally, we address the challenges that need to be resolved via single-particle (-molecule) imaging and super-resolution microscopy in future research.

Gradient sensing limit of an elongated cell with orientational control

Eukaryotic cells perform chemotaxis by determining the direction of chemical gradients based on stochastic sensing of concentrations at the cell surface. To examine the efficiency of this process, previous studies have investigated the limit of estimation accuracy for gradients. However, most studies have treated a circular cell shape, and the few considering elongated shapes assume the elongated direction as fixed. This leaves the question of how adaptive regulation of cell shape affects the estimation limit. Dynamics of cell shape during gradient sensing is biologically ubiquitous and can influence the estimation by altering the way the concentration is measured, and cells may strategically regulate their shape to improve estimation accuracy. To address this gap, we investigate the estimation limits in dynamic situations where elongated cells change their orientation adaptively depending on the sensed signal. We approach this problem by analyzing the stationary solution of the Bayesian nonlinear filtering equation. By applying diffusion approximation to the ligand-receptor binding process and the Laplace method for the posterior expectation under a high signal-to-noise ratio regime, we obtain an analytical expression for the estimation limit. This expression indicates that estimation accuracy can be improved by aligning the elongated direction perpendicular to the estimated direction, which is also confirmed by numerical simulations. Our analysis provides a basis for clarifying the interplay between estimation and control in gradient sensing and sheds light on how cells optimize their shape to enhance chemotactic efficiency.

Single molecule tracking based drug screening

The single-molecule tracking of transmembrane receptors in living cells has provided significant insights into signaling mechanisms, such as mobility and clustering upon their activation/inactivation, making it a potential screening method for drug discovery. Here we show that single-molecule tracking-based screening can be used to explore compounds both detectable and undetectable by conventional methods for disease-related receptors. Using an automated system for a fast large-scale single-molecule analysis, we screen for epidermal growth factor receptor (EGFR) from 1134 of FDA approved drugs. The 18 hit compounds include all EGFR-targeted tyrosine kinase inhibitors (TKIs) in the library that suppress any phosphorylation-dependent mobility shift of EGFR, proving the concept of this approach. The remaining hit compounds are not reported as EGFR-targeted drugs and do not inhibit EGF-induced EGFR phosphorylation. These non-TKI compounds affect the mobility and/or clustering of EGFR without EGF and induce EGFR internalization, to impede EGFR-dependent cell growth. Thus, single-molecule tracking provides an alternative modality for discovering therapeutics on various receptor functions with previously untargeted mechanisms.

Single molecule dynamics in a virtual cell combining a 3-dimensional matrix model with random walks

Recent advances in light microscopy have enabled single molecules to be imaged and tracked within living cells and this approach is impacting our understanding of cell biology. Computer modeling and simulation are important adjuncts to the experimental cycle since they aid interpretation of experimental results and help refine, test and generate hypotheses. Object-oriented computer modeling is particularly well-suited for simulating random, thermal, movements of individual molecules as they interact with other molecules and subcellular structures, but current models are often limited to idealized systems consisting of unit volumes or planar surfaces. Here, a simulation tool is described that combines a 3-dimensional, voxelated, representation of the cell consisting of subcellular structures (e.g. nucleus, endoplasmic reticulum, cytoskeleton, vesicles, and filopodia) combined with numerical floating-point precision simulation of thousands of individual molecules moving and interacting within the 3-dimensional space. Simulations produce realistic time-series video sequences comprising single fluorophore intensities and realistic background noise which can be directly compared to experimental fluorescence video microscopy data sets.

Application of single-molecule analysis to singularity phenomenon of cells

Single-molecule imaging in living cells is an effective tool for elucidating the mechanisms of cellular phenomena at the molecular level. However, the analysis was not designed for throughput and requires high expertise, preventing it from reaching large scale, which is necessary when searching for rare cells that induce singularity phenomena. To overcome this limitation, we have automated the imaging procedures by combining our own focusing device, artificial intelligence, and robotics. The apparatus, called automated in-cell single-molecule imaging system (AiSIS), achieves a throughput that is a hundred-fold higher than conventional manual imaging operations, enabling the analysis of molecular events by individual cells across a large population. Here, using AiSIS, we demonstrate the single-molecule imaging of molecular behaviors and reactions related to tau protein aggregation, which is considered a singularity phenomenon in neurological disorders. Changes in the dynamics and kinetics of molecular events were observed inside and on the basal membrane of cells after the induction of aggregation. Additionally, to detect rare cells based on the molecular behavior, we developed a method to identify the state of individual cells defined by the quantitative distribution of molecular mobility and clustering. Using this method, cellular variations in receptor behavior were shown to decrease following ligand stimulation. This cell state analysis based on large-scale single-molecule imaging by AiSIS will advance the study of molecular mechanisms causing singularity phenomena.

Left-right Myosin-Is, Myosin1C, and Myosin1D exhibit distinct single molecule behaviors on the plasma membrane of Drosophila macrophages

Left-right (LR) asymmetry is crucial for animal development, particularly in Drosophila where LR-asymmetric morphogenesis of organs hinges on cellular-level chirality, termed cell chirality. In this species, two class I myosins, Myosin1D (Myo1D), and Myosin1C (Myo1C), respectively determine dextral (wild type) and sinistral (mirror image) cell chirality. Previous studies demonstrated Myo1D's ability to propel F-actin in leftward circles during in vitro gliding assays, suggesting its mechanochemical role in defining dextral chirality. Conversely, Myo1C propels F-actin without exhibiting LR-directional preference in this assay, suggesting at other properties governing sinistral chirality. Given the interaction of Myo1D and Myo1C with the membrane, we hypothesized that differences in their membrane behaviors might be critical in dictating their dextral or sinistral activities. In this study, employing single-molecule imaging analyses, we investigated the dynamic behaviors of Myo1D and Myo1C on the plasma membrane. Our findings revealed that Myo1C exhibits a significantly greater proportion of slow-diffusing population compared to Myo1D. Importantly, this characteristic was contingent upon both head and tail domains of Myo1C. The distinct diffusion patterns of Myo1D and Myo1C did not exert mutual influence on each other. This divergence in membrane diffusion between Myo1D and Myo1C may be crucial for dictating cell and organ chirality.

Field model for multistate lateral diffusion of various transmembrane proteins observed in living Dictyostelium cells

The lateral diffusion of transmembrane proteins on plasma membranes is a fundamental process for various cellular functions. Diffusion properties specific for individual protein species have been extensively studied, but the common features among protein species are poorly understood. Here, we systematically studied the lateral diffusion of various transmembrane proteins in the lower eukaryote Dictyostelium discoideum cells using a hidden Markov model for single-molecule trajectories obtained experimentally. As common features, all membrane proteins that had from one to ten transmembrane regions adopted three free diffusion states with similar diffusion coefficients regardless of their structural variability. All protein species reduced their mobility similarly upon the inhibition of microtubule or actin cytoskeleton dynamics, or myosin II. The relationship between protein size and the diffusion coefficient was consistent with the Saffman-Delbrück model, meaning that membrane viscosity is a major determinant of lateral diffusion, but protein size is not. These protein species-independent properties of multistate free diffusion were explained simply and quantitatively by free diffusion on the three membrane regions with different viscosities, which is in sharp contrast to the complex diffusion behavior of transmembrane proteins in higher eukaryotes.

Localization of signaling receptors maximizes cellular information acquisition in spatially structured natural environments

Cells in natural environments, such as tissue or soil, sense and respond to extracellular ligands with intricately structured and non-monotonic spatial distributions, sculpted by processes such as fluid flow and substrate adhesion. In this work, we show that spatial sensing and navigation can be optimized by adapting the spatial organization of signaling pathways to the spatial structure of the environment. We develop an information-theoretic framework for computing the optimal spatial organization of a sensing system for a given signaling environment. We find that receptor localization previously observed in cells maximizes information acquisition in simulated natural contexts, including tissue and soil. Specifically, information acquisition is maximized when receptors form localized patches at regions of maximal ligand concentration. Receptor localization extends naturally to produce a dynamic protocol for continuously redistributing signaling receptors, which when implemented using simple feedback, boosts cell navigation efficiency by 30-fold.

Limitations on concentration measurements and gradient discerning times in cellular systems

This work reports on two results. At first we revisit the Berg and Purcell calculation that provides a lower bound to the error in concentration measurement by cells by considering the realistic case when the cell starts measuring the moment it comes in contact with the chemoattractants, instead of measuring after equilibrating with the chemotactic concentration as done in the classic Berg and Purcell paper. We find that the error in concentration measurement is still the same as evaluated by Berg and Purcell. We next derive a lower bound on measurement time below which it is not possible for the cell to discern extracellular chemotactic gradients through spatial sensing mechanisms. This bound is independent of diffusion rate and concentration of the chemoattracts and is instead set by detachment rate of ligands from the cell receptors. The result could help explain experimental observations.

A systems approach to investigate GPCR-mediated Ras signaling network in chemoattractant sensing

A GPCR-mediated signaling network enables a chemotactic cell to generate adaptative Ras signaling in response to a large range of concentrations of a chemoattractant. To explore potential regulatory mechanisms of GPCR-controlled Ras signaling in chemosensing, we applied a software package, Simmune, to construct detailed spatiotemporal models simulating responses of the cAR1-mediated Ras signaling network. We first determined the dynamics of G-protein activation and Ras signaling in Dictyostelium cells in response to cAMP stimulations using live-cell imaging and then constructed computation models by incorporating potential mechanisms. Using simulations, we validated the dynamics of signaling events and predicted the dynamic profiles of those events in the cAR1-mediated Ras signaling networks with defective Ras inhibitory mechanisms, such as without RasGAP, with RasGAP overexpression, or with RasGAP hyperactivation. We describe a method of using Simmune to construct spatiotemporal models of a signaling network and run computational simulations without writing mathematical equations. This approach will help biologists to develop and analyze computational models that parallel live-cell experiments.

Plasmonic Imaging of Dynamic Interactions between Membrane Receptor Clusters beyond the Diffraction Limit in Live Cells

As a general mechanism, ligand-induced receptor clustering on cell membrane plays determinative roles in pattern recognition and transmembrane signaling. Nevertheless, probing the dynamic characteristics for the complicated interactions between receptor clusters remains difficult because of the lack of strategy for receptor cluster labeling and long-term monitoring in live cells. Herein, we proposed a data-mining-integrated plasmon coupling microscopy to study the dynamic cluster-cluster interactions on cell surface. The receptor clusters were activated and labeled with multivalent plasmonic nanoprobes, which enables the real-time monitoring of individual receptor clusters and the measurement of cluster-cluster interactions from the analysis of plasmonic coupling for the nanoprobe pairs beyond the diffraction limit. Using this method, we found that the protease-activated receptor 1 (PAR1) clusters would experience an initial contact and then form a weakly bound cluster-cluster complex, followed by cluster fusion to generate large-sized signaling complexes. The underlying state transitions for the cluster-cluster fusion process were uncovered using a data-mining technique named the K-means-based hidden Markov model with the scattering intensity of coupled nanoprobe pairs as observations. All of the findings from single-particle analysis and bulk measurements suggested that the allosteric inhibitors could suppress the dynamic transitions from the weakly bound cluster-cluster complexes to fused signaling complexes, leading to the subsequent downregulation of intracellular calcium signaling pathways. We believe that this strategy is promising for imaging and monitoring receptor clustering as well as protein phase separation on the cell surface in various biological and physiological processes.

Exploring the influence of cytosolic and membrane FAK activation on YAP/TAZ nuclear translocation

Membrane binding and unbinding dynamics play a crucial role in the biological activity of several nonintegral membrane proteins, which have to be recruited to the membrane to perform their functions. By localizing to the membrane, these proteins are able to induce downstream signal amplification in their respective signaling pathways. Here, we present a 3D computational approach using reaction-diffusion equations to investigate the relation between membrane localization of focal adhesion kinase (FAK), Ras homolog family member A (RhoA), and signal amplification of the YAP/TAZ signaling pathway. Our results show that the theoretical scenarios in which FAK is membrane bound yield robust and amplified YAP/TAZ nuclear translocation signals. Moreover, we predict that the amount of YAP/TAZ nuclear translocation increases with cell spreading, confirming the experimental findings in the literature. In summary, our in silico predictions show that when the cell membrane interaction area with the underlying substrate increases, for example, through cell spreading, this leads to more encounters between membrane-bound signaling partners and downstream signal amplification. Because membrane activation is a motif common to many signaling pathways, this study has important implications for understanding the design principles of signaling networks.

Different Heterotrimeric G Protein Dynamics for Wide-Range Chemotaxis in Eukaryotic Cells

Chemotaxis describes directional motility along ambient chemical gradients and has important roles in human physiology and pathology. Typical chemotactic cells, such as neutrophils and Dictyostelium cells, can detect spatial differences in chemical gradients over a background concentration of a 10⁵ scale. Studies of Dictyostelium cells have elucidated the molecular mechanisms of gradient sensing involving G protein coupled receptor (GPCR) signaling. GPCR transduces spatial information through its cognate heterotrimeric G protein as a guanine nucleotide change factor (GEF). More recently, studies have revealed unconventional regulation of heterotrimeric G protein in the gradient sensing. In this review, we explain how multiple mechanisms of GPCR signaling ensure the broad range sensing of chemical gradients in Dictyostelium cells as a model for eukaryotic chemotaxis.

How Phagocytes Acquired the Capability of Hunting and Removing Pathogens From a Human Body: Lessons Learned From Chemotaxis and Phagocytosis of Dictyostelium discoideum (Review)

How phagocytes find invading microorganisms and eliminate pathogenic ones from human bodies is a fundamental question in the study of infectious diseases. About 2.5 billion years ago, eukaryotic unicellular organisms-protozoans-appeared and started to interact with various bacteria. Less than 1 billion years ago, multicellular animals-metazoans-appeared and acquired the ability to distinguish self from non-self and to remove harmful organisms from their bodies. Since then, animals have developed innate immunity in which specialized white-blood cells phagocytes- patrol the body to kill pathogenic bacteria. The social amoebae Dictyostelium discoideum are prototypical phagocytes that chase various bacteria via chemotaxis and consume them as food via phagocytosis. Studies of this genetically amendable organism have revealed evolutionarily conserved mechanisms underlying chemotaxis and phagocytosis and shed light on studies of phagocytes in mammals. In this review, we briefly summarize important studies that contribute to our current understanding of how phagocytes effectively find and kill pathogens via chemotaxis and phagocytosis.

Three-dimensional stochastic simulation of chemoattractant-mediated excitability in cells

During the last decade, a consensus has emerged that the stochastic triggering of an excitable system drives pseudopod formation and subsequent migration of amoeboid cells. The presence of chemoattractant stimuli alters the threshold for triggering this activity and can bias the direction of migration. Though noise plays an important role in these behaviors, mathematical models have typically ignored its origin and merely introduced it as an external signal into a series of reaction-diffusion equations. Here we consider a more realistic description based on a reaction-diffusion master equation formalism to implement these networks. In this scheme, noise arises naturally from a stochastic description of the various reaction and diffusion terms. Working on a three-dimensional geometry in which separate compartments are divided into a tetrahedral mesh, we implement a modular description of the system, consisting of G-protein coupled receptor signaling (GPCR), a local excitation-global inhibition mechanism (LEGI), and signal transduction excitable network (STEN). Our models implement detailed biochemical descriptions whenever this information is available, such as in the GPCR and G-protein interactions. In contrast, where the biochemical entities are less certain, such as the LEGI mechanism, we consider various possible schemes and highlight the differences between them. Our simulations show that even when the LEGI mechanism displays perfect adaptation in terms of the mean level of proteins, the variance shows a dose-dependence. This differs between the various models considered, suggesting a possible means for determining experimentally among the various potential networks. Overall, our simulations recreate temporal and spatial patterns observed experimentally in both wild-type and perturbed cells, providing further evidence for the excitable system paradigm. Moreover, because of the overall importance and ubiquity of the modules we consider, including GPCR signaling and adaptation, our results will be of interest beyond the field of directed migration.

Though the term noise usually carries negative connotations, it can also contribute positively to the characteristic dynamics of a system. In biological systems, where noise arises from the stochastic interactions between molecules, its study is usually confined to genetic regulatory systems in which copy numbers are small and fluctuations large. However, noise can have important roles when the number of signaling molecules is large. The extension of pseudopods and the subsequent motion of amoeboid cells arises from the noise-induced trigger of an excitable system. Chemoattractant signals bias this triggering thereby directing cell motion. To date, this paradigm has not been tested by mathematical models that account accurately for the noise that arises in the corresponding reactions. In this study, we employ a reaction-diffusion master equation approach to investigate the effects of noise. Using a modular approach and a three-dimensional cell model with specific subdomains attributed to the cell membrane and cortex, we explore the spatiotemporal dynamics of the system. Our simulations recreate many experimentally-observed cell behaviors thereby supporting the biased-excitable network hypothesis.

A sub-population of Dictyostelium discoideum cells shows extremely high sensitivity to cAMP for directional migration

The chemotaxis of Dictysotelium discoideum cells in response to a chemical gradient of cyclic adenosine 3',5'-monophosphate (cAMP) was studied using a newly designed microfluidic device. The device consists of 800 cell-sized channels in parallel, each 4 μm wide, 5 μm high, and 100 μm long, allowing us to prepare the same chemical gradient in all channels and observe the motility of 500-1000 individual cells simultaneously. The percentage of cells that exhibited directed migration was determined for various cAMP concentrations ranging from 0.1 pM to 10 μM. The results show that chemotaxis was highest at 100 nM cAMP, consistent with previous observations. At concentrations as low as 10 pM, about 16% of cells still exhibited chemotaxis, suggesting that the receptor occupancy of only 6 cAMP molecules/cell can induce chemotaxis in very sensitive cells. At 100 pM cAMP, chemotaxis was suppressed due to the self-production and secretion of intracellular cAMP induced by extracellular cAMP. Overall, systematic observations of a large number of individual cells under the same chemical gradients revealed the heterogeneity of chemotaxis responses in a genetically homogeneous cell population, especially the existence of a sub-population with extremely high sensitivity for chemotaxis.

A method for imaging single molecules at the plasma membrane of live cells within tissue slices

Recent advances in light microscopy allow individual biological macromolecules to be visualized in the plasma membrane and cytosol of live cells with nanometer precision and ∼10-ms time resolution. This allows new discoveries to be made because the location and kinetics of molecular interactions can be directly observed in situ without the inherent averaging of bulk measurements. To date, the majority of single-molecule imaging studies have been performed in either unicellular organisms or cultured, and often chemically fixed, mammalian cell lines. However, primary cell cultures and cell lines derived from multi-cellular organisms might exhibit different properties from cells in their native tissue environment, in particular regarding the structure and organization of the plasma membrane. Here, we describe a simple approach to image, localize, and track single fluorescently tagged membrane proteins in freshly prepared live tissue slices and demonstrate how this method can give information about the movement and localization of a G protein–coupled receptor in cardiac tissue slices. In principle, this experimental approach can be used to image the dynamics of single molecules at the plasma membrane of many different soft tissue samples and may be combined with other experimental techniques.

Unified control of amoeboid pseudopod extension in multiple organisms by branched F-actin in the front and parallel F-actin/myosin in the cortex

The trajectory of moving eukaryotic cells depends on the kinetics and direction of extending pseudopods. The direction of pseudopods has been well studied to unravel mechanisms for chemotaxis, wound healing and inflammation. However, the kinetics of pseudopod extension-when and why do pseudopods start and stop- is equally important, but is largely unknown. Here the START and STOP of about 4000 pseudopods was determined in four different species, at four conditions and in nine mutants (fast amoeboids Dictyostelium and neutrophils, slow mesenchymal stem cells, and fungus B.d. chytrid with pseudopod and a flagellum). The START of a first pseudopod is a random event with a probability that is species-specific (23%/s for neutrophils). In all species and conditions, the START of a second pseudopod is strongly inhibited by the extending first pseudopod, which depends on parallel filamentous actin/myosin in the cell cortex. Pseudopods extend at a constant rate by polymerization of branched F-actin at the pseudopod tip, which requires the Scar complex. The STOP of pseudopod extension is induced by multiple inhibitory processes that evolve during pseudopod extension and mainly depend on the increasing size of the pseudopod. Surprisingly, no differences in pseudopod kinetics are detectable between polarized, unpolarized or chemotactic cells, and also not between different species except for small differences in numerical values. This suggests that the analysis has uncovered the fundament of cell movement with distinct roles for stimulatory branched F-actin in the protrusion and inhibitory parallel F-actin in the contractile cortex.

Helicity Manipulation of a Double-Paddled Binaphthyl in a Two-Dimensional Matrix Field at the Air-Water Interface

Molecular behavior and functionality are affected by their prevailing immediate environment. Molecular machines function according to conformational variations and have been studied largely in solution states. In order to access more highly complex functional molecular machines, it is necessary to analyze and control them in various environments. We have designed and synthesized a bisbinaphthyldurene (BBD) molecule that has two binaphthyl groups connected through a central durene moiety, allowing for the formation of several conformers. In density functional theory (DFT) calculations, BBD has five major conformers, denoted anti-1/anti-2/syn-1/syn-2/flat. It has been demonstrated that BBD exhibits different conformations in solution (anti-1 and syn-1) than on a gold surface (syn dimer and flat). In this work, the ratio of BBD conformations has been controlled in mixed monolayers with several different lipids at an air-water interface in order to compare conformational activity under different conditions. The conformations of BBD in transferred films obtained by using Langmuir-Blodgett techniques were estimated from circular dichroism spectra and DFT calculations. It has been found that the conformation of BBD in the mixed monolayer depends on its aggregated state, which has been controlled here by the mechanical properties and miscibility. In mixed monolayers with "hard" lipids having less miscibility with BBD as well as in cast film, BBD is self-aggregated and mostly forms stable anti-1 and syn-1 conformations, while unstable anti-2 and syn-2 conformers dominated in the more dispersed states involving "soft" lipids, which show good miscibility with BBD. Conformational changes in BBD are due to the formation of different aggregated states in each mixed monolayer according to the miscibility. Overall, BBD molecular conformations (and the resulting spectra) could be tuned by controlling the environment whether in solution, on a solid substrate, or in an admixture with lipids at the air-water interface.

Spatial gradient sensing and chemotaxis via excitability in Dictyostelium discoideum

The social amoeba Dictyostelium discoideum performs chemotaxis under starvation conditions, aggregating towards clusters of cells following waves of the signaling molecule cAMP. Cells sense extracellular cAMP and produce internal caches of cAMP to be released, relaying the signal. These events lead to traveling waves of cAMP washing over the population of cells. While much research has been performed to understand the functioning of the chemotaxis network in D. discoideum, limited work has been done to link the operation of the signal relay network with the chemotaxis network to provide a holistic view of the system. We take inspiration from D. discoideum and propose a model that directly links the relaying of a chemical message to the directional sensing of that signal. Utilizing an excitable dynamical systems model that has been previously validated experimentally, we show that it is possible to have both signal amplification and perfect adaptation in a single module. We show that noise plays a vital role in chemotaxing to static gradients, where stochastic tunneling of transient bursts biases the system towards accurate gradient sensing. Moreover, this model also automatically matches its internal time scale of adaptation to the naturally occurring periodicity of the traveling chemical waves generated in the population. Numerical simulations were performed to study the qualitative phenomenology of the system and explore how the system responds to diverse dynamic spatiotemporal stimuli. Finally, we address dynamical instabilities that impede chemotactic ability in a continuum version of the model.

Single-molecule imaging of PI(4,5)P2 and PTEN in vitro reveals a positive feedback mechanism for PTEN membrane binding

PTEN, a 3-phosphatase of phosphoinositide, regulates asymmetric PI(3,4,5)P3 signaling for the anterior-posterior polarization and migration of motile cells. PTEN acts through posterior localization on the plasma membrane, but the mechanism for this accumulation is poorly understood. Here we developed an in vitro single-molecule imaging assay with various lipid compositions and use it to demonstrate that the enzymatic product, PI(4,5)P2, stabilizes PTEN's membrane-binding. The dissociation kinetics and lateral mobility of PTEN depended on the PI(4,5)P2 density on artificial lipid bilayers. The basic residues of PTEN were responsible for electrostatic interactions with anionic PI(4,5)P2 and thus the PI(4,5)P2-dependent stabilization. Single-molecule imaging in living Dictyostelium cells revealed that these interactions were indispensable for the stabilization in vivo, which enabled efficient cell migration by accumulating PTEN posteriorly to restrict PI(3,4,5)P3 distribution to the anterior. These results suggest that PI(4,5)P2-mediated positive feedback and PTEN-induced PI(4,5)P2 clustering may be important for anterior-posterior polarization.

Large-scale single-molecule imaging aided by artificial intelligence

Single-molecule imaging analysis has been applied to study the dynamics and kinetics of molecular behaviors and interactions in living cells. In spite of its high potential as a technique to investigate the molecular mechanisms of cellular phenomena, single-molecule imaging analysis has not been extended to a large scale of molecules in cells due to the low measurement throughput as well as required expertise. To overcome these problems, we have automated the imaging processes by using computer operations, robotics and artificial intelligence (AI). AI is an ideal substitute for expertise to obtain high-quality images for quantitative analysis. Our automated in-cell single-molecule imaging system, AiSIS, could analyze 1600 cells in 1 day, which corresponds to ∼ 100-fold higher efficiency than manual analysis. The large-scale analysis revealed cell-to-cell heterogeneity in the molecular behavior, which had not been recognized in previous studies. An analysis of the receptor behavior and downstream signaling was accomplished within a significantly reduced time frame and revealed the detailed activation scheme of signal transduction, advancing cell biology research. Furthermore, by combining the high-throughput analysis with our previous finding that a receptor changes its behavioral dynamics depending on the presence of a ligand/agonist or inhibitor/antagonist, we show that AiSIS is applicable to comprehensive pharmacological analysis such as drug screening. This AI-aided automation has wide applications for single-molecule analysis.

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.

Mutual inhibition between PTEN and PIP3 generates bistability for polarity in motile cells

Phosphatidylinositol 3,4,5-trisphosphate (PIP3) and PIP3 phosphatase (PTEN) are enriched mutually exclusively on the anterior and posterior membranes of eukaryotic motile cells. However, the mechanism that causes this spatial separation between the two molecules is unknown. Here we develop a method to manipulate PIP3 levels in living cells and used it to show PIP3 suppresses the membrane localization of PTEN. Single-molecule measurements of membrane-association and -dissociation kinetics and of lateral diffusion reveal that PIP3 suppresses the PTEN binding site required for stable PTEN membrane binding. Mutual inhibition between PIP3 and PTEN provides a mechanistic basis for bistability that creates a PIP3-enriched/PTEN-excluded state and a PTEN-enriched/PIP3-excluded state underlying the strict spatial separation between PIP3 and PTEN. The PTEN binding site also mediates the suppression of PTEN membrane localization in chemotactic signaling. These results illustrate that the PIP3-PTEN bistable system underlies a cell's decision-making for directional movement irrespective of the environment.

Chemotaxis Model for Breast Cancer Cells Based on Signal/Noise Ratio

Chemotaxis, a biased migration of cells under a chemical gradient, plays a significant role in diverse biological phenomena including cancer metastasis. Stromal cells release signaling proteins to induce chemotaxis, which leads to organ-specific metastasis. Epidermal growth factor (EGF) is an example of the chemical attractants, and its gradient stimulates metastasis of breast cancer cells. Hence, the interactions between EGF and breast cancer cells have long been a subject of interest for oncologists and clinicians. However, most current approaches do not systematically separate the effects of gradient and absolute concentration of EGF on chemotaxis of breast cancer cells. In this work, we develop a theoretical model based on signal/noise ratio to represent stochastic properties and report our microfluidic experiments to verify the analytical predictions from the model. The results demonstrate that even under the same EGF concentration gradients (0-50 or 0-150 ng/mL), breast cancer cells reveal a more evident chemotaxis pattern when the absolute EGF concentrations are low. Moreover, we found that reducing the number of EGF receptors (EGFRs) with addition of EGFR antibody (1 ng/mL) can promote chemotaxis at an EGF gradient of 0-1 ng/mL as shown by chemotaxis index (0.121 ± 0.037, reduced EGFRs vs. 0.003 ± 0.041, control). This counterintuitive finding suggests that EGFR-targeted therapy may stimulate metastasis of breast cancer because the partial suppression of the receptors makes the number of receptors close to the optimal one for chemotaxis. This analysis should be considered in anticancer drug design.

Electric Pulses Can Influence Galvanotaxis of Dictyostelium discoideum

Galvanotaxis, or electrotaxis, plays an essential role in wound healing, embryogenesis, and nerve regeneration. Up until now great efforts have been made to identify the underlying mechanism related to galvanotaxis in various cells under direct current electric field (DCEF) in laboratory studies. However, abundant clinical research shows that non-DCEFs including monopolar or bipolar electric field may also contribute to wound healing and regeneration, although the mechanism remains elusive. Here, we designed a novel electric stimulator and applied DCEF, pulsed DCEF (pDCEF), and bipolar pulse electric field (bpEF) to the cells of Dictyostelium discoideum. The cells had better directional performance under asymmetric 90% duty cycle pDCEF and 80% duty cycle bpEF compared to DCEF, with 10 Hz frequency electric fields eliciting a better cell response than 5 Hz. Interestingly, electrically neutral 50% duty cycle bpEF triggered the highest migration speed, albeit in random directions. The results suggest that electric pulses are vital to galvanotaxis and non-DCEF is promising in both basic and clinical researches.

Automated single-molecule imaging in living cells

An automated single-molecule imaging system developed for live-cell analyses based on artificial intelligence-assisted microscopy is presented. All significant procedures, i.e., searching for cells suitable for observation, detecting in-focus positions, and performing image acquisition and single-molecule tracking, are fully automated, and numerous highly accurate, efficient, and reproducible single-molecule imaging experiments in living cells can be performed. Here, the apparatus is applied for single-molecule imaging and analysis of epidermal growth factor receptors (EGFRs) in 1600 cells in a 96-well plate within 1 day. Changes in the lateral mobility of EGFRs on the plasma membrane in response to various ligands and drug concentrations are clearly detected in individual cells, and several dynamic and pharmacological parameters are determined, including the diffusion coefficient, oligomer size, and half-maximal effective concentration (EC50). Automated single-molecule imaging for systematic cell signaling analyses is feasible and can be applied to single-molecule screening, thus extensively contributing to biological and pharmacological research.

Mechanochemical modeling of neutrophil migration based on four signaling layers, integrin dynamics, and substrate stiffness

Directional neutrophil migration during human immune responses is a highly coordinated process regulated by both biochemical and biomechanical environments. In this paper, we developed an integrative mathematical model of neutrophil migration using a lattice Boltzmann-particle method built in-house to solve the moving boundary problem with spatiotemporal regulation of biochemical components. The mechanical features of the cell cortex are modeled by a series of spring-connected nodes representing discrete cell-substrate adhesive sites. The intracellular signaling cascades responsible for cytoskeletal remodeling [e.g., small GTPases, phosphoinositide-3-kinase (PI3K), and phosphatase and tensin homolog] are built based on our previous four-layered signaling model centered on the bidirectional molecular transport mechanism and implemented as reaction-diffusion equations. Focal adhesion dynamics are determined by force-dependent integrin-ligand binding kinetics and integrin recycling and are thus integrated with cell motion. Using numerical simulations, the model reproduces the major features of cell migration in response to uniform and gradient biochemical stimuli based on the quantitative spatiotemporal regulation of signaling molecules, which agree with experimental observations. The existence of multiple types of integrins with different binding kinetics could act as an adaptation mechanism for substrate stiffness. Moreover, cells can perform reversal, U-turn, or lock-on behaviors depending on the steepness of the reversal biochemical signals received. Finally, this model is also applied to predict the responses of mutants in which PTEN is overexpressed or disrupted.

Arabidopsis Blue Light Receptor Phototropin 1 Undergoes Blue Light-Induced Activation in Membrane Microdomains

Phototropin (phot)-mediated signaling initiated by blue light (BL) plays a critical role in optimizing photosynthetic light capture at the plasma membrane (PM) in plants. However, the mechanisms underlying the regulation of phot activity at the PM in response to BL remain largely unclear. In this study, by single-particle tracking and stepwise photobleaching analysis of phot1-GFP proteins we demonstrated that in the dark phot1 proteins remain in an inactive state and mostly exist as monomers. Dimerization and the diffusion rate of phot1-GFP increased in a dose-dependent manner in response to BL. In contrast, BL did not affect the lateral diffusion of kinase-inactive phot1^D806N-GFP but did enhance its dimerization, suggesting that phot1 dimerization is independent of phosphorylation. Förster resonance energy transfer-fluorescence lifetime imaging microscopy analysis revealed that the interaction between phot1-GFP and a marker of sterol-rich lipid environments, AtRem1.3-mCherry, was enhanced with increased time of BL treatment. However, this BL-dependent interaction was not obvious in plants co-expressing phot1^D806N-GFP and AtRem1.3-mCherry, indicating that BL facilitates the translocation of functional phot1-GFP into AtRem1.3-labeled microdomains to activate phot-mediated signaling. Conversely, sterol depletion attenuated phot1-GFP dynamics, dimerization, and phosphorylation. Taken together, these results indicate that membrane microdomains act as organizing platforms essential for the proper function of activated phot1 at the PM.

Dynamic seesaw model for rapid signaling responses in eukaryotic chemotaxis

Directed movement of eukaryotic cells toward spatiotemporally varied chemotactic stimuli enables rapid intracellular signaling responses. While macroscopic cellular manifestation is shaped by balancing external stimuli strength with finite internal delays, the organizing principles of the underlying molecular mechanisms remain to be clarified. Here, we developed a novel modeling framework based on a simple seesaw mechanism to elucidate how cells repeatedly reverse polarity. As a key feature of the modeling, the bottom module of bidirectional molecular transport is successively controlled by three upstream modules of signal reception, initial signal processing, and Rho GTPase regulation. Our simulations indicated that an isotropic cell is polarized in response to a graded input signal. By applying a reversal gradient to a chemoattractant signal, lamellipod-specific molecules (i.e. PIP₃ and PI3K) disappear, first from the cell front, and then they redistribute at the opposite side, whereas functional molecules at the rear of the cell (i.e. PIP₂ and PTEN) act oppositely. In particular, the model cell exhibits a seesaw-like spatiotemporal pattern for the establishment of front and rear and interconversion, consistent with those related experimental observations. Increasing the switching frequency of the chemotactic gradient causes the cell to stay in a trapped state, further supporting the proposed dynamics of eukaryotic chemotaxis with the underlying cytoskeletal remodeling.

Estimation of diffusion constants from single molecular measurement without explicit tracking

BACKGROUND

Time course measurement of single molecules on a cell surface provides detailed information about the dynamics of the molecules that would otherwise be inaccessible. To extract the quantitative information, single particle tracking (SPT) is typically performed. However, trajectories extracted by SPT inevitably have linking errors when the diffusion speed of single molecules is high compared to the scale of the particle density.

METHODS

To circumvent this problem, we develop an algorithm to estimate diffusion constants without relying on SPT. The proposed algorithm is based on a probabilistic model of the distance to the nearest point in subsequent frames. This probabilistic model generalizes the model of single particle Brownian motion under an isolated environment into the one surrounded by indistinguishable multiple particles, with a mean field approximation.

RESULTS

We demonstrate that the proposed algorithm provides reasonable estimation of diffusion constants, even when other methods suffer due to high particle density or inhomogeneous particle distribution. In addition, our algorithm can be used for visualization of time course data from single molecular measurements.

CONCLUSIONS

The proposed algorithm based on the probabilistic model of indistinguishable Brownian particles provide accurate estimation of diffusion constants even in the regime where the traditional SPT methods underestimate them due to linking errors.

Extracellular Processing of Molecular Gradients by Eukaryotic Cells Can Improve Gradient Detection Accuracy

Eukaryotic cells sense molecular gradients by measuring spatial concentration variation through the difference in the number of occupied receptors to which molecules can bind. They also secrete enzymes that degrade these molecules, and it is presently not well understood how this affects the local gradient perceived by cells. Numerical and analytical results show that these enzymes can substantially increase the signal-to-noise ratio of the receptor difference and allow cells to respond to a much broader range of molecular concentrations and gradients than they would without these enzymes.

Discrete Modeling of Amoeboid Locomotion and Chemotaxis in Dictyostelium discoideum by Tracking Pseudopodium Growth Direction

Dictyostelium discoideum amoeba is a well-established model organism for studying the crawling locomotion of eukaryotic cells. These amoebae extend pseudopodium - a temporary actin-based protrusion of their body membrane to probe the medium and crawl through it. Experiments show highly-ordered patterns in the growth direction of these pseudopodia, which results in persistence cell motility. Here, we propose a discrete model for studying and investigating the cell locomotion based on the experimental evidences. According to our model, Dictyostelium selects its pseudopodium growth direction based on a second-order Markov chain process, in the absence of external cues. Consequently, compared to a random walk process, our model indicates stronger growth in the mean-square displacement of cells, which is consistent with empirical findings. In the presence of external chemical stimulants, cells tend to align with the gradient of chemoattractant molecules. To quantify this tendency, we define a coupling coefficient between the pseudopodium extension direction and the gradient of an external stimulant, which depends on the local stimulant concentration and its gradient. Additionally, we generalize the model to weak-coupling regime by utilizing perturbation methods.

Single-molecule imaging and manipulation of biomolecular machines and systems

BACKGROUND

Biological molecular machines support various activities and behaviors of cells, such as energy production, signal transduction, growth, differentiation, and migration.

SCOPE OF REVIEW

We provide an overview of single-molecule imaging methods involving both small and large probes used to monitor the dynamic motions of molecular machines in vitro (purified proteins) and in living cells, and single-molecule manipulation methods used to measure the forces, mechanical properties and responses of biomolecules. We also introduce several examples of single-molecule analysis, focusing primarily on motor proteins and signal transduction systems.

MAJOR CONCLUSIONS

Single-molecule analysis is a powerful approach to unveil the operational mechanisms both of individual molecular machines and of systems consisting of many molecular machines.

GENERAL SIGNIFICANCE

Quantitative, high-resolution single-molecule analyses of biomolecular systems at the various hierarchies of life will help to answer our fundamental question: "What is life?" This article is part of a Special Issue entitled "Biophysical Exploration of Dynamical Ordering of Biomolecular Systems" edited by Dr. Koichi Kato.

Seeing the unseen: Imaging rotation in cells with designer anisotropic particles

Cellular functions are enabled by cascades of transient biological events. Imaging and tracking the dynamics of these events have proven to be a powerful means of understanding the principles of cellular processes. These studies have typically focused on translational dynamics. By contrast, investigations of rotational dynamics have been scarce, despite emerging evidence that rotational dynamics are an inherent feature of many cellular processes and may also provide valuable clues to understanding those cell functions. Such studies have been impeded by the limited availability of suitable rotational imaging probes. This has recently changed thanks to the advances in the development of anisotropic particles for rotational imaging. In this review, we will summarize current techniques for imaging rotation using particle probes that are anisotropic in shape or optical properties. We will highlight two studies that demonstrate how these techniques can be applied to explore important facets of cellular functions.

Single molecule detection, thermal fluctuation and life

Single molecule detection has contributed to our understanding of the unique mechanisms of life. Unlike artificial man-made machines, biological molecular machines integrate thermal noises rather than avoid them. For example, single molecule detection has demonstrated that myosin motors undergo biased Brownian motion for stepwise movement and that single protein molecules spontaneously change their conformation, for switching to interactions with other proteins, in response to thermal fluctuation. Thus, molecular machines have flexibility and efficiency not seen in artificial machines.

Connecting G protein signaling to chemoattractant-mediated cell polarity and cytoskeletal reorganization

The directional movement toward extracellular chemical gradients, a process called chemotaxis, is an important property of cells. Central to eukaryotic chemotaxis is the molecular mechanism by which chemoattractant-mediated activation of G-protein coupled receptors (GPCRs) induces symmetry breaking in the activated downstream signaling pathways. Studies with mainly Dictyostelium and mammalian neutrophils as experimental systems have shown that chemotaxis is mediated by a complex network of signaling pathways. Recently, several labs have used extensive and efficient proteomic approaches to further unravel this dynamic signaling network. Together these studies showed the critical role of the interplay between heterotrimeric G-protein subunits and monomeric G proteins in regulating cytoskeletal rearrangements during chemotaxis. Here we highlight how these proteomic studies have provided greater insight into the mechanisms by which the heterotrimeric G protein cycle is regulated, how heterotrimeric G proteins-induced symmetry breaking is mediated through small G protein signaling, and how symmetry breaking in G protein signaling subsequently induces cytoskeleton rearrangements and cell migration.

Local modulation of chemoattractant concentrations by single cells: dissection using a bulk-surface computational model

Chemoattractant gradients are usually considered in terms of sources and sinks that are independent of the chemotactic cell. However, recent interest has focused on 'self-generated' gradients, in which cell populations create their own local gradients as they move. Here, we consider the interplay between chemoattractants and single cells. To achieve this, we extend a recently developed computational model to incorporate breakdown of extracellular attractants by membrane-bound enzymes. Model equations are parametrized, using the published estimates from Dictyostelium cells chemotaxing towards cyclic AMP. We find that individual cells can substantially modulate their local attractant field under physiologically appropriate conditions of attractant and enzymes. This means the attractant concentration perceived by receptors can be a small fraction of the ambient concentration. This allows efficient chemotaxis in chemoattractant concentrations that would be saturating without local breakdown. Similar interactions in which cells locally mould a stimulus could function in many types of directed cell motility, including haptotaxis, durotaxis and even electrotaxis.

Individual cell heterogeneity in Predictive Food Microbiology: Challenges in predicting a "noisy" world

Gene expression is a fundamentally noisy process giving rise to a significant cell to cell variability at the phenotype level. The phenotypic noise is manifested in a wide range of microbial traits. Heterogeneous behavior of individual cells is observed at the growth, survival and inactivation responses and should be taken into account in the context of Predictive Food Microbiology (PMF). Recent methodological advances can be employed for the study and modeling of single cell dynamics leading to a new generation of mechanistic models which can provide insight into the link between phenotype, gene-expression, protein and metabolic functional units at the single cell level. Such models however, need to deal with an enormous amount of interactions and processes that influence each other, forming an extremely complex system. In this review paper, we discuss the importance of noise and present the future challenges in predicting the "noisy" microbial responses in foods.

A Gα-Stimulated RapGEF Is a Receptor-Proximal Regulator of Dictyostelium Chemotaxis

Chemotaxis, or directional movement toward extracellular chemical gradients, is an important property of cells that is mediated through G-protein-coupled receptors (GPCRs). Although many chemotaxis pathways downstream of Gβγ have been identified, few Gα effectors are known. Gα effectors are of particular importance because they allow the cell to distinguish signals downstream of distinct chemoattractant GPCRs. Here we identify GflB, a Gα2 binding partner that directly couples the Dictyostelium cyclic AMP GPCR to Rap1. GflB localizes to the leading edge and functions as a Gα-stimulated, Rap1-specific guanine nucleotide exchange factor required to balance Ras and Rap signaling. The kinetics of GflB translocation are fine-tuned by GSK-3 phosphorylation. Cells lacking GflB display impaired Rap1/Ras signaling and actin and myosin dynamics, resulting in defective chemotaxis. Our observations demonstrate that GflB is an essential upstream regulator of chemoattractant-mediated cell polarity and cytoskeletal reorganization functioning to directly link Gα activation to monomeric G-protein signaling.

A Model for Direction Sensing in Dictyostelium discoideum: Ras Activity and Symmetry Breaking Driven by a Gβγ-Mediated, Gα2-Ric8 -- Dependent Signal Transduction Network

Chemotaxis is a dynamic cellular process, comprised of direction sensing, polarization and locomotion, that leads to the directed movement of eukaryotic cells along extracellular gradients. As a primary step in the response of an individual cell to a spatial stimulus, direction sensing has attracted numerous theoretical treatments aimed at explaining experimental observations in a variety of cell types. Here we propose a new model of direction sensing based on experiments using Dictyostelium discoideum (Dicty). The model is built around a reaction-diffusion-translocation system that involves three main component processes: a signal detection step based on G-protein-coupled receptors (GPCR) for cyclic AMP (cAMP), a transduction step based on a heterotrimetic G protein Gα2βγ, and an activation step of a monomeric G-protein Ras. The model can predict the experimentally-observed response of cells treated with latrunculin A, which removes feedback from downstream processes, under a variety of stimulus protocols. We show that [Formula: see text] cycling modulated by Ric8, a nonreceptor guanine exchange factor for [Formula: see text] in Dicty, drives multiple phases of Ras activation and leads to direction sensing and signal amplification in cAMP gradients. The model predicts that both [Formula: see text] and Gβγ are essential for direction sensing, in that membrane-localized [Formula: see text], the activated GTP-bearing form of [Formula: see text], leads to asymmetrical recruitment of RasGEF and Ric8, while globally-diffusing Gβγ mediates their activation. We show that the predicted response at the level of Ras activation encodes sufficient 'memory' to eliminate the 'back-of-the wave' problem, and the effects of diffusion and cell shape on direction sensing are also investigated. In contrast with existing LEGI models of chemotaxis, the results do not require a disparity between the diffusion coefficients of the Ras activator GEF and the Ras inhibitor GAP. Since the signal pathways we study are highly conserved between Dicty and mammalian leukocytes, the model can serve as a generic one for direction sensing.

Hybrid mechanosensing system to generate the polarity needed for migration in fish keratocytes

Crawling cells can generate polarity for migration in response to forces applied from the substratum. Such reaction varies according to cell type: there are both fast- and slow-crawling cells. In response to periodic stretching of the elastic substratum, the intracellular stress fibers in slow-crawling cells, such as fibroblasts, rearrange themselves perpendicular to the direction of stretching, with the result that the shape of the cells extends in that direction; whereas fast-crawling cells, such as neutrophil-like differentiated HL-60 cells and Dictyostelium cells, which have no stress fibers, migrate perpendicular to the stretching direction. Fish epidermal keratocytes are another type of fast-crawling cell. However, they have stress fibers in the cell body, which gives them a typical slow-crawling cell structure. In response to periodic stretching of the elastic substratum, intact keratocytes rearrange their stress fibers perpendicular to the direction of stretching in the same way as fibroblasts and migrate parallel to the stretching direction, while blebbistatin-treated stress fiber-less keratocytes migrate perpendicular to the stretching direction, in the same way as seen in HL-60 cells and Dictyostelium cells. Our results indicate that keratocytes have a hybrid mechanosensing system that comprises elements of both fast- and slow-crawling cells, to generate the polarity needed for migration.

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.

Depth-of-Focus Correction in Single-Molecule Data Allows Analysis of 3D Diffusion of the Glucocorticoid Receptor in the Nucleus

Single-molecule imaging of proteins in a 2D environment like membranes has been frequently used to extract diffusive properties of multiple fractions of receptors. In a 3D environment the apparent fractions however change with observation time due to the movements of molecules out of the depth-of-field of the microscope. Here we developed a mathematical framework that allowed us to correct for the change in fraction size due to the limited detection volume in 3D single-molecule imaging. We applied our findings on the mobility of activated glucocorticoid receptors in the cell nucleus, and found a freely diffusing fraction of 0.49±0.02. Our analysis further showed that interchange between this mobile fraction and an immobile fraction does not occur on time scales shorter than 150 ms.

Dynamic filopodia are required for chemokine-dependent intracellular polarization during guided cell migration in vivo

Cell migration and polarization is controlled by signals in the environment. Migrating cells typically form filopodia that extend from the cell surface, but the precise function of these structures in cell polarization and guided migration is poorly understood. Using the in vivo model of zebrafish primordial germ cells for studying chemokine-directed single cell migration, we show that filopodia distribution and their dynamics are dictated by the gradient of the chemokine Cxcl12a. By specifically interfering with filopodia formation, we demonstrate for the first time that these protrusions play an important role in cell polarization by Cxcl12a, as manifested by elevation of intracellular pH and Rac1 activity at the cell front. The establishment of this polarity is at the basis of effective cell migration towards the target. Together, we show that filopodia allow the interpretation of the chemotactic gradient in vivo by directing single-cell polarization in response to the guidance cue.

DOI:http://dx.doi.org/10.7554/eLife.05279.001

Some of the cells in an animal embryo have to migrate long distances to reach their final positions; that is to say, to reach the locations where they will participate in the formation of tissues and organs. The migration of cells is also important throughout the entire lifespan of an animal. White blood cells, for example, must be able to move within tissues to search for and fight infections as well as to detect and remove abnormal cells.

The front end of a migrating cell typically protrudes. The back of the cell is then pulled and detaches, which allows the whole cell to move forward. Migrating cells generate thin finger-like projections known as filopodia that have been suggested to help the cell sense their external environments and follow chemical cues. It is not clear what happens to a migrating cell in a living organism if the formation of its filopodia is impaired, or even how filipodia help the normal migration of cells in animals.

To define how filopodia help to guide migrating cells in an animal, Meyen et al. analyzed the migration of cells called ‘primordial germ cells’ (or PGCs) in zebrafish. These cells form very early on in development of a zebrafish embryo at a position that is far away from their final location (in the testes or ovaries where they will go on to form sperm or egg cells respectively). Meyen et al. revealed that cells that are exposed to the guidance cue (a protein called a chemokine) form more filopodia at their front compared to their rear. The filopodia formed at the cell front also extend and retract more frequently.

Meyen et al. further observed that the specific chemokine that guides the cells can bind to the filopodia and enter the cell. This leads to a signal inside the cell that tells the cell to move in the direction where more of the chemokine is found. Indeed, altering the distribution and number of filopodia around the cell's edge decreases the ability of the primordial germ cells to reach their targets. Together, this work shows that the filopodia at the front end of cells are required for sensing the chemokines that guide cell movement.

Further work is required to understand the mechanism that determines the distribution of filopodia on the surface of migrating cells, and the role of chemokines in the process. Moreover, this work may also be relevant for understanding the migration of cancer cells, because several types of cancer can invade new tissues by following directional cues including chemokines.

DOI:http://dx.doi.org/10.7554/eLife.05279.002

Compact halo-ligand-conjugated quantum dots for multicolored single-molecule imaging of overcrowding GPCR proteins on cell membranes

To detect single molecules within the optical diffraction limit (< ca. 200 nm), a multicolored imaging technique is developed using Halo-ligand conjugated quantum dots (Halo-QDs; <6 nm in diameter). Using three types of Halo-QDs, multicolored single-molecule fluorescence imaging of GPCR proteins in Dictyostelium cells is achieved.

How receptor diffusion influences gradient sensing

Chemotaxis, or directed motion in chemical gradients, is critical for various biological processes. Many eukaryotic cells perform spatial sensing, i.e. they detect gradients by comparing spatial differences in binding occupancy of chemosensory receptors across their membrane. In many theoretical models of spatial sensing, it is assumed, for the sake of simplicity, that the receptors concerned do not move. However, in reality, receptors undergo diverse modes of diffusion, and can traverse considerable distances in the time it takes such cells to turn in an external gradient. This sets a physical limit on the accuracy of spatial sensing, which we explore using a model in which receptors diffuse freely over the membrane. We find that the Fisher information carried in binding and unbinding events decreases monotonically with the diffusion constant of the receptors.