ICAM-1 nanoclusters regulate hepatic epithelial cell polarity by leukocyte adhesion-independent control of apical actomyosin

Epithelial intercellular adhesion molecule (ICAM)-1 is apically polarized, interacts with, and guides leukocytes across epithelial barriers. Polarized hepatic epithelia organize their apical membrane domain into bile canaliculi and ducts, which are not accessible to circulating immune cells but that nevertheless confine most of ICAM-1. Here, by analyzing ICAM-1_KO human hepatic cells, liver organoids from ICAM-1_KO mice and rescue-of-function experiments, we show that ICAM-1 regulates epithelial apicobasal polarity in a leukocyte adhesion-independent manner. ICAM-1 signals to an actomyosin network at the base of canalicular microvilli, thereby controlling the dynamics and size of bile canalicular-like structures. We identified the scaffolding protein EBP50/NHERF1/SLC9A3R1, which connects membrane proteins with the underlying actin cytoskeleton, in the proximity interactome of ICAM-1. EBP50 and ICAM-1 form nano-scale domains that overlap in microvilli, from which ICAM-1 regulates EBP50 nano-organization. Indeed, EBP50 expression is required for ICAM-1-mediated control of BC morphogenesis and actomyosin. Our findings indicate that ICAM-1 regulates the dynamics of epithelial apical membrane domains beyond its role as a heterotypic cell-cell adhesion molecule and reveal potential therapeutic strategies for preserving epithelial architecture during inflammatory stress.

Did the first description of patients with polymyalgia rheumatica take place in Scotland or in Denmark?

The first description of polymyalgia rheumatica (PMR) is generally attributed to Dr. Bruce. In an 1888 article entitled Senile rheumatic gout, he described five male patients aged from 60 to 74 years whom he had visited at the Strathpeffer spa in Scotland. In 1945, Dr. Holst and Dr. Johansen reported on five female patients examined over several months at the Medical Department of Roskilde County Hospital in Denmark. These patients suffered from hip, upper arms, and neck pain associated with elevated ESR and constitutional manifestations such as low-grade fever or loss of weight. In the same year, Meulengracht, another Danish physician, reported on two patients with shoulder pain and stiffness associated with fever, weight loss, and an increased erythrocyte sedimentation rate. As in the five patients reported by Dr. Holst and Dr. Johansen, a prolonged recovery time was recorded. On reading and comparing these three accounts, we question whether it is correct to attribute the first description of PMR to Dr. Bruce and put forward shifting this accolade to the three Danish physicians.

Learning Continuous 2D Diffusion Maps from Particle Trajectories without Data Binning

Diffusion coefficients often vary across regions, such as cellular membranes, and quantifying their variation can provide valuable insight into local membrane properties such as composition and stiffness. Toward quantifying diffusion coefficient spatial maps and uncertainties from particle tracks, we use a Bayesian method and place Gaussian Process (GP) Priors on the maps. For the sake of computational efficiency, we leverage inducing point methods on GPs arising from the mathematical structure of the data giving rise to non-conjugate likelihood-prior pairs. We analyze both synthetic data, where ground truth is known, as well as data drawn from live-cell single-molecule imaging of membrane proteins. The resulting tool provides an unsupervised method to rigorously map diffusion coefficients continuously across membranes without data binning.

Inferring pointwise diffusion properties of single trajectories with deep learning

To characterize the mechanisms governing the diffusion of particles in biological scenarios, it is essential to accurately determine their diffusive properties. To do so, we propose a machine-learning method to characterize diffusion processes with time-dependent properties at the experimental time resolution. Our approach operates at the single-trajectory level predicting the properties of interest, such as the diffusion coefficient or the anomalous diffusion exponent, at every time step of the trajectory. In this way, changes in the diffusive properties occurring along the trajectory emerge naturally in the prediction and thus allow the characterization without any prior knowledge or assumption about the system. We first benchmark the method on synthetic trajectories simulated under several conditions. We show that our approach can successfully characterize both abrupt and continuous changes in the diffusion coefficient or the anomalous diffusion exponent. Finally, we leverage the method to analyze experiments of single-molecule diffusion of two membrane proteins in living cells: the pathogen-recognition receptor DC-SIGN and the integrin α5β1. The analysis allows us to characterize physical parameters and diffusive states with unprecedented accuracy, shedding new light on the underlying mechanisms.

Broadband Plasmonic Nanoantennas for Multi-Color Nanoscale Dynamics in Living Cells

Recently, the implementation of plasmonic nanoantennas has opened new possibilities to investigate the nanoscale dynamics of individual biomolecules in living cells. However, studies so far have been restricted to single molecular species as the narrow wavelength resonance of gold-based nanostructures precludes the simultaneous interrogation of different fluorescently labeled molecules. Here, broadband aluminum-based nanoantennas carved at the apex of near-field probes are exploited to resolve nanoscale-dynamic molecular interactions on living cell membranes. Through multicolor excitation, the authors simultaneously recorded fluorescence fluctuations of dual-color labeled transmembrane receptors known to form nanoclusters. Fluorescence cross-correlation studies revealed transient interactions between individual receptors in regions of ≈60 nm. Moreover, the high signal-to-background ratio provided by the antenna illumination allowed the authors to directly detect fluorescent bursts arising from the passage of individual receptors underneath the antenna. Remarkably, by reducing the illumination volume below the characteristic receptor nanocluster sizes, the molecular diffusion within nanoclusters is resolved and distinguished from nanocluster diffusion. Spatiotemporal characterization of transient interactions between molecules is crucial to understand how they communicate with each other to regulate cell function. This work demonstrates the potential of broadband photonic antennas to study multi-molecular events and interactions in living cell membranes with unprecedented spatiotemporal resolution.

Actin-regulated Siglec-1 nanoclustering influences HIV-1 capture and virus-containing compartment formation in dendritic cells

The immunoglobulin-like lectin receptor CD169 (Siglec-1) mediates the capture of HIV-1 by activated dendritic cells (DC) through binding to sialylated ligands. These interactions result in a more efficient virus capture as compared to resting DCs, although the underlying mechanisms are poorly understood. Using a combination of super-resolution microscopy, single particle tracking and biochemical perturbations we studied the nanoscale organization of Siglec-1 on activated DCs and its impact on viral capture and its trafficking to a single viral-containing compartment. We found that activation of DCs leads to Siglec-1 basal nanoclustering at specific plasma membrane regions where receptor diffusion is constrained by Rho-ROCK activation and formin-dependent actin polymerization. Using liposomes with varying ganglioside concentrations, we further demonstrate that Siglec-1 nanoclustering enhances the receptor avidity to limiting concentrations of gangliosides carrying sialic ligands. Binding to either HIV-1 particles or ganglioside-bearing liposomes lead to enhanced Siglec-1 nanoclustering and global actin rearrangements characterized by a drop in RhoA activity, facilitating the final accumulation of viral particles in a single sac-like compartment. Overall, our work provides new insights on the role of the actin machinery of activated DCs in regulating the formation of basal Siglec-1 nanoclustering, being decisive for the capture and actin-dependent trafficking of HIV-1 into the virus-containing compartment.

Roadmap on Deep Learning for Microscopy

Through digital imaging, microscopy has evolved from primarily being a means for visual observation of life at the micro- and nano-scale, to a quantitative tool with ever-increasing resolution and throughput. Artificial intelligence, deep neural networks, and machine learning are all niche terms describing computational methods that have gained a pivotal role in microscopy-based research over the past decade. This Roadmap is written collectively by prominent researchers and encompasses selected aspects of how machine learning is applied to microscopy image data, with the aim of gaining scientific knowledge by improved image quality, automated detection, segmentation, classification and tracking of objects, and efficient merging of information from multiple imaging modalities. We aim to give the reader an overview of the key developments and an understanding of possibilities and limitations of machine learning for microscopy. It will be of interest to a wide cross-disciplinary audience in the physical sciences and life sciences.

Objective comparison of methods to decode anomalous diffusion

Deviations from Brownian motion leading to anomalous diffusion are found in transport dynamics from quantum physics to life sciences. The characterization of anomalous diffusion from the measurement of an individual trajectory is a challenging task, which traditionally relies on calculating the trajectory mean squared displacement. However, this approach breaks down for cases of practical interest, e.g., short or noisy trajectories, heterogeneous behaviour, or non-ergodic processes. Recently, several new approaches have been proposed, mostly building on the ongoing machine-learning revolution. To perform an objective comparison of methods, we gathered the community and organized an open competition, the Anomalous Diffusion challenge (AnDi). Participating teams applied their algorithms to a commonly-defined dataset including diverse conditions. Although no single method performed best across all scenarios, machine-learning-based approaches achieved superior performance for all tasks. The discussion of the challenge results provides practical advice for users and a benchmark for developers.

Convolutional Neural Network for Skin Lesion Classification: Understanding the Fundamentals Through Hands-On Learning

Deep learning architectures for the classification of images have shown outstanding results in a variety of disciplines, including dermatology. The expectations generated by deep learning for, e.g., image-based diagnosis have created the need for non-experts to become familiar with the working principles of these algorithms. In our opinion, getting hands-on experience with these tools through a simplified but accurate model can facilitate their understanding in an intuitive way. The visualization of the results of the operations performed by deep learning algorithms on dermatological images can help students to grasp concepts like convolution, even without an advanced mathematical background. In addition, the possibility to tune hyperparameters and even to tweak computer code further empower the reach of an intuitive comprehension of these processes, without requiring advanced computational and theoretical skills. This is nowadays possible thanks to recent advances that have helped to lower technical and technological barriers associated with the use of these tools, making them accessible to a broader community. Therefore, we propose a hands-on pedagogical activity that dissects the procedures to train a convolutional neural network on a dataset containing images of skin lesions associated with different skin cancer categories. The activity is available open-source and its execution does not require the installation of software. We further provide a step-by-step description of the algorithm and of its functions, following the development of the building blocks of the computer code, guiding the reader through the execution of a realistic example, including the visualization and the evaluation of the results.

A toolkit for the quantitative evaluation of chronic wounds evolution for early detection of non-healing wounds

BACKGROUND

Chronic wounds resulting from a number of conditions do not heal properly and can pose serious health problems. Beyond clinician visual inspection, an objective evaluation of the wound is required to assess wound evolution and the effectiveness of therapies.

AIM

Our objective is to provide a methodology for the analysis of wound area vs. time for the early prediction of non-healing wounds evolution.

METHODS

We propose a two-step approach consisting of: i) wound area quantification from planimetries and ii) classification of wound healing through the inference of characteristic parameters. For the first step, we describe a user-friendly software (Woundaries) to automatically calculate the wound area and other geometric parameters from hand-traced planimetries. For the second, we use a procedure for the objective classification of wound time evolution and the early assessment of treatment efficacy. The methodology was tested on simulations and retrospectively applied to data from 85 patients to compare the effect of a biological therapy with respect to general basic therapeutics.

RESULTS

Woundaries provides measurements of wound surface equivalent to a validated device. The two-step methodology allows to determine if a wound is healing with high sensitivity, even with limited amount of data. Therefore, it allows the early assessment of the efficacy of a therapy.

CONCLUSION

The performance of this methodology for the quantification and the objective evaluation of wound area evolution suggest it as a useful toolkit to assist clinicians in the early assessment of the efficacy of treatments, leading to a timely change of therapy.

Clinical practice guidelines for patients with polymyalgia rheumatica: the need for an active involvement of all stakeholder is still unmet

Not available.

Direct and Fast Assessment of Antimicrobial Surface Activity Using Molecular Dynamics Simulation and Time-Lapse Imaging

With the alarming rise of antimicrobial resistance, studies on bacteria-surface interactions are both relevant and timely. Scanning electron microscopy and colony forming unit counting are commonly used techniques but require sophisticated sample preparation and long incubation time. Here, we present a direct method based on molecular dynamics simulation of nanostructured surfaces providing in silico predictions, complemented with time-lapse fluorescence imaging to study live interactions of bacteria at the membrane-substrate level. We evaluate its effectiveness in predicting and statistically analyzing the temporal evolution and spatial distribution of prototypical bacteria with costained nucleoids and membranes (E. coli) on surfaces with nanopillars. We observed cell reorientation, clustering, membrane damage, growth inhibition, and in the extreme case of hydrocarbon-coated nanopillars, this was followed by cell disappearance, validating the obtained simulation results. Contrary to commonly used experimental methods, microscopy data are fast processed, in less than 1 h. In particular, the bactericidal effects can be straightforwardly detected and correlated with surface morphology and/or wettability.

Bayesian analysis of data from segmented super-resolution images for quantifying protein clustering

Super-resolution imaging techniques have largely improved our capabilities to visualize nanometric structures in biological systems. Their application further permits the quantitation relevant parameters to determine the molecular organization and stoichiometry in cells. However, the inherently stochastic nature of fluorescence emission and labeling strategies imposes the use of dedicated methods to accurately estimate these parameters. Here, we describe a Bayesian approach to precisely quantitate the relative abundance of molecular aggregates of different stoichiometry from segmented images. The distribution of proxies for the number of molecules in a cluster, such as the number of localizations or the fluorescence intensity, is fitted via a nested sampling algorithm to compare mixture models of increasing complexity and thus determine the optimum number of mixture components and their weights. We test the performance of the algorithm on in silico data as a function of the number of data points, threshold, and distribution shape. We compare these results to those obtained with other statistical methods, showing the improved performance of our approach. Our method provides a robust tool for model selection in fitting data extracted from fluorescence imaging, thus improving the precision of parameter determination. Importantly, the largest benefit of this method occurs for small-statistics or incomplete datasets, enabling an accurate analysis at the single image level. We further present the results of its application to experimental data obtained from the super-resolution imaging of dynein in HeLa cells, confirming the presence of a mixed population of cytoplasmic single motors and higher-order structures.

Dynamic actin-mediated nano-scale clustering of CD44 regulates its meso-scale organization at the plasma membrane

Transmembrane adhesion receptors at the cell surface, such as CD44, are often equipped with modules to interact with the extracellular matrix (ECM) and the intracellular cytoskeletal machinery. CD44 has been recently shown to compartmentalize the membrane into domains by acting as membrane pickets, facilitating the function of signaling receptors. While spatial organization and diffusion studies of membrane proteins are usually conducted separately, here we combine observations of organization and diffusion by using high spatio-temporal resolution imaging on living cells to reveal a hierarchical organization of CD44. CD44 is present in a meso-scale meshwork pattern where it exhibits enhanced confinement and is enriched in nanoclusters of CD44 along its boundaries. This nanoclustering is orchestrated by the underlying cortical actin dynamics. Interaction with actin is mediated by specific segments of the intracellular domain. This influences the organization of the protein at the nano-scale, generating a selective requirement for formin over Arp2/3-based actin-nucleation machinery. The extracellular domain and its interaction with elements of ECM do not influence the meso-scale organization, but may serve to reposition the meshwork with respect to the ECM. Taken together, our results capture the hierarchical nature of CD44 organization at the cell surface, with active cytoskeleton-templated nanoclusters localized to a meso-scale meshwork pattern.

PLANT: A Method for Detecting Changes of Slope in Noisy Trajectories

Time traces obtained from a variety of biophysical experiments contain valuable information on underlying processes occurring at the molecular level. Accurate quantification of these data can help explain the details of the complex dynamics of biological systems. Here, we describe PLANT (Piecewise Linear Approximation of Noisy Trajectories), a segmentation algorithm that allows the reconstruction of time-trace data with constant noise as consecutive straight lines, from which changes of slopes and their respective durations can be extracted. We present a general description of the algorithm and perform extensive simulations to characterize its strengths and limitations, providing a rationale for the performance of the algorithm in the different conditions tested. We further apply the algorithm to experimental data obtained from tracking the centroid position of lymphocytes migrating under the effect of a laminar flow and from single myosin molecules interacting with actin in a dual-trap force-clamp configuration.

Separating Actin-Dependent Chemokine Receptor Nanoclustering from Dimerization Indicates a Role for Clustering in CXCR4 Signaling and Function

A current challenge in cell motility studies is to understand the molecular and physical mechanisms that govern chemokine receptor nanoscale organization at the cell membrane, and their influence on cell response. Using single-particle tracking and super-resolution microscopy, we found that the chemokine receptor CXCR4 forms basal nanoclusters in resting T cells, whose extent, dynamics, and signaling strength are modulated by the orchestrated action of the actin cytoskeleton, the co-receptor CD4, and its ligand CXCL12. We identified three CXCR4 structural residues that are crucial for nanoclustering and generated an oligomerization-defective mutant that dimerized but did not form nanoclusters in response to CXCL12, which severely impaired signaling. Overall, our data provide new insights to the field of chemokine biology by showing that receptor dimerization in the absence of nanoclustering is unable to fully support CXCL12-mediated responses, including signaling and cell function in vivo.

Inhomogeneous membrane receptor diffusion explained by a fractional heteroscedastic time series model

A fractional heteroscedastic time series model explains inhomogeneous membrane receptor diffusion and interprets ergodicity when the diffusion parameter fluctuates in time.

C1q Solid-Phase Enzymatic Microassay for Detection of Circulating Immune Complexes: Its Application in Human Breast Cancer

Circulating immune complexes (CIC) were detected and quantitated in human breast cancer to monitor the efficiency of mastectomy. For this aim a microimmunoenzymatic test was set up, applying a solid-phase C1q. Features of this assay can be summarized as follows: ability to estimate as low as 10 ng of aggregated human IgG (ΔIgG), good reproducibility and simplicity of execution, and small serum sample required. A group of women with breast cancer at different stages (TNM classification) was tested for CIC, and 31.75 % were positive. Almost all patients submitted to surgery showed a reduction of this parameter thereafter. A parallel study was carried out in another group of women with benign breast disease, and a significant incidence of CIC was found.

The role of the general practitioner and the out-of-hospital public rheumatologist in the diagnosis and follow-up of patients with polymyalgia rheumatica

Polymyalgia rheumatica (PMR) is a chronic inflammatory disease characterized by shoulder and pelvic girdle pain. Its onset peaks around the age of 75; the prevalence increases until the age of 90 and it is more frequent in females. Diagnosis is mostly performed on the basis of symptoms. An increase of serum inflammatory markers is indicative, but not essential, while therapy is mainly based on glucocorticoids. Since there is no universal agreement about diagnostic criteria for PMR, its detection is still difficult. There are discordant opinions about the fact that PMR can be recognised and managed by general practitioners (GPs), while patients with atypical features need to be referred to the rheumatologist. In the Italian setting, the absence of recent epidemiological studies is associated with the total lack of a research protocol in primary care, from which relevant information could be derived. The out-of-hospital public rheumatologist is a peculiar figure of the Italian National Health System, who takes care of outpatients. Although differences between the different Italian regional health services exist, this professional figure has proved to be effective in reducing delay and increasing accuracy in PMR diagnosis.

Cannabis through the looking glass: chemo- and enantio-selective separation of phytocannabinoids by enantioselective ultra high performance supercritical fluid chromatography

By using the Inverted Chirality Columns Approach (ICCA) we have developed an enantioselective UHPSFC method to determine the enantiomeric excess (ee) of (-)-Δ⁹-THC in medicinal marijuana (Bedrocan®). The ee was high (99.73%), but the concentration of the (+)-enantiomer (0.13₅%) was not negligible, and it is worth a systematic evaluation of bioactivity.

Transient subdiffusion from an Ising environment

We introduce a model in which a particle performs a continuous-time random walk (CTRW) coupled to an environment with Ising dynamics. The particle shows locally varying diffusivity determined by the geometrical properties of the underlying Ising environment, that is, the diffusivity depends on the size of the connected area of spins pointing in the same direction. The model shows anomalous diffusion when the Ising environment is at critical temperature. We show that any finite scale introduced by a temperature different from the critical one, or a finite size of the environment, cause subdiffusion only during a transient time. The characteristic time, at which the system returns to normal diffusion after the subdiffusive plateau depends on the limiting scale and on how close the temperature is to criticality. The system also displays apparent ergodicity breaking at intermediate time, while ergodicity breaking at longer time occurs only under the idealized infinite environment at the critical temperature.

Planar Optical Nanoantennas Resolve Cholesterol-Dependent Nanoscale Heterogeneities in the Plasma Membrane of Living Cells

Optical nanoantennas can efficiently confine light into nanoscopic hotspots, enabling single-molecule detection sensitivity at biological relevant conditions. This innovative approach to breach the diffraction limit offers a versatile platform to investigate the dynamics of individual biomolecules in living cell membranes and their partitioning into cholesterol-dependent lipid nanodomains. Here, we present optical nanoantenna arrays with accessible surface hotspots to study the characteristic diffusion dynamics of phosphoethanolamine (PE) and sphingomyelin (SM) in the plasma membrane of living cells at the nanoscale. Fluorescence burst analysis and fluorescence correlation spectroscopy performed on nanoantennas of different gap sizes show that, unlike PE, SM is transiently trapped in cholesterol-enriched nanodomains of 10 nm diameter with short characteristic times around 100 μs. The removal of cholesterol led to the free diffusion of SM, consistent with the dispersion of nanodomains. Our results are consistent with the existence of highly transient and fluctuating nanoscale assemblies enriched by cholesterol and sphingolipids in living cell membranes, also known as lipid rafts. Quantitative data on sphingolipids partitioning into lipid rafts is crucial to understand the spatiotemporal heterogeneous organization of transient molecular complexes on the membrane of living cells at the nanoscale. The proposed technique is fully biocompatible and thus provides various opportunities for biophysics and live cell research to reveal details that remain hidden in confocal diffraction-limited measurements.

A DNA origami platform for quantifying protein copy number in super-resolution

Single-molecule-based super-resolution microscopy offers a unique opportunity for quantifying protein copy-number with nanoscale resolution. However, while fluorescent proteins have been characterized for quantitative imaging using calibration standards, similar calibration tools for immunofluorescence with small organic fluorophores are lacking. Here, we show that DNA origami in combination with GFP antibodies is a versatile platform for calibrating fluorophore and antibody labeling efficiency to quantify protein copy-number in cellular contexts using super-resolution microscopy.

Top-down approach from satellite to terrestrial rover application for environmental monitoring of landfills

This paper describes a methodology to perform chemical analyses in landfill areas by integrating multisource geomatic data. We used a top-down approach to identify Environmental Point of Interest (EPI) based on very high-resolution satellite data (Pleiades and WorldView 2) and on in situ thermal and photogrammetric surveys. Change detection techniques and geostatistical analysis supported the chemical survey, undertaken using an accumulation chamber and an RIIA, an unmanned ground vehicle developed by CNR IIA, equipped with a multiparameter sensor platform for environmental monitoring. Such an approach improves site characterization, identifying the key environmental points of interest where it is necessary to perform detailed chemical analyses.

Nonergodic subdiffusion from transient interactions with heterogeneous partners

Spatiotemporal disorder has been recently associated to the occurrence of anomalous nonergodic diffusion of molecular components in biological systems, but the underlying microscopic mechanism is still unclear. We introduce a model in which a particle performs continuous Brownian motion with changes of diffusion coefficients induced by transient molecular interactions with diffusive binding partners. In spite of the exponential distribution of waiting times, the model shows subdiffusion and nonergodicity similar to the heavy-tailed continuous time random walk. The dependence of these properties on the density of binding partners is analyzed and discussed. Our work provides an experimentally testable microscopic model to investigate the nature of nonergodicity in disordered media.

Fractional kinetics emerging from ergodicity breaking in random media

We present a modeling approach for diffusion in a complex medium characterized by a random length scale. The resulting stochastic process shows subdiffusion with a behavior in qualitative agreement with single-particle tracking experiments in living cells, such as ergodicity breaking, p variation, and aging. In particular, this approach recapitulates characteristic features previously described in part by the fractional Brownian motion and in part by the continuous-time random walk. Moreover, for a proper distribution of the length scale, a single parameter controls the ergodic-to-nonergodic transition and, remarkably, also drives the transition of the diffusion equation of the process from nonfractional to fractional, thus demonstrating that fractional kinetics emerges from ergodicity breaking.

Lateral Mobility and Nanoscale Spatial Arrangement of Chemokine-activated α4β1 Integrins on T Cells

Chemokine stimulation of integrin α4β1-dependent T lymphocyte adhesion is a key step during lymphocyte trafficking. A central question regarding α4β1 function is how its lateral mobility and organization influence its affinity and avidity following cell stimulation with chemokines and/or ligands. Using single particle tracking and superresolution imaging approaches, we explored the lateral mobility and spatial arrangement of individual α4β1integrins on T cells exposed to different activating stimuli. We show that CXCL12 stimulation leads to rapid and transient α4β1activation, measured by induction of the activation epitope recognized by the HUTS-21 anti-β1antibody and by increased talin-β1 association. CXCL12-dependent α4β1 activation directly correlated with restricted lateral diffusion and integrin immobilization. Moreover, co-stimulation by CXCL12 together with soluble VCAM-1 potentiated integrin immobilization with a 5-fold increase in immobile integrins compared with unstimulated conditions. Our data indicate that docking by talin of the chemokine-activated α4β1 to the actin cytoskeleton favors integrin immobilization, which likely facilitates ligand interaction and increased adhesiveness. Superresolution imaging showed that the nanoscale organization of high-affinity α4β1 remains unaffected following chemokine and/or ligand addition. Instead, newly activated α4β1 integrins organize on the cell membrane as independent units without joining pre-established integrin sites to contribute to cluster formation. Altogether, our results provide a rationale to understand how the spatiotemporal organization of activated α4β1 integrins regulates T lymphocyte adhesion.

Changes in membrane sphingolipid composition modulate dynamics and adhesion of integrin nanoclusters

Sphingolipids are essential constituents of the plasma membrane (PM) and play an important role in signal transduction by modulating clustering and dynamics of membrane receptors. Changes in lipid composition are therefore likely to influence receptor organisation and function, but how this precisely occurs is difficult to address given the intricacy of the PM lipid-network. Here, we combined biochemical assays and single molecule dynamic approaches to demonstrate that the local lipid environment regulates adhesion of integrin receptors by impacting on their lateral mobility. Induction of sphingomyelinase (SMase) activity reduced sphingomyelin (SM) levels by conversion to ceramide (Cer), resulting in impaired integrin adhesion and reduced integrin mobility. Dual-colour imaging of cortical actin in combination with single molecule tracking of integrins showed that this reduced mobility results from increased coupling to the actin cytoskeleton brought about by Cer formation. As such, our data emphasizes a critical role for the PM local lipid composition in regulating the lateral mobility of integrins and their ability to dynamically increase receptor density for efficient ligand binding in the process of cell adhesion.

The actin cytoskeleton modulates the activation of iNKT cells by segregating CD1d nanoclusters on antigen-presenting cells

Invariant natural killer T (iNKT) cells recognize endogenous and exogenous lipid antigens presented in the context of CD1d molecules. The ability of iNKT cells to recognize endogenous antigens represents a distinct immune recognition strategy, which underscores the constitutive memory phenotype of iNKT cells and their activation during inflammatory conditions. However, the mechanisms regulating such "tonic" activation of iNKT cells remain unclear. Here, we show that the spatiotemporal distribution of CD1d molecules on the surface of antigen-presenting cells (APCs) modulates activation of iNKT cells. By using superresolution microscopy, we show that CD1d molecules form nanoclusters at the cell surface of APCs, and their size and density are constrained by the actin cytoskeleton. Dual-color single-particle tracking revealed that diffusing CD1d nanoclusters are actively arrested by the actin cytoskeleton, preventing their further coalescence. Formation of larger nanoclusters occurs in the absence of interactions between CD1d cytosolic tail and the actin cytoskeleton and correlates with enhanced iNKT cell activation. Importantly and consistently with iNKT cell activation during inflammatory conditions, exposure of APCs to the Toll-like receptor 7/8 agonist R848 increases nanocluster density and iNKT cell activation. Overall, these results define a previously unidentified mechanism that modulates iNKT cell autoreactivity based on the tight control by the APC cytoskeleton of the sizes and densities of endogenous antigen-loaded CD1d nanoclusters.

A review of progress in single particle tracking: from methods to biophysical insights

Optical microscopy has for centuries been a key tool to study living cells with minimum invasiveness. The advent of single molecule techniques over the past two decades has revolutionized the field of cell biology by providing a more quantitative picture of the complex and highly dynamic organization of living systems. Amongst these techniques, single particle tracking (SPT) has emerged as a powerful approach to study a variety of dynamic processes in life sciences. SPT provides access to single molecule behavior in the natural context of living cells, thereby allowing a complete statistical characterization of the system under study. In this review we describe the foundations of SPT together with novel optical implementations that nowadays allow the investigation of single molecule dynamic events with increasingly high spatiotemporal resolution using molecular densities closer to physiological expression levels. We outline some of the algorithms for the faithful reconstruction of SPT trajectories as well as data analysis, and highlight biological examples where the technique has provided novel insights into the role of diffusion regulating cellular function. The last part of the review concentrates on different theoretical models that describe anomalous transport behavior and ergodicity breaking observed from SPT studies in living cells.

Large-Scale Arrays of Bowtie Nanoaperture Antennas for Nanoscale Dynamics in Living Cell Membranes

We present a novel blurring-free stencil lithography patterning technique for high-throughput fabrication of large-scale arrays of nanoaperture optical antennas. The approach relies on dry etching through nanostencils to achieve reproducible and uniform control of nanoantenna geometries at the nanoscale, over millimeter-sizes in a thin aluminum film. We demonstrate the fabrication of over 400 000 bowtie nanoaperture (BNA) antennas on biocompatible substrates, having gap sizes ranging from (80 ± 5) nm down to (20 ± 10) nm. To validate their applicability on live cell research, we used the antenna substrates as hotspots of localized illumination to excite fluorescently labeled lipids on living cell membranes. The high signal-to-background afforded by the BNA arrays allowed the recording of single fluorescent bursts corresponding to the passage of freely diffusing individual lipids through hotspot excitation regions as small as 20 nm. Statistical analysis of burst length and intensity together with simulations demonstrate that the measured signals arise from the ultraconfined excitation region of the antennas. Because these inexpensive antenna arrays are fully biocompatible and amenable to their integration in most fluorescence microscopes, we foresee a large number of applications including the investigation of the plasma membrane of living cells with nanoscale resolution at endogenous expression levels.

Chromatin fibers are formed by heterogeneous groups of nucleosomes in vivo

Nucleosomes help structure chromosomes by compacting DNA into fibers. To gain insight into how nucleosomes are arranged in vivo, we combined quantitative super-resolution nanoscopy with computer simulations to visualize and count nucleosomes along the chromatin fiber in single nuclei. Nucleosomes assembled in heterogeneous groups of varying sizes, here termed "clutches," and these were interspersed with nucleosome-depleted regions. The median number of nucleosomes inside clutches and their compaction defined as nucleosome density were cell-type-specific. Ground-state pluripotent stem cells had, on average, less dense clutches containing fewer nucleosomes and clutch size strongly correlated with the pluripotency potential of induced pluripotent stem cells. RNA polymerase II preferentially associated with the smallest clutches while linker histone H1 and heterochromatin were enriched in the largest ones. Our results reveal how the chromatin fiber is formed at nanoscale level and link chromatin fiber architecture to stem cell state.

Enhanced tethered-particle motion analysis reveals viscous effects

Tethered-particle motion experiments do not require expensive or technically complex hardware, and increasing numbers of researchers are adopting this methodology to investigate the topological effects of agents that act on the tethering polymer or the characteristics of the polymer itself. These investigations depend on accurate measurement and interpretation of changes in the effective length of the tethering polymer (often DNA). However, the bead size, tether length, and buffer affect the confined diffusion of the bead in this experimental system. To evaluate the effects of these factors, improved measurements to calibrate the two-dimensional range of motion (excursion) versus DNA length were carried out. Microspheres of 160 or 240 nm in radius were tethered by DNA molecules ranging from 225 to 3477 basepairs in length in aqueous buffers containing 100 mM potassium glutamate and 8 mM MgCl2 or 10 mM Tris-HCl and 200 mM KCl, with or without 0.5% Tween added to the buffer, and the motion was recorded. Different buffers altered the excursion of beads on identical DNA tethers. Buffer with only 10 mM NaCl and >5 mM magnesium greatly reduced excursion. Glycerol added to increase viscosity slowed confined diffusion of the tethered beads but did not change excursion. The confined-diffusion coefficients for all tethered beads were smaller than those expected for freely diffusing beads and decreased for shorter tethers. Tethered-particle motion is a sensitive framework for diffusion experiments in which small beads on long leashes most closely resemble freely diffusing, untethered beads.

Priming by chemokines restricts lateral mobility of the adhesion receptor LFA-1 and restores adhesion to ICAM-1 nano-aggregates on human mature dendritic cells

LFA-1 is a leukocyte specific β2 integrin that plays a major role in regulating adhesion and migration of different immune cells. Recent data suggest that LFA-1 on mature dendritic cells (mDCs) may function as a chemokine-inducible anchor during homing of DCs through the afferent lymphatics into the lymph nodes, by transiently switching its molecular conformational state. However, the role of LFA-1 mobility in this process is not yet known, despite that the importance of lateral organization and dynamics for LFA-1-mediated adhesion regulation is broadly recognized. Using single particle tracking approaches we here show that LFA-1 exhibits higher mobility on resting mDCs compared to monocytes. Lymphoid chemokine CCL21 stimulation of the LFA-1 high affinity state on mDCs, led to a significant reduction of mobility and an increase on the fraction of stationary receptors, consistent with re-activation of the receptor. Addition of soluble monomeric ICAM-1 in the presence of CCL21 did not alter the diffusion profile of LFA-1 while soluble ICAM-1 nano-aggregates in the presence of CCL21 further reduced LFA-1 mobility and readily bound to the receptor. Overall, our results emphasize the importance of LFA-1 lateral mobility across the membrane on the regulation of integrin activation and its function as adhesion receptor. Importantly, our data show that chemokines alone are not sufficient to trigger the high affinity state of the integrin based on the strict definition that affinity refers to the adhesion capacity of a single receptor to its ligand in solution. Instead our data indicate that nanoclustering of the receptor, induced by multi-ligand binding, is required to maintain stable cell adhesion once LFA-1 high affinity state is transiently triggered by inside-out signals.

Nonergodic subdiffusion from Brownian motion in an inhomogeneous medium

Nonergodicity observed in single-particle tracking experiments is usually modeled by transient trapping rather than spatial disorder. We introduce models of a particle diffusing in a medium consisting of regions with random sizes and random diffusivities. The particle is never trapped but rather performs continuous Brownian motion with the local diffusion constant. Under simple assumptions on the distribution of the sizes and diffusivities, we find that the mean squared displacement displays subdiffusion due to nonergodicity for both annealed and quenched disorder. The model is formulated as a walk continuous in both time and space, similar to the Lévy walk.

MADS domain transcription factors mediate short-range DNA looping that is essential for target gene expression in Arabidopsis

MADS domain transcription factors are key regulators of eukaryotic development. In plants, the homeotic MIKC MADS factors that regulate floral organ identity have been studied in great detail. Based on genetic and protein-protein interaction studies, a floral quartet model was proposed that describes how these MADS domain proteins assemble into higher order complexes to regulate their target genes. However, despite the attractiveness of this model and its general acceptance in the literature, solid in vivo proof has never been provided. To gain deeper insight into the mechanisms of transcriptional regulation by MADS domain factors, we studied how SEEDSTICK (STK) and SEPALLATA3 (SEP3) directly regulate the expression of the reproductive meristem gene family transcription factor-encoding gene VERDANDI (VDD). Our data show that STK-SEP3 dimers can induce loop formation in the VDD promoter by binding to two nearby CC(A/T)6GG (CArG) boxes and that this is essential for promoter activity. Our in vivo data show that the size and position of this loop, determined by the choice of CArG element usage, is essential for correct expression. Our studies provide solid in vivo evidence for the floral quartet model.

The effect of nonspecific binding of lambda repressor on DNA looping dynamics

The λ repressor (CI) protein-induced DNA loop maintains stable lysogeny, yet allows efficient switching to lysis. Herein, the kinetics of loop formation and breakdown has been characterized at various concentrations of protein using tethered particle microscopy and a novel, to our knowledge, method of analysis. Our results show that a broad distribution of rate constants and complex kinetics underlie loop formation and breakdown. In addition, comparison of the kinetics of looping in wild-type DNA and DNA with mutated o3 operators showed that these sites may trigger nucleation of nonspecific binding at the closure of the loop. The average activation energy calculated from the rate constant distribution is consistent with a model in which nonspecific binding of CI between the operators shortens their effective separation, thereby lowering the energy barrier for loop formation and broadening the rate constant distribution for looping. Similarly, nonspecific binding affects the kinetics of loop breakdown by increasing the number of loop-securing protein interactions, and broadens the rate constant distribution for this reaction. Therefore, simultaneous increase of the rate constant for loop formation and reduction of that for loop breakdown stabilizes lysogeny. Given these simultaneous changes, the frequency of transitions between the looped and the unlooped state remains nearly constant. Although the loop becomes more stable thermodynamically with increasing CI concentration, it still opens periodically, conferring sensitivity to environmental changes, which may require switching to lytic conditions.

The neck region of the C-type lectin DC-SIGN regulates its surface spatiotemporal organization and virus-binding capacity on antigen-presenting cells

The C-type lectin DC-SIGN expressed on dendritic cells (DCs) facilitates capture and internalization of a plethora of different pathogens. Although it is known that DC-SIGN organizes in nanoclusters at the surface of DCs, the molecular mechanisms responsible for this well defined nanopatterning and role in viral binding remain enigmatic. By combining biochemical and advanced biophysical techniques, including optical superresolution and single particle tracking, we demonstrate that DC-SIGN intrinsic nanoclustering strictly depends on its molecular structure. DC-SIGN nanoclusters exhibited free, Brownian diffusion on the cell membrane. Truncation of the extracellular neck region, known to abrogate tetramerization, significantly reduced nanoclustering and concomitantly increased lateral diffusion. Importantly, DC-SIGN nanocluster dissolution exclusively compromised binding to nanoscale size pathogens. Monte Carlo simulations revealed that heterogeneity on nanocluster density and spatial distribution confers broader binding capabilities to DC-SIGN. As such, our results underscore a direct relationship between spatial nanopatterning, driven by intermolecular interactions between the neck regions, and receptor diffusion to provide DC-SIGN with the exquisite ability to dock pathogens at the virus length scale. Insight into how virus receptors are organized prior to virus binding and how they assemble into functional platforms for virus docking is helpful to develop novel strategies to prevent virus entry and infection.

Geometry sensing by dendritic cells dictates spatial organization and PGE(2)-induced dissolution of podosomes

Assembly and disassembly of adhesion structures such as focal adhesions (FAs) and podosomes regulate cell adhesion and differentiation. On antigen-presenting dendritic cells (DCs), acquisition of a migratory and immunostimulatory phenotype depends on podosome dissolution by prostaglandin E₂ (PGE₂). Whereas the effects of physico-chemical and topographical cues have been extensively studied on FAs, little is known about how podosomes respond to these signals. Here, we show that, unlike for FAs, podosome formation is not controlled by substrate physico-chemical properties. We demonstrate that cell adhesion is the only prerequisite for podosome formation and that substrate availability dictates podosome density. Interestingly, we show that DCs sense 3-dimensional (3-D) geometry by aligning podosomes along the edges of 3-D micropatterned surfaces. Finally, whereas on a 2-dimensional (2-D) surface PGE₂ causes a rapid increase in activated RhoA levels leading to fast podosome dissolution, 3-D geometric cues prevent PGE₂-mediated RhoA activation resulting in impaired podosome dissolution even after prolonged stimulation. Our findings indicate that 2-D and 3-D geometric cues control the spatial organization of podosomes. More importantly, our studies demonstrate the importance of substrate dimensionality in regulating podosome dissolution and suggest that substrate dimensionality plays an important role in controlling DC activation, a key process in initiating immune responses.

Nanoscale fluorescence correlation spectroscopy on intact living cell membranes with NSOM probes

Characterization of molecular dynamics on living cell membranes at the nanoscale is fundamental to unravel the mechanisms of membrane organization and compartmentalization. Here we demonstrate the feasibility of fluorescence correlation spectroscopy (FCS) based on the nanometric illumination of near-field scanning optical microscopy (NSOM) probes on intact living cells. NSOM-FCS applied to fluorescent lipid analogs allowed us to reveal details of the diffusion hidden by larger illumination areas. Moreover, the technique offers the unique advantages of evanescent axial illumination and straightforward implementation of multiple color excitation. As such, NSOM-FCS represents a powerful tool to study a variety of dynamic processes occurring at the nanometer scale on cell membranes.