Glycosylation-Dependent IFN-γR Partitioning in Lipid and Actin Nanodomains Is Critical for JAK Activation.

Understanding how membrane nanoscale organization controls transmembrane receptors signaling activity remains a challenge. We studied interferon-γ receptor (IFN-γR) signaling in fibroblasts from homozygous patients with a T168N mutation in IFNGR2. By adding a neo-N-glycan on IFN-γR2 subunit, this mutation blocks IFN-γ activity by unknown mechanisms. We show that the lateral diffusion of IFN-γR2 is confined by sphingolipid/cholesterol nanodomains. In contrast, the IFN-γR2 T168N mutant diffusion is confined by distinct actin nanodomains where conformational changes required for Janus-activated tyrosine kinase/signal transducer and activator of transcription (JAK/STAT) activation by IFN-γ could not occur. Removing IFN-γR2 T168N-bound galectins restored lateral diffusion in lipid nanodomains and JAK/STAT signaling in patient cells, whereas adding galectins impaired these processes in control cells. These experiments prove the critical role of dynamic receptor interactions with actin and lipid nanodomains and reveal a new function for receptor glycosylation and galectins. Our study establishes the physiological relevance of membrane nanodomains in the control of transmembrane receptor signaling in vivo. VIDEO ABSTRACT.

Quantitative nanoscale imaging of orientational order in biological filaments by polarized superresolution microscopy.

Essential cellular functions as diverse as genome maintenance and tissue morphogenesis rely on the dynamic organization of filamentous assemblies. For example, the precise structural organization of DNA filaments has profound consequences on all DNA-mediated processes including gene expression, whereas control over the precise spatial arrangement of cytoskeletal protein filaments is key for mechanical force generation driving animal tissue morphogenesis. Polarized fluorescence is currently used to extract structural organization of fluorescently labeled biological filaments by determining the orientation of fluorescent labels, however with a strong drawback: polarized fluorescence imaging is indeed spatially limited by optical diffraction, and is thus unable to discriminate between the intrinsic orientational mobility of the fluorophore labels and the real structural disorder of the labeled biomolecules. Here, we demonstrate that quantitative single-molecule polarized detection in biological filament assemblies allows not only to correct for the rotational flexibility of the label but also to image orientational order of filaments at the nanoscale using superresolution capabilities. The method is based on polarized direct stochastic optical reconstruction microscopy, using dedicated optical scheme and image analysis to determine both molecular localization and orientation with high precision. We apply this method to double-stranded DNA in vitro and microtubules and actin stress fibers in whole cells.

A Theoretical High-Density Nanoscopy Study Leads to the Design of UNLOC, a Parameter-free Algorithm.

Single-molecule localization microscopy (SMLM) enables the production of high-resolution images by imaging spatially isolated fluorescent particles. Although challenging, the result of SMLM analysis lists the position of individual molecules, leading to a valuable quantification of the stoichiometry and spatial organization of molecular actors. Both the signal/noise ratio and the density (Dframe), i.e., the number of fluorescent particles per µm2 per frame, have previously been identified as determining factors for reaching a given SMLM precision. Establishing a comprehensive theoretical study relying on these two parameters is therefore of central interest to delineate the achievable limits for accurate SMLM observations. Our study reports that in absence of prior knowledge of the signal intensity α, the density effect on particle localization is more prominent than that anticipated from theoretical studies performed at known α. A first limit appears when, under a low-density hypothesis (i.e., one-Gaussian fitting hypothesis), any fluorescent particle distant by less than ∼600 nm from the particle of interest biases its localization. In fact, all particles should be accounted for, even those dimly fluorescent, to ascertain unbiased localization of any surrounding particles. Moreover, even under a high-density hypothesis (i.e., multi-Gaussian fitting hypothesis), a second limit arises because of the impossible distinction of particles located too closely. An increase in Dframe is thus likely to deteriorate the localization precision, the image reconstruction, and more generally the quantification accuracy. Our study firstly provides a density-signal/noise ratio space diagram for use as a guide in data recording toward reaching an achievable SMLM resolution. Additionally, it leads to the identification of the essential requirements for implementing UNLOC, a parameter-free and fast computing algorithm approaching the Cramér-Rao bound for particles at high-density per frame and without any prior knowledge of their intensity. UNLOC is available as an ImageJ plugin.

Comparison of different active polarimetric imaging modes for target detection in outdoor environment.

We address the detection of manufactured objects in different types of environments with active polarimetric imaging. Using an original, fully adaptive imager, we compare several imaging modes having different numbers of polarimetric degrees of freedom. We demonstrate the efficiency of active polarimetric imaging for decamouflage and hazardous object detection, and underline the characteristics that a polarimetric imager aimed at this type of application should possess. We show that in most encountered scenarios the Mueller matrices are nearly diagonal, and sufficient detection performance can be obtained with simple polarimetric imaging systems having reduced degrees of freedom. Moreover, intensity normalization of images is of paramount importance to better reveal polarimetric contrast.

Active polarimetric imager with near infrared laser illumination for adaptive contrast optimization.

We designed and built an active polarimetric imager with laser illumination at 1.5 µm wavelength for adaptive polarimetric contrast optimization. It can generate and analyze any polarization state on the Poincaré sphere in order to best adapt to the polarimetric properties of the scene. Polarimetric contrast optimization is performed by analyzing the scene with an ultrafast active-contour-based segmentation algorithm. This device is, to the best of our knowledge, the first fully adaptive imager controlled by image processing algorithms for polarimetric contrast enhancement. Its capabilities are illustrated in some examples of real-world decamouflage applications.

Barcoding T cell calcium response diversity with methods for automated and accurate analysis of cell signals (MAAACS).

We introduce a series of experimental procedures enabling sensitive calcium monitoring in T cell populations by confocal video-microscopy. Tracking and post-acquisition analysis was performed using Methods for Automated and Accurate Analysis of Cell Signals (MAAACS), a fully customized program that associates a high throughput tracking algorithm, an intuitive reconnection routine and a statistical platform to provide, at a glance, the calcium barcode of a population of individual T-cells. Combined with a sensitive calcium probe, this method allowed us to unravel the heterogeneity in shape and intensity of the calcium response in T cell populations and especially in naive T cells, which display intracellular calcium oscillations upon stimulation by antigen presenting cells.

Joint contrast optimization and object segmentation in active polarimetric images.

We present a method for automatic target detection based on the iterative interplay between an active polarimetric imager with adaptive capabilities and a snake-based image segmentation algorithm. It successfully addresses the difficult situations where the target and the background differ only by their polarimetric properties. This method illustrates the benefits of integrating digital processing algorithms at the heart of the image acquisition process rather than using them only for postprocessing.

Dynamic multiple-target tracing to probe spatiotemporal cartography of cell membranes.

Although the highly dynamic and mosaic organization of the plasma membrane is well-recognized, depicting a resolved, global view of this organization remains challenging. We present an analytical single-particle tracking (SPT) method and tool, multiple-target tracing (MTT), that takes advantage of the high spatial resolution provided by single-fluorophore sensitivity. MTT can be used to generate dynamic maps at high densities of tracked particles, thereby providing global representation of molecular dynamics in cell membranes. Deflation by subtracting detected peaks allows detection of lower-intensity peaks. We exhaustively detected particles using MTT, with performance reaching theoretical limits, and then reconnected trajectories integrating the statistical information from past trajectories. We demonstrate the potential of this method by applying it to the epidermal growth factor receptor (EGFR) labeled with quantum dots (Qdots), in the plasma membrane of live cells. We anticipate the use of MTT to explore molecular dynamics and interactions at the cell membrane.

Spot Variation Fluorescence Correlation Spectroscopy for Analysis of Molecular Diffusion at the Plasma Membrane of Living Cells.

Dynamic biological processes in living cells, including those associated with plasma membrane organization, occur on various spatial and temporal scales, ranging from nanometers to micrometers and microseconds to minutes, respectively. Such a broad range of biological processes challenges conventional microscopy approaches. Here, we detail the procedure for implementing spot variation Fluorescence Correlation Spectroscopy (svFCS) measurements using a classical fluorescence microscope that has been customized. The protocol includes a specific performance check of the svFCS setup and the guidelines for molecular diffusion measurements by svFCS on the plasma membrane of living cells under physiological conditions. Additionally, we provide a procedure for disrupting plasma membrane raft nanodomains by cholesterol oxidase treatment and demonstrate how these changes in the lateral organization of the plasma membrane might be revealed by svFCS analysis. In conclusion, this fluorescence-based method can provide unprecedented details on the lateral organization of the plasma membrane with the appropriate spatial and temporal resolution.

Influence of multiple scattering on the resolution of an imaging system: a Cramér-Rao analysis.

We revisit the notion of resolution of an imaging system in the light of a probabilistic concept, the Cramér-Rao bound (CRB). We show that the CRB provides a simple quantitative estimation of the accuracy one can expect in measuring an unknown parameter from a scattering experiment. We then investigate the influence of multiple scattering on the CRB for the estimation of the interdistance between two objects in a typical two-sphere scattering experiments. We show that, contrarily to a common belief, the occurence of strong multiple scattering does not automatically lead to a resolution enhancement.

Minimum description length synthetic aperture radar image segmentation.

We present a new minimum description length (MDL) approach based on a deformable partition--a polygonal grid--for automatic segmentation of a speckled image composed of several homogeneous regions. The image segmentation thus consists in the estimation of the polygonal grid, or, more precisely, its number of regions, its number of nodes and the location of its nodes. These estimations are performed by minimizing a unique MDL criterion which takes into account the probabilistic properties of speckle fluctuations and a measure of the stochastic complexity of the polygonal grid. This approach then leads to a global MDL criterion without an undetermined parameter since no other regularization term than the stochastic complexity of the polygonal grid is necessary and noise parameters can be estimated with maximum likelihood-like approaches. The performance of this technique is illustrated on synthetic and real synthetic aperture radar images of agricultural regions and the influence of different terms of the model is analyzed.

Probing the plasma membrane organization in living cells by spot variation fluorescence correlation spectroscopy.

While intrinsic Brownian agitation within a lipid bilayer does homogenize the molecular distribution, the extremely diverse composition of the plasma membrane, in contrast, favors the development of inhomogeneity due to the propensity of such a system to minimize its total free energy. Precisely, deciphering such inhomogeneous organization with appropriate spatiotemporal resolution remains, however, a challenge. In accordance with its ability to accurately measure diffusion parameters, fluorescence correlation spectroscopy (FCS) has been developed in association with innovative experimental strategies to monitor modes of molecular lateral confinement within the plasma membrane of living cells. Here, we describe a method, namely spot variation FCS (svFCS), to decipher the dynamics of the plasma membrane organization. The method is based on questioning the relationship between the diffusion time τ(d) and the squared waist of observation w(2). Theoretical models have been developed to predict how geometrical constraints such as the presence of adjacent or isolated domains affect the svFCS observations. These investigations have allowed significant progress in the characterization of cell membrane lateral organization at the suboptical level, and have provided, for instance, compelling evidence for the in vivo existence of raft nanodomains.

Mapping molecular diffusion in the plasma membrane by Multiple-Target Tracing (MTT).

Our goal is to obtain a comprehensive description of molecular processes occurring at cellular membranes in different biological functions. We aim at characterizing the complex organization and dynamics of the plasma membrane at single-molecule level, by developing analytic tools dedicated to Single-Particle Tracking (SPT) at high density: Multiple-Target Tracing (MTT). Single-molecule videomicroscopy, offering millisecond and nanometric resolution, allows a detailed representation of membrane organization by accurately mapping descriptors such as cell receptors localization, mobility, confinement or interactions. We revisited SPT, both experimentally and algorithmically. Experimental aspects included optimizing setup and cell labeling, with a particular emphasis on reaching the highest possible labeling density, in order to provide a dynamic snapshot of molecular dynamics as it occurs within the membrane. Algorithmic issues concerned each step used for rebuilding trajectories: peaks detection, estimation and reconnection, addressed by specific tools from image analysis. Implementing deflation after detection allows rescuing peaks initially hidden by neighboring, stronger peaks. Of note, improving detection directly impacts reconnection, by reducing gaps within trajectories. Performances have been evaluated using Monte-Carlo simulations for various labeling density and noise values, which typically represent the two major limitations for parallel measurements at high spatiotemporal resolution. The nanometric accuracy obtained for single molecules, using either successive on/off photoswitching or non-linear optics, can deliver exhaustive observations. This is the basis of nanoscopy methods such as STORM, PALM, RESOLFT or STED, which may often require imaging fixed samples. The central task is the detection and estimation of diffraction-limited peaks emanating from single-molecules. Hence, providing adequate assumptions such as handling a constant positional accuracy instead of Brownian motion, MTT is straightforwardly suited for nanoscopic analyses. Furthermore, MTT can fundamentally be used at any scale: not only for molecules, but also for cells or animals, for instance. Hence, MTT is a powerful tracking algorithm that finds applications at molecular and cellular scales.

Adaptive log-quadratic approach for target detection in nonhomogeneous backgrounds perturbed with speckle fluctuations.

An approach for point target detection in the presence of speckle fluctuations with nonhomogeneous backgrounds is proposed. This approach is based on an automatic selection between the standard constant background model and a quadratic model for the logarithm of the background values. An improvement of the regulation of the false alarm probability in nonhomogeneous backgrounds is demonstrated.

Speckle removal using a maximum-likelihood technique with isoline gray-level regularization.

We propose a method based on the maximum-likelihood technique for removing speckle patterns that plague coherent images. The proposed method is designed for images whose gray levels vary continuously in space. The image model is based on a lattice of nodes corresponding to vertices of triangles in which the gray level of each pixel is produced by linear interpolation. A constraint on isoline gray levels is introduced to regularize the solution.

Real-time three-dimensional object reconstruction by use of a phase-encoded digital hologram.

A three-dimensional (3D) object reconstruction technique that uses only phase information of a phase-shifting digital hologram and a phase-only spatial-light modulator is proposed. It is well known that a digital hologram can store both amplitude and phase information of an optical electric field and can reconstruct the original 3D object in a computer. We demonstrate that it is possible to reconstruct optically 3D objects using only phase information of the optical field calculated from phase-shifting digital holograms. The use of phase-only information enables us to reduce the amount of data in the digital hologram and reconstruct optically the 3D objects using a liquid-crystal spatial light modulator without optical power loss. Numerical evaluation of the reconstructed 3D object is presented.