Quantifying protein densities on cell membranes using super-resolution optical fluctuation imaging

In Operando Locally-Resolved Photophysics in Perovskite Solar Cells by Correlation Clustering Imaging

The instability of metal halide perovskites limits the commercialization of solar cells despite their impressive efficiencies. This instability, driven by photo-induced ion migration, leads to material restructuring, defect formation, degradation, and defect healing. However, these same "unwanted" properties enable to propose Correlation Clustering Imaging (CLIM), a technique that detects local photoluminescence (PL) fluctuations through wide-field fluorescence microscopy. It is shown that such fluctuations are present in high-quality perovskites and their corresponding solar cells. CLIM successfully visualizes the polycrystalline grain structure in perovskite films, closely matching electron microscopy images. The analysis of fluctuations reveals a dominant metastable defect responsible for the fluctuations. In solar cells in short-circuit conditions, these fluctuations are significantly larger, and corresponding correlated regions extend up to 10 micrometers, compared to 2 micrometers in films. It is proposed that the regions resolved by CLIM in solar cells possess a common pool of charge extraction channels, which fluctuate and cause PL to vary. Since PL fluctuations reflect non-radiative recombination processes, CLIM provides valuable insights into the structural and functional dynamics of carrier transport, ion migration, defect behavior, and recombination losses. CLIM offers a non-invasive approach to understanding luminescent materials and devices in operando, utilizing contrasts based on previously untapped properties.

Subcellular Drug Distribution: Exploring Organelle-Specific Characteristics for Enhanced Therapeutic Efficacy

The efficacy and potential toxicity of drug treatments depends on the drug concentration at its site of action, intricately linked to its distribution within diverse organelles of mammalian cells. These organelles, including the nucleus, endosome, lysosome, mitochondria, endoplasmic reticulum, Golgi apparatus, lipid droplets, exosomes, and membrane-less structures, create distinct sub-compartments within the cell, each with unique biological features. Certain structures within these sub-compartments possess the ability to selectively accumulate or exclude drugs based on their physicochemical attributes, directly impacting drug efficacy. Under pathological conditions, such as cancer, many cells undergo dynamic alterations in subcellular organelles, leading to changes in the active concentration of drugs. A mechanistic and quantitative understanding of how organelle characteristics and abundance alter drug partition coefficients is crucial. This review explores biological factors and physicochemical properties influencing subcellular drug distribution, alongside strategies for modulation to enhance efficacy. Additionally, we discuss physiologically based computational models for subcellular drug distribution, providing a quantifiable means to simulate and predict drug distribution at the subcellular level, with the potential to optimize drug development strategies.

Super-resolution microscopy to study membrane nanodomains and transport mechanisms in the plasma membrane

Biological membranes are complex, heterogeneous, and dynamic systems that play roles in the compartmentalization and protection of cells from the environment. It is still a challenge to elucidate kinetics and real-time transport routes for molecules through biological membranes in live cells. Currently, by developing and employing super-resolution microscopy; increasing evidence indicates channels and transporter nano-organization and dynamics within membranes play an important role in these regulatory mechanisms. Here we review recent advances and discuss the major advantages and disadvantages of using super-resolution microscopy to investigate protein organization and transport within plasma membranes.

Quantitative image analysis of intracellular protein translocation in 3-dimensional tissues for pharmacodynamic studies of immunogenic cell death

A recent development in cancer chemotherapy is to use cytotoxics to induce tumor-specific immune response through immunogenic cell death (ICD). In ICD, calreticulin is translocated from endoplasmic reticulum to cell membrane (ecto-CRT) which serves as the 'eat-me-signal' to antigen-presenting cells. Ecto-CRT measurements, e.g., by ecto-CRT immunostaining plus flow cytometry, can be used to study the pharmacodynamics of ICD in single cells, whereas ICD studies in intact 3-dimensional tissues such as human tumors require different approaches. The present study described a method that used (a) immunostaining with fluorescent antibodies followed by confocal microscopy to obtain the spatial locations of two molecules-of-interest (CRT and a marker protein WGA), and (b) machine-learning (trainable WEKA segmentation) and additional image processing tools to locate the target molecules, remove the interfering signals in the nucleus, cytosol and extracellular space, enable the distinction of the inner and outer edges of the cell membrane and thereby identify the cells with ecto-CRT. This method, when applied to 3-dimensional human bladder cancer cell spheroids, yielded drug-induced ecto-CRT measurements that were qualitatively comparable to the flow cytometry results obtained with single cells disaggregated from spheroids. This new method was applied to study drug-induced ICD in short-term cultures of surgical specimens of human patient bladder tumors.

Pre-organized landscape of T cell surface

T cell activation is initiated by the recognition of specific antigenic peptides and subsequently accomplished by complex signaling cascades. These aspects have been extensively studied for decades as pivotal factors in the establishment of adaptive immunity. However, how receptors or signaling molecules are organized in the resting state prior to encountering antigens has received less attention. Recent advancements in super-resolution microscopy techniques have revealed topographically controlled pre-formed organization of key molecules involved in antigen recognition and signal transduction on microvillar projections of T cells before activation and substantial effort has been dedicated to characterizing the topological structure of resting T cells over the past decade. This review will summarize our current understanding of how key surface receptors are pre-organized on the T-cell plasma membrane and discuss the potential role of these receptors, which are preassembled prior to ligand binding in the early activation events of T cells.

A framework for evaluating the performance of SMLM cluster analysis algorithms

Single-molecule localization microscopy (SMLM) generates data in the form of coordinates of localized fluorophores. Cluster analysis is an attractive route for extracting biologically meaningful information from such data and has been widely applied. Despite a range of cluster analysis algorithms, there exists no consensus framework for the evaluation of their performance. Here, we use a systematic approach based on two metrics to score the success of clustering algorithms in simulated conditions mimicking experimental data. We demonstrate the framework using seven diverse analysis algorithms: DBSCAN, ToMATo, KDE, FOCAL, CAML, ClusterViSu and SR-Tesseler. Given that the best performer depended on the underlying distribution of localizations, we demonstrate an analysis pipeline based on statistical similarity measures that enables the selection of the most appropriate algorithm, and the optimized analysis parameters for real SMLM data. We propose that these standard simulated conditions, metrics and analysis pipeline become the basis for future analysis algorithm development and evaluation.

Approach to map nanotopography of cell surface receptors

Cells communicate with their environment via surface receptors, but nanoscopic receptor organization with respect to complex cell surface morphology remains unclear. This is mainly due to a lack of accessible, robust and high-resolution methods. Here, we present an approach for mapping the topography of receptors at the cell surface with nanometer precision. The method involves coating glass coverslips with glycine, which preserves the fine membrane morphology while allowing immobilized cells to be positioned close to the optical surface. We developed an advanced and simplified algorithm for the analysis of single-molecule localization data acquired in a biplane detection scheme. These advancements enable direct and quantitative mapping of protein distribution on ruffled plasma membranes with near isotropic 3D nanometer resolution. As demonstrated successfully for CD4 and CD45 receptors, the described workflow is a straightforward quantitative technique to study molecules and their interactions at the complex surface nanomorphology of differentiated metazoan cells.

A super-resolution localisation-based method is shown to map receptor topography in immune cells, which allows quantitative study of molecules and their interactions at the complex surface nanomorphology of cells.

Shedding Structured Light on Molecular Immunity: The Past, Present and Future of Immune Cell Super Resolution Microscopy

In the two decades since the invention of laser-based super resolution microscopy this family of technologies has revolutionised the way life is viewed and understood. Its unparalleled resolution, speed, and accessibility makes super resolution imaging particularly useful in examining the highly complex and dynamic immune system. Here we introduce the super resolution technologies and studies that have already fundamentally changed our understanding of a number of central immunological processes and highlight other immunological puzzles only addressable in super resolution.

How Blinking Affects Photon Correlations in Multichromophoric Nanoparticles

A single chromophore can only emit a maximum of one single photon per excitation cycle. This limitation results in a phenomenon commonly referred to as photon antibunching (pAB). When multiple chromophores contribute to the fluorescence measured, the degree of pAB has been used as a metric to "count" the number of chromophores. But the fact that chromophores can switch randomly between bright and dark states also impacts pAB and can lead to incorrect chromophore numbers being determined from pAB measurements. By both simulations and experiment, we demonstrate how pAB is affected by independent and collective chromophore blinking, enabling us to formulate universal guidelines for correct interpretation of pAB measurements. We use DNA-origami nanostructures to design multichromophoric model systems that exhibit either independent or collective chromophore blinking. Two approaches are presented that can distinguish experimentally between these two blinking mechanisms. The first one utilizes the different excitation intensity dependence on the blinking mechanisms. The second approach exploits the fact that collective blinking implies energy transfer to a quenching moiety, which is a time-dependent process. In pulsed-excitation experiments, the degree of collective blinking can therefore be altered by time gating the fluorescence photon stream, enabling us to extract the energy-transfer rate to a quencher. The ability to distinguish between different blinking mechanisms is valuable in materials science, such as for multichromophoric nanoparticles like conjugated-polymer chains as well as in biophysics, for example, for quantitative analysis of protein assemblies by counting chromophores.

Correlative Light-Environmental Scanning Electron Microscopy of Plasma Membrane Efflux Carriers of Plant Hormone Auxin

Fluorescence light microscopy provided convincing evidence for the domain organization of plant plasma membrane (PM) proteins. Both peripheral and integral PM proteins show an inhomogeneous distribution within the PM. However, the size of PM nanodomains and protein clusters is too small to accurately determine their dimensions and nano-organization using routine confocal fluorescence microscopy and super-resolution methods. To overcome this limitation, we have developed a novel correlative light electron microscopy method (CLEM) using total internal reflection fluorescence microscopy (TIRFM) and advanced environmental scanning electron microscopy (A-ESEM). Using this technique, we determined the number of auxin efflux carriers from the PINFORMED (PIN) family (NtPIN3b-GFP) within PM nanodomains of tobacco cell PM ghosts. Protoplasts were attached to coverslips and immunostained with anti-GFP primary antibody and secondary antibody conjugated to fluorochrome and gold nanoparticles. After imaging the nanodomains within the PM with TIRFM, the samples were imaged with A-ESEM without further processing, and quantification of the average number of molecules within the nanodomain was performed. Without requiring any post-fixation and coating procedures, this method allows to study details of the organization of auxin carriers and other plant PM proteins.

Polymer brush-induced depletion interactions and clustering of membrane proteins

We investigate the effect of mobile polymer brushes on proteins embedded in biological membranes by employing both Asakura-Oosawa type of theoretical model and coarse-grained molecular dynamics simulations. The brush polymer-induced depletion attraction between proteins changes non-monotonically with the size of brush. The depletion interaction, which is determined by the ratio of the protein size to the grafting distance between brush polymers, increases linearly with the brush size as long as the polymer brush height is shorter than the protein size. When the brush height exceeds the protein size, however, the depletion attraction among proteins is slightly reduced. We also explore the possibility of the brush polymer-induced assembly of a large protein cluster, which can be related to one of many molecular mechanisms underlying recent experimental observations of integrin nanocluster formation and signaling.

Rapid statistical discrimination of fluorescence images of T cell receptors on immobilizing surfaces with different coating conditions

The spatial organization of T cell receptors (TCRs) correlates with membrane-associated signal amplification, dispersion, and regulation during T cell activation. Despite its potential clinical importance, quantitative analysis of the spatial arrangement of TCRs from standard fluorescence images remains difficult. Here, we report Statistical Classification Analyses of Membrane Protein Images or SCAMPI as a technique capable of analyzing the spatial arrangement of TCRs on the plasma membrane of T cells. We leveraged medical image analysis techniques that utilize pixel-based values. We transformed grayscale pixel values from fluorescence images of TCRs into estimated model parameters of partial differential equations. The estimated model parameters enabled an accurate classification using linear discrimination techniques, including Fisher Linear Discriminant (FLD) and Logistic Regression (LR). In a proof-of-principle study, we modeled and discriminated images of fluorescently tagged TCRs from Jurkat T cells on uncoated cover glass surfaces (Null) or coated cover glass surfaces with either positively charged poly-L-lysine (PLL) or TCR cross-linking anti-CD3 antibodies (OKT3). Using 80 training images and 20 test images per class, our statistical technique achieved 85% discrimination accuracy for both OKT3 versus PLL and OKT3 versus Null conditions. The run time of image data download, model construction, and image discrimination was 21.89 s on a laptop computer, comprised of 20.43 s for image data download, 1.30 s on the FLD-SCAMPI analysis, and 0.16 s on the LR-SCAMPI analysis. SCAMPI represents an alternative approach to morphology-based qualifications for discriminating complex patterns of membrane proteins conditioned on a small sample size and fast runtime. The technique paves pathways to characterize various physiological and pathological conditions using the spatial organization of TCRs from patient T cells.

Cytomembrane visualization using Stokes parameter confocal microscopy

A new, to the best of our knowledge, method for Stokes vector imaging is proposed to achieve imaging and dynamic monitoring of a non-labeled cytomembrane. In this work, a polarization state vector is described by a Stokes vector and expressed in chrominance space. A physical quantity called polarization chromaticity value (PCV) corresponding to a Stokes vector is used as the imaging parameter to perform Stokes vector imaging. By using the PCV imaging technique, the Stokes vector can be expressed in three-dimensional real space rather than in a Poincare sphere. Furthermore, a four-way Stokes parameter confocal microscopy system is designed to measure four Stokes parameters simultaneously and obtain micro-imaging. Label-free living onion cell membranes and their plasmolysis process are selected as the representative micro-anisotropy experimental analysis. It is proved that PCV imaging can perform visualization of cytomembranes, and further, microscopic orientation is demonstrated. The prospect of universal measurement of anisotropy details for analysis and diagnosis is provided.

Three-dimensional single molecule localization close to the coverslip: a comparison of methods exploiting supercritical angle fluorescence

The precise spatial localization of single molecules in three dimensions is an important basis for single molecule localization microscopy (SMLM) and tracking. At distances up to a few hundred nanometers from the coverslip, evanescent wave coupling into the glass, also known as supercritical angle fluorescence (SAF), can strongly improve the axial precision, thus facilitating almost isotropic localization performance. Specific detection systems, introduced as Supercritical angle localization microscopy (SALM) or Direct optical nanoscopy with axially localized detection (DONALD), have been developed to exploit SAF in modified two-channel imaging schemes. Recently, our group has shown that off-focus microscopy, i.e., imaging at an intentional slight defocus, can perform equally well, but uses only a single detection arm. Here we compare SALM, off-focus imaging and the most commonly used 3D SMLM techniques, namely cylindrical lens and biplane imaging, regarding 3D localization in close proximity to the coverslip. We show that all methods gain from SAF, which leaves a high detection NA as the only major key requirement to unlock the SAF benefit. We find parameter settings for cylindrical lens and biplane imaging for highest z-precision. Further, we compare the methods in view of robustness to aberrations, fixed dipole emission and double-emitter events. We show that biplane imaging provides the best overall performance and support our findings by DNA-PAINT experiments on DNA-nanoruler samples. Our study sheds light on the effects of SAF for SMLM and is helpful for researchers who plan to employ localization-based 3D nanoscopy close to the coverslip.

Enhanced temporal and spatial resolution in super-resolution covariance imaging algorithm with deconvolution optimization

Based on the numerical analysis that covariance exhibits superior statistical precision than cumulant and variance, a new SOFI algorithm by calculating the n orders covariance for each pixel is presented with an almost 2n -fold resolution improvement, which can be enhanced to 2ⁿ via deconvolution. An optimized deconvolution is also proposed by calculating the (n + 1) order SD associated with each n order covariance pixel, and introducing the results into the deconvolution as a damping factor to suppress noise generation. Moreover, a re-deconvolution of the covariance image with the covariance-equivalent point spread function is used to further increase the final resolution by above 2-fold. Simulated and experimental results show that this algorithm can significantly increase the temporal-spatial resolution of SOFI, meanwhile, preserve the sample's structure. Thus, a resolution of 58 nm is achieved for 20 experimental images, and the corresponding acquisition time is 0.8 seconds.

Adaptive Lipid Immiscibility and Membrane Remodeling Are Active Functional Determinants of Primary Ciliogenesis

Lipid liquid-liquid immiscibility and its consequent lateral heterogeneity have been observed under thermodynamic equilibrium in model and native membranes. However, cholesterol-rich membrane domains, sometimes referred to as lipid rafts, are difficult to observe spatiotemporally in live cells. Despite their importance in many biological processes, robust evidence for their existence remains elusive. This is mainly due to the difficulty in simultaneously determining their chemical composition and physicochemical nature, whilst spatiotemporally resolving their nanodomain lifetime and molecular dynamics. In this study, a bespoke method based on super-resolution stimulated emission depletion (STED) microscopy and raster imaging correlation spectroscopy (RICS) is used to overcome this issue. This methodology, laser interleaved confocal RICS and STED-RICS (LICSR), enables simultaneous tracking of lipid lateral packing and dynamics at the nanoscale. Previous work indicated that, in polarized epithelial cells, the midbody remnant licenses primary cilium formation through an unidentified mechanism. LICSR shows that lipid immiscibility and its adaptive collective nanoscale self-assembly are crucial for the midbody remnant to supply condensed membranes to the centrosome for the biogenesis of the ciliary membrane. Hence, this work poses a breakthrough in the field of lipid biology by providing compelling evidence of a functional role for liquid ordered-like membranes in primary ciliogenesis.

Single-Molecule Super-Resolution Imaging of T-Cell Plasma Membrane CD4 Redistribution upon HIV-1 Binding

The first step of cellular entry for the human immunodeficiency virus type-1 (HIV-1) occurs through the binding of its envelope protein (Env) with the plasma membrane receptor CD4 and co-receptor CCR5 or CXCR4 on susceptible cells, primarily CD4+ T cells and macrophages. Although there is considerable knowledge of the molecular interactions between Env and host cell receptors that lead to successful fusion, the precise way in which HIV-1 receptors redistribute to sites of virus binding at the nanoscale remains unknown. Here, we quantitatively examine changes in the nanoscale organisation of CD4 on the surface of CD4+ T cells following HIV-1 binding. Using single-molecule super-resolution imaging, we show that CD4 molecules are distributed mostly as either individual molecules or small clusters of up to 4 molecules. Following virus binding, we observe a local 3-to-10-fold increase in cluster diameter and molecule number for virus-associated CD4 clusters. Moreover, a similar but smaller magnitude reorganisation of CD4 was also observed with recombinant gp120. For one of the first times, our results quantify the nanoscale CD4 reorganisation triggered by HIV-1 on host CD4+ T cells. Our quantitative approach provides a robust methodology for characterising the nanoscale organisation of plasma membrane receptors in general with the potential to link spatial organisation to function.

Photonic technologies for liquid biopsies: recent advances and open research challenges

The recent development of sophisticated techniques capable of detecting extremely low concentrations of circulating tumor biomarkers in accessible body fluids, such as blood or urine, could contribute to a paradigm shift in cancer diagnosis and treatment. By applying such techniques, clinicians can carry out liquid biopsies, providing information on tumor presence, evolution, and response to therapy. The implementation of biosensing platforms for liquid biopsies is particularly complex because this application domain demands high selectivity/specificity and challenging limit-of-detection (LoD) values. The interest in photonics as an enabling technology for liquid biopsies is growing owing to the well-known advantages of photonic biosensors over competing technologies in terms of compactness, immunity to external disturbance, and ultra-high spatial resolution. Some encouraging experimental results in the field of photonic devices and systems for liquid biopsy have already been achieved by using fluorescent labels and label-free techniques and by exploiting super-resolution microscopy, surface plasmon resonance, surface-enhanced Raman scattering, and whispering gallery mode resonators. This paper critically reviews the current state-of-the-art, starting from the requirements imposed by the detection of the most common circulating biomarkers. Open research challenges are considered together with competing technologies, and the most promising paths of improvement are discussed for future applications.

Self-Blinking Dyes Unlock High-Order and Multiplane Super-Resolution Optical Fluctuation Imaging

Most diffraction-unlimited super-resolution imaging critically depends on the switching of fluorophores between at least two states, often induced using intense laser light and specialized buffers or UV radiation. Recently, so-called self-blinking dyes that switch spontaneously between an open, fluorescent "on" state and a closed, colorless "off" state were introduced. Here, we exploit the synergy between super-resolution optical fluctuation imaging (SOFI) and spontaneously switching fluorophores for 2D and 3D imaging. SOFI analyzes higher order statistics of fluctuations in the fluorophore emission instead of localizing individual molecules. It thereby tolerates a broad range of labeling densities, switching behavior, and probe brightness. Thus, even dyes that exhibit spontaneous blinking characteristics that are not suitable or suboptimal for single molecule localization microscopy can be used successfully for SOFI-based super-resolution imaging. We demonstrate 2D imaging of fixed cells with almost uniform resolution up to 50-60 nm in 6th order SOFI and characterize changing experimental conditions. Next, we investigate volumetric imaging using biplane and eight-plane data acquisition. We extend 3D cross-cumulant analysis to 4th order, achieving super-resolution in 3D with up to 29 depth planes. Finally, the low laser excitation intensities needed for single and biplane self-blinking SOFI are well suited for live-cell imaging. We show the perspective for time-resolved imaging by observing slow membrane movements in cells. Self-blinking SOFI thus provides a more robust alternative route for easy-to-use 2D and 3D high-resolution imaging.

Grease on-Perspectives in lipid droplet biology

Lipid droplets (LDs) are now recognized as omnipresent and dynamic subcellular organelles of amazing morphological and functional diversity. Beyond the obvious benefit of having molecules full of chemical energy stored in a dedicated structural entity, LDs may also be viewed as a safe harbor for potentially damaging metabolites. This protective function might in many cases even supersede the relevance of lipid storage for eventual energy gain and membrane biogenesis. Furthermore, the LD surface constitutes a unique membrane environment, creating a platform for hosting specific proteins and thus enabling their interactions. These metabolic hotspots would contribute decisively to compartmentalized metabolism in the cytosol. LDs are also communicating extensively with other subcellular organelles in directing and regulating lipid metabolism. Deciphering the relevance of LD storage and regulation at the organismic level will be essential for the understanding of widespread and serious metabolic complications in humans. Increasing attention is also devoted to pathogens appropriating LDs for their own benefit. LD biology is still considered an emerging research area in rapid and vibrant development, attracting scientists from all disciplines of the life sciences and beyond, which is mirrored by the accompanying review collection. Here, we present our personal views on areas we believe are especially exciting and hold great potential for future developments. Particularly, we address issues relating to LD biogenesis and heterogeneity, required technological advances, and the complexity of human physiology.

Spectral cross-cumulants for multicolor super-resolved SOFI imaging

Super-resolution optical fluctuation imaging provides a resolution beyond the diffraction limit by analysing stochastic fluorescence fluctuations with higher-order statistics. Using nth order spatio-temporal cross-cumulants the spatial resolution and the sampling can be increased up to n-fold in all spatial dimensions. In this study, we extend the cumulant analysis into the spectral domain and propose a multicolor super-resolution scheme. The simultaneous acquisition of two spectral channels followed by spectral cross-cumulant analysis and unmixing increases the spectral sampling. The number of discriminable fluorophore species is thus not limited to the number of physical detection channels. Using two color channels, we demonstrate spectral unmixing of three fluorophore species in simulations and experiments in fixed and live cells. Based on an eigenvalue/vector analysis, we propose a scheme for an optimized spectral filter choice. Overall, our methodology provides a route for easy-to-implement multicolor sub-diffraction imaging using standard microscopes while conserving the spatial super-resolution property.

A Review of Super-Resolution Single-Molecule Localization Microscopy Cluster Analysis and Quantification Methods

Single-molecule localization microscopy (SMLM) is a relatively new imaging modality, winning the 2014 Nobel Prize in Chemistry, and considered as one of the key super-resolution techniques. SMLM resolution goes beyond the diffraction limit of light microscopy and achieves resolution on the order of 10-20 nm. SMLM thus enables imaging single molecules and study of the low-level molecular interactions at the subcellular level. In contrast to standard microscopy imaging that produces 2D pixel or 3D voxel grid data, SMLM generates big data of 2D or 3D point clouds with millions of localizations and associated uncertainties. This unprecedented breakthrough in imaging helps researchers employ SMLM in many fields within biology and medicine, such as studying cancerous cells and cell-mediated immunity and accelerating drug discovery. However, SMLM data quantification and interpretation methods have yet to keep pace with the rapid advancement of SMLM imaging. Researchers have been actively exploring new computational methods for SMLM data analysis to extract biosignatures of various biological structures and functions. In this survey, we describe the state-of-the-art clustering methods adopted to analyze and quantify SMLM data and examine the capabilities and shortcomings of the surveyed methods. We classify the methods according to (1) the biological application (i.e., the imaged molecules/structures), (2) the data acquisition (such as imaging modality, dimension, resolution, and number of localizations), and (3) the analysis details (2D versus 3D, field of view versus region of interest, use of machine-learning and multi-scale analysis, biosignature extraction, etc.). We observe that the majority of methods that are based on second-order statistics are sensitive to noise and imaging artifacts, have not been applied to 3D data, do not leverage machine-learning formulations, and are not scalable for big-data analysis. Finally, we summarize state-of-the-art methodology, discuss some key open challenges, and identify future opportunities for better modeling and design of an integrated computational pipeline to address the key challenges.

Imaging of the immune system - towards a subcellular and molecular understanding

Immune responses involve many types of leukocytes that traffic to the site of injury, recognize the insult and respond appropriately. Imaging of the immune system involves a set of methods and analytical tools that are used to visualize immune responses at the cellular and molecular level as they occur in real time. We will review recent and emerging technological advances in optical imaging, and their application to understanding the molecular and cellular responses of neutrophils, macrophages and lymphocytes. Optical live-cell imaging provides deep mechanistic insights at the molecular, cellular, tissue and organism levels. Live-cell imaging can capture quantitative information in real time at subcellular resolution with minimal phototoxicity and repeatedly in the same living cells or in accessible tissues of the living organism. Advanced FRET probes allow tracking signaling events in live cells. Light-sheet microscopy allows for deeper tissue penetration in optically clear samples, enriching our understanding of the higher-level organization of the immune response. Super-resolution microscopy offers insights into compartmentalized signaling at a resolution beyond the diffraction limit, approaching single-molecule resolution. This Review provides a current perspective on live-cell imaging in vitro and in vivo with a focus on the assessment of the immune system.

Profiling of Exosomal Biomarkers for Accurate Cancer Identification: Combining DNA-PAINT with Machine- Learning-Based Classification

Exosomes are endosome-derived vesicles enriched in body fluids such as urine, blood, and saliva. So far, they have been recognized as potential biomarkers for cancer diagnostics. However, the present single-variate analysis of exosomes has greatly limited the accuracy and specificity of diagnoses. Besides, most diagnostic approaches focus on bulk analysis using lots of exosomes and tend to be less accurate because they are vulnerable to impure extraction and concentration differences of exosomes. To address these challenges, a quantitative analysis platform is developed to implement a sequential quantification analysis of multiple exosomal surface biomarkers at the single-exosome level, which utilizes DNA-PAINT and a machine learning algorithm to automatically analyze the results. As a proof of concept, the profiling of four exosomal surface biomarkers (HER2, GPC-1, EpCAM, EGFR) is developed to identify exosomes from cancer-derived blood samples. Then, this technique is further applied to detect pancreatic cancer and breast cancer from unknown samples with 100% accuracy.

An extended quantitative model for super-resolution optical fluctuation imaging (SOFI)

Super-resolution optical fluctuation imaging (SOFI) provides super-resolution (SR) fluorescence imaging by analyzing fluctuations in the fluorophore emission. The technique has been used both to acquire quantitative SR images and to provide SR biosensing by monitoring changes in fluorophore blinking dynamics. Proper analysis of such data relies on a fully quantitative model of the imaging. However, previous SOFI imaging models made several assumptions that can not be realized in practice. In this work we address these limitations by developing and verifying a fully quantitative model that better approximates real-world imaging conditions. Our model shows that (i) SOFI images are free of bias, or can be made so, if the signal is stationary and fluorophores blink independently, (ii) allows a fully quantitative description of the link between SOFI imaging and probe dynamics, and (iii) paves the way for more advanced SOFI image reconstruction by offering a computationally fast way to calculate SOFI images for arbitrary probe, sample and instrumental properties.

A tessellation-based colocalization analysis approach for single-molecule localization microscopy

Multicolor single-molecule localization microscopy (λSMLM) is a powerful technique to reveal the relative nanoscale organization and potential colocalization between different molecular species. While several standard analysis methods exist for pixel-based images, λSMLM still lacks such a standard. Moreover, existing methods only work on 2D data and are usually sensitive to the relative molecular organization, a very important parameter to consider in quantitative SMLM. Here, we present an efficient, parameter-free colocalization analysis method for 2D and 3D λSMLM using tessellation analysis. We demonstrate that our method allows for the efficient computation of several popular colocalization estimators directly from molecular coordinates and illustrate its capability to analyze multicolor SMLM data in a robust and efficient manner.

Multicolour single-molecule localization microscopy lacks a standard analysis method. Here Levet et al. introduce Coloc-Tesseler, a parameter-free colocalisation analysis method based on tessellation analysis for the efficient analysis of multicolour SMLM data.

Dual Role of CD4 in Peripheral T Lymphocytes

The interaction of T-cell receptors (TCRs) with self- and non-self-peptides in the major histocompatibility complex (MHC) stimulates crucial signaling events, which in turn can activate T lymphocytes. A variety of accessory molecules further modulate T-cell signaling. Of these, the CD4 and CD8 coreceptors make the most critical contributions to T cell sensitivity in vivo. Whereas, CD4 function in T cell development is well-characterized, its role in peripheral T cells remains incompletely understood. It was originally suggested that CD4 stabilizes weak interactions between TCRs and peptides in the MHC and delivers Lck kinases to that complex. The results of numerous experiments support the latter role, indicating that the CD4-Lck complex accelerates TCR-triggered signaling and controls the availability of the kinase for TCR in the absence of the ligand. On the other hand, extremely low affinity of CD4 for MHC rules out its ability to stabilize the receptor-ligand complex. In this review, we summarize the current knowledge on CD4 in T cells, with a special emphasis on the spatio-temporal organization of early signaling events and the relevance for CD4 function. We further highlight the capacity of CD4 to interact with the MHC in the absence of TCR. It drives the adhesion of T cells to the cells that express the MHC. This process is facilitated by the CD4 accumulation in the tips of microvilli on the surface of unstimulated T cells. Based on these observations, we suggest an alternative model of CD4 role in T-cell activation.

Kinetics of Nanoparticle-Membrane Adhesion Mediated by Multivalent Interactions

Multivalent adhesive interactions mediated by a large number of ligands and receptors underpin many biological processes, including cell adhesion and the uptake of particles, viruses, parasites, and nanomedical vectors. In materials science, multivalent interactions between colloidal particles have enabled unprecedented control over the phase behavior of self-assembled materials. Theoretical and experimental studies have pinpointed the relationship between equilibrium states and microscopic system parameters such as the ligand-receptor binding strength and their density. In regimes of strong interactions, however, kinetic factors are expected to slow down equilibration and lead to the emergence of long-lived out-of-equilibrium states that may significantly influence the outcome of self-assembly experiments and the adhesion of particles to biological membranes. Here we experimentally investigate the kinetics of adhesion of nanoparticles to biomimetic lipid membranes. Multivalent interactions are reproduced by strongly interacting DNA constructs, playing the role of both ligands and receptors. The rate of nanoparticle adhesion is investigated as a function of the surface density of membrane-anchored receptors and the bulk concentration of nanoparticles and is observed to decrease substantially in regimes where the number of available receptors is limited compared to the overall number of ligands. We attribute such peculiar behavior to the rapid sequestration of available receptors after initial nanoparticle adsorption. The experimental trends and the proposed interpretation are supported by numerical simulations.

Quantitative profiling of CD13 on single acute myeloid leukemia cells by super-resolution imaging and its implication in targeted drug susceptibility assessment

Quantitative profiling of membrane proteins on the cell surface is of great interest in tumor targeted therapy and single cell biology. However, the existing technologies are either of insufficient resolution, or unable to provide precise information on the localization of individual proteins. Here, we report a new method that combines the use of quantum dot labeling, super-resolution microscopy (structured illumination microscopy, SIM) and software modeling. In this proof-of-principle study, we assessed the biological effects of Bestatin on individual cells from different AML cell lines expressing CD13 proteins, a potential target for tumor targeted therapy. Using the proposed method, we found that the different AML cell lines exhibit different CD13 expression densities, ranging from 0.1 to 1.3 molecules per μm2 cell surface, respectively. Importantly, Bestatin treatment assays shows that its effects on cell growth inhibition, apoptosis and cell cycle change are directly proportional to the density of CD13 on the cell surface of these cell lines. The results suggest that the proposed method advances the quantitative analysis of single cell surface proteins, and that the quantitative profiling information of the target protein on single cells has potential value in targeted drug susceptibility assessment.

The phagocytic state of brain myeloid cells after ischemia revealed by superresolution structured illumination microscopy

BACKGROUND

Phagocytosis is a key function of myeloid cells and is highly involved in brain ischemic injury. It has been scarcely studied in vivo, thus preventing a deep knowledge of the processes occurring in the ischemic environment. Structured illumination microscopy (SIM) is a superresolution technique which helps study phagocytosis, a process involving the recruitment of vesicles sized below the resolution limits of standard confocal microscopy.

METHODS

Mice underwent permanent occlusion of the middle cerebral artery and were sacrificed at 48 h or 7 days after insult. Immunofluorescence for CD11b, myeloid cell membrane marker, and CD68, lysosomal marker was done in the ischemic area. Images were acquired using a SIM system and verified with SIM check. Lysosomal distribution was measured in the ischemic area by the gray level co-occurrence matrix (GLCM). SIM dataset was compared with transmission electron microscopy images of macrophages in the ischemic tissue at the same time points. Cultured microglia were stimulated with LPS to uptake 100 nm fluorescent beads and imaged by time-lapse SIM. GLCM was used to analyze bead distribution over the cytoplasm.

RESULTS

SIM images reached a resolution of 130 nm and passed the quality control diagnose, ruling out possible artifacts. After ischemia, GLCM applied to the CD68 images showed that myeloid cells at 48 h had higher angular second moment (ASM), inverse difference moment (IDM), and lower entropy than myeloid cells at 7 days indicating higher lysosomal clustering at 48 h. At this time point, lysosomal clustering was proximal (< 700 nm) to the cell membrane indicating active target internalization, while at 7 days, it was perinuclear, consistent with final stages of phagocytosis or autophagy. Electron microscopy images indicated a similar pattern of lysosomal distribution thus validating the SIM dataset. GLCM on time-lapse SIM from phagocytic microglia cultures revealed a temporal decrease in ASM and IDM and increase in entropy, as beads were uptaken, indicating that GLCM informs on the progression of phagocytosis.

CONCLUSIONS

GLCM analysis on SIM dataset quantitatively described different phases of macrophage phagocytic behavior revealing the dynamics of lysosomal movements in the ischemic brain indicating initial active internalization vs. final digestion/autophagy.

Proteome Imaging: From Classic to Modern Mass Spectrometry-Based Molecular Histology

In order to overcome the limitations of classic imaging in Histology during the actually era of multiomics, the multi-color "molecular microscope" by its emerging "molecular pictures" offers quantitative and spatial information about thousands of molecular profiles without labeling of potential targets. Healthy and diseased human tissues, as well as those of diverse invertebrate and vertebrate animal models, including genetically engineered species and cultured cells, can be easily analyzed by histology-directed MALDI imaging mass spectrometry. The aims of this review are to discuss a range of proteomic information emerging from MALDI mass spectrometry imaging comparative to classic histology, histochemistry and immunohistochemistry, with applications in biology and medicine, concerning the detection and distribution of structural proteins and biological active molecules, such as antimicrobial peptides and proteins, allergens, neurotransmitters and hormones, enzymes, growth factors, toxins and others. The molecular imaging is very well suited for discovery and validation of candidate protein biomarkers in neuroproteomics, oncoproteomics, aging and age-related diseases, parasitoproteomics, forensic, and ecotoxicology. Additionally, in situ proteome imaging may help to elucidate the physiological and pathological mechanisms involved in developmental biology, reproductive research, amyloidogenesis, tumorigenesis, wound healing, neural network regeneration, matrix mineralization, apoptosis and oxidative stress, pain tolerance, cell cycle and transformation under oncogenic stress, tumor heterogeneity, behavior and aggressiveness, drugs bioaccumulation and biotransformation, organism's reaction against environmental penetrating xenobiotics, immune signaling, assessment of integrity and functionality of tissue barriers, behavioral biology, and molecular origins of diseases. MALDI MSI is certainly a valuable tool for personalized medicine and "Eco-Evo-Devo" integrative biology in the current context of global environmental challenges.

Membrane Lipid Nanodomains

Lipid membranes can spontaneously organize their components into domains of different sizes and properties. The organization of membrane lipids into nanodomains might potentially play a role in vital functions of cells and organisms. Model membranes represent attractive systems to study lipid nanodomains, which cannot be directly addressed in living cells with the currently available methods. This review summarizes the knowledge on lipid nanodomains in model membranes and exposes how their specific character contrasts with large-scale phase separation. The overview on lipid nanodomains in membranes composed of diverse lipids (e.g., zwitterionic and anionic glycerophospholipids, ceramides, glycosphingolipids) and cholesterol aims to evidence the impact of chemical, electrostatic, and geometric properties of lipids on nanodomain formation. Furthermore, the effects of curvature, asymmetry, and ions on membrane nanodomains are shown to be highly relevant aspects that may also modulate lipid nanodomains in cellular membranes. Potential mechanisms responsible for the formation and dynamics of nanodomains are discussed with support from available theories and computational studies. A brief description of current fluorescence techniques and analytical tools that enabled progress in lipid nanodomain studies is also included. Further directions are proposed to successfully extend this research to cells.

Synergizing superresolution optical fluctuation imaging with single molecule localization microscopy

Single-molecule-localization-microscopy (SMLM) and superresolution-optical-fluctuation-imaging (SOFI) enable imaging biological samples well beyond the diffraction-limit of light. SOFI imaging is typically faster, yet has lower resolution than SMLM. Since the same (or similar) data format is acquired for both methods, their algorithms could presumably be combined synergistically for reconstruction and improvement of overall imaging performance. For that, we first defined a measure of the acquired-SNR for each method. This measure was ∼x10 to x100 higher for SOFI as compared to SMLM, indicating faster recognition and acquisition of features by SOFI. This measure also allowed fluorophore-specific optimization of SOFI reconstruction over its time-window and time-lag. We show that SOFI-assisted SMLM imaging can improve image reconstruction by rejecting common sources of background (e.g. out-of-focus emission and auto-fluorescence), especially under low signal-to-noise ratio conditions, by efficient optical sectioning and by shortening image reconstruction time. The performance and utility of our approach was evaluated by realistic simulations and by SOFI-assisted SMLM imaging of the plasma membrane of activated fixed and live T-cells (in isolation or in conjugation to antigen presenting cells). Our approach enhances SMLM performance under demanding imaging conditions and could set an example for synergizing additional imaging techniques.