Super-resolution Microscopy in Plant Cell Imaging.

New technologies are ready to revolutionize glomerular imaging and significantly improve or replace immunofluorescence and electron microscopy, which have driven research and diagnosis of glomerular diseases for over 50 years. Advanced forms of transmission and scanning electron microscopy have revealed the detailed spatial relationships of the glomerular basement membrane, podocytes, and endothelial cells. These may be overshadowed by super resolution microscopy (SRM), which combines the advantages of immunofluorescence and electron microscopy, offers high resolution identification of specific molecules, and images large, physiologically relevant volumes of the glomerulus. Rapidity, ease of use and low cost with some types of SRM make them potentially suitable for routine diagnosis. SRM visualizes structures below the classical diffraction limit of conventional light microscopy by adding a time variable to either the illumination of the specimen, or to the fluorescence signal emitted by it. Ensemble techniques vary illumination and include Structured Illumination Microscopy (SIM) and Stimulation Emission Depletion Microscopy (STED). Single molecule localization techniques vary the light emission by fluorescence labels in the specimen, and include Photoactivated Localization Microscopy (PALM) and Stochastic Optical Reconstruction Microscopy (STORM). Technologies such as expansion microscopy and genetic labeling can also create effective super resolution imaging by non-optical, specialized preparation techniques. All technologies require dark field fluorescence and some require computer image analysis and reconstruction. Replicating successful application in other areas of biology, SIM, STED, and STORM have visualized normal and nephrotic disease podocytes, and have confirmed their appearances to be similar to those seen by electron microscopy, but with added new information on cell configuration and protein localization. STORM has also localized podocyte cytoskeleton and adhesion proteins, and glomerular basement membrane proteins at a resolution never before possible. These pioneering efforts show the promise of super resolution microscopy, and lay the groundwork for future study and new diagnostic tools for glomerular diseases.

Chapter 14 - Super-resolution Microscopy: A Comparison of Commercially Available Options

This review provides a practical introduction to superresolution microscopy from the perspective of microbiological research. Because of the small sizes of bacterial cells, superresolution methods are particularly powerful and suitable for revealing details of cellular structures that are not resolvable under conventional fluorescence light microscopy. Here we describe the methodological concepts behind three major categories of superresolution light microscopy: photoactivated localization microscopy (PALM) and stochastic optical reconstruction microscopy (STORM), structured illumination microscopy (SIM) and stimulated emission-depletion (STED) microscopy. We then present recent applications of each of these techniques to microbial systems, which have revealed novel conformations of cellular structures and described new properties of in vivo protein function and interactions. Finally, we discuss the unique issues related to implementing each of these superresolution techniques with bacterial specimens and suggest avenues for future development. The goal of this review is to provide the necessary technical background for interested microbiologists to choose the appropriate superresolution method for their biological systems, and to introduce the practical considerations required for designing and analysing superresolution imaging experiments.

Far-field optical microscopy using focused light is an important tool in a number of scientific disciplines including chemical, (bio)physical and biomedical research, particularly with respect to the study of living cells and organisms. Unfortunately, the applicability of the optical microscope is limited, since the diffraction of light imposes limitations on the spatial resolution of the image. Consequently the details of, for example, cellular protein distributions, can be visualized only to a certain extent. Fortunately, recent years have witnessed the development of ‘super-resolution’ far-field optical microscopy (nanoscopy) techniques such as stimulated emission depletion (STED), ground state depletion (GSD), reversible saturated optical (fluorescence) transitions (RESOLFT), photoactivation localization microscopy (PALM), stochastic optical reconstruction microscopy (STORM), structured illumination microscopy (SIM) or saturated structured illumination microscopy (SSIM), all in one way or another addressing the problem of the limited spatial resolution of far-field optical microscopy. While SIM achieves a two-fold improvement in spatial resolution compared to conventional optical microscopy, STED, RESOLFT, PALM/STORM, or SSIM have all gone beyond, pushing the limits of optical image resolution to the nanometer scale. Consequently, all super-resolution techniques open new avenues of biomedical research. Because the field is so young, the potential capabilities of different super-resolution microscopy approaches have yet to be fully explored, and uncertainties remain when considering the best choice of methodology. Thus, even for experts, the road to the future is sometimes shrouded in mist. The super-resolution optical microscopy roadmap of Journal of Physics D: Applied Physics addresses this need for clarity. It provides guidance to the outstanding questions through a collection of short review articles from experts in the field, giving a thorough discussion on the concepts underlying super-resolution optical microscopy, the potential of different approaches, the importance of label optimization (such as reversible photoswitchable proteins) and applications in which these methods will have a significant impact.Mark Bates, Christian Eggeling

Multiplexed Superresolution CRISPR Imaging of Chromatin in Living Cells

The field of optical nanoscopy , a paradigm referring to the recent cutting-edge developments aimed at surpassing the widely acknowledged 200nm-diffraction limit in traditional optical microscopy, has gained recent prominence & traction in the $21^{\mathrm {st}}$ century. Numerous optical implementations allowing for a new frontier in traditional confocal laser scanning fluorescence microscopy to be explored (termed super-resolution fluorescence microscopy ) have been realized through the development of techniques such as stimulated emission and depletion (STED) microscopy, photoactivated localization microscopy (PALM) and stochastic optical reconstruction microscopy (STORM), amongst others. Nonetheless, it would be apt to mention at this juncture that optical nanoscopy has been explored since the mid-late $20^{\mathrm {th}}$ century, through several computational techniques such as deblurring and deconvolution algorithms. In this review, we take a step back in the field, evaluating the various in silico methods used to achieve optical nanoscopy today, ranging from traditional deconvolution algorithms (such as the Nearest Neighbors algorithm) to the latest developments in the field of computational nanoscopy, founded on artificial intelligence (AI). An insight is provided into some of the commercial applications of AI-based super-resolution imaging, prior to delving into the potentially promising future implications of computational nanoscopy. This is facilitated by recent advancements in the field of AI, deep learning (DL) and convolutional neural network (CNN) architectures, coupled with the growing size of data sources and rapid improvements in computing hardware, such as multi-core CPUs & GPUs, low-latency RAM and hard-drive capacities.

Microsphere-aided optical microscopy and its applications for super-resolution imaging

Nanoscopic imaging techniques provide a powerful set of tools for static and dynamic fluorescence microscopy below the diffraction limit of light. Among these super-resolution techniques, photoactivated localization microscopy (PALM) and stochastic optical reconstruction microscopy (STORM) are based on the detection of single fluorophores, whose signals are localized with great precision. The strength of single-molecule approaches lies in their high localization accuracy and their molecular specificity and in the development of multicolor approaches, three-dimensional imaging, and the quantification of absolute molecule numbers. These capabilities make PALM and STORM imaging ideally suited to visualize the ultrastructures of synapses, to track the movements of synaptic components, and to quantify the molecular plasticity at synapses.Key wordsActive zone (AZ)Dendritic spineGluA1 (AMPA receptor subunit GluR1)GluN2B (NMDA receptor subunit NR2B)Photoactivated localization microscopy (PALM)Postsynaptic density (PSD)Stochastic optical reconstruction microscopy (STORM)

The structure of the centrosome was resolved by EM many years ago to reveal a pair of centrioles embedded in a dense network of proteins. More recently, the molecular composition of the centrosome was catalogued by mass spectroscopy and many novel components were identified. Determining precisely where a novel component localizes to within the centrosome remains a challenge, and until now it has required the use of immuno-EM. This technique is both time-consuming and unreliable, as it often fails due to problems with antigen accessibility. We have investigated the use of two nanoscopic techniques, photoactivated localization microscopy (PALM) and stochastic optical reconstruction microscopy (STORM), as alternative techniques for localizing centrosomal proteins. The localization of a known centrosomal component, the distal appendage protein Cep164 was investigated by direct STORM (dSTORM) and resolved with a high spatial resolution. We further validated the use of nanoscopic PALM imaging by showing that the previously uncharacterized centrosomal protein CCDC123 (Cep123) localizes to the distal appendages, forming ring-like structures with a diameter of 500 nm. Our results demonstrate that both PALM and STORM imaging have great potential as alternatives to immuno-EM.

Quantitative Microstructure Analysis of Casein Network Dynamics using STED Microscopy with Relation to Macroscopic Gel Properties

Cell polarity reflected by asymmetric distribution of proteins at the plasma membrane is a fundamental feature of unicellular and multicellular organisms. It remains conceptually unclear how cell polarity is kept in cell wall-encapsulated plant cells. We have used super-resolution and semi-quantitative live-cell imaging in combination with pharmacological, genetic, and computational approaches to reveal insights into the mechanism of cell polarity maintenance in Arabidopsis thaliana. We show that polar-competent PIN transporters for the phytohormone auxin are delivered to the center of polar domains by super-polar recycling. Within the plasma membrane, PINs are recruited into non-mobile membrane clusters and their lateral diffusion is dramatically reduced, which ensures longer polar retention. At the circumventing edges of the polar domain, spatially defined internalization of escaped cargos occurs by clathrin-dependent endocytosis. Computer simulations confirm that the combination of these processes provides a robust mechanism for polarity maintenance in plant cells. Moreover, our study suggests that the regulation of lateral diffusion and spatially defined endocytosis, but not super-polar exocytosis have primary importance for PIN polarity maintenance.

Conventional microscopy techniques, namely, the confocal microscope or deconvolution processes, are resolution limited to approximately 200-250 nm by the diffraction properties of light as developed by Ernst Abbe in 1873. This diffraction limit is appreciably above the size of most multi-protein complexes, which are typically 20-50 nm in diameter. In the mid-2000s, biophysicists moved beyond the diffraction barrier by structuring the illumination pattern and then applying mathematical principles and algorithms to allow a resolution of approximately 100 nm, sufficient to address protein subcellular co-localization questions. This "breaking" of the diffraction barrier, affording resolution beyond 200 nm, is termed super-resolution microscopy. More recent approaches include single-molecule localization (such as photoactivated localization microscopy (PALM)/stochastic optical reconstruction microscopy (STORM)) and point spread function engineering (such as stimulated emission depletion (STED) microscopy). In this review, we explain basic principles behind currently commercialized super-resolution setups and address advantages and considerations in applying these techniques to protein co-localization in biological systems.

Localization-based superresolution microscopy techniques such as Photoactivated Localization Microscopy (PALM) and Stochastic Optical Reconstruction Microscopy (STORM) have allowed investigations of cellular structures with unprecedented optical resolutions. One major obstacle to interpreting superresolution images, however, is the overcounting of molecule numbers caused by fluorophore photoblinking. Using both experimental and simulated images, we determined the effects of photoblinking on the accurate reconstruction of superresolution images and on quantitative measurements of structural dimension and molecule density made from those images. We found that structural dimension and relative density measurements can be made reliably from images that contain photoblinking-related overcounting, but accurate absolute density measurements, and consequently faithful representations of molecule counts and positions in cellular structures, require the application of a clustering algorithm to group localizations that originate from the same molecule. We analyzed how applying a simple algorithm with different clustering thresholds (tThresh and dThresh) affects the accuracy of reconstructed images, and developed an easy method to select optimal thresholds. We also identified an empirical criterion to evaluate whether an imaging condition is appropriate for accurate superresolution image reconstruction with the clustering algorithm. Both the threshold selection method and imaging condition criterion are easy to implement within existing PALM clustering algorithms and experimental conditions. The main advantage of our method is that it generates a superresolution image and molecule position list that faithfully represents molecule counts and positions within a cellular structure, rather than only summarizing structural properties into ensemble parameters. This feature makes it particularly useful for cellular structures of heterogeneous densities and irregular geometries, and allows a variety of quantitative measurements tailored to specific needs of different biological systems.

New imaging methodologies with high contrast and molecular specificity allow researchers to analyze dynamic processes in plant cells at multiple scales, from single protein and RNA molecules to organelles and cells, to whole organs and tissues. These techniques produce informative images and quantitative data on molecular dynamics to address questions that cannot be answered by conventional biochemical assays. Here, we review selected microscopy techniques, focusing on their basic principles and applications in plant science, discussing the pros and cons of each technique, and introducing methods for quantitative analysis. This review thus provides guidance for plant scientists in selecting the most appropriate techniques to decipher structures and dynamic processes at different levels, from protein dynamics to morphogenesis.

Covering: up to the end of 2013 New mass spectrometry imaging (MSI) techniques are gaining importance in the analysis of plant metabolite distributions, and significant technological improvements have been introduced in the past decade. This review provides an introduction to the different MSI techniques and their applications in plant science. The most common methods for sample preparation are described, and the review also features a comprehensive table of published studies in MSI of plant material. A number of significant works are highlighted for their contributions to advance the understanding of plant biology through applications of plant metabolite imaging. Particular attention is given to the possibility for imaging of surface metabolites since this is highly dependent on the methods and techniques which are applied in imaging studies.