The understanding of cytoskeleton dynamics has benefited from the capacity to generate fluorescent fiducial marks on cytoskeleton components. Here we show that light-induced imprinting of three-dimensional (3D) fluorescent speckles significantly improves speckle signal and contrast relative to classic (random) fluorescent speckle microscopy. We predict theoretically that speckle imprinting using photobleaching is optimal when the laser energy and fluorophore responsivity are related by the golden ratio. This relation, which we confirm experimentally, translates into a 40% remaining signal after speckle imprinting and provides a rule of thumb in selecting the laser power required to optimally prepare the sample for imaging. This inducible speckle imaging (ISI) technique allows 3D speckle microscopy to be performed in readily available libraries of cell lines or primary tissues expressing fluorescent proteins and does not preclude conventional imaging before speckle imaging. As a proof of concept, we use ISI to measure metaphase spindle microtubule poleward flux in primary cells and explore a scaling relation connecting microtubule flux to metaphase duration.

Expansion microscopy (ExM) increases the effective resolving power of any microscope by expanding the sample with swellable hydrogel. Since its invention, ExM has been successfully applied to a wide range of cell, tissue, and animal samples. Still, fluorescence signal loss during polymerization and digestion limits molecular-scale imaging using ExM. Here, we report the development of label-retention ExM (LR-ExM) with a set of trifunctional anchors that not only prevent signal loss but also enable high-efficiency labeling using SNAP and CLIP tags. We have demonstrated multicolor LR-ExM for a variety of subcellular structures. Combining LR-ExM with superresolution stochastic optical reconstruction microscopy (STORM), we have achieved molecular resolution in the visualization of polyhedral lattice of clathrin-coated pits in situ.

Fluorescence microscopy is one of the most powerful tools to investigate complex cellular processes such as cell division, cell motility, or intracellular trafficking. The availability of RNA interference (RNAi) technology and automated microscopy has opened the possibility to perform cellular imaging in functional genomics and other large-scale applications. Although imaging often dramatically increases the content of a screening assay, it poses new challenges to achieve accurate quantitative annotation and therefore needs to be carefully adjusted to the specific needs of individual screening applications. In this review, we discuss principles of assay design, large-scale RNAi, microscope automation, and computational data analysis. We highlight strategies for imaging-based RNAi screening adapted to different library and assay designs.

Cells are 3D objects. Therefore, volume EM (vEM) is often crucial for correct interpretation of ultrastructural data. Today, scanning EM (SEM) methods such as focused ion beam (FIB)-SEM are frequently used for vEM analyses. While they allow automated data acquisition, precise targeting of volumes of interest within a large sample remains challenging. Here, we provide a workflow to target FIB-SEM acquisition of fluorescently labeled cells or subcellular structures with micrometer precision. The strategy relies on fluorescence preservation during sample preparation and targeted trimming guided by confocal maps of the fluorescence signal in the resin block. Laser branding is used to create landmarks on the block surface to position the FIB-SEM acquisition. Using this method, we acquired volumes of specific single cells within large tissues such as 3D cultures of mouse mammary gland organoids, tracheal terminal cells in Drosophila melanogaster larvae, and ovarian follicular cells in adult Drosophila, discovering ultrastructural details that could not be appreciated before.

Total internal reflection fluorescence microscopy has been applied to image the final stage of constitutive exocytosis, which is the fusion of single post-Golgi carriers with the plasma membrane. The use of a membrane protein tagged with green fluorescent protein allowed the kinetics of fusion to be followed with a time resolution of 30 frames/s. Quantitative analysis allowed carriers undergoing fusion to be easily distinguished from carriers moving perpendicularly to the plasma membrane. The flattening of the carriers into the plasma membrane is seen as a simultaneous rise in the total, peak, and width of the fluorescence intensity. The duration of this flattening process depends on the size of the carriers, distinguishing small spherical from large tubular carriers. The spread of the membrane protein into the plasma membrane upon fusion is diffusive. Mapping many fusion sites of a single cell reveals that there are no preferred sites for constitutive exocytosis in this system.

Genetic screens using high-throughput fluorescent microscopes have generated large datasets, contributing many cell biological insights. Such approaches cannot tackle questions requiring knowledge of ultrastructure below the resolution limit of fluorescent microscopy. Electron microscopy (EM) reveals detailed cellular ultrastructure but requires time-consuming sample preparation, limiting throughput. Here we describe a robust method for screening by high-throughput EM. Our approach uses combinations of fluorophores as barcodes to uniquely mark each cell type in mixed populations and correlative light and EM (CLEM) to read the barcode of each cell before it is imaged by EM. Coupled with an easy-to-use software workflow for correlation, segmentation, and computer image analysis, our method, called "MultiCLEM," allows us to extract and analyze multiple cell populations from each EM sample preparation. We demonstrate several uses for MultiCLEM with 15 different yeast variants. The methodology is not restricted to yeast, can be scaled to higher throughput, and can be used in multiple ways to enable EM to become a powerful screening technique.

The endoplasmic reticulum (ER) is composed of interconnected membrane sheets and tubules. Superresolution microscopy recently revealed densely packed, rapidly moving ER tubules mistaken for sheets by conventional light microscopy, highlighting the importance of revisiting classical views of ER structure with high spatiotemporal resolution in living cells. In this study, we use live-cell stimulated emission depletion (STED) microscopy to survey the architecture of the ER at 50-nm resolution. We determine the nanoscale dimensions of ER tubules and sheets for the first time in living cells. We demonstrate that ER sheets contain highly dynamic, subdiffraction-sized holes, which we call nanoholes, that coexist with uniform sheet regions. Reticulon family members localize to curved edges of holes within sheets and are required for their formation. The luminal tether Climp63 and microtubule cytoskeleton modulate their nanoscale dynamics and organization. Thus, by providing the first quantitative analysis of ER membrane structure and dynamics at the nanoscale, our work reveals that the ER in living cells is not limited to uniform sheets and tubules; instead, we suggest the ER contains a continuum of membrane structures that includes dynamic nanoholes in sheets as well as clustered tubules.

The spatial organization of the genome is enigmatic. Direct evidence of physical contacts between chromosomes and their visualization at nanoscale resolution has been limited. We used superresolution microscopy to demonstrate that ribosomal DNA (rDNA) can form linkages between chromosomes. We observed rDNA linkages in many different human cell types and demonstrated their resolution in anaphase. rDNA linkages are coated by the transcription factor UBF and their formation depends on UBF, indicating that they regularly occur between transcriptionally active loci. Overexpression of c-Myc increases rDNA transcription and the frequency of rDNA linkages, further suggesting that their formation depends on active transcription. Linkages persist in the absence of cohesion, but inhibition of topoisomerase II prevents their resolution in anaphase. We propose that linkages are topological intertwines occurring between transcriptionally active rDNA loci spatially colocated in the same nucleolar compartment. Our findings suggest that active DNA loci engage in physical interchromosomal connections that are an integral and pervasive feature of genome organization.

Paraspeckles are nuclear bodies built on the long noncoding RNA Neat1, which regulates a variety of physiological processes including cancer progression and corpus luteum formation. To obtain further insight into the molecular basis of the function of paraspeckles, we performed fine structural analyses of these nuclear bodies using structural illumination microscopy. Notably, paraspeckle proteins are found within different layers along the radially arranged bundles of Neat1 transcripts, forming a characteristic core-shell spheroidal structure. In cells lacking the RNA binding protein Fus, paraspeckle spheroids are disassembled into smaller particles containing Neat1, which are diffusely distributed in the nucleoplasm. Sequencing analysis of RNAs purified from paraspeckles revealed that AG-rich transcripts associate with Neat1, which are distributed along the shell of the paraspeckle spheroids. We propose that paraspeckles sequester core components inside the spheroids, whereas the outer surface associates with other components in the nucleoplasm to fulfill their function.

Images generated by a microscope are never a perfect representation of the biological specimen. Microscopes and specimen preparation methods are prone to error and can impart images with unintended attributes that might be misconstrued as belonging to the biological specimen. In addition, our brains are wired to quickly interpret what we see, and with an unconscious bias toward that which makes the most sense to us based on our current understanding. Unaddressed errors in microscopy images combined with the bias we bring to visual interpretation of images can lead to false conclusions and irreproducible imaging data. Here we review important aspects of designing a rigorous light microscopy experiment: validation of methods used to prepare samples and of imaging system performance, identification and correction of errors, and strategies for avoiding bias in the acquisition and analysis of images.

Metabolic energy is stored in cells primarily as triacylglycerols in lipid droplets (LDs), and LD dysregulation leads to metabolic diseases. The formation of monolayer-bound LDs from the endoplasmic reticulum (ER) bilayer is poorly understood, but the ER protein seipin is essential to this process. In this study, we report a cryo-electron microscopy structure and functional characterization of Drosophila melanogaster seipin. The structure reveals a ring-shaped dodecamer with the luminal domain of each monomer resolved at ∼4.0 Å. Each luminal domain monomer exhibits two distinctive features: a hydrophobic helix (HH) positioned toward the ER bilayer and a β-sandwich domain with structural similarity to lipid-binding proteins. This structure and our functional testing in cells suggest a model in which seipin oligomers initially detect forming LDs in the ER via HHs and subsequently act as membrane anchors to enable lipid transfer and LD growth.

Understanding biological function requires the identification and characterization of complex patterns of molecules. Single-molecule localization microscopy (SMLM) can quantitatively measure molecular components and interactions at resolutions far beyond the diffraction limit, but this information is only useful if these patterns can be quantified and interpreted. We provide a new approach for the analysis of SMLM data that develops the concept of structures and super-structures formed by interconnected elements, such as smaller protein clusters. Using a formal framework and a parameter-free algorithm, (super-)structures formed from smaller components are found to be abundant in classes of nuclear proteins, such as heterogeneous nuclear ribonucleoprotein particles (hnRNPs), but are absent from ceramides located in the plasma membrane. We suggest that mesoscopic structures formed by interconnected protein clusters are common within the nucleus and have an important role in the organization and function of the genome. Our algorithm, SuperStructure, can be used to analyze and explore complex SMLM data and extract functionally relevant information.

The key endosomal regulators Rab5, EEA1, and APPL1 are frequently applied in fluorescence microscopy to mark early endosomes, whereas Rab7 is used as a marker for late endosomes and lysosomes. However, endogenous levels of these proteins localize poorly in immuno-EM, and systematic studies on their native ultrastructural distributions are lacking. To address this gap, we here present a quantitative, on-section correlative light and electron microscopy (CLEM) approach. Using the sensitivity of fluorescence microscopy, we label hundreds of organelles that are subsequently visualized by EM and classified by ultrastructure. We show that Rab5 predominantly marks small, endocytic vesicles and early endosomes. EEA1 colocalizes with Rab5 on early endosomes, but unexpectedly also labels Rab5-negative late endosomes, which are positive for PI(3)P but lack Rab7. APPL1 is restricted to small Rab5-positive, tubulo-vesicular profiles. Rab7 primarily labels late endosomes and lysosomes. These data increase our understanding of the structural-functional organization of the endosomal system and introduce quantitative CLEM as a sensitive alternative for immuno-EM.

Colocalization analysis of multicolor microscopy images is a cornerstone approach in cell biology. It provides information on the localization of molecules within subcellular compartments and allows the interrogation of known molecular interactions in their cellular context. However, almost all colocalization analyses are designed for two-color images, limiting the type of information that they reveal. Here, we describe an approach, termed "conditional colocalization analysis," for analyzing the colocalization relationships between three molecular entities in three-color microscopy images. Going beyond the question of whether colocalization is present or not, it addresses the question of whether the colocalization between two entities is influenced, positively or negatively, by their colocalization with a third entity. We benchmark the approach and showcase its application to investigate receptor-downstream adaptor colocalization relationships in the context of functionally relevant plasma membrane locations. The software for conditional colocalization analysis is available at https://github.com/kjaqaman/conditionalColoc.

Correlative electron and fluorescence microscopy has the potential to elucidate the ultrastructural details of dynamic and rare cellular events, but has been limited by low precision and sensitivity. Here we present a method for direct mapping of signals originating from ∼20 fluorescent protein molecules to 3D electron tomograms with a precision of less than 100 nm. We demonstrate that this method can be used to identify individual HIV particles bound to mammalian cell surfaces. We also apply the method to image microtubule end structures bound to mal3p in fission yeast, and demonstrate that growing microtubule plus-ends are flared in vivo. We localize Rvs167 to endocytic sites in budding yeast, and show that scission takes place halfway through a 10-s time period during which amphiphysins are bound to the vesicle neck. This new technique opens the door for direct correlation of fluorescence and electron microscopy to visualize cellular processes at the ultrastructural scale.

Volume electron microscopy is an important imaging modality in contemporary cell biology. Identification of intracellular structures is a laborious process limiting the effective use of this potentially powerful tool. We resolved this bottleneck with automated segmentation of intracellular substructures in electron microscopy (ASEM), a new pipeline to train a convolutional neural network to detect structures of a wide range in size and complexity. We obtained dedicated models for each structure based on a small number of sparsely annotated ground truth images from only one or two cells. Model generalization was improved with a rapid, computationally effective strategy to refine a trained model by including a few additional annotations. We identified mitochondria, Golgi apparatus, endoplasmic reticulum, nuclear pore complexes, caveolae, clathrin-coated pits, and vesicles imaged by focused ion beam scanning electron microscopy. We uncovered a wide range of membrane-nuclear pore diameters within a single cell and derived morphological metrics from clathrin-coated pits and vesicles, consistent with the classical constant-growth assembly model.

Object detection networks are high-performance algorithms famously applied to the task of identifying and localizing objects in photography images. We demonstrate their application for the classification and localization of cells in fluorescence microscopy by benchmarking four leading object detection algorithms across multiple challenging 2D microscopy datasets. Furthermore we develop and demonstrate an algorithm that can localize and image cells in 3D, in close to real time, at the microscope using widely available and inexpensive hardware. Furthermore, we exploit the fast processing of these networks and develop a simple and effective augmented reality (AR) system for fluorescence microscopy systems using a display screen and back-projection onto the eyepiece. We show that it is possible to achieve very high classification accuracy using datasets with as few as 26 images present. Using our approach, it is possible for relatively nonskilled users to automate detection of cell classes with a variety of appearances and enable new avenues for automation of fluorescence microscopy acquisition pipelines.

In parallel with the development of tissue-clearing methods, over the last decade, light sheet fluorescence microscopy has contributed to major advances in various fields, such as cell and developmental biology and neuroscience. While biologists are increasingly integrating three-dimensional imaging into their research projects, their experience with the technique is not always up to their expectations. In response to a survey of specific challenges associated with sample clearing and labeling, image acquisition, and data analysis, we have critically assessed the recent literature to characterize the difficulties inherent to light sheet fluorescence microscopy applied to cleared biological samples and to propose solutions to overcome them. This review aims to provide biologists interested in light sheet fluorescence microscopy with a primer for the development of their imaging pipeline, from sample preparation to image analysis. Importantly, we believe that issues could be avoided with better anticipation of image analysis requirements, which should be kept in mind while optimizing sample preparation and acquisition parameters.

In recent years, Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) has emerged as a flexible method that enables semi-automated volume ultrastructural imaging. We present a toolset for adherent cells that enables tracking and finding cells, previously identified in light microscopy (LM), in the FIB-SEM, along with the automatic acquisition of high-resolution volume datasets. We detect the underlying grid pattern in both modalities (LM and EM), to identify common reference points. A combination of computer vision techniques enables complete automation of the workflow. This includes setting the coincidence point of both ion and electron beams, automated evaluation of the image quality and constantly tracking the sample position with the microscope's field of view reducing or even eliminating operator supervision. We show the ability to target the regions of interest in EM within 5 µm accuracy while iterating between different targets and implementing unattended data acquisition. Our results demonstrate that executing volume acquisition in multiple locations autonomously is possible in EM.

Current knowledge of the structural changes taking place during clathrin-mediated endocytosis is largely based on electron microscopy images of fixed preparations and x-ray crystallography data of purified proteins. In this paper, we describe a study of clathrin-coated pit dynamics in living cells using ion conductance microscopy to directly image the changes in pit shape, combined with simultaneous confocal microscopy to follow molecule-specific fluorescence. We find that 70% of pits closed with the formation of a protrusion that grew on one side of the pit, covered the entire pit, and then disappeared together with pit-associated clathrin-enhanced green fluorescent protein (EGFP) and actin-binding protein-EGFP (Abp1-EGFP) fluorescence. This was in contrast to conventionally closing pits that closed and cleaved from flat membrane sheets and lacked accompanying Abp1-EGFP fluorescence. Scission of both types of pits was found to be dynamin-2 dependent. This technique now enables direct spatial and temporal correlation between functional molecule-specific fluorescence and structural information to follow key biological processes at cell surfaces.