The ability to localize proteins precisely within subcellular space is crucial to understanding the functioning of biological systems. Recently, we described a protocol that correlates a precise map of fluorescent fusion proteins localized using three-dimensional super-resolution optical microscopy with the fine ultrastructural context of three-dimensional electron micrographs. While it achieved the difficult simultaneous objectives of high photoactivated fluorophore preservation and ultrastructure preservation, it required a super-resolution optical and specialized electron microscope that is not available to many researchers. We present here a faster and more practical protocol with the advantage of a simpler two-dimensional optical (Photoactivated Localization Microscopy (PALM)) and scanning electron microscope (SEM) system that retains the often mutually exclusive attributes of fluorophore preservation and ultrastructure preservation. As before, cryosections were prepared using the Tokuyasu protocol, but the staining protocol was modified to be amenable for use in a standard SEM without the need for focused ion beam ablation. We show the versatility of this technique by labeling different cellular compartments and structures including mitochondrial nucleoids, peroxisomes, and the nuclear lamina. We also demonstrate simultaneous two-color PALM imaging with correlated electron micrographs. Lastly, this technique can be used with small-molecule dyes as demonstrated with actin labeling using phalloidin conjugated to a caged dye. By retaining the dense protein labeling expected for super-resolution microscopy combined with ultrastructural preservation, simplifying the tools required for correlative microscopy, and expanding the number of useful labels we expect this method to be accessible and valuable to a wide variety of researchers.

A central problem in neuroscience is reconstructing neuronal circuits on the synapse level. Due to a wide range of scales in brain architecture such reconstruction requires imaging that is both high-resolution and high-throughput. Existing electron microscopy (EM) techniques possess required resolution in the lateral plane and either high-throughput or high depth resolution but not both. Here, we exploit recent advances in unsupervised learning and signal processing to obtain high depth-resolution EM images computationally without sacrificing throughput. First, we show that the brain tissue can be represented as a sparse linear combination of localized basis functions that are learned using high-resolution datasets. We then develop compressive sensing-inspired techniques that can reconstruct the brain tissue from very few (typically 5) tomographic views of each section. This enables tracing of neuronal processes and, hence, high throughput reconstruction of neural circuits on the level of individual synapses.

Microscopic images of specific proteins in their cellular context yield important insights into biological processes and cellular architecture. The advent of superresolution optical microscopy techniques provides the possibility to augment EM with nanometer-resolution fluorescence microscopy to access the precise location of proteins in the context of cellular ultrastructure. Unfortunately, efforts to combine superresolution fluorescence and EM have been stymied by the divergent and incompatible sample preparation protocols of the two methods. Here, we describe a protocol that preserves both the delicate photoactivatable fluorescent protein labels essential for superresolution microscopy and the fine ultrastructural context of EM. This preparation enables direct 3D imaging in 500- to 750-nm sections with interferometric photoactivatable localization microscopy followed by scanning EM images generated by focused ion beam ablation. We use this process to "colorize" detailed EM images of the mitochondrion with the position of labeled proteins. The approach presented here has provided a new level of definition of the in vivo nature of organization of mitochondrial nucleoids, and we expect this straightforward method to be applicable to many other biological questions that can be answered by direct imaging.

The molecular mechanism responsible for capturing, sorting and retrieving vesicle membrane proteins following triggered exocytosis is not understood. Here we image the post-fusion release and then capture of a vesicle membrane protein, the vesicular acetylcholine transporter, from single vesicles in living neuroendocrine cells. We combine these measurements with super-resolution interferometric photo-activation localization microscopy and electron microscopy, and modelling to map the nanometer-scale topography and architecture of the structures responsible for the transporter’s capture following exocytosis. We show that after exocytosis, the transporter rapidly diffuses into the plasma membrane, but most travels only a short distance before it is locally captured over a dense network of membrane-resident clathrin-coated structures. We propose that the extreme density of these structures acts as a short-range diffusion trap. They quickly sequester diffusing vesicle material and limit its spread across the membrane. This system could provide a means for clathrin-mediated endocytosis to quickly recycle vesicle proteins in highly excitable cells.

A central problem in neuroscience is reconstructing neuronal circuits on the synapse level. Due to a wide range of scales in brain architecture such reconstruction requires imaging that is both high-resolution and high-throughput. Existing electron microscopy (EM) techniques possess required resolution in the lateral plane and either high-throughput or high depth resolution but not both. Here, we exploit recent advances in unsupervised learning and signal processing to obtain high depth-resolution EM images computationally without sacrificing throughput. First, we show that the brain tissue can be represented as a sparse linear combination of localized basis functions that are learned using high-resolution datasets. We then develop compressive sensing-inspired techniques that can reconstruct the brain tissue from very few (typically 5) tomographic views of each section. This enables tracing of neuronal processes and, hence, high throughput reconstruction of neural circuits on the level of individual synapses.

A fundamental objective in molecular biology is to understand how DNA is organized in concert with various proteins, RNA, and biological membranes. Mitochondria maintain and express their own DNA (mtDNA), which is arranged within structures called nucleoids. Their functions, dimensions, composition, and precise locations relative to other mitochondrial structures are poorly defined. Superresolution fluorescence microscopy techniques that exceed the previous limits of imaging within the small and highly compartmentalized mitochondria have been recently developed. We have improved and employed both two- and three-dimensional applications of photoactivated localization microscopy (PALM and iPALM, respectively) to visualize the core dimensions and relative locations of mitochondrial nucleoids at an unprecedented resolution. PALM reveals that nucleoids differ greatly in size and shape. Three-dimensional volumetric analysis indicates that, on average, the mtDNA within ellipsoidal nucleoids is extraordinarily condensed. Two-color PALM shows that the freely diffusible mitochondrial matrix protein is largely excluded from the nucleoid. In contrast, nucleoids are closely associated with the inner membrane and often appear to be wrapped around cristae or crista-like inner membrane invaginations. Determinations revealing high packing density, separation from the matrix, and tight association with the inner membrane underscore the role of mechanisms that regulate access to mtDNA and that remain largely unknown.

The challenge of recovering the topology of massive neuronal circuits can potentially be met by high throughput Electron Microscopy (EM) imagery. Segmenting a 3-dimensional stack of EM images into the individual neurons is difficult, due to the low depth-resolution in existing high-throughput EM technology, such as serial section Transmission EM (ssTEM). In this paper we propose methods for detecting the high resolution locations of membranes from low depth-resolution images. We approach this problem using both a method that learns a discriminative, over-complete dictionary and a kernel SVM. We test this approach on tomographic sections produced in simulations from high resolution Focused Ion Beam (FIB) images and on low depth-resolution images acquired with ssTEM and evaluate our results by comparing it to manual labeling of this data.

Cell adhesions to the extracellular matrix (ECM) are necessary for morphogenesis, immunity, and wound healing. Focal adhesions are multifunctional organelles that mediate cell-ECM adhesion, force transmission, cytoskeletal regulation and signaling. Focal adhesions consist of a complex network of trans-plasma-membrane integrins and cytoplasmic proteins that form a <200-nm plaque linking the ECM to the actin cytoskeleton. The complexity of focal adhesion composition and dynamics implicate an intricate molecular machine. However, focal adhesion molecular architecture remains unknown. Here we used three-dimensional super-resolution fluorescence microscopy (interferometric photoactivated localization microscopy) to map nanoscale protein organization in focal adhesions. Our results reveal that integrins and actin are vertically separated by a \~{}40-nm focal adhesion core region consisting of multiple protein-specific strata: a membrane-apposed integrin signaling layer containing integrin cytoplasmic tails, focal adhesion kinase, and paxillin; an intermediate force-transduction layer containing talin and vinculin; and an uppermost actin-regulatory layer containing zyxin, vasodilator-stimulated phosphoprotein and α-actinin. By localizing amino- and carboxy-terminally tagged talins, we reveal talin’s polarized orientation, indicative of a role in organizing the focal adhesion strata. The composite multilaminar protein architecture provides a molecular blueprint for understanding focal adhesion functions.