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Abstract Mapping neuronal networks is a central focus in neuroscience. While volume electron microscopy (vEM) can reveal the fine structure of neuronal networks (connectomics), it does not provide molecular information to identify cell types or functions. We developed an approach that uses fluorescent single-chain variable fragments (scFvs) to perform multiplexed detergent-free immunolabeling and volumetric-correlated-light-and-electron-microscopy on the same sample. We generated eight fluorescent scFvs targeting brain markers. Six fluorescent probes were imaged in the cerebellum of a female mouse, using confocal microscopy with spectral unmixing, followed by vEM of the same sample. The results provide excellent ultrastructure superimposed with multiple fluorescence channels. Using this approach, we documented a poorly described cell type, two types of mossy fiber terminals, and the subcellular localization of one type of ion channel. Because scFvs can be derived from existing monoclonal antibodies, hundreds of such probes can be generated to enable molecular overlays for connectomic studies.

IntroductionMacular Telangiectasia type 2 (MacTel), is an uncommon form of late-onset, slowly-progressive macular degeneration. Associated with regional Müller glial cell loss in the retina and the amino acid serine synthesized by Müller cells, the disease is functionally confined to a central retinal region – the MacTel zone.MethodsWe have used high-throughput multi-resolution electron microscopy techniques, optimized for disease analysis, to study the retinas from two women, mother and daughter, aged 79 and 48 years respectively, suffering from MacTel.ResultsIn both eyes, the principal observations made were changes specific to mitochondrial structure both outside and within the MacTel zone in all retinal cell types, with the exception of those in the retinal pigment epithelium (RPE). The lesion areas, which are a hallmark of MacTel, extend from Bruch’s membrane and the choriocapillaris, through all depths of the retina, and include cells from the RPE, retinal vascular elements, and extensive hypertrophic basement membrane material. Where the Müller glial cells are lost, we have identified a significant population of microglial cells, exclusively within the Henle fiber layer, which appear to ensheathe the Henle fibers, similar to that seen normally by Müller cells.DiscussionSince Müller cells synthesize retinal serine, whereas retinal neurons do not, we propose that serine deficiency, required for normal mitochondrial function, may relate to mitochondrial changes that underlie the development of MacTel. With mitochondrial changes occurring retina-wide, the question remains as to why the Müller cells are uniquely susceptible within the MacTel zone.

Connectomics is fundamental in propelling our understanding of the nervous system's organization, unearthing cells and wiring diagrams reconstructed from volume electron microscopy (EM) datasets. Such reconstructions, on the one hand, have benefited from ever more precise automatic segmentation methods, which leverage sophisticated deep learning architectures and advanced machine learning algorithms. On the other hand, the field of neuroscience at large, and of image processing in particular, has manifested a need for user-friendly and open source tools which enable the community to carry out advanced analyses. In line with this second vein, here we propose mEMbrain, an interactive MATLAB-based software which wraps algorithms and functions that enable labeling and segmentation of electron microscopy datasets in a user-friendly user interface compatible with Linux and Windows. Through its integration as an API to the volume annotation and segmentation tool VAST, mEMbrain encompasses functions for ground truth generation, image preprocessing, training of deep neural networks, and on-the-fly predictions for proofreading and evaluation. The final goals of our tool are to expedite manual labeling efforts and to harness MATLAB users with an array of semi-automatic approaches for instance segmentation. We tested our tool on a variety of datasets that span different species at various scales, regions of the nervous system and developmental stages. To further expedite research in connectomics, we provide an EM resource of ground truth annotation from four different animals and five datasets, amounting to around 180 h of expert annotations, yielding more than 1.2 GB of annotated EM images. In addition, we provide a set of four pre-trained networks for said datasets. All tools are available from https://lichtman.rc.fas.harvard.edu/mEMbrain/. With our software, our hope is to provide a solution for lab-based neural reconstructions which does not require coding by the user, thus paving the way to affordable connectomics.

Neuroscientists can leverage technological advances to image neural tissue across a range of different scales, potentially forming the basis for the next generation of brain atlases and circuit reconstructions at submicron resolution, using Electron Microscopy and X-ray Microtomography modalities. However, there is variability in data collection, annotation, and storage approaches, which limits effective comparative and secondary analysis. There has been great progress in standardizing interfaces for large-scale spatial image data, but more work is needed to standardize annotations, especially metadata associated with neuroanatomical entities. Standardization will enable validation, sharing, and replication, greatly amplifying investment throughout the connectomics community. We share key design considerations and a usecase developed for metadata for a recent large-scale dataset.

Multicolour images are difficult to acquire with large-scale microscopy approaches. Here the authors present a microtome-assisted microscope capable of trichromatic two-photon excitation and label-free nonlinear modalities based on wavelength mixing, and use it to analyze astrocyte morphology and neuronal projections in thick brain samples.

Abstract Imaging as a means of scientific data storage has evolved rapidly over the past century from hand drawings, to photography, to digital images. Only recently can sufficiently large datasets be acquired, stored, and processed such that tissue digitization can actually reveal more than direct observation of tissue. One field where this transformation is occurring is connectomics: the mapping of neural connections in large volumes of digitized brain tissue.

Recent improvements in correlative light and electron microscopy (CLEM) technology have led to dramatic improvements in the ability to observe tissues and cells. Fluorescence labeling has been used to visualize the localization of molecules of interest through immunostaining or genetic modification strategies for the identification of the molecular signatures of biological specimens. Newer technologies such as tissue clearing have expanded the field of observation available for fluorescence labeling; however, the area of correlative observation available for electron microscopy (EM) remains restricted. In this study, we developed a large-area CLEM imaging procedure to show specific molecular localization in large-scale EM sections of mouse and marmoset brain. Target molecules were labeled with antibodies and sequentially visualized in cryostat sections using fluorescence and gold particles. Fluorescence images were obtained by light microscopy immediately after antibody staining. Immunostained sections were postfixed for EM, and silver-enhanced sections were dehydrated in a graded ethanol series and embedded in resin. Ultrathin sections for EM were prepared from fully polymerized resin blocks, collected on silicon wafers, and observed by multibeam scanning electron microscopy (SEM). Multibeam SEM has made rapid, large-area observation at high resolution possible, paving the way for the analysis of detailed structures using the CLEM approach. Here, we describe detailed methods for large-area CLEM in various tissues of both rodents and primates.

Recent developments in serial-section electron microscopy allow the efficient generation of very large image data sets but analyzing such data poses challenges for software tools. Here we introduce Volume Annotation and Segmentation Tool (VAST), a freely available utility program for generating and editing annotations and segmentations of large volumetric image (voxel) data sets. It provides a simple yet powerful user interface for real-time exploration and analysis of large data sets even in the Petabyte range.

Affiliation 4 incorrectly read ‘University of the Basque Country (Ikerbasque), University of the Basque Country and Donostia International Physics Center, San Sebastian 20018, Spain.’ Also, the affiliations of Ignacio Arganda-Carreras with ‘IKERBASQUE, Basque Foundation for Science, Bilbao, 48013, Spain’ and ‘Donostia International Physics Center (DIPC), San Sebastian, 20018, Spain’ were inadvertently omitted. Additionally, the third sentence of the first paragraph of the Results section entitled ‘Multicontrast organ-scale imaging with ChroMS microscopy’ incorrectly read ‘For example, one can choose lambda1 = 850 and lambda2 = 110 nm for optimal two-photon excitation of blue and red chromophores.’. The correct version reads ‘lambda2 = 1100 nm’ instead of ‘lambda2 = 110 nm’. These errors have now been corrected in the PDF and HTML versions of the Article.

OBJECTIVES/SPECIFIC AIMS: Müller cells, radial glial cells of the retina, are the principal repository of xanthophyll pigment (lutein, zeaxanthin, meso-zeaxanthin), which are modifiable by diet and visible clinically by autofluorescence imaging. To understand the structural basis of xanthophyll visualization in vivo, we used 3-dimensional electron microscopic reconstruction of Müller cells surrounding one cone in a healthy human fovea. METHODS/STUDY POPULATION: From a 21-year-old male organ donor, dissected retinas were rejuvenated by oxygenated Ames medium then fixed in 4% glutaraldehyde. A tissue block 3.5 mm2 centered on the fovea was prepared for Automated Tape Ultramicrotomy (Kasthuri et al., Cell 162: 648–661, 2015). From 1462 serial 65 nm horizontal sections, an area ~250×250 μm was imaged at 6 nm xy resolution. Images were stitched and aligned. TrackEM software on a pen display was used to trace, reconstruct, and display cone #5 (of 186) and its contacting Müller cells. RESULTS/ANTICIPATED RESULTS: Cone 5 is ensheathed by 2 types of Müller cells, outer and inner (Dacey, ARVO, 2016). The outer cell is first seen at the external limiting membrane (ELM) between cones 5 and 17. Moving inward from the ELM, it tightly wraps around cone 5’s fiber in a C-shape profile for 78 µm. This Müller cell also intermittently projects to neighboring cones, 2 of which were close to cone 5 at the ELM. As cone 5’s axon approaches the pedicle, it contorts into a corkscrew. The outer cell fluidly molds to this changing shape. At this level, this Müller cell doubles in volume to encompass not only cone 5, but also cone 17 and another Müller cell. In the final 17 µm of the block the Müller cell’s volume quickly dissipates as it sends a small projection towards the internal limiting membrane, eventually encasing an OFF midget bipolar cell also associated with cone 5. In contrast to this outer cell, an inner Müller cell adjoining cone 5 spans only 19 µm, interacting directly with cone 5 and the outer cell for 3.9 µm. DISCUSSION/SIGNIFICANCE OF IMPACT: Neural-glial relationships in a human fovea are visible through 3-dimensional volume EM. The volume of Müller cells in the fovea was impressive, consistent with a pivotal role in the health of cone photoreceptors and xanthophyll homeostasis. It is possible that individual glia also ensheath the post-receptoral neurons in a cone-driven circuit, supporting the concept that xanthophylls contribute to neural efficiency in vision.

We describe a method to label specific membrane proteins with fluorophores for live imaging. Fusion proteins are generated that incorporate into their extracellular domains short peptide sequences (13–38 amino acids) recognized with high affinity and specificity by protein ligands, α-bungarotoxin (BTX), or streptavidin (SA). Many fluorophore- and enzyme-conjugated derivatives of both ligands are commercially available. To demonstrate the general utility of the methods, we tagged a vesicle-associated protein (VAMP2), a receptor tyrosine kinase [muscle-specific kinase (MuSK)], and receptors for three neurotransmitters: acetylcholine (nAChRα3), glutamate (mGluR2), and γ-aminobutyric acid (GABAAα3). In all cases, we could selectively label surface-exposed proteins without interference from intracellular pools. By successive pulse-labeling with different fluorophore conjugates of a single ligand, we were able to monitor endocytosis of tagged molecules. By combining the two ligands, we could assess co-localization of synaptic components in cells. This strategy for epitope tagging provides a useful adjunct to green fluorescent protein (GFP)-tagging, which fails to distinguish intracellular from extracellular pools, sometimes interferes with protein localization or function, and requires a separate construct for each color.

Connectomics has recently begun to image brain tissue at nanometer resolution, which produces petabytes of data. This data must be aligned, labeled, proofread, and formed into graphs, and each step of this process requires visualization for human verification. As such, we present the BUTTERFLY middleware, a scalable platform that can handle massive data for interactive visualization in connectomics. Our platform outputs image and geometry data suitable for hardware-accelerated rendering, and abstracts low-level data wrangling to enable faster development of new visualizations. We demonstrate scalability and extendability with a series of open source Web-based applications for every step of the typical connectomics workflow: data management and storage, informative queries, 2D and 3D visualizations, interactive editing, and graph-based analysis. We report design choices for all developed applications and describe typical scenarios of isolated and combined use in everyday connectomics research. In addition, we measure and optimize rendering throughput—from storage to display—in quantitative experiments. Finally, we share insights, experiences, and recommendations for creating an open source data management and interactive visualization platform for connectomics.

The automated tape-collecting ultramicrotome (ATUM) makes it possible to collect large numbers of ultrathin sections quickly—the equivalent of a petabyte of high resolution images each day. However, even high throughput image acquisition strategies generate images far more slowly (at present ~1 terabyte per day). We therefore developed WaferMapper, a software package that takes a multi-resolution approach to mapping and imaging select regions within a library of ultrathin sections. This automated method selects and directs imaging of corresponding regions within each section of an ultrathin section library that may contain many thousands of sections. Using WaferMapper, it is possible to map all the sections at low resolution and target multiple points of interest for high resolution imaging based on anatomical landmarks. The program can also be used to expand previously imaged regions, acquire data under different imaging conditions, or re-image after additional tissue treatments.

The inner ear is a fluid-filled closed-epithelial structure whose function requires maintenance of an internal hydrostatic pressure and fluid composition. The endolymphatic sac (ES) is a dead-end epithelial tube connected to the inner ear whose function is unclear. ES defects can cause distended ear tissue, a pathology often seen in hearing and balance disorders. Using live imaging of zebrafish larvae, we reveal that the ES undergoes cycles of slow pressure-driven inflation followed by rapid deflation. Absence of these cycles in lmx1bb mutants leads to distended ear tissue. Using serial-section electron microscopy and adaptive optics lattice light-sheet microscopy, we find a pressure relief valve in the ES comprised of partially separated apical junctions and dynamic overlapping basal lamellae that separate under pressure to release fluid. We propose that this lmx1-dependent pressure relief valve is required to maintain fluid homeostasis in the inner ear and other fluid-filled cavities.

In many parts of the nervous system, signals pass across multiple synaptic relays on their way to a destination, but little is known about how these relays form and the function they serve. To get some insight into this question we ask how the connectivity patterns are organized at two successive synaptic relays in a simple, cholinergic efferent pathway. We found that the organization at successive relays in the parasympathetic nervous system strongly resemble each other despite the different embryological origin and physiological properties of the pre- and postsynaptic cells. Additionally, we found a similar developmental synaptic pruning and elaboration strategy is used at both sites to generate their adult organizations. The striking parallels in adult innervation and developmental mechanisms at the relays argue that a general strategy is in operation. We discuss why from a functional standpoint this structural organization may amplify central signals while at the same time maintaining positional targeting.

Resolving patterns of synaptic connectivity in neural circuits currently requires serial section electron microscopy. However, complete circuit reconstruction is prohibitively slow and may not be necessary for many purposes such as comparing neuronal structure and connectivity among multiple animals. Here, we present an alternative strategy, targeted reconstruction of specific neuronal types. We used viral vectors to deliver peroxidase derivatives, which catalyze production of an electron-dense tracer, to genetically identify neurons, and developed a protocol that enhances the electron-density of the labeled cells while retaining the quality of the ultrastructure. The high contrast of the marked neurons enabled two innovations that speed data acquisition: targeted high-resolution reimaging of regions selected from rapidly-acquired lower resolution reconstruction, and an unsupervised segmentation algorithm. This pipeline reduces imaging and reconstruction times by two orders of magnitude, facilitating directed inquiry of circuit motifs.