key: cord-0284412-mb77sis3
authors: Dittmayer, Carsten; Goebel, Hans-Hilmar; Heppner, Frank L.; Stenzel, Werner; Bachmann, Sebastian
title: Preparation of large-scale digitization samples for automated electron microscopy of tissue and cell ultrastructure
date: 2021-03-02
journal: bioRxiv
DOI: 10.1101/2021.03.02.433512
sha: 02c0e51b58bb51f7a331163ca3cd2370c77f8624
doc_id: 284412
cord_uid: mb77sis3

Manual selection of targets in experimental or diagnostic samples by transmission electron microscopy (TEM), based on single overview and detail micrographs, has been time- consuming and susceptible to bias. Substantial information and throughput gain may now be achieved by automated acquisition of virtually all structures in a given EM section. Resulting datasets allow convenient pan-and-zoom examination of tissue ultrastructure with preserved microanatomical orientation. The technique is, however, critically sensitive to artifacts in sample preparation. We therefore established a methodology to prepare large-scale digitization samples (LDS) designed to acquire entire sections free of obscuring flaws. For evaluation, we highlight the supreme performance of scanning EM in transmission mode compared to other EM technology. The use of LDS will substantially facilitate access to EM data for a broad range of applications.

Electron microscopy (EM) continues to be a valuable tool in basic research and anatomical pathology. Aside from educated inspection of regions of interest (ROI) by the operator, EM traditionally serves to detect unexpected features in cells and tissues in an "open view" manner 1 . In research, EM allows flexible recording of structures that may vary in size by three orders of magnitude, delivering excellent resolution down to the nanometer scale. In diagnosis of disease, EM is irreplaceable for muscle or kidney biopsies 1, 2 . The traditional workflow for transmission electron microscopy (TEM) with an operator interactively screening specimens at low magnification and selecting targets of interest for snapshots at high resolution may, however, be time-consuming, laborious, and sensitive to bias so that its use became diminished over the past decades despite its undisputed values 3, 4 . Consequent loss of expertise may lead to misinterpretations as recently reported for coronavirus particle structure in SARS-CoV-2 pandemic 3, 5, 6 .

State-of-the-art EM technology now has made substantial progress to revolutionize the traditional approach. Introducing large-scale digitization of ultrathin sections, i.e. the automated recording of ROIs in an unbiased manner with overlapping, high-resolution TEM images (mosaic tiling) has been a major step forward. ROIs may now be as large as the entire ultrathin section. Collected datasets permit software-assisted pan-and-zoom examination independent of the physical location of the facility. This mode has been termed nanotomy, nanoscopy, or virtual EM 4, [7] [8] [9] . A TEM equipped with a computer-driven stage may be used therefore, although with major restrictions 4, 8, 9 . For a better and more flexible alternative, the traditional scanning electron microscope (SEM) has been modernized.

Automated acquisition procedures, extended scanfields, and improved detectors have documented its benefits in large-scale digitization of extended ROIs 10, 11 . For SEM in backscattered electron detection mode, sections are comfortably collected and stained on stable material such as silicon wafer substrate to be imaged individually for 2D nanotomy or, in series, for array tomography and volume EM 11 . Inherent stability of the sections favours as well the recording of concomitant light microscopical signals for correlative light-and electron microscopy (CLEM) 12 . However, high electrical conductivity and contrast are mandatory for these samples 13 , and image acquisition time in SEM-BSD may be slow, ranging between 30 and 60 h per mm 2 with 6 to 12 µs beam dwell time per pixel and 7.3 nm pixel size adjusted.

Alternatively, an SEM platform adjusted for scanning TEM mode (SEM-STEM) has proven superior imaging performance and was compatible with conventionally prepared samples [14] [15] [16] . Here, a tenfold accelerated image acquisition at e.g. 1 µs dwell time is easily achievable.

Still, the SEM-STEM mode depends on the use of EM grids carrying the sections, whose preparation is technically more demanding compared to silicon wafers. The use of grids notoriously encompasses a number of artifacts, but typically occurring wrinkles and contaminations, which may impair high-end automated image acquisition, visual examination and quantifying approaches substantially, had to be avoided 14 . A substantial need for technological improvement prevailed to overcome this bottleneck in quality and prepare entire sections with virtual absence of flaws.

We therefore set out to establish a reliable and easy-to-implement workflow to produce sections on large-slot, filmed grids. Resulting large-scale digitization samples (LDS), virtually free of artifacts and with slot dimensions of up to 2 x 1.5 mm, were suitable to be digitized in conventional modern SEM-STEM systems at high throughput and also permitted individual high-end examination using advanced TEM systems. We further address the emerging need for a straightforward data processing pipeline. Resulting bigtif files allow in-depth analysis with the help of tools for annotation and measurement. We illustrate the potential of LDS to improve access to high-quality EM analysis for a broad user community.

Requirements for large-scale digitization. Reliable and easy-to-implement methodology for the preparation of ultrathin sections was to be adapted for large-scale digitization with modern SEM-STEM or TEM systems, serving to analyze a broad range of native or experimental tissues and cells. Since artifacts critically impair recording at large scale, a central goal was to prevent formation of wrinkles, stain precipitates, and other contaminations. Therefore, selection and treatment of grids, collection of large-size sections, and staining steps were to be specified. For simplicity, the resulting specimens comprising the filmed slot grid and the large ultrathin or semithin section were termed large-scale digitization samples (LDS). EM recording of LDS had to meet the criteria of high imaging speed, optimal tile size, adequate automation, high structural resolution, and satisfactory signal-to-noise ratio (SNR).

Preparing support films for LDS. Grids were coated using pioloform film for its established mechanical and thermal stability 17 . Film had to be placed on the shiny side of the grid to secure a smooth transition between slot and metal surface (Fig. 1a-c) . Typical film artifacts such as series of spots of different size and shape, deformations resulting from focal attachments to glass, or variations in thickness could be substantially reduced ( Fig. S1 and Providing hydrophilicity of filmed grids. Hydrophilicity of the support film was a strong requirement to avoid artifacts when mounting sections on the grid. This was achieved by glow-discharging the grid surface using a vacuum evaporator. A current of 6.6 to 6.9 mA and a duration of 10 s were optimal for the process; deviations in time caused wrinkle formation during collection due to over-or underhydration of the support. Prior to collection, grids were individually dipped in ethanol and distilled water. This step was critical to prevent fine needleor "geographical"folds ( Fig. 1g-l) .

Preparing sections for LDS or silicon wafer. Tissue blocks were trimmed to a slim leading edge, and areas of pure resin were removed for optimal consistency of the samples. Ultrathin sections (60-70 nm) were carefully prepared to avoid folds or knife marks. For electron tomography, semithin sections (200-250 nm) were cut and intensely stretched using xylene vapor to reduce compression. Mechanical vibrations of local or external origin had to be controlled to avoid chatters (Fig. S2 ).

Collecting and attaching the sections for LDS or silicon wafers. For imaging with SEM-STEM or TEM, the filmed grids were used. After sectioning, the grid was submersed in the water bath of the diamond knife and the sections directed to the site of attachment at a straight borderline between water and grid surface using an eyelash. Here, the grid was to be held at its edge near the short side of the slot by a forceps to ensure straightness of the borderline (Fig. S3) . The section was picked up by lifting the grid out of the water trough.

Holding the grid in horizontal position by the forceps, the section was then dried. Quality of the drying process had to be closely monitored. It comprised two different phases, one, the drying of the film's back side which had to start from the periphery (Fig. 1a) , and another, the drying between section and film which had to start from the center as indicated by Newton ring formation (Fig. 1b) . Ideally, no folds or wrinkles resulted from this initial drying process.

For completion of the process, drying was then extended for another 1 or 2 d to avoid ringshaped wrinkles during consecutive staining. For comparative SEM-BSD imaging, sections were collected on silicon fragments that had been glow-discharged for 60 to 90 s The size of the fragments allowed to collect multiple sections. 

For conventional imaging, minimized preparation artifacts and absence of obscuring bars in LDS permitted a significantly more rapid navigation and improved imaging results as compared to standard samples (Fig. S1 ). Medium-sized ROIs of muscle, nerve, liver ( Fig. S4 ) or brain and kidney sections (Fig. 2a,d) For electron tomography (ET), the SEM-STEM system was used to record LDS carrying serial semithin sections (Fig. 5b) . ROIs from these sections were digitized at high resolution, profiting from the absence of artifacts as well. Preparation of multiple sections allowed to either select a single section with optimal detail for 3D analysis of small volumes or analyze volumes that extend the thickness of single sections by applying ET to the same ROI of consecutive sections in form of serial-section ET. Here, shuttling of LDS to the TEM allowed to apply complementary imaging in tomography mode. Combining ET with the respective overview data generated by SEM-STEM thus preserved contextual orientation of the detail (Fig. 5b,c) . A robust basis was thus created to reliably find small ROIs within sections which had been selected for ET before, and the risk of electron beam damage to the section, resulting from extensive live examination, was reduced as well.

Digitizing at large-scale in SEM-BSD. Analyzing ultrathin sections placed on silicon substrate with SEM-BSD, we adapted imaging time for medium-sized ROIs to meet the duration of 1 h. As for SEM-STEM, we selected 7.3 nm pixel size and 3 µs dwell time for digitization ( Fig. 2c,f) . Conventionally embedded material required careful adjustment of further imaging parameters such as working distance and accelerating voltage. Keeping the former small (4-5 mm) and setting the latter at 8 kV resulted in satisfactory SNR typically found in lipid-enriched, compact tissue samples like nerve and muscle, which accumulate high amounts of heavy metals during preparation. SNR was further improved by uranyl acetate en bloc staining. Samples with lower heavy metal content such as kidney biopsies required setting of the aperture diameter at 60 rather than standard 30 µm. Resulting datasets demonstrated an overall satisfactory image quality, however, the subcellular detail was often obscured by inadequate SNR; 10-fold extended dwell times were required to obtain adequate results comparable to SEM-STEM (Fig. 6 ).

Data processing and analysis. Generation of large-scale datasets required the stitching of image tiles to coherent datasets and their conversion into zoomable file format. For TEM, datasets of medium-sized ROIs were suitably generated with TrakEM2. Increasing numbers of image tiles (e.g. 1,000+ 2k images) to be stitched together rendered the procedure vulnerable for misalignments. The stitched datasets were converted into bigtif files to enable pan-and-zoom examination and in-depth analysis with QuPath via annotation and measurements 18 . For SEM-STEM and SEM-BSD, Atlas 5 software permitted convenient stitching and export, but parameters serving to adjust eventual misalignments were limited, which impaired quality of some of the data. The Atlas 5 datasets for browser-based examination provided pan-and-zoom options, basic tools for analysis and convenient implementation into online repositories such as nanotomy.org. Alternatively, stitching and export to bigtif files were performed as for TEM datasets. Here, larger image tiles permitted efficient batch processing and export of multiple, large datasets in an overnight span.

Limitations of conventional TEM imaging are traditionally based on the need to manually select single ROIs which are then recorded individually in the appropriate ranges of resolution. This time-consuming mode has been technically overcome by automated largescale image acquisition enabling nanotomy 4, 9, 15, 19 . Our aim was to obtain EM samples suitable for this destination. 14, 15 We have presented methodology to prepare sections mounted on large-slot grids, termed LDS for their property of minimized artifacts and potential for high-end data acquisition. We have furthermore compared evaluation of LDS in TEM and SEM-STEM systems and discussed the alternative SEM-BSD approach. A robust data processing pipeline, based on open-source software, was proposed in order to create bigtif files which enabled in-depth analysis.

The search for causes and elimination strategies of artifacts in EM sections such as folds, staining precipitates and other contaminations, which obscure their inspection, has been challenging for decades [20] [21] [22] . Quality of the support film has been another source for artifacts; the delicate structure of commonly used support films led to the search of alternatives in materials and their processing, albeit without a breakthrough 23, 24 . Large-scale digitization of sections required further refinement in sample preparation to achieve adequate standards 14, 15 . The measures we took in order to produce reliable support films with minimal amounts of artifacts have been successful (Fig. S2 ). Standard slot grids with large opening sizes (2 x 1 or 2 x 1.5 mm) thus carried a pioloform film which also did not require additional carbon coating 9 . Thus, entire sections prepared from resin blocks in commonly used sizes could be collected for unobscured examination in the EM 7, 19 .

Optimizing the collection step of the sections onto the large-slot grids, control of the hydrophilicity of the grid surface was essential, since focal drying points confounded regular attachment of the sections to the pioloform film. Inadequate hydrophilicity of the grids was indeed problematic, since overhydration caused an oversized bulk of water on the grid during collection, resulting in improper attachment of sections, whereas underhydration led to inhomogeneous wetting of the film; both extremes inevitably led to artifacts.

Glow discharging of the filmed grids prior to collection of the sections essentially solved the problem, providing adequate hydrophilicity in a highly controllable manner. This step has formerly been in use to spread fluids on filmed grids in special applications, or to reduce wrinkles when collecting sections on silicon or plastic substrate 13, [25] [26] [27] . Reducing surface tension of the film by an ethanolic smoothening step prior to collection of the sections was essential as well. Monitoring the subsequent drying process of the sections on the film served as an important quality control.

Staining of sections was necessary, since we envisaged optimal SNR and imaging speed with conventionally embedded samples. Specific protocols for high-contrast en bloc staining were thus not applicable 13 , so that the risk of staining artifacts had to be accepted. A known pitfall is the potential reaction between uranyl acetate and lead citrate, resulting in massive contaminations 22 . This may be related with a vulnerable surface texture resulting from knife marks, folds, or cracks 22, 28 , which were minimized by LDS. Detachment artifacts of sections, forming ring-shaped wrinkles, may occur as well during the staining procedure. Similar artifacts have been described for semithin sections 29 , possibly caused by reaction of free epoxy groups with water. To overcome this problem, we simply extended the drying period of sections for LDS after collection for up to two days, based on the assumption that free epoxy groups may be inactivated by oxidation.

The resulting, refined LDS produced excellent results in conventional imaging and largescale digitization of medium-sized ROIs using a TEM, thus demonstrating viability in routine research and pathology applications. The main goal of our methodology was, however, to confirm whether LDS were reliably applicable for digitization of entire sections at a high throughput. Here, even modern TEM systems reach their limitations owing to small image fields and limited sample-holder capacities 9, 14 . Therefore, SEM-STEM was the optimal choice for its flexible capacities in automated digitization, with the additional advantage of minimal operator involvement 14 . The general benefits of SEM-STEM systems have been previously described, but it was also acknowledged that their performance was limited by flaws on the samples 14, 15 . This drawback has been essentially overcome by the present LDS methodology. Using LDS, imaging parameters such as dwell time and pixel size were varied to critically analyze structural detail in various tissues at intermediate resolution. Highresolution imaging using pixel sizes between 2 and 5 nm has been accomplished as well, albeit at the cost of long acquisition time 15 .

Selecting the SEM-BSD system as an alternative approach facilitates the collection of large sections singly or in series using silicon wafers 11 . Absence of fragile support films as well as an unobscured imaging potential for a larger tissue context favour this approach 30 . Using a standard acquisition speed of 3 µs dwell time, image quality of conventionally embedded samples was not sufficient in SEM-BSD mode owing to poor SNR, and structural detail like components of the glomerular filtration barrier was insufficiently resolved. Acquisition times ranging up to tenfold that of the SEM-STEM mode were required for similar outcomes which clearly limits the use of SEM-BSD. Imaging with SEM-BSD may be improved with advanced en bloc staining protocols, although other shortcomings related to lipid content of the respective tissues may be introduced hereby 13, 30 . Another drawback would be the resulting exclusion of already embedded tissues from routine pathology archives for research 16 .

While the SEM-STEM mode provided superior imaging performance in 2D nanotomy using LDS, collection of serial sections for 3D analysis was cumbersome due to the fragile nature of the support film. Here, the silicon substrate used in the SEM-BSD system delivered better performance with sections stably adhered. This approach is therefore preferable for 3D array tomography 11 . Stable adherence to substrate also favours correlative light-EM (CLEM) by reducing distortion of sections in consecutive imaging procedures 12 . Imaging quality of hydrophilic resin sections imaged by SEM-BSD may, however, be limited by low contrast. On the other hand, LDS prepared with hydrophilic resin sections stained for immunogold may be favorable with SEM-STEM for better contrast 31 . Likewise, LDS may be helpful in localizing electron dense polymers generated via genetically encoded tags that preserve the microanatomical context 32 .

Routine application of large-scale digitization using LDS may ideally be achieved in specialized EM facilities to make nanotomy available to a broad usership, matching current trends to centralize state-of-the-art technology for the sake of cost reduction and improved quality management 3, 33 . In research applications, digitization of entire sections will substantially improve analyses of cultured cells, organoids, animal models and human tissues with more detail and at higher throughput 7-9, 15, 34 . Medical diagnostic applications will be improved as well by the use of LDS, since for instance, about 20 entire renal glomeruli may be digitized overnight with SEM-STEM for optimal diagnostic accuracy 1, 3 . Future innovation in SEM-and TEM technology will allow faster imaging in conventional EM systems that may equally profit from LDS methodology 35, 36 .

In sum, we have presented a detailed workflow to prepare LDS carrying ultrathin sections free of limiting artifacts and ready for routine application of nanotomy. Perspectively, the use of LDS will greatly facilitate quantifying EM and consolidate a novel mode of expert consultation on EM data, based on comprehensive, digitized information. Smooth access to EM in multiple fields of cell biology and pathology becomes available. Online repositories will serve to share the respective information for data mining, translational approaches, and teaching. Technological innovation will make SEM-and TEM systems faster to further improve their routine application of LDS in the future. Preparation of support films for LDS. Support films were prepared by slide stripping as previously described 37 , with several adaptations to reduce artifacts and provide adequate quality for digitization of entire ultrathin sections (Fig. S1 ). Restrictions from mesh grids with obscuring grid bars were avoided by the use of filmed slot grids for unrestricted examination of entire sections prepared as LDS. Briefly, copper or nickel slot grids were ultrasoundcleaned in consecutive steps using acetone, pure ethanol, and distilled water (each 3 times for 2 min). Conventional microscope glass slides were cleaned with warm water and dishwashing detergent, rinsed with 70% denatured ethanol, dipped in pure ethanol, and dried with a Kimtech wipe. The dried slides were coated on their top sides with dry curd soap to ensure later detachment of the pioloform film. The curd soap was evenly distributed by intense rubbing in longitudinal and transverse directions with cotton wool for about 3 min.

Individual slides were then dipped into a filtered 0.7% pioloform solution in chloroform (100 ml in a larger cylinder) with a clamp, lifted smoothly, and held above the fluid for 15 s. The latter time span was facultatively adjusted to prepare a medium to heavy silver film interference color during floating. The slide was then removed and air-dried in dust-free atmosphere (3 min). After drying, the edges of the slide were gently scratched using a stiff razor blade to improve detachment. The pioloform film was then floated onto a water trough and slot grids with standard size (2 x 1 mm aperture) and extra-large slot grids (2 x 1.5 mm aperture) were then placed on the film with their shiny side down. A parafilm stripe was lowered onto the grids and removed with the grids attached. Grids were dried in a glass petri dish (2 d) to stabilize the film. Prior to cutting sections, grids were removed from parafilm and placed on a new sheet of parafilm, the shiny side up, and hydrophilized by glow-discharging in a MED020 sputter coater within the visible plasma zone for 10 s using argon gas at 1.1 to 1.3x10 -1 mbar and 6.6 to 6.9 mA. The hydrophilized grids were used within 2 to 6 h for collection of sections.

Ultramicrotomy. For 2D EM, ultrathin sections (60 to 70 nm), sized up to ~ 2 x 1.5 mm, were cut with an Ultracut E microtome (Reichert-Jung) or PowerTome (RMC) using an ultra 35° diamond knife for minimal compression of sections 38 (Diatome) and stretched using xylene vapor. The grids were picked at their short edge with a fine forceps, dipped into absolute ethanol, then 10 times into distilled water to achieve smoothening of the pioloform film, and then inserted into the water trough of the diamond knife (Fig. S3) . Sections were placed on the pioloform film by attachment of a section at the water-grid borderline and gently removing the grid from the water. Subsequent drying was controlled and documented via the stereomicroscope. For electron tomography, ribbons of multiple semithin sections (200-350 nm) were cut using an ultrasemi diamond knife (Diatome), stretched, and collected on grids. For optimal ribbon formation, the resin block was trimmed with a 20° diamond trim tool (Diatome) to provide parallel edges 39 . To release ribbons from the knife, section thickness was reduced to 5 nm for 1 to 2 cutting movements. For SEM-BSD imaging, ultrathin sections were placed on freshly glow-discharged silicon wafers as substrates 11 .

Contrasting for LDS. Prior to heavy metal staining, grids carrying the ultrathin sections were incubated in 1% aqueous EDTA solution (4 min) to reduce formation of embedding pepper 21 , then stained with 5% aqueous uranyl acetate (8 min) and Reynolds' lead citrate (3 min).

Between these steps, grids were washed with distilled water by moving them up and down gently for more than 20 times consecutively in three 25 ml glass beakers. Petri dishes for lead citrate staining were kept in carbon dioxide-reduced atmosphere by placing NaOH pellets next to the grids to prevent the formation of spherical precipitates during incubation.

Solutions were filtered prior to use (0.22 µm filter; Millipore) and drops pipetted on parafilm stripes attached to the bottom of glass Petri dishes. Grids were stained within the droplets, the section side up, and dried horizontally, held by the forceps. Grids carrying the semithin sections for electron tomography were stained with lead citrate alone (7 min); fiducial gold particles were then added by incubation on droplets for 3 min for each side, then dried with filter paper.

Tecnai G2 (FEI), equipped with a 4k CCD camera (Eagle), were used for standard examination and large-scale digitization. Large-scale digitization with both systems was performed largely as established earlier 4, 8, 9 . Briefly, both TEM systems provided a computer-driven stage to automatically acquire overlapping images in a serpentine pattern, digitizing selected regions of interest (ROI). With TEM 906, columns and rows were selected manually using ImageSP software for square or rectangular datasets, while the TEM Tecnai nm pixel size to define the borders of the sections, followed by overview images at 100 nm pixel size for higher image quality.

6. Beam alignments: Focus and correction for astigmatism were checked at 40,000 to 60,000x, then, the beam was wobbled to center the aperture. 7. Setting parameters: For most datasets, a pixel size of 7.3 nm or 9 nm was used with a tile size of 8k to 12k, resulting in image fields of 50-90 µm. Autofocus settings were adjusted for either automated digitization of multiple sections (using a range of about 10 µm) or digitization of single sections (using a range of 4-5 µm). Usually, 300-500% pixel ratio, 1-3 µs dwell time and pixel averaging (= line averaging 1) and autostigmation with 1% allowed reliable performance. However, in case of very large areas with insufficient amount of structural details, such as lumina of kidney tubules and lung alveoles, a pixel ratio of 1,000% was used in conjunction with an increased range of about 15 µm and a minimum dwell time of 3 µs. Autofocus and autostigmation were performed on the previous tiles. Brightness and contrast of each section or ROI were adjusted manually prior to imaging using small ROIs on representative tissue areas. stitching of TEM large-scale datasets, the images were renamed using bulk rename utility software (001.tif, 002.tif, etc.). The images for the ROI and the lens correction were then adjusted for brightness and contrast using Fiji, exported to 8-bit tif files and imported to TrakEM2. In case of major differences in brightness and contrast between the individual images, an image filter ("normalize local contrast") was applied for temporary compensation.

Images were then stitched by multiple consecutive alignment steps including values of the lens correction dataset. Temporary image filters were then removed and differences in brightness between the individual stitched images were facultatively permanently reduced with the "match intensities" tool. For export of small datasets, the "make flat image" tool was used to prepare a single standard tif file. For large datasets that exceed the pixel limit of standard tif files, a modified CATMAID export script by Stephan Saalfeld was used to export the ROI into multiple non-overlapping tiles with pixel dimensions of 25,000 x 25,000 pixels (see "https://github.com/axtimwalde/fiji-scripts/blob/master/TrakEM2/catmaid-export2.bsh", last accessed 29.10.2018). These tiles were then processed to one coherent large bigtif file using nip2.

For STEM-and BSD data, a similar workflow for processing was used. A text file for import of image tiles to TrakEM2 of up to about 10 entire digitized sections (up to about 4,000 image tiles) was prepared by calculation of image pixel coordinates using an Excel file, as positions of the tiles within each dataset are implemented in the image tile names. A template of this excel file, filled with data of several datasets and a brief documentation for its usage, is provided in the Supplementary Information. An Excel macro was used to extract numbers (see "https://www.extendoffice.com/excel/1622-excel-extract-number-fromstring.html?page_comment=6", last accessed 03.11.2020). For increased data processing speed, all processing steps were performed using a solid-state-drive (SSD). To reduce the size of the TrakEM2-project, jpg-format for mipmap generation was selected (see project properties in TrakEM2). Image tiles with very low amounts of structural information at the periphery of datasets were deleted manually. Only one alignment step with adjusted image parameters was performed (usually with minimum image size of "600" and maximum image size of "1600"), without introducing temporary image filters or lens correction. In case of intensity matching, a black background of image tiles was changed to white using photoshop with batch processing (replace color command, used with "0" tolerance to ensure only a switch of the artificially black background to white). For bigtif export, non-overlapping tif tiles were prepared as for TEM-datasets, however, up to 10 different macros were run in parallel for automated export for several h or overnight. Bigtif files allowed examination and in-depth analysis using QuPath open-source software 18 .

For 3D reconstruction of tilt images using fiducial gold particles, IMOD software package including etomo was used 40 .

Graphical abstract. Large-scale digitization samples (LDS) with virtual absence of limiting artifacts are prepared for advanced data acquisition. Scanning electron microscope (SEM) and transmission electron microscope (TEM) systems are compared for efficient imaging. A refined protocol is required to generate support films with reduced artifacts. Reliable, wrinklefree collection of sections is achieved by glow discharging and smoothening of the film under control of Newton ring formation. Contrasting is optimized by a smooth section surface and refinements of the staining protocol. An SEM operated in transmission mode (STEM) provides automation to reduce operator involvement. This enables efficient recording of large ROIs up to entire sections in high-throughput. Comparingly, TEM imaging is restricted to small-or medium-sized ROIs, but appropriate for additional electron tomography, high-end resolution, or conventional imaging. Processing of data includes stitching of image tiles to mosaics. Resulting large datasets comprise the context between overview and highly resolved detail. Export of data to bigtif files facilitates an improved analysis by annotations or quantification. b, Digital zooming of the boxed area in a; detail of a plaque, shows dystrophic neurites (arrows) and distinct fibrils (fi); neighboring capillaries with empty lumen (asterisk). c, Digital zooming of the boxed area in b; dystrophic, enlarged neurites are filled with autophagic vacuoles (av); note a synapse (asterisk). Images as shown were prepared by screenshots of an Atlas 5 export dataset. Scale bars, 500 µm (a), 10 µm (b), 1,000 nm (c). See also www.nanotomy.org for internet browser-based pan-and-zoom analysis of the full resolution dataset; see Supplementary Video for a demonstration of this analysis. 1 µs in f) increasingly compromise quality. The displayed images were prepared from tif raw data for highest quality in order to minimize image compression artifacts. Scale bars, 1,000 nm (a-f). See also www.nanotomy.org for internet browser-based pan-and-zoom analysis of the full resolution datasets.

The continued vital role of electron microscopy in the diagnosis of renal disease/dysfunction

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High-contrast en bloc staining of neuronal tissue for field emission scanning electron microscopy

Large-volume reconstruction of brain tissue from high-resolution serial section images acquired by SEM-based scanning transmission electron microscopy

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Scanning electron microscopy as a new tool for diagnostic pathology and cell biology

Pioloform F Instead of Formvar as a Support Film for TEM

QuPath: Open source software for digital pathology image analysis

Quality standards for diagnostic electron microscopy

Electron Microscopy, Methods and Protocols

Contamination of thin sections: Some observations on the cause and elimination of "embedding pepper

Forming and removing stain precipitates on ultrathin sections

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Computer visualization of threedimensional image data using IMOD

Diagnostic kidney sample with lupus nephritis, recorded by large-scale scanning transmission electron microscopy. a, Overview of an entire glomerulus (240 x 240 µm); digitization was performed within 25 min using 1 µs dwell time and 7.3 nm pixel size. b, Nuclei of an endothelial cell (E) and a podocyte (P) are readily identified in the coherent, large-scale dataset. c,d, Ultrastructural detail of the podocyte processes (po), glomerular basement membrane (bm), and endothelium (en) with prominent tubuloreticular inclusions (arrows) or electron dense deposits (ed) are well resolved

See also www.nanotomy.org for internet browser-based pan-and-zoom analysis of the full resolution dataset

The authors wish to thank Matthias Ochs for critical discussion of the work; Sara Timm, Petra Schrade, Cordula zum Bruch, Carola Geiler, Agnieszka Münster-Wandowski, and Imre Vida 

The authors declare no competing interests.

All data are available in the main text and the Supplementary Information, or are available upon request. Selected large-scale datasets are provided for open access pan-and-zoom analysis via www.nanotomy.org.

For this study, archive resin blocks from diagnostic muscle, nerve and kidney samples as well as experimental rodent tissues, embedded according to standard protocols, were used. 

A list of Supplementary Information is provided in a separate pdf.