Richard D. Leapman

Volume electron microscopy (vEM) enables biologists to visualize nanoscale 3D ultrastructure of entire eukaryotic cells and tissues prepared by heavy atom staining and plastic embedding. The highest resolution vEM technique is focused ion-beam scanning electron microscopy (FIB-SEM), which provides nearly isotropic (~5-10 nm) spatial resolution at fluences of > 10,000 e^-/nm². However, it is not clear how such high resolution is achievable because serial block-face (SBF) SEM, which incorporates an in-situ ultramicrotome instead of a Ga⁺ FIB beam, results in radiation-induced collapse of similar specimen blocks at fluences of only ~20 e^-/nm². Moreover, the z-resolution (perpendicular to block-face) in FIB-SEM is substantially better than predicted by Monte Carlo modeling of SBF-SEM samples. Here, we show that FIB-SEM implants a thin highly concentrated layer of Ga⁺ ions at the block surface, which greatly reduces the effect of beam-damage, reduces the depth from which backscattered electrons are detected, and prevents specimen charging and collapse.

This study developed a new Cellular Omics-Structural Integration (COSI) technology platform to address the limitation of traditional technologies in simultaneously obtaining gene expression profiles and super-resolution cellular structural information at the single-cell level. The platform comprises three core functional modules: (1) a single-cell transcriptomics and super-resolution fluorescence microscopy integration module that enables simultaneous acquisition of gene expression profiles and super-resolution fluorescence images at the single-cell level; (2) an electron microscopy and super-resolution fluorescence microscopy integration module with deep learning resolution enhancement that further gives fluorescence image high resolution features; and (3) a comprehensive analysis module that integrates transcriptomic data with enhanced super-resolution morphological data. Application of this technology to primary liver sinusoidal endothelial cells successfully achieved efficient matching and analysis of ultrastructural information and gene transcription data at the single-cell level, revealing associations between specific genes and endothelial cell fenestration formation. Through correlation analysis and multivariate statistical methods, we identified specific gene sets associated with fenestration number and average area. Validation in published non-alcoholic steatohepatitis (NASH) and diabetic mouse models demonstrated that these gene sets can effectively assess disease status and drug intervention efficacy, with fenestration number-related gene sets showing significant reduction in NASH and time-dependent changes in response to diabetes treatments. These findings not only expand our understanding of the mechanisms underlying liver and kidney endothelial cell fenestration formation but also provide novel molecular markers and potential therapeutic targets for early diagnosis and treatment evaluation of metabolic diseases. As a fundamental research tool, COSI technology fills critical gaps in existing spatial omics and cellular biology research, particularly for studying cellular structures lacking specific markers, and demonstrates significant potential for clinical applications in chronic metabolic diseases.

We focused on two microenvironments within a 5-min jugular vein puncture wound thrombus. The goal was to infer from 3D platelet morphodynamics how microenvironments determine platelet activation state. Platelets at the collagen-rich adventitial interface were rod shaped and oriented vertical to flow vectors. The net effect was to maximize their interaction with collagen. At the wound hole interface, soluble signaling should predominant. Here, the typical platelet exhibited what appeared to be a “migratory”, granule-free, leading edge extending toward the wound hole from an organelle rich cell body. Morphologically, this structure resembled the leading edge of a wound associated fibroblast. Platelets were aligned parallel with one another and at ~45 degrees to blood flow. We submit the morphodynamics observed here indicate novel similarities between platelets and wound associated nucleated cells.

The complex and highly intertwined morphology of activated platelets within thrombi poses significant challenges for segmentation. In this work, we present a robust dual-network pipeline for cell and organelle segmentation. This multi-network approach enables the detection of fine details near the membrane while simultaneously facilitating long-range smoothing in regions distal to the membrane, drastically improving the performance of the watershed clustering algorithm compared to single-network approaches. We further enhance segmentation performance by collecting neural network predictions along multiple axes, capturing 3D correlations using only 2D neural networks. We segment and analyze hundreds of platelets and report quantitative morphological measurements, showing volumes consistent with hand-segmented results. We apply our segmentation pipeline to the CREMI neuron segmentation challenge data and provide state-of-the-art results.

Volume electron microscopy (vEM) enables biologists to visualize nanoscale 3D ultrastructure of entire eukaryotic cells and tissues processed by heavy atom staining and plastic embedding. The vEM technique with the highest resolution is focused ion-beam scanning electron microscopy (FIB-SEM), which provides nearly isotropic (∼5-10 nm) spatial resolution at fluences up to 10,000 e ^- /nm ² . However, it is still not understood how such resolution is achievable, because serial block-face (SBF) SEM, which incorporates an in-situ ultramicrotome instead of a Ga ⁺ FIB beam, results in radiation-induced collapse of similar specimen blocks at fluences of only ∼20 e ^- /nm ² . Here, we show that FIB-SEM implants a thin concentrated layer of Ga ⁺ ions, which greatly reduces electron beam-damage, reduces the depth from which backscattered electrons are detected, and prevents specimen charging and collapse. Furthermore, we show that the z-resolution (perpendicular to block-face) in FIB-SEM is substantially higher than predicted by Monte Carlo modeling of the backscattered signal when Ga implantation is not included.

Volume electron microscopy has become an important set of techniques for determining the nanoscale 3D ultrastructure of cells and biological tissues prepared by heavy atom staining and embedding in epon or other plastic materials. In the focused-ion-beam scanning electron microscope (FIB-SEM), thin layers of material are successively removed from the surface of the specimen block by Ga ion abrasion and the surface layer is imaged with the backscattered electron signal [ 1-3]. Experience has shown that 5-10 nm spatial resolution is achievable using FIB-SEM, and the resolution is approximately isotropic parallel and perpendicular to the block-face. Images are typically acquired with primary electron beam energies of ∼1.5 keV, and a fluence of ∼600 electrons/nm², producing images of higher quality than can be achieved with the alternative 3D volume EM method of serial block face (SBF)-SEM. Figure 1 illustrates the 3D ultrastructure seen with FIB-SEM from a specimen of isolated blood platelets prepared using the protocol developed by Deerinck et al. [ 4]. Slices through the 3D volume, parallel to the block-face (x-y) and perpendicular to the block-face (x-z), reveal similar resolution in the two orthogonal planes (estimated as 5-10 nm), from which the subcellular ultrastructure of blood platelets can be visualized and segmented, including alpha granules, mitochondria, and canalicular system [ 5].

David Joy has made many important contributions to the fields of scanning electron microscopy (SEM) and scanning transmission electron microscopy (STEM), and his research has had an enormous reach even outside his immediate areas of interest, including at the National Institutes of Health (NIH). In around 1979, David had been considering a position at the NIH to establish an Hitachi 200-keV H700H analytical electron microscope (AEM), equipped with an electron energy loss spectrometer (probably the first such commercial EELS system in the world), which David and his colleagues had designed at Bell Labs [ 1]. NIH’s sudden interest in EELS had been largely due to a study on subcellular detection of fluorine-labeled biological compounds, published in Science in 1978 and co-authored by David [ 2]. In the end, David decided to remain in New Jersey, and instead I found myself at NIH, where I joined Chuck Fiori and a few others who were interested in applying AEM to biological systems. Our group included talented computer scientists led by Keith Gorlen, who developed one of the first digitally controlled EELS systems for nano-analysis [ 3] using David’s spectrometer, which at that time relied on serial detection of the energy loss spectrum using a photomultiplier tube. Despite the relatively low efficiency of serial EELS, by using David’s spectrometer, it was nevertheless possible to demonstrate the feasibility of detecting core-edges of biological elements, as illustrated in Fig. 1 [ 3]. Later on, we were able to obtain a Gatan parallel-detection EELS system [ 4] and in around 1990, a dedicated VG Microscopes HB501 field-emission STEM, which greatly improved sensitivity down to just a few atoms of biological elements like calcium and iron [ 5].

Primary hemostasis results in a platelet-rich thrombus that has long been assumed to form a solid plug. Unexpectedly, our 3-dimensional (3D) electron microscopy of mouse jugular vein puncture wounds revealed that the resulting thrombi were structured about localized, nucleated platelet aggregates, pedestals and columns, that produced a vaulted thrombus capped by extravascular platelet adherence. Pedestal and column surfaces were lined by procoagulant platelets. Furthermore, early steps in thrombus assembly were sensitive to P2Y₁₂ inhibition and late steps to thrombin inhibition. Based on these results, we propose a Cap and Build, puncture wound paradigm that should have translational implications for bleeding control and hemostasis.