Biology subjects

Leapman, R. D.

Publications and source records attributed to Leapman, R. D..

9 recordsLinked to original sources

bioRxiv2025

Study on Liver Sinusoidal Endothelial Cell Fenestrations Based on Cellular Omics-Structure Integration Technology and Its Application in Metabolic Diseases

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.

systems biology↗

bioRxiv2025

Evolution of a fuzzy ribonucleoprotein complex in viral assembly

Previously we showed that the genetic diversity of SARS-CoV-2 nucleocapsid (N) protein explores a wide range of biophysical properties facilitated by non-local impact of point mutations to its intrinsically disordered regions (Nguyen et al., 2024). This includes modulation of self-association, such as the creation of a de novo binding interface through the P13L mutation characteristic of Omicron variants. In the present work we focus on the key function of N condensing viral RNA into ribonucleoprotein particles (RNPs) for viral assembly. Lacking high-resolution structural information, biochemical and biophysical approaches have revealed architectural principles of RNPs, which involve cooperative interactions of several protein-protein and protein-RNA interfaces, initiated through oligomerization of conserved transient helices in the central disordered linker of N. Here we study the impact of defining N-protein mutations in variants of concern on RNP formation, using biophysical tools, a virus-like particle assay, and reverse genetics experiments. We find convergent evolution in repeated, independent introduction of amino acid substitutions strengthening existing binding interfaces, compensating for other substitutions that promote viral replication but decrease RNP stability. Furthermore, we show that the P13L mutation of Omicron variants enhances RNP assembly and increases viral fitness. Overall, our data reveal RNP complexes to be highly variable not only in sequence and conformations, but also in thermodynamic and kinetic stability, with its pleomorphism affecting basic architectural principles. We hypothesize that the formation of polydisperse, fuzzy N-RNA clusters with multiple distributed weak binding interfaces optimizes reversible RNA condensation, while supporting host adaptation and allowing for a large sequence space to be explored.

biophysics↗

bioRxiv2024

Densely Populated Cell and Organelles Segmentation With Multi-Plane Deep Learning Pipeline

The complex and highly intertwined morphology of activated platelets within blood clot thrombi poses significant challenges for segmentation. Here we develop a robust machine vision pipeline for cell and organelle segmentation within volume electron microscope (vEM) datasets and validate that against both model CREMI neuron segmentation challenge data and focused isotropic FIB-SEM imaged platelets and their organelles within a series of ferric chloride indued murine occlusive clots Neural network predictions were collected along multiple planes, capturing 3D correlations using only 2D neural networks. Using a workstation class computer, we segmented and analyzed hundreds of platelets and report quantitative morphological measurements of platelets and their thousands of included organelles. CREMI neuron segmentation challenge analysis produced state-of-the-art outcomes as did platelet data in comparison to manual segmentation. Our work paves the way for large-scale, single cell, 3D studies across multiple examples and lends initial single cell level insights into occlusive thrombus structure and platelet heterogeneity therein. We include a lightweight Jupyter notebook for initializing and running the neural network (Data and Materials Availability). We also provide Amira Avizo protocols for converting neural network outputs to cell and organelle instances and subsequent morphological measurements.

bioengineering↗

bioRxiv2024

Biological volume EM with focused Ga ion beam depends on formation of radiation-resistant Ga-rich layer at block face

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-/nm2. 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-/nm2. 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.

biophysics↗

bioRxiv2024

Single-Platelet Mapping of Jugular, Puncture-Wound Thrombi Reveals the Spatial Evolution of Platelet Activation

BackgroundThe contributions of platelet activation to thrombus formation during hemostatic bleeding cessation likely involve multiple activation states. However, the spatial and temporal distribution of platelets in these states has not been defined in a clot. ObjectivesTo use single-platelet mapping of activation states within jugular vein puncture thrombi to determine how the spatial distribution of platelet state evolves during hemostasis. MethodsMontaged, wide-area electron micrographs (EM) were taken at various time points, post-puncture, and annotated for platelet activation state. These classifications were mapped onto the images to identify regions of platelet activation and calculate neighbor associations. The importance of -granule secretion was tested using VAMP8-/- mice. Resultsmapping of platelet activation states at 1 min post-puncture showed extensive spatial intermixing of most platelet activation classes. No high-activation-state, platelet-rich core was observed in 5-min post-puncture thrombi, rather such platelets tended to be localized on the interior surfaces of thrombus vaults open to the circulation. Only at a later stage, 20 min post-puncture, was distinct clustering of high activation, degranulated, cytosol-rich platelets observed. These clusters localized to the central portion of the intravascular platelet-rich crown, and they were now inaccessible to the circulation. Counterintuitively, deletion of the primary platelet v-SNARE, VAMP8, increased the frequency and spatial clustering of highly activated, degranulated platelets in association with intra-thrombus vault surfaces at 5 min post puncture. ConclusionsWe conclude recent multi-activation state models can provide a realistic thrombus formation framework if linked together to encompass the dynamics of puncture wound formation.

systems biology↗

bioRxiv2020

Dense cellular segmentation using 2D-3D neural network ensembles for electron microscopy

Cell biologists can now build 3D models from segmentations of electron microscopy (EM) images, but accurate manual segmentation of densely-packed organelles across gigavoxel image volumes is infeasible. Here, we introduce 2D-3D neural network ensembles that produce dense cellular segmentations at scale, with accuracy levels that outperform baseline methods and approach those of human annotators.

microbiology↗

bioRxiv2019

Quantitative method for estimating stain density in electron microscopy of conventionally prepared biological specimens

Stain density is an important parameter for optimizing the quality of ultrastructural data obtained from several types of 3D electron microscopy techniques, including serial block-face electron microscopy (SBEM), and focused ion beam scanning electron microscopy (FIB-SEM). Here, we show how some straightforward measurements in the TEM can be used to determine the stain density based on a simple expression that we derive. Numbers of stain atoms per unit volume are determined from the measured ratio of the bright-field intensities from regions of the specimen that contain both pure embedding material and the embedded biological structures of interest. The determination only requires knowledge of the section thickness, which can either be estimated from the microtome setting, or from low-dose electron tomography, and the elastic scattering cross section for the heavy atoms used to stain the specimen. The method is tested on specimens of embedded blood platelets, brain tissue, and liver tissue.

biophysics↗

bioRxiv2019

Use of dual electron probes reveals role of ferritin in erythropoiesis

Much is known about the finely regulated process of mammalian erythropoiesis that occurs in the bone marrow, whereby erythropoietic stem cells undergo terminal differentiation accompanied by enormous morphological changes to generate highly functional specialized red blood cells. However, a crucial step in erythropoiesis, the labile iron pool and its transport to mitochondria for heme production, is not well understood1. We apply a dual 3D imaging and spectroscopic technique, based on scanned electron probes, to measure distributions of ferritin iron-storage protein in ex vivo human erythropoietic stem cells, and to determine how those distributions change during terminal differentiation. After seven days of differentiation, the cells display a highly specialized architecture of organelles with anchored clustering of mitochondria and massive accumulation of Fe3+ in loaded ferritin cores localized to lysosomal storage depots, providing an iron source for heme production. Macrophages are not present in our ex vivo cultures, so they cannot be the source of the ferritin2. We suggest that lysosomal iron depots are required by developing reticulocytes while terminally differentiating and continuing to produce heme and globin, which assemble and concentrate to fill the cytoplasm after much of the cellular machinery is expelled.

cell biology↗

bioRxiv2019

Determination of secretory granule maturation times in pancreatic islet beta-cells by serial block face scanning electron microscopy

It is shown how serial block-face electron microscopy (SBEM) of insulin-secreting beta cells in wild-type mouse pancreatic islets of Langerhans can be used to determine maturation times of secretory granules. Although SBEM captures the beta cell structure at a snapshot in time, the observed ultrastructure can be considered representative of a dynamic equilibrium state of the cells since the pancreatic islets are maintained in culture in approximate homeostasis. It is found that 7.2{+/-}1.2% ({+/-}st. dev.) of the beta cell volume is composed of secretory granule dense-cores exhibiting angular shapes surrounded by wide (typically {gtrsim}100 nm) electron-lucent halos. These organelles are identified as mature granules that store insulin for regulated release through the plasma membrane, with a release time of 96{+/-}12 hours, as previously obtained from pulsed 35S-radiolabeling of cysteine and methionine. Analysis of beta cell 3D volumes reveals a subpopulation of secretory organelles without electron-lucent halos, identified as immature secretory granules. Another subpopulation of secretory granules is found with thin (typically [lsim]30 nm) electron-lucent halos, which are attributed to immature granules that are transforming from proinsulin to insulin by action of prohormone convertases. From the volume ratio of proinsulin in the immature granules to insulin in the mature granules, we estimate that the newly formed immature granules remain in morphologically-defined immature states for an average time of 135{+/-}14 minutes, and the immature transforming granules for an average time of 130{+/-}17 minutes.

biophysics↗