Browse
Submit Data
Databases
API
Help

Dataset Information

10 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Creating High-Resolution Multiscale Maps of Human Tissue Using Multi-beam SEM.

ABSTRACT: Multi-beam scanning electron microscopy (mSEM) enables high-throughput, nano-resolution imaging of macroscopic tissue samples, providing an unprecedented means for structure-function characterization of biological tissues and their cellular inhabitants, seamlessly across multiple length scales. Here we describe computational methods to reconstruct and navigate a multitude of high-resolution mSEM images of the human hip. We calculated cross-correlation shift vectors between overlapping images and used a mass-spring-damper model for optimal global registration. We utilized the Google Maps API to create an interactive map and provide open access to our reconstructed mSEM datasets to both the public and scientific communities via our website www.mechbio.org. The nano- to macro-scale map reveals the tissue's biological and material constituents. Living inhabitants of the hip bone (e.g. osteocytes) are visible in their local extracellular matrix milieu (comprising collagen and mineral) and embedded in bone's structural tissue architecture, i.e. the osteonal structures in which layers of mineralized tissue are organized in lamellae around a central blood vessel. Multi-beam SEM and our presented methodology enable an unprecedented, comprehensive understanding of health and disease from the molecular to organ length scale.

SUBMITTER: Pereira AF

PROVIDER: S-EPMC5117996 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

High-resolution Hi-C maps highlight multiscale 3D epigenome reprogramming during pancreatic cancer metastasis.

Project description:BackgroundPancreatic cancer's poor prognosis is caused by distal metastasis, which is associated with epigenetic changes. However, the role of the 3D epigenome in pancreatic cancer biology, especially its metastasis, remains unclear.MethodsHere, we developed high-resolution 3D epigenomic maps of cells derived from normal pancreatic epithelium, primary and metastatic pancreatic cancer by in situ Hi-C, ChIP-seq, ATAC-seq, and RNA-seq to identify key genes involved in pancreatic cancer metastasis RESULTS: We found that A/B compartments, contact domains, and chromatin loops changed significantly in metastatic pancreatic cancer cells, which are associated with epigenetic state alterations. Moreover, we found that upregulated genes, which were located in switched compartments, changed contact domains, and metastasis-specific enhancer-promoter loops, were related to cancer metastasis and poor prognosis of patients with pancreatic cancer. We also found that transcription factors in specific enhancer-promoter loop formation were also associated with metastasis. Finally we demonstrated that LIPC, looped to metastasis-specific enhancers, could promote pancreatic cancer metastasis.ConclusionsThese results highlight the multiscale 3D epigenome reprogramming during pancreatic cancer metastasis and expand our knowledge of mechanisms of gene regulation during pancreatic cancer metastasis.

| S-EPMC8336101 | biostudies-literature

High-resolution Hi-C maps highlight multiscale chromatin architecture reorganization during cold stress in Brachypodium distachyon.

Project description:BackgroundThe adaptation of plants to cold stress involves changes in gene expression profiles that are associated with epigenetic regulation. Although the three-dimensional (3D) genome architecture is considered an important epigenetic regulator, the role of 3D genome organization in the cold stress response remains unclear.ResultsIn this study, we developed high-resolution 3D genomic maps using control and cold-treated leaf tissue of the model plant Brachypodium distachyon using Hi-C to determine how cold stress affects the 3D genome architecture. We generated ~ 1.5 kb resolution chromatin interaction maps and showed that cold stress disrupts different levels of chromosome organization, including A/B compartment transition, a reduction in chromatin compartmentalization and the size of topologically associating domains (TADs), and loss of long-range chromatin loops. Integrating RNA-seq information, we identified cold-response genes and revealed that transcription was largely unaffected by the A/B compartment transition. The cold-response genes were predominantly localized in compartment A. In contrast, transcriptional changes are required for TAD reorganization. We demonstrated that dynamic TAD events were associated with H3K27me3 and H3K27ac state alterations. Moreover, a loss of chromatin looping, rather than a gain of looping, coincides with alterations in gene expression, indicating that chromatin loop disruption may play a more important role than loop formation in the cold-stress response.ConclusionsOur study highlights the multiscale 3D genome reprogramming that occurs during cold stress and expands our knowledge of the mechanisms underlying transcriptional regulation in response to cold stress in plants.

| S-EPMC10186695 | biostudies-literature

Creating high-resolution 3D cranial implant geometry using deep learning techniques.

Project description:Creating a personalized implant for cranioplasty can be costly and aesthetically challenging, particularly for comminuted fractures that affect a wide area. Despite significant advances in deep learning techniques for 2D image completion, generating a 3D shape inpainting remains challenging due to the higher dimensionality and computational demands for 3D skull models. Here, we present a practical deep-learning approach to generate implant geometry from defective 3D skull models created from CT scans. Our proposed 3D reconstruction system comprises two neural networks that produce high-quality implant models suitable for clinical use while reducing training time. The first network repairs low-resolution defective models, while the second network enhances the volumetric resolution of the repaired model. We have tested our method in simulations and real-life surgical practices, producing implants that fit naturally and precisely match defect boundaries, particularly for skull defects above the Frankfort horizontal plane.

| S-EPMC10750412 | biostudies-literature

Multi-beam X-ray ptychography using coded probes for rapid non-destructive high resolution imaging of extended samples.

Project description:Imaging large areas of a sample non-destructively and with high resolution is of great interest for both science and industry. For scanning coherent X-ray diffraction microscopy, i. e., ptychography, the achievable scan area at a given spatial resolution is limited by the coherent photon flux of modern X-ray sources. Multibeam X-ray ptychography can improve the scanning speed by scanning the sample with several parallel mutually incoherent beams, e. g., generated by illuminating multiple focusing optics in parallel by a partially coherent beam. The main difficulty with this scheme is the robust separation of the superimposed signals from the different beams, especially when the beams and the illuminated sample areas are quite similar. We overcome this difficulty by encoding each of the probing beams with its own X-ray phase plate. This helps the algorithm to robustly reconstruct the multibeam data. We compare the coded multibeam scans to uncoded multibeam and single beam scans, demonstrating the enhanced performance on a microchip sample with regular and repeating structures.

| S-EPMC9008058 | biostudies-literature

High resolution single particle cryo-electron microscopy using beam-image shift.

Project description:Automated data acquisition is used widely for single-particle reconstruction of three-dimensional (3D) volumes of biological complexes preserved in vitreous ice and imaged in a transmission electron microscope. Automation has become integral to this method because of the very large number of particle images required in order to overcome the typically low signal-to-noise ratio of these images. For optimal efficiency, automated data acquisition software packages typically employ some beam-image shift targeting as this method is both fast and accurate (±0.1?µm). In contrast, using only stage movement, relocation to a targeted area under low-dose conditions can only be achieved in combination with multiple iterations or long relaxation times, both reducing efficiency. Nevertheless it is well known that applying beam-image shift induces beam-tilt and with it a potential structure phase error with a phase error ?/4 the highest acceptable value. This theory has been used as an argument against beam-image shift for high resolution data collection. Nevertheless, in practice many small beam-image shift datasets have resulted in 3D reconstructions beyond the ?/4 phase error limit. To address this apparent contradiction, we performed cryo-EM single-particle reconstructions on a T20S proteasome sample using applied beam-image shifts corresponding to beam tilts from 0 to 10 mrad. To evaluate the results we compared the FSC values, and examined the water density peaks in the 3D map. We conclude that the phase error does not limit the validity of the 3D reconstruction from single-particle averaging beyond the ?/4 resolution limit.

| S-EPMC6163078 | biostudies-literature

High-resolution cryo-EM using beam-image shift at 200 keV.

Project description:Recent advances in single-particle cryo-electron microscopy (cryo-EM) data collection utilize beam-image shift to improve throughput. Despite implementation on 300 keV cryo-EM instruments, it remains unknown how well beam-image-shift data collection affects data quality on 200 keV instruments and the extent to which aberrations can be computationally corrected. To test this, a cryo-EM data set for aldolase was collected at 200 keV using beam-image shift and analyzed. This analysis shows that the instrument beam tilt and particle motion initially limited the resolution to 4.9 Å. After particle polishing and iterative rounds of aberration correction in RELION, a 2.8 Å resolution structure could be obtained. This analysis demonstrates that software correction of microscope aberrations can provide a significant improvement in resolution at 200 keV.

| S-EPMC7642776 | biostudies-literature

Cerebral gray matter volume losses in essential tremor: A case-control study using high resolution tissue probability maps.

Project description:INTRODUCTION:Essential tremor (ET) is increasingly recognized as a multi-dimensional disorder with both motor and non-motor features. For this reason, imaging studies are more broadly examining regions outside the cerebellar motor loop. Reliable detection of cerebral gray matter (GM) atrophy requires optimized processing, adapted to high-resolution magnetic resonance imaging (MRI). We investigated cerebral GM volume loss in ET cases using automated segmentation of MRI T1-weighted images. METHODS:MRI was acquired on 47 ET cases and 36 controls. Automated segmentation and voxel-wise comparisons of volume were performed using Statistical Parametric Mapping (SPM) software. To improve upon standard protocols, the high-resolution International Consortium for Brain Mapping (ICBM) 2009a atlas and tissue probability maps were used to process each subject image. Group comparisons were performed: all ET vs. Controls, ET with head tremor (ETH) vs. Controls, and severe ET vs. Controls. An analysis of variance (ANOVA) was performed between ET with and without head tremor and controls. Age, sex, and Montreal Cognitive Assessment (MoCA) score were regressed out from each comparison. RESULTS:We were able to consistently identify regions of cerebral GM volume loss in ET and in ET subgroups in the posterior insula, superior temporal gyri, cingulate cortex, inferior frontal gyri and other occipital and parietal regions. There were no significant increases in GM volume in ET in any comparisons with controls. CONCLUSION:This study, which uses improved methodologies, provides evidence that GM volume loss in ET is present beyond the cerebellum, and in fact, is widespread throughout the cerebrum as well.

| S-EPMC6005739 | biostudies-other

Creating and validating cis-regulatory maps of tissue-specific gene expression regulation.

Project description:Predicting which genomic regions control the transcription of a given gene is a challenge. We present a novel computational approach for creating and validating maps that associate genomic regions (cis-regulatory modules-CRMs) with genes. The method infers regulatory relationships that explain gene expression observed in a test tissue using widely available genomic data for 'other' tissues. To predict the regulatory targets of a CRM, we use cross-tissue correlation between histone modifications present at the CRM and expression at genes within 1 Mbp of it. To validate cis-regulatory maps, we show that they yield more accurate models of gene expression than carefully constructed control maps. These gene expression models predict observed gene expression from transcription factor binding in the CRMs linked to that gene. We show that our maps are able to identify long-range regulatory interactions and improve substantially over maps linking genes and CRMs based on either the control maps or a 'nearest neighbor' heuristic. Our results also show that it is essential to include CRMs predicted in multiple tissues during map-building, that H3K27ac is the most informative histone modification, and that CAGE is the most informative measure of gene expression for creating cis-regulatory maps.

| S-EPMC4176179 | biostudies-literature

Creating High-Resolution Microscopic Cross-Section Images of Hardwood Species Using Generative Adversarial Networks

Project description:Microscopic wood identification plays a critical role in many economically important areas in wood science. Historically, producing and curating relevant and representative microscopic cross-section images of wood species is limited to highly experienced and trained anatomists. This manuscript demonstrates the feasibility of generating synthetic microscopic cross-sections of hardwood species. We leveraged a publicly available dataset of 119 hardwood species to train a style-based generative adversarial network (GAN). The proposed GAN generated anatomically accurate cross-section images with remarkable fidelity to actual data. Quantitative metrics corroborated the capacity of the generative model in capturing complex wood structure by resulting in a Fréchet inception distance score of 17.38. Image diversity was calculated using the Structural Similarity Index Measure (SSIM). The SSIM results confirmed that the GAN approach can successfully synthesize diverse images. To confirm the usefulness and realism of the GAN generated images, eight professional wood anatomists in two experience levels participated in a visual Turing test and correctly identified fake and actual images at rates of 48.3 and 43.7%, respectively, with no statistical difference when compared to random guess. The generative model can synthesize realistic, diverse, and meaningful high-resolution microscope cross-section images that are virtually indistinguishable from real images. Furthermore, the framework presented may be suitable for improving current deep learning models, helping understand potential breeding between species, and may be used as an educational tool.

| S-EPMC8548738 | biostudies-literature

High-Spatial-Resolution Multi-Omics Sequencing via Deterministic Barcoding in Tissue.

Project description:We present deterministic barcoding in tissue for spatial omics sequencing (DBiT-seq) for co-mapping of mRNAs and proteins in a formaldehyde-fixed tissue slide via next-generation sequencing (NGS). Parallel microfluidic channels were used to deliver DNA barcodes to the surface of a tissue slide, and crossflow of two sets of barcodes, A1-50 and B1-50, followed by ligation in situ, yielded a 2D mosaic of tissue pixels, each containing a unique full barcode AB. Application to mouse embryos revealed major tissue types in early organogenesis as well as fine features like microvasculature in a brain and pigmented epithelium in an eye field. Gene expression profiles in 10-μm pixels conformed into the clusters of single-cell transcriptomes, allowing for rapid identification of cell types and spatial distributions. DBiT-seq can be adopted by researchers with no experience in microfluidics and may find applications in a range of fields including developmental biology, cancer biology, neuroscience, and clinical pathology.

| S-EPMC7736559 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data