Serial section electron tomography of a Leishmania haptomonad-like cell attached to plastic
Ontology highlight
ABSTRACT:
SUBMITTER: Jack Daniel Sunter
PROVIDER: EMPIAR-11468 | biostudies-other |
REPOSITORIES: biostudies-other
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Project description: Not available
| EMPIAR-11467 | biostudies-other
Project description:Varicella-zoster virus (VZV) is a human alphaherpesvirus that causes varicella (chickenpox) and herpes zoster (shingles). Like all herpesviruses, the VZV DNA genome is replicated in the nucleus and packaged into nucleocapsids that must egress across the nuclear membrane for incorporation into virus particles in the cytoplasm. Our recent work showed that VZV nucleocapsids are sequestered in nuclear cages formed from promyelocytic leukemia protein (PML) in vitro and in human dorsal root ganglia and skin xenografts in vivo. We sought a method to determine the three-dimensional (3D) distribution of nucleocapsids in the nuclei of herpesvirus-infected cells as well as the 3D shape, volume and ultrastructure of these unique PML subnuclear domains. Here we report the development of a novel 3D imaging and reconstruction strategy that we term Serial Section Array-Scanning Electron Microscopy (SSA-SEM) and its application to the analysis of VZV-infected cells and these nuclear PML cages. We show that SSA-SEM permits large volume imaging and 3D reconstruction at a resolution sufficient to localize, count and distinguish different types of VZV nucleocapsids and to visualize complete PML cages. This method allowed a quantitative determination of how many nucleocapsids can be sequestered within individual PML cages (sequestration capacity), what proportion of nucleocapsids are entrapped in single nuclei (sequestration efficiency) and revealed the ultrastructural detail of the PML cages. More than 98% of all nucleocapsids in reconstructed nuclear volumes were contained in PML cages and single PML cages sequestered up to 2,780 nucleocapsids, which were shown by electron tomography to be embedded and cross-linked by an filamentous electron-dense meshwork within these unique subnuclear domains. This SSA-SEM analysis extends our recent characterization of PML cages and provides a proof of concept for this new strategy to investigate events during virion assembly at the single cell level.
| S-EPMC3369938 | biostudies-literature
Project description:BackgroundAs an extension of electron tomography (ET), serial section electron tomography (serial section ET) aims to align the tomographic images of multiple thick tissue sections together, to break through the volume limitation of the single section and preserve the sub-nanoscale voxel size. It could be applied to reconstruct the intact synapse, which expands about one micrometer and contains nanoscale vesicles. However, there are several drawbacks of the existing serial section ET methods. First, locating and imaging regions of interest (ROIs) in serial sections during the shooting process is time-consuming. Second, the alignment of ET volumes is difficult due to the missing information caused by section cutting and imaging. Here we report a workflow to simplify the acquisition of ROIs in serial sections, automatically align the volume of serial section ET, and semi-automatically reconstruct the target synaptic structure.ResultsWe propose an intelligent workflow to reconstruct the intact synapse with sub-nanometer voxel size. Our workflow includes rapid localization of ROIs in serial sections, automatic alignment, restoration, assembly of serial ET volumes, and semi-automatic target structure segmentation. For the localization and acquisition of ROIs in serial sections, we use affine transformations to calculate their approximate position based on their relative location in orderly placed sections. For the alignment of consecutive ET volumes with significantly distinct appearances, we use multi-scale image feature matching and the elastic with belief propagation (BP-Elastic) algorithm to align them from coarse to fine. For the restoration of the missing information in ET, we first estimate the number of lost images based on the pixel changes of adjacent volumes after alignment. Then, we present a missing information generation network that is appropriate for small-sample of ET volume using pre-training interpolation network and distillation learning. And we use it to generate the missing information to achieve the whole volume reconstruction. For the reconstruction of synaptic ultrastructures, we use a 3D neural network to obtain them quickly. In summary, our workflow can quickly locate and acquire ROIs in serial sections, automatically align, restore, assemble serial sections, and obtain the complete segmentation result of the target structure with minimal manual manipulation. Multiple intact synapses in wild-type rat were reconstructed at a voxel size of 0.664 nm/voxel to demonstrate the effectiveness of our workflow.ConclusionsOur workflow contributes to obtaining intact synaptic structures at the sub-nanometer scale through serial section ET, which contains rapid ROI locating, automatic alignment, volume reconstruction, and semi-automatic synapse reconstruction. We have open-sourced the relevant code in our workflow, so it is easy to apply it to other labs and obtain complete 3D ultrastructures which size is similar to intact synapses with sub-nanometer voxel size.
| S-EPMC10519085 | biostudies-literature
Project description: Not available
| EMPIAR-11464 | biostudies-other
Project description: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.
| S-EPMC4959841 | biostudies-literature
Project description:The reconstruction of neural circuits from serial section electron microscopy (ssEM) images is being accelerated by automatic image segmentation methods. Segmentation accuracy is often limited by the preceding step of aligning 2D section images to create a 3D image stack. Precise and robust alignment in the presence of image artifacts is challenging, especially as datasets are attaining the petascale. We present a computational pipeline for aligning ssEM images with several key elements. Self-supervised convolutional nets are trained via metric learning to encode and align image pairs, and they are used to initialize iterative fine-tuning of alignment. A procedure called vector voting increases robustness to image artifacts or missing image data. For speedup the series is divided into blocks that are distributed to computational workers for alignment. The blocks are aligned to each other by composing transformations with decay, which achieves a global alignment without resorting to a time-consuming global optimization. We apply our pipeline to a whole fly brain dataset, and show improved accuracy relative to prior state of the art. We also demonstrate that our pipeline scales to a cubic millimeter of mouse visual cortex. Our pipeline is publicly available through two open source Python packages.
| S-EPMC10767115 | biostudies-literature
Project description:Registration is essential for the volume reconstruction of biological tissues using serial section electron microscope (ssEM) images. However, due to environmental disturbance in section preparation, damage in long serial sections is inevitable. It is difficult to register the damaged sections with the common serial section registration method, creating significant challenges in subsequent neuron tracking and reconstruction. This paper proposes a general registration method that can be used to register damaged sections. This method first extracts the key points and descriptors of the sections to be registered and matches them via a mutual nearest neighbor matcher. K-means and Random Sample Consensus (RANSAC) are used to cluster the key points and approximate the local affine matrices of those clusters. Then, K-nearest neighbor (KNN) is used to estimate the probability density of each cluster and calculate the expected affine matrix for each coordinate point. In clustering and probability density calculations, instead of the Euclidean distance, the path distance is used to measure the correlation between sampling points. The experimental results on real test images show that this method solves the problem of registering damaged sections and contributes to the 3D reconstruction of electronic microscopic images of biological tissues. The code of this paper is available at https://github.com/TongXin-CASIA/Excepted_Affine.
| S-EPMC9478550 | biostudies-literature
Project description:Dendrites, axons, and synapses are dynamic during circuit development; however, changes in microcircuit connections as branches stabilize have not been directly demonstrated. By combining in vivo time-lapse imaging of Xenopus tectal neurons with electron microscope reconstructions of imaged neurons, we report the distribution and ultrastructure of synapses on individual vertebrate neurons and relate these synaptic properties to dynamics in dendritic and axonal arbor structure over hours or days of imaging. Dynamic dendrites have a high density of immature synapses, whereas stable dendrites have sparser, mature synapses. Axons initiate contacts from multisynapse boutons on stable branches. Connections are refined by decreasing convergence from multiple inputs to postsynaptic dendrites and by decreasing divergence from multisynapse boutons to postsynaptic sites. Visual deprivation or NMDAR antagonists decreased synapse maturation and elimination, suggesting that coactive input activity promotes microcircuit development by concurrently regulating synapse elimination and maturation of remaining contacts.
| S-EPMC3052740 | biostudies-literature
Project description:Automated tape-collecting ultramicrotomy in conjunction with scanning electron microscopy (SEM) is a powerful approach for volume electron microscopy and three-dimensional neuronal circuit analysis. Current tapes are limited by section wrinkle formation, surface scratches and sample charging during imaging. Here we show that a plasma-hydrophilized carbon nanotube (CNT)-coated polyethylene terephthalate (PET) tape effectively resolves these issues and produces SEM images of comparable quality to those from transmission electron microscopy. CNT tape can withstand multiple rounds of imaging, offer low surface resistance across the entire tape length and generate no wrinkles during the collection of ultrathin sections. When combined with an enhanced en bloc staining protocol, CNT tape-processed brain sections reveal detailed synaptic ultrastructure. In addition, CNT tape is compatible with post-embedding immunostaining for light and electron microscopy. We conclude that CNT tape can enable high-resolution volume electron microscopy for brain ultrastructure analysis.
| S-EPMC5789869 | biostudies-other
Project description:In order to understand the degradation potential of plastics in the marine environment, microorganisms that preferentially colonize and interact with plastic surfaces, as opposed to generalists potentially colonising everything, need to be identified. Accordingly, it was hypothesized that i.) plastic "specific" microorganisms are closely attached to the polymeric surface and ii.) that specificity of plastics biofilms are rather related to members of the rare biosphere. To answer these hypotheses, a three phased experiment to stepwise uncover closely attached microbes was conducted. In Phase 1, nine chemically distinct plastic films and glass were incubated in situ for 21 months in a seawater flow through system. In Phase 2, a high-pressure water jet treatment technique was used to remove the upper biofilm layers to further, in Phase 3, enrich a plastic "specific" community. To proof whether microbes colonizing different plastics are distinct from each other and from other inert hard substrates, the bacterial communities of these different substrates were analysed using 16S rRNA gene tag sequencing. Our findings indicate that tightly attached microorganisms account to the rare biosphere and suggest the presence of plastic "specific" microorganisms/assemblages which could benefit from the given plastic properties or at least grow under limited carbon resources.
| S-EPMC6478340 | biostudies-literature