Search

Huntington's disease (HD) is an inherited neurodegenerative disorder caused by an expanded CAG repeat in the coding sequence of huntingtin protein. Initially, it predominantly affects medium-sized spiny neurons (MSSNs) of the corpus striatum. No effective treatment is still available, thus urging the identification of potential therapeutic targets. While evidence of mitochondrial structural alterations in HD exists, previous studies mainly employed 2D approaches and were performed outside the strictly native brain context. In this study, we adopted a novel multiscale approach to conduct a comprehensive 3D in situ structural analysis of mitochondrial disturbances in a mouse model of HD. We investigated MSSNs within brain tissue under optimal structural conditions utilizing state-of-the-art 3D imaging technologies, specifically FIB/SEM for the complete imaging of neuronal somas and Electron Tomography for detailed morphological examination, and image processing-based quantitative analysis. Our findings suggest a disruption of the mitochondrial network towards fragmentation in HD. The network of interlaced, slim and long mitochondria observed in healthy conditions transforms into isolated, swollen and short entities, with internal cristae disorganization, cavities and abnormally large matrix granules., (© 2024. The Author(s).)

TomoAlign is a software package that integrates tools to mitigate two important resolution limiting factors in cryoET, namely the beam-induced sample motion and the contrast transfer function (CTF) of the microscope. The package is especially focused on cryoET of thick specimens where fiducial markers are required for accurate tilt-series alignment and sample motion estimation. TomoAlign models the beam-induced sample motion undergone during the tilt-series acquisition. The motion models are used to produce motion-corrected subtilt-series centered on the particles of interest. In addition, the defocus of each particle at each tilt image is determined and can be corrected, resulting in motion-corrected and CTF-corrected subtilt-series from which the subtomograms can be computed. Alternatively, the CTF information can be passed on so that CTF correction can be carried out entirely within external packages like Relion. TomoAlign serves as a versatile tool that can streamline the cryoET workflow from initial alignment of tilt-series to final subtomogram averaging during in situ structure determination., (Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.)

Recently, it has been shown that the resolution in cryo-tomography could be improved by considering the sample motion in tilt-series alignment and reconstruction, where a set of quadratic polynomials were used to model this motion. One requirement of this polynomial method is the optimization of a large number of parameters, which may limit its practical applicability. In this work, we propose an alternative method for modeling the sample motion. Starting from the standard fiducial-based tilt-series alignment, the method uses the alignment residual as local estimates of the sample motion at the 3D fiducial positions. Then, a scattered data interpolation technique characterized by its smoothness and a closed-form solution is applied to model the sample motion. The motion model is then integrated in the tomographic reconstruction. The new method improves the tomogram quality similar to the polynomial one, with the important advantage that the determination of the motion model is greatly simplified, thereby overcoming one of the major limitations of the polynomial model. Therefore, the new method is expected to make the beam-induced motion correction methodology more accessible to the cryoET community., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Macroautophagy is morphologically characterized by autophagosome formation. Autophagosomes are double-membraned vesicles that sequester cytoplasmic components for further degradation in the lysosome. Basal autophagy is paramount for intracellular quality control in post-mitotic cells but, surprisingly, the number of autophagosomes in post-mitotic neurons is very low, suggesting that alternative degradative structures could exist in neurons. To explore this possibility, we have examined neuronal subcellular architecture by performing three-dimensional (3D) electron tomography analysis of mouse brain tissue that had been preserved through high-pressure freezing. Here, we report that sequestration of neuronal cytoplasmic contents occurs at the Golgi complex in distinct and dynamic structures that coexist with autophagosomes in the brain. These structures are composed of several concentric double-membraned layers that appear to be formed simultaneously by the direct bending and sealing of discrete Golgi stacks. These structures are labelled for proteolytic enzymes, and lysosomes and late endosomes are found in contact with them, leading to the possibility that the sequestered material could be degraded inside them. Our findings highlight the key role that 3D electron tomography, together with tissue rapid-freezing techniques, will have in gaining new knowledge about subcellular architecture., (© 2017. Published by The Company of Biologists Ltd.)

The development of cryo-focused ion beam (cryo-FIB) for the thinning of frozen-hydrated biological specimens enabled cryo-electron tomography (cryo-ET) analysis in unperturbed cells and tissues. However, the volume represented within a typical FIB lamella constitutes a small fraction of the biological specimen. Retaining low-abundance and dynamic subcellular structures or macromolecular assemblies within such limited volumes requires precise targeting of the FIB milling process. In this study, we present the development of a cryo-stage allowing for spinning-disk confocal light microscopy at cryogenic temperatures and describe the incorporation of the new hardware into existing workflows for cellular sample preparation by cryo-FIB. Introduction of fiducial markers and subsequent computation of three-dimensional coordinate transformations provide correlation between light microscopy and scanning electron microscopy/FIB. The correlative approach is employed to guide the FIB milling process of vitrified cellular samples and to capture specific structures, namely fluorescently labeled lipid droplets, in lamellas that are 300 nm thick. The correlation procedure is then applied to localize the fluorescently labeled structures in the transmission electron microscopy image of the lamella. This approach can be employed to navigate the acquisition of cryo-ET data within FIB-lamellas at specific locations, unambiguously identified by fluorescence microscopy., (Copyright © 2016 Biophysical Society. Published by Elsevier Inc. All rights reserved.)

Tomo3D is a program for fast tomographic reconstruction on multicore computers. Its high speed stems from code optimization, vectorization with Streaming SIMD Extensions (SSE), multithreading and optimization of disk access. Recently, Advanced Vector eXtensions (AVX) have been introduced in the x86 processor architecture. Compared to SSE, AVX double the number of simultaneous operations, thus pointing to a potential twofold gain in speed. However, in practice, achieving this potential is extremely difficult. Here, we provide a technical description and an assessment of the optimizations included in Tomo3D to take advantage of AVX instructions. Tomo3D 2.0 allows huge reconstructions to be calculated in standard computers in a matter of minutes. Thus, it will be a valuable tool for electron tomography studies with increasing resolution needs., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Three-dimensional (3D) electron microscopy (EM) has become a major player in structural cell biology as it enables the analysis of subcellular architecture at an unprecedented level of detail. Interpretation of the resulting 3D volumes strongly depends on segmentation, which consists in decomposing the volume into their structural components. The computational approaches proposed so far have not turned out to be of general applicability. Thus, manual segmentation still remains a prevalent method. Here, a new computational framework for segmentation of 3D EM datasets is introduced. It relies on detection and characterization of ridges (i.e. local maxima). The detected ridges are modelled as asymmetric Gaussian functions whose parameters constitute ridge descriptors. This local information is then used to cluster the ridges, which leads to the ultimate segmentation. In this work we focus on membranes and locally planar structures in general. The performance of the framework is illustrated with its application to a number of complex 3D datasets and a quantitative analysis., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Electron tomography (ET) has emerged as a powerful technique to address fundamental questions in molecular and cellular biology. It makes possible visualization of the molecular architecture of complex viruses, organelles and cells at a resolution of a few nanometres. In the last decade ET has allowed major breakthroughs that have provided exciting insights into a wide range of biological processes. In ET the biological sample is imaged with an electron microscope, and a series of images is taken from the sample at different views. Prior to imaging, the sample has to be specially prepared to withstand the conditions within the microscope. Subsequently, those images are processed and combined to yield the three-dimensional reconstruction or tomogram. Afterwards, a number of computational steps are necessary to facilitate the interpretation of the tomogram, such as noise reduction, segmentation and analysis of subvolumes. As the computational demands are huge in some of the stages, high performance computing (HPC) techniques are used to make the problem affordable in reasonable time. This article intends to comprehensively review the methods, technologies and tools involved in the different computational stages behind structural studies by ET, from image acquisition to interpretation of tomograms. The HPC techniques usually employed to cope with the computational demands are also briefly described., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

Background: Noise filtering techniques are needed in electron tomography to allow proper interpretation of datasets. The standard linear filtering techniques are characterized by a tradeoff between the amount of reduced noise and the blurring of the features of interest. On the other hand, sophisticated anisotropic nonlinear filtering techniques allow noise reduction with good preservation of structures. However, these techniques are computationally intensive and are difficult to be tuned to the problem at hand., Results: TOMOBFLOW is a program for noise filtering with capabilities of preservation of biologically relevant information. It is an efficient implementation of the Beltrami flow, a nonlinear filtering method that locally tunes the strength of the smoothing according to an edge indicator based on geometry properties. The fact that this method does not have free parameters hard to be tuned makes TOMOBFLOW a user-friendly filtering program equipped with the power of diffusion-based filtering methods. Furthermore, TOMOBFLOW is provided with abilities to deal with different types and formats of images in order to make it useful for electron tomography in particular and bioimaging in general., Conclusion: TOMOBFLOW allows efficient noise filtering of bioimaging datasets with preservation of the features of interest, thereby yielding data better suited for post-processing, visualization and interpretation. It is available at the web site (http://www.ual.es/%7ejjfdez/SW/tomobflow.html).