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Jin W, Zhou Y, Bartesaghi A. Accurate size-based protein localization from cryo-ET tomograms. J Struct Biol X 2024; 10:100104. [PMID: 39044770 PMCID: PMC11263962 DOI: 10.1016/j.yjsbx.2024.100104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/25/2024] Open
Abstract
Cryo-electron tomography (cryo-ET) combined with sub-tomogram averaging (STA) allows the determination of protein structures imaged within the native context of the cell at near-atomic resolution. Particle picking is an essential step in the cryo-ET/STA image analysis pipeline that consists in locating the position of proteins within crowded cellular tomograms so that they can be aligned and averaged in 3D to improve resolution. While extensive work in 2D particle picking has been done in the context of single-particle cryo-EM, comparatively fewer strategies have been proposed to pick particles from 3D tomograms, in part due to the challenges associated with working with noisy 3D volumes affected by the missing wedge. While strategies based on 3D template-matching and deep learning are commonly used, these methods are computationally expensive and require either an external template or manual labelling which can bias the results and limit their applicability. Here, we propose a size-based method to pick particles from tomograms that is fast, accurate, and does not require external templates or user provided labels. We compare the performance of our approach against a commonly used algorithm based on deep learning, crYOLO, and show that our method: i) has higher detection accuracy, ii) does not require user input for labeling or time-consuming training, and iii) runs efficiently on non-specialized CPU hardware. We demonstrate the effectiveness of our approach by automatically detecting particles from tomograms representing different types of samples and using these particles to determine the high-resolution structures of ribosomes imaged in vitro and in situ.
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Affiliation(s)
- Weisheng Jin
- Department of Computer Science, Duke University, Durham, USA
| | - Ye Zhou
- Department of Computer Science, Duke University, Durham, USA
| | - Alberto Bartesaghi
- Department of Computer Science, Duke University, Durham, USA
- Department of Biochemistry, Duke University School of Medicine, Durham, USA
- Department of Electrical and Computer Engineering, Pratt School of Engineering, Duke University, Durham, USA
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Raimondi A, Ilacqua N, Pellegrini L. Liver inter-organelle membrane contact sites revealed by serial section electron tomography. Methods Cell Biol 2023; 177:101-123. [PMID: 37451764 DOI: 10.1016/bs.mcb.2022.12.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/12/2023]
Abstract
Inter-organelle membrane contact sites (MCSs) are defined as areas of close proximity between the membranes of two organelles (10-80nm). They have been implicated in many physiological processes such as Ca++, lipids or small molecules transfer, organelles biogenesis or dynamic and have an important role in many cellular processes such as apoptosis, autophagy, and signaling. Since the distance and the extent of these contacts are in the nanometer range, high resolution techniques are ideal for imaging these structures. It is for this reason that transmission electron microscopy (TEM) has been considered the gold standard for MCSs visualization and the first technique that described them. However, often TEM analysis is limited to 2D lacking information on the 3D association between the organelles involved in MCSs. To fully describe the complex architecture of MSCs and to unveil their role in cellular physiology a 3D analysis is required. This chapter provides a method for the analysis of MCSs using serial section electron tomography (ssET), a technique able to reconstruct in 3D at nanometer resolution cellular and subcellular structures. By applying this procedure, it was possible to elucidate the role of the contacts between Endoplasmic Reticulum (ER) and other organelles in liver lipid metabolism.
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Affiliation(s)
- Andrea Raimondi
- Experimental Imaging Centre, IRCCS San Raffaele Scientific Institute, Milan, Italy.
| | - Nicolò Ilacqua
- Mitochondria Biology Laboratory, Brain Research Center, Quebec, QC, Canada; Department of Molecular Biology, Medical Biochemistry and Pathology, Faculty of Medicine, Laval University, Quebec, QC, Canada
| | - Luca Pellegrini
- Mitochondria Biology Laboratory, Brain Research Center, Quebec, QC, Canada; Department of Molecular Biology, Medical Biochemistry and Pathology, Faculty of Medicine, Laval University, Quebec, QC, Canada; Department of Biochemistry, Microbiology and Immunology, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada.
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3
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A cryo-fixation protocol to study the structure of the synaptonemal complex. Chromosome Res 2022; 30:385-400. [PMID: 35486207 DOI: 10.1007/s10577-022-09689-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 03/08/2022] [Accepted: 03/28/2022] [Indexed: 01/25/2023]
Abstract
Genetic variability in sexually reproducing organisms results from an exchange of genetic material between homologous chromosomes. The genetic exchange mechanism is dependent on the synaptonemal complex (SC), a protein structure localized between the homologous chromosomes. The current structural models of the mammalian SC are based on electron microscopy, superresolution, and expansion microscopy studies using chemical fixatives and sample dehydration of gonads, which are methodologies known to produce structural artifacts. To further analyze the structure of the SC, without chemical fixation, we have adapted a cryo-fixation method for electron microscopy where pachytene cells are isolated from mouse testis by FACS, followed by cryo-fixation, cryo-substitution, and electron tomography. In parallel, we performed conventional chemical fixation and electron tomography on mouse seminiferous tubules to compare the SC structure obtained with the two fixation methods. We found several differences in the structure and organization of the SC in cryo-fixed samples when compared to chemically preserved samples. We found the central region of the SC to be wider and the transverse filaments to be more densely packed in the central region of the SC.
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Moebel E, Martinez-Sanchez A, Lamm L, Righetto RD, Wietrzynski W, Albert S, Larivière D, Fourmentin E, Pfeffer S, Ortiz J, Baumeister W, Peng T, Engel BD, Kervrann C. Deep learning improves macromolecule identification in 3D cellular cryo-electron tomograms. Nat Methods 2021; 18:1386-1394. [PMID: 34675434 DOI: 10.1038/s41592-021-01275-4] [Citation(s) in RCA: 58] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Accepted: 08/18/2021] [Indexed: 11/10/2022]
Abstract
Cryogenic electron tomography (cryo-ET) visualizes the 3D spatial distribution of macromolecules at nanometer resolution inside native cells. However, automated identification of macromolecules inside cellular tomograms is challenged by noise and reconstruction artifacts, as well as the presence of many molecular species in the crowded volumes. Here, we present DeepFinder, a computational procedure that uses artificial neural networks to simultaneously localize multiple classes of macromolecules. Once trained, the inference stage of DeepFinder is faster than template matching and performs better than other competitive deep learning methods at identifying macromolecules of various sizes in both synthetic and experimental datasets. On cellular cryo-ET data, DeepFinder localized membrane-bound and cytosolic ribosomes (roughly 3.2 MDa), ribulose 1,5-bisphosphate carboxylase-oxygenase (roughly 560 kDa soluble complex) and photosystem II (roughly 550 kDa membrane complex) with an accuracy comparable to expert-supervised ground truth annotations. DeepFinder is therefore a promising algorithm for the semiautomated analysis of a wide range of molecular targets in cellular tomograms.
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Affiliation(s)
- Emmanuel Moebel
- Serpico Project-Team, Centre Inria Rennes-Bretagne Atlantique and CNRS-UMR 144, Inria, CNRS, Institut Curie, PSL Research University, Campus Universitaire de Beaulieu, Rennes Cedex, France
| | - Antonio Martinez-Sanchez
- Department of Computer Science, Faculty of Sciences, University of Oviedo, Oviedo, Spain.,Health Research Institute of Asturias (ISPA), Avenida Hospital Universitario s/n, Oviedo, Spain.,Institute of Neuropathology, Cluster of Excellence 'Multiscale Bioimaging: from Molecular Machines to Networks of Excitable Cells', University of Göttingen, Göttingen, Germany
| | - Lorenz Lamm
- Helmholtz Pioneer Campus, Helmholtz Zentrum München, Neuherberg, Germany.,Helmholtz AI, Helmholtz Zentrum München, Neuherberg, Germany
| | - Ricardo D Righetto
- Helmholtz Pioneer Campus, Helmholtz Zentrum München, Neuherberg, Germany
| | | | | | - Damien Larivière
- Fourmentin-Guilbert Scientific Foundation, Noisy-le-Grand, France
| | - Eric Fourmentin
- Fourmentin-Guilbert Scientific Foundation, Noisy-le-Grand, France
| | - Stefan Pfeffer
- Max Planck Institute of Biochemistry, Martinsried, Germany.,Zentrum für Molekulare Biologie der Universität Heidelberg, Heidelberg, Germany
| | - Julio Ortiz
- Max Planck Institute of Biochemistry, Martinsried, Germany.,Ernst Ruska-Centre, Wilhelm-Johnen-Straße, Jülich, Germany
| | | | - Tingying Peng
- Helmholtz AI, Helmholtz Zentrum München, Neuherberg, Germany
| | - Benjamin D Engel
- Helmholtz Pioneer Campus, Helmholtz Zentrum München, Neuherberg, Germany. .,Department of Chemistry, Technical University of Munich, Garching, Germany.
| | - Charles Kervrann
- Serpico Project-Team, Centre Inria Rennes-Bretagne Atlantique and CNRS-UMR 144, Inria, CNRS, Institut Curie, PSL Research University, Campus Universitaire de Beaulieu, Rennes Cedex, France.
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Wan X, Katchalski T, Churas C, Ghosh S, Phan S, Lawrence A, Hao Y, Zhou Z, Chen R, Chen Y, Zhang F, Ellisman MH. Electron tomography simulator with realistic 3D phantom for evaluation of acquisition, alignment and reconstruction methods. J Struct Biol 2017; 198:103-115. [PMID: 28392451 DOI: 10.1016/j.jsb.2017.04.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2016] [Revised: 12/22/2016] [Accepted: 04/03/2017] [Indexed: 11/16/2022]
Abstract
Because of the significance of electron microscope tomography in the investigation of biological structure at nanometer scales, ongoing improvement efforts have been continuous over recent years. This is particularly true in the case of software developments. Nevertheless, verification of improvements delivered by new algorithms and software remains difficult. Current analysis tools do not provide adaptable and consistent methods for quality assessment. This is particularly true with images of biological samples, due to image complexity, variability, low contrast and noise. We report an electron tomography (ET) simulator with accurate ray optics modeling of image formation that includes curvilinear trajectories through the sample, warping of the sample and noise. As a demonstration of the utility of our approach, we have concentrated on providing verification of the class of reconstruction methods applicable to wide field images of stained plastic-embedded samples. Accordingly, we have also constructed digital phantoms derived from serial block face scanning electron microscope images. These phantoms are also easily modified to include alignment features to test alignment algorithms. The combination of more realistic phantoms with more faithful simulations facilitates objective comparison of acquisition parameters, alignment and reconstruction algorithms and their range of applicability. With proper phantoms, this approach can also be modified to include more complex optical models, including distance-dependent blurring and phase contrast functions, such as may occur in cryotomography.
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Affiliation(s)
- Xiaohua Wan
- Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China; National Center for Microscopy and Imaging Research, University of California, San Diego, USA
| | - Tsvi Katchalski
- National Center for Microscopy and Imaging Research, University of California, San Diego, USA
| | - Christopher Churas
- National Center for Microscopy and Imaging Research, University of California, San Diego, USA
| | - Sreya Ghosh
- National Center for Microscopy and Imaging Research, University of California, San Diego, USA
| | - Sebastien Phan
- National Center for Microscopy and Imaging Research, University of California, San Diego, USA
| | - Albert Lawrence
- National Center for Microscopy and Imaging Research, University of California, San Diego, USA.
| | - Yu Hao
- Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China
| | - Ziying Zhou
- Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China; Beijing Institute of Technology, Beijing, China
| | - Ruijuan Chen
- School of Electronic and Information Engineering, Tianjin Polytechnic University, Tianjin, China; National Center for Microscopy and Imaging Research, University of California, San Diego, USA
| | - Yu Chen
- Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China
| | - Fa Zhang
- Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China
| | - Mark H Ellisman
- National Center for Microscopy and Imaging Research, University of California, San Diego, USA; Departments of Neurosciences and Bioengineering, University of California, San Diego, USA
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Phan S, Boassa D, Nguyen P, Wan X, Lanman J, Lawrence A, Ellisman MH. 3D reconstruction of biological structures: automated procedures for alignment and reconstruction of multiple tilt series in electron tomography. ACTA ACUST UNITED AC 2016; 2:8. [PMID: 27547706 PMCID: PMC4972035 DOI: 10.1186/s40679-016-0021-2] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2016] [Accepted: 06/01/2016] [Indexed: 11/10/2022]
Abstract
Transmission electron microscopy allows the collection of multiple views of specimens and their computerized three-dimensional reconstruction and analysis with electron tomography. Here we describe development of methods for automated multi-tilt data acquisition, tilt-series processing, and alignment which allow assembly of electron tomographic data from a greater number of tilt series, yielding enhanced data quality and increasing contrast associated with weakly stained structures. This scheme facilitates visualization of nanometer scale details of fine structure in volumes taken from plastic-embedded samples of biological specimens in all dimensions. As heavy metal-contrasted plastic-embedded samples are less sensitive to the overall dose rather than the electron dose rate, an optimal resampling of the reconstruction space can be achieved by accumulating lower dose electron micrographs of the same area over a wider range of specimen orientations. The computerized multiple tilt series collection scheme is implemented together with automated advanced procedures making collection, image alignment, and processing of multi-tilt tomography data a seamless process. We demonstrate high-quality reconstructions from samples of well-described biological structures. These include the giant Mimivirus and clathrin-coated vesicles, imaged in situ in their normal intracellular contexts. Examples are provided from samples of cultured cells prepared by high-pressure freezing and freeze-substitution as well as by chemical fixation before epoxy resin embedding.
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Affiliation(s)
- Sébastien Phan
- National Center For Microscopy and Imaging Research, Center for Research in Biological Systems, University of California, 9500 Gilman Drive La Jolla, San Diego, CA 92093-0608, USA
| | - Daniela Boassa
- National Center For Microscopy and Imaging Research, Center for Research in Biological Systems, University of California, 9500 Gilman Drive La Jolla, San Diego, CA 92093-0608, USA
| | - Phuong Nguyen
- National Center For Microscopy and Imaging Research, Center for Research in Biological Systems, University of California, 9500 Gilman Drive La Jolla, San Diego, CA 92093-0608, USA
| | - Xiaohua Wan
- National Center For Microscopy and Imaging Research, Center for Research in Biological Systems, University of California, 9500 Gilman Drive La Jolla, San Diego, CA 92093-0608, USA
| | - Jason Lanman
- Departments of Neurosciences and Bioengineering, University of California, 9500 Gilman Drive La Jolla, San Diego, CA 92093-0608, USA.,Department of Biological Sciences, Purdue University, 915 W. State Street, West Lafayette, IN 47907-2054 USA
| | - Albert Lawrence
- National Center For Microscopy and Imaging Research, Center for Research in Biological Systems, University of California, 9500 Gilman Drive La Jolla, San Diego, CA 92093-0608, USA
| | - Mark H Ellisman
- National Center For Microscopy and Imaging Research, Center for Research in Biological Systems, University of California, 9500 Gilman Drive La Jolla, San Diego, CA 92093-0608, USA.,Departments of Neurosciences and Bioengineering, University of California, 9500 Gilman Drive La Jolla, San Diego, CA 92093-0608, USA.,Department of Biological Sciences, Purdue University, 915 W. State Street, West Lafayette, IN 47907-2054 USA
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Single versus dual-axis cryo-electron tomography of microtubules assembled in vitro: limits and perspectives. J Struct Biol 2012. [PMID: 23178680 DOI: 10.1016/j.jsb.2012.11.004] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Single-axis cryo-electron tomography of vitrified specimens has become a method of choice to reconstruct in three dimensions macromolecular assemblies in their cellular context or prepared from purified components. Here, we asked how a dual-axis acquisition scheme would improve three-dimensional reconstructions of microtubules assembled in vitro. We show that in single-axis tomograms, microtubules oriented close to the perpendicular of the tilt axis display diminished contrast, and ultimately transform into sets of parallel lines oriented in the direction of the electron beam when observed in cross-section. Analysis of their three-dimensional Fourier transform indicates that this imaging artifact is due to a decrease in the angular sampling of their equatorial components. Although the second orthogonal series does not fully complement the first one at the specimen level due to increased radiation damage, it still allows elongated features oriented in any directions to be correctly reconstructed, which might be essential for highly heterogeneous specimens such as cells.
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Fernandez JJ. TOMOBFLOW: feature-preserving noise filtering for electron tomography. BMC Bioinformatics 2009; 10:178. [PMID: 19523199 PMCID: PMC2753846 DOI: 10.1186/1471-2105-10-178] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2009] [Accepted: 06/12/2009] [Indexed: 11/28/2022] Open
Abstract
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 .
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Affiliation(s)
- Jose-Jesus Fernandez
- Dept Computer Architecture and Electronics, University of Almería, Almería, Spain.
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