1
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de Isidro-Gómez FP, Vilas JL, Losana P, Carazo JM, Sorzano COS. A deep learning approach to the automatic detection of alignment errors in cryo-electron tomographic reconstructions. J Struct Biol 2024; 216:108056. [PMID: 38101554 DOI: 10.1016/j.jsb.2023.108056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 11/21/2023] [Accepted: 12/11/2023] [Indexed: 12/17/2023]
Abstract
Electron tomography is an imaging technique that allows for the elucidation of three-dimensional structural information of biological specimens in a very general context, including cellular in situ observations. The approach starts by collecting a set of images at different projection directions by tilting the specimen stage inside the microscope. Therefore, a crucial preliminary step is to precisely define the acquisition geometry by aligning all the tilt images to a common reference. Errors introduced in this step will lead to the appearance of artifacts in the tomographic reconstruction, rendering them unsuitable for the sample study. Focusing on fiducial-based acquisition strategies, this work proposes a deep-learning algorithm to detect misalignment artifacts in tomographic reconstructions by analyzing the characteristics of these fiducial markers in the tomogram. In addition, we propose an algorithm designed to detect fiducial markers in the tomogram with which to feed the classification algorithm in case the alignment algorithm does not provide the location of the markers. This open-source software is available as part of the Xmipp software package inside of the Scipion framework, and also through the command-line in the standalone version of Xmipp.
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Affiliation(s)
- F P de Isidro-Gómez
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain; Univ. Autonoma de Madrid, 28049 Cantoblanco, Madrid, Spain
| | - J L Vilas
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - P Losana
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - J M Carazo
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - C O S Sorzano
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain.
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2
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Kleywegt GJ, Adams PD, Butcher SJ, Lawson CL, Rohou A, Rosenthal PB, Subramaniam S, Topf M, Abbott S, Baldwin PR, Berrisford JM, Bricogne G, Choudhary P, Croll TI, Danev R, Ganesan SJ, Grant T, Gutmanas A, Henderson R, Heymann JB, Huiskonen JT, Istrate A, Kato T, Lander GC, Lok SM, Ludtke SJ, Murshudov GN, Pye R, Pintilie GD, Richardson JS, Sachse C, Salih O, Scheres SHW, Schroeder GF, Sorzano COS, Stagg SM, Wang Z, Warshamanage R, Westbrook JD, Winn MD, Young JY, Burley SK, Hoch JC, Kurisu G, Morris K, Patwardhan A, Velankar S. Community recommendations on cryoEM data archiving and validation. IUCrJ 2024; 11:140-151. [PMID: 38358351 PMCID: PMC10916293 DOI: 10.1107/s2052252524001246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Accepted: 02/06/2024] [Indexed: 02/16/2024]
Abstract
In January 2020, a workshop was held at EMBL-EBI (Hinxton, UK) to discuss data requirements for the deposition and validation of cryoEM structures, with a focus on single-particle analysis. The meeting was attended by 47 experts in data processing, model building and refinement, validation, and archiving of such structures. This report describes the workshop's motivation and history, the topics discussed, and the resulting consensus recommendations. Some challenges for future methods-development efforts in this area are also highlighted, as is the implementation to date of some of the recommendations.
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Affiliation(s)
| | - Paul D. Adams
- Lawrence Berkeley National Laboratory, Berkeley, CA, USA
- University of California, Berkeley, CA, USA
| | | | | | | | | | | | - Maya Topf
- Birkbeck, University of London, London, United Kingdom
| | | | | | | | | | | | | | | | - Sai J. Ganesan
- University of California at San Francisco, San Francisco, CA, USA
| | | | | | | | | | | | | | | | | | | | | | | | - Ryan Pye
- EMBL-EBI, Cambridge, United Kingdom
| | | | | | | | | | | | | | | | | | - Zhe Wang
- EMBL-EBI, Cambridge, United Kingdom
| | | | | | - Martyn D. Winn
- Science and Technology Facilities Council, Research Complex at Harwell, Oxon, United Kingdom
| | - Jasmine Y. Young
- RCSB Protein Data Bank, The State University of New Jersey, NJ, USA
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3
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Kleywegt GJ, Adams PD, Butcher SJ, Lawson CL, Rohou A, Rosenthal PB, Subramaniam S, Topf M, Abbott S, Baldwin PR, Berrisford JM, Bricogne G, Choudhary P, Croll TI, Danev R, Ganesan SJ, Grant T, Gutmanas A, Henderson R, Heymann JB, Huiskonen JT, Istrate A, Kato T, Lander GC, Lok SM, Ludtke SJ, Murshudov GN, Pye R, Pintilie GD, Richardson JS, Sachse C, Salih O, Scheres SHW, Schroeder GF, Sorzano COS, Stagg SM, Wang Z, Warshamanage R, Westbrook JD, Winn MD, Young JY, Burley SK, Hoch JC, Kurisu G, Morris K, Patwardhan A, Velankar S. Community recommendations on cryoEM data archiving and validation: Outcomes of a wwPDB/EMDB workshop on cryoEM data management, deposition and validation. ArXiv 2024:arXiv:2311.17640v3. [PMID: 38076521 PMCID: PMC10705588] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Abstract
In January 2020, a workshop was held at EMBL-EBI (Hinxton, UK) to discuss data requirements for deposition and validation of cryoEM structures, with a focus on single-particle analysis. The meeting was attended by 47 experts in data processing, model building and refinement, validation, and archiving of such structures. This report describes the workshop's motivation and history, the topics discussed, and consensus recommendations resulting from the workshop. Some challenges for future methods-development efforts in this area are also highlighted, as is the implementation to date of some of the recommendations.
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Affiliation(s)
| | - Paul D Adams
- Lawrence Berkeley Laboratory, Berkeley, CA, USA and University of California, Berkeley, CA, USA
| | | | - Catherine L Lawson
- RCSB Protein Data Bank, Rutgers, The State University of New Jersey, USA
| | | | | | | | - Maya Topf
- Birkbeck, University of London, London, UK
| | | | | | | | | | | | | | | | - Sai J Ganesan
- University of California at San Francisco, San Francisco, CA, USA
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - John D Westbrook
- RCSB Protein Data Bank, Rutgers, The State University of New Jersey, USA
| | - Martyn D Winn
- Science and Technology Facilities Council, Research Complex at Harwell, Oxon, UK
| | - Jasmine Y Young
- RCSB Protein Data Bank, Rutgers, The State University of New Jersey, USA
| | - Stephen K Burley
- RCSB Protein Data Bank, Rutgers, The State University of New Jersey, USA
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4
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Fernandez-Gimenez E, Carazo JM, Sorzano COS. Local defocus estimation in single particle analysis in cryo-electron microscopy. J Struct Biol 2023; 215:108030. [PMID: 37758154 DOI: 10.1016/j.jsb.2023.108030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2023] [Revised: 08/30/2023] [Accepted: 09/21/2023] [Indexed: 10/02/2023]
Abstract
Single Particle analysis (SPA) aims to determine the three-dimensional structure of proteins and macromolecular complexes. The current state of the art has allowed us to achieve near-atomic and even atomic resolutions. To obtain high-resolution structures, a set of well-defined image processing steps is required. A critical one is the estimation of the Contrast Transfer Function (CTF), which considers the sample defocus and aberrations of the microscope. Defocus is usually globally estimated; in this case, it is the same for all the particles in each micrograph. But proteins are ice-embedded at different heights, suggesting that defocus should be measured in a local (per particle) manner. There are four state-of-the-art programs to estimate local defocus (Gctf, Relion, CryoSPARC, and Xmipp). In this work, we have compared the results of these software packages to check whether the resolution improves. We have used the Scipion framework and developed a specific program to analyze local defocus. The results produced by different programs do not show a clear consensus using the current test datasets in this study.
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Affiliation(s)
- E Fernandez-Gimenez
- Centro Nac. Biotecnologia (CSIC), c/Darwin, 3, 28049 Cantoblanco, Madrid, Spain; Univ. Autonoma de Madrid, 28049 Cantoblanco, Madrid, Spain
| | - J M Carazo
- Centro Nac. Biotecnologia (CSIC), c/Darwin, 3, 28049 Cantoblanco, Madrid, Spain
| | - C O S Sorzano
- Centro Nac. Biotecnologia (CSIC), c/Darwin, 3, 28049 Cantoblanco, Madrid, Spain.
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5
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Fernández-Giménez E, Martínez MM, Marabini R, Strelak D, Sánchez-García R, Carazo JM, Sorzano COS. A new algorithm for particle weighted subtraction to decrease signals from unwanted components in single particle analysis. J Struct Biol 2023; 215:108024. [PMID: 37704013 DOI: 10.1016/j.jsb.2023.108024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Revised: 08/22/2023] [Accepted: 09/04/2023] [Indexed: 09/15/2023]
Abstract
Single particle analysis (SPA) in cryo-electron microscopy (cryo-EM) is highly used to obtain the near-atomic structure of biological macromolecules. The current methods allow users to produce high-resolution maps from many samples. However, there are still challenging cases that require extra processing to obtain high resolution. This is the case when the macromolecule of the sample is composed of different components and we want to focus just on one of them. For example, if the macromolecule is composed of several flexible subunits and we are interested in a specific one, if it is embedded in a viral capsid environment, or if it has additional components to stabilize it, such as nanodiscs. The signal from these components, which in principle we are not interested in, can be removed from the particles using a projection subtraction method. Currently, there are two projection subtraction methods used in practice and both have some limitations. In fact, after evaluating their results, we consider that the problem is still open to new solutions, as they do not fully remove the signal of the components that are not of interest. Our aim is to develop a new and more precise projection subtraction method, improving the performance of state-of-the-art methods. We tested our algorithm with data from public databases and an in-house data set. In this work, we show that the performance of our algorithm improves the results obtained by others, including the localization of small ligands, such as drugs, whose binding location is unknown a priori.
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Affiliation(s)
- E Fernández-Giménez
- Centro Nac. Biotecnología (CSIC), c/Darwin, 3, 28049 Cantoblanco, Madrid, Spain; Univ. Autonoma de Madrid, 28049 Cantoblanco, Madrid, Spain
| | - M M Martínez
- Centro Nac. Biotecnología (CSIC), c/Darwin, 3, 28049 Cantoblanco, Madrid, Spain
| | - R Marabini
- Centro Nac. Biotecnología (CSIC), c/Darwin, 3, 28049 Cantoblanco, Madrid, Spain; Univ. Autonoma de Madrid, 28049 Cantoblanco, Madrid, Spain
| | - D Strelak
- Institute of Computer Science, Masaryk University, Botanická 68a, 60200 Brno, Czech Republic
| | - R Sánchez-García
- Department of Statistics, University of Oxford, 24-29 St Giles', Oxford OX1 3LB, United Kingdom; Astex Pharmaceuticals, 436 Cambridge Science Park, Cambridge CB4 0QA, UK
| | - J M Carazo
- Centro Nac. Biotecnología (CSIC), c/Darwin, 3, 28049 Cantoblanco, Madrid, Spain
| | - C O S Sorzano
- Centro Nac. Biotecnología (CSIC), c/Darwin, 3, 28049 Cantoblanco, Madrid, Spain.
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6
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Cayuela López A, García-Cuesta EM, Gardeta SR, Rodríguez-Frade JM, Mellado M, Gómez-Pedrero JA, S. Sorzano CO. TrackAnalyzer: A Fiji/ImageJ toolbox for a holistic analysis of tracks. Biol Imaging 2023; 3:e18. [PMID: 38510172 PMCID: PMC10951927 DOI: 10.1017/s2633903x23000181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 07/16/2023] [Accepted: 09/08/2023] [Indexed: 03/22/2024]
Abstract
Current live-cell imaging techniques make possible the observation of live events and the acquisition of large datasets to characterize the different parameters of the visualized events. They provide new insights into the dynamics of biological processes with unprecedented spatial and temporal resolutions. Here we describe the implementation and application of a new tool called TrackAnalyzer, accessible from Fiji and ImageJ. Our tool allows running semi-automated single-particle tracking (SPT) and subsequent motion classification, as well as quantitative analysis of diffusion and intensity for selected tracks relying on the graphical user interface (GUI) for large sets of temporal images (X-Y-T or X-Y-C-T dimensions). TrackAnalyzer also allows 3D visualization of the results as overlays of either spots, cells or end-tracks over time, along with corresponding feature extraction and further classification according to user criteria. Our analysis workflow automates the following steps: (1) spot or cell detection and filtering, (2) construction of tracks, (3) track classification and analysis (diffusion and chemotaxis), and (4) detailed analysis and visualization of all the outputs along the pipeline. All these analyses are automated and can be run in batch mode for a set of similar acquisitions.
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Affiliation(s)
- Ana Cayuela López
- Biocomputing Unit, National Centre for Biotechnology, Cantoblanco, Madrid, Spain
| | - Eva M. García-Cuesta
- Department of Immunology and Oncology, National Centre for Biotechnology, Cantoblanco, Madrid, Spain
| | - Sofía R. Gardeta
- Department of Immunology and Oncology, National Centre for Biotechnology, Cantoblanco, Madrid, Spain
| | | | - Mario Mellado
- Department of Immunology and Oncology, National Centre for Biotechnology, Cantoblanco, Madrid, Spain
| | - José Antonio Gómez-Pedrero
- Applied Optics Complutense Group, Faculty of Optics and Optometry, University Complutense of Madrid, Madrid, Spain
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7
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Krieger JM, Sorzano COS, Carazo JM. Scipion-EM-ProDy: A Graphical Interface for the ProDy Python Package within the Scipion Workflow Engine Enabling Integration of Databases, Simulations and Cryo-Electron Microscopy Image Processing. Int J Mol Sci 2023; 24:14245. [PMID: 37762547 PMCID: PMC10532346 DOI: 10.3390/ijms241814245] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 09/10/2023] [Accepted: 09/15/2023] [Indexed: 09/29/2023] Open
Abstract
Macromolecular assemblies, such as protein complexes, undergo continuous structural dynamics, including global reconfigurations critical for their function. Two fast analytical methods are widely used to study these global dynamics, namely elastic network model normal mode analysis and principal component analysis of ensembles of structures. These approaches have found wide use in various computational studies, driving the development of complex pipelines in several software packages. One common theme has been conformational sampling through hybrid simulations incorporating all-atom molecular dynamics and global modes of motion. However, wide functionality is only available for experienced programmers with limited capabilities for other users. We have, therefore, integrated one popular and extensively developed software for such analyses, the ProDy Python application programming interface, into the Scipion workflow engine. This enables a wider range of users to access a complete range of macromolecular dynamics pipelines beyond the core functionalities available in its command-line applications and the normal mode wizard in VMD. The new protocols and pipelines can be further expanded and integrated into larger workflows, together with other software packages for cryo-electron microscopy image analysis and molecular simulations. We present the resulting plugin, Scipion-EM-ProDy, in detail, highlighting the rich functionality made available by its development.
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Affiliation(s)
- James M. Krieger
- Biocomputing Unit, National Centre for Biotechnology (CNB CSIC), Campus Universidad Autónoma de Madrid, Darwin 3, Cantoblanco, 28049 Madrid, Spain
| | | | - Jose Maria Carazo
- Biocomputing Unit, National Centre for Biotechnology (CNB CSIC), Campus Universidad Autónoma de Madrid, Darwin 3, Cantoblanco, 28049 Madrid, Spain
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8
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Soler Palacios B, Villares R, Lucas P, Rodríguez-Frade JM, Cayuela A, Piccirillo JG, Lombardía M, Delgado Gestoso D, Fernández-García M, Risco C, Barbas C, Corrales F, Sorzano COS, Martínez-Martín N, Conesa JJ, Iborra FJ, Mellado M. Growth hormone remodels the 3D-structure of the mitochondria of inflammatory macrophages and promotes metabolic reprogramming. Front Immunol 2023; 14:1200259. [PMID: 37475858 PMCID: PMC10354525 DOI: 10.3389/fimmu.2023.1200259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Accepted: 06/14/2023] [Indexed: 07/22/2023] Open
Abstract
Introduction Macrophages are a heterogeneous population of innate immune cells that support tissue homeostasis through their involvement in tissue development and repair, and pathogen defense. Emerging data reveal that metabolism may control macrophage polarization and function and, conversely, phenotypic polarization may drive metabolic reprogramming. Methods Here we use biochemical analysis, correlative cryogenic fluorescence microscopy and cryo-focused ion-beam scanning electron microscopy. Results We demonstrate that growth hormone (GH) reprograms inflammatory GM-CSF-primed monocyte-derived macrophages (GM-MØ) by functioning as a metabolic modulator. We found that exogenous treatment of GM-MØ with recombinant human GH reduced glycolysis and lactate production to levels similar to those found in anti-inflammatory M-MØ. Moreover, GH treatment of GM-MØ augmented mitochondrial volume and altered mitochondrial dynamics, including the remodeling of the inner membrane to increase the density of cristae. Conclusions Our data demonstrate that GH likely serves a modulatory role in the metabolism of inflammatory macrophages and suggest that metabolic reprogramming of macrophages should be considered as a new target to intervene in inflammatory diseases.
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Affiliation(s)
- Blanca Soler Palacios
- Department of Immunology and Oncology, National Center for Biotechnology/The Spanish National Research Council (CSIC), Madrid, Spain
| | - Ricardo Villares
- Department of Immunology and Oncology, National Center for Biotechnology/The Spanish National Research Council (CSIC), Madrid, Spain
| | - Pilar Lucas
- Department of Immunology and Oncology, National Center for Biotechnology/The Spanish National Research Council (CSIC), Madrid, Spain
| | - José Miguel Rodríguez-Frade
- Department of Immunology and Oncology, National Center for Biotechnology/The Spanish National Research Council (CSIC), Madrid, Spain
| | - Ana Cayuela
- Biocomputing Unit, National Center for Biotechnology/The Spanish National Research Council (CSIC), Madrid, Spain
| | - Jonathan G. Piccirillo
- Department of Macromolecular Structures, National Center for Biotechnology/The Spanish National Research Council) (CSIC), Madrid, Spain
| | - Manuel Lombardía
- Functional Proteomics Laboratory, National Center for Biotechnology/The Spanish National Research Council (CSIC), Madrid, Spain
| | - David Delgado Gestoso
- Department of Macromolecular Structures, National Center for Biotechnology/The Spanish National Research Council) (CSIC), Madrid, Spain
| | - Miguel Fernández-García
- Metabolomic and Bioanalysis Center (CEMBIO), Pharmacy Faculty, Universidad San Pablo-CEU, Centre for Universitary Studies (CEU) Universities, Boadilla del Monte, Spain
- Department of Basic Medical Sciences, Medicine Faculty, Universidad San Pablo-CEU, Centre for Universitary Studies (CEU) Universities, Boadilla del Monte, Spain
| | - Cristina Risco
- Department of Macromolecular Structures, National Center for Biotechnology/The Spanish National Research Council) (CSIC), Madrid, Spain
| | - Coral Barbas
- Metabolomic and Bioanalysis Center (CEMBIO), Pharmacy Faculty, Universidad San Pablo-CEU, Centre for Universitary Studies (CEU) Universities, Boadilla del Monte, Spain
| | - Fernando Corrales
- Functional Proteomics Laboratory, National Center for Biotechnology/The Spanish National Research Council (CSIC), Madrid, Spain
| | - Carlos Oscar S. Sorzano
- Biocomputing Unit, National Center for Biotechnology/The Spanish National Research Council (CSIC), Madrid, Spain
| | - Nuria Martínez-Martín
- Tissue and Organ Homeostasis Program, Centro de Biologia Molecular Severo Ochoa, The Spanish National Research Council (CSIC)–Autonomus University of Madrid (UAM), Madrid, Spain
| | - José Javier Conesa
- Department of Macromolecular Structures, National Center for Biotechnology/The Spanish National Research Council) (CSIC), Madrid, Spain
| | - Francisco J. Iborra
- Príncipe Felípe Research Centre (Associated Unit to the Biomedicine Institute of Valencia), Biomedicine Institute of Valencia, Valencia, Spain
| | - Mario Mellado
- Department of Immunology and Oncology, National Center for Biotechnology/The Spanish National Research Council (CSIC), Madrid, Spain
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Herreros D, Krieger JM, Fonseca Y, Conesa P, Harastani M, Vuillemot R, Hamitouche I, Serrano Gutiérrez R, Gragera M, Melero R, Jonic S, Carazo JM, Sorzano COS. Scipion Flexibility Hub: an integrative framework for advanced analysis of conformational heterogeneity in cryoEM. Acta Crystallogr D Struct Biol 2023; 79:S2059798323004497. [PMID: 37326585 DOI: 10.1107/s2059798323004497] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 05/22/2023] [Indexed: 06/17/2023] Open
Abstract
Understanding how structure and function meet to drive biological processes is progressively shifting the cryoEM field towards a more advanced analysis of macromolecular flexibility. Thanks to techniques such as single-particle analysis and electron tomography, it is possible to image a macromolecule in different states, information that can subsequently be extracted through advanced image-processing methods to build a richer approximation of a conformational landscape. However, the interoperability of all of these algorithms remains a challenging task that is left to users, preventing them from defining a single flexible workflow in which conformational information can be addressed by different algorithms. Therefore, in this work, a new framework integrated into Scipion is proposed called the Flexibility Hub. This framework automatically handles intercommunication between different heterogeneity software, simplifying the task of combining the software into workflows in which the quality and the amount of information extracted from flexibility analysis is maximized.
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Affiliation(s)
- D Herreros
- Centro Nacional de Biotecnologia - CSIC, Calle Darwin 3, 28049 Madrid, Spain
| | - J M Krieger
- Centro Nacional de Biotecnologia - CSIC, Calle Darwin 3, 28049 Madrid, Spain
| | - Y Fonseca
- Centro Nacional de Biotecnologia - CSIC, Calle Darwin 3, 28049 Madrid, Spain
| | - P Conesa
- Centro Nacional de Biotecnologia - CSIC, Calle Darwin 3, 28049 Madrid, Spain
| | - M Harastani
- IMPMC-UMR 7590 CNRS, Sorbonne Université, MNHN, Paris, France
| | - R Vuillemot
- IMPMC-UMR 7590 CNRS, Sorbonne Université, MNHN, Paris, France
| | - I Hamitouche
- IMPMC-UMR 7590 CNRS, Sorbonne Université, MNHN, Paris, France
| | - R Serrano Gutiérrez
- Centro Nacional de Biotecnologia - CSIC, Calle Darwin 3, 28049 Madrid, Spain
| | - M Gragera
- Centro Nacional de Biotecnologia - CSIC, Calle Darwin 3, 28049 Madrid, Spain
| | - R Melero
- Centro Nacional de Biotecnologia - CSIC, Calle Darwin 3, 28049 Madrid, Spain
| | - S Jonic
- IMPMC-UMR 7590 CNRS, Sorbonne Université, MNHN, Paris, France
| | - J M Carazo
- Centro Nacional de Biotecnologia - CSIC, Calle Darwin 3, 28049 Madrid, Spain
| | - C O S Sorzano
- Centro Nacional de Biotecnologia - CSIC, Calle Darwin 3, 28049 Madrid, Spain
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10
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Herreros D, Kiska J, Ramirez E, Filipovic J, Carazo JM, Sorzano COS. ZART: A novel multiresolution reconstruction algorithm with motion-blur correction for single particle analysis. J Mol Biol 2023; 435:168088. [PMID: 37030648 DOI: 10.1016/j.jmb.2023.168088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 03/31/2023] [Accepted: 04/01/2023] [Indexed: 04/10/2023]
Abstract
One of the main purposes of CryoEM Single Particle Analysis is to reconstruct the three-dimensional structure of a macromolecule thanks to the acquisition of many particle images representing different poses of the sample. By estimating the orientation of each projected particle, it is possible to recover the underlying 3D volume by multiple 3D reconstruction methods, usually working either in Fourier or in real space. However, the reconstruction from the projected images works under the assumption that all particles in the dataset correspond to the same conformation of the macromolecule. Although this requisite holds for some macromolecules, it is not true for flexible specimens, leading to motion-induced artefacts in the reconstructed CryoEM maps. In this work, we introduce a new Algebraic Reconstruction Technique called ZART, which is able to include continuous flexibility information during the reconstruction process to improve local resolution and reduce motion blurring. The conformational changes are modelled through Zernike3D polynomials. Our implementation allows for a multiresolution description of the macromolecule adapting itself to the local resolution of the reconstructed map. In addition, ZART has also proven to be a useful algorithm in cases where flexibility is not so dominant, as it improves the overall aspect of the reconstructed maps by improving their local and global resolution.
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Affiliation(s)
- D Herreros
- Centro Nacional de Biotecnologia-CSIC, C/ Darwin, 3, 28049, Cantoblanco, Madrid, Spain.
| | - J Kiska
- Institute of Computer Science, Masaryk University, Botanická 68a, 60200 Brno, Czech Republic
| | - E Ramirez
- Centro Nacional de Biotecnologia-CSIC, C/ Darwin, 3, 28049, Cantoblanco, Madrid, Spain
| | - J Filipovic
- Institute of Computer Science, Masaryk University, Botanická 68a, 60200 Brno, Czech Republic
| | - J M Carazo
- Centro Nacional de Biotecnologia-CSIC, C/ Darwin, 3, 28049, Cantoblanco, Madrid, Spain.
| | - C O S Sorzano
- Centro Nacional de Biotecnologia-CSIC, C/ Darwin, 3, 28049, Cantoblanco, Madrid, Spain.
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11
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Herreros D, Lederman RR, Krieger JM, Jiménez-Moreno A, Martínez M, Myška D, Strelak D, Filipovic J, Sorzano COS, Carazo JM. Estimating conformational landscapes from Cryo-EM particles by 3D Zernike polynomials. Nat Commun 2023; 14:154. [PMID: 36631472 PMCID: PMC9832421 DOI: 10.1038/s41467-023-35791-y] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Accepted: 12/29/2022] [Indexed: 01/12/2023] Open
Abstract
The new developments in Cryo-EM Single Particle Analysis are helping us to understand how the macromolecular structure and function meet to drive biological processes. By capturing many states at the particle level, it is possible to address how macromolecules explore different conformations, information that is classically extracted through 3D classification. However, the limitations of classical approaches prevent us from fully understanding the complete conformational landscape due to the reduced number of discrete states accurately reconstructed. To characterize the whole structural spectrum of a macromolecule, we propose an extension of our Zernike3D approach, able to extract per-image continuous flexibility information directly from a particle dataset. Also, our method can be seamlessly applied to images, maps or atomic models, opening integrative possibilities. Furthermore, we introduce the ZART reconstruction algorithm, which considers the Zernike3D deformation fields to revert particle conformational changes during the reconstruction process, thus minimizing the blurring induced by molecular motions.
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Affiliation(s)
- D Herreros
- Centro Nacional de Biotecnologia-CSIC, C/Darwin, 3, 28049, Cantoblanco, Madrid, Spain.
| | - R R Lederman
- The Department of Statistics and Data Science, Yale University, New Haven, CT, USA
| | - J M Krieger
- Centro Nacional de Biotecnologia-CSIC, C/Darwin, 3, 28049, Cantoblanco, Madrid, Spain
| | - A Jiménez-Moreno
- Centro Nacional de Biotecnologia-CSIC, C/Darwin, 3, 28049, Cantoblanco, Madrid, Spain
| | - M Martínez
- Centro Nacional de Biotecnologia-CSIC, C/Darwin, 3, 28049, Cantoblanco, Madrid, Spain
| | - D Myška
- Institute of Computer Science, Masaryk University, Botanická 68a, 60200, Brno, Czech Republic
| | - D Strelak
- Centro Nacional de Biotecnologia-CSIC, C/Darwin, 3, 28049, Cantoblanco, Madrid, Spain.,Faculty of Informatics, Masaryk University, Botanická 68a, 60200, Brno, Czech Republic
| | - J Filipovic
- Institute of Computer Science, Masaryk University, Botanická 68a, 60200, Brno, Czech Republic
| | - C O S Sorzano
- Centro Nacional de Biotecnologia-CSIC, C/Darwin, 3, 28049, Cantoblanco, Madrid, Spain
| | - J M Carazo
- Centro Nacional de Biotecnologia-CSIC, C/Darwin, 3, 28049, Cantoblanco, Madrid, Spain
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12
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Garcia Condado J, Muñoz-Barrutia A, Sorzano COS. Automatic determination of the handedness of single-particle maps of macromolecules solved by CryoEM. J Struct Biol 2022; 214:107915. [PMID: 36341955 DOI: 10.1016/j.jsb.2022.107915] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Revised: 08/29/2022] [Accepted: 10/25/2022] [Indexed: 12/07/2022]
Abstract
Single-Particle Analysis by Cryo-Electron Microscopy is a well-established technique to elucidate the three-dimensional (3D) structure of biological macromolecules. The orientation of the acquired projection images must be initially estimated without any reference to the final structure. In this step, algorithms may find a mirrored version of all the orientations resulting in a mirrored 3D map. It is as compatible with the acquired images as its unmirrored version from the image processing point of view, only that it is not biologically plausible. In this article, we introduce HaPi (Handedness Pipeline), the first method to automatically determine the hand of electron density maps of macromolecules solved by CryoEM. HaPi is built by training two 3D convolutional neural networks. The first determines α-helices in a map, and the second determines whether the α-helix is left-handed or right-handed. A consensus strategy defines the overall map hand. The pipeline is trained on simulated and experimental data. The handedness can be detected only for maps whose resolution is better than 5 Å. HaPi can identify the hand in 89% of new simulated maps correctly. Moreover, we evaluated all the maps deposited at the Electron Microscopy Data Bank and 11 structures uploaded with the incorrect hand were identified.
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Affiliation(s)
- J Garcia Condado
- Biocruces Bizkaia Instituto Investigación Sanitaria, Cruces Plaza, 48903 Barakaldo, Bizkaia, Spain; Universidad Carlos III de Madrid, Avda. de la Universidad 30, 28911 Leganés, Madrid, Spain; Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - A Muñoz-Barrutia
- Universidad Carlos III de Madrid, Avda. de la Universidad 30, 28911 Leganés, Madrid, Spain
| | - C O S Sorzano
- Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain.
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13
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Bepler T, Borst AJ, Bouvette J, Cannone G, Chen S, Cheng A, Cheng A, Fan Q, Grollios F, Gupta H, Gupta M, Humphreys T, Kim PT, Kuang H, Li Y, Noble AJ, Punjani A, Rice WJ, Oscar S Sorzano C, Stagg SM, Strauss J, Yu L, Carragher B, Potter CS. Smart data collection for CryoEM. J Struct Biol 2022; 214:107913. [PMID: 36341954 DOI: 10.1016/j.jsb.2022.107913] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Revised: 09/29/2022] [Accepted: 10/23/2022] [Indexed: 11/06/2022]
Abstract
This report provides an overview of the discussions, presentations, and consensus thinking from the Workshop on Smart Data Collection for CryoEM held at the New York Structural Biology Center on April 6-7, 2022. The goal of the workshop was to address next generation data collection strategies that integrate machine learning and real-time processing into the workflow to reduce or eliminate the need for operator intervention.
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Affiliation(s)
| | - Andrew J Borst
- University of Washington, Institute for Protein Design, Seattle, WA, USA
| | - Jonathan Bouvette
- National Institute of Environmental Health Sciences, NIH, Durham, NC, USA
| | - Giuseppe Cannone
- Laboratory for Molecular Biology, Medical Research Council, Cambridge, England
| | - Songye Chen
- California Institute of Technology, Pasadena, CA, USA
| | - Anchi Cheng
- New York Structural Biology Center, New York, NY, USA
| | - Ao Cheng
- Northwestern University, Evanston, IL, USA
| | - Quanfu Fan
- MIT-IBM Watson AI Lab, Cambridge, MA, USA
| | | | - Harshit Gupta
- SLAC National Accelerator Laboratory, Menlo Park, CA, USA
| | - Meghna Gupta
- University of California at San Francisco, San Francisco, CA, USA
| | | | - Paul T Kim
- New York Structural Biology Center, New York, NY, USA
| | - Huihui Kuang
- New York Structural Biology Center, New York, NY, USA
| | - Yilai Li
- University of Michigan, Ann Arbor, MI, USA
| | - Alex J Noble
- New York Structural Biology Center, New York, NY, USA
| | | | - William J Rice
- New York University School of Medicine, New York, NY, USA
| | | | | | - Joshua Strauss
- University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Lingbo Yu
- ThermoFisher Scientific, Eindhoven, The Netherlands
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14
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Sorzano COS, Vilas JL, Ramírez-Aportela E, Krieger J, Del Hoyo D, Herreros D, Fernandez-Giménez E, Marchán D, Macías JR, Sánchez I, Del Caño L, Fonseca-Reyna Y, Conesa P, García-Mena A, Burguet J, García Condado J, Méndez García J, Martínez M, Muñoz-Barrutia A, Marabini R, Vargas J, Carazo JM. Image processing tools for the validation of CryoEM maps. Faraday Discuss 2022; 240:210-227. [PMID: 35861059 DOI: 10.1039/d2fd00059h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
The number of maps deposited in public databases (Electron Microscopy Data Bank, EMDB) determined by cryo-electron microscopy has quickly grown in recent years. With this rapid growth, it is critical to guarantee their quality. So far, map validation has primarily focused on the agreement between maps and models. From the image processing perspective, the validation has been mostly restricted to using two half-maps and the measurement of their internal consistency. In this article, we suggest that map validation can be taken much further from the point of view of image processing if 2D classes, particles, angles, coordinates, defoci, and micrographs are also provided. We present a progressive validation scheme that qualifies a result validation status from 0 to 5 and offers three optional qualifiers (A, W, and O) that can be added. The simplest validation state is 0, while the most complete would be 5AWO. This scheme has been implemented in a website https://biocomp.cnb.csic.es/EMValidationService/ to which reconstructed maps and their ESI can be uploaded.
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Affiliation(s)
- C O S Sorzano
- Natl. Center of Biotechnology, CSIC, c/Darwin, 3, 28049, Madrid, Spain.
| | - J L Vilas
- Natl. Center of Biotechnology, CSIC, c/Darwin, 3, 28049, Madrid, Spain.
| | | | - J Krieger
- Natl. Center of Biotechnology, CSIC, c/Darwin, 3, 28049, Madrid, Spain.
| | - D Del Hoyo
- Natl. Center of Biotechnology, CSIC, c/Darwin, 3, 28049, Madrid, Spain.
| | - D Herreros
- Natl. Center of Biotechnology, CSIC, c/Darwin, 3, 28049, Madrid, Spain.
| | | | - D Marchán
- Natl. Center of Biotechnology, CSIC, c/Darwin, 3, 28049, Madrid, Spain.
| | - J R Macías
- Natl. Center of Biotechnology, CSIC, c/Darwin, 3, 28049, Madrid, Spain.
| | - I Sánchez
- Natl. Center of Biotechnology, CSIC, c/Darwin, 3, 28049, Madrid, Spain.
| | - L Del Caño
- Natl. Center of Biotechnology, CSIC, c/Darwin, 3, 28049, Madrid, Spain.
| | - Y Fonseca-Reyna
- Natl. Center of Biotechnology, CSIC, c/Darwin, 3, 28049, Madrid, Spain.
| | - P Conesa
- Natl. Center of Biotechnology, CSIC, c/Darwin, 3, 28049, Madrid, Spain.
| | - A García-Mena
- Natl. Center of Biotechnology, CSIC, c/Darwin, 3, 28049, Madrid, Spain.
| | - J Burguet
- Depto. de Óptica, Univ. Complutense de Madrid, Pl. Ciencias, 1, 28040, Madrid, Spain
| | - J García Condado
- Biocruces Bizkaia Instituto Investigación Sanitaria, Cruces Plaza, 48903, Barakaldo, Bizkaia, Spain
| | | | - M Martínez
- Natl. Center of Biotechnology, CSIC, c/Darwin, 3, 28049, Madrid, Spain.
| | - A Muñoz-Barrutia
- Univ. Carlos III de Madrid, Avda. de la Universidad 30, 28911, Leganés, Madrid, Spain
| | - R Marabini
- Escuela Politécnica Superior, Univ. Autónoma de Madrid, CSIC, C. Francisco Tomás y Valiente, 11, 28049, Madrid, Spain
| | - J Vargas
- Depto. de Óptica, Univ. Complutense de Madrid, Pl. Ciencias, 1, 28040, Madrid, Spain
| | - J M Carazo
- Natl. Center of Biotechnology, CSIC, c/Darwin, 3, 28049, Madrid, Spain.
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15
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Ramírez-Aportela E, Carazo JM, Sorzano COS. Higher resolution in cryo-EM by the combination of macromolecular prior knowledge and image-processing tools. IUCrJ 2022; 9:632-638. [PMID: 36071808 PMCID: PMC9438491 DOI: 10.1107/s2052252522006959] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 07/07/2022] [Indexed: 06/15/2023]
Abstract
Single-particle cryo-electron microscopy has become a powerful technique for the 3D structure determination of biological molecules. The last decade has seen an astonishing development of both hardware and software, and an exponential growth of new structures obtained at medium-high resolution. However, the knowledge accumulated in this field over the years has hardly been utilized as feedback in the reconstruction of new structures. In this context, this article explores the use of the deep-learning approach deepEMhancer as a regularizer in the RELION refinement process. deepEMhancer introduces prior information derived from macromolecular structures, and contributes to noise reduction and signal enhancement, as well as a higher degree of isotropy. These features have a direct effect on image alignment and reduction of overfitting during iterative refinement. The advantages of this combination are demonstrated for several membrane proteins, for which it is especially useful because of their high disorder and flexibility.
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Affiliation(s)
- Erney Ramírez-Aportela
- Biocomputing Unit, National Centre for Biotechnology (CNB CSIC), Darwin 3, Campus Universidad Autónoma de Madrid, Cantoblanco, Madrid 28049, Spain
| | - Jose M. Carazo
- Biocomputing Unit, National Centre for Biotechnology (CNB CSIC), Darwin 3, Campus Universidad Autónoma de Madrid, Cantoblanco, Madrid 28049, Spain
| | - Carlos Oscar S. Sorzano
- Biocomputing Unit, National Centre for Biotechnology (CNB CSIC), Darwin 3, Campus Universidad Autónoma de Madrid, Cantoblanco, Madrid 28049, Spain
- Universidad CEU San Pablo, Campus Urb. Montepríncipe, Boadilla del Monte, Madrid 28668, Spain
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16
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Abstract
Cryo-electron microscopy (CryoEM) has become a vital technique in structural biology. It is an interdisciplinary field that takes advantage of advances in biochemistry, physics, and image processing, among other disciplines. Innovations in these three basic pillars have contributed to the boosting of CryoEM in the past decade. This work reviews the main contributions in image processing to the current reconstruction workflow of single particle analysis (SPA) by CryoEM. Our review emphasizes the time evolution of the algorithms across the different steps of the workflow differentiating between two groups of approaches: analytical methods and deep learning algorithms. We present an analysis of the current state of the art. Finally, we discuss the emerging problems and challenges still to be addressed in the evolution of CryoEM image processing methods in SPA.
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Affiliation(s)
- Jose Luis Vilas
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - Jose Maria Carazo
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - Carlos Oscar S Sorzano
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
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17
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Jiménez de la Morena J, Conesa P, Fonseca YC, de Isidro-Gómez FP, Herreros D, Fernández-Giménez E, Strelak D, Moebel E, Buchholz TO, Jug F, Martinez-Sanchez A, Harastani M, Jonic S, Conesa JJ, Cuervo A, Losana P, Sánchez I, Iceta M, Del Cano L, Gragera M, Melero R, Sharov G, Castaño-Díez D, Koster A, Piccirillo JG, Vilas JL, Otón J, Marabini R, Sorzano COS, Carazo JM. ScipionTomo: Towards cryo-electron tomography software integration, reproducibility, and validation. J Struct Biol 2022; 214:107872. [PMID: 35660516 PMCID: PMC7613607 DOI: 10.1016/j.jsb.2022.107872] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 05/26/2022] [Accepted: 05/28/2022] [Indexed: 11/25/2022]
Abstract
Image processing in cryogenic electron tomography (cryoET) is currently at a similar state as Single Particle Analysis (SPA) in cryogenic electron microscopy (cryoEM) was a few years ago. Its data processing workflows are far from being well defined and the user experience is still not smooth. Moreover, file formats of different software packages and their associated metadata are not standardized, mainly since different packages are developed by different groups, focusing on different steps of the data processing pipeline. The Scipion framework, originally developed for SPA (de la Rosa-Trevín et al., 2016), has a generic python workflow engine that gives it the versatility to be extended to other fields, as demonstrated for model building (Martínez et al., 2020). In this article, we provide an extension of Scipion based on a set of tomography plugins (referred to as ScipionTomo hereafter), with a similar purpose: to allow users to be focused on the data processing and analysis instead of having to deal with multiple software installation issues and the inconvenience of switching from one to another, converting metadata files, managing possible incompatibilities, scripting (writing a simple program in a language that the computer must convert to machine language each time the program is run), etcetera. Additionally, having all the software available in an integrated platform allows comparing the results of different algorithms trying to solve the same problem. In this way, the commonalities and differences between estimated parameters shed light on which results can be more trusted than others. ScipionTomo is developed by a collaborative multidisciplinary team composed of Scipion team engineers, structural biologists, and in some cases, the developers whose software packages have been integrated. It is open to anyone in the field willing to contribute to this project. The result is a framework extension that combines the acquired knowledge of Scipion developers in close collaboration with third-party developers, and the on-demand design of functionalities requested by beta testers applying this solution to actual biological problems.
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Affiliation(s)
| | - P Conesa
- National Center of Biotechnology (CNB-CSIC), Madrid, Spain
| | - Y C Fonseca
- National Center of Biotechnology (CNB-CSIC), Madrid, Spain
| | | | - D Herreros
- National Center of Biotechnology (CNB-CSIC), Madrid, Spain
| | | | - D Strelak
- National Center of Biotechnology (CNB-CSIC), Madrid, Spain; Masaryk University, Brno, Czech Republic
| | - E Moebel
- Inria Rennes - Bretagne Atlantique, Rennes
| | - T O Buchholz
- Max Planck Institute of Molecular Cell Biology and Genetics (MPI-CBG), Germany; Center for Systems Biology Dresden (CSBD), Germany
| | - F Jug
- Max Planck Institute of Molecular Cell Biology and Genetics (MPI-CBG), Germany; Fondazione Human Technopole, Milan, Italy
| | - A Martinez-Sanchez
- University of Oviedo, Department of Computer Sciences, Oviedo, Spain; Health Research Institute of Asturias (ISPA), Oviedo, Spain
| | - M Harastani
- IMPMC-UMR 7590 CNRS, Sorbonne Université, MNHN, Paris, France
| | - S Jonic
- IMPMC-UMR 7590 CNRS, Sorbonne Université, MNHN, Paris, France
| | - J J Conesa
- National Center of Biotechnology (CNB-CSIC), Madrid, Spain
| | - A Cuervo
- National Center of Biotechnology (CNB-CSIC), Madrid, Spain
| | - P Losana
- National Center of Biotechnology (CNB-CSIC), Madrid, Spain
| | - I Sánchez
- National Center of Biotechnology (CNB-CSIC), Madrid, Spain
| | - M Iceta
- National Center of Biotechnology (CNB-CSIC), Madrid, Spain
| | - L Del Cano
- National Center of Biotechnology (CNB-CSIC), Madrid, Spain
| | - M Gragera
- National Center of Biotechnology (CNB-CSIC), Madrid, Spain
| | - R Melero
- National Center of Biotechnology (CNB-CSIC), Madrid, Spain
| | - G Sharov
- Structural Studies Division, MRC Laboratory of Molecular Biology, Cambridge, United Kingdom
| | - D Castaño-Díez
- BioEM Lab, Biozentrum, University of Basel, Basel, Switzerland
| | - A Koster
- University of Leiden, Ultrastructural and molecular imaging, Leiden, The Netherlands
| | - J G Piccirillo
- National Center of Biotechnology (CNB-CSIC), Madrid, Spain
| | - J L Vilas
- National Center of Biotechnology (CNB-CSIC), Madrid, Spain
| | - J Otón
- Alba Synchrotron - CELLS (ICTS), Barcelona, Spain
| | - R Marabini
- National Center of Biotechnology (CNB-CSIC), Madrid, Spain; Superior Polytechnic School. Univ. Autónoma of Madrid. Madrid, Spain
| | - C O S Sorzano
- National Center of Biotechnology (CNB-CSIC), Madrid, Spain
| | - J M Carazo
- National Center of Biotechnology (CNB-CSIC), Madrid, Spain
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18
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Cayuela López A, Gómez-Pedrero JA, Blanco AMO, Sorzano COS. Cell-TypeAnalyzer: A flexible Fiji/ImageJ plugin to classify cells according to user-defined criteria. Biol Imaging 2022; 2:e5. [PMID: 38510432 PMCID: PMC10951792 DOI: 10.1017/s2633903x22000058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 04/06/2022] [Accepted: 05/08/2022] [Indexed: 03/22/2024]
Abstract
Fluorescence microscopy techniques have experienced a substantial increase in the visualization and analysis of many biological processes in life science. We describe a semiautomated and versatile tool called Cell-TypeAnalyzer to avoid the time-consuming and biased manual classification of cells according to cell types. It consists of an open-source plugin for Fiji or ImageJ to detect and classify cells in 2D images. Our workflow consists of (a) image preprocessing actions, data spatial calibration, and region of interest for analysis; (b) segmentation to isolate cells from background (optionally including user-defined preprocessing steps helping the identification of cells); (c) extraction of features from each cell; (d) filters to select relevant cells; (e) definition of specific criteria to be included in the different cell types; (f) cell classification; and (g) flexible analysis of the results. Our software provides a modular and flexible strategy to perform cell classification through a wizard-like graphical user interface in which the user is intuitively guided through each step of the analysis. This procedure may be applied in batch mode to multiple microscopy files. Once the analysis is set up, it can be automatically and efficiently performed on many images. The plugin does not require any programming skill and can analyze cells in many different acquisition setups.
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Affiliation(s)
| | - José A. Gómez-Pedrero
- Applied Optics Complutense Group, Faculty of Optics and Optometry, University Complutense of Madrid, Madrid, Spain
| | - Ana M. O. Blanco
- Advanced Light Microscopy Unit, National Centre for Biotechnology, Madrid, Spain
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19
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Sorzano COS, Carazo JM. Cryo-Electron Microscopy: the field of 1,000 + methods. J Struct Biol 2022; 214:107861. [PMID: 35568276 DOI: 10.1016/j.jsb.2022.107861] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Revised: 03/21/2022] [Accepted: 04/21/2022] [Indexed: 01/18/2023]
Abstract
Cryo-Electron Microscopy (CryoEM) is currently a well-established method to elucidate a biological macromolecule's three-dimensional (3D) structure. Its success is due to technological and methodological advances in several fronts: sample preparation, electron optics and detection, image acquisition, image processing, and map interpretation. The first methods started in the late 1960s and, since then, new methods on all fronts have continuously been published, maturating the field as we know it now. In terms of publications, we can distinguish several periods, witnessing a substantial acceleration of methodological publications in recent years, pointing out to an increased interest in the domain. On the other hand, this accelerated increase of methods development may confuse practitioners about which method they should be using (and how) and highlight the importance of paying attention to establishing best practices for methods reporting and usage. In this paper, we analyze the trends identified in over 1,000 methodological papers. Our focus is primarily on computational image processing methods. However, our list also covers some aspects of sample preparation and image acquisition. Several interesting ideas stem out from this study: 1) Single Particle Analysis (SPA) has largely accelerated in the last decade and sample preparation methods in the last five years; 2) Electron Tomography is not yet in a rapidly growing phase, but it is foreseeable that it will soon be; 3) the work horses of SPA are 3D classification, 3D reconstruction, and 3D alignment, and there have been many papers on these topics, which are not considered to be solved yet, but ever improving; and 4) since the resolution revolution, atomic modelling has also caught on as a hot topic.
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Affiliation(s)
- C O S Sorzano
- Natl. Center of Biotechnology, CSIC. c/Darwin, 3. Campus Univ. Autónoma de Madrid. 28049 Madrid, Spain
| | - J M Carazo
- Natl. Center of Biotechnology, CSIC. c/Darwin, 3. Campus Univ. Autónoma de Madrid. 28049 Madrid, Spain
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20
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Krieger JM, Sorzano COS, Carazo JM, Bahar I. Protein dynamics developments for the large scale and cryoEM: case study of ProDy 2.0. Acta Crystallogr D Struct Biol 2022; 78:399-409. [PMID: 35362464 PMCID: PMC8972803 DOI: 10.1107/s2059798322001966] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 02/18/2022] [Indexed: 11/24/2022]
Abstract
New computational biophysics pipelines for analysing the global dynamics of structural ensembles and large, dynamic complexes resolved by cryoEM are reviewed. Cryo-electron microscopy (cryoEM) has become a well established technique with the potential to produce structures of large and dynamic supramolecular complexes that are not amenable to traditional approaches for studying structure and dynamics. The size and low resolution of such molecular systems often make structural modelling and molecular dynamics simulations challenging and computationally expensive. This, together with the growing wealth of structural data arising from cryoEM and other structural biology methods, has driven a trend in the computational biophysics community towards the development of new pipelines for analysing global dynamics using coarse-grained models and methods. At the centre of this trend has been a return to elastic network models, normal mode analysis (NMA) and ensemble analyses such as principal component analysis, and the growth of hybrid simulation methodologies that make use of them. Here, this field is reviewed with a focus on ProDy, the Python application programming interface for protein dynamics, which has been developed over the last decade. Two key developments in this area are highlighted: (i) ensemble NMA towards extracting and comparing the signature dynamics of homologous structures, aided by the recent SignDy pipeline, and (ii) pseudoatom fitting for more efficient global dynamics analyses of large and low-resolution supramolecular assemblies from cryoEM, revisited in the CryoDy pipeline. It is believed that such a renewal and extension of old models and methods in new pipelines will be critical for driving the field forward into the next cryoEM revolution.
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21
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Varadi M, Anyango S, Armstrong D, Berrisford J, Choudhary P, Deshpande M, Nadzirin N, Nair SS, Pravda L, Tanweer A, Al-Lazikani B, Andreini C, Barton GJ, Bednar D, Berka K, Blundell T, Brock KP, Carazo JM, Damborsky J, David A, Dey S, Dunbrack R, Recio JF, Fraternali F, Gibson T, Helmer-Citterich M, Hoksza D, Hopf T, Jakubec D, Kannan N, Krivak R, Kumar M, Levy ED, London N, Macias JR, Srivatsan MM, Marks DS, Martens L, McGowan SA, McGreig JE, Modi V, Parra RG, Pepe G, Piovesan D, Prilusky J, Putignano V, Radusky LG, Ramasamy P, Rausch AO, Reuter N, Rodriguez LA, Rollins NJ, Rosato A, Rubach P, Serrano L, Singh G, Skoda P, Sorzano COS, Stourac J, Sulkowska JI, Svobodova R, Tichshenko N, Tosatto SCE, Vranken W, Wass MN, Xue D, Zaidman D, Thornton J, Sternberg M, Orengo C, Velankar S. PDBe-KB: collaboratively defining the biological context of structural data. Nucleic Acids Res 2022; 50:D534-D542. [PMID: 34755867 PMCID: PMC8728252 DOI: 10.1093/nar/gkab988] [Citation(s) in RCA: 36] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 10/01/2021] [Accepted: 10/14/2021] [Indexed: 12/15/2022] Open
Abstract
The Protein Data Bank in Europe - Knowledge Base (PDBe-KB, https://pdbe-kb.org) is an open collaboration between world-leading specialist data resources contributing functional and biophysical annotations derived from or relevant to the Protein Data Bank (PDB). The goal of PDBe-KB is to place macromolecular structure data in their biological context by developing standardised data exchange formats and integrating functional annotations from the contributing partner resources into a knowledge graph that can provide valuable biological insights. Since we described PDBe-KB in 2019, there have been significant improvements in the variety of available annotation data sets and user functionality. Here, we provide an overview of the consortium, highlighting the addition of annotations such as predicted covalent binders, phosphorylation sites, effects of mutations on the protein structure and energetic local frustration. In addition, we describe a library of reusable web-based visualisation components and introduce new features such as a bulk download data service and a novel superposition service that generates clusters of superposed protein chains weekly for the whole PDB archive.
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22
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Cuesta-Geijo MÁ, García-Dorival I, del Puerto A, Urquiza J, Galindo I, Barrado-Gil L, Lasala F, Cayuela A, Sorzano COS, Gil C, Delgado R, Alonso C. New insights into the role of endosomal proteins for African swine fever virus infection. PLoS Pathog 2022; 18:e1009784. [PMID: 35081156 PMCID: PMC8820605 DOI: 10.1371/journal.ppat.1009784] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 02/07/2022] [Accepted: 01/11/2022] [Indexed: 01/01/2023] Open
Abstract
African swine fever virus (ASFV) infectious cycle starts with the viral adsorption and entry into the host cell. Then, the virus is internalized via clathrin/dynamin mediated endocytosis and macropinocytosis. Similar to other viruses, ASF virion is then internalized and incorporated into the endocytic pathway. While the endosomal maturation entails luminal acidification, the decrease in pH acts on the multilayer structure of the virion dissolving the outer capsid. Upon decapsidation, the inner viral membrane is exposed to interact with the limiting membrane of the late endosome for fusion. Viral fusion is then necessary for the egress of incoming virions from endosomes into the cytoplasm, however this remains an intriguing and yet essential process for infection, specifically for the egress of viral nucleic acid into the cytoplasm for replication. ASFV proteins E248R and E199L, located at the exposed inner viral membrane, might be implicated in the fusion step. An interaction between these viral proteins and cellular endosomal proteins such as the Niemann-Pick C type 1 (NPC1) and lysosomal membrane proteins (Lamp-1 and -2) was shown. Furthermore, the silencing of these proteins impaired ASFV infection. It was also observed that NPC1 knock-out cells using CRISPR jeopardized ASFV infection and that the progression and endosomal exit of viral cores was arrested within endosomes at viral entry. These results suggest that the interactions of ASFV proteins with some endosomal proteins might be important for the membrane fusion step. In addition to this, reductions on ASFV infectivity and replication in NPC1 KO cells were accompanied by fewer and smaller viral factories. Our findings pave the way to understanding the role of proteins of the endosomal membrane in ASFV infection. African swine fever virus (ASFV) causes a deadly disease of pigs and wild boars that was endemic in Africa but has spread in recent years to Europe, Asia and Oceania with a high socioeconomic impact. ASFV enters the cell by endocytosis and has adapted to the endosomal conditions to acquire infectivity. Fusion of the internal viral membrane with the endosomal membrane is required for the exit of viral DNA into the cytoplasm to start replication. We have found that ASF virion internal membrane proteins E248R and E199L interact with the endosomal proteins Niemann Pick C1 (NPC1) and lysosomal membrane proteins (Lamp)-1 and -2. And, appear to be required for endosomal trafficking of ASF virions endosomal traffic and exit to the cytoplasm in the cell entry process. These molecules act regulating cholesterol flux from the endosome to the endoplasmic reticulum, and appear to be important for the viral infection cycle. In silenced and knockout cells, ASFV infection was affected at early and later stages. In null cells, virion entry and progression through the endosomal pathway at entry was arrested and several viral cores were retained at late endosomes without entering the fusion phase for cytoplasmic exit. These results provide new insights into the role of endosomal proteins for ASFV infection.
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Affiliation(s)
- Miguel Ángel Cuesta-Geijo
- Departmento de Biotecnología, INIA-CSIC, Centro Nacional Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, Madrid, Spain
| | - Isabel García-Dorival
- Departmento de Biotecnología, INIA-CSIC, Centro Nacional Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, Madrid, Spain
| | - Ana del Puerto
- Departmento de Biotecnología, INIA-CSIC, Centro Nacional Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, Madrid, Spain
| | - Jesús Urquiza
- Departmento de Biotecnología, INIA-CSIC, Centro Nacional Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, Madrid, Spain
| | - Inmaculada Galindo
- Departmento de Biotecnología, INIA-CSIC, Centro Nacional Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, Madrid, Spain
| | - Lucía Barrado-Gil
- Departmento de Biotecnología, INIA-CSIC, Centro Nacional Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, Madrid, Spain
| | - Fátima Lasala
- Instituto de Investigación Hospital 12 de Octubre Imas12, Madrid, Spain
| | - Ana Cayuela
- Centro Nacional de Biotecnología CSIC, Madrid, Spain
| | | | - Carmen Gil
- Centro de Investigaciones Biológicas Margarita Salas CSIC, Madrid, Spain
| | - Rafael Delgado
- Instituto de Investigación Hospital 12 de Octubre Imas12, Madrid, Spain
- Facultad de Medicina, Universidad Complutense de Madrid, Madrid, Spain
| | - Covadonga Alonso
- Departmento de Biotecnología, INIA-CSIC, Centro Nacional Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, Madrid, Spain
- * E-mail:
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23
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Ramírez-Aportela E, Maluenda D, Fonseca YC, Conesa P, Marabini R, Sorzano COS, Carazo JM. FSC-Q: a method for quality analysis of cryoEM-derived models. Acta Crystallogr A Found Adv 2021. [DOI: 10.1107/s0108767321096215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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24
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Sorzano COS, Jiménez-Moreno A, Maluenda D, Ramírez-Aportela E, Martínez M, Cuervo A, Melero R, Conesa JJ, Sánchez-García R, Strelak D, Filipovic J, Fernández-Giménez E, de Isidro-Gómez F, Herreros D, Conesa P, Del Caño L, Fonseca Y, de la Morena JJ, Macías JR, Losana P, Marabini R, Carazo JM. Image Processing in Cryo-Electron Microscopy of Single Particles: The Power of Combining Methods. Methods Mol Biol 2021; 2305:257-289. [PMID: 33950394 DOI: 10.1007/978-1-0716-1406-8_13] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Cryo-electron microscopy has established as a mature structural biology technique to elucidate the three-dimensional structure of biological macromolecules. The Coulomb potential of the sample is imaged by an electron beam, and fast semi-conductor detectors produce movies of the sample under study. These movies have to be further processed by a whole pipeline of image-processing algorithms that produce the final structure of the macromolecule. In this chapter, we illustrate this whole processing pipeline putting in value the strength of "meta algorithms," which are the combination of several algorithms, each one with different mathematical rationale, in order to distinguish correctly from incorrectly estimated parameters. We show how this strategy leads to superior performance of the whole pipeline as well as more confident assessments about the reconstructed structures. The "meta algorithms" strategy is common to many fields and, in particular, it has provided excellent results in bioinformatics. We illustrate this combination using the workflow engine, Scipion.
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Affiliation(s)
| | | | | | | | | | - Ana Cuervo
- National Centre for Biotechnology (CSIC), Madrid, Spain
| | - Robert Melero
- National Centre for Biotechnology (CSIC), Madrid, Spain
| | | | | | - David Strelak
- National Centre for Biotechnology (CSIC), Madrid, Spain
| | | | | | | | | | - Pablo Conesa
- National Centre for Biotechnology (CSIC), Madrid, Spain
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25
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Méndez J, Garduño E, Carazo JM, S Sorzano CO. Identification of incorrectly oriented particles in cryo-EM single particle analysis. J Struct Biol 2021; 213:107771. [PMID: 34324977 DOI: 10.1016/j.jsb.2021.107771] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 06/23/2021] [Accepted: 07/18/2021] [Indexed: 11/24/2022]
Abstract
The quality of a 3D map produced by the single-particle analysis method is highly dependent on an accurate assignment of orientations to the many experimental images. However, the problem's complexity implies the presence of several local minima in the optimized goal functions. Consequently, validation methods to confirm the angular assignment are very useful to yield higher-resolution 3D maps. In this work, we present a graph-signal-processing-based methodology that analyzes the correlation landscape as a function of the orientation, an approach allowing the estimation of the assigned orientations' reliability. Using this method, we may identify low-reliability images that probably incorrectly contribute to the final 3D reconstruction.
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Affiliation(s)
- Jeison Méndez
- Posgrado en Ingeniería Eléctrica, Universidad Nacional Autónoma de México, Cd.Universitaria, C.P.04510, Mexico City, Mexico.
| | - Edgar Garduño
- Department of Computer Science, Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico.
| | - José María Carazo
- National Center of Biotechnology, CSIC, Campus Univ. Autónoma de Madrid, 28049 Cantoblanco, Madrid, Spain.
| | - Carlos Oscar S Sorzano
- Univ. San Pablo CEU, Campus Urb. Montepríncipe s/n, 28668, Boadilla del Monte, Madrid, Spain; National Center of Biotechnology, CSIC, Campus Univ. Autónoma de Madrid, 28049 Cantoblanco, Madrid, Spain.
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26
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Abstract
Principal component analysis (PCA) has been widely proposed to analyze flexibility and heterogeneity in cryo-electron microscopy (cryoEM). In this paper, it is argued that (i) PCA is an excellent technique to describe continuous flexibility at low resolution (but not so much at high resolution) and (ii) PCA components should be analyzed in a concerted manner (and not independently).
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Affiliation(s)
- Carlos Oscar S. Sorzano
- National Center of Biotechnology (CSIC), Darwin 3, Campus Universidad Autónoma de Madrid, Cantoblanco, 28049 Madrid, Spain
| | - Jose Maria Carazo
- National Center of Biotechnology (CSIC), Darwin 3, Campus Universidad Autónoma de Madrid, Cantoblanco, 28049 Madrid, Spain
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27
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Jiménez-Moreno A, Del Caño L, Martínez M, Ramírez-Aportela E, Cuervo A, Melero R, Sánchez-García R, Strelak D, Fernández-Giménez E, de Isidro-Gómez FP, Herreros D, Conesa P, Fonseca Y, Maluenda D, Jiménez de la Morena J, Macías JR, Losana P, Marabini R, Carazo JM, Sorzano COS. Cryo-EM and Single-Particle Analysis with Scipion. J Vis Exp 2021. [PMID: 34125107 DOI: 10.3791/62261] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2022] Open
Abstract
Cryo-electron microscopy has become one of the most important tools in biological research to reveal the structural information of macromolecules at near-atomic resolution. In single-particle analysis, the vitrified sample is imaged by an electron beam and the detectors at the end of the microscope column produce movies of that sample. These movies contain thousands of images of identical particles in random orientations. The data need to go through an image processing workflow with multiple steps to obtain the final 3D reconstructed volume. The goal of the image processing workflow is to identify the acquisition parameters to be able to reconstruct the specimen under study. Scipion provides all the tools to create this workflow using several image processing packages in an integrative framework, also allowing the traceability of the results. In this article the whole image processing workflow in Scipion is presented and discussed with data coming from a real test case, giving all the details necessary to go from the movies obtained by the microscope to a high resolution final 3D reconstruction. Also, the power of using consensus tools that allow combining methods, and confirming results along every step of the workflow, improving the accuracy of the obtained results, is discussed.
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Affiliation(s)
- A Jiménez-Moreno
- Centro Nacional de Biotecnología, Campus Universidad Autónoma de Madrid
| | - L Del Caño
- Centro Nacional de Biotecnología, Campus Universidad Autónoma de Madrid
| | - M Martínez
- Centro Nacional de Biotecnología, Campus Universidad Autónoma de Madrid
| | | | - A Cuervo
- Centro Nacional de Biotecnología, Campus Universidad Autónoma de Madrid
| | - R Melero
- Centro Nacional de Biotecnología, Campus Universidad Autónoma de Madrid
| | - R Sánchez-García
- Centro Nacional de Biotecnología, Campus Universidad Autónoma de Madrid
| | - D Strelak
- Centro Nacional de Biotecnología, Campus Universidad Autónoma de Madrid; Faculty of Informatics, Masaryk University; Institute of Computer Science, Masaryk University
| | | | | | - D Herreros
- Centro Nacional de Biotecnología, Campus Universidad Autónoma de Madrid
| | - P Conesa
- Centro Nacional de Biotecnología, Campus Universidad Autónoma de Madrid
| | - Y Fonseca
- Centro Nacional de Biotecnología, Campus Universidad Autónoma de Madrid
| | - D Maluenda
- Centro Nacional de Biotecnología, Campus Universidad Autónoma de Madrid;
| | | | - J R Macías
- Centro Nacional de Biotecnología, Campus Universidad Autónoma de Madrid
| | - P Losana
- Centro Nacional de Biotecnología, Campus Universidad Autónoma de Madrid
| | - R Marabini
- Centro Nacional de Biotecnología, Campus Universidad Autónoma de Madrid
| | - J M Carazo
- Centro Nacional de Biotecnología, Campus Universidad Autónoma de Madrid
| | - C O S Sorzano
- Centro Nacional de Biotecnología, Campus Universidad Autónoma de Madrid; Campus Urbanización Montepríncipe, Universidad San Pablo CEU
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28
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Di Pilato M, Palomino-Segura M, Mejías-Pérez E, Gómez CE, Rubio-Ponce A, D'Antuono R, Pizzagalli DU, Pérez P, Kfuri-Rubens R, Benguría A, Dopazo A, Ballesteros I, Sorzano COS, Hidalgo A, Esteban M, Gonzalez SF. Neutrophil subtypes shape HIV-specific CD8 T-cell responses after vaccinia virus infection. NPJ Vaccines 2021; 6:52. [PMID: 33846352 PMCID: PMC8041892 DOI: 10.1038/s41541-021-00314-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Accepted: 03/09/2021] [Indexed: 12/20/2022] Open
Abstract
Neutrophils are innate immune cells involved in the elimination of pathogens and can also induce adaptive immune responses. Nα and Nβ neutrophils have been described with distinct in vitro capacity to generate antigen-specific CD8 T-cell responses. However, how these cell types exert their role in vivo and how manipulation of Nβ/Nα ratio influences vaccine-mediated immune responses are not known. In this study, we find that these neutrophil subtypes show distinct migratory and motility patterns and different ability to interact with CD8 T cells in the spleen following vaccinia virus (VACV) infection. Moreover, after analysis of adhesion, inflammatory, and migration markers, we observe that Nβ neutrophils overexpress the α4β1 integrin compared to Nα. Finally, by inhibiting α4β1 integrin, we increase the Nβ/Nα ratio and enhance CD8 T-cell responses to HIV VACV-delivered antigens. These findings provide significant advancements in the comprehension of neutrophil-based control of adaptive immune system and their relevance in vaccine design.
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Affiliation(s)
- Mauro Di Pilato
- Institute for Research in Biomedicine, Università della Svizzera Italiana, Bellinzona, Switzerland. .,Department of Molecular and Cellular Biology, Centro Nacional de Biotecnología-CSIC, Madrid, Spain. .,Center for Immunology and Inflammatory Diseases, Massachusetts General Hospital, Boston, MA, USA. .,Harvard Medical School, Boston, MA, USA. .,Department of Immunology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
| | - Miguel Palomino-Segura
- Institute for Research in Biomedicine, Università della Svizzera Italiana, Bellinzona, Switzerland.,Area of Cell & Developmental Biology, Centro Nacional de Investigaciones Cardiovasculares, Madrid, Spain
| | - Ernesto Mejías-Pérez
- Department of Molecular and Cellular Biology, Centro Nacional de Biotecnología-CSIC, Madrid, Spain.,Max von Pettenkofer-Institute, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Carmen E Gómez
- Department of Molecular and Cellular Biology, Centro Nacional de Biotecnología-CSIC, Madrid, Spain
| | - Andrea Rubio-Ponce
- Area of Cell & Developmental Biology, Centro Nacional de Investigaciones Cardiovasculares, Madrid, Spain.,Bioinformatics Unit, Centro Nacional de Investigaciones Cardiovasculares, Madrid, Spain
| | - Rocco D'Antuono
- Institute for Research in Biomedicine, Università della Svizzera Italiana, Bellinzona, Switzerland.,Crick Advanced Light Microscopy Science and Technology Platform, The Francis Crick Institute, London, United Kingdom
| | - Diego Ulisse Pizzagalli
- Institute for Research in Biomedicine, Università della Svizzera Italiana, Bellinzona, Switzerland.,Institute of Computational Science, Università della Svizzera Italiana, Lugano, Switzerland
| | - Patricia Pérez
- Institute for Research in Biomedicine, Università della Svizzera Italiana, Bellinzona, Switzerland.,Department of Molecular and Cellular Biology, Centro Nacional de Biotecnología-CSIC, Madrid, Spain
| | - Raphael Kfuri-Rubens
- Center of Integrated Protein Science Munich and Division of Clinical Pharmacology, Klinikum der Universität München, Munich, Germany
| | - Alberto Benguría
- Genomics Unit, Centro Nacional de Investigaciones Cardiovasculares, Madrid, Spain
| | - Ana Dopazo
- Genomics Unit, Centro Nacional de Investigaciones Cardiovasculares, Madrid, Spain
| | - Iván Ballesteros
- Area of Cell & Developmental Biology, Centro Nacional de Investigaciones Cardiovasculares, Madrid, Spain
| | - Carlos Oscar S Sorzano
- Department of Molecular and Cellular Biology, Centro Nacional de Biotecnología-CSIC, Madrid, Spain
| | - Andrés Hidalgo
- Area of Cell & Developmental Biology, Centro Nacional de Investigaciones Cardiovasculares, Madrid, Spain
| | - Mariano Esteban
- Department of Molecular and Cellular Biology, Centro Nacional de Biotecnología-CSIC, Madrid, Spain.
| | - Santiago F Gonzalez
- Institute for Research in Biomedicine, Università della Svizzera Italiana, Bellinzona, Switzerland.
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29
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Jiménez-Moreno A, Střelák D, Filipovič J, Carazo JM, Sorzano COS. DeepAlign, a 3D alignment method based on regionalized deep learning for Cryo-EM. J Struct Biol 2021; 213:107712. [PMID: 33676034 DOI: 10.1016/j.jsb.2021.107712] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Revised: 02/02/2021] [Accepted: 02/21/2021] [Indexed: 02/02/2023]
Abstract
Cryo Electron Microscopy (Cryo-EM) is currently one of the main tools to reveal the structural information of biological specimens at high resolution. Despite the great development of the techniques involved to solve the biological structures with Cryo-EM in the last years, the reconstructed 3D maps can present lower resolution due to errors committed while processing the information acquired by the microscope. One of the main problems comes from the 3D alignment step, which is an error-prone part of the reconstruction workflow due to the very low signal-to-noise ratio (SNR) common in Cryo-EM imaging. In fact, as we will show in this work, it is not unusual to find a disagreement in the alignment parameters in approximately 20-40% of the processed images, when outputs of different alignment algorithms are compared. In this work, we present a novel method to align sets of single particle images in the 3D space, called DeepAlign. Our proposal is based on deep learning networks that have been successfully used in plenty of problems in image classification. Specifically, we propose to design several deep neural networks on a regionalized basis to classify the particle images in sub-regions and, then, make a refinement of the 3D alignment parameters only inside that sub-region. We show that this method results in accurately aligned images, improving the Fourier shell correlation (FSC) resolution obtained with other state-of-the-art methods while decreasing computational time.
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Affiliation(s)
- A Jiménez-Moreno
- Centro Nac. Biotecnología (CSIC), c/Darwin, 3, 28049 Cantoblanco, Madrid, Spain
| | - D Střelák
- Centro Nac. Biotecnología (CSIC), c/Darwin, 3, 28049 Cantoblanco, Madrid, Spain; Faculty of Informatics, Masaryk University, Botanická 68a, 662 00 Brno, Czech Republic; Institute of Computer Science, Masaryk University, Botanická 68a, 60200 Brno, Czech Republic
| | - J Filipovič
- Institute of Computer Science, Masaryk University, Botanická 68a, 60200 Brno, Czech Republic
| | - J M Carazo
- Centro Nac. Biotecnología (CSIC), c/Darwin, 3, 28049 Cantoblanco, Madrid, Spain.
| | - C O S Sorzano
- Centro Nac. Biotecnología (CSIC), c/Darwin, 3, 28049 Cantoblanco, Madrid, Spain; Univ. San Pablo - CEU, Campus Urb. Montepríncipe, 28668 Boadilla del Monte, Madrid, Spain.
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30
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Zhang Y, Krieger J, Mikulska-Ruminska K, Kaynak B, Sorzano COS, Carazo JM, Xing J, Bahar I. State-dependent sequential allostery exhibited by chaperonin TRiC/CCT revealed by network analysis of Cryo-EM maps. Prog Biophys Mol Biol 2021; 160:104-120. [PMID: 32866476 PMCID: PMC7914283 DOI: 10.1016/j.pbiomolbio.2020.08.006] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Revised: 06/25/2020] [Accepted: 08/16/2020] [Indexed: 12/17/2022]
Abstract
The eukaryotic chaperonin TRiC/CCT plays a major role in assisting the folding of many proteins through an ATP-driven allosteric cycle. Recent structures elucidated by cryo-electron microscopy provide a broad view of the conformations visited at various stages of the chaperonin cycle, including a sequential activation of its subunits in response to nucleotide binding. But we lack a thorough mechanistic understanding of the structure-based dynamics and communication properties that underlie the TRiC/CCT machinery. In this study, we present a computational methodology based on elastic network models adapted to cryo-EM density maps to gain a deeper understanding of the structure-encoded allosteric dynamics of this hexadecameric machine. We have analysed several structures of the chaperonin resolved in different states toward mapping its conformational landscape. Our study indicates that the overall architecture intrinsically favours cooperative movements that comply with the structural variabilities observed in experiments. Furthermore, the individual subunits CCT1-CCT8 exhibit state-dependent sequential events at different states of the allosteric cycle. For example, in the ATP-bound state, subunits CCT5 and CCT4 selectively initiate the lid closure motions favoured by the overall architecture; whereas in the apo form of the heteromer, the subunit CCT7 exhibits the highest predisposition to structural change. The changes then propagate through parallel fluxes of allosteric signals to neighbours on both rings. The predicted state-dependent mechanisms of sequential activation provide new insights into TRiC/CCT intra- and inter-ring signal transduction events.
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Affiliation(s)
- Yan Zhang
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA, 15261, USA
| | - James Krieger
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA, 15261, USA
| | - Karolina Mikulska-Ruminska
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA, 15261, USA
| | - Burak Kaynak
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA, 15261, USA
| | | | - José-María Carazo
- Centro Nacional de Biotecnología (CSIC), Darwin, 3, 28049, Madrid, Spain
| | - Jianhua Xing
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA, 15261, USA
| | - Ivet Bahar
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA, 15261, USA.
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31
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Kazemi M, Sorzano COS, Carazo JM, Georges AD, Abrishami V, Vargas J. ENRICH: A fast method to improve the quality of flexible macromolecular reconstructions. Prog Biophys Mol Biol 2021; 164:92-100. [PMID: 33450244 DOI: 10.1016/j.pbiomolbio.2021.01.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/16/2020] [Revised: 12/21/2020] [Accepted: 01/04/2021] [Indexed: 11/27/2022]
Abstract
Cryo-electron microscopy using single particle analysis requires the computational averaging of thousands of projection images captured from identical macromolecules. However, macromolecules usually present some degree of flexibility showing different conformations. Computational approaches are then required to classify heterogeneous single particle images into homogeneous sets corresponding to different structural states. Nonetheless, sometimes the attainable resolution of reconstructions obtained from these smaller homogeneous sets is compromised because of reduced number of particles or lack of images at certain macromolecular orientations. In these situations, the current solution to improve map resolution is returning to the electron microscope and collect more data. In this work, we present a fast approach to partially overcome this limitation for heterogeneous data sets. Our method is based on deforming and then moving particles between different conformations using an optical flow approach. Particles are then merged into a unique conformation obtaining reconstructions with improved resolution, contrast and signal-to-noise ratio. We present experimental results that show clear improvements in the quality of obtained 3D maps, however, there are also limits to this approach, i.e., the method is restricted to small deformations and cannot determine local patterns of flexibility of small elements, such as secondary structures, which we discuss in the manuscript.
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Affiliation(s)
- M Kazemi
- Dep. of Biochemistry and Pharmacology and Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Parkville, VIC, 3010, Australia.
| | - C O S Sorzano
- Biocomputing Unit, Centro Nacional de Biotecnología-CSIC, C/ Darwin 3, 28049, Cantoblanco, Madrid, Spain
| | - J M Carazo
- Biocomputing Unit, Centro Nacional de Biotecnología-CSIC, C/ Darwin 3, 28049, Cantoblanco, Madrid, Spain
| | - A des Georges
- Structural Biology Initiative, CUNY Advanced Science Research Center, New York, NY, 10031, USA; Dept. of Chemistry & Biochemistry, City College of New York, New York, NY, 10031, USA; Ph.D. Program in Biochemistry, The Graduate Center of the City University of New York, New York, NY, 10016, USA
| | - V Abrishami
- Laboratory of Structural Biology, Helsinki Institute of Life Science HiLIFE, Finland
| | - J Vargas
- Departamento de Optica, Universidad Complutense de Madrid, Avda. Computense s/n, Ciudad Universitaria, 28040, Madrid, Spain; Department of Anatomy and Cell Biology, McGill University, 3640, Rue University, Montréal, QC, H3A 0C7, Canada.
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Sorzano COS, Semchonok D, Lin SC, Lo YC, Vilas JL, Jiménez-Moreno A, Gragera M, Vacca S, Maluenda D, Martínez M, Ramírez-Aportela E, Melero R, Cuervo A, Conesa JJ, Conesa P, Losana P, Caño LD, de la Morena JJ, Fonseca YC, Sánchez-García R, Strelak D, Fernández-Giménez E, de Isidro F, Herreros D, Kastritis PL, Marabini R, Bruce BD, Carazo JM. Algorithmic robustness to preferred orientations in single particle analysis by CryoEM. J Struct Biol 2021; 213:107695. [PMID: 33421545 DOI: 10.1016/j.jsb.2020.107695] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Revised: 12/18/2020] [Accepted: 12/24/2020] [Indexed: 01/30/2023]
Abstract
The presence of preferred orientations in single particle analysis (SPA) by cryo-Electron Microscopy (cryoEM) is currently one of the hurdles preventing many structural analyses from yielding high-resolution structures. Although the existence of preferred orientations is mostly related to the grid preparation, in this technical note, we show that some image processing algorithms used for angular assignment and three-dimensional (3D) reconstruction are more robust than others to these detrimental conditions. We exemplify this argument with three different data sets in which the presence of preferred orientations hindered achieving a 3D reconstruction without artifacts or, even worse, a 3D reconstruction could never be achieved.
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Affiliation(s)
- C O S Sorzano
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain.
| | - D Semchonok
- ZIK HALOMEM & Institute of Biochemistry and Biotechnology, Martin Luther University Halle-Wittenberg, Biozentrum, Halle (Saale), Germany
| | - S-C Lin
- Genomics Research Center, Academia Sinica, Taipei 11529, Taiwan
| | - Y-C Lo
- Dept. Biotechnology and Bioindustry Sciences, College of Bioscience and Biotechnology, National Cheng Kung University, Tainan 70101, Taiwan
| | - J L Vilas
- Dept. of Biomedical Engineering, Yale University, New Haven, United States
| | - A Jiménez-Moreno
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - M Gragera
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - S Vacca
- Dept. of Biochemistry, Univ. Zurich, Winterthurerstr. 190, CH-8057 Zurich, Switzerland
| | - D Maluenda
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - M Martínez
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - E Ramírez-Aportela
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - R Melero
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - A Cuervo
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - J J Conesa
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - P Conesa
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - P Losana
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - L Del Caño
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - J Jiménez de la Morena
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - Y C Fonseca
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - R Sánchez-García
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - D Strelak
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - E Fernández-Giménez
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - F de Isidro
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - D Herreros
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - P L Kastritis
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - R Marabini
- Escuela Politecnica Superior, Universidad Autónoma de Madrid, 28049 Cantoblanco, Madrid, Spain
| | - B D Bruce
- Dept. Biochemistry & Cellular and Molecular Biology, Univ. Tennessee Knoxville, Knoxville, TN 37996, United States
| | - J M Carazo
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
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Ramírez-Aportela E, Maluenda D, Fonseca YC, Conesa P, Marabini R, Heymann JB, Carazo JM, Sorzano COS. FSC-Q: a CryoEM map-to-atomic model quality validation based on the local Fourier shell correlation. Nat Commun 2021; 12:42. [PMID: 33397925 PMCID: PMC7782520 DOI: 10.1038/s41467-020-20295-w] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Accepted: 11/23/2020] [Indexed: 12/17/2022] Open
Abstract
In recent years, advances in cryoEM have dramatically increased the resolution of reconstructions and, with it, the number of solved atomic models. It is widely accepted that the quality of cryoEM maps varies locally; therefore, the evaluation of the maps-derived structural models must be done locally as well. In this article, a method for the local analysis of the map-to-model fit is presented. The algorithm uses a comparison of two local resolution maps. The first is the local FSC (Fourier shell correlation) between the full map and the model, while the second is calculated between the half maps normally used in typical single particle analysis workflows. We call the quality measure "FSC-Q", and it is a quantitative estimation of how much of the model is supported by the signal content of the map. Furthermore, we show that FSC-Q may be helpful to detect overfitting. It can be used to complement other methods, such as the Q-score method that estimates the resolvability of atoms.
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Affiliation(s)
- Erney Ramírez-Aportela
- Biocomputing Unit, National Center for Biotechnology (CSIC), Darwin 3, Campus Univ. Autónoma de Madrid, Cantoblanco, 28049, Madrid, Spain.
| | - David Maluenda
- Biocomputing Unit, National Center for Biotechnology (CSIC), Darwin 3, Campus Univ. Autónoma de Madrid, Cantoblanco, 28049, Madrid, Spain
| | - Yunior C Fonseca
- Biocomputing Unit, National Center for Biotechnology (CSIC), Darwin 3, Campus Univ. Autónoma de Madrid, Cantoblanco, 28049, Madrid, Spain
| | - Pablo Conesa
- Biocomputing Unit, National Center for Biotechnology (CSIC), Darwin 3, Campus Univ. Autónoma de Madrid, Cantoblanco, 28049, Madrid, Spain
| | - Roberto Marabini
- Univ. Autónoma de Madrid, Campus Univ. Autónoma de Madrid, Cantoblanco, 28049, Madrid, Spain
| | - J Bernard Heymann
- Laboratory of Structural Biology Research, NIAMS, NIH, Bethesda, MD, USA
| | - Jose Maria Carazo
- Biocomputing Unit, National Center for Biotechnology (CSIC), Darwin 3, Campus Univ. Autónoma de Madrid, Cantoblanco, 28049, Madrid, Spain.
| | - Carlos Oscar S Sorzano
- Biocomputing Unit, National Center for Biotechnology (CSIC), Darwin 3, Campus Univ. Autónoma de Madrid, Cantoblanco, 28049, Madrid, Spain. .,Univ. CEU San Pablo, Campus Urb. Montepríncipe, Boadilla del Monte, 28668, Madrid, Spain.
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34
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Melero R, Sorzano COS, Foster B, Vilas JL, Martínez M, Marabini R, Ramírez-Aportela E, Sanchez-Garcia R, Herreros D, del Caño L, Losana P, Fonseca-Reyna YC, Conesa P, Wrapp D, Chacon P, McLellan JS, Tagare HD, Carazo JM. Continuous flexibility analysis of SARS-CoV-2 spike prefusion structures. IUCrJ 2020; 7:S2052252520012725. [PMID: 33063791 PMCID: PMC7553147 DOI: 10.1107/s2052252520012725] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Accepted: 09/18/2020] [Indexed: 05/09/2023]
Abstract
Using a new consensus-based image-processing approach together with principal component analysis, the flexibility and conformational dynamics of the SARS-CoV-2 spike in the prefusion state have been analysed. These studies revealed concerted motions involving the receptor-binding domain (RBD), N-terminal domain, and subdomains 1 and 2 around the previously characterized 1-RBD-up state, which have been modeled as elastic deformations. It is shown that in this data set there are not well defined, stable spike conformations, but virtually a continuum of states. An ensemble map was obtained with minimum bias, from which the extremes of the change along the direction of maximal variance were modeled by flexible fitting. The results provide a warning of the potential image-processing classification instability of these complicated data sets, which has a direct impact on the interpretability of the results.
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Affiliation(s)
- Roberto Melero
- Centro Nacional de Biotecnologia–CSIC, Calle Darwin 3, 28049 Cantoblanco, Madrid, Spain
| | | | - Brent Foster
- Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT 06520, USA
| | - José-Luis Vilas
- Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT 06520, USA
| | - Marta Martínez
- Centro Nacional de Biotecnologia–CSIC, Calle Darwin 3, 28049 Cantoblanco, Madrid, Spain
| | - Roberto Marabini
- Centro Nacional de Biotecnologia–CSIC, Calle Darwin 3, 28049 Cantoblanco, Madrid, Spain
- Universidad Autónoma de Madrid, Calle Francisco Tomás y Valiente 11, 28049 Cantoblanco, Madrid, Spain
| | | | - Ruben Sanchez-Garcia
- Centro Nacional de Biotecnologia–CSIC, Calle Darwin 3, 28049 Cantoblanco, Madrid, Spain
| | - David Herreros
- Centro Nacional de Biotecnologia–CSIC, Calle Darwin 3, 28049 Cantoblanco, Madrid, Spain
| | - Laura del Caño
- Centro Nacional de Biotecnologia–CSIC, Calle Darwin 3, 28049 Cantoblanco, Madrid, Spain
| | - Patricia Losana
- Centro Nacional de Biotecnologia–CSIC, Calle Darwin 3, 28049 Cantoblanco, Madrid, Spain
| | | | - Pablo Conesa
- Centro Nacional de Biotecnologia–CSIC, Calle Darwin 3, 28049 Cantoblanco, Madrid, Spain
| | - Daniel Wrapp
- Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX 78712, USA
| | - Pablo Chacon
- Department of Biological Physical Chemistry, Instituto Rocasolano–CSIC, Calle de Serrano 119, 28006 Madrid, Spain
| | - Jason S. McLellan
- Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX 78712, USA
| | - Hemant D. Tagare
- Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT 06520, USA
| | - Jose-Maria Carazo
- Centro Nacional de Biotecnologia–CSIC, Calle Darwin 3, 28049 Cantoblanco, Madrid, Spain
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Sorzano COS, de Isidro-Gómez F, Fernández-Giménez E, Herreros D, Marco S, Carazo JM, Messaoudi C. Improvements on marker-free images alignment for electron tomography. J Struct Biol X 2020; 4:100037. [PMID: 33024955 PMCID: PMC7527754 DOI: 10.1016/j.yjsbx.2020.100037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
Abstract
Electron tomography is a technique to obtain three-dimensional structural information of samples. However, the technique is limited by shifts occurring during acquisition that need to be corrected before the reconstruction process. In 2009, we proposed an approach for post-acquisition alignment of tilt series images. This approach was marker-free, based on patch tracking and integrated in free software. Here, we present improvements to the method to make it more reliable, stable and accurate. In addition, we modified the image formation model underlying the alignment procedure to include different deformations occurring during acquisition. We propose a new way to correct these computed deformations to obtain reconstructions with reduced artifacts. The new approach has demonstrated to improve the quality of the final 3D reconstruction, giving access to better defined structures for different transmission electron tomography methods: resin embedded STEM-tomography and cryo-TEM tomography. The method is freely available in TomoJ software.
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Affiliation(s)
- C O S Sorzano
- Biocomputing Unit, National Center for Biotechnology (CSIC), c/Darwin, 3, Campus Universidad Aut'onoma, 28049 Cantoblanco, Madrid, Spain
| | - F de Isidro-Gómez
- Biocomputing Unit, National Center for Biotechnology (CSIC), c/Darwin, 3, Campus Universidad Aut'onoma, 28049 Cantoblanco, Madrid, Spain
| | - E Fernández-Giménez
- Biocomputing Unit, National Center for Biotechnology (CSIC), c/Darwin, 3, Campus Universidad Aut'onoma, 28049 Cantoblanco, Madrid, Spain
| | - D Herreros
- Biocomputing Unit, National Center for Biotechnology (CSIC), c/Darwin, 3, Campus Universidad Aut'onoma, 28049 Cantoblanco, Madrid, Spain
| | - S Marco
- Institite Curie, 110 Avenue de Bures, 91440 Bures-sur-Yvette, France
| | - J M Carazo
- Biocomputing Unit, National Center for Biotechnology (CSIC), c/Darwin, 3, Campus Universidad Aut'onoma, 28049 Cantoblanco, Madrid, Spain
| | - C Messaoudi
- Institite Curie, 110 Avenue de Bures, 91440 Bures-sur-Yvette, France
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Melero R, Sorzano COS, Foster B, Vilas JL, Martínez M, Marabini R, Ramírez-Aportela E, Sanchez-Garcia R, Herreros D, del Caño L, Losana P, Fonseca-Reyna YC, Conesa P, Wrapp D, Chacon P, McLellan JS, Tagare HD, Carazo JM. Continuous flexibility analysis of SARS-CoV-2 Spike prefusion structures. bioRxiv 2020:2020.07.08.191072. [PMID: 32676604 PMCID: PMC7359526 DOI: 10.1101/2020.07.08.191072] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
With the help of novel processing workflows and algorithms, we have obtained a better understanding of the flexibility and conformational dynamics of the SARS-CoV-2 spike in the prefusion state. We have re-analyzed previous cryo-EM data combining 3D clustering approaches with ways to explore a continuous flexibility space based on 3D Principal Component Analysis. These advanced analyses revealed a concerted motion involving the receptor-binding domain (RBD), N-terminal domain (NTD), and subdomain 1 and 2 (SD1 & SD2) around the previously characterized 1-RBD-up state, which have been modeled as elastic deformations. We show that in this dataset there are not well-defined, stable, spike conformations, but virtually a continuum of states moving in a concerted fashion. We obtained an improved resolution ensemble map with minimum bias, from which we model by flexible fitting the extremes of the change along the direction of maximal variance. Moreover, a high-resolution structure of a recently described biochemically stabilized form of the spike is shown to greatly reduce the dynamics observed for the wild-type spike. Our results provide new detailed avenues to potentially restrain the spike dynamics for structure-based drug and vaccine design and at the same time give a warning of the potential image processing classification instability of these complicated datasets, having a direct impact on the interpretability of the results.
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Affiliation(s)
- Roberto Melero
- Centro Nacional de Biotecnologia-CSIC, C/ Darwin, 3, 28049, Cantoblanco, Madrid, Spain
| | | | - Brent Foster
- Dept. of Radiology and Biomedical Imaging, Yale University, New Haven, CT 06520, USA
| | - José-Luis Vilas
- Dept. of Radiology and Biomedical Imaging, Yale University, New Haven, CT 06520, USA
| | - Marta Martínez
- Centro Nacional de Biotecnologia-CSIC, C/ Darwin, 3, 28049, Cantoblanco, Madrid, Spain
| | - Roberto Marabini
- Centro Nacional de Biotecnologia-CSIC, C/ Darwin, 3, 28049, Cantoblanco, Madrid, Spain
- Universidad Autónoma de Madrid, c/Tomás y Valiente, 11, 28049, Cantoblanco, Madrid, Spain
| | | | - Ruben Sanchez-Garcia
- Centro Nacional de Biotecnologia-CSIC, C/ Darwin, 3, 28049, Cantoblanco, Madrid, Spain
| | - David Herreros
- Centro Nacional de Biotecnologia-CSIC, C/ Darwin, 3, 28049, Cantoblanco, Madrid, Spain
| | - Laura del Caño
- Centro Nacional de Biotecnologia-CSIC, C/ Darwin, 3, 28049, Cantoblanco, Madrid, Spain
| | - Patricia Losana
- Centro Nacional de Biotecnologia-CSIC, C/ Darwin, 3, 28049, Cantoblanco, Madrid, Spain
| | | | - Pablo Conesa
- Centro Nacional de Biotecnologia-CSIC, C/ Darwin, 3, 28049, Cantoblanco, Madrid, Spain
| | - Daniel Wrapp
- Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX 78712, USA
| | - Pablo Chacon
- Instituto Rocasolano-CSIC, c/Serrano, 119, 28006, Madrid, Spain
| | - Jason S. McLellan
- Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX 78712, USA
| | - Hemant D. Tagare
- Dept. of Radiology and Biomedical Imaging, Yale University, New Haven, CT 06520, USA
| | - Jose-Maria Carazo
- Centro Nacional de Biotecnologia-CSIC, C/ Darwin, 3, 28049, Cantoblanco, Madrid, Spain
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Jiménez A, Jonic S, Majtner T, Otón J, Vilas JL, Maluenda D, Mota J, Ramírez-Aportela E, Martínez M, Rancel Y, Segura J, Sánchez-García R, Melero R, Del Cano L, Conesa P, Skjaerven L, Marabini R, Carazo JM, Sorzano COS. Validation of electron microscopy initial models via small angle X-ray scattering curves. Bioinformatics 2020; 35:2427-2433. [PMID: 30500892 DOI: 10.1093/bioinformatics/bty985] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2018] [Revised: 10/29/2018] [Accepted: 11/29/2018] [Indexed: 11/13/2022] Open
Abstract
MOTIVATION Cryo electron microscopy (EM) is currently one of the main tools to reveal the structural information of biological macromolecules. The re-construction of three-dimensional (3D) maps is typically carried out following an iterative process that requires an initial estimation of the 3D map to be refined in subsequent steps. Therefore, its determination is key in the quality of the final results, and there are cases in which it is still an open issue in single particle analysis (SPA). Small angle X-ray scattering (SAXS) is a well-known technique applied to structural biology. It is useful from small nanostructures up to macromolecular ensembles for its ability to obtain low resolution information of the biological sample measuring its X-ray scattering curve. These curves, together with further analysis, are able to yield information on the sizes, shapes and structures of the analyzed particles. RESULTS In this paper, we show how the low resolution structural information revealed by SAXS is very useful for the validation of EM initial 3D models in SPA, helping the following refinement process to obtain more accurate 3D structures. For this purpose, we approximate the initial map by pseudo-atoms and predict the SAXS curve expected for this pseudo-atomic structure. The match between the predicted and experimental SAXS curves is considered as a good sign of the correctness of the EM initial map. AVAILABILITY AND IMPLEMENTATION The algorithm is freely available as part of the Scipion 1.2 software at http://scipion.i2pc.es/.
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Affiliation(s)
- Amaya Jiménez
- Biocomputing Unit, Centro Nac. Biotecnología (CSIC), Cantoblanco, Madrid, Spain
| | - Slavica Jonic
- UMR CNRS 7590, Muséum National d ´Histoire Naturelle, IRD, Institut de Minéralogie, de Physique des Matériaux et de Cosmochimie, IMPMC, Sorbonne Université, Paris, France
| | - Tomas Majtner
- Biocomputing Unit, Centro Nac. Biotecnología (CSIC), Cantoblanco, Madrid, Spain
| | - Joaquín Otón
- Biocomputing Unit, Centro Nac. Biotecnología (CSIC), Cantoblanco, Madrid, Spain
| | - Jose Luis Vilas
- Biocomputing Unit, Centro Nac. Biotecnología (CSIC), Cantoblanco, Madrid, Spain
| | - David Maluenda
- Biocomputing Unit, Centro Nac. Biotecnología (CSIC), Cantoblanco, Madrid, Spain
| | - Javier Mota
- Biocomputing Unit, Centro Nac. Biotecnología (CSIC), Cantoblanco, Madrid, Spain
| | | | - Marta Martínez
- Biocomputing Unit, Centro Nac. Biotecnología (CSIC), Cantoblanco, Madrid, Spain
| | - Yaiza Rancel
- Biocomputing Unit, Centro Nac. Biotecnología (CSIC), Cantoblanco, Madrid, Spain
| | - Joan Segura
- Biocomputing Unit, Centro Nac. Biotecnología (CSIC), Cantoblanco, Madrid, Spain
| | | | - Roberto Melero
- Biocomputing Unit, Centro Nac. Biotecnología (CSIC), Cantoblanco, Madrid, Spain
| | - Laura Del Cano
- Biocomputing Unit, Centro Nac. Biotecnología (CSIC), Cantoblanco, Madrid, Spain
| | - Pablo Conesa
- Biocomputing Unit, Centro Nac. Biotecnología (CSIC), Cantoblanco, Madrid, Spain
| | - Lars Skjaerven
- Department of Biomedicine, University of Bergen, Bergen, Norway
| | - Roberto Marabini
- Biocomputing Unit, Centro Nac. Biotecnología (CSIC), Cantoblanco, Madrid, Spain.,Department of Computer Science, University Autónoma de Madrid, Cantoblanco, Madrid, Spain
| | - Jose M Carazo
- Biocomputing Unit, Centro Nac. Biotecnología (CSIC), Cantoblanco, Madrid, Spain
| | - Carlos Oscar S Sorzano
- Biocomputing Unit, Centro Nac. Biotecnología (CSIC), Cantoblanco, Madrid, Spain.,Department of Engineering of Electronic and Telecommunication System, University San Pablo-CEU, Campus Urb. Montepríncipe, Boadilla del Monte, Madrid, Spain
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38
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Segura J, Sanchez-Garcia R, Sorzano COS, Carazo JM. 3DBIONOTES v3.0: crossing molecular and structural biology data with genomic variations. Bioinformatics 2020; 35:3512-3513. [PMID: 30768147 PMCID: PMC6748749 DOI: 10.1093/bioinformatics/btz118] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2018] [Revised: 12/17/2018] [Accepted: 02/13/2019] [Indexed: 11/12/2022] Open
Abstract
MOTIVATION Many diseases are associated to single nucleotide polymorphisms that affect critical regions of proteins as binding sites or post translational modifications. Therefore, analysing genomic variants with structural and molecular biology data is a powerful framework in order to elucidate the potential causes of such diseases. RESULTS A new version of our web framework 3DBIONOTES is presented. This version offers new tools to analyse and visualize protein annotations and genomic variants, including a contingency analysis of variants and amino acid features by means of a Fisher exact test, the integration of a gene annotation viewer to highlight protein features on gene sequences and a protein-protein interaction viewer to display protein annotations at network level. AVAILABILITY AND IMPLEMENTATION The web server is available at https://3dbionotes.cnb.csic.es. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online. CONTACT Spanish National Institute for Bioinformatics (INB ELIXIR-ES) and Biocomputing Unit, National Centre of Biotechnology (CSIC)/Instruct Image Processing Centre, C/ Darwin nº 3, Campus of Cantoblanco, 28049 Madrid, Spain.
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Affiliation(s)
- Joan Segura
- Spanish National Institute for Bioinformatics (INB ELIXIR-ES) and Biocomputing Unit, National Centre of Biotechnology (CSIC)/Instruct Image Processing Centre, Madrid, Spain
| | - Ruben Sanchez-Garcia
- Spanish National Institute for Bioinformatics (INB ELIXIR-ES) and Biocomputing Unit, National Centre of Biotechnology (CSIC)/Instruct Image Processing Centre, Madrid, Spain
| | - C O S Sorzano
- Spanish National Institute for Bioinformatics (INB ELIXIR-ES) and Biocomputing Unit, National Centre of Biotechnology (CSIC)/Instruct Image Processing Centre, Madrid, Spain
| | - J M Carazo
- Spanish National Institute for Bioinformatics (INB ELIXIR-ES) and Biocomputing Unit, National Centre of Biotechnology (CSIC)/Instruct Image Processing Centre, Madrid, Spain
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Sanchez-Garcia R, Segura J, Maluenda D, Sorzano COS, Carazo JM. MicrographCleaner: A python package for cryo-EM micrograph cleaning using deep learning. J Struct Biol 2020; 210:107498. [PMID: 32276087 DOI: 10.1016/j.jsb.2020.107498] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2020] [Revised: 03/03/2020] [Accepted: 03/26/2020] [Indexed: 01/21/2023]
Abstract
Cryo-EM Single Particle Analysis workflows require tens of thousands of high-quality particle projections to unveil the three-dimensional structure of macromolecules. Conventional methods for automatic particle picking tend to suffer from high false-positive rates, hampering the reconstruction process. One common cause of this problem is the presence of carbon and different types of high-contrast contaminations. In order to overcome this limitation, we have developed MicrographCleaner, a deep learning package designed to discriminate, in an automated fashion, between regions of micrographs which are suitable for particle picking, and those which are not. MicrographCleaner implements a U-net-like deep learning model trained on a manually curated dataset compiled from over five hundred micrographs. The benchmarking, carried out on approximately one hundred independent micrographs, shows that MicrographCleaner is a very efficient approach for micrograph preprocessing. MicrographCleaner (micrograph_cleaner_em) package is available at PyPI and Anaconda Cloud and also as a Scipion/Xmipp protocol. Source code is available at https://github.com/rsanchezgarc/micrograph_cleaner_em.
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Affiliation(s)
- Ruben Sanchez-Garcia
- National Center of Biotechnology (CSIC)/Instruct Image Processing Center, C/ Darwin n° 3, Campus of Cantoblanco, 28049 Madrid, Spain.
| | - Joan Segura
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA 92093, USA
| | - David Maluenda
- National Center of Biotechnology (CSIC)/Instruct Image Processing Center, C/ Darwin n° 3, Campus of Cantoblanco, 28049 Madrid, Spain
| | - C O S Sorzano
- National Center of Biotechnology (CSIC)/Instruct Image Processing Center, C/ Darwin n° 3, Campus of Cantoblanco, 28049 Madrid, Spain
| | - J M Carazo
- National Center of Biotechnology (CSIC)/Instruct Image Processing Center, C/ Darwin n° 3, Campus of Cantoblanco, 28049 Madrid, Spain
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Iriondo-DeHond M, Iriondo-DeHond A, Herrera T, Fernández-Fernández AM, Sorzano COS, Miguel E, del Castillo MD. Sensory Acceptance, Appetite Control and Gastrointestinal Tolerance of Yogurts Containing Coffee-Cascara Extract and Inulin. Nutrients 2020; 12:nu12030627. [PMID: 32121016 PMCID: PMC7146162 DOI: 10.3390/nu12030627] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2020] [Revised: 02/24/2020] [Accepted: 02/25/2020] [Indexed: 11/24/2022] Open
Abstract
The improvement of the nutritional quality of dairy foods has become a key strategy for reducing the risk of developing diet-related non-communicable diseases. In this context, we aimed to optimize the concentration of inulin in combination with 10 mg/mL of coffee-cascara extract in yogurt while considering their effect on appetite control, gastrointestinal wellbeing, and their effect on the sensory and technological properties of the product. For this purpose, we tested four coffee-cascara yogurt treatments in a blind cross-over nutritional trial with 45 healthy adults: a coffee-cascara yogurt without inulin (Y0) and coffee-cascara yogurts containing 3% (Y3), 7% (Y7), and 13% (Y13) of inulin. The ratings on sensory acceptance, satiety, gastrointestinal tolerance, and stool frequency were measured. Surveys were carried out digitally in each participant’s cellphone. Yogurt pH, titratable acidity, syneresis, and instrumental texture were analyzed. Inulin addition increased the yogurt’s firmness and consistency. Y13 achieved significantly higher overall acceptance, texture, and taste scores than Y0 (p < 0.05). Y3 presented similar gastrointestinal tolerance to Y0. However, 7% and 13% of inulin produced significant (p < 0.05) bloating and flatulence when compared to Y0. The appetite ratings were not significantly affected by the acute intake of the different yogurts. Overall, Y3 was identified as the formulation that maximized nutritional wellbeing, reaching a “source of fiber” nutritional claim, without compromising its technological and sensory properties.
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Affiliation(s)
- Maite Iriondo-DeHond
- Instituto Madrileño de Investigación y Desarrollo Rural, Agrario y Alimentario (IMIDRA), N-II km 38,200, 28800 Alcalá de Henares, Spain; (M.I.-D.); (E.M.)
- Instituto de Investigación en Ciencias de la Alimentación (CIAL) (UAM-CSIC), C/ Nicolás Cabrera, 9, Campus de la Universidad Autónoma de Madrid, 28049 Madrid, Spain; (A.I.-D.); (T.H.)
| | - Amaia Iriondo-DeHond
- Instituto de Investigación en Ciencias de la Alimentación (CIAL) (UAM-CSIC), C/ Nicolás Cabrera, 9, Campus de la Universidad Autónoma de Madrid, 28049 Madrid, Spain; (A.I.-D.); (T.H.)
| | - Teresa Herrera
- Instituto de Investigación en Ciencias de la Alimentación (CIAL) (UAM-CSIC), C/ Nicolás Cabrera, 9, Campus de la Universidad Autónoma de Madrid, 28049 Madrid, Spain; (A.I.-D.); (T.H.)
| | - Adriana Maite Fernández-Fernández
- Departamento de Ciencia y Tecnología de Alimentos, Facultad de Química, Universidad de la República, General Flores 2124, Montevideo 11800, Uruguay;
| | | | - Eugenio Miguel
- Instituto Madrileño de Investigación y Desarrollo Rural, Agrario y Alimentario (IMIDRA), N-II km 38,200, 28800 Alcalá de Henares, Spain; (M.I.-D.); (E.M.)
| | - María Dolores del Castillo
- Instituto de Investigación en Ciencias de la Alimentación (CIAL) (UAM-CSIC), C/ Nicolás Cabrera, 9, Campus de la Universidad Autónoma de Madrid, 28049 Madrid, Spain; (A.I.-D.); (T.H.)
- Correspondence: ; Tel.: +34-91-0017900 (ext. 953)
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Martínez M, Jiménez-Moreno A, Maluenda D, Ramírez-Aportela E, Melero R, Cuervo A, Conesa P, Del Caño L, Fonseca YC, Sánchez-García R, Strelak D, Conesa JJ, Fernández-Giménez E, de Isidro F, Sorzano COS, Carazo JM, Marabini R. Integration of Cryo-EM Model Building Software in Scipion. J Chem Inf Model 2020; 60:2533-2540. [PMID: 31994878 DOI: 10.1021/acs.jcim.9b01032] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Advances in cryo-electron microscopy (cryo-EM) have made it possible to obtain structures of large biological macromolecules at near-atomic resolution. This "resolution revolution" has encouraged the use and development of modeling tools able to produce high-quality atomic models from cryo-EM density maps. Unfortunately, many practical problems appear when combining different packages in the same processing workflow, which make difficult the use of these tools by non-experts and, therefore, reduce their utility. We present here a major extension of the image processing framework Scipion that provides inter-package integration in the model building area and full tracking of the complete workflow, from image processing to structure validation.
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Affiliation(s)
- M Martínez
- CNB-CSIC, C/Darwin 3, 28049 Madrid, Spain
| | | | - D Maluenda
- CNB-CSIC, C/Darwin 3, 28049 Madrid, Spain
| | | | - R Melero
- CNB-CSIC, C/Darwin 3, 28049 Madrid, Spain
| | - A Cuervo
- CNB-CSIC, C/Darwin 3, 28049 Madrid, Spain
| | - P Conesa
- CNB-CSIC, C/Darwin 3, 28049 Madrid, Spain
| | - L Del Caño
- CNB-CSIC, C/Darwin 3, 28049 Madrid, Spain
| | | | | | - D Strelak
- CNB-CSIC, C/Darwin 3, 28049 Madrid, Spain.,Institute of Computer Science, Masaryk University, Botanická 68a, 60200 Brno, Czech Republic
| | - J J Conesa
- CNB-CSIC, C/Darwin 3, 28049 Madrid, Spain
| | | | | | | | - J M Carazo
- CNB-CSIC, C/Darwin 3, 28049 Madrid, Spain
| | - R Marabini
- Escuela Politécnica, Universidad Autónoma de Madrid, C/Francisco Tomás y Valiente 11, 28049 Madrid, Spain
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Vilas JL, Vargas J, Martinez M, Ramirez-Aportela E, Melero R, Jimenez-Moreno A, Garduño E, Conesa P, Marabini R, Maluenda D, Carazo JM, Sorzano COS. Re-examining the spectra of macromolecules. Current practice of spectral quasi B-factor flattening. J Struct Biol 2020; 209:107447. [PMID: 31911170 DOI: 10.1016/j.jsb.2020.107447] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2019] [Revised: 12/29/2019] [Accepted: 01/01/2020] [Indexed: 11/24/2022]
Abstract
The analysis of structure factors in 3D cryo-EM Coulomb potential maps and their "enhancement" at the end of the reconstruction process is a well-established practice, normally referred to as sharpening. The aim is to increase contrast and, in this way, to help tracing the atomic model. The most common way to accomplish this enhancement is by means of the so-called B-factor correction, which applies a global filter to boost high frequencies with some dampening considerations related to noise amplification. The results are maps with a better visual aspect and a quasiflat spectrum at medium and high frequencies. This practice is so widespread that most map depositions in the Electron Microscopy Data Base (EMDB) only contain sharpened maps. Here, the use in cryoEM of global B-factor corrections is theoretically and experimentally analyzed. Results clearly illustrate that protein spectra present a falloff. Thus, spectral quasi-flattening may produce protein spectra with distortions when compared with experimental ones, this fact, combined with the practice of reporting only sharpened maps, generates a sub-optimal situation in terms of data preservation, reuse and reproducibility. Now that the field is more advanced, we put forward two suggestions: (1) to use methods which keep more faithfully the original experimental signal properties of macromolecules when "enhancing" the map, and (2) to further stress the need to deposit the original experimental maps without any postprocessing or sharpening, not only the enhanced maps. In the absence of access to these original maps data is lost, preventing their future analysis with new methods.
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Affiliation(s)
- J L Vilas
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - J Vargas
- Dept. Anatomy and Cell Biology, McGill Univ., Montreal, Canada
| | - M Martinez
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - E Ramirez-Aportela
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - R Melero
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - A Jimenez-Moreno
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - E Garduño
- Department of Computer Science, Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas, Universidad Nacional Autónoma de México, 04510 Mexico City, Mexico
| | - P Conesa
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - R Marabini
- Escuela Politecnica Superior, Universidad Autónoma de Madrid, 28049 Cantoblanco, Madrid, Spain
| | - D Maluenda
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - J M Carazo
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - C O S Sorzano
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain; Univ. San Pablo - CEU, Campus Urb. Monteprincipe, 28668 Boadilla del Monte, Madrid, Spain.
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Vilas JL, Tagare HD, Vargas J, Carazo JM, Sorzano COS. Measuring local-directional resolution and local anisotropy in cryo-EM maps. Nat Commun 2020; 11:55. [PMID: 31896756 PMCID: PMC6940361 DOI: 10.1038/s41467-019-13742-w] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2019] [Accepted: 11/18/2019] [Indexed: 12/17/2022] Open
Abstract
The introduction of local resolution has enormously helped the understanding of cryo-EM maps. Still, for any given pixel it is a global, aggregated value, that makes impossible the individual analysis of the contribution of the different projection directions. We introduce MonoDir, a fully automatic, parameter-free method that, starting only from the final cryo-EM map, decomposes local resolution into the different projection directions, providing a detailed level of analysis of the final map. Many applications of directional local resolution are possible, and we concentrate here on map quality and validation. It is important to analyse the local resolution of cryo-EM maps. Here the authors present MonoDir, a fully automatic and parameter free method for the directional local resolution analysis of cryo-EM maps that requires only the final map as input and they also propose indicators for assessing map quality.
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Affiliation(s)
- Jose Luis Vilas
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Campus Universidad Autonoma, 28049, Cantoblanco, Madrid, Spain
| | - Hemant D Tagare
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06520, USA
| | - Javier Vargas
- Department of Anatomy and Cell Biology, McGill University, Montreal, H3A 0G4, Canada
| | - Jose Maria Carazo
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Campus Universidad Autonoma, 28049, Cantoblanco, Madrid, Spain.
| | - Carlos Oscar S Sorzano
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Campus Universidad Autonoma, 28049, Cantoblanco, Madrid, Spain.
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Raman SC, Mejías-Pérez E, Gomez CE, García-Arriaza J, Perdiguero B, Vijayan A, Pérez-Ruiz M, Cuervo A, Santiago C, Sorzano COS, Sánchez-Corzo C, Moog C, Burger JA, Schorcht A, Sanders RW, Carrascosa JL, Esteban M. The Envelope-Based Fusion Antigen GP120C14K Forming Hexamer-Like Structures Triggers T Cell and Neutralizing Antibody Responses Against HIV-1. Front Immunol 2019; 10:2793. [PMID: 31867001 PMCID: PMC6904342 DOI: 10.3389/fimmu.2019.02793] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2019] [Accepted: 11/14/2019] [Indexed: 11/20/2022] Open
Abstract
There is an urgent need for the development of potent vaccination regimens that are able to induce specific T and B cell responses against human immunodeficiency virus type 1 (HIV-1). Here, we describe the generation and characterization of a fusion antigen comprised of the HIV-1 envelope GP120 glycoprotein from clade C (GP120C) fused at its C-terminus, with the modified vaccinia virus (VACV) 14K protein (A27L gene) (termed GP120C14K). The design is directed toward improving the immunogenicity of the GP120C protein through its oligomerization facilitated by the fused VACV 14K protein that results in hexamer-like structures. Two different immunogens were generated: a recombinant GP120C14K fusion protein (purified from a stable CHO-K1 cell line) and a recombinant modified vaccinia virus Ankara (MVA) poxvirus vector expressing the GP120C14K fusion protein (termed MVA-GP120C14K). The GP120C14K fusion protein is recognized by broadly neutralizing antibodies (bNAbs) against HIV-1. In a murine model, a heterologous prime/boost immunization regimen with MVA-GP120C14K prime followed by adjuvanted GP120C14K protein boost generated stronger and polyfunctional HIV-1 Env-specific CD8 T cell responses when compared with the delivery of the monomeric GP120C form. Furthermore, the immunization protocol MVA-GP120C14K/GP120C14K elicited higher HIV-1 Env-specific T follicular helper cells, germinal center B cells and antibody responses than monomeric GP120. In addition, a similar MVA-GP120C14K prime/GP120C14K protein boost regimen performed in rabbits triggered high HIV-1-Env-specific IgG binding antibody titers that were capable of neutralizing HIV-1 pseudoviruses. The extent of HIV-1 neutralization was comparable to that elicited by the current standard GP140 SOSIP trimers from clades B and C when immunized as MVA-SOSIP prime/SOSIP protein boost regimen. Overall, the novel fusion antigen and the corresponding immunization scheme provided in this report can therefore be considered as potential vaccine strategies against HIV-1.
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Affiliation(s)
- Suresh C Raman
- Department of Molecular and Cellular Biology, Centro Nacional de Biotecnología, Consejo Superior de Investigaciones Científicas (CNB-CSIC), Madrid, Spain
| | - Ernesto Mejías-Pérez
- Department of Molecular and Cellular Biology, Centro Nacional de Biotecnología, Consejo Superior de Investigaciones Científicas (CNB-CSIC), Madrid, Spain
| | - Carmen E Gomez
- Department of Molecular and Cellular Biology, Centro Nacional de Biotecnología, Consejo Superior de Investigaciones Científicas (CNB-CSIC), Madrid, Spain
| | - Juan García-Arriaza
- Department of Molecular and Cellular Biology, Centro Nacional de Biotecnología, Consejo Superior de Investigaciones Científicas (CNB-CSIC), Madrid, Spain
| | - Beatriz Perdiguero
- Department of Molecular and Cellular Biology, Centro Nacional de Biotecnología, Consejo Superior de Investigaciones Científicas (CNB-CSIC), Madrid, Spain
| | - Aneesh Vijayan
- Department of Molecular and Cellular Biology, Centro Nacional de Biotecnología, Consejo Superior de Investigaciones Científicas (CNB-CSIC), Madrid, Spain
| | - Mar Pérez-Ruiz
- Department of Structure of Macromolecules, Centro Nacional de Biotecnología, Consejo Superior de Investigaciones Científicas (CNB-CSIC), Madrid, Spain
| | - Ana Cuervo
- Department of Structure of Macromolecules, Centro Nacional de Biotecnología, Consejo Superior de Investigaciones Científicas (CNB-CSIC), Madrid, Spain
| | - César Santiago
- X-ray Crystallization Unit, Centro Nacional de Biotecnología, Consejo Superior de Investigaciones Científicas (CNB-CSIC), Madrid, Spain
| | - Carlos Oscar S Sorzano
- Biocomputing Unit, Centro Nacional de Biotecnología, Consejo Superior de Investigaciones Científicas (CNB-CSIC), Madrid, Spain
| | - Cristina Sánchez-Corzo
- Department of Molecular and Cellular Biology, Centro Nacional de Biotecnología, Consejo Superior de Investigaciones Científicas (CNB-CSIC), Madrid, Spain
| | - Christiane Moog
- INSERM U1109, Fédération Hospitalo-Universitaire (FHU) OMICARE, Fédération de Médecine Translationnelle de Strasbourg (FMTS), Université de Strasbourg, Strasbourg, France
| | - Judith A Burger
- Department of Medical Microbiology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands
| | - Anna Schorcht
- Department of Medical Microbiology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands
| | - Rogier W Sanders
- Department of Medical Microbiology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands.,Department of Microbiology and Immunology, Weill Medical College of Cornell University, New York, NY, United States
| | - José L Carrascosa
- Department of Structure of Macromolecules, Centro Nacional de Biotecnología, Consejo Superior de Investigaciones Científicas (CNB-CSIC), Madrid, Spain
| | - Mariano Esteban
- Department of Molecular and Cellular Biology, Centro Nacional de Biotecnología, Consejo Superior de Investigaciones Científicas (CNB-CSIC), Madrid, Spain
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Vilas JL, Oton J, Messaoudi C, Melero R, Conesa P, Ramirez-Aportela E, Mota J, Martinez M, Jimenez A, Marabini R, Carazo JM, Vargas J, Sorzano COS. Measurement of local resolution in electron tomography. J Struct Biol X 2019; 4:100016. [PMID: 32647820 PMCID: PMC7337044 DOI: 10.1016/j.yjsbx.2019.100016] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/30/2019] [Revised: 05/13/2019] [Accepted: 11/20/2019] [Indexed: 02/07/2023]
Abstract
Resolution (global and local) is one of the most reported metrics of quality measurement in Single Particle Analysis (SPA). However, in electron tomography, the situation is different and its computation is not straightforward. Typically, resolution estimation is global and, therefore, reduces the assessment of a whole tomogram to a single number. However, it is known that tomogram quality is spatially variant. Still, up to our knowledge, a method to estimate local quality metrics in tomography is lacking. This work introduces MonoTomo, a method developed to estimate locally in a tomogram the highest reliable frequency component, expressed as a form of local resolution. The fundamentals lie in a local analysis of the density map via monogenic signals, which, in analogy to MonoRes, allows for local estimations. Results with experimental data show that the local resolution range that MonoTomo casts agrees with reported resolution values for experimental data sets, with the advantage of providing a local estimation. A range of applications of MonoTomo are suggested for further exploration.
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Affiliation(s)
- J L Vilas
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - J Oton
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom
| | - C Messaoudi
- U1196, Institut Curie, INSERM, PSL Reseach University, F-91405 Orsay, France
| | - R Melero
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - P Conesa
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - E Ramirez-Aportela
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - J Mota
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - M Martinez
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - A Jimenez
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - R Marabini
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - J M Carazo
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - J Vargas
- Dept. Anatomy and Cell Biology, McGill Univ., Montreal, Canada
| | - C O S Sorzano
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain.,Univ. San Pablo - CEU, Campus Urb. Monteprincipe, 28668 Boadilla del Monte, Madrid, Spain
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46
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Harastani M, Sorzano COS, Jonić S. Hybrid Electron Microscopy Normal Mode Analysis with Scipion. Protein Sci 2019; 29:223-236. [PMID: 31693263 DOI: 10.1002/pro.3772] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2019] [Revised: 11/03/2019] [Accepted: 11/04/2019] [Indexed: 12/12/2022]
Abstract
Hybrid Electron Microscopy Normal Mode Analysis (HEMNMA) method was introduced in 2014. HEMNMA computes normal modes of a reference model (an atomic structure or an electron microscopy map) of a molecular complex and uses this model and its normal modes to analyze single-particle images of the complex to obtain information on its continuous conformational changes, by determining the full distribution of conformational variability from the images. An advantage of HEMNMA is a simultaneous determination of all parameters of each image (particle conformation, orientation, and shift) through their iterative optimization, which allows applications of HEMNMA even when the effects of conformational changes dominate those of orientational changes. HEMNMA was first implemented in Xmipp and was using MATLAB for statistical analysis of obtained conformational distributions and for fitting of underlying trajectories of conformational changes. A HEMNMA implementation independent of MATLAB is now available as part of a plugin of Scipion V2.0 (http://scipion.i2pc.es). This plugin, named ContinuousFlex, can be installed by following the instructions at https://pypi.org/project/scipion-em-continuousflex. In this article, we present this new HEMNMA software, which is user-friendly, totally free, and open-source. STATEMENT FOR A BROADER AUDIENCE: This article presents Hybrid Electron Microscopy Normal Mode Analysis (HEMNMA) software that allows analyzing single-particle images of a complex to obtain information on continuous conformational changes of the complex, by determining the full distribution of conformational variability from the images. The HEMNMA software is user-friendly, totally free, open-source, and available as part of ContinuousFlex plugin (https://pypi.org/project/scipion-em-continuousflex) of Scipion V2.0 (http://scipion.i2pc.es).
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Affiliation(s)
- Mohamad Harastani
- Sorbonne Université, UMR CNRS 7590, Muséum National d'Histoire Naturelle, IRD, Institut de Minéralogie, de Physique des Matériaux et de Cosmochimie, IMPMC, Paris, France
| | | | - Slavica Jonić
- Sorbonne Université, UMR CNRS 7590, Muséum National d'Histoire Naturelle, IRD, Institut de Minéralogie, de Physique des Matériaux et de Cosmochimie, IMPMC, Paris, France
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Sanchez-Garcia R, Sorzano COS, Carazo JM, Segura J. BIPSPI: a method for the prediction of partner-specific protein-protein interfaces. Bioinformatics 2019; 35:470-477. [PMID: 30020406 PMCID: PMC6361243 DOI: 10.1093/bioinformatics/bty647] [Citation(s) in RCA: 51] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2018] [Accepted: 07/17/2018] [Indexed: 11/15/2022] Open
Abstract
Motivation Protein-Protein Interactions (PPI) are essentials for most cellular processes and thus, unveiling how proteins interact is a crucial question that can be better understood by identifying which residues are responsible for the interaction. Computational approaches are orders of magnitude cheaper and faster than experimental ones, leading to proliferation of multiple methods aimed to predict which residues belong to the interface of an interaction. Results We present BIPSPI, a new machine learning-based method for the prediction of partner-specific PPI sites. Contrary to most binding site prediction methods, the proposed approach takes into account a pair of interacting proteins rather than a single one in order to predict partner-specific binding sites. BIPSPI has been trained employing sequence-based and structural features from both protein partners of each complex compiled in the Protein-Protein Docking Benchmark version 5.0 and in an additional set independently compiled. Also, a version trained only on sequences has been developed. The performance of our approach has been assessed by a leave-one-out cross-validation over different benchmarks, outperforming state-of-the-art methods. Availability and implementation BIPSPI web server is freely available at http://bipspi.cnb.csic.es. BIPSPI code is available at https://github.com/bioinsilico/BIPSPI. Docker image is available at https://hub.docker.com/r/bioinsilico/bipspi/. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Ruben Sanchez-Garcia
- GN7 of the Spanish National Institute for Bioinformatics (INB), Biocomputing Unit, National Center of Biotechnology (CSIC), Instruct Image Processing Center, Madrid, Spain
| | - C O S Sorzano
- GN7 of the Spanish National Institute for Bioinformatics (INB), Biocomputing Unit, National Center of Biotechnology (CSIC), Instruct Image Processing Center, Madrid, Spain
| | - J M Carazo
- GN7 of the Spanish National Institute for Bioinformatics (INB), Biocomputing Unit, National Center of Biotechnology (CSIC), Instruct Image Processing Center, Madrid, Spain
| | - Joan Segura
- GN7 of the Spanish National Institute for Bioinformatics (INB), Biocomputing Unit, National Center of Biotechnology (CSIC), Instruct Image Processing Center, Madrid, Spain
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Ramírez-Aportela E, Mota J, Conesa P, Carazo JM, Sorzano COS. DeepRes: a new deep-learning- and aspect-based local resolution method for electron-microscopy maps. IUCrJ 2019; 6:1054-1063. [PMID: 31709061 PMCID: PMC6830216 DOI: 10.1107/s2052252519011692] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/28/2019] [Accepted: 08/22/2019] [Indexed: 05/26/2023]
Abstract
In this article, a method is presented to estimate a new local quality measure for 3D cryoEM maps that adopts the form of a 'local resolution' type of information. The algorithm (DeepRes) is based on deep-learning 3D feature detection. DeepRes is fully automatic and parameter-free, and avoids the issues of most current methods, such as their insensitivity to enhancements owing to B-factor sharpening (unless the 3D mask is changed), among others, which is an issue that has been virtually neglected in the cryoEM field until now. In this way, DeepRes can be applied to any map, detecting subtle changes in local quality after applying enhancement processes such as isotropic filters or substantially more complex procedures, such as model-based local sharpening, non-model-based methods or denoising, that may be very difficult to follow using current methods. It performs as a human observer expects. The comparison with traditional local resolution indicators is also addressed.
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Affiliation(s)
- Erney Ramírez-Aportela
- Biocomputing Unit, National Center for Biotechnology (CSIC), Calle Darwin 3, Campus Universidad Autónoma de Madrid, Cantoblanco, 28049 Madrid, Spain
| | - Javier Mota
- Biocomputing Unit, National Center for Biotechnology (CSIC), Calle Darwin 3, Campus Universidad Autónoma de Madrid, Cantoblanco, 28049 Madrid, Spain
| | - Pablo Conesa
- Biocomputing Unit, National Center for Biotechnology (CSIC), Calle Darwin 3, Campus Universidad Autónoma de Madrid, Cantoblanco, 28049 Madrid, Spain
| | - Jose Maria Carazo
- Biocomputing Unit, National Center for Biotechnology (CSIC), Calle Darwin 3, Campus Universidad Autónoma de Madrid, Cantoblanco, 28049 Madrid, Spain
| | - Carlos Oscar S. Sorzano
- Biocomputing Unit, National Center for Biotechnology (CSIC), Calle Darwin 3, Campus Universidad Autónoma de Madrid, Cantoblanco, 28049 Madrid, Spain
- Universidad CEU San Pablo, Campus Urbanizacion Montepríncipe, Boadilla del Monte, 28668 Madrid, Spain
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Ramírez-Aportela E, Vilas JL, Glukhova A, Melero R, Conesa P, Martínez M, Maluenda D, Mota J, Jiménez A, Vargas J, Marabini R, Sexton PM, Carazo JM, Sorzano COS. Automatic local resolution-based sharpening of cryo-EM maps. Bioinformatics 2019; 36:765-772. [PMID: 31504163 PMCID: PMC9883678 DOI: 10.1093/bioinformatics/btz671] [Citation(s) in RCA: 69] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Revised: 08/02/2019] [Accepted: 08/22/2019] [Indexed: 02/02/2023] Open
Abstract
MOTIVATION Recent technological advances and computational developments have allowed the reconstruction of Cryo-Electron Microscopy (cryo-EM) maps at near-atomic resolution. On a typical workflow and once the cryo-EM map has been calculated, a sharpening process is usually performed to enhance map visualization, a step that has proven very important in the key task of structural modeling. However, sharpening approaches, in general, neglects the local quality of the map, which is clearly suboptimal. RESULTS Here, a new method for local sharpening of cryo-EM density maps is proposed. The algorithm, named LocalDeblur, is based on a local resolution-guided Wiener restoration approach of the original map. The method is fully automatic and, from the user point of view, virtually parameter-free, without requiring either a starting model or introducing any additional structure factor correction or boosting. Results clearly show a significant impact on map interpretability, greatly helping modeling. In particular, this local sharpening approach is especially suitable for maps that present a broad resolution range, as is often the case for membrane proteins or macromolecules with high flexibility, all of them otherwise very suitable and interesting specimens for cryo-EM. To our knowledge, and leaving out the use of local filters, it represents the first application of local resolution in cryo-EM sharpening. AVAILABILITY AND IMPLEMENTATION The source code (LocalDeblur) can be found at https://github.com/I2PC/xmipp and can be run using Scipion (http://scipion.cnb.csic.es) (release numbers greater than or equal 1.2.1). SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
| | | | - Alisa Glukhova
- Drug Discovery Biology, Monash Institute of Pharmaceutical Sciences, Parkville, 3052 VIC, Australia
| | - Roberto Melero
- Biocomputing Unit, National Center for Biotechnology (CSIC), Darwin 3, Campus Univ. Autónoma de Madrid, Cantoblanco, 28049 Madrid, Spain
| | - Pablo Conesa
- Biocomputing Unit, National Center for Biotechnology (CSIC), Darwin 3, Campus Univ. Autónoma de Madrid, Cantoblanco, 28049 Madrid, Spain
| | - Marta Martínez
- Biocomputing Unit, National Center for Biotechnology (CSIC), Darwin 3, Campus Univ. Autónoma de Madrid, Cantoblanco, 28049 Madrid, Spain
| | - David Maluenda
- Biocomputing Unit, National Center for Biotechnology (CSIC), Darwin 3, Campus Univ. Autónoma de Madrid, Cantoblanco, 28049 Madrid, Spain
| | - Javier Mota
- Biocomputing Unit, National Center for Biotechnology (CSIC), Darwin 3, Campus Univ. Autónoma de Madrid, Cantoblanco, 28049 Madrid, Spain
| | - Amaya Jiménez
- Biocomputing Unit, National Center for Biotechnology (CSIC), Darwin 3, Campus Univ. Autónoma de Madrid, Cantoblanco, 28049 Madrid, Spain
| | - Javier Vargas
- Department of Anatomy and Cell Biology, McGill University, 3640 Rue University, Montreal QC H3A 0C7 Canada
| | - Roberto Marabini
- Campus Univ. Autónoma de Madrid, Univ. Autónoma de Madrid, 28049 Cantoblanco, Madrid, Spain
| | - Patrick M Sexton
- Drug Discovery Biology, Monash Institute of Pharmaceutical Sciences, Parkville, 3052 VIC, Australia,School of Pharmacy, Fudan University, Shanghai 201203, China
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Perdiguero B, Sánchez-Corzo C, S Sorzano CO, Mediavilla P, Saiz L, Esteban M, Gómez CE. Induction of Broad and Polyfunctional HIV-1-Specific T Cell Responses by the Multiepitopic Protein TMEP-B Vectored by MVA Virus. Vaccines (Basel) 2019; 7:vaccines7030057. [PMID: 31261918 PMCID: PMC6789790 DOI: 10.3390/vaccines7030057] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2019] [Revised: 06/21/2019] [Accepted: 06/26/2019] [Indexed: 11/16/2022] Open
Abstract
A human immunodeficiency virus (HIV)/acquired immune deficiency syndrome (AIDS) vaccine able to induce long-lasting immunity remains a major challenge. We previously designed a T cell multiepitopic immunogen including protective conserved epitopes from HIV-1 Gag, Pol and Nef proteins (TMEP-B), that induced potent HIV-1-specific CD8 T cells when vectored by DNA and combined with the vaccine candidate modified vaccinia virus Ankara (MVA)-B. Here, we described the vectorization of TMEP-B in MVA (MVA-TMEP) and evaluated the T cell immunogenicity profile elicited in mice when administered in homologous (MVA/MVA) or heterologous (DNA/MVA) prime/boost vector regimens or using homologous or heterologous inserts. The heterologous vector regimen was superior to the homologous protocol in inducing T cell responses. DNA-TMEP-primed animals boosted with MVA-TMEP or MVA-B exhibited the highest magnitudes of HIV-1-specific CD8, CD4 and T follicular helper (Tfh) cells, with MVA-TMEP significantly expanding Gag-specific CD8 T cell responses. In the homologous vector regimen, all groups exhibited similar HIV-1-specific CD8 and CD4 T cell responses, but both MVA-B/MVA-B and MVA-TMEP/MVA-TMEP combinations elicited higher Gag-Pol-Nef (GPN)-specific CD8 T cell responses compared to MVA-TMEP/MVA-B. Our results revealed an enhanced induction of HIV-1-specific T cell responses by TMEP-B when vectored in both DNA and MVA, and supported their use in combined prime/boost strategies for HIV-1 prevention and/or therapy.
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Affiliation(s)
- Beatriz Perdiguero
- Department of Molecular and Cellular Biology, Centro Nacional de Biotecnología, Consejo Superior de Investigaciones Científicas (CNB-CSIC), Campus de Cantoblanco, 28049 Madrid, Spain
| | - Cristina Sánchez-Corzo
- Department of Molecular and Cellular Biology, Centro Nacional de Biotecnología, Consejo Superior de Investigaciones Científicas (CNB-CSIC), Campus de Cantoblanco, 28049 Madrid, Spain
| | - Carlos Oscar S Sorzano
- Biocomputing Unit, Centro Nacional de Biotecnología, Consejo Superior de Investigaciones Científicas (CNB-CSIC), Campus de Cantoblanco, 28049 Madrid, Spain
| | - Pilar Mediavilla
- Department of Molecular and Cellular Biology, Centro Nacional de Biotecnología, Consejo Superior de Investigaciones Científicas (CNB-CSIC), Campus de Cantoblanco, 28049 Madrid, Spain
| | - Lidia Saiz
- Department of Molecular and Cellular Biology, Centro Nacional de Biotecnología, Consejo Superior de Investigaciones Científicas (CNB-CSIC), Campus de Cantoblanco, 28049 Madrid, Spain
| | - Mariano Esteban
- Department of Molecular and Cellular Biology, Centro Nacional de Biotecnología, Consejo Superior de Investigaciones Científicas (CNB-CSIC), Campus de Cantoblanco, 28049 Madrid, Spain.
| | - Carmen Elena Gómez
- Department of Molecular and Cellular Biology, Centro Nacional de Biotecnología, Consejo Superior de Investigaciones Científicas (CNB-CSIC), Campus de Cantoblanco, 28049 Madrid, Spain.
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