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Soltwedel JR, Haase R. Challenges and opportunities for bioimage analysis core-facilities. J Microsc 2024; 294:338-349. [PMID: 37199456 DOI: 10.1111/jmi.13192] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 05/05/2023] [Accepted: 05/15/2023] [Indexed: 05/19/2023]
Abstract
Recent advances in microscopy imaging and image analysis motivate more and more institutes worldwide to establish dedicated core-facilities for bioimage analysis. To maximise the benefits research groups at these institutes gain from their core-facilities, they should be established to fit well into their respective environment. In this article, we introduce common collaborator requests and corresponding potential services core-facilities can offer. We also discuss potential competing interests between the targeted missions and implementations of services to guide decision makers and core-facility founders to circumvent common pitfalls.
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Affiliation(s)
| | - Robert Haase
- DFG Cluster of Excellence 'Physics of Life', TU Dresden, Germany
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2
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Dessimoz C, Thomas PD. AI and the democratization of knowledge. Sci Data 2024; 11:268. [PMID: 38443367 PMCID: PMC10915151 DOI: 10.1038/s41597-024-03099-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Accepted: 02/28/2024] [Indexed: 03/07/2024] Open
Affiliation(s)
- Christophe Dessimoz
- Swiss Institute of Bioinformatics, Lausanne, Switzerland.
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.
| | - Paul D Thomas
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, 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. 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] [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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4
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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] [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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5
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Turner J, Abbott S, Fonseca N, Pye R, Carrijo L, Duraisamy AK, Salih O, Wang Z, Kleywegt GJ, Morris KL, Patwardhan A, Burley SK, Crichlow G, Feng Z, Flatt JW, Ghosh S, Hudson BP, Lawson CL, Liang Y, Peisach E, Persikova I, Sekharan M, Shao C, Young J, Velankar S, Armstrong D, Bage M, Bueno WM, Evans G, Gaborova R, Ganguly S, Gupta D, Harrus D, Tanweer A, Bansal M, Rangannan V, Kurisu G, Cho H, Ikegawa Y, Kengaku Y, Kim JY, Niwa S, Sato J, Takuwa A, Yu J, Hoch JC, Baskaran K, Xu W, Zhang W, Ma X. EMDB-the Electron Microscopy Data Bank. Nucleic Acids Res 2024; 52:D456-D465. [PMID: 37994703 PMCID: PMC10767987 DOI: 10.1093/nar/gkad1019] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 10/18/2023] [Accepted: 10/20/2023] [Indexed: 11/24/2023] Open
Abstract
The Electron Microscopy Data Bank (EMDB) is the global public archive of three-dimensional electron microscopy (3DEM) maps of biological specimens derived from transmission electron microscopy experiments. As of 2021, EMDB is managed by the Worldwide Protein Data Bank consortium (wwPDB; wwpdb.org) as a wwPDB Core Archive, and the EMDB team is a core member of the consortium. Today, EMDB houses over 30 000 entries with maps containing macromolecules, complexes, viruses, organelles and cells. Herein, we provide an overview of the rapidly growing EMDB archive, including its current holdings, recent updates, and future plans.
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Kwon S, Safer J, Nguyen DT, Hoksza D, May P, Arbesfeld JA, Rubin AF, Campbell AJ, Burgin A, Iqbal S. Genomics 2 Proteins portal: A resource and discovery tool for linking genetic screening outputs to protein sequences and structures. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.02.573913. [PMID: 38260256 PMCID: PMC10802383 DOI: 10.1101/2024.01.02.573913] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Recent advances in AI-based methods have revolutionized the field of structural biology. Concomitantly, high-throughput sequencing and functional genomics technologies have enabled the detection and generation of variants at an unprecedented scale. However, efficient tools and resources are needed to link these two disparate data types - to "map" variants onto protein structures, to better understand how the variation causes disease and thereby design therapeutics. Here we present the Genomics 2 Proteins Portal (G2P; g2p.broadinstitute.org/): a human proteome-wide resource that maps 19,996,443 genetic variants onto 42,413 protein sequences and 77,923 structures, with a comprehensive set of structural and functional features. Additionally, the G2P portal generalizes the capability of linking genomics to proteins beyond databases by allowing users to interactively upload protein residue-wise annotations (variants, scores, etc.) as well as the protein structure to establish the connection. The portal serves as an easy-to-use discovery tool for researchers and scientists to hypothesize the structure-function relationship between natural or synthetic variations and their molecular phenotype.
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Poger D, Yen L, Braet F. Big data in contemporary electron microscopy: challenges and opportunities in data transfer, compute and management. Histochem Cell Biol 2023; 160:169-192. [PMID: 37052655 PMCID: PMC10492738 DOI: 10.1007/s00418-023-02191-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/21/2023] [Indexed: 04/14/2023]
Abstract
The second decade of the twenty-first century witnessed a new challenge in the handling of microscopy data. Big data, data deluge, large data, data compliance, data analytics, data integrity, data interoperability, data retention and data lifecycle are terms that have introduced themselves to the electron microscopy sciences. This is largely attributed to the booming development of new microscopy hardware tools. As a result, large digital image files with an average size of one terabyte within one single acquisition session is not uncommon nowadays, especially in the field of cryogenic electron microscopy. This brings along numerous challenges in data transfer, compute and management. In this review, we will discuss in detail the current state of international knowledge on big data in contemporary electron microscopy and how big data can be transferred, computed and managed efficiently and sustainably. Workflows, solutions, approaches and suggestions will be provided, with the example of the latest experiences in Australia. Finally, important principles such as data integrity, data lifetime and the FAIR and CARE principles will be considered.
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Affiliation(s)
- David Poger
- Microscopy Australia, The University of Sydney, Sydney, NSW, 2006, Australia.
| | - Lisa Yen
- Microscopy Australia, The University of Sydney, Sydney, NSW, 2006, Australia
| | - Filip Braet
- Australian Centre for Microscopy and Microanalysis, The University of Sydney, Sydney, NSW, 2006, Australia
- School of Medical Sciences (Molecular and Cellular Biomedicine), The University of Sydney, Sydney, NSW, 2006, Australia
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Iudin A, Korir PK, Somasundharam S, Weyand S, Cattavitello C, Fonseca N, Salih O, Kleywegt GJ, Patwardhan A. EMPIAR: the Electron Microscopy Public Image Archive. Nucleic Acids Res 2023; 51:D1503-D1511. [PMID: 36440762 PMCID: PMC9825465 DOI: 10.1093/nar/gkac1062] [Citation(s) in RCA: 52] [Impact Index Per Article: 52.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 10/21/2022] [Accepted: 10/25/2022] [Indexed: 11/29/2022] Open
Abstract
Public archiving in structural biology is well established with the Protein Data Bank (PDB; wwPDB.org) catering for atomic models and the Electron Microscopy Data Bank (EMDB; emdb-empiar.org) for 3D reconstructions from cryo-EM experiments. Even before the recent rapid growth in cryo-EM, there was an expressed community need for a public archive of image data from cryo-EM experiments for validation, software development, testing and training. Concomitantly, the proliferation of 3D imaging techniques for cells, tissues and organisms using volume EM (vEM) and X-ray tomography (XT) led to calls from these communities to publicly archive such data as well. EMPIAR (empiar.org) was developed as a public archive for raw cryo-EM image data and for 3D reconstructions from vEM and XT experiments and now comprises over a thousand entries totalling over 2 petabytes of data. EMPIAR resources include a deposition system, entry pages, facilities to search, visualize and download datasets, and a REST API for programmatic access to entry metadata. The success of EMPIAR also poses significant challenges for the future in dealing with the very fast growth in the volume of data and in enhancing its reusability.
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Affiliation(s)
- Andrii Iudin
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - Paul K Korir
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - Sriram Somasundharam
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - Simone Weyand
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - Cesare Cattavitello
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - Neli Fonseca
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - Osman Salih
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - Gerard J Kleywegt
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - Ardan Patwardhan
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
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Burley SK, Berman HM, Chiu W, Dai W, Flatt JW, Hudson BP, Kaelber JT, Khare SD, Kulczyk AW, Lawson CL, Pintilie GD, Sali A, Vallat B, Westbrook JD, Young JY, Zardecki C. Electron microscopy holdings of the Protein Data Bank: the impact of the resolution revolution, new validation tools, and implications for the future. Biophys Rev 2022; 14:1281-1301. [PMID: 36474933 PMCID: PMC9715422 DOI: 10.1007/s12551-022-01013-w] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Accepted: 11/06/2022] [Indexed: 12/04/2022] Open
Abstract
As a discipline, structural biology has been transformed by the three-dimensional electron microscopy (3DEM) "Resolution Revolution" made possible by convergence of robust cryo-preservation of vitrified biological materials, sample handling systems, and measurement stages operating a liquid nitrogen temperature, improvements in electron optics that preserve phase information at the atomic level, direct electron detectors (DEDs), high-speed computing with graphics processing units, and rapid advances in data acquisition and processing software. 3DEM structure information (atomic coordinates and related metadata) are archived in the open-access Protein Data Bank (PDB), which currently holds more than 11,000 3DEM structures of proteins and nucleic acids, and their complexes with one another and small-molecule ligands (~ 6% of the archive). Underlying experimental data (3DEM density maps and related metadata) are stored in the Electron Microscopy Data Bank (EMDB), which currently holds more than 21,000 3DEM density maps. After describing the history of the PDB and the Worldwide Protein Data Bank (wwPDB) partnership, which jointly manages both the PDB and EMDB archives, this review examines the origins of the resolution revolution and analyzes its impact on structural biology viewed through the lens of PDB holdings. Six areas of focus exemplifying the impact of 3DEM across the biosciences are discussed in detail (icosahedral viruses, ribosomes, integral membrane proteins, SARS-CoV-2 spike proteins, cryogenic electron tomography, and integrative structure determination combining 3DEM with complementary biophysical measurement techniques), followed by a review of 3DEM structure validation by the wwPDB that underscores the importance of community engagement.
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Affiliation(s)
- Stephen K. Burley
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, New Brunswick, NJ 08901 USA
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer Center, University of California San Diego, La Jolla, CA 92093 USA
- Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, 174 Frelinghuysen Road, Piscataway, NJ 08854 USA
| | - Helen M. Berman
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, 174 Frelinghuysen Road, Piscataway, NJ 08854 USA
| | - Wah Chiu
- Department of Bioengineering, Stanford University, Stanford, CA USA
- Division of CryoEM and Bioimaging, SSRL, SLAC National Accelerator Laboratory, Stanford University, Menlo Park, CA USA
| | - Wei Dai
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Department of Cell Biology and Neuroscience, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
| | - Justin W. Flatt
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
| | - Brian P. Hudson
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
| | - Jason T. Kaelber
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
| | - Sagar D. Khare
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, New Brunswick, NJ 08901 USA
- Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, 174 Frelinghuysen Road, Piscataway, NJ 08854 USA
| | - Arkadiusz W. Kulczyk
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Department of Biochemistry and Microbiology, Rutgers, The State University of New Jersey, Piscataway, NJ 08901 USA
| | - Catherine L. Lawson
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
| | | | - Andrej Sali
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, Quantitative Biosciences Institute, University of California San Francisco, San Francisco, CA 94158 USA
| | - Brinda Vallat
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, New Brunswick, NJ 08901 USA
| | - John D. Westbrook
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, New Brunswick, NJ 08901 USA
| | - Jasmine Y. Young
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
| | - Christine Zardecki
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
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Hartley M, Kleywegt GJ, Patwardhan A, Sarkans U, Swedlow JR, Brazma A. The BioImage Archive - Building a Home for Life-Sciences Microscopy Data. J Mol Biol 2022; 434:167505. [PMID: 35189131 DOI: 10.1016/j.jmb.2022.167505] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 02/04/2022] [Accepted: 02/15/2022] [Indexed: 01/15/2023]
Abstract
Despite the huge impact of data resources in genomics and structural biology, until now there has been no central archive for biological data for all imaging modalities. The BioImage Archive is a new data resource at the European Bioinformatics Institute (EMBL-EBI) designed to fill this gap. In its initial development BioImage Archive accepts bioimaging data associated with publications, in any format, from any imaging modality from the molecular to the organism scale, excluding medical imaging. The BioImage Archive will ensure reproducibility of published studies that derive results from image data and reduce duplication of effort. Most importantly, the BioImage Archive will help scientists to generate new insights through reuse of existing data to answer new biological questions, and provision of training, testing and benchmarking data for development of tools for image analysis. The archive is available at https://www.ebi.ac.uk/bioimage-archive/.
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Affiliation(s)
- Matthew Hartley
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK.
| | - Gerard J Kleywegt
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Ardan Patwardhan
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Ugis Sarkans
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Jason R Swedlow
- Division of Computational Biology, Centre for Gene Regulation and Expression, School of Life Sciences, University of Dundee, Dundee, UK
| | - Alvis Brazma
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK.
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11
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Nguyen NP, Ersoy I, Gotberg J, Bunyak F, White TA. DRPnet: automated particle picking in cryo-electron micrographs using deep regression. BMC Bioinformatics 2021; 22:55. [PMID: 33557750 PMCID: PMC7869254 DOI: 10.1186/s12859-020-03948-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Accepted: 12/22/2020] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND Identification and selection of protein particles in cryo-electron micrographs is an important step in single particle analysis. In this study, we developed a deep learning-based particle picking network to automatically detect particle centers from cryoEM micrographs. This is a challenging task due to the nature of cryoEM data, having low signal-to-noise ratios with variable particle sizes, shapes, distributions, grayscale variations as well as other undesirable artifacts. RESULTS We propose a double convolutional neural network (CNN) cascade for automated detection of particles in cryo-electron micrographs. This approach, entitled Deep Regression Picker Network or "DRPnet", is simple but very effective in recognizing different particle sizes, shapes, distributions and grayscale patterns corresponding to 2D views of 3D particles. Particles are detected by the first network, a fully convolutional regression network (FCRN), which maps the particle image to a continuous distance map that acts like a probability density function of particle centers. Particles identified by FCRN are further refined to reduce false particle detections by the second classification CNN. DRPnet's first CNN pretrained with only a single cryoEM dataset can be used to detect particles from different datasets without retraining. Compared to RELION template-based autopicking, DRPnet results in better particle picking performance with drastically reduced user interactions and processing time. DRPnet also outperforms the state-of-the-art particle picking networks in terms of the supervised detection evaluation metrics recall, precision, and F-measure. To further highlight quality of the picked particle sets, we compute and present additional performance metrics assessing the resulting 3D reconstructions such as number of 2D class averages, efficiency/angular coverage, Rosenthal-Henderson plots and local/global 3D reconstruction resolution. CONCLUSION DRPnet shows greatly improved time-savings to generate an initial particle dataset compared to manual picking, followed by template-based autopicking. Compared to other networks, DRPnet has equivalent or better performance. DRPnet excels on cryoEM datasets that have low contrast or clumped particles. Evaluating other performance metrics, DRPnet is useful for higher resolution 3D reconstructions with decreased particle numbers or unknown symmetry, detecting particles with better angular orientation coverage.
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Affiliation(s)
- Nguyen Phuoc Nguyen
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO USA
| | - Ilker Ersoy
- Institute for Data Science and Informatics, University of Missouri, Columbia, MO USA
| | - Jacob Gotberg
- Research Computing Support Services, University of Missouri, Columbia, MO USA
| | - Filiz Bunyak
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO USA
| | - Tommi A. White
- Department of Biochemistry, University of Missouri, Columbia, MO USA
- Electron Microscopy Core, University of Missouri, Columbia, MO USA
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12
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Lawson CL, Berman HM, Chiu W. Evolving data standards for cryo-EM structures. STRUCTURAL DYNAMICS (MELVILLE, N.Y.) 2020; 7:014701. [PMID: 32002441 PMCID: PMC6980868 DOI: 10.1063/1.5138589] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Accepted: 01/07/2020] [Indexed: 05/04/2023]
Abstract
Electron cryo-microscopy (cryo-EM) is increasingly being used to determine 3D structures of a broad spectrum of biological specimens from molecules to cells. Anticipating this progress in the early 2000s, an international collaboration of scientists with expertise in both cryo-EM and structure data archiving was established (EMDataResource, previously known as EMDataBank). The major goals of the collaboration have been twofold: to develop the necessary infrastructure for archiving cryo-EM-derived density maps and models, and to promote development of cryo-EM structure validation standards. We describe how cryo-EM data archiving and validation have been developed and jointly coordinated for the Electron Microscopy Data Bank and Protein Data Bank archives over the past two decades, as well as the impact of evolving technology on data standards. Just as for X-ray crystallography and nuclear magnetic resonance, engaging the scientific community via workshops and challenging activities has played a central role in developing recommendations and requirements for the cryo-EM structure data archives.
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Affiliation(s)
- Catherine L. Lawson
- Institute for Quantitative Biomedicine and Research Collaboratory for Structural Bioinformatics, Rutgers, The State University of New Jersey, Piscataway, New Jersey 08854, USA
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13
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Berman HM, Adams PD, Bonvin AA, Burley SK, Carragher B, Chiu W, DiMaio F, Ferrin TE, Gabanyi MJ, Goddard TD, Griffin PR, Haas J, Hanke CA, Hoch JC, Hummer G, Kurisu G, Lawson CL, Leitner A, Markley JL, Meiler J, Montelione GT, Phillips GN, Prisner T, Rappsilber J, Schriemer DC, Schwede T, Seidel CAM, Strutzenberg TS, Svergun DI, Tajkhorshid E, Trewhella J, Vallat B, Velankar S, Vuister GW, Webb B, Westbrook JD, White KL, Sali A. Federating Structural Models and Data: Outcomes from A Workshop on Archiving Integrative Structures. Structure 2019; 27:1745-1759. [PMID: 31780431 DOI: 10.1016/j.str.2019.11.002] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2019] [Revised: 10/31/2019] [Accepted: 11/06/2019] [Indexed: 12/23/2022]
Abstract
Structures of biomolecular systems are increasingly computed by integrative modeling. In this approach, a structural model is constructed by combining information from multiple sources, including varied experimental methods and prior models. In 2019, a Workshop was held as a Biophysical Society Satellite Meeting to assess progress and discuss further requirements for archiving integrative structures. The primary goal of the Workshop was to build consensus for addressing the challenges involved in creating common data standards, building methods for federated data exchange, and developing mechanisms for validating integrative structures. The summary of the Workshop and the recommendations that emerged are presented here.
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Affiliation(s)
- Helen M Berman
- Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA; Bridge Institute, Michelson Center, University of Southern California, Los Angeles, CA 90089, USA.
| | - Paul D Adams
- Physical Biosciences Division, Lawrence Berkeley Laboratory, Berkeley, CA 94720-8235, USA; Department of Bioengineering, University of California-Berkeley, Berkeley, CA 94720, USA
| | - Alexandre A Bonvin
- Bijvoet Center for Biomolecular Research, Faculty of Science - Chemistry, Utrecht University, Padualaan 8, 3584 CH Utrecht, the Netherlands
| | - Stephen K Burley
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, The State University of New Jersey, Piscataway, NJ 08854, USA; Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Skaggs School of Pharmacy and Pharmaceutical Sciences and San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA 92093, USA; Rutgers Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, New Brunswick, NJ 08903, USA
| | - Bridget Carragher
- Simons Electron Microscopy Center, New York Structural Biology Center, New York, NY 10027, USA; Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA
| | - Wah Chiu
- Department of Bioengineering, Department of Microbiology and Immunology, Stanford University, Stanford, CA 94305-5447, USA; SLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA
| | - Frank DiMaio
- Department of Biochemistry and Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
| | - Thomas E Ferrin
- Department of Pharmaceutical Chemistry, University of California, San Francisco, CA 94158, USA
| | - Margaret J Gabanyi
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Thomas D Goddard
- Department of Pharmaceutical Chemistry, University of California, San Francisco, CA 94158, USA
| | | | - Juergen Haas
- Swiss Institute of Bioinformatics and Biozentrum, University of Basel, 4056 Basel, Switzerland
| | - Christian A Hanke
- Molecular Physical Chemistry, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
| | - Jeffrey C Hoch
- Department of Molecular Biology and Biophysics, UConn Health, Farmington, CT 06030, USA
| | - Gerhard Hummer
- Department of Theoretical Biophysics, Max Planck Institute of Biophysics, 60438 Frankfurt am Main, Germany; Institute for Biophysics, Goethe University Frankfurt, 60438 Frankfurt am Main, Germany
| | - Genji Kurisu
- Protein Data Bank Japan (PDBj), Institute for Protein Research, Osaka University, Osaka 565-0871, Japan
| | - Catherine L Lawson
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Alexander Leitner
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, 8093 Zurich, Switzerland
| | - John L Markley
- BioMagResBank (BMRB), Biochemistry Department, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Jens Meiler
- Center for Structural Biology, Vanderbilt University, 465 21st Avenue South, Nashville, TN 37221, USA
| | - Gaetano T Montelione
- Center for Advanced Biotechnology and Medicine, Department of Molecular Biology and Biochemistry, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Department of Biochemistry, Robert Wood Johnson Medical School, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytech Institute, Troy, NY 12180, USA
| | - George N Phillips
- BioSciences at Rice and Department of Chemistry, Rice University, Houston, TX 77251, USA
| | - Thomas Prisner
- Institute of Physical and Theoretical Chemistry and Center of Biomolecular Magnetic Resonance, Goethe University Frankfurt, 60438 Frankfurt am Main, Germany
| | - Juri Rappsilber
- Wellcome Trust Centre for Cell Biology, Edinburgh EH9 3JR, Scotland
| | - David C Schriemer
- Department of Biochemistry & Molecular Biology, Robson DNA Science Centre, University of Calgary, Calgary, AB T2N 4N1, Canada
| | - Torsten Schwede
- Swiss Institute of Bioinformatics and Biozentrum, University of Basel, 4056 Basel, Switzerland
| | - Claus A M Seidel
- Molecular Physical Chemistry, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
| | | | - Dmitri I Svergun
- European Molecular Biology Laboratory (EMBL), Hamburg Outstation, Notkestrasse 85, 22607 Hamburg, Germany
| | - Emad Tajkhorshid
- Department of Biochemistry, NIH Center for Macromolecular Modeling and Bioinformatics, Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Jill Trewhella
- School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW 2006, Australia; Department of Chemistry, University of Utah, Salt Lake City, UT 84112, USA
| | - Brinda Vallat
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Sameer Velankar
- Protein Data Bank in Europe (PDBe), European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridgeshire CB10 1SD, UK
| | - Geerten W Vuister
- Department of Molecular and Cell Biology, Leicester Institute of Structural and Chemical Biology, University of Leicester, Leicester LE1 9HN, UK
| | - Benjamin Webb
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - John D Westbrook
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, The State University of New Jersey, Piscataway, NJ 08854, USA; Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Kate L White
- Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA; Bridge Institute, Michelson Center, University of Southern California, Los Angeles, CA 90089, USA
| | - Andrej Sali
- Department of Pharmaceutical Chemistry, University of California, San Francisco, CA 94158, USA; Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA 94158, USA; California Institute for Quantitative Biosciences, University of California, San Francisco, San Francisco, CA 94158, USA.
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Eng ET, Kopylov M, Negro CJ, Dallaykan S, Rice WJ, Jordan KD, Kelley K, Carragher B, Potter CS. Reducing cryoEM file storage using lossy image formats. J Struct Biol 2019; 207:49-55. [PMID: 31121317 DOI: 10.1016/j.jsb.2019.04.013] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2018] [Revised: 03/11/2019] [Accepted: 04/16/2019] [Indexed: 10/26/2022]
Abstract
Recent advances in instrumentation and software for cryoEM have increased the applicability and utility of this method. High levels of automation and faster data acquisition rates require hard decisions to be made regarding data retention. Here we investigate the efficacy of data compression applied to aligned summed movie files. Surprisingly, these images can be compressed using a standard lossy method that reduces file storage by 90-95% and yet can still be processed to provide sub-2 Å reconstructed maps. We do not advocate this as an archival method, but it may provide a useful means for retaining images as an historical record, especially at large facilities.
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Affiliation(s)
- Edward T Eng
- Simons Electron Microscopy Center, New York Structural Biology Center, 89 Convent Ave, New York, NY 10027, USA
| | - Mykhailo Kopylov
- Simons Electron Microscopy Center, New York Structural Biology Center, 89 Convent Ave, New York, NY 10027, USA
| | - Carl J Negro
- Simons Electron Microscopy Center, New York Structural Biology Center, 89 Convent Ave, New York, NY 10027, USA
| | - Sarkis Dallaykan
- Simons Electron Microscopy Center, New York Structural Biology Center, 89 Convent Ave, New York, NY 10027, USA
| | - William J Rice
- Simons Electron Microscopy Center, New York Structural Biology Center, 89 Convent Ave, New York, NY 10027, USA
| | - Kelsey D Jordan
- Simons Electron Microscopy Center, New York Structural Biology Center, 89 Convent Ave, New York, NY 10027, USA
| | - Kotaro Kelley
- Simons Electron Microscopy Center, New York Structural Biology Center, 89 Convent Ave, New York, NY 10027, USA
| | - Bridget Carragher
- Simons Electron Microscopy Center, New York Structural Biology Center, 89 Convent Ave, New York, NY 10027, USA; Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA
| | - Clinton S Potter
- Simons Electron Microscopy Center, New York Structural Biology Center, 89 Convent Ave, New York, NY 10027, USA; Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA.
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15
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Ortega DR, Oikonomou CM, Ding HJ, Rees-Lee P, Jensen GJ. ETDB-Caltech: A blockchain-based distributed public database for electron tomography. PLoS One 2019; 14:e0215531. [PMID: 30986271 PMCID: PMC6464211 DOI: 10.1371/journal.pone.0215531] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2018] [Accepted: 04/03/2019] [Indexed: 01/12/2023] Open
Abstract
Three-dimensional electron microscopy techniques like electron tomography provide valuable insights into cellular structures, and present significant challenges for data storage and dissemination. Here we explored a novel method to publicly release more than 11,000 such datasets, more than 30 TB in total, collected by our group. Our method, based on a peer-to-peer file sharing network built around a blockchain ledger, offers a distributed solution to data storage. In addition, we offer a user-friendly browser-based interface, https://etdb.caltech.edu, for anyone interested to explore and download our data. We discuss the relative advantages and disadvantages of this system and provide tools for other groups to mine our data and/or use the same approach to share their own imaging datasets.
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Affiliation(s)
- Davi R. Ortega
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, United States of America
| | - Catherine M. Oikonomou
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, United States of America
| | - H. Jane Ding
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, United States of America
| | - Prudence Rees-Lee
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, United States of America
| | | | - Grant J. Jensen
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, United States of America
- Howard Hughes Medical Institute, Pasadena, California, United States of America
- * E-mail:
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16
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Affiliation(s)
- Catherine L Lawson
- Institute for Quantitative Biomedicine, Rutgers University, Piscataway, NJ 08854, USA.
| | - Wah Chiu
- Division of Cryo-EM and Bioimaging, SSRL, SLAC National Accelerator Laboratory, Stanford University, Menlo Park, CA 94025, USA; Department of Bioengineering, Department of Microbiology and Immunology, James H. Clark Center, Stanford University, Stanford, CA 94305, USA.
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17
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Baldwin PR, Tan YZ, Eng ET, Rice WJ, Noble AJ, Negro CJ, Cianfrocco MA, Potter CS, Carragher B. Big data in cryoEM: automated collection, processing and accessibility of EM data. Curr Opin Microbiol 2017; 43:1-8. [PMID: 29100109 DOI: 10.1016/j.mib.2017.10.005] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2017] [Revised: 09/27/2017] [Accepted: 10/09/2017] [Indexed: 11/24/2022]
Abstract
The scope and complexity of cryogenic electron microscopy (cryoEM) data has greatly increased, and will continue to do so, due to recent and ongoing technical breakthroughs that have led to much improved resolutions for macromolecular structures solved using this method. This big data explosion includes single particle data as well as tomographic tilt series, both generally acquired as direct detector movies of ∼10-100 frames per image or per tilt-series. We provide a brief survey of the developments leading to the current status, and describe existing cryoEM pipelines, with an emphasis on the scope of data acquisition, methods for automation, and use of cloud storage and computing.
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Affiliation(s)
- Philip R Baldwin
- The National Resource for Automated Molecular Microscopy, Simons Electron Microscopy Center, New York Structural Biology Center, 89 Convent Ave, New York, NY 10027, USA
| | - Yong Zi Tan
- The National Resource for Automated Molecular Microscopy, Simons Electron Microscopy Center, New York Structural Biology Center, 89 Convent Ave, New York, NY 10027, USA; Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA
| | - Edward T Eng
- The National Resource for Automated Molecular Microscopy, Simons Electron Microscopy Center, New York Structural Biology Center, 89 Convent Ave, New York, NY 10027, USA
| | - William J Rice
- The National Resource for Automated Molecular Microscopy, Simons Electron Microscopy Center, New York Structural Biology Center, 89 Convent Ave, New York, NY 10027, USA
| | - Alex J Noble
- The National Resource for Automated Molecular Microscopy, Simons Electron Microscopy Center, New York Structural Biology Center, 89 Convent Ave, New York, NY 10027, USA
| | - Carl J Negro
- The National Resource for Automated Molecular Microscopy, Simons Electron Microscopy Center, New York Structural Biology Center, 89 Convent Ave, New York, NY 10027, USA
| | - Michael A Cianfrocco
- Life Sciences Institute and Department of Biological Chemistry, University of Michigan, Ann Arbor, MI 48109, USA
| | - Clinton S Potter
- The National Resource for Automated Molecular Microscopy, Simons Electron Microscopy Center, New York Structural Biology Center, 89 Convent Ave, New York, NY 10027, USA; Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA
| | - Bridget Carragher
- The National Resource for Automated Molecular Microscopy, Simons Electron Microscopy Center, New York Structural Biology Center, 89 Convent Ave, New York, NY 10027, USA; Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA.
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18
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Patwardhan A, Brandt R, Butcher SJ, Collinson L, Gault D, Grünewald K, Hecksel C, Huiskonen JT, Iudin A, Jones ML, Korir PK, Koster AJ, Lagerstedt I, Lawson CL, Mastronarde D, McCormick M, Parkinson H, Rosenthal PB, Saalfeld S, Saibil HR, Sarntivijai S, Solanes Valero I, Subramaniam S, Swedlow JR, Tudose I, Winn M, Kleywegt GJ. Building bridges between cellular and molecular structural biology. eLife 2017; 6:e25835. [PMID: 28682240 PMCID: PMC5524535 DOI: 10.7554/elife.25835] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2017] [Accepted: 06/30/2017] [Indexed: 11/13/2022] Open
Abstract
The integration of cellular and molecular structural data is key to understanding the function of macromolecular assemblies and complexes in their in vivo context. Here we report on the outcomes of a workshop that discussed how to integrate structural data from a range of public archives. The workshop identified two main priorities: the development of tools and file formats to support segmentation (that is, the decomposition of a three-dimensional volume into regions that can be associated with defined objects), and the development of tools to support the annotation of biological structures.
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Affiliation(s)
- Ardan Patwardhan
- Cellular Structure and 3D Bioimaging, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, United Kingdom
| | | | - Sarah J Butcher
- Institute of Biotechnology and the Department of Biosciences, University of Helsinki, Helsinki, Finland
| | - Lucy Collinson
- Electron Microscopy Science Technology Platform, Francis Crick Institute, London, United Kingdom
| | - David Gault
- Centre for Gene Regulation and Expression, University of Dundee, Dundee, United Kingdom
| | - Kay Grünewald
- Division of Structural Biology, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Corey Hecksel
- National Center for Macromolecular Imaging, Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, United States
| | - Juha T Huiskonen
- Division of Structural Biology, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Andrii Iudin
- Cellular Structure and 3D Bioimaging, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, United Kingdom
| | - Martin L Jones
- Electron Microscopy Science Technology Platform, Francis Crick Institute, London, United Kingdom
| | - Paul K Korir
- Cellular Structure and 3D Bioimaging, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, United Kingdom
| | - Abraham J Koster
- Department of Molecular Cell Biology, Leiden University Medical Center, Leiden, The Netherlands
| | - Ingvar Lagerstedt
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, United Kingdom
| | - Catherine L Lawson
- Center for Integrative Proteomics Research and the Research Collaboratory for Structural Bioinformatics, Rutgers, The State University of New Jersey, Piscataway, United States
| | - David Mastronarde
- Department of Molecular, Cellular, and Developmental Biology, University of Colorado, Boulder, United States
| | | | - Helen Parkinson
- Molecular Archival Resources, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, United Kingdom
| | - Peter B Rosenthal
- Structural Biology of Cells and Viruses, Francis Crick Institute, London, United Kingdom
| | - Stephan Saalfeld
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Helen R Saibil
- Institute of Structural and Molecular Biology, Department of Crystallography, Birkbeck College, London, United Kingdom
| | - Sirarat Sarntivijai
- Molecular Archival Resources, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, United Kingdom
| | - Irene Solanes Valero
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, United Kingdom
| | - Sriram Subramaniam
- Laboratory for Cell Biology, Center for Cancer Research, National Cancer Institute, Bethesda, United States
| | - Jason R Swedlow
- Centre for Gene Regulation and Expression and the Division of Computational Biology, University of Dundee, Dundee, United Kingdom
| | - Ilinca Tudose
- Molecular Archival Resources, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, United Kingdom
| | - Martyn Winn
- Scientific Computing Department, Science and Technology Facilities Council, Research Complex at Harwell, Didcot, United Kingdom
| | - Gerard J Kleywegt
- Molecular and Cellular Structure Cluster, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, United Kingdom
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19
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Patwardhan A. Trends in the Electron Microscopy Data Bank (EMDB). ACTA CRYSTALLOGRAPHICA SECTION D-STRUCTURAL BIOLOGY 2017; 73:503-508. [PMID: 28580912 PMCID: PMC5458492 DOI: 10.1107/s2059798317004181] [Citation(s) in RCA: 67] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/31/2016] [Accepted: 03/14/2017] [Indexed: 12/11/2022]
Abstract
The Electron Microscopy Data Bank (EMDB), the public archive for three-dimensional EM reconstructions, is an invaluable resource for obtaining a birds-eye view of trends affecting the field of cryo-EM. EMDB is growing rapidly, with almost a quarter of the entries having been released over the past year. Recent technological advances, such as the introduction of the direct electron detector, have transformed the field of cryo-EM and the landscape of molecular and cellular structural biology. This study analyses these trends from the vantage point of the Electron Microscopy Data Bank (EMDB), the public archive for three-dimensional EM reconstructions. Over 1000 entries were released in 2016, representing almost a quarter of the total number of entries (4431). Structures at better than 6 Å resolution now represent one of the fastest-growing categories, while the share of annually released tomography-related structures is approaching 20%. The use of direct electron detectors is growing very rapidly: they were used for 70% of the structures released in 2016, in contrast to none before 2011. Microscopes from FEI have an overwhelming lead in terms of usage, and the use of the RELION software package continues to grow rapidly after having attained a leading position in the field. China is rapidly emerging as a major player in the field, supplementing the US, Germany and the UK as the big four. Similarly, Tsinghua University ranks only second to the MRC Laboratory for Molecular Biology in terms of involvement in publications associated with cryo-EM structures at better than 4 Å resolution. Overall, the numbers point to a rapid democratization of the field, with more countries and institutes becoming involved.
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Affiliation(s)
- Ardan Patwardhan
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton CB10 1SD, England
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20
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Use of evolutionary information in the fitting of atomic level protein models in low resolution cryo-EM map of a protein assembly improves the accuracy of the fitting. J Struct Biol 2016; 195:294-305. [PMID: 27444391 DOI: 10.1016/j.jsb.2016.07.012] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2015] [Revised: 07/15/2016] [Accepted: 07/18/2016] [Indexed: 11/22/2022]
Abstract
Protein-protein interface residues, especially those at the core of the interface, exhibit higher conservation than residues in solvent exposed regions. Here, we explore the ability of this differential conservation to evaluate fittings of atomic models in low-resolution cryo-EM maps and select models from the ensemble of solutions that are often proposed by different model fitting techniques. As a prelude, using a non-redundant and high-resolution structural dataset involving 125 permanent and 95 transient complexes, we confirm that core interface residues are conserved significantly better than nearby non-interface residues and this result is used in the cryo-EM map analysis. From the analysis of inter-component interfaces in a set of fitted models associated with low-resolution cryo-EM maps of ribosomes, chaperones and proteasomes we note that a few poorly conserved residues occur at interfaces. Interestingly a few conserved residues are not in the interface, though they are close to the interface. These observations raise the potential requirement of refitting the models in the cryo-EM maps. We show that sampling an ensemble of models and selection of models with high residue conservation at the interface and in good agreement with the density helps in improving the accuracy of the fit. This study indicates that evolutionary information can serve as an additional input to improve and validate fitting of atomic models in cryo-EM density maps.
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21
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Abstract
CryoEM in structural biology is currently served by three public archives-EMDB for 3DEM reconstructions, PDB for models built from 3DEM reconstructions, and EMPIAR for the raw 2D image data used to obtain the 3DEM reconstructions. These archives play a vital role for both the structural community and the wider biological community in making the data accessible so that results may be reused, reassessed, and integrated with other structural and bioinformatics resources. The important role of the archives is underpinned by the fact that many journals mandate the deposition of data to PDB and EMDB on publication. The field is currently undergoing transformative changes where on the one hand high-resolution structures are becoming a routine occurrence while on the other hand electron tomography is enabling the study of macromolecules in the cellular context. Concomitantly the archives are evolving to best serve their stakeholder communities. In this chapter, we describe the current state of the archives, resources available for depositing, accessing, searching, visualizing and validating data, on-going community-wide initiatives and opportunities, and challenges for the future.
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Affiliation(s)
- A Patwardhan
- Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, United Kingdom.
| | - C L Lawson
- Research Collaboratory for Structural Bioinformatics, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ, United States.
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22
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Joseph AP, Malhotra S, Burnley T, Wood C, Clare DK, Winn M, Topf M. Refinement of atomic models in high resolution EM reconstructions using Flex-EM and local assessment. Methods 2016; 100:42-9. [PMID: 26988127 PMCID: PMC4854230 DOI: 10.1016/j.ymeth.2016.03.007] [Citation(s) in RCA: 75] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2016] [Revised: 03/09/2016] [Accepted: 03/14/2016] [Indexed: 01/19/2023] Open
Abstract
As the resolutions of Three Dimensional Electron Microscopic reconstructions of biological macromolecules are being improved, there is a need for better fitting and refinement methods at high resolutions and robust approaches for model assessment. Flex-EM/MODELLER has been used for flexible fitting of atomic models in intermediate-to-low resolution density maps of different biological systems. Here, we demonstrate the suitability of the method to successfully refine structures at higher resolutions (2.5-4.5Å) using both simulated and experimental data, including a newly processed map of Apo-GroEL. A hierarchical refinement protocol was adopted where the rigid body definitions are relaxed and atom displacement steps are reduced progressively at successive stages of refinement. For the assessment of local fit, we used the SMOC (segment-based Manders' overlap coefficient) score, while the model quality was checked using the Qmean score. Comparison of SMOC profiles at different stages of refinement helped in detecting regions that are poorly fitted. We also show how initial model errors can have significant impact on the goodness-of-fit. Finally, we discuss the implementation of Flex-EM in the CCP-EM software suite.
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Affiliation(s)
- Agnel Praveen Joseph
- Institute of Structural and Molecular Biology, Department of Biological Sciences, Birkbeck College, University of London, Malet Street, London WC1E 7HX, United Kingdom
| | - Sony Malhotra
- Scientific Computing Department, Science and Technology Facilities Council, Research Complex at Harwell, Didcot OX11 0FA, United Kingdom
| | - Tom Burnley
- Scientific Computing Department, Science and Technology Facilities Council, Research Complex at Harwell, Didcot OX11 0FA, United Kingdom
| | - Chris Wood
- Scientific Computing Department, Science and Technology Facilities Council, Research Complex at Harwell, Didcot OX11 0FA, United Kingdom
| | - Daniel K Clare
- Electron Bio-Imaging Centre (eBIC), Diamond Light Source, Harwell Science & Innovation Campus, OX11 0DE, United Kingdom
| | - Martyn Winn
- Scientific Computing Department, Science and Technology Facilities Council, Research Complex at Harwell, Didcot OX11 0FA, United Kingdom.
| | - Maya Topf
- Institute of Structural and Molecular Biology, Department of Biological Sciences, Birkbeck College, University of London, Malet Street, London WC1E 7HX, United Kingdom.
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23
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24
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Rawson S, Davies S, Lippiat JD, Muench SP. The changing landscape of membrane protein structural biology through developments in electron microscopy. Mol Membr Biol 2016; 33:12-22. [PMID: 27608730 PMCID: PMC5206964 DOI: 10.1080/09687688.2016.1221533] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2016] [Revised: 07/14/2016] [Accepted: 07/19/2016] [Indexed: 11/30/2022]
Abstract
Membrane proteins are ubiquitous in biology and are key targets for therapeutic development. Despite this, our structural understanding has lagged behind that of their soluble counterparts. This review provides an overview of this important field, focusing in particular on the recent resurgence of electron microscopy (EM) and the increasing role it has to play in the structural studies of membrane proteins, and illustrating this through several case studies. In addition, we examine some of the challenges remaining in structural determination, and what steps are underway to enhance our knowledge of these enigmatic proteins.
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Affiliation(s)
- Shaun Rawson
- School of Biomedical Sciences, Faculty of Biological Sciences, University of Leeds,
Leeds,
UK
| | - Simon Davies
- School of Biomedical Sciences, Faculty of Biological Sciences, University of Leeds,
Leeds,
UK
| | - Jonathan D. Lippiat
- School of Biomedical Sciences, Faculty of Biological Sciences, University of Leeds,
Leeds,
UK
| | - Stephen P. Muench
- School of Biomedical Sciences, Faculty of Biological Sciences, University of Leeds,
Leeds,
UK
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25
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Salavert-Torres J, Iudin A, Lagerstedt I, Sanz-García E, Kleywegt GJ, Patwardhan A. Web-based volume slicer for 3D electron-microscopy data from EMDB. J Struct Biol 2016; 194:164-70. [PMID: 26876163 PMCID: PMC4819904 DOI: 10.1016/j.jsb.2016.02.012] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2015] [Revised: 02/08/2016] [Accepted: 02/09/2016] [Indexed: 12/05/2022]
Abstract
We describe the functionality and design of the Volume slicer – a web-based slice viewer for EMDB entries. This tool uniquely provides the facility to view slices from 3D EM reconstructions along the three orthogonal axes and to rapidly switch between them and navigate through the volume. We have employed multiple rounds of user-experience testing with members of the EM community to ensure that the interface is easy and intuitive to use and the information provided is relevant. The impetus to develop the Volume slicer has been calls from the EM community to provide web-based interactive visualisation of 2D slice data. This would be useful for quick initial checks of the quality of a reconstruction. Again in response to calls from the community, we plan to further develop the Volume slicer into a fully-fledged Volume browser that provides integrated visualisation of EMDB and PDB entries from the molecular to the cellular scale.
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Affiliation(s)
- José Salavert-Torres
- Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton CB10 1SD, United Kingdom; Present address: Universitat Politècnica de València, DISCA, Edificio 1G - Lab 3S-15, Camino de Vera S/N, 46022 València, Spain.
| | - Andrii Iudin
- Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton CB10 1SD, United Kingdom.
| | - Ingvar Lagerstedt
- Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton CB10 1SD, United Kingdom.
| | - Eduardo Sanz-García
- Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton CB10 1SD, United Kingdom.
| | - Gerard J Kleywegt
- Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton CB10 1SD, United Kingdom.
| | - Ardan Patwardhan
- Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton CB10 1SD, United Kingdom.
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26
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Dahmen T, Marsalek L, Marniok N, Turoňová B, Bogachev S, Trampert P, Nickels S, Slusallek P. The Ettention software package. Ultramicroscopy 2016; 161:110-118. [DOI: 10.1016/j.ultramic.2015.10.012] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2015] [Revised: 10/09/2015] [Accepted: 10/11/2015] [Indexed: 11/29/2022]
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27
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Brown JR, Schwartz CL, Heumann JM, Dawson SC, Hoenger A. A detailed look at the cytoskeletal architecture of the Giardia lamblia ventral disc. J Struct Biol 2016; 194:38-48. [PMID: 26821343 DOI: 10.1016/j.jsb.2016.01.011] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2015] [Revised: 01/21/2016] [Accepted: 01/24/2016] [Indexed: 11/16/2022]
Abstract
Giardia lamblia is a protistan parasite that infects and colonizes the small intestine of mammals. It is widespread and particularly endemic in the developing world. Here we present a detailed structural study by 3-D negative staining and cryo-electron tomography of a unique Giardia organelle, the ventral disc. The disc is composed of a regular array of microtubules and associated sheets, called microribbons that form a large spiral, held together by a myriad of mostly unknown associated proteins. In a previous study we analyzed by cryo-electron tomography the central microtubule portion (here called disc body) of the ventral disc and found a large portion of microtubule associated inner (MIPs) and outer proteins (MAPs) that render these microtubules hyper-stable. With this follow-up study we expanded our 3-D analysis to different parts of the disc such as the ventral and dorsal areas of the overlap zone, as well as the outer disc margin. There are intrinsic location-specific characteristics in the composition of microtubule-associated proteins between these regions, as well as large differences between the overall architecture of microtubules and microribbons. The lateral packing of microtubule-microribbon complexes varies substantially, and closer packing often comes with contracted lateral tethers that seem to hold the disc together. It appears that the marginal microtubule-microribbon complexes function as outer, laterally contractible lids that may help the cell to clamp onto the intestinal microvilli. Furthermore, we analyzed length, quantity, curvature and distribution between different zones of the disc, which we found to differ from previous publications.
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Affiliation(s)
- Joanna R Brown
- University of Colorado, Dept. MCD Biology, Boulder, CO 80309, USA
| | - Cindi L Schwartz
- University of Colorado, Dept. MCD Biology, Boulder, CO 80309, USA
| | - John M Heumann
- University of Colorado, Dept. MCD Biology, Boulder, CO 80309, USA
| | - Scott C Dawson
- University of California Davis, Dept. Microbiology and Molecular Genetics, Davis, CA 95616, USA
| | - Andreas Hoenger
- University of Colorado, Dept. MCD Biology, Boulder, CO 80309, USA.
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28
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Carroni M, Saibil HR. Cryo electron microscopy to determine the structure of macromolecular complexes. Methods 2015; 95:78-85. [PMID: 26638773 PMCID: PMC5405050 DOI: 10.1016/j.ymeth.2015.11.023] [Citation(s) in RCA: 60] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2015] [Revised: 11/14/2015] [Accepted: 11/26/2015] [Indexed: 01/28/2023] Open
Abstract
Structural biology. Cryo electron microscopy. Macromolecular complexes. Single particle analysis.
Cryo-electron microscopy (cryo-EM) is a structural molecular and cellular biology technique that has experienced major advances in recent years. Technological developments in image recording as well as in processing software make it possible to obtain three-dimensional reconstructions of macromolecular assemblies at near-atomic resolution that were formerly obtained only by X-ray crystallography or NMR spectroscopy. In parallel, cryo-electron tomography has also benefitted from these technological advances, so that visualization of irregular complexes, organelles or whole cells with their molecular machines in situ has reached subnanometre resolution. Cryo-EM can therefore address a broad range of biological questions. The aim of this review is to provide a brief overview of the principles and current state of the cryo-EM field.
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Affiliation(s)
- Marta Carroni
- ISMB, Birkbeck College, Malet St, London WC1E 7HX, UK
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29
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Lawson CL, Patwardhan A, Baker ML, Hryc C, Garcia ES, Hudson BP, Lagerstedt I, Ludtke SJ, Pintilie G, Sala R, Westbrook JD, Berman HM, Kleywegt GJ, Chiu W. EMDataBank unified data resource for 3DEM. Nucleic Acids Res 2015; 44:D396-403. [PMID: 26578576 PMCID: PMC4702818 DOI: 10.1093/nar/gkv1126] [Citation(s) in RCA: 177] [Impact Index Per Article: 19.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2015] [Accepted: 10/15/2015] [Indexed: 01/10/2023] Open
Abstract
Three-dimensional Electron Microscopy (3DEM) has become a key experimental method in structural biology for a broad spectrum of biological specimens from molecules to cells. The EMDataBank project provides a unified portal for deposition, retrieval and analysis of 3DEM density maps, atomic models and associated metadata (emdatabank.org). We provide here an overview of the rapidly growing 3DEM structural data archives, which include maps in EM Data Bank and map-derived models in the Protein Data Bank. In addition, we describe progress and approaches toward development of validation protocols and methods, working with the scientific community, in order to create a validation pipeline for 3DEM data.
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Affiliation(s)
- Catherine L Lawson
- Department of Chemistry and Chemical Biology and Research Collaboratory for Structural Bioinformatics, Rutgers, The State University of New Jersey, 610 Taylor Road Piscataway, NJ 08854, USA
| | - Ardan Patwardhan
- Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Matthew L Baker
- Verna and Marrs McLean Department of Biochemistry & Molecular Biology, National Center for Macromolecular Imaging, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 70030, USA
| | - Corey Hryc
- Verna and Marrs McLean Department of Biochemistry & Molecular Biology, National Center for Macromolecular Imaging, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 70030, USA
| | - Eduardo Sanz Garcia
- Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Brian P Hudson
- Department of Chemistry and Chemical Biology and Research Collaboratory for Structural Bioinformatics, Rutgers, The State University of New Jersey, 610 Taylor Road Piscataway, NJ 08854, USA
| | - Ingvar Lagerstedt
- Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Steven J Ludtke
- Verna and Marrs McLean Department of Biochemistry & Molecular Biology, National Center for Macromolecular Imaging, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 70030, USA
| | - Grigore Pintilie
- Verna and Marrs McLean Department of Biochemistry & Molecular Biology, National Center for Macromolecular Imaging, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 70030, USA
| | - Raul Sala
- Department of Chemistry and Chemical Biology and Research Collaboratory for Structural Bioinformatics, Rutgers, The State University of New Jersey, 610 Taylor Road Piscataway, NJ 08854, USA
| | - John D Westbrook
- Department of Chemistry and Chemical Biology and Research Collaboratory for Structural Bioinformatics, Rutgers, The State University of New Jersey, 610 Taylor Road Piscataway, NJ 08854, USA
| | - Helen M Berman
- Department of Chemistry and Chemical Biology and Research Collaboratory for Structural Bioinformatics, Rutgers, The State University of New Jersey, 610 Taylor Road Piscataway, NJ 08854, USA
| | - Gerard J Kleywegt
- Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Wah Chiu
- Verna and Marrs McLean Department of Biochemistry & Molecular Biology, National Center for Macromolecular Imaging, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 70030, USA
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30
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Abstract
Validation is a necessity to trust the structures solved by electron microscopy by single particle techniques. The impressive achievements in single particle reconstruction fuel its expansion beyond a small community of image processing experts. This poses the risk of inappropriate data processing with dubious results. Nowhere is it more clearly illustrated than in the recovery of a reference density map from pure noise aligned to that map—a phantom in the noise. Appropriate use of existing validating methods such as resolution-limited alignment and the processing of independent data sets (“gold standard”) avoid this pitfall. However, these methods can be undermined by biases introduced in various subtle ways. How can we test that a map is a coherent structure present in the images selected from the micrographs? In stead of viewing the phantom emerging from noise as a cautionary tale, it should be used as a defining baseline. Any map is always recoverable from noise images, provided a sufficient number of images are aligned and used in reconstruction. However, with smaller numbers of images, the expected coherence in the real particle images should yield better reconstructions than equivalent numbers of noise or background images, even without masking or imposing resolution limits as potential biases. The validation test proposed is therefore a simple alignment of a limited number of micrograph and noise images against the final reconstruction as reference, demonstrating that the micrograph images yield a better reconstruction. I examine synthetic cases to relate the resolution of a reconstruction to the alignment error as a function of the signal-to-noise ratio. I also administered the test to real cases of publicly available data. Adopting such a test can aid the microscopist in assessing the usefulness of the micrographs taken before committing to lengthy processing with questionable outcomes.
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Affiliation(s)
- J Bernard Heymann
- National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health, 50 South Dr, Bethesda, MD 20892, USA
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31
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Saibil HR, Grünewald K, Stuart DI. A national facility for biological cryo-electron microscopy. ACTA CRYSTALLOGRAPHICA. SECTION D, BIOLOGICAL CRYSTALLOGRAPHY 2015; 71:127-35. [PMID: 25615867 PMCID: PMC4304693 DOI: 10.1107/s1399004714025280] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/09/2014] [Accepted: 11/18/2014] [Indexed: 11/16/2022]
Abstract
Three-dimensional electron microscopy is an enormously powerful tool for structural biologists. It is now able to provide an understanding of the molecular machinery of cells, disease processes and the actions of pathogenic organisms from atomic detail through to the cellular context. However, cutting-edge research in this field requires very substantial resources for equipment, infrastructure and expertise. Here, a brief overview is provided of the plans for a UK national three-dimensional electron-microscopy facility for integrated structural biology to enable internationally leading research on the machinery of life. State-of-the-art equipment operated with expert support will be provided, optimized for both atomic-level single-particle analysis of purified macromolecules and complexes and for tomography of cell sections. The access to and organization of the facility will be modelled on the highly successful macromolecular crystallography (MX) synchrotron beamlines, and will be embedded at the Diamond Light Source, facilitating the development of user-friendly workflows providing near-real-time experimental feedback.
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Affiliation(s)
- Helen R. Saibil
- Crystallography, Institute for Structural and Molecular Biology, Birkbeck College, Malet Street, London WC1E 7HX, England
| | - Kay Grünewald
- Division of Structural Biology, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, England
| | - David I. Stuart
- Division of Structural Biology, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, England
- Diamond Light Source, Didcot OX11 0DE, England
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32
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Meyerson JR, Rao P, Kumar J, Chittori S, Banerjee S, Pierson J, Mayer ML, Subramaniam S. Self-assembled monolayers improve protein distribution on holey carbon cryo-EM supports. Sci Rep 2014; 4:7084. [PMID: 25403871 PMCID: PMC4235105 DOI: 10.1038/srep07084] [Citation(s) in RCA: 65] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2014] [Accepted: 10/20/2014] [Indexed: 01/04/2023] Open
Abstract
Poor partitioning of macromolecules into the holes of holey carbon support grids frequently limits structural determination by single particle cryo-electron microscopy (cryo-EM). Here, we present a method to deposit, on gold-coated carbon grids, a self-assembled monolayer whose surface properties can be controlled by chemical modification. We demonstrate the utility of this approach to drive partitioning of ionotropic glutamate receptors into the holes, thereby enabling 3D structural analysis using cryo-EM methods.
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Affiliation(s)
- Joel R. Meyerson
- Laboratory of Cell Biology, Center for Cancer Research, NCI, NIH, Bethesda, MD 20892
| | - Prashant Rao
- Laboratory of Cell Biology, Center for Cancer Research, NCI, NIH, Bethesda, MD 20892
| | - Janesh Kumar
- Laboratory of Cellular and Molecular Neurophysiology, Porter Neuroscience Research Center, NICHD, NIH, Bethesda MD 20892
| | - Sagar Chittori
- Laboratory of Cellular and Molecular Neurophysiology, Porter Neuroscience Research Center, NICHD, NIH, Bethesda MD 20892
| | - Soojay Banerjee
- Laboratory of Cell Biology, Center for Cancer Research, NCI, NIH, Bethesda, MD 20892
| | | | - Mark L. Mayer
- Laboratory of Cellular and Molecular Neurophysiology, Porter Neuroscience Research Center, NICHD, NIH, Bethesda MD 20892
| | - Sriram Subramaniam
- Laboratory of Cell Biology, Center for Cancer Research, NCI, NIH, Bethesda, MD 20892
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33
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Patwardhan A, Ashton A, Brandt R, Butcher S, Carzaniga R, Chiu W, Collinson L, Doux P, Duke E, Ellisman MH, Franken E, Grünewald K, Heriche JK, Koster A, Kühlbrandt W, Lagerstedt I, Larabell C, Lawson CL, Saibil HR, Sanz-García E, Subramaniam S, Verkade P, Swedlow JR, Kleywegt GJ. A 3D cellular context for the macromolecular world. Nat Struct Mol Biol 2014; 21:841-5. [PMID: 25289590 PMCID: PMC4346196 DOI: 10.1038/nsmb.2897] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
We report the outcomes of the discussion initiated at the workshop entitled A 3D Cellular Context for the Macromolecular World and propose how data from emerging three-dimensional (3D) cellular imaging techniques—such as electron tomography, 3D scanning electron microscopy and soft X-ray tomography—should be archived, curated, validated and disseminated, to enable their interpretation and reuse by the biomedical community.
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Affiliation(s)
- Ardan Patwardhan
- Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | | | | | - Sarah Butcher
- Institute of Biotechnology, University of Helsinki, Helsinki, Finland
| | - Raffaella Carzaniga
- Electron Microscopy Unit, Cancer Research UK London Research Institute, London, UK
| | - Wah Chiu
- National Center for Macromolecular Imaging, Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, Texas
| | - Lucy Collinson
- Electron Microscopy Unit, Cancer Research UK London Research Institute, London, UK
| | - Pascal Doux
- FEI Visualization Sciences Group, Mérignac, France
| | | | - Mark H Ellisman
- Center for Research in Biological Systems, National Center for Microscopy and Imaging Research (NCMIR), University of California, San Diego, San Diego, California, USA
| | - Erik Franken
- FEI Electron Optics B.V., Eindhoven, the Netherlands
| | - Kay Grünewald
- Division of Structural Biology, Wellcome Trust Centre for Human Genetics, Oxford, UK
| | - Jean-Karim Heriche
- Cell Biology and Biophysics Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Abraham Koster
- Department of Molecular Cell Biology, Leiden University Medical Center, Leiden, the Netherlands
| | - Werner Kühlbrandt
- Department of Structural Biology, Max Planck Institute for Biophysics, Frankfurt, Germany
| | - Ingvar Lagerstedt
- Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Carolyn Larabell
- Department of Anatomy, University of California, San Francisco, San Francisco, California, USA
| | - Catherine L Lawson
- Research Collaboratory for Structural Bioinformatics, Rutgers University, Piscataway, New Jersey, USA
| | - Helen R Saibil
- Institute of Structural and Molecular Biology, Department of Crystallography, Birkbeck College, London, UK
| | - Eduardo Sanz-García
- Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Sriram Subramaniam
- Center for Cancer Research, National Cancer Institute, Bethesda, Maryland, USA
| | - Paul Verkade
- Wolfson Bioimaging Facility, School of Biochemistry, University of Bristol, Bristol, UK
| | - Jason R Swedlow
- Centre for Gene Regulation and Expression, University of Dundee, Dundee, UK
| | - Gerard J Kleywegt
- Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
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34
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Hoenger A. High-resolution cryo-electron microscopy on macromolecular complexes and cell organelles. PROTOPLASMA 2014; 251:417-427. [PMID: 24390311 PMCID: PMC3927062 DOI: 10.1007/s00709-013-0600-1] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/09/2013] [Accepted: 12/12/2013] [Indexed: 06/03/2023]
Abstract
Cryo-electron microscopy techniques and computational 3-D reconstruction of macromolecular assemblies are tightly linked tools in modern structural biology. This symbiosis has produced vast amounts of detailed information on the structure and function of biological macromolecules. Typically, one of two fundamentally different strategies is used depending on the specimens and their environment. A: 3-D reconstruction based on repetitive and structurally identical unit cells that allow for averaging, and B: tomographic 3-D reconstructions where tilt-series between approximately ± 60 and ± 70° at small angular increments are collected from highly complex and flexible structures that are beyond averaging procedures, at least during the first round of 3-D reconstruction. Strategies of group A are averaging-based procedures and collect large number of 2-D projections at different angles that are computationally aligned, averaged together, and back-projected in 3-D space to reach a most complete 3-D dataset with high resolution, today often down to atomic detail. Evidently, success relies on structurally repetitive particles and an aligning procedure that unambiguously determines the angular relationship of all 2-D projections with respect to each other. The alignment procedure of small particles may rely on their packing into a regular array such as a 2-D crystal, an icosahedral (viral) particle, or a helical assembly. Critically important for cryo-methods, each particle will only be exposed once to the electron beam, making these procedures optimal for highest-resolution studies where beam-induced damage is a significant concern. In contrast, tomographic 3-D reconstruction procedures (group B) do not rely on averaging, but collect an entire dataset from the very same structure of interest. Data acquisition requires collecting a large series of tilted projections at angular increments of 1-2° or less and a tilt range of ± 60° or more. Accordingly, tomographic data collection exposes its specimens to a large electron dose, which is particularly problematic for frozen-hydrated samples. Currently, cryo-electron tomography is a rapidly emerging technology, on one end driven by the newest developments of hardware such as super-stabile microscopy stages as well as the latest generation of direct electron detectors and cameras. On the other end, success also strongly depends on new software developments on all kinds of fronts such as tilt-series alignment and back-projection procedures that are all adapted to the very low-dose and therefore very noisy primary data. Here, we will review the status quo of cryo-electron microscopy and discuss the future of cellular cryo-electron tomography from data collection to data analysis, CTF-correction of tilt-series, post-tomographic sub-volume averaging, and 3-D particle classification. We will also discuss the pros and cons of plunge freezing of cellular specimens to vitrified sectioning procedures and their suitability for post-tomographic volume averaging despite multiple artifacts that may distort specimens to some degree.
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Affiliation(s)
- Andreas Hoenger
- Department of Molecular, Cellular and Developmental Biology, University of Colorado at Boulder, Boulder, CO, 80309, USA,
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35
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Wasilewski S, Rosenthal PB. Web server for tilt-pair validation of single particle maps from electron cryomicroscopy. J Struct Biol 2014; 186:122-31. [PMID: 24582855 DOI: 10.1016/j.jsb.2014.02.012] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2013] [Revised: 02/18/2014] [Accepted: 02/19/2014] [Indexed: 11/16/2022]
Abstract
Three-dimensional structures of biological assemblies may be calculated from images of single particles obtained by electron cryomicroscopy. A key step is the correct determination of the orientation of the particle in individual image projections. A useful tool for validation of the quality of a 3D map and its consistency with images is tilt-pair analysis. In a successful tilt-pair test, the relative angle between orientations assigned to each image of a tilt-pair agrees with the known relative rotation angle of the microscope specimen holder during the experiment. To make the procedure easy to apply to the increasing number of single particle maps, we have developed software and a web server for tilt-pair analysis. The tilt-pair analysis program reports the overall agreement of the assigned orientations with the known tilt angle and axis of the experiment and the distribution of tilt transformations for individual particles recorded in a single image field. We illustrate application of the validation tool to several single particle specimens and describe how to interpret the scores.
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Affiliation(s)
- Sebastian Wasilewski
- Division of Physical Biochemistry, MRC National Institute for Medical Research, The Ridgeway, Mill Hill, London NW7 1AA, United Kingdom
| | - Peter B Rosenthal
- Division of Physical Biochemistry, MRC National Institute for Medical Research, The Ridgeway, Mill Hill, London NW7 1AA, United Kingdom.
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36
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Combined approaches to flexible fitting and assessment in virus capsids undergoing conformational change. J Struct Biol 2013; 185:427-39. [PMID: 24333899 PMCID: PMC3988922 DOI: 10.1016/j.jsb.2013.12.003] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2013] [Revised: 11/28/2013] [Accepted: 12/06/2013] [Indexed: 01/25/2023]
Abstract
Fitting of atomic components into electron cryo-microscopy (cryoEM) density maps is routinely used to understand the structure and function of macromolecular machines. Many fitting methods have been developed, but a standard protocol for successful fitting and assessment of fitted models has yet to be agreed upon among the experts in the field. Here, we created and tested a protocol that highlights important issues related to homology modelling, density map segmentation, rigid and flexible fitting, as well as the assessment of fits. As part of it, we use two different flexible fitting methods (Flex-EM and iMODfit) and demonstrate how combining the analysis of multiple fits and model assessment could result in an improved model. The protocol is applied to the case of the mature and empty capsids of Coxsackievirus A7 (CAV7) by flexibly fitting homology models into the corresponding cryoEM density maps at 8.2 and 6.1 Å resolution. As a result, and due to the improved homology models (derived from recently solved crystal structures of a close homolog – EV71 capsid – in mature and empty forms), the final models present an improvement over previously published models. In close agreement with the capsid expansion observed in the EV71 structures, the new CAV7 models reveal that the expansion is accompanied by ∼5° counterclockwise rotation of the asymmetric unit, predominantly contributed by the capsid protein VP1. The protocol could be applied not only to viral capsids but also to many other complexes characterised by a combination of atomic structure modelling and cryoEM density fitting.
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Lagerstedt I, Moore WJ, Patwardhan A, Sanz-García E, Best C, Swedlow JR, Kleywegt GJ. Web-based visualisation and analysis of 3D electron-microscopy data from EMDB and PDB. J Struct Biol 2013; 184:173-81. [PMID: 24113529 PMCID: PMC3898923 DOI: 10.1016/j.jsb.2013.09.021] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2013] [Revised: 09/24/2013] [Accepted: 09/25/2013] [Indexed: 11/25/2022]
Abstract
The Protein Data Bank in Europe (PDBe) has developed web-based tools for the visualisation and analysis of 3D electron microscopy (3DEM) structures in the Electron Microscopy Data Bank (EMDB) and Protein Data Bank (PDB). The tools include: (1) a volume viewer for 3D visualisation of maps, tomograms and models, (2) a slice viewer for inspecting 2D slices of tomographic reconstructions, and (3) visual analysis pages to facilitate analysis and validation of maps, tomograms and models. These tools were designed to help non-experts and experts alike to get some insight into the content and assess the quality of 3DEM structures in EMDB and PDB without the need to install specialised software or to download large amounts of data from these archives. The technical challenges encountered in developing these tools, as well as the more general considerations when making archived data available to the user community through a web interface, are discussed.
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Affiliation(s)
- Ingvar Lagerstedt
- Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, United Kingdom
| | - William J. Moore
- Centre for Gene Regulation and Expression, College of Life Sciences, University of Dundee, Dow Street, Dundee DD1 5EH, United Kingdom
| | - Ardan Patwardhan
- Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, United Kingdom
| | - Eduardo Sanz-García
- Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, United Kingdom
| | - Christoph Best
- Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, United Kingdom
| | - Jason R. Swedlow
- Centre for Gene Regulation and Expression, College of Life Sciences, University of Dundee, Dow Street, Dundee DD1 5EH, United Kingdom
| | - Gerard J. Kleywegt
- Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, United Kingdom
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Cossio P, Hummer G. Bayesian analysis of individual electron microscopy images: towards structures of dynamic and heterogeneous biomolecular assemblies. J Struct Biol 2013; 184:427-37. [PMID: 24161733 DOI: 10.1016/j.jsb.2013.10.006] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2013] [Revised: 10/05/2013] [Accepted: 10/09/2013] [Indexed: 10/26/2022]
Abstract
We develop a method to extract structural information from electron microscopy (EM) images of dynamic and heterogeneous molecular assemblies. To overcome the challenge of disorder in the imaged structures, we analyze each image individually, avoiding information loss through clustering or averaging. The Bayesian inference of EM (BioEM) method uses a likelihood-based probabilistic measure to quantify the consistency between each EM image and given structural models. The likelihood function accounts for uncertainties in the molecular position and orientation, variations in the relative intensities and noise in the experimental images. The BioEM formalism is physically intuitive and mathematically simple. We show that for experimental GroEL images, BioEM correctly identifies structures according to the functional state. The top-ranked structure is the corresponding X-ray crystal structure, followed by an EM structure generated previously from a superset of the EM images used here. To analyze EM images of highly flexible molecules, we propose an ensemble refinement procedure, and validate it with synthetic EM maps of the ESCRT-I-II supercomplex. Both the size of the ensemble and its structural members are identified correctly. BioEM offers an alternative to 3D-reconstruction methods, extracting accurate population distributions for highly flexible structures and their assemblies. We discuss limitations of the method, and possible applications beyond ensemble refinement, including the cross-validation and unbiased post-assessment of model structures, and the structural characterization of systems where traditional approaches fail. Overall, our results suggest that the BioEM framework can be used to analyze EM images of both ordered and disordered molecular systems.
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Affiliation(s)
- Pilar Cossio
- Department of Theoretical Biophysics, Max Planck Institute of Biophysics, 60438 Frankfurt am Main, Germany; Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892-0520, USA
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39
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Affiliation(s)
- Robert M Glaeser
- Lawrence Berkeley National Laboratory, University of California, Berkeley, CA 94720, United States.
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Woollett B, Whitmore L, Janes RW, Wallace BA. ValiDichro: a website for validating and quality control of protein circular dichroism spectra. Nucleic Acids Res 2013; 41:W417-21. [PMID: 23625965 PMCID: PMC3977657 DOI: 10.1093/nar/gkt287] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2013] [Revised: 03/26/2013] [Accepted: 03/31/2013] [Indexed: 11/13/2022] Open
Abstract
Circular dichroism (CD) spectroscopy is widely used in structural biology as a technique for examining the structure, folding and conformational changes of proteins. A new server, ValiDichro, has been developed for checking the quality and validity of CD spectral data and metadata, both as an aid to data collection and processing and as a validation procedure for spectra to be included in publications. ValiDichro currently includes 25 tests for data completeness, consistency and quality. For each test that is done, not only is a validation report produced, but the user is also provided with suggestions for correcting or improving the data. The ValiDichro server is freely available at http://valispec.cryst.bbk.ac.uk/circularDichroism/ValiDichro/upload.html.
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Affiliation(s)
- Benjamin Woollett
- Institute of Structural and Molecular Biology, Birkbeck
College, University of London, London WC1E 7HX, UK and School of Biological and
Chemical Sciences, Queen Mary University of London, London E1 4NS, UK
| | - Lee Whitmore
- Institute of Structural and Molecular Biology, Birkbeck
College, University of London, London WC1E 7HX, UK and School of Biological and
Chemical Sciences, Queen Mary University of London, London E1 4NS, UK
| | - Robert W. Janes
- Institute of Structural and Molecular Biology, Birkbeck
College, University of London, London WC1E 7HX, UK and School of Biological and
Chemical Sciences, Queen Mary University of London, London E1 4NS, UK
| | - B. A. Wallace
- Institute of Structural and Molecular Biology, Birkbeck
College, University of London, London WC1E 7HX, UK and School of Biological and
Chemical Sciences, Queen Mary University of London, London E1 4NS, UK
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Gutmanas A, Oldfield TJ, Patwardhan A, Sen S, Velankar S, Kleywegt GJ. The role of structural bioinformatics resources in the era of integrative structural biology. ACTA CRYSTALLOGRAPHICA. SECTION D, BIOLOGICAL CRYSTALLOGRAPHY 2013; 69:710-21. [PMID: 23633580 PMCID: PMC3640467 DOI: 10.1107/s0907444913001157] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/06/2012] [Accepted: 01/11/2013] [Indexed: 11/10/2022]
Abstract
The history and the current state of the PDB and EMDB archives is briefly described, as well as some of the challenges that they face. It seems natural that the role of structural biology archives will change from being a pure repository of historic data into becoming an indispensable resource for the wider biomedical community. As part of this transformation, it will be necessary to validate the biomacromolecular structure data and ensure the highest possible quality for the archive holdings, to combine structural data from different spatial scales into a unified resource and to integrate structural data with functional, genetic and taxonomic data as well as other information available in bioinformatics resources. Some recent developments and plans to address these challenges at PDBe are presented.
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Affiliation(s)
- Aleksandras Gutmanas
- Protein Data Bank in Europe, EMBL–EBI, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, England
| | - Thomas J. Oldfield
- Protein Data Bank in Europe, EMBL–EBI, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, England
| | - Ardan Patwardhan
- Protein Data Bank in Europe, EMBL–EBI, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, England
| | - Sanchayita Sen
- Protein Data Bank in Europe, EMBL–EBI, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, England
| | - Sameer Velankar
- Protein Data Bank in Europe, EMBL–EBI, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, England
| | - Gerard J. Kleywegt
- Protein Data Bank in Europe, EMBL–EBI, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, England
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