251
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Tsai KL, Yu X, Gopalan S, Chao TC, Zhang Y, Florens L, Washburn MP, Murakami K, Conaway RC, Conaway JW, Asturias FJ. Mediator structure and rearrangements required for holoenzyme formation. Nature 2017; 544:196-201. [PMID: 28241144 DOI: 10.1038/nature21393] [Citation(s) in RCA: 108] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2016] [Accepted: 12/28/2016] [Indexed: 12/12/2022]
Abstract
The conserved Mediator co-activator complex has an essential role in the regulation of RNA polymerase II transcription in all eukaryotes. Understanding the structure and interactions of Mediator is crucial for determining how the complex influences transcription initiation and conveys regulatory information to the basal transcription machinery. Here we present a 4.4 Å resolution cryo-electron microscopy map of Schizosaccharomyces pombe Mediator in which conserved Mediator subunits are individually resolved. The essential Med14 subunit works as a central backbone that connects the Mediator head, middle and tail modules. Comparison with a 7.8 Å resolution cryo-electron microscopy map of a Mediator-RNA polymerase II holoenzyme reveals that changes in the structure of Med14 facilitate a large-scale Mediator rearrangement that is essential for holoenzyme formation. Our study suggests that access to different conformations and crosstalk between structural elements are essential for the Mediator regulation mechanism, and could explain the capacity of the complex to integrate multiple regulatory signals.
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Affiliation(s)
- Kuang-Lei Tsai
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla California, USA
| | - Xiaodi Yu
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla California, USA
| | - Sneha Gopalan
- Stowers Institute for Medical Research, Kansas City, Missouri, USA
| | - Ti-Chun Chao
- Department of Pediatrics and Institute for Genomic Medicine, University of California San Diego School of Medicine, La Jolla, California, USA
| | - Ying Zhang
- Stowers Institute for Medical Research, Kansas City, Missouri, USA
| | - Laurence Florens
- Stowers Institute for Medical Research, Kansas City, Missouri, USA
| | - Michael P Washburn
- Stowers Institute for Medical Research, Kansas City, Missouri, USA.,Department of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City Kansas, USA
| | - Kenji Murakami
- Department of Structural Biology, Stanford University School of Medicine, Stanford, California, USA
| | - Ronald C Conaway
- Stowers Institute for Medical Research, Kansas City, Missouri, USA.,Department of Biochemistry &Molecular Biology, University of Kansas Medical Center, Kansas City, Kansas, USA
| | - Joan W Conaway
- Stowers Institute for Medical Research, Kansas City, Missouri, USA.,Department of Biochemistry &Molecular Biology, University of Kansas Medical Center, Kansas City, Kansas, USA
| | - Francisco J Asturias
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla California, USA
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252
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Shao C, Yang H, Westbrook JD, Young JY, Zardecki C, Burley SK. Multivariate Analyses of Quality Metrics for Crystal Structures in the PDB Archive. Structure 2017; 25:458-468. [PMID: 28216043 DOI: 10.1016/j.str.2017.01.013] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2016] [Revised: 01/19/2017] [Accepted: 01/29/2017] [Indexed: 11/18/2022]
Abstract
Following deployment of an augmented validation system by the Worldwide Protein Data Bank (wwPDB) partnership, the quality of crystal structures entering the PDB has improved. Of significance are improvements in quality measures now prominently displayed in the wwPDB validation report. Comparisons of PDB depositions made before and after introduction of the new reporting system show improvements in quality measures relating to pairwise atom-atom clashes, side-chain torsion angle rotamers, and local agreement between the atomic coordinate structure model and experimental electron density data. These improvements are largely independent of resolution limit and sample molecular weight. No significant improvement in the quality of associated ligands was observed. Principal component analysis revealed that structure quality could be summarized with three measures (Rfree, real-space R factor Z score, and a combined molecular geometry quality metric), which can in turn be reduced to a single overall quality metric readily interpretable by all PDB archive users.
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Affiliation(s)
- Chenghua Shao
- RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers University, The State University of New Jersey, 174 Frelinghuysen Road, Piscataway, NJ 08854, USA.
| | - Huanwang Yang
- RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers University, The State University of New Jersey, 174 Frelinghuysen Road, Piscataway, NJ 08854, USA
| | - John D Westbrook
- RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers University, The State University of New Jersey, 174 Frelinghuysen Road, Piscataway, NJ 08854, USA; Institute for Quantitative Biomedicine, Rutgers University, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Jasmine Y Young
- RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers University, The State University of New Jersey, 174 Frelinghuysen Road, Piscataway, NJ 08854, USA
| | - Christine Zardecki
- RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers University, The State University of New Jersey, 174 Frelinghuysen Road, Piscataway, NJ 08854, USA
| | - Stephen K Burley
- RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers University, The State University of New Jersey, 174 Frelinghuysen Road, Piscataway, NJ 08854, USA; Institute for Quantitative Biomedicine, Rutgers University, The State University of New Jersey, Piscataway, NJ 08854, USA; Rutgers Cancer Institute of New Jersey, Rutgers University, The State University of New Jersey, New Brunswick, NJ 08903, USA; RCSB Protein Databank, San Diego Supercomputer Center, University of California San Diego, La Jolla, CA 92093, USA; Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA 92093, USA
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253
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Abstract
We describe a new implementation for the reconstruction of helical assemblies in the empirical Bayesian framework of RELION. Our approach calculates optimal linear filters for the 3D reconstruction by embedding helical symmetry operators in Fourier-space, and deals with deviations from perfect helical symmetry through Gaussian-shaped priors on the orientations of individual segments. By incorporating our approach into the standard pipeline for single-particle analysis in RELION, our implementation aims to be easily accessible for non-experienced users. Although our implementation does not solve the problem that grossly incorrect structures can be obtained when the wrong helical symmetry is imposed, we show for four different test cases that it is capable of reconstructing structures to near-atomic resolution.
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Affiliation(s)
- Shaoda He
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge Biomedical Campus, CB2 0QH Cambridge, UK
| | - Sjors H W Scheres
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge Biomedical Campus, CB2 0QH Cambridge, UK.
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254
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Young JY, Westbrook JD, Feng Z, Sala R, Peisach E, Oldfield TJ, Sen S, Gutmanas A, Armstrong DR, Berrisford JM, Chen L, Chen M, Di Costanzo L, Dimitropoulos D, Gao G, Ghosh S, Gore S, Guranovic V, Hendrickx PMS, Hudson BP, Igarashi R, Ikegawa Y, Kobayashi N, Lawson CL, Liang Y, Mading S, Mak L, Mir MS, Mukhopadhyay A, Patwardhan A, Persikova I, Rinaldi L, Sanz-Garcia E, Sekharan MR, Shao C, Swaminathan GJ, Tan L, Ulrich EL, van Ginkel G, Yamashita R, Yang H, Zhuravleva MA, Quesada M, Kleywegt GJ, Berman HM, Markley JL, Nakamura H, Velankar S, Burley SK. OneDep: Unified wwPDB System for Deposition, Biocuration, and Validation of Macromolecular Structures in the PDB Archive. Structure 2017; 25:536-545. [PMID: 28190782 DOI: 10.1016/j.str.2017.01.004] [Citation(s) in RCA: 116] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2016] [Revised: 11/08/2016] [Accepted: 01/10/2017] [Indexed: 10/20/2022]
Abstract
OneDep, a unified system for deposition, biocuration, and validation of experimentally determined structures of biological macromolecules to the PDB archive, has been developed as a global collaboration by the worldwide PDB (wwPDB) partners. This new system was designed to ensure that the wwPDB could meet the evolving archiving requirements of the scientific community over the coming decades. OneDep unifies deposition, biocuration, and validation pipelines across all wwPDB, EMDB, and BMRB deposition sites with improved focus on data quality and completeness in these archives, while supporting growth in the number of depositions and increases in their average size and complexity. In this paper, we describe the design, functional operation, and supporting infrastructure of the OneDep system, and provide initial performance assessments.
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Affiliation(s)
- Jasmine Y Young
- RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA.
| | - John D Westbrook
- RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Zukang Feng
- RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Raul Sala
- RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Ezra Peisach
- RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Thomas J Oldfield
- Protein Data Bank in Europe (PDBe), European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - Sanchayita Sen
- Protein Data Bank in Europe (PDBe), European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - Aleksandras Gutmanas
- Protein Data Bank in Europe (PDBe), European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - David R Armstrong
- Protein Data Bank in Europe (PDBe), European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - John M Berrisford
- Protein Data Bank in Europe (PDBe), European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - Li Chen
- RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Minyu Chen
- PDBj, Institute for Protein Research, Osaka University, Osaka, 565-0871, Japan
| | - Luigi Di Costanzo
- RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Dimitris Dimitropoulos
- RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Guanghua Gao
- RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Sutapa Ghosh
- RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Swanand Gore
- Protein Data Bank in Europe (PDBe), European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - Vladimir Guranovic
- RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Pieter M S Hendrickx
- Protein Data Bank in Europe (PDBe), European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - Brian P Hudson
- RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Reiko Igarashi
- PDBj, Institute for Protein Research, Osaka University, Osaka, 565-0871, Japan
| | - Yasuyo Ikegawa
- PDBj, Institute for Protein Research, Osaka University, Osaka, 565-0871, Japan
| | - Naohiro Kobayashi
- PDBj, Institute for Protein Research, Osaka University, Osaka, 565-0871, Japan
| | - Catherine L Lawson
- RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Yuhe Liang
- RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Steve Mading
- BMRB, BioMagResBank, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Lora Mak
- Protein Data Bank in Europe (PDBe), European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - M Saqib Mir
- Protein Data Bank in Europe (PDBe), European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - Abhik Mukhopadhyay
- Protein Data Bank in Europe (PDBe), European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - Ardan Patwardhan
- Protein Data Bank in Europe (PDBe), European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - Irina Persikova
- RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Luana Rinaldi
- Protein Data Bank in Europe (PDBe), European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - Eduardo Sanz-Garcia
- Protein Data Bank in Europe (PDBe), European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - Monica R Sekharan
- RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Chenghua Shao
- RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - G Jawahar Swaminathan
- Protein Data Bank in Europe (PDBe), European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - Lihua Tan
- RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Eldon L Ulrich
- BMRB, BioMagResBank, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Glen van Ginkel
- Protein Data Bank in Europe (PDBe), European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - Reiko Yamashita
- PDBj, Institute for Protein Research, Osaka University, Osaka, 565-0871, Japan
| | - Huanwang Yang
- RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Marina A Zhuravleva
- RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Martha Quesada
- RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Gerard J Kleywegt
- Protein Data Bank in Europe (PDBe), European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - Helen M Berman
- RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - John L Markley
- BMRB, BioMagResBank, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Haruki Nakamura
- PDBj, Institute for Protein Research, Osaka University, Osaka, 565-0871, Japan
| | - Sameer Velankar
- Protein Data Bank in Europe (PDBe), European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - Stephen K Burley
- RCSB Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; RCSB Protein Data Bank, San Diego Supercomputer Center, University of California San Diego, La Jolla, CA 92093, USA; Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA 92093, USA; Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Rutgers Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, New Brunswick, NJ 08903, USA
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255
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cryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination. Nat Methods 2017; 14:290-296. [PMID: 28165473 DOI: 10.1038/nmeth.4169] [Citation(s) in RCA: 5754] [Impact Index Per Article: 719.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2016] [Accepted: 12/27/2016] [Indexed: 01/02/2023]
Abstract
Single-particle electron cryomicroscopy (cryo-EM) is a powerful method for determining the structures of biological macromolecules. With automated microscopes, cryo-EM data can often be obtained in a few days. However, processing cryo-EM image data to reveal heterogeneity in the protein structure and to refine 3D maps to high resolution frequently becomes a severe bottleneck, requiring expert intervention, prior structural knowledge, and weeks of calculations on expensive computer clusters. Here we show that stochastic gradient descent (SGD) and branch-and-bound maximum likelihood optimization algorithms permit the major steps in cryo-EM structure determination to be performed in hours or minutes on an inexpensive desktop computer. Furthermore, SGD with Bayesian marginalization allows ab initio 3D classification, enabling automated analysis and discovery of unexpected structures without bias from a reference map. These algorithms are combined in a user-friendly computer program named cryoSPARC (http://www.cryosparc.com).
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256
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Davies RB, Smits C, Wong ASW, Stock D, Christie M, Sandin S, Stewart AG. Cryo-EM analysis of a domain antibody bound rotary ATPase complex. J Struct Biol 2017; 197:350-353. [PMID: 28115258 DOI: 10.1016/j.jsb.2017.01.002] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2016] [Revised: 01/16/2017] [Accepted: 01/17/2017] [Indexed: 01/11/2023]
Abstract
The bacterial A/V-type ATPase/synthase rotary motor couples ATP hydrolysis/synthesis with proton translocation across biological membranes. The A/V-type ATPase/synthase from Thermus thermophilus has been extensively studied both structurally and functionally for many years. Here we provide an 8.7Å resolution cryo-electron microscopy 3D reconstruction of this complex bound to single-domain antibody fragments, small monomeric antibodies containing just the variable heavy domain. Docking of known structures into the density revealed the molecular orientation of the domain antibodies, suggesting that structure determination of co-domain antibody:protein complexes could be a useful avenue for unstable or smaller proteins. Although previous studies suggested that the presence of fluoroaluminate in this complex could change the rotary state of this enzyme, we observed no gross structural rearrangements under these conditions.
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Affiliation(s)
- Roberta B Davies
- Molecular, Structural and Computational Biology Division, The Victor Chang Cardiac Research Institute, Darlinghurst, NSW 2010, Australia
| | - Callum Smits
- Molecular, Structural and Computational Biology Division, The Victor Chang Cardiac Research Institute, Darlinghurst, NSW 2010, Australia
| | - Andrew S W Wong
- NTU Institute of Structural Biology, Nanyang Technological University, 636921, Singapore
| | - Daniela Stock
- Molecular, Structural and Computational Biology Division, The Victor Chang Cardiac Research Institute, Darlinghurst, NSW 2010, Australia; Faculty of Medicine, The University of New South Wales, Sydney, NSW 2052, Australia
| | - Mary Christie
- Molecular, Structural and Computational Biology Division, The Victor Chang Cardiac Research Institute, Darlinghurst, NSW 2010, Australia; Faculty of Medicine, The University of New South Wales, Sydney, NSW 2052, Australia
| | - Sara Sandin
- NTU Institute of Structural Biology, Nanyang Technological University, 636921, Singapore; School of Biological Sciences, Nanyang Technological University, 637551, Singapore
| | - Alastair G Stewart
- Molecular, Structural and Computational Biology Division, The Victor Chang Cardiac Research Institute, Darlinghurst, NSW 2010, Australia; Faculty of Medicine, The University of New South Wales, Sydney, NSW 2052, Australia.
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257
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Mackay JP, Landsberg MJ, Whitten AE, Bond CS. Whaddaya Know: A Guide to Uncertainty and Subjectivity in Structural Biology. Trends Biochem Sci 2017; 42:155-167. [PMID: 28089412 DOI: 10.1016/j.tibs.2016.11.002] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2016] [Revised: 10/20/2016] [Accepted: 11/01/2016] [Indexed: 12/28/2022]
Abstract
The methods of structural biology, while powerful, are technically complex. Although the Protein Data Bank (PDB) provides a repository that allows anyone to download any structure, many users would not appreciate the caveats that should be considered when examining a structure. Here, we describe several key uncertainties associated with the application of X-ray crystallography, NMR spectroscopy, single-particle electron microscopy (SPEM), and small-angle scattering (SAS) to biological macromolecules. The take-home message is that structures are not absolute truths - they are models that fit the experimental data and therefore have uncertainty and subjectivity associated with them. These uncertainties must be appreciated - careful reading of the associated paper, and any validation report provided by the structure database, is highly recommended.
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Affiliation(s)
- Joel P Mackay
- School of Life and Environmental Sciences, University of Sydney, NSW 2006, Australia.
| | - Michael J Landsberg
- School of Chemistry and Molecular Biosciences, University of Queensland, QLD, Australia
| | - Andrew E Whitten
- Australian Centre for Neutron Science, ANSTO, Lucas Heights, NSW, Australia
| | - Charles S Bond
- School of Chemistry and Biochemistry, The University of Western Australia, Crawley, WA 6014, Australia
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258
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Han Y, Yan C, Nguyen THD, Jackobel AJ, Ivanov I, Knutson BA, He Y. Structural mechanism of ATP-independent transcription initiation by RNA polymerase I. eLife 2017; 6:e27414. [PMID: 28623663 PMCID: PMC5489313 DOI: 10.7554/elife.27414] [Citation(s) in RCA: 50] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2017] [Accepted: 06/17/2017] [Indexed: 12/02/2022] Open
Abstract
Transcription initiation by RNA Polymerase I (Pol I) depends on the Core Factor (CF) complex to recognize the upstream promoter and assemble into a Pre-Initiation Complex (PIC). Here, we solve a structure of Saccharomyces cerevisiae Pol I-CF-DNA to 3.8 Å resolution using single-particle cryo-electron microscopy. The structure reveals a bipartite architecture of Core Factor and its recognition of the promoter from -27 to -16. Core Factor's intrinsic mobility correlates well with different conformational states of the Pol I cleft, in addition to the stabilization of either Rrn7 N-terminal domain near Pol I wall or the tandem winged helix domain of A49 at a partially overlapping location. Comparison of the three states in this study with the Pol II system suggests that a ratchet motion of the Core Factor-DNA sub-complex at upstream facilitates promoter melting in an ATP-independent manner, distinct from a DNA translocase actively threading the downstream DNA in the Pol II PIC.
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Affiliation(s)
- Yan Han
- Department of Molecular Biosciences, Northwestern University, Evanston, United States
| | - Chunli Yan
- Department of Chemistry, Georgia State University, Atlanta, United States,Center for Diagnostics and Therapeutics, Georgia State University, Atlanta, United States
| | | | - Ashleigh J Jackobel
- Department of Biochemistry and Molecular Biology, SUNY Upstate Medical University, Syracuse, United States
| | - Ivaylo Ivanov
- Department of Chemistry, Georgia State University, Atlanta, United States,Center for Diagnostics and Therapeutics, Georgia State University, Atlanta, United States
| | - Bruce A Knutson
- Department of Biochemistry and Molecular Biology, SUNY Upstate Medical University, Syracuse, United States, (BAK)
| | - Yuan He
- Department of Molecular Biosciences, Northwestern University, Evanston, United States, (YHe)
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259
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Burley SK, Berman HM, Kleywegt GJ, Markley JL, Nakamura H, Velankar S. Protein Data Bank (PDB): The Single Global Macromolecular Structure Archive. Methods Mol Biol 2017; 1607:627-641. [PMID: 28573592 PMCID: PMC5823500 DOI: 10.1007/978-1-4939-7000-1_26] [Citation(s) in RCA: 579] [Impact Index Per Article: 72.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2023]
Abstract
The Protein Data Bank (PDB)--the single global repository of experimentally determined 3D structures of biological macromolecules and their complexes--was established in 1971, becoming the first open-access digital resource in the biological sciences. The PDB archive currently houses ~130,000 entries (May 2017). It is managed by the Worldwide Protein Data Bank organization (wwPDB; wwpdb.org), which includes the RCSB Protein Data Bank (RCSB PDB; rcsb.org), the Protein Data Bank Japan (PDBj; pdbj.org), the Protein Data Bank in Europe (PDBe; pdbe.org), and BioMagResBank (BMRB; www.bmrb.wisc.edu). The four wwPDB partners operate a unified global software system that enforces community-agreed data standards and supports data Deposition, Biocuration, and Validation of ~11,000 new PDB entries annually (deposit.wwpdb.org). The RCSB PDB currently acts as the archive keeper, ensuring disaster recovery of PDB data and coordinating weekly updates. wwPDB partners disseminate the same archival data from multiple FTP sites, while operating complementary websites that provide their own views of PDB data with selected value-added information and links to related data resources. At present, the PDB archives experimental data, associated metadata, and 3D-atomic level structural models derived from three well-established methods: crystallography, nuclear magnetic resonance spectroscopy (NMR), and electron microscopy (3DEM). wwPDB partners are working closely with experts in related experimental areas (small-angle scattering, chemical cross-linking/mass spectrometry, Forster energy resonance transfer or FRET, etc.) to establish a federation of data resources that will support sustainable archiving and validation of 3D structural models and experimental data derived from integrative or hybrid methods.
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Affiliation(s)
- Stephen K Burley
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Center for Integrative Proteomics, Research, Institute for Quantitative Biomedicine, and Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ, 08854, USA.
- Rutgers Cancer Institute of New Jersey, Robert Wood Johnson Medical School, New Brunswick, NJ, 08903, USA.
- Skaggs School of Pharmacy and Pharmaceutical Sciences and San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA, 92093, USA.
| | - Helen M Berman
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Center for Integrative Proteomics, Research, Institute for Quantitative Biomedicine, and Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ, 08854, USA
| | - Gerard J Kleywegt
- Protein Data Bank in Europe, European Molecular Biology Laboratory-European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, CB10 1SD, UK
| | - John L Markley
- BioMagResBank, Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Haruki Nakamura
- Protein Data Bank Japan, Institute for Protein Research, Osaka University, Suita, Osaka, 565-0871, Japan
| | - Sameer Velankar
- Protein Data Bank in Europe, European Molecular Biology Laboratory-European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, CB10 1SD, UK
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Adams PD, Aertgeerts K, Bauer C, Bell JA, Berman HM, Bhat TN, Blaney JM, Bolton E, Bricogne G, Brown D, Burley SK, Case DA, Clark KL, Darden T, Emsley P, Feher VA, Feng Z, Groom CR, Harris SF, Hendle J, Holder T, Joachimiak A, Kleywegt GJ, Krojer T, Marcotrigiano J, Mark AE, Markley JL, Miller M, Minor W, Montelione GT, Murshudov G, Nakagawa A, Nakamura H, Nicholls A, Nicklaus M, Nolte RT, Padyana AK, Peishoff CE, Pieniazek S, Read RJ, Shao C, Sheriff S, Smart O, Soisson S, Spurlino J, Stouch T, Svobodova R, Tempel W, Terwilliger TC, Tronrud D, Velankar S, Ward SC, Warren GL, Westbrook JD, Williams P, Yang H, Young J. Outcome of the First wwPDB/CCDC/D3R Ligand Validation Workshop. Structure 2016; 24:502-508. [PMID: 27050687 DOI: 10.1016/j.str.2016.02.017] [Citation(s) in RCA: 53] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2015] [Revised: 02/24/2016] [Accepted: 02/25/2016] [Indexed: 10/22/2022]
Abstract
Crystallographic studies of ligands bound to biological macromolecules (proteins and nucleic acids) represent an important source of information concerning drug-target interactions, providing atomic level insights into the physical chemistry of complex formation between macromolecules and ligands. Of the more than 115,000 entries extant in the Protein Data Bank (PDB) archive, ∼75% include at least one non-polymeric ligand. Ligand geometrical and stereochemical quality, the suitability of ligand models for in silico drug discovery and design, and the goodness-of-fit of ligand models to electron-density maps vary widely across the archive. We describe the proceedings and conclusions from the first Worldwide PDB/Cambridge Crystallographic Data Center/Drug Design Data Resource (wwPDB/CCDC/D3R) Ligand Validation Workshop held at the Research Collaboratory for Structural Bioinformatics at Rutgers University on July 30-31, 2015. Experts in protein crystallography from academe and industry came together with non-profit and for-profit software providers for crystallography and with experts in computational chemistry and data archiving to discuss and make recommendations on best practices, as framed by a series of questions central to structural studies of macromolecule-ligand complexes. What data concerning bound ligands should be archived in the PDB? How should the ligands be best represented? How should structural models of macromolecule-ligand complexes be validated? What supplementary information should accompany publications of structural studies of biological macromolecules? Consensus recommendations on best practices developed in response to each of these questions are provided, together with some details regarding implementation. Important issues addressed but not resolved at the workshop are also enumerated.
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Affiliation(s)
- Paul D Adams
- Molecular Biophysics & Integrated Bioimaging Division, Lawrence Berkeley Laboratory, Department of Bioengineering, UC Berkeley, Berkeley, CA 94720-8235, USA
| | | | - Cary Bauer
- Bruker AXS, Inc., Madison, WI 53711, USA
| | | | - Helen M Berman
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Talapady N Bhat
- Biosystems and Biomaterials Division, NIST, Gaithersburg, MD 20899, USA
| | | | - Evan Bolton
- National Center for Biotechnology Information, U.S. National Library of Medicine, Bethesda, MD 20894, USA
| | | | - David Brown
- School of Biosciences, University of Kent, Canterbury CT2 7NH, UK; Charles River Ltd., Structural Biology and Biophysics, Cambridge CB10 1XL, UK
| | - Stephen K Burley
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Department of Chemistry and Chemical Biology, 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.
| | - David A Case
- Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Kirk L Clark
- Novartis Institutes for BioMedical Research, Cambridge, MA 02139, USA
| | - Tom Darden
- OpenEye Scientific, Cambridge, MA 02142, USA
| | - Paul Emsley
- MRC Laboratory of Molecular Biology, Cambridge CB2 0QH, UK
| | - Victoria A Feher
- Drug Design Data Resource and Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, CA 92093, USA.
| | - Zukang Feng
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Colin R Groom
- Cambridge Crystallographic Data Centre, Cambridge CB2 1EZ, UK.
| | | | - Jorg Hendle
- Structural Biology, Lilly Biotechnology Center, San Diego, CA 92121, USA
| | | | - Andrzej Joachimiak
- Structural Biology Center, Biosciences, Argonne National Laboratory, Argonne, IL 60439, USA
| | - Gerard J Kleywegt
- Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Tobias Krojer
- Structural Genomics Consortium, University of Oxford, Oxford OX3 7DQ, UK
| | - Joseph Marcotrigiano
- Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Center for Advanced Biotechnology and Medicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Alan E Mark
- School of Chemistry & Molecular Biosciences, University of Queensland, St Lucia, QLD 4072, Australia
| | - John L Markley
- BioMagResBank, Department of Biochemistry, University of Wisconsin-Madison, Madison, WI 53706-1544, USA
| | - Matthew Miller
- Center for Advanced Biotechnology and Medicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Wladek Minor
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA 22908, USA
| | - Gaetano T Montelione
- Center for Advanced Biotechnology and Medicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Department of Molecular Biology and Biochemistry, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | | | - Atsushi Nakagawa
- Protein Data Bank Japan, Institute for Protein Research, Osaka University, Osaka 565-0871, Japan
| | - Haruki Nakamura
- Protein Data Bank Japan, Institute for Protein Research, Osaka University, Osaka 565-0871, Japan
| | | | - Marc Nicklaus
- Computer-Aided Drug Design Group, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Frederick, MD 21702, USA
| | | | | | | | - Susan Pieniazek
- Bristol-Myers Squibb Research and Development, Pennington, NJ 08534, USA
| | - Randy J Read
- Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Cambridge CB2 0XY, UK
| | - Chenghua Shao
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Steven Sheriff
- Bristol-Myers Squibb Research and Development, Princeton, NJ 08543, USA
| | - Oliver Smart
- Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | | | - John Spurlino
- Janssen Pharmaceuticals, Inc., Spring House, PA 19002, USA
| | - Terry Stouch
- Science For Solutions, LLC, West Windsor, NJ 08550, USA
| | - Radka Svobodova
- CEITEC-Central European Institute of Technology and National Centre for Biomolecular Research, Masaryk University Brno, 625 00 Brno, Czech Republic
| | - Wolfram Tempel
- Structural Genomics Consortium, University of Toronto, Toronto, ON M5G 1L7, Canada
| | | | - Dale Tronrud
- Department of Biochemistry and Biophysics, Oregon State University, Corvallis, OR 97331, USA
| | - Sameer Velankar
- Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Suzanna C Ward
- Cambridge Crystallographic Data Centre, Cambridge CB2 1EZ, UK
| | | | - John D Westbrook
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | | | - Huanwang Yang
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Jasmine Young
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
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261
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Setiaputra DT, Cheng DT, Lu S, Hansen JM, Dalwadi U, Lam CH, To JL, Dong MQ, Yip CK. Molecular architecture of the yeast Elongator complex reveals an unexpected asymmetric subunit arrangement. EMBO Rep 2016; 18:280-291. [PMID: 27872205 DOI: 10.15252/embr.201642548] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2016] [Revised: 10/18/2016] [Accepted: 10/25/2016] [Indexed: 11/09/2022] Open
Abstract
Elongator is a ~850 kDa protein complex involved in multiple processes from transcription to tRNA modification. Conserved from yeast to humans, Elongator is assembled from two copies of six unique subunits (Elp1 to Elp6). Despite the wealth of structural data on the individual subunits, the overall architecture and subunit organization of the full Elongator and the molecular mechanisms of how it exerts its multiple activities remain unclear. Using single-particle electron microscopy (EM), we revealed that yeast Elongator adopts a bilobal architecture and an unexpected asymmetric subunit arrangement resulting from the hexameric Elp456 subassembly anchored to one of the two Elp123 lobes that form the structural scaffold. By integrating the EM data with available subunit crystal structures and restraints generated from cross-linking coupled to mass spectrometry, we constructed a multiscale molecular model that showed the two Elp3, the main catalytic subunit, are located in two distinct environments. This work provides the first structural insights into Elongator and a framework to understand the molecular basis of its multifunctionality.
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Affiliation(s)
- Dheva T Setiaputra
- Department of Biochemistry and Molecular Biology, The University of British Columbia, Vancouver, BC, Canada
| | - Derrick Th Cheng
- Department of Biochemistry and Molecular Biology, The University of British Columbia, Vancouver, BC, Canada
| | - Shan Lu
- National Institute of Biological Sciences, Beijing, Beijing, China
| | - Jesse M Hansen
- Department of Biochemistry and Molecular Biology, The University of British Columbia, Vancouver, BC, Canada
| | - Udit Dalwadi
- Department of Biochemistry and Molecular Biology, The University of British Columbia, Vancouver, BC, Canada
| | - Cindy Hy Lam
- Department of Biochemistry and Molecular Biology, The University of British Columbia, Vancouver, BC, Canada
| | - Jeffrey L To
- Department of Biochemistry and Molecular Biology, The University of British Columbia, Vancouver, BC, Canada
| | - Meng-Qiu Dong
- National Institute of Biological Sciences, Beijing, Beijing, China
| | - Calvin K Yip
- Department of Biochemistry and Molecular Biology, The University of British Columbia, Vancouver, BC, Canada
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262
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Blotting-free and lossless cryo-electron microscopy grid preparation from nanoliter-sized protein samples and single-cell extracts. J Struct Biol 2016; 197:220-226. [PMID: 27864160 DOI: 10.1016/j.jsb.2016.11.002] [Citation(s) in RCA: 77] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2016] [Revised: 10/24/2016] [Accepted: 11/14/2016] [Indexed: 12/28/2022]
Abstract
We present a sample preparation method for cryo-electron microscopy (cryo-EM) that requires only 3-20nL of sample to prepare a cryo-EM grid, depending on the protocol used. The sample is applied and spread on the grid by a microcapillary. The procedure does not involve any blotting steps, and real-time monitoring allows the water film thickness to be assessed and decreased to an optimum value prior to vitrification. We demonstrate that the method is suitable for high-resolution cryo-EM and will enable alternative electron microscopy approaches, such as single-cell visual proteomics.
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263
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Rose PW, Prlić A, Altunkaya A, Bi C, Bradley AR, Christie CH, Costanzo LD, Duarte JM, Dutta S, Feng Z, Green RK, Goodsell DS, Hudson B, Kalro T, Lowe R, Peisach E, Randle C, Rose AS, Shao C, Tao YP, Valasatava Y, Voigt M, Westbrook JD, Woo J, Yang H, Young JY, Zardecki C, Berman HM, Burley SK. The RCSB protein data bank: integrative view of protein, gene and 3D structural information. Nucleic Acids Res 2016; 45:D271-D281. [PMID: 27794042 PMCID: PMC5210513 DOI: 10.1093/nar/gkw1000] [Citation(s) in RCA: 423] [Impact Index Per Article: 47.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2016] [Revised: 10/12/2016] [Accepted: 10/14/2016] [Indexed: 12/02/2022] Open
Abstract
The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB, http://rcsb.org), the US data center for the global PDB archive, makes PDB data freely available to all users, from structural biologists to computational biologists and beyond. New tools and resources have been added to the RCSB PDB web portal in support of a ‘Structural View of Biology.’ Recent developments have improved the User experience, including the high-speed NGL Viewer that provides 3D molecular visualization in any web browser, improved support for data file download and enhanced organization of website pages for query, reporting and individual structure exploration. Structure validation information is now visible for all archival entries. PDB data have been integrated with external biological resources, including chromosomal position within the human genome; protein modifications; and metabolic pathways. PDB-101 educational materials have been reorganized into a searchable website and expanded to include new features such as the Geis Digital Archive.
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Affiliation(s)
- Peter W Rose
- RCSB Protein Data Bank, San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA 92093, USA
| | - Andreas Prlić
- RCSB Protein Data Bank, San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA 92093, USA
| | - Ali Altunkaya
- RCSB Protein Data Bank, San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA 92093, USA
| | - Chunxiao Bi
- RCSB Protein Data Bank, San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA 92093, USA
| | - Anthony R Bradley
- RCSB Protein Data Bank, San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA 92093, USA
| | - Cole H Christie
- RCSB Protein Data Bank, San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA 92093, USA
| | - Luigi Di Costanzo
- RCSB Protein Data Bank, Department of Chemistry and Chemical Biology, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Jose M Duarte
- RCSB Protein Data Bank, San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA 92093, USA
| | - Shuchismita Dutta
- RCSB Protein Data Bank, Department of Chemistry and Chemical Biology, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Zukang Feng
- RCSB Protein Data Bank, Department of Chemistry and Chemical Biology, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Rachel Kramer Green
- RCSB Protein Data Bank, Department of Chemistry and Chemical Biology, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - David S Goodsell
- RCSB Protein Data Bank, Department of Chemistry and Chemical Biology, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA.,Department of Molecular Biology, The Scripps Research Institute, La Jolla, CA 92037, USA
| | - Brian Hudson
- RCSB Protein Data Bank, Department of Chemistry and Chemical Biology, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Tara Kalro
- RCSB Protein Data Bank, San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA 92093, USA
| | - Robert Lowe
- RCSB Protein Data Bank, Department of Chemistry and Chemical Biology, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Ezra Peisach
- RCSB Protein Data Bank, Department of Chemistry and Chemical Biology, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Christopher Randle
- RCSB Protein Data Bank, San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA 92093, USA
| | - Alexander S Rose
- RCSB Protein Data Bank, San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA 92093, USA
| | - Chenghua Shao
- RCSB Protein Data Bank, Department of Chemistry and Chemical Biology, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Yi-Ping Tao
- RCSB Protein Data Bank, Department of Chemistry and Chemical Biology, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Yana Valasatava
- RCSB Protein Data Bank, San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA 92093, USA
| | - Maria Voigt
- RCSB Protein Data Bank, Department of Chemistry and Chemical Biology, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - John D Westbrook
- RCSB Protein Data Bank, Department of Chemistry and Chemical Biology, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Jesse Woo
- RCSB Protein Data Bank, San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA 92093, USA
| | - Huangwang Yang
- RCSB Protein Data Bank, Department of Chemistry and Chemical Biology, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Jasmine Y Young
- RCSB Protein Data Bank, Department of Chemistry and Chemical Biology, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Christine Zardecki
- RCSB Protein Data Bank, Department of Chemistry and Chemical Biology, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Helen M Berman
- RCSB Protein Data Bank, Department of Chemistry and Chemical Biology, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Stephen K Burley
- RCSB Protein Data Bank, San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA 92093, USA .,RCSB Protein Data Bank, Department of Chemistry and Chemical Biology, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA.,Institute for Quantitative BioMedicine and Rutgers Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, New Brunswick, NJ 08901, USA.,Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA 92093, USA
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264
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Liu Z, Gutierrez-Vargas C, Wei J, Grassucci RA, Sun M, Espina N, Madison-Antenucci S, Tong L, Frank J. Determination of the ribosome structure to a resolution of 2.5 Å by single-particle cryo-EM. Protein Sci 2016; 26:82-92. [PMID: 27750394 DOI: 10.1002/pro.3068] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2016] [Revised: 10/13/2016] [Accepted: 10/14/2016] [Indexed: 11/06/2022]
Abstract
With the advance of new instruments and algorithms, and the accumulation of experience over decades, single-particle cryo-EM has become a pivotal part of structural biology. Recently, we determined the structure of a eukaryotic ribosome at 2.5 Å for the large subunit. The ribosome was derived from Trypanosoma cruzi, the protozoan pathogen of Chagas disease. The high-resolution density map allowed us to discern a large number of unprecedented details including rRNA modifications, water molecules, and ions such as Mg2+ and Zn2+ . In this paper, we focus on the procedures for data collection, image processing, and modeling, with particular emphasis on factors that contributed to the attainment of high resolution. The methods described here are readily applicable to other macromolecules for high-resolution reconstruction by single-particle cryo-EM.
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Affiliation(s)
- Zheng Liu
- Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, 10032
| | - Cristina Gutierrez-Vargas
- Department of Biochemistry and Molecular Biophysics, Howard Hughes Medical Institute, Columbia University, New York, New York, 10032
| | - Jia Wei
- Department of Biochemistry and Molecular Biophysics, Howard Hughes Medical Institute, Columbia University, New York, New York, 10032
| | - Robert A Grassucci
- Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, 10032
| | - Ming Sun
- Department of Biochemistry and Molecular Biophysics, Howard Hughes Medical Institute, Columbia University, New York, New York, 10032
| | - Noel Espina
- Division of Infectious Diseases, New York State Department of Health, Wadsworth Center, Albany, New York, 12201
| | - Susan Madison-Antenucci
- Division of Infectious Diseases, New York State Department of Health, Wadsworth Center, Albany, New York, 12201
| | - Liang Tong
- Department of Biochemistry and Molecular Biophysics, Howard Hughes Medical Institute, Columbia University, New York, New York, 10032
| | - Joachim Frank
- Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, 10032.,Department of Biochemistry and Molecular Biophysics, Howard Hughes Medical Institute, Columbia University, New York, New York, 10032.,Department of Biological Sciences, Columbia University, New York, New York, 10027
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265
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Structure and assembly model for the Trypanosoma cruzi 60S ribosomal subunit. Proc Natl Acad Sci U S A 2016; 113:12174-12179. [PMID: 27791004 DOI: 10.1073/pnas.1614594113] [Citation(s) in RCA: 53] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Ribosomes of trypanosomatids, a family of protozoan parasites causing debilitating human diseases, possess multiply fragmented rRNAs that together are analogous to 28S rRNA, unusually large rRNA expansion segments, and r-protein variations compared with other eukaryotic ribosomes. To investigate the architecture of the trypanosomatid ribosomes, we determined the 2.5-Å structure of the Trypanosoma cruzi ribosome large subunit by single-particle cryo-EM. Examination of this structure and comparative analysis of the yeast ribosomal assembly pathway allowed us to develop a stepwise assembly model for the eight pieces of the large subunit rRNAs and a number of ancillary "glue" proteins. This model can be applied to the characterization of Trypanosoma brucei and Leishmania spp. ribosomes as well. Together with other details, our atomic-level structure may provide a foundation for structure-based design of antitrypanosome drugs.
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266
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Berman HM, Burley SK, Kleywegt GJ, Markley JL, Nakamura H, Velankar S. The archiving and dissemination of biological structure data. Curr Opin Struct Biol 2016; 40:17-22. [PMID: 27450113 PMCID: PMC5161703 DOI: 10.1016/j.sbi.2016.06.018] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2016] [Revised: 06/28/2016] [Accepted: 06/30/2016] [Indexed: 01/11/2023]
Abstract
The global Protein Data Bank (PDB) was the first open-access digital archive in biology. The history and evolution of the PDB are described, together with the ways in which molecular structural biology data and information are collected, curated, validated, archived, and disseminated by the members of the Worldwide Protein Data Bank organization (wwPDB; http://wwpdb.org). Particular emphasis is placed on the role of community in establishing the standards and policies by which the PDB archive is managed day-to-day.
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Affiliation(s)
- Helen M Berman
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Department of Chemistry and Chemical Biology, Center for Integrative Proteomics Research, Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, 174 Frelinghuysen Road, Piscataway, NJ 08854, USA.
| | - Stephen K Burley
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Department of Chemistry and Chemical Biology, Center for Integrative Proteomics Research, Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, 174 Frelinghuysen Road, Piscataway, NJ 08854, USA; Research Collaboratory for Structural Bioinformatics Protein Data Bank, Skaggs School of Pharmacy and Pharmaceutical Sciences and San Diego Supercomputer Center, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
| | - Gerard J Kleywegt
- Protein Data Bank in Europe, European Molecular Biology Laboratory-European Bioinformatics Institute, Wellcome Genome Campus, Cambridge CB10 1SD, UK
| | - John L Markley
- Biological Magnetic Resonance Bank, Department of Biochemistry, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Haruki Nakamura
- Protein Data Bank Japan, Institute for Protein Research, Osaka University, 3-2 Yamadaoka, Suita, Osaka, 565-0871, Japan
| | - Sameer Velankar
- Protein Data Bank in Europe, European Molecular Biology Laboratory-European Bioinformatics Institute, Wellcome Genome Campus, Cambridge CB10 1SD, UK
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267
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Resolving macromolecular structures from electron cryo-tomography data using subtomogram averaging in RELION. Nat Protoc 2016; 11:2054-65. [PMID: 27685097 DOI: 10.1038/nprot.2016.124] [Citation(s) in RCA: 190] [Impact Index Per Article: 21.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Electron cryo-tomography (cryo-ET) is a technique that is used to produce 3D pictures (tomograms) of complex objects such as asymmetric viruses, cellular organelles or whole cells from a series of tilted electron cryo-microscopy (cryo-EM) images. Averaging of macromolecular complexes found within tomograms is known as subtomogram averaging, and this technique allows structure determination of macromolecular complexes in situ. Subtomogram averaging is also gaining in popularity for the calculation of initial models for single-particle analysis. We describe herein a protocol for subtomogram averaging from cryo-ET data using the RELION software (http://www2.mrc-lmb.cam.ac.uk/relion). RELION was originally developed for cryo-EM single-particle analysis, and the subtomogram averaging approach presented in this protocol has been implemented in the existing workflow for single-particle analysis so that users may conveniently tap into existing capabilities of the RELION software. We describe how to calculate 3D models for the contrast transfer function (CTF) that describe the transfer of information in the imaging process, and we illustrate the results of classification and subtomogram averaging refinement for cryo-ET data of purified hepatitis B capsid particles and Saccharomyces cerevisiae 80S ribosomes. Using the steps described in this protocol, along with the troubleshooting and optimization guidelines, high-resolution maps can be obtained in which secondary structure elements are resolved subtomogram.
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268
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Costanzo LD, Ghosh S, Zardecki C, Burley SK. Using the Tools and Resources of the RCSB Protein Data Bank. ACTA ACUST UNITED AC 2016; 55:1.9.1-1.9.35. [DOI: 10.1002/cpbi.13] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Affiliation(s)
- Luigi Di Costanzo
- RCSB Protein Data Bank, Department of Chemistry and Chemical Biology and Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey Piscataway New Jersey
| | - Sutapa Ghosh
- RCSB Protein Data Bank, Department of Chemistry and Chemical Biology and Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey Piscataway New Jersey
| | - Christine Zardecki
- RCSB Protein Data Bank, Department of Chemistry and Chemical Biology and Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey Piscataway New Jersey
| | - Stephen K. Burley
- RCSB Protein Data Bank, Department of Chemistry and Chemical Biology and Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey Piscataway New Jersey
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey Piscataway New Jersey
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego California
- San Diego Supercomputer Center, University of California San Diego California
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269
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Structure of human Aichi virus and implications for receptor binding. Nat Microbiol 2016; 1:16150. [DOI: 10.1038/nmicrobiol.2016.150] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2016] [Accepted: 07/21/2016] [Indexed: 12/14/2022]
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270
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DiMaio F, Chiu W. Tools for Model Building and Optimization into Near-Atomic Resolution Electron Cryo-Microscopy Density Maps. Methods Enzymol 2016; 579:255-76. [PMID: 27572730 PMCID: PMC5103630 DOI: 10.1016/bs.mie.2016.06.003] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
Abstract
Electron cryo-microscopy (cryoEM) has advanced dramatically to become a viable tool for high-resolution structural biology research. The ultimate outcome of a cryoEM study is an atomic model of a macromolecule or its complex with interacting partners. This chapter describes a variety of algorithms and software to build a de novo model based on the cryoEM 3D density map, to optimize the model with the best stereochemistry restraints and finally to validate the model with proper protocols. The full process of atomic structure determination from a cryoEM map is described. The tools outlined in this chapter should prove extremely valuable in revealing atomic interactions guided by cryoEM data.
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Affiliation(s)
- F DiMaio
- University of Washington, Seattle, WA, United States; Institute for Protein Design, University of Washington, Seattle, WA, United States.
| | - W Chiu
- National Center for Macromolecular Imaging, Baylor College of Medicine, Houston, TX, United States.
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271
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Affiliation(s)
- David I Stuart
- Instruct, Division of Structural Biology, the Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- Diamond Light Source Ltd., Diamond House, Harwell Science and Innovation Campus, Didcot, UK
| | - Sriram Subramaniam
- Laboratory of Cell Biology, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, Maryland, USA
| | - Nicola G A Abrescia
- Structural Biology Unit, CICbioGUNE, CIBERehd, Derio, Spain
- IKERBASQUE, Basque Foundation for Science, Bilbao, Spain
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272
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Abstract
AbstractThere has been enormous progress during the last few years in the determination of three-dimensional biological structures by single particle electron cryomicroscopy (cryoEM), allowing maps to be obtained with higher resolution and from fewer images than required previously. This is due principally to the introduction of a new type of direct electron detector that has 2- to 3-fold higher detective quantum efficiency than available previously, and to the improvement of the computational algorithms for image processing. In spite of the great strides that have been made, quantitative analysis shows that there are still significant gains to be made provided that the problems associated with image degradation can be solved, possibly by minimising beam-induced specimen movement and charge build up during imaging. If this can be achieved, it should be possible to obtain near atomic resolution structures of smaller single particles, using fewer images and resolving more conformational states than at present, thus realising the full potential of the method. The recent popularity of cryoEM for molecular structure determination also highlights the need for lower cost microscopes, so we encourage development of an inexpensive, 100 keV electron cryomicroscope with a high-brightness field emission gun to make the method accessible to individual groups or institutions that cannot afford the investment and running costs of a state-of-the-art 300 keV installation. A key requisite for successful high-resolution structure determination by cryoEM includes interpretation of images and optimising the biochemistry and grid preparation to obtain nicely distributed macromolecules of interest. We thus include in this review a gallery of cryoEM micrographs that shows illustrative examples of single particle images of large and small macromolecular complexes.
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273
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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: 1.0] [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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274
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Abstract
CryoEM single-particle reconstruction has been growing rapidly over the last 3 years largely due to the development of direct electron detectors, which have provided data with dramatic improvements in image quality. It is now possible in many cases to produce near-atomic resolution structures, and yet 2/3 of published structures remain at substantially lower resolutions. One important cause for this is compositional and conformational heterogeneity, which is both a resolution-limiting factor and presenting a unique opportunity to better relate structure to function. This manuscript discusses the canonical methods for high-resolution refinement in EMAN2.12, and then considers the wide range of available methods within this package for resolving structural variability, targeting both improved resolution and additional knowledge about particle dynamics.
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Affiliation(s)
- S J Ludtke
- National Center for Macromolecular Imaging, Baylor College of Medicine, Houston, TX, United States.
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275
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Riedel C, Vasishtan D, Siebert CA, Whittle C, Lehmann MJ, Mothes W, Grünewald K. Native structure of a retroviral envelope protein and its conformational change upon interaction with the target cell. J Struct Biol 2016; 197:172-180. [PMID: 27345930 PMCID: PMC5182179 DOI: 10.1016/j.jsb.2016.06.017] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2016] [Revised: 06/20/2016] [Accepted: 06/21/2016] [Indexed: 11/22/2022]
Abstract
Enveloped viruses enter their host cells by membrane fusion. The process of attachment and fusion in retroviruses is mediated by a single viral envelope glycoprotein (Env). Conformational changes of Env in the course of fusion are a focus of intense studies. Here we provide further insight into the changes occurring in retroviral Env during its initial interaction with the cell, employing murine leukemia virus (MLV) as model system. We first determined the structure of both natively membrane anchored MLV Env and MLV Env tagged with YFP in the proline rich region (PRR) by electron cryo tomography (cET) and sub-volume averaging. At a resolution of ∼20 Å, native MLV Env presents as a hollow trimer (height ∼85 Å, diameter ∼120 Å) composed of step-shaped protomers. The major difference to the YFP-tagged protein was in regions outside of the central trimer. Next, we focused on elucidating the changes in MLV Env upon interaction with a host cell. Virus interaction with the plasma membrane occurred over a large surface and Env clustering on the binding site was observed. Sub-volume averaging did yield a low-resolution structure of Env interacting with the cell, which had lost its threefold symmetry and was elongated by ∼35 Å in comparison to the unbound protein. This indicates a major rearrangement of Env upon host cell binding. At the site of virus interaction, the otherwise clearly defined bilayer structure of the host cell plasma membrane was much less evident, indicative of integral membrane protein accumulation and/or a change in membrane lipid composition.
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Affiliation(s)
- Christiane Riedel
- Division of Structural Biology, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK; Institute of Virology, University of Veterinary Medicine, Vienna, Austria
| | - Daven Vasishtan
- Division of Structural Biology, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - C Alistair Siebert
- Division of Structural Biology, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Cathy Whittle
- Division of Structural Biology, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Maik J Lehmann
- Department of Life Sciences and Engineering, University of Applied Sciences Bingen, Germany
| | - Walther Mothes
- Department of Microbial Pathogenesis, Yale University School of Medicine, New Haven, CT, USA
| | - Kay Grünewald
- Division of Structural Biology, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK.
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276
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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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277
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Abstract
Frealign is a software tool designed to process electron microscope images of single molecules and complexes to obtain reconstructions at the highest possible resolution. It provides a number of refinement parameters and options that allow users to tune their refinement to achieve specific goals, such as masking to classify selected regions within a particle, control over the refinement of specific alignment parameters to accommodate various data collection schemes, refinement of pseudosymmetric particles, and generation of initial maps. This chapter provides a general overview of Frealign functions and a more detailed guide to using Frealign in typical scenarios.
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278
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Abstract
This chapter describes algorithmic advances in the RELION software, and how these are used in high-resolution cryo-electron microscopy (cryo-EM) structure determination. Since the presence of projections of different three-dimensional structures in the dataset probably represents the biggest challenge in cryo-EM data processing, special emphasis is placed on how to deal with structurally heterogeneous datasets. As such, this chapter aims to be of practical help to those who wish to use RELION in their cryo-EM structure determination efforts.
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279
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He Y, Yan C, Fang J, Inouye C, Tjian R, Ivanov I, Nogales E. Near-atomic resolution visualization of human transcription promoter opening. Nature 2016; 533:359-65. [PMID: 27193682 PMCID: PMC4940141 DOI: 10.1038/nature17970] [Citation(s) in RCA: 230] [Impact Index Per Article: 25.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2015] [Accepted: 04/05/2016] [Indexed: 12/11/2022]
Abstract
In eukaryotic transcription initiation, a large multi-subunit pre-initiation complex (PIC) that assembles at the core promoter is required for the opening of the duplex DNA and identification of the start site for transcription by RNA polymerase II. Here we use cryo-electron microscropy (cryo-EM) to determine near-atomic resolution structures of the human PIC in a closed state (engaged with duplex DNA), an open state (engaged with a transcription bubble), and an initially transcribing complex (containing six base pairs of DNA-RNA hybrid). Our studies provide structures for previously uncharacterized components of the PIC, such as TFIIE and TFIIH, and segments of TFIIA, TFIIB and TFIIF. Comparison of the different structures reveals the sequential conformational changes that accompany the transition from each state to the next throughout the transcription initiation process. This analysis illustrates the key role of TFIIB in transcription bubble stabilization and provides strong structural support for a translocase activity of XPB.
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Affiliation(s)
- Yuan He
- Molecular Biophysics and Integrative Bio-Imaging Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA.,Department of Molecular Biosciences, Northwestern University, Evanston, Illinois 60208, USA
| | - Chunli Yan
- Department of Chemistry, Center for Diagnostics and Therapeutics, Georgia State University, Atlanta, Georgia 30302, USA
| | - Jie Fang
- Howard Hughes Medical Institute, University of California, Berkeley, California 94720, USA
| | - Carla Inouye
- Li Ka Shing Center for Biomedical and Health Sciences, University of California, Berkeley, California 94720, USA
| | - Robert Tjian
- Howard Hughes Medical Institute, University of California, Berkeley, California 94720, USA.,Li Ka Shing Center for Biomedical and Health Sciences, University of California, Berkeley, California 94720, USA.,Department of Molecular and Cell Biology, University of California, Berkeley, California 94720, USA
| | - Ivaylo Ivanov
- Department of Chemistry, Center for Diagnostics and Therapeutics, Georgia State University, Atlanta, Georgia 30302, USA
| | - Eva Nogales
- Molecular Biophysics and Integrative Bio-Imaging Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA.,Howard Hughes Medical Institute, University of California, Berkeley, California 94720, USA.,Department of Molecular and Cell Biology, University of California, Berkeley, California 94720, USA
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280
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Goh BC, Hadden JA, Bernardi RC, Singharoy A, McGreevy R, Rudack T, Cassidy CK, Schulten K. Computational Methodologies for Real-Space Structural Refinement of Large Macromolecular Complexes. Annu Rev Biophys 2016; 45:253-78. [PMID: 27145875 DOI: 10.1146/annurev-biophys-062215-011113] [Citation(s) in RCA: 53] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
The rise of the computer as a powerful tool for model building and refinement has revolutionized the field of structure determination for large biomolecular systems. Despite the wide availability of robust experimental methods capable of resolving structural details across a range of spatiotemporal resolutions, computational hybrid methods have the unique ability to integrate the diverse data from multimodal techniques such as X-ray crystallography and electron microscopy into consistent, fully atomistic structures. Here, commonly employed strategies for computational real-space structural refinement are reviewed, and their specific applications are illustrated for several large macromolecular complexes: ribosome, virus capsids, chemosensory array, and photosynthetic chromatophore. The increasingly important role of computational methods in large-scale structural refinement, along with current and future challenges, is discussed.
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Affiliation(s)
- Boon Chong Goh
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801.,Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Jodi A Hadden
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801.,Energy Biosciences Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Rafael C Bernardi
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801.,Energy Biosciences Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Abhishek Singharoy
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Ryan McGreevy
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Till Rudack
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - C Keith Cassidy
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801.,Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Klaus Schulten
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801.,Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801.,Energy Biosciences Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801.,Center for the Physics of Living Cells, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801.,Center for Biophysics and Computational Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801;
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281
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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: 79] [Impact Index Per Article: 8.8] [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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282
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Bell JM, Chen M, Baldwin PR, Ludtke SJ. High resolution single particle refinement in EMAN2.1. Methods 2016; 100:25-34. [PMID: 26931650 PMCID: PMC4848122 DOI: 10.1016/j.ymeth.2016.02.018] [Citation(s) in RCA: 121] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2015] [Revised: 02/25/2016] [Accepted: 02/26/2016] [Indexed: 01/01/2023] Open
Abstract
EMAN2.1 is a complete image processing suite for quantitative analysis of grayscale images, with a primary focus on transmission electron microscopy, with complete workflows for performing high resolution single particle reconstruction, 2-D and 3-D heterogeneity analysis, random conical tilt reconstruction and subtomogram averaging, among other tasks. In this manuscript we provide the first detailed description of the high resolution single particle analysis pipeline and the philosophy behind its approach to the reconstruction problem. High resolution refinement is a fully automated process, and involves an advanced set of heuristics to select optimal algorithms for each specific refinement task. A gold standard FSC is produced automatically as part of refinement, providing a robust resolution estimate for the final map, and this is used to optimally filter the final CTF phase and amplitude corrected structure. Additional methods are in-place to reduce model bias during refinement, and to permit cross-validation using other computational methods.
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Affiliation(s)
- James M Bell
- Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA
| | - Muyuan Chen
- Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA
| | - Philip R Baldwin
- Department of Psychiatry, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA
| | - Steven J Ludtke
- Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA.
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283
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McGreevy R, Teo I, Singharoy A, Schulten K. Advances in the molecular dynamics flexible fitting method for cryo-EM modeling. Methods 2016; 100:50-60. [PMID: 26804562 PMCID: PMC4848153 DOI: 10.1016/j.ymeth.2016.01.009] [Citation(s) in RCA: 65] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2015] [Revised: 01/16/2016] [Accepted: 01/20/2016] [Indexed: 02/02/2023] Open
Abstract
Molecular Dynamics Flexible Fitting (MDFF) is an established technique for fitting all-atom structures of molecules into corresponding cryo-electron microscopy (cryo-EM) densities. The practical application of MDFF is simple but requires a user to be aware of and take measures against a variety of possible challenges presented by each individual case. Some of these challenges arise from the complexity of a molecular structure or the limited quality of available structural models and densities to be interpreted, while others stem from the intricacies of MDFF itself. The current article serves as an overview of the strategies that have been developed since MDFF's inception to overcome common challenges and successfully perform MDFF simulations.
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Affiliation(s)
- Ryan McGreevy
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, USA
| | - Ivan Teo
- Department of Physics, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Abhishek Singharoy
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, USA
| | - Klaus Schulten
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, USA; Department of Physics, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.
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284
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Extensive subunit contacts underpin herpesvirus capsid stability and interior-to-exterior allostery. Nat Struct Mol Biol 2016; 23:531-9. [PMID: 27111889 PMCID: PMC4899274 DOI: 10.1038/nsmb.3212] [Citation(s) in RCA: 53] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2016] [Accepted: 03/23/2016] [Indexed: 11/09/2022]
Abstract
The herpesvirus capsid is a complex protein assembly that includes hundreds of copies of four major subunits and lesser numbers of several minor proteins, all of which are essential for infectivity. Cryo-electron microscopy is uniquely suited for studying interactions that govern the assembly and function of such large functional complexes. Here we report two high-quality capsid structures, from human herpes simplex virus type 1 (HSV-1) and the animal pseudorabies virus (PRV), imaged inside intact virions at ~7-Å resolution. From these, we developed a complete model of subunit and domain organization and identified extensive networks of subunit contacts that underpin capsid stability and form a pathway that may signal the completion of DNA packaging from the capsid interior to outer surface, thereby initiating nuclear egress. Differences in the folding and orientation of subunit domains between herpesvirus capsids suggest that common elements have been modified for specific functions.
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285
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Structure of promoter-bound TFIID and model of human pre-initiation complex assembly. Nature 2016; 531:604-9. [PMID: 27007846 PMCID: PMC4856295 DOI: 10.1038/nature17394] [Citation(s) in RCA: 179] [Impact Index Per Article: 19.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2015] [Accepted: 02/03/2016] [Indexed: 12/11/2022]
Abstract
The general transcription factor IID (TFIID) plays a central role in the initiation of RNA polymerase II (Pol II)-dependent transcription by nucleating pre-initiation complex (PIC) assembly at the core promoter. TFIID comprises the TATA-binding protein (TBP) and 13 TBP-associated factors (TAF1-13), which specifically interact with a variety of core promoter DNA sequences. Here we present the structure of human TFIID in complex with TFIIA and core promoter DNA, determined by single-particle cryo-electron microscopy at sub-nanometre resolution. All core promoter elements are contacted by subunits of TFIID, with TAF1 and TAF2 mediating major interactions with the downstream promoter. TFIIA bridges the TBP-TATA complex with lobe B of TFIID. We also present the cryo-electron microscopy reconstruction of a fully assembled human TAF-less PIC. Superposition of common elements between the two structures provides novel insights into the general role of TFIID in promoter recognition, PIC assembly, and transcription initiation.
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286
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Sharp TH, Koster AJ, Gros P. Heterogeneous MAC Initiator and Pore Structures in a Lipid Bilayer by Phase-Plate Cryo-electron Tomography. Cell Rep 2016; 15:1-8. [PMID: 27052168 DOI: 10.1016/j.celrep.2016.03.002] [Citation(s) in RCA: 66] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2016] [Revised: 02/09/2016] [Accepted: 02/24/2016] [Indexed: 02/07/2023] Open
Abstract
Pore formation in membranes is important for mammalian immune defense against invading bacteria. Induced by complement activation, the membrane attack complex (MAC) forms through sequential binding and membrane insertion of C5b6, C7, C8, and C9. Using cryo-electron tomography with a Volta phase plate and subtomogram averaging, we imaged C5b-7, C5b-8, and C5b-9 complexes and determined the C5b-9 pore structure in lipid bilayers. The in situ C5b-9 pore structure at 2.3-nm resolution reveals a 10- to 11.5-nm cone-shaped pore starting with C5b678 and multiple copies of C9 that is poorly closed, yielding a seam between C9 and C6 substituting for the shorter β strands in C6 and C7. However, large variations of composite pore complexes are apparent in subtomograms. Oligomerized initiator complexes C5b-7 and C5b-8 show stages of membrane binding, deformation, and perforation that yield ∼3.5-nm-wide pores. These data indicate a dynamic process of pore formation that likely adapts to biological membranes under attack.
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Affiliation(s)
- Thomas H Sharp
- Section Electron Microscopy, Department of Molecular Cell Biology, Leiden University Medical Center, 2300 RC Leiden, the Netherlands.
| | - Abraham J Koster
- Section Electron Microscopy, Department of Molecular Cell Biology, Leiden University Medical Center, 2300 RC Leiden, the Netherlands; NeCEN, Gorlaeus Laboratories, Leiden University, 2333 CC Leiden, the Netherlands
| | - Piet Gros
- Crystal and Structural Chemistry, Bijvoet Center for Biomolecular Research and Department of Chemistry, Faculty of Science, Utrecht University, Padualaan 8, 3584 CH Utrecht, the Netherlands.
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287
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Galaz-Montoya JG, Hecksel CW, Baldwin PR, Wang E, Weaver SC, Schmid MF, Ludtke SJ, Chiu W. Alignment algorithms and per-particle CTF correction for single particle cryo-electron tomography. J Struct Biol 2016; 194:383-94. [PMID: 27016284 DOI: 10.1016/j.jsb.2016.03.018] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2016] [Revised: 03/11/2016] [Accepted: 03/21/2016] [Indexed: 10/22/2022]
Abstract
Single particle cryo-electron tomography (cryoSPT) extracts features from cryo-electron tomograms, followed by 3D classification, alignment and averaging to generate improved 3D density maps of such features. Robust methods to correct for the contrast transfer function (CTF) of the electron microscope are necessary for cryoSPT to reach its resolution potential. Many factors can make CTF correction for cryoSPT challenging, such as lack of eucentricity of the specimen stage, inherent low dose per image, specimen charging, beam-induced specimen motions, and defocus gradients resulting both from specimen tilting and from unpredictable ice thickness variations. Current CTF correction methods for cryoET make at least one of the following assumptions: that the defocus at the center of the image is the same across the images of a tiltseries, that the particles all lie at the same Z-height in the embedding ice, and/or that the specimen, the cryo-electron microscopy (cryoEM) grid and/or the carbon support are flat. These experimental conditions are not always met. We have developed a CTF correction algorithm for cryoSPT without making any of the aforementioned assumptions. We also introduce speed and accuracy improvements and a higher degree of automation to the subtomogram averaging algorithms available in EMAN2. Using motion-corrected images of isolated virus particles as a benchmark specimen, recorded with a DE20 direct detection camera, we show that our CTF correction and subtomogram alignment routines can yield subtomogram averages close to 4/5 Nyquist frequency of the detector under our experimental conditions.
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Affiliation(s)
- Jesús G Galaz-Montoya
- National Center for Macromolecular Imaging, Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, TX, USA
| | - Corey W Hecksel
- National Center for Macromolecular Imaging, Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, TX, USA; Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA
| | - Philip R Baldwin
- National Center for Macromolecular Imaging, Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, TX, USA; Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
| | - Eryu Wang
- Institute for Human Infections and Immunity and Department of Microbiology and Immunology, University of Texas Medical Branch, Galveston, TX, USA
| | - Scott C Weaver
- Institute for Human Infections and Immunity and Department of Microbiology and Immunology, University of Texas Medical Branch, Galveston, TX, USA
| | - Michael F Schmid
- National Center for Macromolecular Imaging, Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, TX, USA
| | - Steven J Ludtke
- National Center for Macromolecular Imaging, Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, TX, USA
| | - Wah Chiu
- National Center for Macromolecular Imaging, Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, TX, USA; Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA.
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288
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289
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Abstract
Bacteriophage T4 consists of a head for protecting its genome and a sheathed tail for inserting its genome into a host. The tail terminates with a multiprotein baseplate that changes its conformation from a "high-energy" dome-shaped to a "low-energy" star-shaped structure during infection. Although these two structures represent different minima in the total energy landscape of the baseplate assembly, as the dome-shaped structure readily changes to the star-shaped structure when the virus infects a host bacterium, the dome-shaped structure must have more energy than the star-shaped structure. Here we describe the electron microscopy structure of a 3.3-MDa in vitro-assembled star-shaped baseplate with a resolution of 3.8 Å. This structure, together with other genetic and structural data, shows why the high-energy baseplate is formed in the presence of the central hub and how the baseplate changes to the low-energy structure, via two steps during infection. Thus, the presence of the central hub is required to initiate the assembly of metastable, high-energy structures. If the high-energy structure is formed and stabilized faster than the low-energy structure, there will be insufficient components to assemble the low-energy structure.
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290
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Marabini R, Ludtke SJ, Murray SC, Chiu W, de la Rosa-Trevín JM, Patwardhan A, Heymann JB, Carazo JM. The Electron Microscopy eXchange (EMX) initiative. J Struct Biol 2016; 194:156-63. [PMID: 26873784 DOI: 10.1016/j.jsb.2016.02.008] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2015] [Revised: 02/02/2016] [Accepted: 02/05/2016] [Indexed: 02/02/2023]
Abstract
Three-dimensional electron microscopy (3DEM) of ice-embedded samples allows the structural analysis of large biological macromolecules close to their native state. Different techniques have been developed during the last forty years to process cryo-electron microscopy (cryo-EM) data. Not surprisingly, success in analysis and interpretation is highly correlated with the continuous development of image processing packages. The field has matured to the point where further progress in data and methods sharing depends on an agreement between the packages on how to describe common image processing tasks. Such standardization will facilitate the use of software as well as seamless collaboration, allowing the sharing of rich information between different platforms. Our aim here is to describe the Electron Microscopy eXchange (EMX) initiative, launched at the 2012 Instruct Image Processing Center Developer Workshop, with the intention of developing a first set of standard conventions for the interchange of information for single-particle analysis (EMX version 1.0). These conventions cover the specification of the metadata for micrograph and particle images, including contrast transfer function (CTF) parameters and particle orientations. EMX v1.0 has already been implemented in the Bsoft, EMAN, Xmipp and Scipion image processing packages. It has been and will be used in the CTF and EMDataBank Validation Challenges respectively. It is also being used in EMPIAR, the Electron Microscopy Pilot Image Archive, which stores raw image data related to the 3DEM reconstructions in EMDB.
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Affiliation(s)
- Roberto Marabini
- Escuela Politecnica Superior, Universidad Autonoma de Madrid, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain.
| | - Steven J Ludtke
- National Center for Macromolecular Imaging, Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Stephen C Murray
- Graduate Program in Structural and Computational Biology and Molecular Biophysics, Baylor College of Medicine, Houston, TX 77030 USA
| | - Wah Chiu
- National Center for Macromolecular Imaging, Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Jose M de la Rosa-Trevín
- Biocomputing Unit, National Center for Biotechnology (CSIC), c/Darwin, 3, Campus Universidad Autónoma, 28049 Cantoblanco, Madrid, Spain
| | - Ardan Patwardhan
- European Molecular Biology Laboratory - European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - J Bernard Heymann
- Laboratory of Structural Biology Research, National Institute of Arthritis, Musculoskeletal and Skin Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Jose M Carazo
- Biocomputing Unit, National Center for Biotechnology (CSIC), c/Darwin, 3, Campus Universidad Autónoma, 28049 Cantoblanco, Madrid, Spain
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291
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Touw WG, Joosten RP, Vriend G. New Biological Insights from Better Structure Models. J Mol Biol 2016; 428:1375-1393. [PMID: 26869101 DOI: 10.1016/j.jmb.2016.02.002] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2015] [Revised: 01/04/2016] [Accepted: 02/01/2016] [Indexed: 02/01/2023]
Abstract
Structure validation is a key component of all steps in the structure determination process, from structure building, refinement, deposition, and evaluation all the way to post-deposition optimisation of structures in the Protein Data Bank (PDB) by re-refinement and re-building. Today, many aspects of protein structures are understood better than 10years ago, and combined with improved software and more computing power, the automated PDB_REDO procedure can significantly improve about 85% of all X-ray structures ever deposited in the PDB. We review structure validation, structure improvement, and a series of validation resources and facilities that give access to improved PDB files and to reports on the quality of the original and the improved structures. Post-deposition optimisation generally leads to improved protein structures and a series of examples will illustrate how that, in turn, leads to improved or even novel biological insights.
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Affiliation(s)
- Wouter G Touw
- Centre for Molecular and Biomolecular Informatics, Radboud University Medical Center, Geert Grooteplein-Zuid 26-28, 6525 GA Nijmegen, The Netherlands
| | - Robbie P Joosten
- Department of Biochemistry, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Gert Vriend
- Centre for Molecular and Biomolecular Informatics, Radboud University Medical Center, Geert Grooteplein-Zuid 26-28, 6525 GA Nijmegen, The Netherlands.
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292
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Oldham ML, Hite RK, Steffen AM, Damko E, Li Z, Walz T, Chen J. A mechanism of viral immune evasion revealed by cryo-EM analysis of the TAP transporter. Nature 2016; 529:537-40. [PMID: 26789246 PMCID: PMC4848044 DOI: 10.1038/nature16506] [Citation(s) in RCA: 99] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2015] [Accepted: 12/01/2015] [Indexed: 02/07/2023]
Abstract
Cellular immunity against viral infection and tumor cells depends on antigen presentation by the major histocompatibility complex class 1 molecules (MHC I). Intracellular antigenic peptides are transported into the endoplasmic reticulum (ER) by the transporter associated with antigen processing (TAP) and then loaded onto the nascent MHC I, which are exported to the cell surface and present peptides to the immune system1. Cytotoxic T lymphocytes recognize non-self peptides and program the infected or malignant cells for apoptosis. Defects in TAP account for immunodeficiency and tumor development. To escape immune surveillance, some viruses have evolved strategies to either down-regulate TAP expression or directly inhibit TAP activity. To date neither the architecture of TAP nor the mechanism of viral inhibition has been elucidated at the structural level. In this study we describe the cryo-electron microscopy (cryo-EM) structure of human TAP in complex with its inhibitor ICP47, a small protein produced by the herpes simplex virus I. We show that the twelve transmembrane helices and two cytosolic nucleotide-binding domains (NBDs) of the transporter adopt an inward-facing conformation with the two NBDs separated. The viral inhibitor ICP47 forms a long helical hairpin, which plugs the translocation pathway of TAP from the cytoplasmic side. Association of ICP47 precludes substrate binding and also prevents NBD closure necessary for ATP hydrolysis. This work illustrates a striking example of immune evasion by persistent viruses. By blocking viral antigens from entering the ER, herpes simplex virus is hidden from cytotoxic T lymphocytes, which may contribute to establishing a lifelong infection in the host.
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Affiliation(s)
- Michael L Oldham
- The Rockefeller University, 1230 York Avenue, New York, New York 10065, USA.,Howard Hughes Medical Institute, 4000 Jones Bridge Road, Chevy Chase, Maryland 20815, USA
| | - Richard K Hite
- The Rockefeller University, 1230 York Avenue, New York, New York 10065, USA.,Howard Hughes Medical Institute, 4000 Jones Bridge Road, Chevy Chase, Maryland 20815, USA
| | - Alanna M Steffen
- Howard Hughes Medical Institute, 4000 Jones Bridge Road, Chevy Chase, Maryland 20815, USA
| | - Ermelinda Damko
- The Rockefeller University, 1230 York Avenue, New York, New York 10065, USA
| | - Zongli Li
- Howard Hughes Medical Institute, 4000 Jones Bridge Road, Chevy Chase, Maryland 20815, USA.,Department of Cell Biology, Harvard Medical School, 240 Longwood Avenue, Boston, Massachusetts 02115, USA
| | - Thomas Walz
- The Rockefeller University, 1230 York Avenue, New York, New York 10065, USA
| | - Jue Chen
- The Rockefeller University, 1230 York Avenue, New York, New York 10065, USA.,Howard Hughes Medical Institute, 4000 Jones Bridge Road, Chevy Chase, Maryland 20815, USA
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293
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Liu Z, Guo F, Wang F, Li TC, Jiang W. 2.9 Å Resolution Cryo-EM 3D Reconstruction of Close-Packed Virus Particles. Structure 2016; 24:319-28. [PMID: 26777413 DOI: 10.1016/j.str.2015.12.006] [Citation(s) in RCA: 67] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2015] [Revised: 12/14/2015] [Accepted: 12/14/2015] [Indexed: 01/15/2023]
Abstract
Single-particle cryoelectron microscopy typically discards close-packed particle images as unusable data. Here, we report an image processing strategy and case study of obtaining near-atomic resolution 3D reconstructions from close-packed particles. Multiple independent de novo initial models were constructed to determine and cross-validate the particle parameters. The particles with consistent views were further refined including not only Euler angles and center positions but also defocus, astigmatism, beam tilt, and overall and anisotropic magnification. We demonstrated this strategy with a 2.9 Å resolution reconstruction of a 1.67 MDa virus-like particle of a circovirus, PCV2, recorded on 86 photographic films. The map resolution was further validated with a phase-randomization test and local resolution assessment, and the atomic model was validated with MolProbity and EMRinger. Close-packed virus particles were thus shown not only to be useful for high-resolution 3D reconstructions but also to allow data collection at significantly improved throughput for near-atomic resolution reconstructions.
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Affiliation(s)
- Zheng Liu
- Department of Biological Sciences, Markey Center for Structural Biology, Purdue University, West Lafayette, IN 47907, USA
| | - Fei Guo
- Department of Biological Sciences, Markey Center for Structural Biology, Purdue University, West Lafayette, IN 47907, USA
| | - Feng Wang
- Department of Biological Sciences, Markey Center for Structural Biology, Purdue University, West Lafayette, IN 47907, USA
| | - Tian-Cheng Li
- Department of Virology II, National Institute of Infectious Diseases, Gakuen 4-7-1, Musashi-murayama, Tokyo 208-0011, Japan
| | - Wen Jiang
- Department of Biological Sciences, Markey Center for Structural Biology, Purdue University, West Lafayette, IN 47907, USA.
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294
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Abstract
Web-based protein structure databases come in a wide variety of types and levels of information content. Those having the most general interest are the various atlases that describe each experimentally determined protein structure and provide useful links, analyses, and schematic diagrams relating to its 3D structure and biological function. Also of great interest are the databases that classify 3D structures by their folds as these can reveal evolutionary relationships which may be hard to detect from sequence comparison alone. Related to these are the numerous servers that compare folds-particularly useful for newly solved structures, and especially those of unknown function. Beyond these are a vast number of databases for the more specialized user, dealing with specific families, diseases, structural features, and so on.
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Affiliation(s)
- Roman A Laskowski
- European Bioinformatics Institute, European Molecular Biology Laboratory, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.
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295
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296
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Abstract
The use of macromolecular structures is widespread for a variety of applications, from teaching protein structure principles all the way to ligand optimization in drug development. Applying data mining techniques on these experimentally determined structures requires a highly uniform, standardized structural data source. The Protein Data Bank (PDB) has evolved over the years toward becoming the standard resource for macromolecular structures. However, the process selecting the data most suitable for specific applications is still very much based on personal preferences and understanding of the experimental techniques used to obtain these models. In this chapter, we will first explain the challenges with data standardization, annotation, and uniformity in the PDB entries determined by X-ray crystallography. We then discuss the specific effect that crystallographic data quality and model optimization methods have on structural models and how validation tools can be used to make informed choices. We also discuss specific advantages of using the PDB_REDO databank as a resource for structural data. Finally, we will provide guidelines on how to select the most suitable protein structure models for detailed analysis and how to select a set of structure models suitable for data mining.
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Affiliation(s)
- Bart van Beusekom
- Department of Biochemistry, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
| | - Anastassis Perrakis
- Department of Biochemistry, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
| | - Robbie P Joosten
- Department of Biochemistry, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands.
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297
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Pintilie G, Chen DH, Haase-Pettingell CA, King JA, Chiu W. Resolution and Probabilistic Models of Components in CryoEM Maps of Mature P22 Bacteriophage. Biophys J 2015; 110:827-39. [PMID: 26743049 DOI: 10.1016/j.bpj.2015.11.3522] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2015] [Revised: 10/14/2015] [Accepted: 11/11/2015] [Indexed: 01/08/2023] Open
Abstract
CryoEM continues to produce density maps of larger and more complex assemblies with multiple protein components of mixed symmetries. Resolution is not always uniform throughout a cryoEM map, and it can be useful to estimate the resolution in specific molecular components of a large assembly. In this study, we present procedures to 1) estimate the resolution in subcomponents by gold-standard Fourier shell correlation (FSC); 2) validate modeling procedures, particularly at medium resolutions, which can include loop modeling and flexible fitting; and 3) build probabilistic models that combine high-accuracy priors (such as crystallographic structures) with medium-resolution cryoEM densities. As an example, we apply these methods to new cryoEM maps of the mature bacteriophage P22, reconstructed without imposing icosahedral symmetry. Resolution estimates based on gold-standard FSC show the highest resolution in the coat region (7.6 Å), whereas other components are at slightly lower resolutions: portal (9.2 Å), hub (8.5 Å), tailspike (10.9 Å), and needle (10.5 Å). These differences are indicative of inherent structural heterogeneity and/or reconstruction accuracy in different subcomponents of the map. Probabilistic models for these subcomponents provide new insights, to our knowledge, and structural information when taking into account uncertainty given the limitations of the observed density.
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Affiliation(s)
- Grigore Pintilie
- Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, Texas.
| | - Dong-Hua Chen
- Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, Texas
| | | | - Jonathan A King
- Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Wah Chiu
- Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, Texas
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298
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Rosenthal PB. From high symmetry to high resolution in biological electron microscopy: a commentary on Crowther (1971) 'Procedures for three-dimensional reconstruction of spherical viruses by Fourier synthesis from electron micrographs'. Philos Trans R Soc Lond B Biol Sci 2015; 370:rstb.2014.0345. [PMID: 25750240 PMCID: PMC4360125 DOI: 10.1098/rstb.2014.0345] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Elucidation of the structure of biological macromolecules and larger assemblies has been essential to understanding the roles they play in living processes. Methods for three-dimensional structure determination of biological assemblies from images recorded in the electron microscope were therefore a key development. In his paper published in Philosophical Transactions B in 1971, Crowther described new computational procedures applied to the first three-dimensional reconstruction of an icosahedral virus from images of virus particles preserved in negative stain. The method for determining the relative orientation of randomly oriented particles and combining their images for reconstruction exploited the high symmetry of the virus particle. Computational methods for image analysis have since been extended to include biological assemblies without symmetry. Further experimental advances, combined with image analysis, have led to the method of cryomicroscopy, which is now used by structural biologists to study the structure and dynamics of biological machines and assemblies in atomic detail. This commentary was written to celebrate the 350th anniversary of the journal Philosophical Transactions of the Royal Society.
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Affiliation(s)
- Peter B Rosenthal
- Division of Physical Biochemistry, MRC National Institute for Medical Research, The Ridgeway, Mill Hill, London NW7 1AA, UK
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299
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Degiacomi MT, Benesch JLP. EM∩IM: software for relating ion mobility mass spectrometry and electron microscopy data. Analyst 2015; 141:70-5. [PMID: 26616427 DOI: 10.1039/c5an01636c] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
We present EM∩IM, software that allows the calculation of collision cross-sections from electron density maps obtained for example by means of transmission electron microscopy. This allows the assessment of structures other than those described by atomic coordinates with ion mobility mass spectrometry data, and provides a new means for contouring and validating electron density maps. EM∩IM thereby facilitates the use of data obtained in the gas phase within structural biology studies employing diverse experimental methodologies.
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Affiliation(s)
- Matteo T Degiacomi
- Department of Chemistry, Physical & Theoretical Chemistry Laboratory, South Parks Road, Oxford, OX1 3QZ, UK.
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300
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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: 200] [Impact Index Per Article: 20.0] [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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