1
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Singh D, Soni N, Hutchings J, Echeverria I, Shaikh F, Duquette M, Suslov S, Li Z, van Eeuwen T, Molloy K, Shi Y, Wang J, Guo Q, Chait BT, Fernandez-Martinez J, Rout MP, Sali A, Villa E. The molecular architecture of the nuclear basket. Cell 2024; 187:5267-5281.e13. [PMID: 39127037 DOI: 10.1016/j.cell.2024.07.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2024] [Revised: 05/24/2024] [Accepted: 07/12/2024] [Indexed: 08/12/2024]
Abstract
The nuclear pore complex (NPC) is the sole mediator of nucleocytoplasmic transport. Despite great advances in understanding its conserved core architecture, the peripheral regions can exhibit considerable variation within and between species. One such structure is the cage-like nuclear basket. Despite its crucial roles in mRNA surveillance and chromatin organization, an architectural understanding has remained elusive. Using in-cell cryo-electron tomography and subtomogram analysis, we explored the NPC's structural variations and the nuclear basket across fungi (yeast; S. cerevisiae), mammals (mouse; M. musculus), and protozoa (T. gondii). Using integrative structural modeling, we computed a model of the basket in yeast and mammals that revealed how a hub of nucleoporins (Nups) in the nuclear ring binds to basket-forming Mlp/Tpr proteins: the coiled-coil domains of Mlp/Tpr form the struts of the basket, while their unstructured termini constitute the basket distal densities, which potentially serve as a docking site for mRNA preprocessing before nucleocytoplasmic transport.
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Affiliation(s)
- Digvijay Singh
- School of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, USA
| | - Neelesh Soni
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Joshua Hutchings
- School of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, USA
| | - Ignacia Echeverria
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Farhaz Shaikh
- School of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, USA
| | - Madeleine Duquette
- School of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, USA
| | - Sergey Suslov
- School of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, USA
| | - Zhixun Li
- State Key Laboratory of Protein and Plant Gene Research, Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, School of Life Sciences, Peking University, Beijing 100871, P.R. China
| | - Trevor van Eeuwen
- Laboratory of Cellular and Structural Biology, The Rockefeller University, New York, NY 10065, USA
| | - Kelly Molloy
- Laboratory of Mass Spectrometry and Gaseous Ion Chemistry, The Rockefeller University, New York, NY 10065, USA
| | - Yi Shi
- Laboratory of Mass Spectrometry and Gaseous Ion Chemistry, The Rockefeller University, New York, NY 10065, USA
| | - Junjie Wang
- Laboratory of Mass Spectrometry and Gaseous Ion Chemistry, The Rockefeller University, New York, NY 10065, USA
| | - Qiang Guo
- State Key Laboratory of Protein and Plant Gene Research, Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, School of Life Sciences, Peking University, Beijing 100871, P.R. China
| | - Brian T Chait
- Laboratory of Mass Spectrometry and Gaseous Ion Chemistry, The Rockefeller University, New York, NY 10065, USA
| | - Javier Fernandez-Martinez
- Laboratory of Cellular and Structural Biology, The Rockefeller University, New York, NY 10065, USA; Ikerbasque, Basque Foundation for Science, 48013 Bilbao, Spain; Instituto Biofisika (UPV/EHU, CSIC), University of the Basque Country, 48940 Leioa, Spain.
| | - Michael P Rout
- Laboratory of Cellular and Structural Biology, The Rockefeller University, New York, NY 10065, USA.
| | - Andrej Sali
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA 94158, USA; Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA 94158, USA.
| | - Elizabeth Villa
- School of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, USA; Howard Hughes Medical Institute, University of California, San Diego, La Jolla, CA 92093, USA.
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2
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Lacey SE, Graziadei A, Pigino G. Extensive structural rearrangement of intraflagellar transport trains underpins bidirectional cargo transport. Cell 2024; 187:4621-4636.e18. [PMID: 39067443 PMCID: PMC11349379 DOI: 10.1016/j.cell.2024.06.041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Revised: 05/06/2024] [Accepted: 06/28/2024] [Indexed: 07/30/2024]
Abstract
Bidirectional transport in cilia is carried out by polymers of the IFTA and IFTB protein complexes, called anterograde and retrograde intraflagellar transport (IFT) trains. Anterograde trains deliver cargoes from the cell to the cilium tip, then convert into retrograde trains for cargo export. We set out to understand how the IFT complexes can perform these two directly opposing roles before and after conversion. We use cryoelectron tomography and in situ cross-linking mass spectrometry to determine the structure of retrograde IFT trains and compare it with the known structure of anterograde trains. The retrograde train is a 2-fold symmetric polymer organized around a central thread of IFTA complexes. We conclude that anterograde-to-retrograde remodeling involves global rearrangements of the IFTA/B complexes and requires complete disassembly of the anterograde train. Finally, we describe how conformational changes to cargo-binding sites facilitate unidirectional cargo transport in a bidirectional system.
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3
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Liu X, Zhang Y, Wen Z, Hao Y, Banks CAS, Cesare J, Bhattacharya S, Arvindekar S, Lange JJ, Xie Y, Garcia BA, Slaughter BD, Unruh JR, Viswanath S, Florens L, Workman JL, Washburn MP. An integrated structural model of the DNA damage-responsive H3K4me3 binding WDR76:SPIN1 complex with the nucleosome. Proc Natl Acad Sci U S A 2024; 121:e2318601121. [PMID: 39116123 PMCID: PMC11331135 DOI: 10.1073/pnas.2318601121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Accepted: 06/21/2024] [Indexed: 08/10/2024] Open
Abstract
Serial capture affinity purification (SCAP) is a powerful method to isolate a specific protein complex. When combined with cross-linking mass spectrometry and computational approaches, one can build an integrated structural model of the isolated complex. Here, we applied SCAP to dissect a subpopulation of WDR76 in complex with SPIN1, a histone reader that recognizes trimethylated histone H3 lysine4 (H3K4me3). In contrast to a previous SCAP analysis of the SPIN1:SPINDOC complex, histones and the H3K4me3 mark were enriched with the WDR76:SPIN1 complex. Next, interaction network analysis of copurifying proteins and microscopy analysis revealed a potential role of the WDR76:SPIN1 complex in the DNA damage response. Since we detected 149 pairs of cross-links between WDR76, SPIN1, and histones, we then built an integrated structural model of the complex where SPIN1 recognized the H3K4me3 epigenetic mark while interacting with WDR76. Finally, we used the powerful Bayesian Integrative Modeling approach as implemented in the Integrative Modeling Platform to build a model of WDR76 and SPIN1 bound to the nucleosome.
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Affiliation(s)
- Xingyu Liu
- Stowers Institute for Medical Research, Kansas City, MO 64110
| | - Ying Zhang
- Stowers Institute for Medical Research, Kansas City, MO 64110
| | - Zhihui Wen
- Stowers Institute for Medical Research, Kansas City, MO 64110
| | - Yan Hao
- Stowers Institute for Medical Research, Kansas City, MO 64110
| | | | - Joseph Cesare
- Stowers Institute for Medical Research, Kansas City, MO 64110
- Medical Scientist Training Program, Department of Cancer Biology, University of Kansas Medical Center, Kansas City, KS 66150
| | | | - Shreyas Arvindekar
- National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bangalore 560065, India
| | - Jeffrey J Lange
- Stowers Institute for Medical Research, Kansas City, MO 64110
| | - Yixuan Xie
- Department of Biochemistry and Molecular Biophysics, Washington University St. Louis School of Medicine, St. Louis, MO 63110
| | - Benjamin A Garcia
- Department of Biochemistry and Molecular Biophysics, Washington University St. Louis School of Medicine, St. Louis, MO 63110
| | | | - Jay R Unruh
- Stowers Institute for Medical Research, Kansas City, MO 64110
| | - Shruthi Viswanath
- National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bangalore 560065, India
| | | | - Jerry L Workman
- Stowers Institute for Medical Research, Kansas City, MO 64110
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4
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Latham AP, Tempkin JOB, Otsuka S, Zhang W, Ellenberg J, Sali A. Integrative spatiotemporal modeling of biomolecular processes: application to the assembly of the Nuclear Pore Complex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.06.606842. [PMID: 39149317 PMCID: PMC11326192 DOI: 10.1101/2024.08.06.606842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/17/2024]
Abstract
Dynamic processes involving biomolecules are essential for the function of the cell. Here, we introduce an integrative method for computing models of these processes based on multiple heterogeneous sources of information, including time-resolved experimental data and physical models of dynamic processes. We first compute integrative structure models at fixed time points and then optimally select and connect these snapshots into a series of trajectories that optimize the likelihood of both the snapshots and transitions between them. The method is demonstrated by application to the assembly process of the human Nuclear Pore Complex in the context of the reforming nuclear envelope during mitotic cell division, based on live-cell correlated electron tomography, bulk fluorescence correlation spectroscopy-calibrated quantitative live imaging, and a structural model of the fully-assembled Nuclear Pore Complex. Modeling of the assembly process improves the model precision over static integrative structure modeling alone. The method is applicable to a wide range of time-dependent systems in cell biology, and is available to the broader scientific community through an implementation in the open source Integrative Modeling Platform software.
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Affiliation(s)
- Andrew P Latham
- Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Jeremy O B Tempkin
- Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Shotaro Otsuka
- Cell Biology and Biophysics Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Wanlu Zhang
- Cell Biology and Biophysics Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Jan Ellenberg
- Cell Biology and Biophysics Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Andrej Sali
- Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, CA 94143, USA
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5
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Singh D, Soni N, Hutchings J, Echeverria I, Shaikh F, Duquette M, Suslov S, Li Z, van Eeuwen T, Molloy K, Shi Y, Wang J, Guo Q, Chait BT, Fernandez-Martinez J, Rout MP, Sali A, Villa E. The Molecular Architecture of the Nuclear Basket. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.27.587068. [PMID: 38586009 PMCID: PMC10996695 DOI: 10.1101/2024.03.27.587068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
The nuclear pore complex (NPC) is the sole mediator of nucleocytoplasmic transport. Despite great advances in understanding its conserved core architecture, the peripheral regions can exhibit considerable variation within and between species. One such structure is the cage-like nuclear basket. Despite its crucial roles in mRNA surveillance and chromatin organization, an architectural understanding has remained elusive. Using in-cell cryo-electron tomography and subtomogram analysis, we explored the NPC's structural variations and the nuclear basket across fungi (yeast; S. cerevisiae), mammals (mouse; M. musculus), and protozoa (T. gondii). Using integrative structural modeling, we computed a model of the basket in yeast and mammals that revealed how a hub of Nups in the nuclear ring binds to basket-forming Mlp/Tpr proteins: the coiled-coil domains of Mlp/Tpr form the struts of the basket, while their unstructured termini constitute the basket distal densities, which potentially serve as a docking site for mRNA preprocessing before nucleocytoplasmic transport.
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Affiliation(s)
- Digvijay Singh
- School of Biological Sciences, University of California San Diego, La Jolla, CA 92093, USA
| | - Neelesh Soni
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA
| | - Joshua Hutchings
- School of Biological Sciences, University of California San Diego, La Jolla, CA 92093, USA
| | - Ignacia Echeverria
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Farhaz Shaikh
- School of Biological Sciences, University of California San Diego, La Jolla, CA 92093, USA
| | - Madeleine Duquette
- School of Biological Sciences, University of California San Diego, La Jolla, CA 92093, USA
| | - Sergey Suslov
- School of Biological Sciences, University of California San Diego, La Jolla, CA 92093, USA
| | - Zhixun Li
- State Key Laboratory of Protein and Plant Gene Research, Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, School of Life Sciences, Peking University, Beijing 100871, P. R. China
| | - Trevor van Eeuwen
- Laboratory of Cellular and Structural Biology, The Rockefeller University, New York, NY 10065, USA
| | - Kelly Molloy
- Laboratory of Mass Spectrometry and Gaseous Ion Chemistry, The Rockefeller University, New York, NY 10065, USA
| | - Yi Shi
- Laboratory of Mass Spectrometry and Gaseous Ion Chemistry, The Rockefeller University, New York, NY 10065, USA
| | - Junjie Wang
- Laboratory of Mass Spectrometry and Gaseous Ion Chemistry, The Rockefeller University, New York, NY 10065, USA
| | - Qiang Guo
- State Key Laboratory of Protein and Plant Gene Research, Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, School of Life Sciences, Peking University, Beijing 100871, P. R. China
| | - Brian T Chait
- Laboratory of Mass Spectrometry and Gaseous Ion Chemistry, The Rockefeller University, New York, NY 10065, USA
| | - Javier Fernandez-Martinez
- Laboratory of Cellular and Structural Biology, The Rockefeller University, New York, NY 10065, USA
- Ikerbasque, Basque Foundation for Science, 48013 Bilbao, Spain
- Instituto Biofisika (UPV/EHU, CSIC), University of the Basque Country, 48940 Leioa, Spain
| | - Michael P Rout
- Laboratory of Cellular and Structural Biology, The Rockefeller University, New York, NY 10065, USA
| | - Andrej Sali
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA
- Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, CA 94158, USA
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Elizabeth Villa
- School of Biological Sciences, University of California San Diego, La Jolla, CA 92093, USA
- Howard Hughes Medical Institute, University of California San Diego, La Jolla, CA 92093, USA
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6
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Pasani S, Menon KS, Viswanath S. The molecular architecture of the desmosomal outer dense plaque by integrative structural modeling. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.06.13.544884. [PMID: 37398295 PMCID: PMC10312763 DOI: 10.1101/2023.06.13.544884] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Desmosomes mediate cell-cell adhesion and are prevalent in tissues under mechanical stress. However, their detailed structural characterization is not available. Here, we characterized the molecular architecture of the desmosomal outer dense plaque (ODP) using Bayesian integrative structural modeling via the Integrative Modeling Platform. Starting principally from the structural interpretation of an electron cryo-tomogram, we integrated information from X-ray crystallography, an immuno-electron microscopy study, biochemical assays, in-silico predictions of transmembrane and disordered regions, homology modeling, and stereochemistry information. The integrative structure was validated by information from imaging, tomography, and biochemical studies that were not used in modeling. The ODP resembles a densely packed cylinder with a PKP layer and a PG layer; the desmosomal cadherins and PKP span these two layers. Our integrative approach allowed us to localize disordered regions, such as N-PKP and PG-C. We refined previous protein-protein interactions between desmosomal proteins and provided possible structural hypotheses for defective cell-cell adhesion in several diseases by mapping disease-related mutations on the structure. Finally, we point to features of the structure that could confer resilience to mechanical stress. Our model provides a basis for generating experimentally verifiable hypotheses on the structure and function of desmosomal proteins in normal and disease states.
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Affiliation(s)
- Satwik Pasani
- National Center for Biological Sciences, Tata Institute of Fundamental Research, Bengaluru 560065, India
| | - Kavya S Menon
- National Center for Biological Sciences, Tata Institute of Fundamental Research, Bengaluru 560065, India
| | - Shruthi Viswanath
- National Center for Biological Sciences, Tata Institute of Fundamental Research, Bengaluru 560065, India
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7
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Arvindekar S, Pathak AS, Majila K, Viswanath S. Optimizing representations for integrative structural modeling using Bayesian model selection. Bioinformatics 2024; 40:btae106. [PMID: 38391029 PMCID: PMC10924281 DOI: 10.1093/bioinformatics/btae106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Revised: 02/03/2024] [Accepted: 02/21/2024] [Indexed: 02/24/2024] Open
Abstract
MOTIVATION Integrative structural modeling combines data from experiments, physical principles, statistics of previous structures, and prior models to obtain structures of macromolecular assemblies that are challenging to characterize experimentally. The choice of model representation is a key decision in integrative modeling, as it dictates the accuracy of scoring, efficiency of sampling, and resolution of analysis. But currently, the choice is usually made ad hoc, manually. RESULTS Here, we report NestOR (Nested Sampling for Optimizing Representation), a fully automated, statistically rigorous method based on Bayesian model selection to identify the optimal coarse-grained representation for a given integrative modeling setup. Given an integrative modeling setup, it determines the optimal representations from given candidate representations based on their model evidence and sampling efficiency. The performance of NestOR was evaluated on a benchmark of four macromolecular assemblies. AVAILABILITY AND IMPLEMENTATION NestOR is implemented in the Integrative Modeling Platform (https://integrativemodeling.org) and is available at https://github.com/isblab/nestor. Data for the benchmark is at https://www.doi.org/10.5281/zenodo.10360718.
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Affiliation(s)
- Shreyas Arvindekar
- National Center for Biological Sciences, Tata Institute of Fundamental Research, Bangalore 560065, India
| | - Aditi S Pathak
- National Center for Biological Sciences, Tata Institute of Fundamental Research, Bangalore 560065, India
| | - Kartik Majila
- National Center for Biological Sciences, Tata Institute of Fundamental Research, Bangalore 560065, India
| | - Shruthi Viswanath
- National Center for Biological Sciences, Tata Institute of Fundamental Research, Bangalore 560065, India
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8
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Arvindekar S, Pathak AS, Majila K, Viswanath S. Optimizing representations for integrative structural modeling using Bayesian model selection. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.12.571227. [PMID: 38168172 PMCID: PMC10760022 DOI: 10.1101/2023.12.12.571227] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
Motivation Integrative structural modeling combines data from experiments, physical principles, statistics of previous structures, and prior models to obtain structures of macromolecular assemblies that are challenging to characterize experimentally. The choice of model representation is a key decision in integrative modeling, as it dictates the accuracy of scoring, efficiency of sampling, and resolution of analysis. But currently, the choice is usually made ad hoc, manually. Results Here, we report NestOR (Nested Sampling for Optimizing Representation), a fully automated, statistically rigorous method based on Bayesian model selection to identify the optimal coarse-grained representation for a given integrative modeling setup. Given an integrative modeling setup, it determines the optimal representations from given candidate representations based on their model evidence and sampling efficiency. The performance of NestOR was evaluated on a benchmark of four macromolecular assemblies. Availability NestOR is implemented in the Integrative Modeling Platform (https://integrativemodeling.org) and is available at https://github.com/isblab/nestor.
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Affiliation(s)
- Shreyas Arvindekar
- National Center for Biological Sciences, Tata Institute of Fundamental Research, Bangalore, India 560065
| | - Aditi S. Pathak
- National Center for Biological Sciences, Tata Institute of Fundamental Research, Bangalore, India 560065
| | - Kartik Majila
- National Center for Biological Sciences, Tata Institute of Fundamental Research, Bangalore, India 560065
| | - Shruthi Viswanath
- National Center for Biological Sciences, Tata Institute of Fundamental Research, Bangalore, India 560065
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9
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Ghanaeian A, Majhi S, McCafferty CL, Nami B, Black CS, Yang SK, Legal T, Papoulas O, Janowska M, Valente-Paterno M, Marcotte EM, Wloga D, Bui KH. Integrated modeling of the Nexin-dynein regulatory complex reveals its regulatory mechanism. Nat Commun 2023; 14:5741. [PMID: 37714832 PMCID: PMC10504270 DOI: 10.1038/s41467-023-41480-7] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Accepted: 09/05/2023] [Indexed: 09/17/2023] Open
Abstract
Cilia are hairlike protrusions that project from the surface of eukaryotic cells and play key roles in cell signaling and motility. Ciliary motility is regulated by the conserved nexin-dynein regulatory complex (N-DRC), which links adjacent doublet microtubules and regulates and coordinates the activity of outer doublet complexes. Despite its critical role in cilia motility, the assembly and molecular basis of the regulatory mechanism are poorly understood. Here, using cryo-electron microscopy in conjunction with biochemical cross-linking and integrative modeling, we localize 12 DRC subunits in the N-DRC structure of Tetrahymena thermophila. We also find that the CCDC96/113 complex is in close contact with the DRC9/10 in the linker region. In addition, we reveal that the N-DRC is associated with a network of coiled-coil proteins that most likely mediates N-DRC regulatory activity.
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Affiliation(s)
- Avrin Ghanaeian
- Department of Anatomy and Cell Biology, Faculty of Medicine and Health Sciences, McGill University, Québec, Canada
| | - Sumita Majhi
- Laboratory of Cytoskeleton and Cilia Biology, Nencki Institute of Experimental Biology of Polish Academy of Sciences, 3 Pasteur Street, 02-093, Warsaw, Poland
| | - Caitlyn L McCafferty
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of Texas, Austin, TX, USA
| | - Babak Nami
- Genetics and Genome Biology Program, Hospital for Sick Children, Toronto, Canada
| | - Corbin S Black
- Department of Anatomy and Cell Biology, Faculty of Medicine and Health Sciences, McGill University, Québec, Canada
| | - Shun Kai Yang
- Department of Anatomy and Cell Biology, Faculty of Medicine and Health Sciences, McGill University, Québec, Canada
| | - Thibault Legal
- Department of Anatomy and Cell Biology, Faculty of Medicine and Health Sciences, McGill University, Québec, Canada
| | - Ophelia Papoulas
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of Texas, Austin, TX, USA
| | - Martyna Janowska
- Laboratory of Cytoskeleton and Cilia Biology, Nencki Institute of Experimental Biology of Polish Academy of Sciences, 3 Pasteur Street, 02-093, Warsaw, Poland
- Laboratory of Immunology, Mossakowski Institute of Experimental and Clinical Medicine, Polish Academy of Science, Pawinskiego 5, 02-106, Warsaw, Poland
| | - Melissa Valente-Paterno
- Department of Anatomy and Cell Biology, Faculty of Medicine and Health Sciences, McGill University, Québec, Canada
| | - Edward M Marcotte
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of Texas, Austin, TX, USA
| | - Dorota Wloga
- Laboratory of Cytoskeleton and Cilia Biology, Nencki Institute of Experimental Biology of Polish Academy of Sciences, 3 Pasteur Street, 02-093, Warsaw, Poland.
| | - Khanh Huy Bui
- Department of Anatomy and Cell Biology, Faculty of Medicine and Health Sciences, McGill University, Québec, Canada.
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10
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Habeck M. Bayesian methods in integrative structure modeling. Biol Chem 2023; 404:741-754. [PMID: 37505205 DOI: 10.1515/hsz-2023-0145] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Accepted: 07/07/2023] [Indexed: 07/29/2023]
Abstract
There is a growing interest in characterizing the structure and dynamics of large biomolecular assemblies and their interactions within the cellular environment. A diverse array of experimental techniques allows us to study biomolecular systems on a variety of length and time scales. These techniques range from imaging with light, X-rays or electrons, to spectroscopic methods, cross-linking mass spectrometry and functional genomics approaches, and are complemented by AI-assisted protein structure prediction methods. A challenge is to integrate all of these data into a model of the system and its functional dynamics. This review focuses on Bayesian approaches to integrative structure modeling. We sketch the principles of Bayesian inference, highlight recent applications to integrative modeling and conclude with a discussion of current challenges and future perspectives.
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Affiliation(s)
- Michael Habeck
- Microscopic Image Analysis Group, Jena University Hospital, D-07743 Jena, Germany
- Max Planck Institute for Multidisciplinary Sciences, d-37077 Göttingen, Germany
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11
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Ghanaeian A, Majhi S, McCaffrey CL, Nami B, Black CS, Yang SK, Legal T, Papoulas O, Janowska M, Valente-Paterno M, Marcotte EM, Wloga D, Bui KH. Integrated modeling of the Nexin-dynein regulatory complex reveals its regulatory mechanism. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.31.543107. [PMID: 37398254 PMCID: PMC10312493 DOI: 10.1101/2023.05.31.543107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Cilia are hairlike protrusions that project from the surface of eukaryotic cells and play key roles in cell signaling and motility. Ciliary motility is regulated by the conserved nexin-dynein regulatory complex (N-DRC), which links adjacent doublet microtubules and regulates and coordinates the activity of outer doublet complexes. Despite its critical role in cilia motility, the assembly and molecular basis of the regulatory mechanism are poorly understood. Here, utilizing cryo-electron microscopy in conjunction with biochemical cross-linking and integrative modeling, we localized 12 DRC subunits in the N-DRC structure of Tetrahymena thermophila . We also found that the CCDC96/113 complex is in close contact with the N-DRC. In addition, we revealed that the N-DRC is associated with a network of coiled-coil proteins that most likely mediates N-DRC regulatory activity.
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Affiliation(s)
- Avrin Ghanaeian
- Department of Anatomy and Cell Biology, Faculty of Medicine and Health Sciences, McGill University, Québec, Canada
| | - Sumita Majhi
- Laboratory of Cytoskeleton and Cilia Biology, Nencki Institute of Experimental Biology of Polish Academy of Sciences, 3 Pasteur Street, 02-093, Warsaw, Poland
| | - Caitie L McCaffrey
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of Texas, Austin, United States
| | - Babak Nami
- Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Canada
| | - Corbin S Black
- Department of Anatomy and Cell Biology, Faculty of Medicine and Health Sciences, McGill University, Québec, Canada
| | - Shun Kai Yang
- Department of Anatomy and Cell Biology, Faculty of Medicine and Health Sciences, McGill University, Québec, Canada
| | - Thibault Legal
- Department of Anatomy and Cell Biology, Faculty of Medicine and Health Sciences, McGill University, Québec, Canada
| | - Ophelia Papoulas
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of Texas, Austin, United States
| | - Martyna Janowska
- Laboratory of Cytoskeleton and Cilia Biology, Nencki Institute of Experimental Biology of Polish Academy of Sciences, 3 Pasteur Street, 02-093, Warsaw, Poland
- current address: Laboratory of Immunology, Mossakowski Institute of Experimental and Clinical Medicine, Polish Academy of Science, Pawinskiego 5, 02-106 Warsaw, Poland
| | - Melissa Valente-Paterno
- Department of Anatomy and Cell Biology, Faculty of Medicine and Health Sciences, McGill University, Québec, Canada
| | - Edward M Marcotte
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of Texas, Austin, United States
| | - Dorota Wloga
- Laboratory of Cytoskeleton and Cilia Biology, Nencki Institute of Experimental Biology of Polish Academy of Sciences, 3 Pasteur Street, 02-093, Warsaw, Poland
| | - Khanh Huy Bui
- Department of Anatomy and Cell Biology, Faculty of Medicine and Health Sciences, McGill University, Québec, Canada
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12
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Echeverria I, Braberg H, Krogan NJ, Sali A. Integrative structure determination of histones H3 and H4 using genetic interactions. FEBS J 2023; 290:2565-2575. [PMID: 35298864 PMCID: PMC9481981 DOI: 10.1111/febs.16435] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Revised: 02/11/2022] [Accepted: 03/15/2022] [Indexed: 11/28/2022]
Abstract
Integrative structure modeling is increasingly used for determining the architectures of biological assemblies, especially those that are structurally heterogeneous. Recently, we reported on how to convert in vivo genetic interaction measurements into spatial restraints for structural modeling: first, phenotypic profiles are generated for each point mutation and thousands of gene deletions or environmental perturbations. Following, the phenotypic profile similarities are converted into distance restraints on the pairs of mutated residues. We illustrate the approach by determining the structure of the histone H3-H4 complex. The method is implemented in our open-source IMP program, expanding the structural biology toolbox by allowing structural characterization based on in vivo data without the need to purify the target system. We compare genetic interaction measurements to other sources of structural information, such as residue coevolution and deep-learning structure prediction of complex subunits. We also suggest that determining genetic interactions could benefit from new technologies, such as CRISPR-Cas9 approaches to gene editing, especially for mammalian cells. Finally, we highlight the opportunity for using genetic interactions to determine recalcitrant biomolecular structures, such as those of disordered proteins, transient protein assemblies, and host-pathogen protein complexes.
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Affiliation(s)
- Ignacia Echeverria
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
- Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, CA 94158, USA
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Hannes Braberg
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
- Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Nevan J. Krogan
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
- Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, CA 94158, USA
- Gladstone Institute of Data Science and Biotechnology, J. David Gladstone Institutes, San Francisco, CA 94158, USA
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Andrej Sali
- Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, CA 94158, USA
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA 94158, USA
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA 94158, USA
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13
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McCafferty CL, Pennington EL, Papoulas O, Taylor DW, Marcotte EM. Does AlphaFold2 model proteins' intracellular conformations? An experimental test using cross-linking mass spectrometry of endogenous ciliary proteins. Commun Biol 2023; 6:421. [PMID: 37061613 PMCID: PMC10105775 DOI: 10.1038/s42003-023-04773-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Accepted: 03/28/2023] [Indexed: 04/17/2023] Open
Abstract
A major goal in structural biology is to understand protein assemblies in their biologically relevant states. Here, we investigate whether AlphaFold2 structure predictions match native protein conformations. We chemically cross-linked proteins in situ within intact Tetrahymena thermophila cilia and native ciliary extracts, identifying 1,225 intramolecular cross-links within the 100 best-sampled proteins, providing a benchmark of distance restraints obeyed by proteins in their native assemblies. The corresponding structure predictions were highly concordant, positioning 86.2% of cross-linked residues within Cɑ-to-Cɑ distances of 30 Å, consistent with the cross-linker length. 43% of proteins showed no violations. Most inconsistencies occurred in low-confidence regions or between domains. Overall, AlphaFold2 predictions with lower predicted aligned error corresponded to more correct native structures. However, we observe cases where rigid body domains are oriented incorrectly, as for ciliary protein BBC118, suggesting that combining structure prediction with experimental information will better reveal biologically relevant conformations.
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Affiliation(s)
- Caitlyn L McCafferty
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of Texas, Austin, TX, 78712, USA.
| | - Erin L Pennington
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of Texas, Austin, TX, 78712, USA
| | - Ophelia Papoulas
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of Texas, Austin, TX, 78712, USA
| | - David W Taylor
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of Texas, Austin, TX, 78712, USA.
| | - Edward M Marcotte
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of Texas, Austin, TX, 78712, USA.
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14
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Flacht L, Lunelli M, Kaszuba K, Chen ZA, Reilly FJO, Rappsilber J, Kosinski J, Kolbe M. Integrative structural analysis of the type III secretion system needle complex from Shigella flexneri. Protein Sci 2023; 32:e4595. [PMID: 36790757 PMCID: PMC10019453 DOI: 10.1002/pro.4595] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Revised: 01/31/2023] [Accepted: 02/09/2023] [Indexed: 02/16/2023]
Abstract
The type III secretion system (T3SS) is a large, transmembrane protein machinery used by various pathogenic gram-negative bacteria to transport virulence factors into the host cell during infection. Understanding the structure of T3SSs is crucial for future developments of therapeutics that could target this system. However, much of the knowledge about the structure of T3SS is available only for Salmonella, and it is unclear how this large assembly is conserved across species. Here, we combined cryo-electron microscopy, cross-linking mass spectrometry, and integrative modeling to determine the structure of the T3SS needle complex from Shigella flexneri. We show that the Shigella T3SS exhibits unique features distinguishing it from other structurally characterized T3SSs. The secretin pore complex adopts a new fold of its C-terminal S domain and the pilotin MxiM[SctG] locates around the outer surface of the pore. The export apparatus structure exhibits a conserved pseudohelical arrangement but includes the N-terminal domain of the SpaS[SctU] subunit, which was not present in any of the previously published virulence-related T3SS structures. Similar to other T3SSs, however, the apparatus is anchored within the needle complex by a network of flexible linkers that either adjust conformation to connect to equivalent patches on the secretin oligomer or bind distinct surface patches at the same height of the export apparatus. The conserved and unique features delineated by our analysis highlight the necessity to analyze T3SS in a species-specific manner, in order to fully understand the underlying molecular mechanisms of these systems. The structure of the type III secretion system from Shigella flexneri delineates conserved and unique features, which could be used for the development of broad-range therapeutics.
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Affiliation(s)
- Lara Flacht
- Department for Structural Infection BiologyCenter for Structural Systems Biology (CSSB) & Helmholtz Centre for Infection Research (HZI)HamburgGermany
- Dynamics of Viral Structures, Leibniz Institute for Virology (LIV)HamburgGermany
| | - Michele Lunelli
- Department for Structural Infection BiologyCenter for Structural Systems Biology (CSSB) & Helmholtz Centre for Infection Research (HZI)HamburgGermany
| | - Karol Kaszuba
- Department for Structural Infection BiologyCenter for Structural Systems Biology (CSSB) & Helmholtz Centre for Infection Research (HZI)HamburgGermany
- Centre for Structural Systems Biology (CSSB) & European Molecular Biology Laboratory (EMBL)HamburgGermany
| | - Zhuo Angel Chen
- Technische Universität Berlin, Institute of Biotechnology, Chair of BioanalyticsBerlinGermany
| | - Francis J. O'. Reilly
- Technische Universität Berlin, Institute of Biotechnology, Chair of BioanalyticsBerlinGermany
| | - Juri Rappsilber
- Technische Universität Berlin, Institute of Biotechnology, Chair of BioanalyticsBerlinGermany
- University of Edinburgh, Wellcome Centre for Cell BiologyEdinburghUK
| | - Jan Kosinski
- Centre for Structural Systems Biology (CSSB) & European Molecular Biology Laboratory (EMBL)HamburgGermany
- Structural and Computational Biology Unit, European Molecular Biology LaboratoryHeidelbergGermany
| | - Michael Kolbe
- Department for Structural Infection BiologyCenter for Structural Systems Biology (CSSB) & Helmholtz Centre for Infection Research (HZI)HamburgGermany
- MIN‐FacultyUniversity HamburgHamburgGermany
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15
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Kim SK, Dickinson MS, Finer-Moore J, Guan Z, Kaake RM, Echeverria I, Chen J, Pulido EH, Sali A, Krogan NJ, Rosenberg OS, Stroud RM. Structure and dynamics of the essential endogenous mycobacterial polyketide synthase Pks13. Nat Struct Mol Biol 2023; 30:296-308. [PMID: 36782050 PMCID: PMC10312659 DOI: 10.1038/s41594-022-00918-0] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Accepted: 12/21/2022] [Indexed: 02/15/2023]
Abstract
The mycolic acid layer of the Mycobacterium tuberculosis cell wall is essential for viability and virulence, and the enzymes responsible for its synthesis are targets for antimycobacterial drug development. Polyketide synthase 13 (Pks13) is a module encoding several enzymatic and transport functions that carries out the condensation of two different long-chain fatty acids to produce mycolic acids. We determined structures by cryogenic-electron microscopy of dimeric multi-enzyme Pks13 purified from mycobacteria under normal growth conditions, captured with native substrates. Structures define the ketosynthase (KS), linker and acyl transferase (AT) domains at 1.8 Å resolution and two alternative locations of the N-terminal acyl carrier protein. These structures suggest intermediate states on the pathway for substrate delivery to the KS domain. Other domains, visible at lower resolution, are flexible relative to the KS-AT core. The chemical structures of three bound endogenous long-chain fatty acid substrates were determined by electrospray ionization mass spectrometry.
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Affiliation(s)
- Sun Kyung Kim
- Department of Biochemistry and Biophysics, University of California San Francisco, San Francisco, CA, USA
| | - Miles Sasha Dickinson
- Department of Biochemistry and Biophysics, University of California San Francisco, San Francisco, CA, USA
- Chemistry and Chemical Biology Graduate Program, University of California San Francisco, San Francisco, CA, USA
| | - Janet Finer-Moore
- Department of Biochemistry and Biophysics, University of California San Francisco, San Francisco, CA, USA
| | - Ziqiang Guan
- Department of Biochemistry, Duke University Medical Center, Durham, NC, USA
| | - Robyn M Kaake
- Gladstone Institute of Data Science and Biotechnology, J. David Gladstone Institutes, San Francisco, CA, USA
- Department of Cellular and Molecular Pharmacology, University of California San Francisco, San Francisco, CA, USA
- Quantitative Biosciences Institute, University of California San Francisco, San Francisco, CA, USA
| | - Ignacia Echeverria
- Department of Cellular and Molecular Pharmacology, University of California San Francisco, San Francisco, CA, USA
- Quantitative Biosciences Institute, University of California San Francisco, San Francisco, CA, USA
| | - Jen Chen
- Department of Biochemistry and Biophysics, University of California San Francisco, San Francisco, CA, USA
| | - Ernst H Pulido
- Gladstone Institute of Data Science and Biotechnology, J. David Gladstone Institutes, San Francisco, CA, USA
| | - Andrej Sali
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA
| | - Nevan J Krogan
- Gladstone Institute of Data Science and Biotechnology, J. David Gladstone Institutes, San Francisco, CA, USA
- Department of Cellular and Molecular Pharmacology, University of California San Francisco, San Francisco, CA, USA
- Quantitative Biosciences Institute, University of California San Francisco, San Francisco, CA, USA
| | - Oren S Rosenberg
- Department of Biochemistry and Biophysics, University of California San Francisco, San Francisco, CA, USA.
- Department of Medicine, Division of Infectious Diseases, University of California San Francisco, San Francisco, CA, USA.
| | - Robert M Stroud
- Department of Biochemistry and Biophysics, University of California San Francisco, San Francisco, CA, USA.
- Chemistry and Chemical Biology Graduate Program, University of California San Francisco, San Francisco, CA, USA.
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16
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Gorbea Colón JJ, Palao L, Chen SF, Kim HJ, Snyder L, Chang YW, Tsai KL, Murakami K. Structural basis of a transcription pre-initiation complex on a divergent promoter. Mol Cell 2023; 83:574-588.e11. [PMID: 36731470 PMCID: PMC10162435 DOI: 10.1016/j.molcel.2023.01.011] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 11/28/2022] [Accepted: 01/06/2023] [Indexed: 02/04/2023]
Abstract
Most eukaryotic promoter regions are divergently transcribed. As the RNA polymerase II pre-initiation complex (PIC) is intrinsically asymmetric and responsible for transcription in a single direction, it is unknown how divergent transcription arises. Here, the Saccharomyces cerevisiae Mediator complexed with a PIC (Med-PIC) was assembled on a divergent promoter and analyzed by cryoelectron microscopy. The structure reveals two distinct Med-PICs forming a dimer through the Mediator tail module, induced by a homodimeric activator protein localized near the dimerization interface. The tail dimer is associated with ∼80-bp upstream DNA, such that two flanking core promoter regions are positioned and oriented in a suitable form for PIC assembly in opposite directions. Also, cryoelectron tomography visualized the progress of the PIC assembly on the two core promoter regions, providing direct evidence for the role of the Med-PIC dimer in divergent transcription.
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Affiliation(s)
- Jose J Gorbea Colón
- Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Biochemistry and Molecular Biophysics Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Leon Palao
- Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Biochemistry and Molecular Biophysics Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Shin-Fu Chen
- Department of Biochemistry and Molecular Biology, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Hee Jong Kim
- Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Biochemistry and Molecular Biophysics Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Laura Snyder
- Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Yi-Wei Chang
- Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
| | - Kuang-Lei Tsai
- Department of Biochemistry and Molecular Biology, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX 77030, USA.
| | - Kenji Murakami
- Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Penn Center for Genome Integrity, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
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17
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New opportunities in integrative structural modeling. Curr Opin Struct Biol 2022; 77:102488. [PMID: 36279817 DOI: 10.1016/j.sbi.2022.102488] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2022] [Revised: 09/13/2022] [Accepted: 09/15/2022] [Indexed: 12/14/2022]
Abstract
Integrative structural modeling enables structure determination of macromolecules and their complexes by integrating data from multiple sources. It has been successfully used to characterize macromolecular structures when a single structural biology technique was insufficient. Recent developments in cellular structural biology, including in-cell cryo-electron tomography and artificial intelligence-based structure prediction, have created new opportunities for integrative structural modeling. Here, we will review these opportunities along with the latest developments in integrative modeling methods and their applications. We also highlight open challenges and directions for further development.
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18
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McCafferty CL, Papoulas O, Jordan MA, Hoogerbrugge G, Nichols C, Pigino G, Taylor DW, Wallingford JB, Marcotte EM. Integrative modeling reveals the molecular architecture of the intraflagellar transport A (IFT-A) complex. eLife 2022; 11:e81977. [PMID: 36346217 PMCID: PMC9674347 DOI: 10.7554/elife.81977] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Accepted: 11/07/2022] [Indexed: 11/10/2022] Open
Abstract
Intraflagellar transport (IFT) is a conserved process of cargo transport in cilia that is essential for development and homeostasis in organisms ranging from algae to vertebrates. In humans, variants in genes encoding subunits of the cargo-adapting IFT-A and IFT-B protein complexes are a common cause of genetic diseases known as ciliopathies. While recent progress has been made in determining the atomic structure of IFT-B, little is known of the structural biology of IFT-A. Here, we combined chemical cross-linking mass spectrometry and cryo-electron tomography with AlphaFold2-based prediction of both protein structures and interaction interfaces to model the overall architecture of the monomeric six-subunit IFT-A complex, as well as its polymeric assembly within cilia. We define monomer-monomer contacts and membrane-associated regions available for association with transported cargo, and we also use this model to provide insights into the pleiotropic nature of human ciliopathy-associated genetic variants in genes encoding IFT-A subunits. Our work demonstrates the power of integration of experimental and computational strategies both for multi-protein structure determination and for understanding the etiology of human genetic disease.
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Affiliation(s)
- Caitlyn L McCafferty
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of TexasAustinUnited States
| | - Ophelia Papoulas
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of TexasAustinUnited States
| | - Mareike A Jordan
- Max Planck Institute of Molecular Cell Biology and GeneticsDresdenGermany
| | - Gabriel Hoogerbrugge
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of TexasAustinUnited States
| | - Candice Nichols
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of TexasAustinUnited States
| | | | - David W Taylor
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of TexasAustinUnited States
| | - John B Wallingford
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of TexasAustinUnited States
| | - Edward M Marcotte
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of TexasAustinUnited States
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19
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Van Leene J, Eeckhout D, Gadeyne A, Matthijs C, Han C, De Winne N, Persiau G, Van De Slijke E, Persyn F, Mertens T, Smagghe W, Crepin N, Broucke E, Van Damme D, Pleskot R, Rolland F, De Jaeger G. Mapping of the plant SnRK1 kinase signalling network reveals a key regulatory role for the class II T6P synthase-like proteins. NATURE PLANTS 2022; 8:1245-1261. [PMID: 36376753 DOI: 10.1038/s41477-022-01269-w] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Accepted: 09/09/2022] [Indexed: 06/16/2023]
Abstract
The central metabolic regulator SnRK1 controls plant growth and survival upon activation by energy depletion, but detailed molecular insight into its regulation and downstream targets is limited. Here we used phosphoproteomics to infer the sucrose-dependent processes targeted upon starvation by kinases as SnRK1, corroborating the relation of SnRK1 with metabolic enzymes and transcriptional regulators, while also pointing to SnRK1 control of intracellular trafficking. Next, we integrated affinity purification, proximity labelling and crosslinking mass spectrometry to map the protein interaction landscape, composition and structure of the SnRK1 heterotrimer, providing insight in its plant-specific regulation. At the intersection of this multi-dimensional interactome, we discovered a strong association of SnRK1 with class II T6P synthase (TPS)-like proteins. Biochemical and cellular assays show that TPS-like proteins function as negative regulators of SnRK1. Next to stable interactions with the TPS-like proteins, similar intricate connections were found with known regulators, suggesting that plants utilize an extended kinase complex to fine-tune SnRK1 activity for optimal responses to metabolic stress.
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Affiliation(s)
- Jelle Van Leene
- Ghent University, Department of Plant Biotechnology and Bioinformatics, Ghent, Belgium
- VIB Center for Plant Systems Biology, Ghent, Belgium
| | - Dominique Eeckhout
- Ghent University, Department of Plant Biotechnology and Bioinformatics, Ghent, Belgium
- VIB Center for Plant Systems Biology, Ghent, Belgium
| | - Astrid Gadeyne
- Ghent University, Department of Plant Biotechnology and Bioinformatics, Ghent, Belgium
- VIB Center for Plant Systems Biology, Ghent, Belgium
| | - Caroline Matthijs
- Ghent University, Department of Plant Biotechnology and Bioinformatics, Ghent, Belgium
- VIB Center for Plant Systems Biology, Ghent, Belgium
| | - Chao Han
- Ghent University, Department of Plant Biotechnology and Bioinformatics, Ghent, Belgium
- VIB Center for Plant Systems Biology, Ghent, Belgium
- The Key Laboratory of Plant Development and Environmental Adaptation Biology, Ministry of Education, School of Life Sciences, Shandong University, Qingdao, China
| | - Nancy De Winne
- Ghent University, Department of Plant Biotechnology and Bioinformatics, Ghent, Belgium
- VIB Center for Plant Systems Biology, Ghent, Belgium
| | - Geert Persiau
- Ghent University, Department of Plant Biotechnology and Bioinformatics, Ghent, Belgium
- VIB Center for Plant Systems Biology, Ghent, Belgium
| | - Eveline Van De Slijke
- Ghent University, Department of Plant Biotechnology and Bioinformatics, Ghent, Belgium
- VIB Center for Plant Systems Biology, Ghent, Belgium
| | - Freya Persyn
- Ghent University, Department of Plant Biotechnology and Bioinformatics, Ghent, Belgium
- VIB Center for Plant Systems Biology, Ghent, Belgium
| | - Toon Mertens
- Ghent University, Department of Plant Biotechnology and Bioinformatics, Ghent, Belgium
- VIB Center for Plant Systems Biology, Ghent, Belgium
| | - Wouter Smagghe
- Ghent University, Department of Plant Biotechnology and Bioinformatics, Ghent, Belgium
- VIB Center for Plant Systems Biology, Ghent, Belgium
| | - Nathalie Crepin
- Laboratory for Molecular Plant Biology, Biology Department, KU Leuven, Heverlee-Leuven, Belgium
- KU Leuven Plant Institute-LPI, Heverlee-Leuven, Belgium
| | - Ellen Broucke
- Laboratory for Molecular Plant Biology, Biology Department, KU Leuven, Heverlee-Leuven, Belgium
- KU Leuven Plant Institute-LPI, Heverlee-Leuven, Belgium
| | - Daniël Van Damme
- Ghent University, Department of Plant Biotechnology and Bioinformatics, Ghent, Belgium
- VIB Center for Plant Systems Biology, Ghent, Belgium
| | - Roman Pleskot
- Ghent University, Department of Plant Biotechnology and Bioinformatics, Ghent, Belgium
- VIB Center for Plant Systems Biology, Ghent, Belgium
- Institute of Experimental Botany, Czech Academy of Sciences, Prague, Czech Republic
| | - Filip Rolland
- Laboratory for Molecular Plant Biology, Biology Department, KU Leuven, Heverlee-Leuven, Belgium
- KU Leuven Plant Institute-LPI, Heverlee-Leuven, Belgium
| | - Geert De Jaeger
- Ghent University, Department of Plant Biotechnology and Bioinformatics, Ghent, Belgium.
- VIB Center for Plant Systems Biology, Ghent, Belgium.
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20
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Arvindekar S, Jackman MJ, Low JKK, Landsberg MJ, Mackay JP, Viswanath S. Molecular architecture of nucleosome remodeling and deacetylase sub-complexes by integrative structure determination. Protein Sci 2022; 31:e4387. [PMID: 36040254 PMCID: PMC9413472 DOI: 10.1002/pro.4387] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 05/18/2022] [Accepted: 06/19/2022] [Indexed: 11/11/2022]
Abstract
The nucleosome remodeling and deacetylase (NuRD) complex is a chromatin-modifying assembly that regulates gene expression and DNA damage repair. Despite its importance, limited structural information describing the complete NuRD complex is available and a detailed understanding of its mechanism is therefore lacking. Drawing on information from SEC-MALLS, DIA-MS, XLMS, negative-stain EM, X-ray crystallography, NMR spectroscopy, secondary structure predictions, and homology models, we applied Bayesian integrative structure determination to investigate the molecular architecture of three NuRD sub-complexes: MTA1-HDAC1-RBBP4, MTA1N -HDAC1-MBD3GATAD2CC , and MTA1-HDAC1-RBBP4-MBD3-GATAD2A [nucleosome deacetylase (NuDe)]. The integrative structures were corroborated by examining independent crosslinks, cryo-EM maps, biochemical assays, known cancer-associated mutations, and structure predictions from AlphaFold. The robustness of the models was assessed by jack-knifing. Localization of the full-length MBD3, which connects the deacetylase and chromatin remodeling modules in NuRD, has not previously been possible; our models indicate two different locations for MBD3, suggesting a mechanism by which MBD3 in the presence of GATAD2A asymmetrically bridges the two modules in NuRD. Further, our models uncovered three previously unrecognized subunit interfaces in NuDe: HDAC1C -MTA1BAH , MTA1BAH -MBD3MBD , and HDAC160-100 -MBD3MBD . Our approach also allowed us to localize regions of unknown structure, such as HDAC1C and MBD3IDR , thereby resulting in the most complete and robustly cross-validated structural characterization of these NuRD sub-complexes so far.
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Affiliation(s)
- Shreyas Arvindekar
- National Centre for Biological SciencesTata Institute of Fundamental ResearchBangaloreIndia
| | - Matthew J. Jackman
- School of Chemistry and Molecular BiosciencesUniversity of QueenslandBrisbaneQueenslandAustralia
| | - Jason K. K. Low
- School of Life and Environmental SciencesUniversity of SydneySydneyNew South WalesAustralia
| | - Michael J. Landsberg
- School of Chemistry and Molecular BiosciencesUniversity of QueenslandBrisbaneQueenslandAustralia
| | - Joel P. Mackay
- School of Life and Environmental SciencesUniversity of SydneySydneyNew South WalesAustralia
| | - Shruthi Viswanath
- National Centre for Biological SciencesTata Institute of Fundamental ResearchBangaloreIndia
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21
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Integrative modeling of the cell. Acta Biochim Biophys Sin (Shanghai) 2022; 54:1213-1221. [PMID: 36017893 PMCID: PMC9909318 DOI: 10.3724/abbs.2022115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
A whole-cell model represents certain aspects of the cell structure and/or function. Due to the high complexity of the cell, an integrative modeling approach is often taken to utilize all available information including experimental data, prior knowledge and prior models. In this review, we summarize an emerging workflow of whole-cell modeling into five steps: (i) gather information; (ii) represent the modeled system into modules; (iii) translate input information into scoring function; (iv) sample the whole-cell model; (v) validate and interpret the model. In particular, we propose the integrative modeling of the cell by combining available (whole-cell) models to maximize the accuracy, precision, and completeness. In addition, we list quantitative predictions of various aspects of cell biology from existing whole-cell models. Moreover, we discuss the remaining challenges and future directions, and highlight the opportunity to establish an integrative spatiotemporal multi-scale whole-cell model based on a community approach.
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22
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Sae-Lee W, McCafferty CL, Verbeke EJ, Havugimana PC, Papoulas O, McWhite CD, Houser JR, Vanuytsel K, Murphy GJ, Drew K, Emili A, Taylor DW, Marcotte EM. The protein organization of a red blood cell. Cell Rep 2022; 40:111103. [PMID: 35858567 PMCID: PMC9764456 DOI: 10.1016/j.celrep.2022.111103] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 04/18/2022] [Accepted: 06/24/2022] [Indexed: 11/28/2022] Open
Abstract
Red blood cells (RBCs) (erythrocytes) are the simplest primary human cells, lacking nuclei and major organelles and instead employing about a thousand proteins to dynamically control cellular function and morphology in response to physiological cues. In this study, we define a canonical RBC proteome and interactome using quantitative mass spectrometry and machine learning. Our data reveal an RBC interactome dominated by protein homeostasis, redox biology, cytoskeletal dynamics, and carbon metabolism. We validate protein complexes through electron microscopy and chemical crosslinking and, with these data, build 3D structural models of the ankyrin/Band 3/Band 4.2 complex that bridges the spectrin cytoskeleton to the RBC membrane. The model suggests spring-like compression of ankyrin may contribute to the characteristic RBC cell shape and flexibility. Taken together, our study provides an in-depth view of the global protein organization of human RBCs and serves as a comprehensive resource for future research.
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Affiliation(s)
- Wisath Sae-Lee
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of Texas, Austin, TX 78712, USA
| | - Caitlyn L McCafferty
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of Texas, Austin, TX 78712, USA
| | - Eric J Verbeke
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of Texas, Austin, TX 78712, USA
| | - Pierre C Havugimana
- Center for Network Systems Biology, Boston University, Boston, MA 02118, USA
| | - Ophelia Papoulas
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of Texas, Austin, TX 78712, USA
| | - Claire D McWhite
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of Texas, Austin, TX 78712, USA
| | - John R Houser
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of Texas, Austin, TX 78712, USA
| | - Kim Vanuytsel
- Center for Regenerative Medicine, Boston University School of Medicine, 670 Albany Street, Boston, MA 02118, USA
| | - George J Murphy
- Center for Regenerative Medicine, Boston University School of Medicine, 670 Albany Street, Boston, MA 02118, USA
| | - Kevin Drew
- Department of Biological Sciences, University of Illinois at Chicago, 900 S. Ashland Avenue, Chicago, IL 60607, USA
| | - Andrew Emili
- Center for Network Systems Biology, Boston University, Boston, MA 02118, USA
| | - David W Taylor
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of Texas, Austin, TX 78712, USA
| | - Edward M Marcotte
- Department of Molecular Biosciences, Center for Systems and Synthetic Biology, University of Texas, Austin, TX 78712, USA.
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23
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Ullanat V, Kasukurthi N, Viswanath S. PrISM: Precision for Integrative Structural Models. Bioinformatics 2022; 38:3837-3839. [PMID: 35723541 DOI: 10.1093/bioinformatics/btac400] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 06/04/2022] [Accepted: 06/16/2022] [Indexed: 11/14/2022] Open
Abstract
MOTIVATION A single precision value is currently reported for an integrative model. However, precision may vary for different regions of an integrative model owing to varying amounts of input information. RESULTS We develop PrISM (Precision for Integrative Structural Models), to efficiently identify high and low-precision regions for integrative models. AVAILABILITY PrISM is written in Python and available under the GNU General Public License v3.0 at https://github.com/isblab/prism; benchmark data used in this paper is available at doi:10.5281/zenodo.6241200. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Varun Ullanat
- National Center for Biological Sciences, Tata Institute of Fundamental Research, Bangalore, India
| | - Nikhil Kasukurthi
- National Center for Biological Sciences, Tata Institute of Fundamental Research, Bangalore, India
| | - Shruthi Viswanath
- National Center for Biological Sciences, Tata Institute of Fundamental Research, Bangalore, India
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24
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Braberg H, Echeverria I, Kaake RM, Sali A, Krogan NJ. From systems to structure - using genetic data to model protein structures. Nat Rev Genet 2022; 23:342-354. [PMID: 35013567 PMCID: PMC8744059 DOI: 10.1038/s41576-021-00441-w] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/25/2021] [Indexed: 12/11/2022]
Abstract
Understanding the effects of genetic variation is a fundamental problem in biology that requires methods to analyse both physical and functional consequences of sequence changes at systems-wide and mechanistic scales. To achieve a systems view, protein interaction networks map which proteins physically interact, while genetic interaction networks inform on the phenotypic consequences of perturbing these protein interactions. Until recently, understanding the molecular mechanisms that underlie these interactions often required biophysical methods to determine the structures of the proteins involved. The past decade has seen the emergence of new approaches based on coevolution, deep mutational scanning and genome-scale genetic or chemical-genetic interaction mapping that enable modelling of the structures of individual proteins or protein complexes. Here, we review the emerging use of large-scale genetic datasets and deep learning approaches to model protein structures and their interactions, and discuss the integration of structural data from different sources.
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Affiliation(s)
- Hannes Braberg
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA, USA
- Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Ignacia Echeverria
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA, USA
- Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, CA, USA
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA
| | - Robyn M Kaake
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA, USA
- Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, CA, USA
- Gladstone Institutes, San Francisco, CA, USA
| | - Andrej Sali
- Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, CA, USA
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, USA
| | - Nevan J Krogan
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA, USA.
- Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, CA, USA.
- Gladstone Institutes, San Francisco, CA, USA.
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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25
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Rafiei A, Cruz Tetlalmatzi S, Edrington CH, Lee L, Crowder DA, Saltzberg DJ, Sali A, Brouhard G, Schriemer DC. Doublecortin engages the microtubule lattice through a cooperative binding mode involving its C-terminal domain. eLife 2022; 11:66975. [PMID: 35485925 PMCID: PMC9122500 DOI: 10.7554/elife.66975] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Accepted: 04/07/2022] [Indexed: 11/17/2022] Open
Abstract
Doublecortin (DCX) is a microtubule (MT)-associated protein that regulates MT structure and function during neuronal development and mutations in DCX lead to a spectrum of neurological disorders. The structural properties of MT-bound DCX that explain these disorders are incompletely determined. Here, we describe the molecular architecture of the DCX–MT complex through an integrative modeling approach that combines data from X-ray crystallography, cryo-electron microscopy, and a high-fidelity chemical crosslinking method. We demonstrate that DCX interacts with MTs through its N-terminal domain and induces a lattice-dependent self-association involving the C-terminal structured domain and its disordered tail, in a conformation that favors an open, domain-swapped state. The networked state can accommodate multiple different attachment points on the MT lattice, all of which orient the C-terminal tails away from the lattice. As numerous disease mutations cluster in the C-terminus, and regulatory phosphorylations cluster in its tail, our study shows that lattice-driven self-assembly is an important property of DCX.
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Affiliation(s)
- Atefeh Rafiei
- Department of Chemistry, University of Calgary, Calgary, Canada
| | | | | | - Linda Lee
- Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, Canada
| | - D Alex Crowder
- Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, Canada
| | - Daniel J Saltzberg
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, United States
| | - Andrej Sali
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, United States
| | - Gary Brouhard
- Department of Biology, McGill University, Montreal, Canada
| | - David C Schriemer
- Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, Canada
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26
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Soluble TREM2 inhibits secondary nucleation of Aβ fibrillization and enhances cellular uptake of fibrillar Aβ. Proc Natl Acad Sci U S A 2022; 119:2114486119. [PMID: 35082148 PMCID: PMC8812518 DOI: 10.1073/pnas.2114486119] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/13/2021] [Indexed: 01/21/2023] Open
Abstract
Triggering receptor expressed on myeloid cells 2 (TREM2) is a single-pass transmembrane receptor of the immunoglobulin superfamily that is secreted in a soluble (sTREM2) form. Mutations in TREM2 have been linked to increased risk of Alzheimer's disease (AD). A prominent neuropathological component of AD is deposition of the amyloid-β (Aβ) into plaques, particularly Aβ40 and Aβ42. While the membrane-bound form of TREM2 is known to facilitate uptake of Aβ fibrils and the polarization of microglial processes toward amyloid plaques, the role of its soluble ectodomain, particularly in interactions with monomeric or fibrillar Aβ, has been less clear. Our results demonstrate that sTREM2 does not bind to monomeric Aβ40 and Aβ42, even at a high micromolar concentration, while it does bind to fibrillar Aβ42 and Aβ40 with equal affinities (2.6 ± 0.3 µM and 2.3 ± 0.4 µM). Kinetic analysis shows that sTREM2 inhibits the secondary nucleation step in the fibrillization of Aβ, while having little effect on the primary nucleation pathway. Furthermore, binding of sTREM2 to fibrils markedly enhanced uptake of fibrils into human microglial and neuroglioma derived cell lines. The disease-associated sTREM2 mutant, R47H, displayed little to no effect on fibril nucleation and binding, but it decreased uptake and functional responses markedly. We also probed the structure of the WT sTREM2-Aβ fibril complex using integrative molecular modeling based primarily on the cross-linking mass spectrometry data. The model shows that sTREM2 binds fibrils along one face of the structure, leaving a second, mutation-sensitive site free to mediate cellular binding and uptake.
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27
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Akey CW, Singh D, Ouch C, Echeverria I, Nudelman I, Varberg JM, Yu Z, Fang F, Shi Y, Wang J, Salzberg D, Song K, Xu C, Gumbart JC, Suslov S, Unruh J, Jaspersen SL, Chait BT, Sali A, Fernandez-Martinez J, Ludtke SJ, Villa E, Rout MP. Comprehensive structure and functional adaptations of the yeast nuclear pore complex. Cell 2022; 185:361-378.e25. [PMID: 34982960 PMCID: PMC8928745 DOI: 10.1016/j.cell.2021.12.015] [Citation(s) in RCA: 89] [Impact Index Per Article: 44.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 11/26/2021] [Accepted: 12/13/2021] [Indexed: 02/06/2023]
Abstract
Nuclear pore complexes (NPCs) mediate the nucleocytoplasmic transport of macromolecules. Here we provide a structure of the isolated yeast NPC in which the inner ring is resolved by cryo-EM at sub-nanometer resolution to show how flexible connectors tie together different structural and functional layers. These connectors may be targets for phosphorylation and regulated disassembly in cells with an open mitosis. Moreover, some nucleoporin pairs and transport factors have similar interaction motifs, which suggests an evolutionary and mechanistic link between assembly and transport. We provide evidence for three major NPC variants that may foreshadow functional specializations at the nuclear periphery. Cryo-electron tomography extended these studies, providing a model of the in situ NPC with a radially expanded inner ring. Our comprehensive model reveals features of the nuclear basket and central transporter, suggests a role for the lumenal Pom152 ring in restricting dilation, and highlights structural plasticity that may be required for transport.
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Affiliation(s)
- Christopher W Akey
- Department of Physiology and Biophysics, Boston University School of Medicine, 700 Albany Street, Boston, MA 02118, USA.
| | - Digvijay Singh
- Section of Molecular Biology, Division of Biological Sciences, University of California San Diego, La Jolla, CA 92093, USA
| | - Christna Ouch
- Department of Physiology and Biophysics, Boston University School of Medicine, 700 Albany Street, Boston, MA 02118, USA; Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, 364 Plantation Street, Worcester, MA 01605, USA
| | - Ignacia Echeverria
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA; Department of Cellular and Molecular Pharmacology, San Francisco, San Francisco, CA 94158, USA
| | - Ilona Nudelman
- Laboratory of Cellular and Structural Biology, The Rockefeller University, New York, NY 10065, USA
| | | | - Zulin Yu
- Stowers Institute for Medical Research, Kansas City, MO, USA
| | - Fei Fang
- Department of Cell Biology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Yi Shi
- Department of Cell Biology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Junjie Wang
- Laboratory of Mass Spectrometry and Gaseous Ion Chemistry, The Rockefeller University, New York, NY, USA
| | - Daniel Salzberg
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA
| | - Kangkang Song
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, 364 Plantation Street, Worcester, MA 01605, USA
| | - Chen Xu
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, 364 Plantation Street, Worcester, MA 01605, USA
| | - James C Gumbart
- School of Physics, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Sergey Suslov
- Section of Molecular Biology, Division of Biological Sciences, University of California San Diego, La Jolla, CA 92093, USA
| | - Jay Unruh
- Stowers Institute for Medical Research, Kansas City, MO, USA
| | - Sue L Jaspersen
- Stowers Institute for Medical Research, Kansas City, MO, USA; Department of Molecular and Integrative Physiology, University of Kansas Medical Center, Kansas City, KS, USA
| | - Brian T Chait
- Laboratory of Mass Spectrometry and Gaseous Ion Chemistry, The Rockefeller University, New York, NY, USA
| | - Andrej Sali
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA; Quantitative Biosciences Institute, University of California San Francisco, San Francisco, CA 94158, USA; Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA 94158, USA
| | | | - Steven J Ludtke
- Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, 1 Baylor Plaza, Houston, Texas 77030, USA.
| | - Elizabeth Villa
- Section of Molecular Biology, Division of Biological Sciences, University of California San Diego, La Jolla, CA 92093, USA; Howard Hughes Medical Institute, University of California, San Diego, La Jolla, CA 92093, USA.
| | - Michael P Rout
- Laboratory of Cellular and Structural Biology, The Rockefeller University, New York, NY 10065, USA.
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28
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Zimmerli CE, Allegretti M, Rantos V, Goetz SK, Obarska-Kosinska A, Zagoriy I, Halavatyi A, Hummer G, Mahamid J, Kosinski J, Beck M. Nuclear pores dilate and constrict in cellulo. Science 2021; 374:eabd9776. [PMID: 34762489 DOI: 10.1126/science.abd9776] [Citation(s) in RCA: 151] [Impact Index Per Article: 50.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
[Figure: see text].
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Affiliation(s)
- Christian E Zimmerli
- Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), 69117 Heidelberg, Germany.,Collaboration for joint PhD degree between EMBL and Heidelberg University, Faculty of Biosciences, 69120 Heidelberg, Germany.,Department of Molecular Sociology, Max Planck Institute of Biophysics, 60438 Frankfurt am Main, Germany
| | - Matteo Allegretti
- Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), 69117 Heidelberg, Germany.,Department of Molecular Sociology, Max Planck Institute of Biophysics, 60438 Frankfurt am Main, Germany
| | - Vasileios Rantos
- Centre for Structural Systems Biology (CSSB), 22607 Hamburg, Germany.,EMBL Hamburg, 22607 Hamburg, Germany
| | - Sara K Goetz
- Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), 69117 Heidelberg, Germany.,Collaboration for joint PhD degree between EMBL and Heidelberg University, Faculty of Biosciences, 69120 Heidelberg, Germany
| | - Agnieszka Obarska-Kosinska
- Department of Molecular Sociology, Max Planck Institute of Biophysics, 60438 Frankfurt am Main, Germany.,EMBL Hamburg, 22607 Hamburg, Germany
| | - Ievgeniia Zagoriy
- Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), 69117 Heidelberg, Germany
| | | | - Gerhard Hummer
- Department of Theoretical Biophysics, Max Planck Institute of Biophysics, 60438 Frankfurt am Main, Germany.,Institute of Biophysics, Goethe University Frankfurt, 60438 Frankfurt am Main, Germany
| | - Julia Mahamid
- Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), 69117 Heidelberg, Germany
| | - Jan Kosinski
- Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), 69117 Heidelberg, Germany.,Centre for Structural Systems Biology (CSSB), 22607 Hamburg, Germany.,EMBL Hamburg, 22607 Hamburg, Germany
| | - Martin Beck
- Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), 69117 Heidelberg, Germany.,Department of Molecular Sociology, Max Planck Institute of Biophysics, 60438 Frankfurt am Main, Germany
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29
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Graziadei A, Rappsilber J. Leveraging crosslinking mass spectrometry in structural and cell biology. Structure 2021; 30:37-54. [PMID: 34895473 DOI: 10.1016/j.str.2021.11.007] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Revised: 10/11/2021] [Accepted: 11/17/2021] [Indexed: 12/18/2022]
Abstract
Crosslinking mass spectrometry (crosslinking-MS) is a versatile tool providing structural insights into protein conformation and protein-protein interactions. Its medium-resolution residue-residue distance restraints have been used to validate protein structures proposed by other methods and have helped derive models of protein complexes by integrative structural biology approaches. The use of crosslinking-MS in integrative approaches is underpinned by progress in estimating error rates in crosslinking-MS data and in combining these data with other information. The flexible and high-throughput nature of crosslinking-MS has allowed it to complement the ongoing resolution revolution in electron microscopy by providing system-wide residue-residue distance restraints, especially for flexible regions or systems. Here, we review how crosslinking-MS information has been leveraged in structural model validation and integrative modeling. Crosslinking-MS has also been a key technology for cell biology studies and structural systems biology where, in conjunction with cryoelectron tomography, it can provide structural and mechanistic insights directly in situ.
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Affiliation(s)
- Andrea Graziadei
- Bioanalytics, Institute of Biotechnology, Technische Universität Berlin, 13355 Berlin, Germany
| | - Juri Rappsilber
- Bioanalytics, Institute of Biotechnology, Technische Universität Berlin, 13355 Berlin, Germany; Wellcome Centre for Cell Biology, University of Edinburgh, Max Born Crescent, Edinburgh EH9 3BF, UK.
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30
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Integrative structural modeling of macromolecular complexes using Assembline. Nat Protoc 2021; 17:152-176. [PMID: 34845384 DOI: 10.1038/s41596-021-00640-z] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2020] [Accepted: 09/30/2021] [Indexed: 11/08/2022]
Abstract
Integrative modeling enables structure determination of macromolecular complexes by combining data from multiple experimental sources such as X-ray crystallography, electron microscopy or cross-linking mass spectrometry. It is particularly useful for complexes not amenable to high-resolution electron microscopy-complexes that are flexible, heterogeneous or imaged in cells with cryo-electron tomography. We have recently developed an integrative modeling protocol that allowed us to model multi-megadalton complexes as large as the nuclear pore complex. Here, we describe the Assembline software package, which combines multiple programs and libraries with our own algorithms in a streamlined modeling pipeline. Assembline builds ensembles of models satisfying data from atomic structures or homology models, electron microscopy maps and other experimental data, and provides tools for their analysis. Compared with other methods, Assembline enables efficient sampling of conformational space through a multistep procedure, provides new modeling restraints and includes a unique configuration system for setting up the modeling project. Our protocol achieves exhaustive sampling in less than 100-1,000 CPU-hours even for complexes in the megadalton range. For larger complexes, resources available in institutional or public computer clusters are needed and sufficient to run the protocol. We also provide step-by-step instructions for preparing the input, running the core modeling steps and assessing modeling performance at any stage.
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31
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A Framework for Stochastic Optimization of Parameters for Integrative Modeling of Macromolecular Assemblies. Life (Basel) 2021; 11:life11111183. [PMID: 34833059 PMCID: PMC8618978 DOI: 10.3390/life11111183] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 10/20/2021] [Accepted: 10/23/2021] [Indexed: 01/15/2023] Open
Abstract
Integrative modeling of macromolecular assemblies requires stochastic sampling, for example, via MCMC (Markov Chain Monte Carlo), since exhaustively enumerating all structural degrees of freedom is infeasible. MCMC-based methods usually require tuning several parameters, such as the move sizes for coarse-grained beads and rigid bodies, for sampling to be efficient and accurate. Currently, these parameters are tuned manually. To automate this process, we developed a general heuristic for derivative-free, global, stochastic, parallel, multiobjective optimization, termed StOP (Stochastic Optimization of Parameters) and applied it to optimize sampling-related parameters for the Integrative Modeling Platform (IMP). Given an integrative modeling setup, list of parameters to optimize, their domains, metrics that they influence, and the target ranges of these metrics, StOP produces the optimal values of these parameters. StOP is adaptable to the available computing capacity and converges quickly, allowing for the simultaneous optimization of a large number of parameters. However, it is not efficient at high dimensions and not guaranteed to find optima in complex landscapes. We demonstrate its performance on several examples of random functions, as well as on two integrative modeling examples, showing that StOP enhances the efficiency of sampling the posterior distribution, resulting in more good-scoring models and better sampling precision.
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32
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Ziemianowicz DS, Saltzberg D, Pells T, Crowder DA, Schräder C, Hepburn M, Sali A, Schriemer DC. IMProv: A Resource for Cross-link-Driven Structure Modeling that Accommodates Protein Dynamics. Mol Cell Proteomics 2021; 20:100139. [PMID: 34418567 PMCID: PMC8452774 DOI: 10.1016/j.mcpro.2021.100139] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Revised: 07/27/2021] [Accepted: 08/11/2021] [Indexed: 11/01/2022] Open
Abstract
Proteomics methodology has expanded to include protein structural analysis, primarily through cross-linking mass spectrometry (XL-MS) and hydrogen-deuterium exchange mass spectrometry (HX-MS). However, while the structural proteomics community has effective tools for primary data analysis, there is a need for structure modeling pipelines that are accessible to the proteomics specialist. Integrative structural biology requires the aggregation of multiple distinct types of data to generate models that satisfy all inputs. Here, we describe IMProv, an app in the Mass Spec Studio that combines XL-MS data with other structural data, such as cryo-EM densities and crystallographic structures, for integrative structure modeling on high-performance computing platforms. The resource provides an easily deployed bundle that includes the open-source Integrative Modeling Platform program (IMP) and its dependencies. IMProv also provides functionality to adjust cross-link distance restraints according to the underlying dynamics of cross-linked sites, as characterized by HX-MS. A dynamics-driven conditioning of restraint values can improve structure modeling precision, as illustrated by an integrative structure of the five-membered Polycomb Repressive Complex 2. IMProv is extensible to additional types of data.
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Affiliation(s)
- Daniel S Ziemianowicz
- Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, Alberta, Canada; Robson DNA Science Centre, Arnie Charbonneau Cancer Institute, University of Calgary, Calgary, Alberta, Canada
| | - Daniel Saltzberg
- Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Sciences, and California Institute for Quantitative Biomedical Sciences, University of California, San Francisco, California, USA
| | - Troy Pells
- Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, Alberta, Canada; Robson DNA Science Centre, Arnie Charbonneau Cancer Institute, University of Calgary, Calgary, Alberta, Canada
| | - D Alex Crowder
- Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, Alberta, Canada; Robson DNA Science Centre, Arnie Charbonneau Cancer Institute, University of Calgary, Calgary, Alberta, Canada
| | - Christoph Schräder
- Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, Alberta, Canada; Robson DNA Science Centre, Arnie Charbonneau Cancer Institute, University of Calgary, Calgary, Alberta, Canada
| | - Morgan Hepburn
- Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, Alberta, Canada; Robson DNA Science Centre, Arnie Charbonneau Cancer Institute, University of Calgary, Calgary, Alberta, Canada
| | - Andrej Sali
- Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Sciences, and California Institute for Quantitative Biomedical Sciences, University of California, San Francisco, California, USA
| | - David C Schriemer
- Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, Alberta, Canada; Robson DNA Science Centre, Arnie Charbonneau Cancer Institute, University of Calgary, Calgary, Alberta, Canada; Department of Chemistry, University of Calgary, Calgary, Alberta, Canada.
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33
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Kaake RM, Echeverria I, Kim SJ, Von Dollen J, Chesarino NM, Feng Y, Yu C, Ta H, Chelico L, Huang L, Gross J, Sali A, Krogan NJ. Characterization of an A3G-Vif HIV-1-CRL5-CBFβ Structure Using a Cross-linking Mass Spectrometry Pipeline for Integrative Modeling of Host-Pathogen Complexes. Mol Cell Proteomics 2021; 20:100132. [PMID: 34389466 PMCID: PMC8459920 DOI: 10.1016/j.mcpro.2021.100132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 07/15/2021] [Accepted: 08/04/2021] [Indexed: 10/24/2022] Open
Abstract
Structural analysis of host-pathogen protein complexes remains challenging, largely due to their structural heterogeneity. Here, we describe a pipeline for the structural characterization of these complexes using integrative structure modeling based on chemical cross-links and residue-protein contacts inferred from mutagenesis studies. We used this approach on the HIV-1 Vif protein bound to restriction factor APOBEC3G (A3G), the Cullin-5 E3 ring ligase (CRL5), and the cellular transcription factor Core Binding Factor Beta (CBFβ) to determine the structure of the (A3G-Vif-CRL5-CBFβ) complex. Using the MS-cleavable DSSO cross-linker to obtain a set of 132 cross-links within this reconstituted complex along with the atomic structures of the subunits and mutagenesis data, we computed an integrative structure model of the heptameric A3G-Vif-CRL5-CBFβ complex. The structure, which was validated using a series of tests, reveals that A3G is bound to Vif mostly through its N-terminal domain. Moreover, the model ensemble quantifies the dynamic heterogeneity of the A3G C-terminal domain and Cul5 positions. Finally, the model was used to rationalize previous structural, mutagenesis and functional data not used for modeling, including information related to the A3G-bound and unbound structures as well as mapping functional mutations to the A3G-Vif interface. The experimental and computational approach described here is generally applicable to other challenging host-pathogen protein complexes.
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Affiliation(s)
- Robyn M Kaake
- Department of Cellular and Molecular Pharmacology, California Institute for Quantitative Biosciences, University of California, San Francisco, San Francisco, California, USA; Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, California, USA; Gladstone Institute of Data Science and Biotechnology, J. David Gladstone Institutes, San Francisco, California, USA
| | - Ignacia Echeverria
- Department of Cellular and Molecular Pharmacology, California Institute for Quantitative Biosciences, University of California, San Francisco, San Francisco, California, USA; Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California, USA
| | - Seung Joong Kim
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California, USA
| | - John Von Dollen
- Department of Cellular and Molecular Pharmacology, California Institute for Quantitative Biosciences, University of California, San Francisco, San Francisco, California, USA; Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, California, USA
| | - Nicholas M Chesarino
- Divisions of Human Biology and Basic Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Yuqing Feng
- Department of Biochemistry, Microbiology, Immunology, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Clinton Yu
- Department of Physiology & Biophysics, University of California, Irvine, California, USA
| | - Hai Ta
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, California, USA
| | - Linda Chelico
- Department of Biochemistry, Microbiology, Immunology, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Lan Huang
- Department of Physiology & Biophysics, University of California, Irvine, California, USA
| | - John Gross
- Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, California, USA; Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, California, USA
| | - Andrej Sali
- Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, California, USA; Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California, USA; Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, California, USA.
| | - Nevan J Krogan
- Department of Cellular and Molecular Pharmacology, California Institute for Quantitative Biosciences, University of California, San Francisco, San Francisco, California, USA; Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, California, USA; Gladstone Institute of Data Science and Biotechnology, J. David Gladstone Institutes, San Francisco, California, USA.
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Faylo JL, van Eeuwen T, Kim HJ, Gorbea Colón JJ, Garcia BA, Murakami K, Christianson DW. Structural insight on assembly-line catalysis in terpene biosynthesis. Nat Commun 2021; 12:3487. [PMID: 34108468 PMCID: PMC8190136 DOI: 10.1038/s41467-021-23589-9] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Accepted: 05/05/2021] [Indexed: 12/20/2022] Open
Abstract
Fusicoccadiene synthase from Phomopsis amygdali (PaFS) is a unique bifunctional terpenoid synthase that catalyzes the first two steps in the biosynthesis of the diterpene glycoside Fusicoccin A, a mediator of 14-3-3 protein interactions. The prenyltransferase domain of PaFS generates geranylgeranyl diphosphate, which the cyclase domain then utilizes to generate fusicoccadiene, the tricyclic hydrocarbon skeleton of Fusicoccin A. Here, we use cryo-electron microscopy to show that the structure of full-length PaFS consists of a central octameric core of prenyltransferase domains, with the eight cyclase domains radiating outward via flexible linker segments in variable splayed-out positions. Cryo-electron microscopy and chemical crosslinking experiments additionally show that compact conformations can be achieved in which cyclase domains are more closely associated with the prenyltransferase core. This structural analysis provides a framework for understanding substrate channeling, since most of the geranylgeranyl diphosphate generated by the prenyltransferase domains remains on the enzyme for cyclization to form fusicoccadiene.
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Affiliation(s)
- Jacque L Faylo
- Roy and Diana Vagelos Laboratories, Department of Chemistry, University of Pennsylvania, Philadelphia, PA, United States
| | - Trevor van Eeuwen
- Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Biochemistry and Molecular Biophysics Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Hee Jong Kim
- Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Biochemistry and Molecular Biophysics Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Jose J Gorbea Colón
- Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Biochemistry and Molecular Biophysics Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Benjamin A Garcia
- Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Kenji Murakami
- Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - David W Christianson
- Roy and Diana Vagelos Laboratories, Department of Chemistry, University of Pennsylvania, Philadelphia, PA, United States.
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35
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Beckham KSH, Ritter C, Chojnowski G, Ziemianowicz DS, Mullapudi E, Rettel M, Savitski MM, Mortensen SA, Kosinski J, Wilmanns M. Structure of the mycobacterial ESX-5 type VII secretion system pore complex. SCIENCE ADVANCES 2021; 7:eabg9923. [PMID: 34172453 PMCID: PMC8232910 DOI: 10.1126/sciadv.abg9923] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Accepted: 05/10/2021] [Indexed: 05/28/2023]
Abstract
The ESX-5 type VII secretion system is a membrane-spanning protein complex key to the virulence of mycobacterial pathogens. However, the overall architecture of the fully assembled translocation machinery and the composition of the central secretion pore have remained unknown. Here, we present the high-resolution structure of the 2.1-megadalton ESX-5 core complex. Our structure captured a dynamic, secretion-competent conformation of the pore within a well-defined transmembrane section, sandwiched between two flexible protein layers at the cytosolic entrance and the periplasmic exit. We propose that this flexibility endows the ESX-5 machinery with large conformational plasticity required to accommodate targeted protein secretion. Compared to known secretion systems, a highly dynamic state of the pore may represent a fundamental principle of bacterial secretion machineries.
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Affiliation(s)
- Katherine S H Beckham
- European Molecular Biology Laboratory, Hamburg Unit, Notkestrasse 85, 22607 Hamburg, Germany
| | - Christina Ritter
- European Molecular Biology Laboratory, Hamburg Unit, Notkestrasse 85, 22607 Hamburg, Germany
| | - Grzegorz Chojnowski
- European Molecular Biology Laboratory, Hamburg Unit, Notkestrasse 85, 22607 Hamburg, Germany
| | - Daniel S Ziemianowicz
- European Molecular Biology Laboratory, Hamburg Unit, Notkestrasse 85, 22607 Hamburg, Germany
| | - Edukondalu Mullapudi
- European Molecular Biology Laboratory, Hamburg Unit, Notkestrasse 85, 22607 Hamburg, Germany
| | - Mandy Rettel
- European Molecular Biology Laboratory, Heidelberg, Germany
| | | | - Simon A Mortensen
- European Molecular Biology Laboratory, Hamburg Unit, Notkestrasse 85, 22607 Hamburg, Germany
| | - Jan Kosinski
- European Molecular Biology Laboratory, Hamburg Unit, Notkestrasse 85, 22607 Hamburg, Germany.
- Centre for Structural Systems Biology (CSSB), Hamburg, Germany
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117 Heidelberg, Germany
| | - Matthias Wilmanns
- European Molecular Biology Laboratory, Hamburg Unit, Notkestrasse 85, 22607 Hamburg, Germany.
- University Hamburg Clinical Centre Hamburg-Eppendorf, Martinistrasse 52, 20246 Hamburg, Germany
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36
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Brilot AF, Lyon AS, Zelter A, Viswanath S, Maxwell A, MacCoss MJ, Muller EG, Sali A, Davis TN, Agard DA. CM1-driven assembly and activation of yeast γ-tubulin small complex underlies microtubule nucleation. eLife 2021; 10:e65168. [PMID: 33949948 PMCID: PMC8099430 DOI: 10.7554/elife.65168] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Accepted: 04/12/2021] [Indexed: 01/08/2023] Open
Abstract
Microtubule (MT) nucleation is regulated by the γ-tubulin ring complex (γTuRC), conserved from yeast to humans. In Saccharomyces cerevisiae, γTuRC is composed of seven identical γ-tubulin small complex (γTuSC) sub-assemblies, which associate helically to template MT growth. γTuRC assembly provides a key point of regulation for the MT cytoskeleton. Here, we combine crosslinking mass spectrometry, X-ray crystallography, and cryo-EM structures of both monomeric and dimeric γTuSCs, and open and closed helical γTuRC assemblies in complex with Spc110p to elucidate the mechanisms of γTuRC assembly. γTuRC assembly is substantially aided by the evolutionarily conserved CM1 motif in Spc110p spanning a pair of adjacent γTuSCs. By providing the highest resolution and most complete views of any γTuSC assembly, our structures allow phosphorylation sites to be mapped, surprisingly suggesting that they are mostly inhibitory. A comparison of our structures with the CM1 binding site in the human γTuRC structure at the interface between GCP2 and GCP6 allows for the interpretation of significant structural changes arising from CM1 helix binding to metazoan γTuRC.
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Affiliation(s)
- Axel F Brilot
- Department of Biochemistry and Biophysics, University of California at San FranciscoSan FranciscoUnited States
| | - Andrew S Lyon
- Department of Biochemistry and Biophysics, University of California at San FranciscoSan FranciscoUnited States
| | - Alex Zelter
- Department of Biochemistry, University of WashingtonSeattleUnited States
| | - Shruthi Viswanath
- Department of Bioengineering and Therapeutic Sciences, University of California at San FranciscoSan FranciscoUnited States
| | - Alison Maxwell
- Department of Biochemistry and Biophysics, University of California at San FranciscoSan FranciscoUnited States
| | - Michael J MacCoss
- Department of Genome Sciences, University of WashingtonSeattleUnited States
| | - Eric G Muller
- Department of Biochemistry, University of WashingtonSeattleUnited States
| | - Andrej Sali
- Department of Bioengineering and Therapeutic Sciences, University of California at San FranciscoSan FranciscoUnited States
| | - Trisha N Davis
- Department of Biochemistry, University of WashingtonSeattleUnited States
| | - David A Agard
- Department of Biochemistry and Biophysics, University of California at San FranciscoSan FranciscoUnited States
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37
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McCafferty CL, Taylor DW, Marcotte EM. Improving integrative 3D modeling into low- to medium-resolution electron microscopy structures with evolutionary couplings. Protein Sci 2021; 30:1006-1021. [PMID: 33759266 PMCID: PMC8040867 DOI: 10.1002/pro.4067] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2021] [Revised: 03/16/2021] [Accepted: 03/16/2021] [Indexed: 12/12/2022]
Abstract
Electron microscopy (EM) continues to provide near-atomic resolution structures for well-behaved proteins and protein complexes. Unfortunately, structures of some complexes are limited to low- to medium-resolution due to biochemical or conformational heterogeneity. Thus, the application of unbiased systematic methods for fitting individual structures into EM maps is important. A method that employs co-evolutionary information obtained solely from sequence data could prove invaluable for quick, confident localization of subunits within these structures. Here, we incorporate the co-evolution of intermolecular amino acids as a new type of distance restraint in the integrative modeling platform in order to build three-dimensional models of atomic structures into EM maps ranging from 10-14 Å in resolution. We validate this method using four complexes of known structure, where we highlight the conservation of intermolecular couplings despite dynamic conformational changes using the BAM complex. Finally, we use this method to assemble the subunits of the bacterial holo-translocon into a model that agrees with previous biochemical data. The use of evolutionary couplings in integrative modeling improves systematic, unbiased fitting of atomic models into medium- to low-resolution EM maps, providing additional information to integrative models lacking in spatial data.
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Affiliation(s)
| | - David W. Taylor
- Department of Molecular BiosciencesUniversity of Texas at AustinAustinTexasUSA
- Center for Systems and Synthetic BiologyUniversity of Texas at AustinAustinTexasUSA
- LIVESTRONG Cancer InstitutesDell Medical SchoolAustinTexasUSA
| | - Edward M. Marcotte
- Department of Molecular BiosciencesUniversity of Texas at AustinAustinTexasUSA
- Center for Systems and Synthetic BiologyUniversity of Texas at AustinAustinTexasUSA
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38
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Mast FD, Fridy PC, Ketaren NE, Wang J, Jacobs EY, Olivier JP, Sanyal T, Molloy KR, Schmidt F, Rutkowska M, Weisblum Y, Rich LM, Vanderwall ER, Dambrauskas N, Vigdorovich V, Keegan S, Jiler JB, Stein ME, Olinares PDB, Hatziioannou T, Sather DN, Debley JS, Fenyö D, Sali A, Bieniasz PD, Aitchison JD, Chait BT, Rout MP. Nanobody Repertoires for Exposing Vulnerabilities of SARS-CoV-2. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2021:2021.04.08.438911. [PMID: 33851164 PMCID: PMC8043454 DOI: 10.1101/2021.04.08.438911] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Despite the great promise of vaccines, the COVID-19 pandemic is ongoing and future serious outbreaks are highly likely, so that multi-pronged containment strategies will be required for many years. Nanobodies are the smallest naturally occurring single domain antigen binding proteins identified to date, possessing numerous properties advantageous to their production and use. We present a large repertoire of high affinity nanobodies against SARS-CoV-2 Spike protein with excellent kinetic and viral neutralization properties, which can be strongly enhanced with oligomerization. This repertoire samples the epitope landscape of the Spike ectodomain inside and outside the receptor binding domain, recognizing a multitude of distinct epitopes and revealing multiple neutralization targets of pseudoviruses and authentic SARS-CoV-2, including in primary human airway epithelial cells. Combinatorial nanobody mixtures show highly synergistic activities, and are resistant to mutational escape and emerging viral variants of concern. These nanobodies establish an exceptional resource for superior COVID-19 prophylactics and therapeutics.
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Affiliation(s)
- Fred D Mast
- Center for Global Infectious Disease Research, Seattle Children's Research Institute, Seattle, Washington, USA
| | - Peter C Fridy
- Laboratory of Cellular and Structural Biology, The Rockefeller University, New York, New York 10065, USA
| | - Natalia E Ketaren
- Laboratory of Cellular and Structural Biology, The Rockefeller University, New York, New York 10065, USA
| | - Junjie Wang
- Laboratory of Mass Spectrometry and Gaseous Ion Chemistry, The Rockefeller University, New York, New York 10065, USA
| | - Erica Y Jacobs
- Laboratory of Mass Spectrometry and Gaseous Ion Chemistry, The Rockefeller University, New York, New York 10065, USA
| | - Jean Paul Olivier
- Center for Global Infectious Disease Research, Seattle Children's Research Institute, Seattle, Washington, USA
| | - Tanmoy Sanyal
- Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, California Institute for Quantitative Biosciences, Byers Hall, 1700 4th Street, Suite 503B, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Kelly R Molloy
- Laboratory of Mass Spectrometry and Gaseous Ion Chemistry, The Rockefeller University, New York, New York 10065, USA
| | - Fabian Schmidt
- Laboratory of Retrovirology, The Rockefeller University, New York, New York 10065, USA
| | - Magda Rutkowska
- Laboratory of Retrovirology, The Rockefeller University, New York, New York 10065, USA
| | - Yiska Weisblum
- Laboratory of Retrovirology, The Rockefeller University, New York, New York 10065, USA
| | - Lucille M Rich
- Center for Immunity and Immunotherapies, Seattle Children's Research Institute, Seattle, Washington, USA
| | - Elizabeth R Vanderwall
- Center for Immunity and Immunotherapies, Seattle Children's Research Institute, Seattle, Washington, USA
| | - Nicolas Dambrauskas
- Center for Global Infectious Disease Research, Seattle Children's Research Institute, Seattle, Washington, USA
| | - Vladimir Vigdorovich
- Center for Global Infectious Disease Research, Seattle Children's Research Institute, Seattle, Washington, USA
| | - Sarah Keegan
- Center for Health Informatics and Bioinformatics, New York University School of Medicine, New York, NY, USA
| | - Jacob B Jiler
- Laboratory of Cellular and Structural Biology, The Rockefeller University, New York, New York 10065, USA
| | - Milana E Stein
- Laboratory of Cellular and Structural Biology, The Rockefeller University, New York, New York 10065, USA
| | - Paul Dominic B Olinares
- Laboratory of Mass Spectrometry and Gaseous Ion Chemistry, The Rockefeller University, New York, New York 10065, USA
| | - Theodora Hatziioannou
- Laboratory of Retrovirology, The Rockefeller University, New York, New York 10065, USA
| | - D Noah Sather
- Center for Global Infectious Disease Research, Seattle Children's Research Institute, Seattle, Washington, USA
- Department of Pediatrics, University of Washington, Seattle, Washington, USA
| | - Jason S Debley
- Center for Immunity and Immunotherapies, Seattle Children's Research Institute, Seattle, Washington, USA
- Department of Pediatrics, University of Washington, Seattle, Washington, USA
- Division of Pulmonary and Sleep Medicine, Seattle Children's Hospital, Seattle, Washington, USA
| | - David Fenyö
- Center for Health Informatics and Bioinformatics, New York University School of Medicine, New York, NY, USA
| | - Andrej Sali
- Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, California Institute for Quantitative Biosciences, Byers Hall, 1700 4th Street, Suite 503B, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Paul D Bieniasz
- Laboratory of Retrovirology, The Rockefeller University, New York, New York 10065, USA
- Howard Hughes Medical Institute, The Rockefeller University, New York, New York 10065, USA
| | - John D Aitchison
- Center for Global Infectious Disease Research, Seattle Children's Research Institute, Seattle, Washington, USA
- Department of Pediatrics, University of Washington, Seattle, Washington, USA
- Department of Biochemistry, University of Washington, Seattle, Washington, USA
| | - Brian T Chait
- Laboratory of Mass Spectrometry and Gaseous Ion Chemistry, The Rockefeller University, New York, New York 10065, USA
| | - Michael P Rout
- Laboratory of Cellular and Structural Biology, The Rockefeller University, New York, New York 10065, USA
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39
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Yperman K, Wang J, Eeckhout D, Winkler J, Vu LD, Vandorpe M, Grones P, Mylle E, Kraus M, Merceron R, Nolf J, Mor E, De Bruyn P, Loris R, Potocký M, Savvides SN, De Rybel B, De Jaeger G, Van Damme D, Pleskot R. Molecular architecture of the endocytic TPLATE complex. SCIENCE ADVANCES 2021; 7:eabe7999. [PMID: 33637534 PMCID: PMC7909872 DOI: 10.1126/sciadv.abe7999] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Accepted: 01/15/2021] [Indexed: 05/03/2023]
Abstract
Eukaryotic cells rely on endocytosis to regulate their plasma membrane proteome and lipidome. Most eukaryotic groups, except fungi and animals, have retained the evolutionary ancient TSET complex as an endocytic regulator. Unlike other coatomer complexes, structural insight into TSET is lacking. Here, we reveal the molecular architecture of plant TSET [TPLATE complex (TPC)] using an integrative structural approach. We identify crucial roles for specific TSET subunits in complex assembly and membrane interaction. Our data therefore generate fresh insight into the differences between the hexameric TSET in Dictyostelium and the octameric TPC in plants. Structural elucidation of this ancient adaptor complex represents the missing piece in the coatomer puzzle and vastly advances our functional as well as evolutionary insight into the process of endocytosis.
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Affiliation(s)
- Klaas Yperman
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Technologiepark 71, 9052 Ghent, Belgium
- VIB Center for Plant Systems Biology, Technologiepark 71, 9052 Ghent, Belgium
| | - Jie Wang
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Technologiepark 71, 9052 Ghent, Belgium
- VIB Center for Plant Systems Biology, Technologiepark 71, 9052 Ghent, Belgium
| | - Dominique Eeckhout
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Technologiepark 71, 9052 Ghent, Belgium
- VIB Center for Plant Systems Biology, Technologiepark 71, 9052 Ghent, Belgium
| | - Joanna Winkler
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Technologiepark 71, 9052 Ghent, Belgium
- VIB Center for Plant Systems Biology, Technologiepark 71, 9052 Ghent, Belgium
| | - Lam Dai Vu
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Technologiepark 71, 9052 Ghent, Belgium
- VIB Center for Plant Systems Biology, Technologiepark 71, 9052 Ghent, Belgium
| | - Michael Vandorpe
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Technologiepark 71, 9052 Ghent, Belgium
- VIB Center for Plant Systems Biology, Technologiepark 71, 9052 Ghent, Belgium
| | - Peter Grones
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Technologiepark 71, 9052 Ghent, Belgium
- VIB Center for Plant Systems Biology, Technologiepark 71, 9052 Ghent, Belgium
| | - Evelien Mylle
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Technologiepark 71, 9052 Ghent, Belgium
- VIB Center for Plant Systems Biology, Technologiepark 71, 9052 Ghent, Belgium
| | - Michael Kraus
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Technologiepark 71, 9052 Ghent, Belgium
- VIB Center for Plant Systems Biology, Technologiepark 71, 9052 Ghent, Belgium
| | - Romain Merceron
- Department of Biochemistry and Microbiology, Ghent University, 9052 Ghent, Belgium
- VIB Center for Inflammation Research, 9052 Ghent, Belgium
| | - Jonah Nolf
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Technologiepark 71, 9052 Ghent, Belgium
- VIB Center for Plant Systems Biology, Technologiepark 71, 9052 Ghent, Belgium
| | - Eliana Mor
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Technologiepark 71, 9052 Ghent, Belgium
- VIB Center for Plant Systems Biology, Technologiepark 71, 9052 Ghent, Belgium
| | - Pieter De Bruyn
- Vrije Universiteit Brussel, Structural Biology Brussels, Department of Biotechnology, 1050 Brussels, Belgium
- VIB-VUB Center for Structural Biology, Structural Biology Research Center, Molecular Recognition Unit, 1050 Brussels, Belgium
| | - Remy Loris
- VIB-VUB Center for Structural Biology, Structural Biology Research Center, Molecular Recognition Unit, 1050 Brussels, Belgium
- Institute of Experimental Botany, Academy of Sciences of the Czech Republic, Rozvojová 263, 16502 Prague 6, Czech Republic
| | - Martin Potocký
- Institute of Experimental Botany, Academy of Sciences of the Czech Republic, Rozvojová 263, 16502 Prague 6, Czech Republic
| | - Savvas N Savvides
- Department of Biochemistry and Microbiology, Ghent University, 9052 Ghent, Belgium
- VIB Center for Inflammation Research, 9052 Ghent, Belgium
| | - Bert De Rybel
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Technologiepark 71, 9052 Ghent, Belgium
- VIB Center for Plant Systems Biology, Technologiepark 71, 9052 Ghent, Belgium
| | - Geert De Jaeger
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Technologiepark 71, 9052 Ghent, Belgium
- VIB Center for Plant Systems Biology, Technologiepark 71, 9052 Ghent, Belgium
| | - Daniël Van Damme
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Technologiepark 71, 9052 Ghent, Belgium.
- VIB Center for Plant Systems Biology, Technologiepark 71, 9052 Ghent, Belgium
| | - Roman Pleskot
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Technologiepark 71, 9052 Ghent, Belgium.
- VIB Center for Plant Systems Biology, Technologiepark 71, 9052 Ghent, Belgium
- Institute of Experimental Botany, Academy of Sciences of the Czech Republic, Rozvojová 263, 16502 Prague 6, Czech Republic
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40
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Hepburn M, Saltzberg DJ, Lee L, Fang S, Atkinson C, Strynadka NCJ, Sali A, Lees-Miller SP, Schriemer DC. The active DNA-PK holoenzyme occupies a tensed state in a staggered synaptic complex. Structure 2021; 29:467-478.e6. [PMID: 33412091 DOI: 10.1016/j.str.2020.12.006] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2020] [Revised: 11/14/2020] [Accepted: 12/09/2020] [Indexed: 01/06/2023]
Abstract
In the non-homologous end-joining (NHEJ) of a DNA double-strand break, DNA ends are bound and protected by DNA-PK, which synapses across the break to tether the broken ends and initiate repair. There is little clarity surrounding the nature of the synaptic complex and the mechanism governing the transition to repair. We report an integrative structure of the synaptic complex at a precision of 13.5 Å, revealing a symmetric head-to-head arrangement with a large offset in the DNA ends and an extensive end-protection mechanism involving a previously uncharacterized plug domain. Hydrogen/deuterium exchange mass spectrometry identifies an allosteric pathway connecting DNA end-binding with the kinase domain that places DNA-PK under tension in the kinase-active state. We present a model for the transition from end-protection to repair, where the synaptic complex supports hierarchical processing of the ends and scaffold assembly, requiring displacement of the catalytic subunit and tension release through kinase activity.
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Affiliation(s)
- Morgan Hepburn
- Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, AB, Canada
| | - Daniel J Saltzberg
- Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Sciences, and California Institute for Quantitative Biomedical Sciences, University of California, San Francisco, CA 94158, USA
| | - Linda Lee
- Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, AB, Canada
| | - Shujuan Fang
- Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, AB, Canada
| | - Claire Atkinson
- Department of Biochemistry and Molecular Biology and High-Resolution Macromolecular Electron Microscopy Facility, The University of British Columbia, Vancouver, British Columbia V6T 1Z3, Canada
| | - Natalie C J Strynadka
- Department of Biochemistry and Molecular Biology and High-Resolution Macromolecular Electron Microscopy Facility, The University of British Columbia, Vancouver, British Columbia V6T 1Z3, Canada
| | - Andrej Sali
- Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Sciences, and California Institute for Quantitative Biomedical Sciences, University of California, San Francisco, CA 94158, USA
| | - Susan P Lees-Miller
- Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, AB, Canada; Robson DNA Science Centre, Arnie Charbonneau Cancer Institute, University of Calgary, Calgary, AB, Canada
| | - David C Schriemer
- Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, AB, Canada; Robson DNA Science Centre, Arnie Charbonneau Cancer Institute, University of Calgary, Calgary, AB, Canada; Department of Chemistry, University of Calgary, Calgary, AB, Canada.
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41
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Jeschke G. MMM: Integrative ensemble modeling and ensemble analysis. Protein Sci 2021; 30:125-135. [PMID: 33015891 PMCID: PMC7737775 DOI: 10.1002/pro.3965] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Revised: 10/01/2020] [Accepted: 10/02/2020] [Indexed: 12/30/2022]
Abstract
Proteins and their complexes can be heterogeneously disordered. In ensemble modeling of such systems with restraints from several experimental techniques the following problems arise: (a) integration of diverse restraints obtained on different samples under different conditions; (b) estimation of a realistic ensemble width; (c) sufficient sampling of conformational space; (d) representation of the ensemble by an interpretable number of conformers; (e) recognition of weak order with site resolution. Here, I introduce several tools that address these problems, focusing on utilization of distance distribution information for estimating ensemble width. The RigiFlex approach integrates such information with high-resolution structures of ordered domains and small-angle scattering data. The EnsembleFit module provides moderately sized ensembles by fitting conformer populations and discarding conformers with low population. EnsembleFit balances the loss in fit quality upon combining restraint subsets from different techniques. Pair correlation analysis for residues and local compaction analysis help in feature detection. The RigiFlex pipeline is tested on data simulated from the structure 70 kDa protein-RNA complex RsmE/RsmZ. It recovers this structure with ensemble width and difference from ground truth both being on the order of 4.2 Å. EnsembleFit reduces the ensemble of the proliferating-cell-nuclear-antigen-associated factor p15PAF from 4,939 to 75 conformers while maintaining good fit quality of restraints. Local compaction analysis for the PaaA2 antitoxin from E. coli O157 revealed correlations between compactness and enhanced residual dipolar couplings in the original NMR restraint set.
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Affiliation(s)
- Gunnar Jeschke
- ETH Zürich, Department of Chemistry and Applied BiosciencesETH ZürichZürichSwitzerland
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42
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Sali A. From integrative structural biology to cell biology. J Biol Chem 2021; 296:100743. [PMID: 33957123 PMCID: PMC8203844 DOI: 10.1016/j.jbc.2021.100743] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Revised: 04/09/2021] [Accepted: 04/30/2021] [Indexed: 12/16/2022] Open
Abstract
Integrative modeling is an increasingly important tool in structural biology, providing structures by combining data from varied experimental methods and prior information. As a result, molecular architectures of large, heterogeneous, and dynamic systems, such as the ∼52-MDa Nuclear Pore Complex, can be mapped with useful accuracy, precision, and completeness. Key challenges in improving integrative modeling include expanding model representations, increasing the variety of input data and prior information, quantifying a match between input information and a model in a Bayesian fashion, inventing more efficient structural sampling, as well as developing better model validation, analysis, and visualization. In addition, two community-level challenges in integrative modeling are being addressed under the auspices of the Worldwide Protein Data Bank (wwPDB). First, the impact of integrative structures is maximized by PDB-Development, a prototype wwPDB repository for archiving, validating, visualizing, and disseminating integrative structures. Second, the scope of structural biology is expanded by linking the wwPDB resource for integrative structures with archives of data that have not been generally used for structure determination but are increasingly important for computing integrative structures, such as data from various types of mass spectrometry, spectroscopy, optical microscopy, proteomics, and genetics. To address the largest of modeling problems, a type of integrative modeling called metamodeling is being developed; metamodeling combines different types of input models as opposed to different types of data to compute an output model. Collectively, these developments will facilitate the structural biology mindset in cell biology and underpin spatiotemporal mapping of the entire cell.
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Affiliation(s)
- Andrej Sali
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, the Department of Bioengineering and Therapeutic Sciences, the Quantitative Biosciences Institute (QBI), and the Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, California, USA.
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43
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Braberg H, Echeverria I, Bohn S, Cimermancic P, Shiver A, Alexander R, Xu J, Shales M, Dronamraju R, Jiang S, Dwivedi G, Bogdanoff D, Chaung KK, Hüttenhain R, Wang S, Mavor D, Pellarin R, Schneidman D, Bader JS, Fraser JS, Morris J, Haber JE, Strahl BD, Gross CA, Dai J, Boeke JD, Sali A, Krogan NJ. Genetic interaction mapping informs integrative structure determination of protein complexes. Science 2020; 370:eaaz4910. [PMID: 33303586 PMCID: PMC7946025 DOI: 10.1126/science.aaz4910] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2019] [Revised: 07/23/2020] [Accepted: 10/23/2020] [Indexed: 12/17/2022]
Abstract
Determining structures of protein complexes is crucial for understanding cellular functions. Here, we describe an integrative structure determination approach that relies on in vivo measurements of genetic interactions. We construct phenotypic profiles for point mutations crossed against gene deletions or exposed to environmental perturbations, followed by converting similarities between two profiles into an upper bound on the distance between the mutated residues. We determine the structure of the yeast histone H3-H4 complex based on ~500,000 genetic interactions of 350 mutants. We then apply the method to subunits Rpb1-Rpb2 of yeast RNA polymerase II and subunits RpoB-RpoC of bacterial RNA polymerase. The accuracy is comparable to that based on chemical cross-links; using restraints from both genetic interactions and cross-links further improves model accuracy and precision. The approach provides an efficient means to augment integrative structure determination with in vivo observations.
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Affiliation(s)
- Hannes Braberg
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
- Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Ignacia Echeverria
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
- Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, CA 94158, USA
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Stefan Bohn
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
- Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, CA 94158, USA
- Gladstone Institutes, San Francisco, CA 94158, USA
| | - Peter Cimermancic
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Anthony Shiver
- Graduate Group in Biophysics, University of California San Francisco, San Francisco, CA 94158, USA
| | - Richard Alexander
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Jiewei Xu
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
- Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, CA 94158, USA
- Gladstone Institutes, San Francisco, CA 94158, USA
| | - Michael Shales
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
- Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Raghuvar Dronamraju
- Department of Biochemistry and Biophysics, University of North Carolina School of Medicine, Chapel Hill, NC 27599, USA
| | - Shuangying Jiang
- CAS Key Laboratory of Quantitative Engineering Biology, Guangdong Provincial Key Laboratory of Synthetic Genomics and Shenzhen Key Laboratory of Synthetic Genomics, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Gajendradhar Dwivedi
- Department of Biology and Rosenstiel Basic Medical Sciences Research Center, Brandeis University, Waltham, MA 02454, USA
| | - Derek Bogdanoff
- Center for Advanced Technology, Department of Biophysics and Biochemistry, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Kaitlin K Chaung
- Center for Advanced Technology, Department of Biophysics and Biochemistry, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Ruth Hüttenhain
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
- Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, CA 94158, USA
- Gladstone Institutes, San Francisco, CA 94158, USA
| | - Shuyi Wang
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - David Mavor
- Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, CA 94158, USA
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Riccardo Pellarin
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Dina Schneidman
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Joel S Bader
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - James S Fraser
- Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, CA 94158, USA
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - John Morris
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA 94158, USA
| | - James E Haber
- Department of Biology and Rosenstiel Basic Medical Sciences Research Center, Brandeis University, Waltham, MA 02454, USA
| | - Brian D Strahl
- Department of Biochemistry and Biophysics, University of North Carolina School of Medicine, Chapel Hill, NC 27599, USA
| | - Carol A Gross
- Department of Microbiology and Immunology and Department of Cell and Tissue Biology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Junbiao Dai
- CAS Key Laboratory of Quantitative Engineering Biology, Guangdong Provincial Key Laboratory of Synthetic Genomics and Shenzhen Key Laboratory of Synthetic Genomics, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Jef D Boeke
- NYU Langone Health, New York, NY 10016, USA.
- High Throughput Biology Center and Department of Molecular Biology & Genetics, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY 10016, USA
- Department of Biomedical Engineering, NYU Tandon School of Engineering, Brooklyn, NY 11201, USA
| | - Andrej Sali
- Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, CA 94158, USA.
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA 94158, USA
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Nevan J Krogan
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA.
- Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, CA 94158, USA
- Gladstone Institutes, San Francisco, CA 94158, USA
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
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44
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Saltzberg DJ, Viswanath S, Echeverria I, Chemmama IE, Webb B, Sali A. Using Integrative Modeling Platform to compute, validate, and archive a model of a protein complex structure. Protein Sci 2020; 30:250-261. [PMID: 33166013 DOI: 10.1002/pro.3995] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Revised: 11/06/2020] [Accepted: 11/06/2020] [Indexed: 12/18/2022]
Abstract
Biology is advanced by producing structural models of biological systems, such as protein complexes. Some systems are recalcitrant to traditional structure determination methods. In such cases, it may still be possible to produce useful models by integrative structure determination that depends on simultaneous use of multiple types of data. An ensemble of models that are sufficiently consistent with the data is produced by a structural sampling method guided by a data-dependent scoring function. The variation in the ensemble of models quantified the uncertainty of the structure, generally resulting from the uncertainty in the input information and actual structural heterogeneity in the samples used to produce the data. Here, we describe how to generate, assess, and interpret ensembles of integrative structural models using our open source Integrative Modeling Platform program (https://integrativemodeling.org).
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Affiliation(s)
- Daniel J Saltzberg
- Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, and California Institute for Quantitative Biosciences, University of California, San Francisco, California, USA
| | - Shruthi Viswanath
- National Center for Biological Sciences, Tata Institute of Fundamental Research, Bangalore, India
| | - Ignacia Echeverria
- Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, and California Institute for Quantitative Biosciences, University of California, San Francisco, California, USA.,Department of Cellular and Molecular Pharmacology, University of California, San Francisco, California, USA
| | - Ilan E Chemmama
- Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, and California Institute for Quantitative Biosciences, University of California, San Francisco, California, USA
| | - Ben Webb
- Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, and California Institute for Quantitative Biosciences, University of California, San Francisco, California, USA
| | - Andrej Sali
- Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, and California Institute for Quantitative Biosciences, University of California, San Francisco, California, USA
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45
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O'Reilly FJ, Xue L, Graziadei A, Sinn L, Lenz S, Tegunov D, Blötz C, Singh N, Hagen WJH, Cramer P, Stülke J, Mahamid J, Rappsilber J. In-cell architecture of an actively transcribing-translating expressome. Science 2020; 369:554-557. [PMID: 32732422 DOI: 10.1126/science.abb3758] [Citation(s) in RCA: 154] [Impact Index Per Article: 38.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Accepted: 06/01/2020] [Indexed: 12/18/2022]
Abstract
Structural biology studies performed inside cells can capture molecular machines in action within their native context. In this work, we developed an integrative in-cell structural approach using the genome-reduced human pathogen Mycoplasma pneumoniae We combined whole-cell cross-linking mass spectrometry, cellular cryo-electron tomography, and integrative modeling to determine an in-cell architecture of a transcribing and translating expressome at subnanometer resolution. The expressome comprises RNA polymerase (RNAP), the ribosome, and the transcription elongation factors NusG and NusA. We pinpointed NusA at the interface between a NusG-bound elongating RNAP and the ribosome and propose that it can mediate transcription-translation coupling. Translation inhibition dissociated the expressome, whereas transcription inhibition stalled and rearranged it. Thus, the active expressome architecture requires both translation and transcription elongation within the cell.
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Affiliation(s)
- Francis J O'Reilly
- Bioanalytics Unit, Institute of Biotechnology, Technische Universität Berlin, 13355 Berlin, Germany
| | - Liang Xue
- Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), 69117 Heidelberg, Germany.,Collaboration for joint PhD degree between EMBL and Heidelberg University, Faculty of Biosciences, 69120 Heidelberg, Germany
| | - Andrea Graziadei
- Bioanalytics Unit, Institute of Biotechnology, Technische Universität Berlin, 13355 Berlin, Germany
| | - Ludwig Sinn
- Bioanalytics Unit, Institute of Biotechnology, Technische Universität Berlin, 13355 Berlin, Germany
| | - Swantje Lenz
- Bioanalytics Unit, Institute of Biotechnology, Technische Universität Berlin, 13355 Berlin, Germany
| | - Dimitry Tegunov
- Department of Molecular Biology, Max-Planck-Institute for Biophysical Chemistry, 37077 Göttingen, Germany
| | - Cedric Blötz
- Department of General Microbiology, Institute of Microbiology and Genetics, GZMB, Georg-August-University Göttingen, 37077 Göttingen, Germany
| | - Neil Singh
- Department of General Microbiology, Institute of Microbiology and Genetics, GZMB, Georg-August-University Göttingen, 37077 Göttingen, Germany
| | - Wim J H Hagen
- Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), 69117 Heidelberg, Germany
| | - Patrick Cramer
- Department of Molecular Biology, Max-Planck-Institute for Biophysical Chemistry, 37077 Göttingen, Germany
| | - Jörg Stülke
- Department of General Microbiology, Institute of Microbiology and Genetics, GZMB, Georg-August-University Göttingen, 37077 Göttingen, Germany
| | - Julia Mahamid
- Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), 69117 Heidelberg, Germany.
| | - Juri Rappsilber
- Bioanalytics Unit, Institute of Biotechnology, Technische Universität Berlin, 13355 Berlin, Germany. .,Wellcome Centre for Cell Biology, University of Edinburgh, Edinburgh, EH9 3BF, UK
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46
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Kwon Y, Kaake RM, Echeverria I, Suarez M, Karimian Shamsabadi M, Stoneham C, Ramirez PW, Kress J, Singh R, Sali A, Krogan N, Guatelli J, Jia X. Structural basis of CD4 downregulation by HIV-1 Nef. Nat Struct Mol Biol 2020; 27:822-828. [PMID: 32719457 PMCID: PMC7483821 DOI: 10.1038/s41594-020-0463-z] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2020] [Accepted: 06/16/2020] [Indexed: 02/06/2023]
Abstract
The HIV-1 Nef protein suppresses multiple immune surveillance mechanisms to promote viral pathogenesis and is an attractive target for the development of novel therapeutics. A key function of Nef is to remove the CD4 receptor from the cell surface by hijacking clathrin- and adaptor protein complex 2 (AP2)-dependent endocytosis. However, exactly how Nef does this has been elusive. Here, we describe the underlying mechanism as revealed by a 3.0-Å crystal structure of a fusion protein comprising Nef and the cytoplasmic domain of CD4 bound to the tetrameric AP2 complex. An intricate combination of conformational changes occurs in both Nef and AP2 to enable CD4 binding and downregulation. A pocket on Nef previously identified as crucial for recruiting class I MHC is also responsible for recruiting CD4, revealing a potential approach to inhibit two of Nef's activities and sensitize the virus to immune clearance.
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Affiliation(s)
- Yonghwa Kwon
- Department of Chemistry and Biochemistry, University of Massachusetts Dartmouth, Dartmouth, MA, USA
| | - Robyn M Kaake
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA, USA
- Gladstone Institutes, San Francisco, CA, USA
| | - Ignacia Echeverria
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA
| | | | | | - Charlotte Stoneham
- The VA San Diego Healthcare System, San Diego, CA, USA
- Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Peter W Ramirez
- Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Jacob Kress
- Department of Chemistry and Biochemistry, University of Massachusetts Dartmouth, Dartmouth, MA, USA
| | - Rajendra Singh
- The VA San Diego Healthcare System, San Diego, CA, USA
- Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Andrej Sali
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA
- Department of Pharmaceutical Chemistry and Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Nevan Krogan
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA, USA
- Gladstone Institutes, San Francisco, CA, USA
| | - John Guatelli
- The VA San Diego Healthcare System, San Diego, CA, USA
- Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Xiaofei Jia
- Department of Chemistry and Biochemistry, University of Massachusetts Dartmouth, Dartmouth, MA, USA.
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47
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Rout MP, Sali A. Principles for Integrative Structural Biology Studies. Cell 2020; 177:1384-1403. [PMID: 31150619 DOI: 10.1016/j.cell.2019.05.016] [Citation(s) in RCA: 165] [Impact Index Per Article: 41.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2019] [Revised: 04/24/2019] [Accepted: 05/06/2019] [Indexed: 12/22/2022]
Abstract
Integrative structure determination is a powerful approach to modeling the structures of biological systems based on data produced by multiple experimental and theoretical methods, with implications for our understanding of cellular biology and drug discovery. This Primer introduces the theory and methods of integrative approaches, emphasizing the kinds of data that can be effectively included in developing models and using the nuclear pore complex as an example to illustrate the practice and challenges involved. These guidelines are intended to aid the researcher in understanding and applying integrative structural methods to systems of their interest and thus take advantage of this rapidly evolving field.
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Affiliation(s)
- Michael P Rout
- Laboratory of Cellular and Structural Biology, The Rockefeller University, New York, NY 10065, USA.
| | - Andrej Sali
- Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, California Institute for Quantitative Biosciences, Byers Hall, 1700 4th Street, Suite 503B, University of California, San Francisco, San Francisco, CA 94158, USA.
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48
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Mintseris J, Gygi SP. High-density chemical cross-linking for modeling protein interactions. Proc Natl Acad Sci U S A 2020; 117:93-102. [PMID: 31848235 PMCID: PMC6955236 DOI: 10.1073/pnas.1902931116] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Detailed mechanistic understanding of protein complex function is greatly enhanced by insights from its 3-dimensional structure. Traditional methods of protein structure elucidation remain expensive and labor-intensive and require highly purified starting material. Chemical cross-linking coupled with mass spectrometry offers an alternative that has seen increased use, especially in combination with other experimental approaches like cryo-electron microscopy. Here we report advances in method development, combining several orthogonal cross-linking chemistries as well as improvements in search algorithms, statistical analysis, and computational cost to achieve coverage of 1 unique cross-linked position pair for every 7 amino acids at a 1% false discovery rate. This is accomplished without any peptide-level fractionation or enrichment. We apply our methods to model the complex between a carbonic anhydrase (CA) and its protein inhibitor, showing that the cross-links are self-consistent and define the interaction interface at high resolution. The resulting model suggests a scaffold for development of a class of protein-based inhibitors of the CA family of enzymes. We next cross-link the yeast proteasome, identifying 3,893 unique cross-linked peptides in 3 mass spectrometry runs. The dataset includes 1,704 unique cross-linked position pairs for the proteasome subunits, more than half of them intersubunit. Using multiple recently solved cryo-EM structures, we show that observed cross-links reflect the conformational dynamics and disorder of some proteasome subunits. We further demonstrate that this level of cross-linking density is sufficient to model the architecture of the 19-subunit regulatory particle de novo.
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Affiliation(s)
- Julian Mintseris
- Department of Cell Biology, Harvard Medical School, Boston, MA 02115
| | - Steven P Gygi
- Department of Cell Biology, Harvard Medical School, Boston, MA 02115
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49
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Berman HM, Adams PD, Bonvin AA, Burley SK, Carragher B, Chiu W, DiMaio F, Ferrin TE, Gabanyi MJ, Goddard TD, Griffin PR, Haas J, Hanke CA, Hoch JC, Hummer G, Kurisu G, Lawson CL, Leitner A, Markley JL, Meiler J, Montelione GT, Phillips GN, Prisner T, Rappsilber J, Schriemer DC, Schwede T, Seidel CAM, Strutzenberg TS, Svergun DI, Tajkhorshid E, Trewhella J, Vallat B, Velankar S, Vuister GW, Webb B, Westbrook JD, White KL, Sali A. Federating Structural Models and Data: Outcomes from A Workshop on Archiving Integrative Structures. Structure 2019; 27:1745-1759. [PMID: 31780431 DOI: 10.1016/j.str.2019.11.002] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2019] [Revised: 10/31/2019] [Accepted: 11/06/2019] [Indexed: 12/23/2022]
Abstract
Structures of biomolecular systems are increasingly computed by integrative modeling. In this approach, a structural model is constructed by combining information from multiple sources, including varied experimental methods and prior models. In 2019, a Workshop was held as a Biophysical Society Satellite Meeting to assess progress and discuss further requirements for archiving integrative structures. The primary goal of the Workshop was to build consensus for addressing the challenges involved in creating common data standards, building methods for federated data exchange, and developing mechanisms for validating integrative structures. The summary of the Workshop and the recommendations that emerged are presented here.
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Affiliation(s)
- Helen M Berman
- Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA; Bridge Institute, Michelson Center, University of Southern California, Los Angeles, CA 90089, USA.
| | - Paul D Adams
- Physical Biosciences Division, Lawrence Berkeley Laboratory, Berkeley, CA 94720-8235, USA; Department of Bioengineering, University of California-Berkeley, Berkeley, CA 94720, USA
| | - Alexandre A Bonvin
- Bijvoet Center for Biomolecular Research, Faculty of Science - Chemistry, Utrecht University, Padualaan 8, 3584 CH Utrecht, the Netherlands
| | - Stephen K Burley
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, The State University of New Jersey, Piscataway, NJ 08854, USA; Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Skaggs School of Pharmacy and Pharmaceutical Sciences and San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA 92093, USA; Rutgers Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, New Brunswick, NJ 08903, USA
| | - Bridget Carragher
- Simons Electron Microscopy Center, New York Structural Biology Center, New York, NY 10027, USA; Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA
| | - Wah Chiu
- Department of Bioengineering, Department of Microbiology and Immunology, Stanford University, Stanford, CA 94305-5447, USA; SLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA
| | - Frank DiMaio
- Department of Biochemistry and Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
| | - Thomas E Ferrin
- Department of Pharmaceutical Chemistry, University of California, San Francisco, CA 94158, USA
| | - Margaret J Gabanyi
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Thomas D Goddard
- Department of Pharmaceutical Chemistry, University of California, San Francisco, CA 94158, USA
| | | | - Juergen Haas
- Swiss Institute of Bioinformatics and Biozentrum, University of Basel, 4056 Basel, Switzerland
| | - Christian A Hanke
- Molecular Physical Chemistry, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
| | - Jeffrey C Hoch
- Department of Molecular Biology and Biophysics, UConn Health, Farmington, CT 06030, USA
| | - Gerhard Hummer
- Department of Theoretical Biophysics, Max Planck Institute of Biophysics, 60438 Frankfurt am Main, Germany; Institute for Biophysics, Goethe University Frankfurt, 60438 Frankfurt am Main, Germany
| | - Genji Kurisu
- Protein Data Bank Japan (PDBj), Institute for Protein Research, Osaka University, Osaka 565-0871, Japan
| | - Catherine L Lawson
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Alexander Leitner
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, 8093 Zurich, Switzerland
| | - John L Markley
- BioMagResBank (BMRB), Biochemistry Department, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Jens Meiler
- Center for Structural Biology, Vanderbilt University, 465 21st Avenue South, Nashville, TN 37221, USA
| | - Gaetano T Montelione
- Center for Advanced Biotechnology and Medicine, Department of Molecular Biology and Biochemistry, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Department of Biochemistry, Robert Wood Johnson Medical School, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytech Institute, Troy, NY 12180, USA
| | - George N Phillips
- BioSciences at Rice and Department of Chemistry, Rice University, Houston, TX 77251, USA
| | - Thomas Prisner
- Institute of Physical and Theoretical Chemistry and Center of Biomolecular Magnetic Resonance, Goethe University Frankfurt, 60438 Frankfurt am Main, Germany
| | - Juri Rappsilber
- Wellcome Trust Centre for Cell Biology, Edinburgh EH9 3JR, Scotland
| | - David C Schriemer
- Department of Biochemistry & Molecular Biology, Robson DNA Science Centre, University of Calgary, Calgary, AB T2N 4N1, Canada
| | - Torsten Schwede
- Swiss Institute of Bioinformatics and Biozentrum, University of Basel, 4056 Basel, Switzerland
| | - Claus A M Seidel
- Molecular Physical Chemistry, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
| | | | - Dmitri I Svergun
- European Molecular Biology Laboratory (EMBL), Hamburg Outstation, Notkestrasse 85, 22607 Hamburg, Germany
| | - Emad Tajkhorshid
- Department of Biochemistry, NIH Center for Macromolecular Modeling and Bioinformatics, Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Jill Trewhella
- School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW 2006, Australia; Department of Chemistry, University of Utah, Salt Lake City, UT 84112, USA
| | - Brinda Vallat
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Sameer Velankar
- Protein Data Bank in Europe (PDBe), European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridgeshire CB10 1SD, UK
| | - Geerten W Vuister
- Department of Molecular and Cell Biology, Leicester Institute of Structural and Chemical Biology, University of Leicester, Leicester LE1 9HN, UK
| | - Benjamin Webb
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - John D Westbrook
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, The State University of New Jersey, Piscataway, NJ 08854, USA; Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Kate L White
- Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA; Bridge Institute, Michelson Center, University of Southern California, Los Angeles, CA 90089, USA
| | - Andrej Sali
- Department of Pharmaceutical Chemistry, University of California, San Francisco, CA 94158, USA; Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA 94158, USA; California Institute for Quantitative Biosciences, University of California, San Francisco, San Francisco, CA 94158, USA.
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Saltzberg DJ, Hepburn M, Pilla KB, Schriemer DC, Lees-Miller SP, Blundell TL, Sali A. SSEThread: Integrative threading of the DNA-PKcs sequence based on data from chemical cross-linking and hydrogen deuterium exchange. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2019; 147:92-102. [PMID: 31570166 DOI: 10.1016/j.pbiomolbio.2019.09.003] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Revised: 08/09/2019] [Accepted: 09/10/2019] [Indexed: 01/19/2023]
Abstract
X-ray crystallography and electron microscopy maps resolved to 3-8 Å are generally sufficient for tracing the path of the polypeptide chain in space, while often insufficient for unambiguously registering the sequence on the path (i.e., threading). Frequently, however, additional information is available from other biophysical experiments, physical principles, statistical analyses, and other prior models. Here, we formulate an integrative approach for sequence assignment to a partial backbone model as an optimization problem, which requires three main components: the representation of the system, the scoring function, and the optimization method. The method is implemented in the open source Integrative Modeling Platform (IMP) (https://integrativemodeling.org), allowing a number of different terms in the scoring function. We apply this method to localizing the sequence assignment within a 199-residue disordered region of three structured and sequence unassigned helices in the DNA-PKcs crystallographic structure, using chemical crosslinks, hydrogen deuterium exchange, and sequence connectivity. The resulting ensemble of threading models provides two major solutions, one of which suggests that the crucial ABCDE cluster of phosphorylation sites cannot undergo intra-molecular autophosphorylation without a conformational rearrangement. The ensemble of solutions embodies the most accurate and precise sequence threading given the available information.
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Affiliation(s)
- Daniel J Saltzberg
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, USA.
| | - Morgan Hepburn
- Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, Canada
| | - Kala Bharath Pilla
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, USA
| | - David C Schriemer
- Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, Canada
| | - Susan P Lees-Miller
- Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, Canada
| | - Tom L Blundell
- Department of Biochemistry, University of Cambridge, Cambridge, UK
| | - Andrej Sali
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, USA
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