1
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Zhao H, Li J, Xiang Y, Malik S, Vartak SV, Veronezi GMB, Young N, Riney M, Kalchschmidt J, Conte A, Jung SK, Ramachandran S, Roeder RG, Shi Y, Casellas R, Asturias FJ. An IDR-dependent mechanism for nuclear receptor control of Mediator interaction with RNA polymerase II. Mol Cell 2024:S1097-2765(24)00484-2. [PMID: 38955181 DOI: 10.1016/j.molcel.2024.06.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 02/29/2024] [Accepted: 06/07/2024] [Indexed: 07/04/2024]
Abstract
The essential Mediator (MED) coactivator complex plays a well-understood role in regulation of basal transcription in all eukaryotes, but the mechanism underlying its role in activator-dependent transcription remains unknown. We investigated modulation of metazoan MED interaction with RNA polymerase II (RNA Pol II) by antagonistic effects of the MED26 subunit and the CDK8 kinase module (CKM). Biochemical analysis of CKM-MED showed that the CKM blocks binding of the RNA Pol II carboxy-terminal domain (CTD), preventing RNA Pol II interaction. This restriction is eliminated by nuclear receptor (NR) binding to CKM-MED, which enables CTD binding in a MED26-dependent manner. Cryoelectron microscopy (cryo-EM) and crosslinking-mass spectrometry (XL-MS) revealed that the structural basis for modulation of CTD interaction with MED relates to a large intrinsically disordered region (IDR) in CKM subunit MED13 that blocks MED26 and CTD interaction with MED but is repositioned upon NR binding. Hence, NRs can control transcription initiation by priming CKM-MED for MED26-dependent RNA Pol II interaction.
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Affiliation(s)
- Haiyan Zhao
- Department of Biochemistry and Molecular Genetics, University of Colorado Anschutz Medical School, Aurora, CO 80045, USA
| | - Jiaqin Li
- Department of Biochemistry and Molecular Genetics, University of Colorado Anschutz Medical School, Aurora, CO 80045, USA
| | - Yufei Xiang
- Center of Protein Engineering and Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Sohail Malik
- Laboratory of Biochemistry and Molecular Biology, Rockefeller University, New York, NY 10065, USA
| | | | - Giovana M B Veronezi
- Department of Biochemistry and Molecular Genetics, University of Colorado Anschutz Medical School, Aurora, CO 80045, USA
| | - Natalie Young
- Department of Biochemistry and Molecular Genetics, University of Colorado Anschutz Medical School, Aurora, CO 80045, USA
| | - McKayla Riney
- Department of Biochemistry and Molecular Genetics, University of Colorado Anschutz Medical School, Aurora, CO 80045, USA
| | | | - Andrea Conte
- Lymphocyte Nuclear Biology, NIAMS, NIH, Bethesda, MD 20892, USA
| | - Seol Kyoung Jung
- Biodata Mining and Discovery Section, NIAMS, NIH, Bethesda, MD 20892, USA
| | - Srinivas Ramachandran
- Department of Biochemistry and Molecular Genetics, University of Colorado Anschutz Medical School, Aurora, CO 80045, USA; RNA Bioscience Initiative, University of Colorado Anschutz Medical School, Aurora, CO 80045, USA
| | - Robert G Roeder
- Laboratory of Biochemistry and Molecular Biology, Rockefeller University, New York, NY 10065, USA
| | - Yi Shi
- Center of Protein Engineering and Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Rafael Casellas
- Lymphocyte Nuclear Biology, NIAMS, NIH, Bethesda, MD 20892, USA
| | - Francisco J Asturias
- Department of Biochemistry and Molecular Genetics, University of Colorado Anschutz Medical School, Aurora, CO 80045, USA.
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2
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Vallat B, Berman HM. Structural highlights of macromolecular complexes and assemblies. Curr Opin Struct Biol 2024; 85:102773. [PMID: 38271778 DOI: 10.1016/j.sbi.2023.102773] [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: 10/05/2023] [Revised: 12/22/2023] [Accepted: 12/26/2023] [Indexed: 01/27/2024]
Abstract
The structures of macromolecular assemblies have given us deep insights into cellular processes and have profoundly impacted biological research and drug discovery. We highlight the structures of macromolecular assemblies that have been modeled using integrative and computational methods and describe how open access to these structures from structural archives has empowered the research community. The arsenal of experimental and computational methods for structure determination ensures a future where whole organelles and cells can be modeled.
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Affiliation(s)
- Brinda Vallat
- Research Collaboratory for Structural Bioinformatics Protein Data Bank and the Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, New Brunswick, NJ 08901, USA.
| | - Helen M Berman
- Research Collaboratory for Structural Bioinformatics Protein Data Bank and the Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Department of Quantitative and Computational Biology, University of Southern California, Los Angeles CA 90089, USA
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3
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Vallat B, Webb BM, Westbrook JD, Goddard TD, Hanke CA, Graziadei A, Peisach E, Zalevsky A, Sagendorf J, Tangmunarunkit H, Voinea S, Sekharan M, Yu J, Bonvin AAMJJ, DiMaio F, Hummer G, Meiler J, Tajkhorshid E, Ferrin TE, Lawson CL, Leitner A, Rappsilber J, Seidel CAM, Jeffries CM, Burley SK, Hoch JC, Kurisu G, Morris K, Patwardhan A, Velankar S, Schwede T, Trewhella J, Kesselman C, Berman HM, Sali A. IHMCIF: An Extension of the PDBx/mmCIF Data Standard for Integrative Structure Determination Methods. J Mol Biol 2024:168546. [PMID: 38508301 DOI: 10.1016/j.jmb.2024.168546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 03/11/2024] [Accepted: 03/14/2024] [Indexed: 03/22/2024]
Abstract
IHMCIF (github.com/ihmwg/IHMCIF) is a data information framework that supports archiving and disseminating macromolecular structures determined by integrative or hybrid modeling (IHM), and making them Findable, Accessible, Interoperable, and Reusable (FAIR). IHMCIF is an extension of the Protein Data Bank Exchange/macromolecular Crystallographic Information Framework (PDBx/mmCIF) that serves as the framework for the Protein Data Bank (PDB) to archive experimentally determined atomic structures of biological macromolecules and their complexes with one another and small molecule ligands (e.g., enzyme cofactors and drugs). IHMCIF serves as the foundational data standard for the PDB-Dev prototype system, developed for archiving and disseminating integrative structures. It utilizes a flexible data representation to describe integrative structures that span multiple spatiotemporal scales and structural states with definitions for restraints from a variety of experimental methods contributing to integrative structural biology. The IHMCIF extension was created with the benefit of considerable community input and recommendations gathered by the Worldwide Protein Data Bank (wwPDB) Task Force for Integrative or Hybrid Methods (wwpdb.org/task/hybrid). Herein, we describe the development of IHMCIF to support evolving methodologies and ongoing advancements in integrative structural biology. Ultimately, IHMCIF will facilitate the unification of PDB-Dev data and tools with the PDB archive so that integrative structures can be archived and disseminated through PDB.
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Affiliation(s)
- Brinda Vallat
- Research Collaboratory for Structural Bioinformatics Protein Data Bank and the Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, New Brunswick, NJ 08901, USA.
| | - Benjamin M Webb
- Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, the Quantitative Biosciences Institute (QBI), and the Research Collaboratory for Structural Bioinformatics Protein Data Bank, University of California, San Francisco, San Francisco, CA 94157, USA
| | - John D Westbrook
- Research Collaboratory for Structural Bioinformatics Protein Data Bank and the Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, New Brunswick, NJ 08901, USA
| | - Thomas D Goddard
- Department of Pharmaceutical Chemistry, University of California, San Francisco, CA 94158, USA
| | - Christian A Hanke
- Molecular Physical Chemistry, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
| | - Andrea Graziadei
- Bioanalytics, Institute of Biotechnology, Technische Universität Berlin, 10623 Berlin, Germany; Human Technopole, 20157 Milan, Italy
| | - Ezra Peisach
- Research Collaboratory for Structural Bioinformatics Protein Data Bank and the Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Arthur Zalevsky
- Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, the Quantitative Biosciences Institute (QBI), and the Research Collaboratory for Structural Bioinformatics Protein Data Bank, University of California, San Francisco, San Francisco, CA 94157, USA
| | - Jared Sagendorf
- Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, the Quantitative Biosciences Institute (QBI), and the Research Collaboratory for Structural Bioinformatics Protein Data Bank, University of California, San Francisco, San Francisco, CA 94157, USA
| | - Hongsuda Tangmunarunkit
- Information Sciences Institute, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA
| | - Serban Voinea
- Information Sciences Institute, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA
| | - Monica Sekharan
- Research Collaboratory for Structural Bioinformatics Protein Data Bank and the Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Jian Yu
- Protein Data Bank Japan, Institute for Protein Research, Osaka University, Suita, Osaka 565-0871, Japan
| | - Alexander A M J J Bonvin
- Bijvoet Centre for Biomolecular Research, Faculty of Science - Chemistry, Utrecht University, Padualaan 8, 3584 CH Utrecht, the Netherlands
| | - Frank DiMaio
- Department of Biochemistry and Institute for Protein Design, University of Washington, Seattle, WA 98195, 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
| | - Jens Meiler
- Center for Structural Biology, Vanderbilt University, 465 21st Avenue South, Nashville, TN 37221, USA; Institute for Drug Discovery, Leipzig University Medical School, 04103 Leipzig, Germany
| | - Emad Tajkhorshid
- NIH Resource for Macromolecular Modeling and Visualization, Beckman Institute for Advanced Science and Technology, Department of Biochemistry, and Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Thomas E Ferrin
- Department of Pharmaceutical Chemistry, University of California, San Francisco, CA 94158, USA
| | - Catherine L Lawson
- Research Collaboratory for Structural Bioinformatics Protein Data Bank and the 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
| | - Juri Rappsilber
- Bioanalytics, Institute of Biotechnology, Technische Universität Berlin, 10623 Berlin, Germany; Wellcome Centre for Cell Biology, University of Edinburgh, Max Born Crescent, Edinburgh EH9 3BF, UK
| | - Claus A M Seidel
- Molecular Physical Chemistry, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
| | - Cy M Jeffries
- European Molecular Biology Laboratory (EMBL), Hamburg Unit, c/o Deutsches Elektronen-Synchrotron (DESY), Notkestrasse 85, 22607 Hamburg, Germany
| | - Stephen K Burley
- Research Collaboratory for Structural Bioinformatics Protein Data Bank and the Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, New Brunswick, NJ 08901, USA; Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer Center, University of California, La Jolla, CA 92093, USA; Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Jeffrey C Hoch
- Biological Magnetic Resonance Data Bank, Department of Molecular Biology and Biophysics, University of Connecticut, Farmington, CT 06030-3305, USA
| | - Genji Kurisu
- Protein Data Bank Japan, Institute for Protein Research, Osaka University, Suita, Osaka 565-0871, Japan
| | - Kyle Morris
- Electron Microscopy Data Bank, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK
| | - Ardan Patwardhan
- Electron Microscopy Data Bank, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK
| | - Sameer Velankar
- Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, Cambridge CB10 1SD, UK
| | - Torsten Schwede
- Biozentrum, University of Basel, Basel, Switzerland; Computational Structural Biology & SIB Swiss Institute of Bioinformatics, Basel, Switzerland
| | - 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
| | - Carl Kesselman
- Information Sciences Institute, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA
| | - Helen M Berman
- Research Collaboratory for Structural Bioinformatics Protein Data Bank and the Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Department of Quantitative and Computational Biology, University of Southern California, Los Angeles CA 90089, USA
| | - Andrej Sali
- Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, the Quantitative Biosciences Institute (QBI), and the Research Collaboratory for Structural Bioinformatics Protein Data Bank, University of California, San Francisco, San Francisco, CA 94157, USA
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4
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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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5
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Little J, Chikina M, Clark NL. Evolutionary rate covariation is a reliable predictor of co-functional interactions but not necessarily physical interactions. eLife 2024; 12:RP93333. [PMID: 38415754 PMCID: PMC10942632 DOI: 10.7554/elife.93333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/29/2024] Open
Abstract
Co-functional proteins tend to have rates of evolution that covary over time. This correlation between evolutionary rates can be measured over the branches of a phylogenetic tree through methods such as evolutionary rate covariation (ERC), and then used to construct gene networks by the identification of proteins with functional interactions. The cause of this correlation has been hypothesized to result from both compensatory coevolution at physical interfaces and nonphysical forces such as shared changes in selective pressure. This study explores whether coevolution due to compensatory mutations has a measurable effect on the ERC signal. We examined the difference in ERC signal between physically interacting protein domains within complexes compared to domains of the same proteins that do not physically interact. We found no generalizable relationship between physical interaction and high ERC, although a few complexes ranked physical interactions higher than nonphysical interactions. Therefore, we conclude that coevolution due to physical interaction is weak, but present in the signal captured by ERC, and we hypothesize that the stronger signal instead comes from selective pressures on the protein as a whole and maintenance of the general function.
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Affiliation(s)
- Jordan Little
- Department of Human Genetics, University of UtahSalt Lake CityUnited States
| | - Maria Chikina
- Department of Computational Biology, University of PittsburghPittsburghUnited States
| | - Nathan L Clark
- Department of Human Genetics, University of UtahSalt Lake CityUnited States
- Department of Biological Sciences, University of PittsburghPittsburghUnited States
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6
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Binsabaan SA, Freeman KG, Hatfull GF, VanDemark AP. The Cytotoxic Mycobacteriophage Protein Phaedrus gp82 Interacts with and Modulates the Activity of the Host ATPase, MoxR. J Mol Biol 2023; 435:168261. [PMID: 37678706 PMCID: PMC10593117 DOI: 10.1016/j.jmb.2023.168261] [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: 07/18/2023] [Revised: 08/29/2023] [Accepted: 08/30/2023] [Indexed: 09/09/2023]
Abstract
Approximately 70% of bacteriophage-encoded proteins are of unknown function. Elucidating these protein functions represents opportunities to discover new phage-host interactions and mechanisms by which the phages modulate host activities. Here, we describe a pipeline for prioritizing phage-encoded proteins for structural analysis and characterize the gp82 protein encoded by mycobacteriophage Phaedrus. Structural and solution studies of gp82 show it is a trimeric protein containing two domains. Co-precipitation studies with the host Mycobacterium smegmatis identified the ATPase MoxR as an interacting partner protein. Phaedrus gp82-MoxR interaction requires the presence of a loop sequence within gp82 that is highly exposed and disordered in the crystallographic structure. We show that Phaedrus gp82 overexpression in M. smegmatis retards the growth of M. smegmatis on solid medium, resulting in a small colony phenotype. Overexpression of gp82 containing a mutant disordered loop or the overexpression of MoxR both rescue this phenotype. Lastly, we show that recombinant gp82 reduces levels of MoxR-mediated ATPase activity in vitro that is required for its chaperone function, and that the disordered loop plays an important role in this phenotype. We conclude that Phaedrus gp82 binds to and reduces mycobacterial MoxR activity, leading to reduced function of host proteins that require MoxR chaperone activity for their normal activity.
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Affiliation(s)
- Saeed A Binsabaan
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh PA 15260, USA
| | - Krista G Freeman
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh PA 15260, USA
| | - Graham F Hatfull
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh PA 15260, USA
| | - Andrew P VanDemark
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh PA 15260, USA; Department of Chemistry, University of Pittsburgh, Pittsburgh PA 15260, USA.
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7
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Brodie NI, Sarpe V, Crowder DA, Schriemer D. All-in-One Pseudo-MS 3 Method for the Analysis of Gas-Phase Cleavable Protein Crosslinking Reactions. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2023; 34:2146-2155. [PMID: 37590165 DOI: 10.1021/jasms.3c00134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/19/2023]
Abstract
Crosslinking mass spectrometry (XL-MS) supports structure analysis of individual proteins and highly complex whole-cell interactomes. The identification of crosslinked peptides from enzymatic digests remains challenging, especially at the cell level. Empirical methods that use gas-phase cleavable crosslinkers can simplify the identification process by enabling an MS3-based strategy that turns crosslink identification into a simpler problem of detecting two separable peptides. However, the method is limited to select instrument platforms and is challenged by duty cycle constraints. Here, we revisit a pseudo-MS3 concept that incorporates in-source fragmentation, where a fast switch between gentle high-transmission source conditions and harsher in-source fragmentation settings liberates peptides for standard MS2-based peptide identification. We present an all-in-one method where retention time matches between the crosslink precursor and the liberated peptides establish linkage, and MS2 sequencing identifies the source-liberated peptides. We demonstrate that DC4, a very labile cleavable crosslinker, generates high-intensity peptides in-source. Crosslinks can be identified from these liberated peptides, as they are chromatographically well-resolved from monolinks. Using bovine serum albumin (BSA) as a crosslinking test case, we detect 27% more crosslinks with pseudo-MS3 over a best-in-class MS3 method. While performance is slightly lower for whole-cell lysates (generating two-thirds of the identifications of a standard method), we find that 60% of these hits are unique, highlighting the complementarity of the method.
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Affiliation(s)
- Nicholas I Brodie
- Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, Alberta, Canada T2N-4N1
| | - Vladimir Sarpe
- Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, Alberta, Canada T2N-4N1
| | - D Alex Crowder
- Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, Alberta, Canada T2N-4N1
| | - David Schriemer
- Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, Alberta, Canada T2N-4N1
- Department of Chemistry, University of Calgary, Calgary, Alberta, Canada T2N-4N1
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8
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Akey CW, Echeverria I, Ouch C, Nudelman I, Shi Y, Wang J, Chait BT, Sali A, Fernandez-Martinez J, Rout MP. Implications of a multiscale structure of the yeast nuclear pore complex. Mol Cell 2023; 83:3283-3302.e5. [PMID: 37738963 PMCID: PMC10630966 DOI: 10.1016/j.molcel.2023.08.025] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 06/23/2023] [Accepted: 08/24/2023] [Indexed: 09/24/2023]
Abstract
Nuclear pore complexes (NPCs) direct the nucleocytoplasmic transport of macromolecules. Here, we provide a composite multiscale structure of the yeast NPC, based on improved 3D density maps from cryogenic electron microscopy and AlphaFold2 models. Key features of the inner and outer rings were integrated into a comprehensive model. We resolved flexible connectors that tie together the core scaffold, along with equatorial transmembrane complexes and a lumenal ring that anchor this channel within the pore membrane. The organization of the nuclear double outer ring reveals an architecture that may be shared with ancestral NPCs. Additional connections between the core scaffold and the central transporter suggest that under certain conditions, a degree of local organization is present at the periphery of the transport machinery. These connectors may couple conformational changes in the scaffold to the central transporter to modulate transport. Collectively, this analysis provides insights into assembly, transport, and NPC evolution.
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Affiliation(s)
- Christopher W Akey
- Department of Pharmacology, Physiology and Biophysics, Boston University, Chobanian and Avedisian School of Medicine, 700 Albany Street, Boston, MA 02118, USA.
| | - Ignacia Echeverria
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Christna Ouch
- Department of Pharmacology, Physiology and Biophysics, Boston University, Chobanian and Avedisian School of Medicine, 700 Albany Street, Boston, MA 02118, USA; Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, 364 Plantation St., Worcester, MA 01605, USA
| | - Ilona Nudelman
- Laboratory of Cellular and Structural Biology, The Rockefeller University, New York, NY 10065, USA
| | - Yi Shi
- Laboratory of Mass Spectrometry and Gaseous Ion Chemistry, The Rockefeller University, New York, NY, USA
| | - Junjie Wang
- Laboratory of Mass Spectrometry and Gaseous Ion Chemistry, The Rockefeller University, New York, NY, 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
| | - 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.
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9
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Birklbauer MJ, Matzinger M, Müller F, Mechtler K, Dorfer V. MS Annika 2.0 Identifies Cross-Linked Peptides in MS2-MS3-Based Workflows at High Sensitivity and Specificity. J Proteome Res 2023; 22:3009-3021. [PMID: 37566781 PMCID: PMC10476269 DOI: 10.1021/acs.jproteome.3c00325] [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: 05/31/2023] [Indexed: 08/13/2023]
Abstract
Cross-linking mass spectrometry has become a powerful tool for the identification of protein-protein interactions and for gaining insight into the structures of proteins. We previously published MS Annika, a cross-linking search engine which can accurately identify cross-linked peptides in MS2 spectra from a variety of different MS-cleavable cross-linkers. In this publication, we present MS Annika 2.0, an updated version implementing a new search algorithm that, in addition to MS2 level, only supports the processing of data from MS2-MS3-based approaches for the identification of peptides from MS3 spectra, and introduces a novel scoring function for peptides identified across multiple MS stages. Detected cross-links are validated by estimating the false discovery rate (FDR) using a target-decoy approach. We evaluated the MS3-search-capabilities of MS Annika 2.0 on five different datasets covering a variety of experimental approaches and compared it to XlinkX and MaXLinker, two other cross-linking search engines. We show that MS Annika detects up to 4 times more true unique cross-links while simultaneously yielding less false positive hits and therefore a more accurate FDR estimation than the other two search engines. All mass spectrometry proteomics data along with result files have been deposited to the ProteomeXchange consortium via the PRIDE partner repository with the dataset identifier PXD041955.
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Affiliation(s)
- Micha J. Birklbauer
- Bioinformatics
Research Group, University of Applied Sciences
Upper Austria, Softwarepark
11, 4232 Hagenberg, Austria
| | - Manuel Matzinger
- Research
Institute of Molecular Pathology (IMP), Vienna BioCenter (VBC), Campus-Vienna-Biocenter 1, 1030 Vienna, Austria
| | - Fränze Müller
- Research
Institute of Molecular Pathology (IMP), Vienna BioCenter (VBC), Campus-Vienna-Biocenter 1, 1030 Vienna, Austria
| | - Karl Mechtler
- Research
Institute of Molecular Pathology (IMP), Vienna BioCenter (VBC), Campus-Vienna-Biocenter 1, 1030 Vienna, Austria
- Institute
of Molecular Biotechnology (IMBA), Austrian Academy of Sciences, Vienna
BioCenter (VBC), Dr.
Bohr-Gasse 3, 1030 Vienna, Austria
- Gregor
Mendel Institute (GMI), Austrian Academy of Sciences, Vienna BioCenter
(VBC), Dr. Bohr-Gasse
3, 1030 Vienna, Austria
| | - Viktoria Dorfer
- Bioinformatics
Research Group, University of Applied Sciences
Upper Austria, Softwarepark
11, 4232 Hagenberg, Austria
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10
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Ellison MA, Namjilsuren S, Shirra M, Blacksmith M, Schusteff R, Kerr E, Fang F, Xiang Y, Shi Y, Arndt K. Spt6 directly interacts with Cdc73 and is required for Paf1 complex occupancy at active genes in Saccharomyces cerevisiae. Nucleic Acids Res 2023; 51:4814-4830. [PMID: 36928138 PMCID: PMC10250246 DOI: 10.1093/nar/gkad180] [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: 04/29/2022] [Revised: 02/21/2023] [Accepted: 02/28/2023] [Indexed: 03/18/2023] Open
Abstract
The Paf1 complex (Paf1C) is a conserved transcription elongation factor that regulates transcription elongation efficiency, facilitates co-transcriptional histone modifications, and impacts molecular processes linked to RNA synthesis, such as polyA site selection. Coupling of the activities of Paf1C to transcription elongation requires its association with RNA polymerase II (Pol II). Mutational studies in yeast identified Paf1C subunits Cdc73 and Rtf1 as important mediators of Paf1C association with Pol II on active genes. While the interaction between Rtf1 and the general elongation factor Spt5 is relatively well-understood, the interactions involving Cdc73 have not been fully elucidated. Using a site-specific protein cross-linking strategy in yeast cells, we identified direct interactions between Cdc73 and two components of the Pol II elongation complex, the elongation factor Spt6 and the largest subunit of Pol II. Both of these interactions require the tandem SH2 domain of Spt6. We also show that Cdc73 and Spt6 can interact in vitro and that rapid depletion of Spt6 dissociates Paf1 from chromatin, altering patterns of Paf1C-dependent histone modifications genome-wide. These results reveal interactions between Cdc73 and the Pol II elongation complex and identify Spt6 as a key factor contributing to the occupancy of Paf1C at active genes in Saccharomyces cerevisiae.
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Affiliation(s)
- Mitchell A Ellison
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA 15260, USA
| | | | - Margaret K Shirra
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA 15260, USA
| | - Matthew S Blacksmith
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA 15260, USA
| | - Rachel A Schusteff
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA 15260, USA
| | - Eleanor M Kerr
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA 15260, USA
| | - Fei Fang
- Department of Cell Biology, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Yufei Xiang
- Department of Cell Biology, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Yi Shi
- Department of Cell Biology, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Karen M Arndt
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA 15260, USA
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11
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Jiao F, Salituro LJ, Yu C, Gutierrez CB, Rychnovsky SD, Huang L. Exploring an Alternative Cysteine-Reactive Chemistry to Enable Proteome-Wide PPI Analysis by Cross-Linking Mass Spectrometry. Anal Chem 2023; 95:2532-2539. [PMID: 36652389 DOI: 10.1021/acs.analchem.2c04986] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
The development of MS-cleavable cross-linking mass spectrometry (XL-MS) has enabled the effective capture and identification of endogenous protein-protein interactions (PPIs) and their residue contacts at the global scale without cell engineering. So far, only lysine-reactive cross-linkers have been successfully applied for proteome-wide PPI profiling. However, lysine cross-linkers alone cannot uncover the complete PPI map in cells. Previously, we have developed a maleimide-based cysteine-reactive MS-cleavable cross-linker (bismaleimide sulfoxide (BMSO)) that is effective for mapping PPIs of protein complexes to yield interaction contacts complementary to lysine-reactive reagents. While successful, the hydrolysis and limited selectivity of maleimides at physiological pH make their applications in proteome-wide XL-MS challenging. To enable global PPI mapping, we have explored an alternative cysteine-labeling chemistry and thus designed and synthesized a sulfoxide-containing MS-cleavable haloacetamide-based cross-linker, Dibromoacetamide sulfoxide (DBrASO). Our results have demonstrated that DBrASO cross-linked peptides display the same fragmentation characteristics as other sulfoxide-containing MS-cleavable cross-linkers, permitting their unambiguous identification by MSn. In combination with a newly developed two-dimensional peptide fractionation method, we have successfully performed DBrASO-based XL-MS analysis of HEK293 cell lysates and demonstrated its capability to complement lysine-reactive reagents and expand PPI coverage at the systems-level.
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Affiliation(s)
- Fenglong Jiao
- Department of Physiology and Biophysics, University of California, Irvine, Irvine, California 92697, United States
| | - Leah J Salituro
- Department of Chemistry, University of California, Irvine, Irvine, California 92697, United States
| | - Clinton Yu
- Department of Physiology and Biophysics, University of California, Irvine, Irvine, California 92697, United States
| | - Craig B Gutierrez
- Department of Physiology and Biophysics, University of California, Irvine, Irvine, California 92697, United States
| | - Scott D Rychnovsky
- Department of Chemistry, University of California, Irvine, Irvine, California 92697, United States
| | - Lan Huang
- Department of Physiology and Biophysics, University of California, Irvine, Irvine, California 92697, United States
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12
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Burley SK, Berman HM, Chiu W, Dai W, Flatt JW, Hudson BP, Kaelber JT, Khare SD, Kulczyk AW, Lawson CL, Pintilie GD, Sali A, Vallat B, Westbrook JD, Young JY, Zardecki C. Electron microscopy holdings of the Protein Data Bank: the impact of the resolution revolution, new validation tools, and implications for the future. Biophys Rev 2022; 14:1281-1301. [PMID: 36474933 PMCID: PMC9715422 DOI: 10.1007/s12551-022-01013-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Accepted: 11/06/2022] [Indexed: 12/04/2022] Open
Abstract
As a discipline, structural biology has been transformed by the three-dimensional electron microscopy (3DEM) "Resolution Revolution" made possible by convergence of robust cryo-preservation of vitrified biological materials, sample handling systems, and measurement stages operating a liquid nitrogen temperature, improvements in electron optics that preserve phase information at the atomic level, direct electron detectors (DEDs), high-speed computing with graphics processing units, and rapid advances in data acquisition and processing software. 3DEM structure information (atomic coordinates and related metadata) are archived in the open-access Protein Data Bank (PDB), which currently holds more than 11,000 3DEM structures of proteins and nucleic acids, and their complexes with one another and small-molecule ligands (~ 6% of the archive). Underlying experimental data (3DEM density maps and related metadata) are stored in the Electron Microscopy Data Bank (EMDB), which currently holds more than 21,000 3DEM density maps. After describing the history of the PDB and the Worldwide Protein Data Bank (wwPDB) partnership, which jointly manages both the PDB and EMDB archives, this review examines the origins of the resolution revolution and analyzes its impact on structural biology viewed through the lens of PDB holdings. Six areas of focus exemplifying the impact of 3DEM across the biosciences are discussed in detail (icosahedral viruses, ribosomes, integral membrane proteins, SARS-CoV-2 spike proteins, cryogenic electron tomography, and integrative structure determination combining 3DEM with complementary biophysical measurement techniques), followed by a review of 3DEM structure validation by the wwPDB that underscores the importance of community engagement.
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Affiliation(s)
- Stephen K. Burley
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, New Brunswick, NJ 08901 USA
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer Center, University of California San Diego, La Jolla, CA 92093 USA
- Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, 174 Frelinghuysen Road, Piscataway, NJ 08854 USA
| | - Helen M. Berman
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, 174 Frelinghuysen Road, Piscataway, NJ 08854 USA
| | - Wah Chiu
- Department of Bioengineering, Stanford University, Stanford, CA USA
- Division of CryoEM and Bioimaging, SSRL, SLAC National Accelerator Laboratory, Stanford University, Menlo Park, CA USA
| | - Wei Dai
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Department of Cell Biology and Neuroscience, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
| | - Justin W. Flatt
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
| | - Brian P. Hudson
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
| | - Jason T. Kaelber
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
| | - Sagar D. Khare
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, New Brunswick, NJ 08901 USA
- Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, 174 Frelinghuysen Road, Piscataway, NJ 08854 USA
| | - Arkadiusz W. Kulczyk
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Department of Biochemistry and Microbiology, Rutgers, The State University of New Jersey, Piscataway, NJ 08901 USA
| | - Catherine L. Lawson
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
| | | | - Andrej Sali
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, Quantitative Biosciences Institute, University of California San Francisco, San Francisco, CA 94158 USA
| | - Brinda Vallat
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, New Brunswick, NJ 08901 USA
| | - John D. Westbrook
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, New Brunswick, NJ 08901 USA
| | - Jasmine Y. Young
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
| | - Christine Zardecki
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
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13
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Dubey AK, Kumar P, Mandal D, Ravichandiran V, Singh SK. An introduction to dynamic nucleoporins in Leishmania species: Novel targets for tropical-therapeutics. J Parasit Dis 2022; 46:1176-1191. [PMID: 36457769 PMCID: PMC9606170 DOI: 10.1007/s12639-022-01515-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 06/20/2022] [Indexed: 11/28/2022] Open
Abstract
As an ailment, leishmaniasis is still an incessant challenge in neglected tropical diseases and neglected infections of poverty worldwide. At present, the diagnosis and treatment to combat Leishmania tropical infections are not substantial remedies and require advanced & specific research. Therefore, there is a need for a potential novel target to overcome established medicament modalities' limitations in pathogenicity. In this review, we proposed a few ab initio findings in nucleoporins of nuclear pore complex in Leishmania sp. concerning other infectious protists. So, through structural analysis and dynamics studies, we hypothesize the nuclear pore molecular machinery & functionality. The gatekeepers Nups, export of mRNA, mitotic spindle formation are salient features in cellular mechanics and this is regulated by dynamic nucleoporins. Here, diverse studies suggest that Nup93/NIC96, Nup155/Nup144, Mlp1/Mlp2/Tpr of Leishmania Species can be a picked out marker for diagnostic, immune-modulation, and novel drug targets. In silico prediction of nucleoporin-functional interactors such as NUP54/57, RNA helicase, Ubiquitin-protein ligase, Exportin 1, putative T-lymphocyte triggering factor, and 9 uncharacterized proteins suggest few more noble targets. The novel drug targeting to importins/exportins of Leishmania sp. and defining mechanism of Leptomycin-B, SINE compounds, Curcumins, Selinexor can be an arc-light in therapeutics. The essence of the review in Leishmania's nucleoporins is to refocus our research on noble molecular targets for tropical therapeutics. Supplementary Information The online version contains supplementary material available at 10.1007/s12639-022-01515-0.
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Affiliation(s)
- Amit Kumar Dubey
- Department of Biotechnology, National Institute of Pharmaceutical Education and Research (NIPER), Hajipur, Vaishali, Bihar 844102 India
- Parasite Immunology Lab, Microbiology Department, Indian Council of Medical Research (ICMR)-Rajendra Memorial Research Institute of Medical Sciences (RMRIMS), Patna, Bihar 800007 India
| | - Prakash Kumar
- Department of Biotechnology, National Institute of Pharmaceutical Education and Research (NIPER), Hajipur, Vaishali, Bihar 844102 India
| | - Debabrata Mandal
- Department of Biotechnology, National Institute of Pharmaceutical Education and Research (NIPER), Hajipur, Vaishali, Bihar 844102 India
| | - V. Ravichandiran
- Department of Biotechnology, National Institute of Pharmaceutical Education and Research (NIPER), Hajipur, Vaishali, Bihar 844102 India
| | - Shubhankar Kumar Singh
- Parasite Immunology Lab, Microbiology Department, Indian Council of Medical Research (ICMR)-Rajendra Memorial Research Institute of Medical Sciences (RMRIMS), Patna, Bihar 800007 India
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14
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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: 3] [Impact Index Per Article: 1.5] [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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15
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Moll A, Ramirez LM, Ninov M, Schwarz J, Urlaub H, Zweckstetter M. Hsp multichaperone complex buffers pathologically modified Tau. Nat Commun 2022; 13:3668. [PMID: 35760815 PMCID: PMC9237115 DOI: 10.1038/s41467-022-31396-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Accepted: 06/16/2022] [Indexed: 11/23/2022] Open
Abstract
Alzheimer’s disease is a neurodegenerative disorder in which misfolding and aggregation of pathologically modified Tau is critical for neuronal dysfunction and degeneration. The two central chaperones Hsp70 and Hsp90 coordinate protein homeostasis, but the nature of the interaction of Tau with the Hsp70/Hsp90 machinery has remained enigmatic. Here we show that Tau is a high-affinity substrate of the human Hsp70/Hsp90 machinery. Complex formation involves extensive intermolecular contacts, blocks Tau aggregation and depends on Tau’s aggregation-prone repeat region. The Hsp90 co-chaperone p23 directly binds Tau and stabilizes the multichaperone/substrate complex, whereas the E3 ubiquitin-protein ligase CHIP efficiently disassembles the machinery targeting Tau to proteasomal degradation. Because phosphorylated Tau binds the Hsp70/Hsp90 machinery but is not recognized by Hsp90 alone, the data establish the Hsp70/Hsp90 multichaperone complex as a critical regulator of Tau in neurodegenerative diseases. Alzheimer’s disease is characterized by the accumulation of aggregated tau protein. Here the authors find that Hsp chaperones, which normally protect cell homeostasis, can assemble with co-chaperones in a “multichaperone machinery” to target tau aggregation.
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Affiliation(s)
- Antonia Moll
- German Center for Neurodegenerative Diseases (DZNE), Von-Siebold-Str. 3a, 37075, Göttingen, Germany.,Department for NMR-based Structural Biology, Max Planck Institute for Multidisciplinary Sciences, Am Fassberg 11, 37077, Göttingen, Germany
| | - Lisa Marie Ramirez
- German Center for Neurodegenerative Diseases (DZNE), Von-Siebold-Str. 3a, 37075, Göttingen, Germany.,Department for NMR-based Structural Biology, Max Planck Institute for Multidisciplinary Sciences, Am Fassberg 11, 37077, Göttingen, Germany
| | - Momchil Ninov
- Max Planck Institute for Multidisciplinary Sciences, Bioanalytical Mass Spectrometry Group, Am Fassberg 11, 37077, Göttingen, Germany.,University Medical Center Goettingen, Institute of Clinical Chemistry, Bioanalytics, Robert-Koch-Strasse 40, 37075, Göttingen, Germany
| | - Juliane Schwarz
- Max Planck Institute for Multidisciplinary Sciences, Bioanalytical Mass Spectrometry Group, Am Fassberg 11, 37077, Göttingen, Germany.,University Medical Center Goettingen, Institute of Clinical Chemistry, Bioanalytics, Robert-Koch-Strasse 40, 37075, Göttingen, Germany
| | - Henning Urlaub
- Max Planck Institute for Multidisciplinary Sciences, Bioanalytical Mass Spectrometry Group, Am Fassberg 11, 37077, Göttingen, Germany.,University Medical Center Goettingen, Institute of Clinical Chemistry, Bioanalytics, Robert-Koch-Strasse 40, 37075, Göttingen, Germany
| | - Markus Zweckstetter
- German Center for Neurodegenerative Diseases (DZNE), Von-Siebold-Str. 3a, 37075, Göttingen, Germany. .,Department for NMR-based Structural Biology, Max Planck Institute for Multidisciplinary Sciences, Am Fassberg 11, 37077, Göttingen, Germany.
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16
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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 2022; 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] [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 CA USA
- Quantitative Biosciences Institute University of California, San Francisco CA USA
- Department of Bioengineering and Therapeutic Sciences University of California, San Francisco CA USA
| | - Hannes Braberg
- Department of Cellular and Molecular Pharmacology University of California, San Francisco CA USA
- Quantitative Biosciences Institute University of California, San Francisco CA USA
| | - Nevan J. Krogan
- Department of Cellular and Molecular Pharmacology University of California, San Francisco CA USA
- Quantitative Biosciences Institute University of California, San Francisco CA USA
- Gladstone Institute of Data Science and Biotechnology J. David Gladstone Institutes San Francisco CA USA
| | - Andrej Sali
- Quantitative Biosciences Institute University of California, San Francisco CA USA
- Department of Bioengineering and Therapeutic Sciences University of California, San Francisco CA USA
- Department of Pharmaceutical Chemistry University of California, San Francisco CA USA
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17
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Hancock M, Peulen TO, Webb B, Poon B, Fraser JS, Adams P, Sali A. Integration of software tools for integrative modeling of biomolecular systems. J Struct Biol 2022; 214:107841. [PMID: 35149213 PMCID: PMC9278553 DOI: 10.1016/j.jsb.2022.107841] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 01/28/2022] [Accepted: 02/04/2022] [Indexed: 12/31/2022]
Abstract
Integrative modeling computes a model based on varied types of input information, be it from experiments or prior models. Often, a type of input information will be best handled by a specific modeling software package. In such a case, we desire to integrate our integrative modeling software package, Integrative Modeling Platform (IMP), with software specialized to the computational demands of the modeling problem at hand. After several attempts, however, we have concluded that even in collaboration with the software's developers, integration is either impractical or impossible. The reasons for the intractability of integration include software incompatibilities, differing modeling logic, the costs of collaboration, and academic incentives. In the integrative modeling software ecosystem, several large modeling packages exist with often redundant tools. We reason, therefore, that the other development groups have similarly concluded that the benefit of integration does not justify the cost. As a result, modelers are often restricted to the set of tools within a single software package. The inability to integrate tools from distinct software negatively impacts the quality of the models and the efficiency of the modeling. As the complexity of modeling problems grows, we seek to galvanize developers and modelers to consider the long-term benefit that software interoperability yields. In this article, we formulate a demonstrative set of software standards for implementing a model search using tools from independent software packages and discuss our efforts to integrate IMP and the crystallography suite Phenix within the Bayesian modeling framework.
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Affiliation(s)
- Matthew Hancock
- Biophysics Graduate Program, University of California, San Francisco, MC 2240 1600 16th St, San Francisco, CA 94143, United States; Department of Bioengineering and Therapeutic Sciences, UCSF Box 0775 1700 4th St, University of California, San Francisco, San Francisco, CA 94158, United States.
| | - Thomas-Otavio Peulen
- Department of Bioengineering and Therapeutic Sciences, UCSF Box 0775 1700 4th St, University of California, San Francisco, San Francisco, CA 94158, United States.
| | - Benjamin Webb
- Department of Bioengineering and Therapeutic Sciences, UCSF Box 0775 1700 4th St, University of California, San Francisco, San Francisco, CA 94158, United States.
| | - Billy Poon
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Building 33 1 Cyclotron Rd, Berkeley, CA 94270, United States.
| | - James S Fraser
- Department of Bioengineering and Therapeutic Sciences, UCSF Box 0775 1700 4th St, University of California, San Francisco, San Francisco, CA 94158, United States; Quantitative Biosciences Institute (QBI), University of California, San Francisco, 1700 4th St, San Francisco, CA, United States.
| | - Paul Adams
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Building 33 1 Cyclotron Rd, Berkeley, CA 94270, United States; Department of Bioengineering, University of California, Berkeley, MC 1762 306 Stanley Hall, Berkeley, CA 94720, United States.
| | - Andrej Sali
- Department of Bioengineering and Therapeutic Sciences, UCSF Box 0775 1700 4th St, University of California, San Francisco, San Francisco, CA 94158, United States; Department of Pharmaceutical Chemistry, University of California, San Francisco, UCSF Box 2880 600 16th St, San Francisco, CA 94143, United States; Quantitative Biosciences Institute (QBI), University of California, San Francisco, 1700 4th St, San Francisco, CA, United States.
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18
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Yu C, Wang X, Huang L. Developing a Targeted Quantitative Strategy for Sulfoxide-Containing MS-Cleavable Cross-Linked Peptides to Probe Conformational Dynamics of Protein Complexes. Anal Chem 2022; 94:4390-4398. [PMID: 35193351 DOI: 10.1021/acs.analchem.1c05298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
In recent years, cross-linking mass spectrometry (XL-MS) has made enormous strides as a technology for probing protein-protein interactions (PPIs) and elucidating architectures of multisubunit assemblies. To define conformational and interaction dynamics of protein complexes under different physiological conditions, various quantitative cross-linking mass spectrometry (QXL-MS) strategies based on stable isotope labeling have been developed. These QXL-MS approaches have effectively allowed comparative analysis of cross-links to determine their relative abundance changes at global scales. Although successful, it remains challenging to consistently obtain quantitative measurements on low-abundant cross-links. Therefore, targeted QXL-MS is needed to enable MS "Western" analysis of cross-links to enhance sensitivity and reliability in quantitation. To this end, we have established a robust parallel reaction monitoring (PRM)-based targeted QXL-MS platform using sulfoxide-containing MS-cleavable cross-linker disuccinimidyl sulfoxide (DSSO), permitting label-free comparative analysis of selected cross-links across multiple samples. In addition, we have applied this methodology to study phosphorylation-dependent conformational dynamics of the human 26S proteasome. The PRM-based targeted QXL-MS analytical platform described here is applicable for all sulfoxide-containing MS-cleavable cross-linkers and can be directly adopted for comparative studies of protein-protein interactions in various cellular contexts.
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Affiliation(s)
- Clinton Yu
- Department of Physiology & Biophysics, University of California, Irvine, Medical Science I, D233, Irvine, California 92697-4560, United States
| | - Xiaorong Wang
- Department of Physiology & Biophysics, University of California, Irvine, Medical Science I, D233, Irvine, California 92697-4560, United States
| | - Lan Huang
- Department of Physiology & Biophysics, University of California, Irvine, Medical Science I, D233, Irvine, California 92697-4560, United States
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19
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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: 81] [Impact Index Per Article: 40.5] [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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20
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Trahan C, Oeffinger M. Targeted Cross-Linking Mass Spectrometry on Single-Step Affinity Purified Molecular Complexes in the Yeast Saccharomyces cerevisiae. Methods Mol Biol 2022; 2456:185-210. [PMID: 35612743 DOI: 10.1007/978-1-0716-2124-0_13] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Protein cross-linking mass spectrometry (XL-MS) has been developed into a powerful and robust tool that is now well implemented and routinely used by an increasing number of laboratories. While bulk cross-linking of complexes provides useful information on whole complexes, it is limiting for the probing of specific protein "neighbourhoods," or vicinity interactomes. For example, it is not unusual to find cross-linked peptide pairs that are disproportionately overrepresented compared to the surface areas of complexes, while very few or no cross-links are identified in other regions. When studying dynamic complexes along their pathways, some vicinity cross-links may be of too low abundance in the pool of heterogenous complexes of interest to be efficiently identified by standard XL-MS. In this chapter, we describe a targeted XL-MS approach from single-step affinity purified (ssAP) complexes that enables the investigation of specific protein "neighbourhoods" within molecular complexes in yeast, using a small cross-linker anchoring tag, the CH-tag. One advantage of this method over a general cross-linking strategy is the possibility to significantly enrich for localized anchored-cross-links within complexes, thus yielding a higher sensitivity to detect highly dynamic or low abundance protein interactions within a specific protein "neighbourhood" occurring along the pathway of a selected bait protein. Moreover, many variations of the method can be employed; the ssAP-tag and the CH-tag can either be fused to the same or different proteins in the complex, or the CH-tag can be fused to multiple protein components in the same cell line to explore dynamic vicinity interactions along a pathway.
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Affiliation(s)
- Christian Trahan
- Institut de recherches cliniques de Montréal, Montréal, QC, Canada
| | - Marlene Oeffinger
- Institut de recherches cliniques de Montréal, Montréal, QC, Canada.
- Département de biochimie, Faculté de médecine, Université de Montréal, Montréal, QC, Canada.
- Faculty of Medicine, Division of Experimental Medicine, McGill University, Montréal, QC, Canada.
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21
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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: 40] [Impact Index Per Article: 13.3] [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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22
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Vallat B, Webb B, Fayazi M, Voinea S, Tangmunarunkit H, Ganesan SJ, Lawson CL, Westbrook JD, Kesselman C, Sali A, Berman HM. New system for archiving integrative structures. Acta Crystallogr D Struct Biol 2021; 77:1486-1496. [PMID: 34866606 PMCID: PMC8647179 DOI: 10.1107/s2059798321010871] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Accepted: 10/19/2021] [Indexed: 11/30/2022] Open
Abstract
Structures of many complex biological assemblies are increasingly determined using integrative approaches, in which data from multiple experimental methods are combined. A standalone system, called PDB-Dev, has been developed for archiving integrative structures and making them publicly available. Here, the data standards and software tools that support PDB-Dev are described along with the new and updated components of the PDB-Dev data-collection, processing and archiving infrastructure. Following the FAIR (Findable, Accessible, Interoperable and Reusable) principles, PDB-Dev ensures that the results of integrative structure determinations are freely accessible to everyone.
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Affiliation(s)
- Brinda Vallat
- RCSB PDB, Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, New Jersey, USA
| | - Benjamin Webb
- Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, and California Institute for Quantitative Biosciences, University of California at San Francisco, San Francisco, California, USA
| | - Maryam Fayazi
- RCSB PDB, Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, New Jersey, USA
| | - Serban Voinea
- Information Sciences Institute, Viterbi School of Engineering, University of Southern California, Los Angeles, California, USA
| | - Hongsuda Tangmunarunkit
- Information Sciences Institute, Viterbi School of Engineering, University of Southern California, Los Angeles, California, USA
| | - Sai J. Ganesan
- Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, and California Institute for Quantitative Biosciences, University of California at San Francisco, San Francisco, California, USA
| | - Catherine L. Lawson
- RCSB PDB, Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, New Jersey, USA
| | - John D. Westbrook
- RCSB PDB, Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, New Jersey, USA
| | - Carl Kesselman
- RCSB PDB, Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, New Jersey, USA
| | - Andrej Sali
- Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, and California Institute for Quantitative Biosciences, University of California at San Francisco, San Francisco, California, USA
| | - Helen M. Berman
- Department of Chemistry and Chemical Biology and Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, New Jersey, USA
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23
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Shen Z, Xiang Y, Vergara S, Chen A, Xiao Z, Santiago U, Jin C, Sang Z, Luo J, Chen K, Schneidman-Duhovny D, Camacho C, Calero G, Hu B, Shi Y. A resource of high-quality and versatile nanobodies for drug delivery. iScience 2021; 24:103014. [PMID: 34522857 PMCID: PMC8426283 DOI: 10.1016/j.isci.2021.103014] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 06/09/2021] [Accepted: 08/18/2021] [Indexed: 01/08/2023] Open
Abstract
Therapeutic and diagnostic efficacies of small biomolecules and chemical compounds are hampered by suboptimal pharmacokinetics. Here, we developed a repertoire of robust and high-affinity antihuman serum albumin nanobodies (NbHSA) that can be readily fused to small biologics for half-life extension. We characterized the thermostability, binding kinetics, and cross-species reactivity of NbHSAs, mapped their epitopes, and structurally resolved a tetrameric HSA-Nb complex. We parallelly determined the half-lives of a cohort of selected NbHSAs in an HSA mouse model by quantitative proteomics. Compared to short-lived control nanobodies, the half-lives of NbHSAs were drastically prolonged by 771-fold. NbHSAs have distinct and diverse pharmacokinetics, positively correlating with their albumin binding affinities at the endosomal pH. We then generated stable and highly bioactive NbHSA-cytokine fusion constructs “Duraleukin” and demonstrated Duraleukin's high preclinical efficacy for cancer treatment in a melanoma model. This high-quality and versatile Nb toolkit will help tailor drug half-life to specific medical needs. We provide a resource of high-affinity and versatile albumin nanobodies for drug delivery We systematically map albumin nanobody epitopes by hybrid structural approaches We parallelly measure the pharmacokinetics of nanobodies in a humanized mouse model We develop nanobody-cytokine conjugates “Duraleukin” for cancer immunotherapy
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Affiliation(s)
- Zhuolun Shen
- Department of Cell Biology, University of Pittsburgh, Pittsburgh, PA, USA.,School of Medicine, Tsinghua University, Beijing, China
| | - Yufei Xiang
- Department of Cell Biology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Sandra Vergara
- Department of Structural Biology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Apeng Chen
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA.,Pediatric Neurosurgery, UPMC Children's Hospital of Pittsburgh, Pittsburgh, PA, USA
| | - Zhengyun Xiao
- Department of Cell Biology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ulises Santiago
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Changzhong Jin
- Department of Cell Biology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Zhe Sang
- Department of Cell Biology, University of Pittsburgh, Pittsburgh, PA, USA.,University of Pittsburgh-Carnegie Mellon University Joint Program for Computational Biology, Pittsburgh, PA, USA
| | - Jiadi Luo
- Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Kong Chen
- Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Dina Schneidman-Duhovny
- School of Computer Science and Engineering, Institute of Life Sciences, University of Jerusalem, Tambaram, Israel
| | - Carlos Camacho
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Guillermo Calero
- Department of Structural Biology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Baoli Hu
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA.,Pediatric Neurosurgery, UPMC Children's Hospital of Pittsburgh, Pittsburgh, PA, USA.,Molecular and Cellular Cancer Biology Program, UPMC Hillman Cancer Center, Pittsburgh, PA, USA
| | - Yi Shi
- Department of Cell Biology, University of Pittsburgh, Pittsburgh, PA, USA.,University of Pittsburgh-Carnegie Mellon University Joint Program for Computational Biology, Pittsburgh, PA, USA
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24
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Britt HM, Cragnolini T, Thalassinos K. Integration of Mass Spectrometry Data for Structural Biology. Chem Rev 2021; 122:7952-7986. [PMID: 34506113 DOI: 10.1021/acs.chemrev.1c00356] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Mass spectrometry (MS) is increasingly being used to probe the structure and dynamics of proteins and the complexes they form with other macromolecules. There are now several specialized MS methods, each with unique sample preparation, data acquisition, and data processing protocols. Collectively, these methods are referred to as structural MS and include cross-linking, hydrogen-deuterium exchange, hydroxyl radical footprinting, native, ion mobility, and top-down MS. Each of these provides a unique type of structural information, ranging from composition and stoichiometry through to residue level proximity and solvent accessibility. Structural MS has proved particularly beneficial in studying protein classes for which analysis by classic structural biology techniques proves challenging such as glycosylated or intrinsically disordered proteins. To capture the structural details for a particular system, especially larger multiprotein complexes, more than one structural MS method with other structural and biophysical techniques is often required. Key to integrating these diverse data are computational strategies and software solutions to facilitate this process. We provide a background to the structural MS methods and briefly summarize other structural methods and how these are combined with MS. We then describe current state of the art approaches for the integration of structural MS data for structural biology. We quantify how often these methods are used together and provide examples where such combinations have been fruitful. To illustrate the power of integrative approaches, we discuss progress in solving the structures of the proteasome and the nuclear pore complex. We also discuss how information from structural MS, particularly pertaining to protein dynamics, is not currently utilized in integrative workflows and how such information can provide a more accurate picture of the systems studied. We conclude by discussing new developments in the MS and computational fields that will further enable in-cell structural studies.
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Affiliation(s)
- Hannah M Britt
- Institute of Structural and Molecular Biology, Division of Biosciences, University College London, London WC1E 6BT, United Kingdom
| | - Tristan Cragnolini
- Institute of Structural and Molecular Biology, Division of Biosciences, University College London, London WC1E 6BT, United Kingdom.,Institute of Structural and Molecular Biology, Birkbeck College, University of London, London WC1E 7HX, United Kingdom
| | - Konstantinos Thalassinos
- Institute of Structural and Molecular Biology, Division of Biosciences, University College London, London WC1E 6BT, United Kingdom.,Institute of Structural and Molecular Biology, Birkbeck College, University of London, London WC1E 7HX, United Kingdom
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25
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Abstract
Biological mass spectrometry (MS) encompasses a range of methods for characterizing proteins and other biomolecules. MS is uniquely powerful for the structural analysis of endogenous protein complexes, which are often heterogeneous, poorly abundant, and refractive to characterization by other methods. Here, we focus on how biological MS can contribute to the study of endogenous protein complexes, which we define as complexes expressed in the physiological host and purified intact, as opposed to reconstituted complexes assembled from heterologously expressed components. Biological MS can yield information on complex stoichiometry, heterogeneity, topology, stability, activity, modes of regulation, and even structural dynamics. We begin with a review of methods for isolating endogenous complexes. We then describe the various biological MS approaches, focusing on the type of information that each method yields. We end with future directions and challenges for these MS-based methods.
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Affiliation(s)
- Rivkah Rogawski
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Michal Sharon
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot 7610001, Israel
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26
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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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27
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Evolution and diversification of the nuclear pore complex. Biochem Soc Trans 2021; 49:1601-1619. [PMID: 34282823 PMCID: PMC8421043 DOI: 10.1042/bst20200570] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Revised: 06/18/2021] [Accepted: 06/21/2021] [Indexed: 12/21/2022]
Abstract
The nuclear pore complex (NPC) is responsible for transport between the cytoplasm and nucleoplasm and one of the more intricate structures of eukaryotic cells. Typically composed of over 300 polypeptides, the NPC shares evolutionary origins with endo-membrane and intraflagellar transport system complexes. The modern NPC was fully established by the time of the last eukaryotic common ancestor and, hence, prior to eukaryote diversification. Despite the complexity, the NPC structure is surprisingly flexible with considerable variation between lineages. Here, we review diversification of the NPC in major taxa in view of recent advances in genomic and structural characterisation of plant, protist and nucleomorph NPCs and discuss the implications for NPC evolution. Furthermore, we highlight these changes in the context of mRNA export and consider how this process may have influenced NPC diversity. We reveal the NPC as a platform for continual evolution and adaptation.
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28
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Chavez JD, Wippel HH, Tang X, Keller A, Bruce JE. In-Cell Labeling and Mass Spectrometry for Systems-Level Structural Biology. Chem Rev 2021; 122:7647-7689. [PMID: 34232610 PMCID: PMC8966414 DOI: 10.1021/acs.chemrev.1c00223] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Biological systems have evolved to utilize proteins to accomplish nearly all functional roles needed to sustain life. A majority of biological functions occur within the crowded environment inside cells and subcellular compartments where proteins exist in a densely packed complex network of protein-protein interactions. The structural biology field has experienced a renaissance with recent advances in crystallography, NMR, and CryoEM that now produce stunning models of large and complex structures previously unimaginable. Nevertheless, measurements of such structural detail within cellular environments remain elusive. This review will highlight how advances in mass spectrometry, chemical labeling, and informatics capabilities are merging to provide structural insights on proteins, complexes, and networks that exist inside cells. Because of the molecular detection specificity provided by mass spectrometry and proteomics, these approaches provide systems-level information that not only benefits from conventional structural analysis, but also is highly complementary. Although far from comprehensive in their current form, these approaches are currently providing systems structural biology information that can uniquely reveal how conformations and interactions involving many proteins change inside cells with perturbations such as disease, drug treatment, or phenotypic differences. With continued advancements and more widespread adaptation, systems structural biology based on in-cell labeling and mass spectrometry will provide an even greater wealth of structural knowledge.
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Affiliation(s)
- Juan D Chavez
- Department of Genome Sciences, University of Washington, Seattle, Washington 98109, United States
| | - Helisa H Wippel
- Department of Genome Sciences, University of Washington, Seattle, Washington 98109, United States
| | - Xiaoting Tang
- Department of Genome Sciences, University of Washington, Seattle, Washington 98109, United States
| | - Andrew Keller
- Department of Genome Sciences, University of Washington, Seattle, Washington 98109, United States
| | - James E Bruce
- Department of Genome Sciences, University of Washington, Seattle, Washington 98109, United States
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29
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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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30
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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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31
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Gutierrez C, Salituro LJ, Yu C, Wang X, DePeter SF, Rychnovsky SD, Huang L. Enabling Photoactivated Cross-Linking Mass Spectrometric Analysis of Protein Complexes by Novel MS-Cleavable Cross-Linkers. Mol Cell Proteomics 2021; 20:100084. [PMID: 33915260 PMCID: PMC8214149 DOI: 10.1016/j.mcpro.2021.100084] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Revised: 04/02/2021] [Accepted: 04/21/2021] [Indexed: 12/15/2022] Open
Abstract
Cross-linking mass spectrometry (XL-MS) is a powerful tool for studying protein-protein interactions and elucidating architectures of protein complexes. While residue-specific XL-MS studies have been very successful, accessibility of interaction regions nontargetable by specific chemistries remain difficult. Photochemistry has shown great potential in capturing those regions because of nonspecific reactivity, but low yields and high complexities of photocross-linked products have hindered their identification, limiting current studies predominantly to single proteins. Here, we describe the development of three novel MS-cleavable heterobifunctional cross-linkers, namely SDASO (Succinimidyl diazirine sulfoxide), to enable fast and accurate identification of photocross-linked peptides by MSn. The MSn-based workflow allowed SDASO XL-MS analysis of the yeast 26S proteasome, demonstrating the feasibility of photocross-linking of large protein complexes for the first time. Comparative analyses have revealed that SDASO cross-linking is robust and captures interactions complementary to residue-specific reagents, providing the foundation for future applications of photocross-linking in complex XL-MS studies.
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Affiliation(s)
- Craig Gutierrez
- Department of Physiology and Biophysics, University of California, Irvine, California, USA
| | - Leah J Salituro
- Department of Chemistry, University of California, Irvine, California, USA
| | - Clinton Yu
- Department of Physiology and Biophysics, University of California, Irvine, California, USA
| | - Xiaorong Wang
- Department of Physiology and Biophysics, University of California, Irvine, California, USA
| | - Sadie F DePeter
- Department of Chemistry, University of California, Irvine, California, USA
| | - Scott D Rychnovsky
- Department of Chemistry, University of California, Irvine, California, USA
| | - Lan Huang
- Department of Physiology and Biophysics, University of California, Irvine, California, USA.
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32
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Xie Y, Clarke BP, Kim YJ, Ivey AL, Hill PS, Shi Y, Ren Y. Cryo-EM structure of the yeast TREX complex and coordination with the SR-like protein Gbp2. eLife 2021; 10:e65699. [PMID: 33787496 PMCID: PMC8043747 DOI: 10.7554/elife.65699] [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: 12/12/2020] [Accepted: 03/30/2021] [Indexed: 12/21/2022] Open
Abstract
The evolutionarily conserved TRanscript-EXport (TREX) complex plays central roles during mRNP (messenger ribonucleoprotein) maturation and export from the nucleus to the cytoplasm. In yeast, TREX is composed of the THO sub-complex (Tho2, Hpr1, Tex1, Mft1, and Thp2), the DEAD box ATPase Sub2, and Yra1. Here we present a 3.7 Å cryo-EM structure of the yeast THO•Sub2 complex. The structure reveals the intimate assembly of THO revolving around its largest subunit Tho2. THO stabilizes a semi-open conformation of the Sub2 ATPase via interactions with Tho2. We show that THO interacts with the serine-arginine (SR)-like protein Gbp2 through both the RS domain and RRM domains of Gbp2. Cross-linking mass spectrometry analysis supports the extensive interactions between THO and Gbp2, further revealing that RRM domains of Gbp2 are in close proximity to the C-terminal domain of Tho2. We propose that THO serves as a landing pad to configure Gbp2 to facilitate its loading onto mRNP.
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Affiliation(s)
- Yihu Xie
- Department of Biochemistry, Vanderbilt University School of MedicineNashvilleUnited States
| | - Bradley P Clarke
- Department of Biochemistry, Vanderbilt University School of MedicineNashvilleUnited States
| | - Yong Joon Kim
- Department of Cell Biology, University of PittsburghPittsburghUnited States
- Medical Scientist Training Program, University of Pittsburgh and Carnegie Mellon UniversityPittsburghUnited States
| | - Austin L Ivey
- Department of Biochemistry, Vanderbilt University School of MedicineNashvilleUnited States
| | - Pate S Hill
- Department of Biochemistry, Vanderbilt University School of MedicineNashvilleUnited States
| | - Yi Shi
- Department of Cell Biology, University of PittsburghPittsburghUnited States
- Medical Scientist Training Program, University of Pittsburgh and Carnegie Mellon UniversityPittsburghUnited States
| | - Yi Ren
- Department of Biochemistry, Vanderbilt University School of MedicineNashvilleUnited States
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33
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Xiang Y, Sang Z, Bitton L, Xu J, Liu Y, Schneidman-Duhovny D, Shi Y. Integrative proteomics identifies thousands of distinct, multi-epitope, and high-affinity nanobodies. Cell Syst 2021; 12:220-234.e9. [PMID: 33592195 PMCID: PMC7979497 DOI: 10.1016/j.cels.2021.01.003] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Revised: 10/13/2020] [Accepted: 01/20/2021] [Indexed: 12/15/2022]
Abstract
The antibody immune response is essential for the survival of mammals. However, we still lack a systematic understanding of the antibody repertoire. Here, we developed a proteomic strategy to survey, at an unprecedented scale, the landscape of antigen-engaged, circulating camelid heavy-chain antibodies, whose minimal binding fragments are called VHH antibodies or nanobodies. The sensitivity and robustness of this approach were validated with three antigens spanning orders of magnitude in immune responses; thousands of distinct, high-affinity nanobody families were reliably identified and quantified. Using high-throughput structural modeling, cross-linking mass spectrometry, mutagenesis, and deep learning, we mapped and analyzed the epitopes of >100,000 antigen-nanobody complexes. Our results revealed a surprising diversity of ultrahigh-affinity camelid nanobodies for specific antigen binding on various dominant epitope clusters. Nanobodies utilize both shape and charge complementarity to enable highly selective antigen binding. Interestingly, we found that nanobody-antigen binding can mimic conserved intracellular protein-protein interactions. A record of this paper's Transparent Peer Review process is included in the Supplemental information.
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Affiliation(s)
- Yufei Xiang
- Department of Cell Biology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Zhe Sang
- Department of Cell Biology, University of Pittsburgh, Pittsburgh, PA, USA; University of Pittsburgh, Carnegie Mellon University Program for Computational Biology, Pittsburgh, PA, USA
| | - Lirane Bitton
- School of Computer Science and Engineering, Institute of Life Sciences, The Hebrew University of Jerusalem, Israel
| | - Jianquan Xu
- Departments of Medicine and Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Yang Liu
- Departments of Medicine and Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Dina Schneidman-Duhovny
- School of Computer Science and Engineering, Institute of Life Sciences, The Hebrew University of Jerusalem, Israel.
| | - Yi Shi
- Department of Cell Biology, University of Pittsburgh, Pittsburgh, PA, USA; University of Pittsburgh, Carnegie Mellon University Program for Computational Biology, Pittsburgh, PA, USA.
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34
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One Ring to Rule them All? Structural and Functional Diversity in the Nuclear Pore Complex. Trends Biochem Sci 2021; 46:595-607. [PMID: 33563541 DOI: 10.1016/j.tibs.2021.01.003] [Citation(s) in RCA: 51] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2020] [Revised: 01/05/2021] [Accepted: 01/11/2021] [Indexed: 02/07/2023]
Abstract
The nuclear pore complex (NPC) is the massive protein assembly that regulates the transport of macromolecules between the nucleus and the cytoplasm. Recent breakthroughs have provided major insights into the structure of the NPC in different eukaryotes, revealing a previously unsuspected diversity of NPC architectures. In parallel, the NPC has been shown to be a key player in regulating essential nuclear processes such as chromatin organization, gene expression, and DNA repair. However, our knowledge of the NPC structure has not been able to address the molecular mechanisms underlying its regulatory roles. We discuss potential explanations, including the coexistence of alternative NPC architectures with specific functional roles.
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35
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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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36
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Richards AL, Eckhardt M, Krogan NJ. Mass spectrometry-based protein-protein interaction networks for the study of human diseases. Mol Syst Biol 2021; 17:e8792. [PMID: 33434350 PMCID: PMC7803364 DOI: 10.15252/msb.20188792] [Citation(s) in RCA: 88] [Impact Index Per Article: 29.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2019] [Revised: 09/23/2020] [Accepted: 11/03/2020] [Indexed: 12/13/2022] Open
Abstract
A better understanding of the molecular mechanisms underlying disease is key for expediting the development of novel therapeutic interventions. Disease mechanisms are often mediated by interactions between proteins. Insights into the physical rewiring of protein-protein interactions in response to mutations, pathological conditions, or pathogen infection can advance our understanding of disease etiology, progression, and pathogenesis and can lead to the identification of potential druggable targets. Advances in quantitative mass spectrometry (MS)-based approaches have allowed unbiased mapping of these disease-mediated changes in protein-protein interactions on a global scale. Here, we review MS techniques that have been instrumental for the identification of protein-protein interactions at a system-level, and we discuss the challenges associated with these methodologies as well as novel MS advancements that aim to address these challenges. An overview of examples from diverse disease contexts illustrates the potential of MS-based protein-protein interaction mapping approaches for revealing disease mechanisms, pinpointing new therapeutic targets, and eventually moving toward personalized applications.
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Affiliation(s)
- Alicia L Richards
- Quantitative Biosciences Institute (QBI)University of California San FranciscoSan FranciscoCAUSA
- J. David Gladstone InstitutesSan FranciscoCAUSA
- Department of Cellular and Molecular PharmacologyUniversity of California San FranciscoSan FranciscoCAUSA
| | - Manon Eckhardt
- Quantitative Biosciences Institute (QBI)University of California San FranciscoSan FranciscoCAUSA
- J. David Gladstone InstitutesSan FranciscoCAUSA
- Department of Cellular and Molecular PharmacologyUniversity of California San FranciscoSan FranciscoCAUSA
| | - Nevan J Krogan
- Quantitative Biosciences Institute (QBI)University of California San FranciscoSan FranciscoCAUSA
- J. David Gladstone InstitutesSan FranciscoCAUSA
- Department of Cellular and Molecular PharmacologyUniversity of California San FranciscoSan FranciscoCAUSA
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37
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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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38
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Xiang Y, Nambulli S, Xiao Z, Liu H, Sang Z, Duprex WP, Schneidman-Duhovny D, Zhang C, Shi Y. Versatile and multivalent nanobodies efficiently neutralize SARS-CoV-2. Science 2020; 370:1479-1484. [PMID: 33154108 PMCID: PMC7857400 DOI: 10.1126/science.abe4747] [Citation(s) in RCA: 250] [Impact Index Per Article: 62.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Accepted: 10/28/2020] [Indexed: 12/12/2022]
Abstract
Cost-effective, efficacious therapeutics are urgently needed to combat the COVID-19 pandemic. In this study, we used camelid immunization and proteomics to identify a large repertoire of highly potent neutralizing nanobodies (Nbs) to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein receptor binding domain (RBD). We discovered Nbs with picomolar to femtomolar affinities that inhibit viral infection at concentrations below the nanograms-per-milliliter level, and we determined a structure of one of the most potent Nbs in complex with the RBD. Structural proteomics and integrative modeling revealed multiple distinct and nonoverlapping epitopes and indicated an array of potential neutralization mechanisms. We bioengineered multivalent Nb constructs that achieved ultrahigh neutralization potency (half-maximal inhibitory concentration as low as 0.058 ng/ml) and may prevent mutational escape. These thermostable Nbs can be rapidly produced in bulk from microbes and resist lyophilization and aerosolization.
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MESH Headings
- Angiotensin-Converting Enzyme 2/chemistry
- Angiotensin-Converting Enzyme 2/genetics
- Angiotensin-Converting Enzyme 2/immunology
- Animals
- Antibodies, Neutralizing/chemistry
- Antibodies, Neutralizing/genetics
- Antibodies, Neutralizing/immunology
- Antibodies, Viral/chemistry
- Antibodies, Viral/genetics
- Antibodies, Viral/immunology
- Antibody Affinity
- COVID-19/therapy
- Camelids, New World
- Escherichia coli
- Humans
- Neutralization Tests
- Protein Binding
- Protein Domains
- Receptors, Virus/chemistry
- Receptors, Virus/genetics
- Receptors, Virus/immunology
- Recombinant Proteins/chemistry
- Recombinant Proteins/genetics
- Recombinant Proteins/immunology
- SARS-CoV-2/immunology
- Single-Domain Antibodies/chemistry
- Single-Domain Antibodies/genetics
- Single-Domain Antibodies/immunology
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Affiliation(s)
- Yufei Xiang
- Department of Cell Biology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Sham Nambulli
- Center for Vaccine Research, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Microbiology and Molecular Genetics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Zhengyun Xiao
- Department of Cell Biology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Heng Liu
- Department of Pharmacology and Chemical Biology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Zhe Sang
- Department of Cell Biology, University of Pittsburgh, Pittsburgh, PA, USA
- University of Pittsburgh-Carnegie Mellon University Program in Computational Biology, Pittsburgh, PA, USA
| | - W Paul Duprex
- Center for Vaccine Research, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Microbiology and Molecular Genetics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Dina Schneidman-Duhovny
- School of Computer Science and Engineering, Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel.
| | - Cheng Zhang
- Department of Pharmacology and Chemical Biology, University of Pittsburgh, Pittsburgh, PA, USA.
| | - Yi Shi
- Department of Cell Biology, University of Pittsburgh, Pittsburgh, PA, USA.
- University of Pittsburgh-Carnegie Mellon University Program in Computational Biology, Pittsburgh, PA, USA
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39
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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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40
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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: 151] [Impact Index Per Article: 37.8] [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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41
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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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42
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Xiang Y, Nambulli S, Xiao Z, Liu H, Sang Z, Duprex WP, Schneidman-Duhovny D, Zhang C, Shi Y. Versatile, Multivalent Nanobody Cocktails Efficiently Neutralize SARS-CoV-2. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2020. [PMID: 32869034 PMCID: PMC7457627 DOI: 10.1101/2020.08.24.264333] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
The outbreak of COVID-19 has severely impacted global health and the economy. Cost-effective, highly efficacious therapeutics are urgently needed. Here, we used camelid immunization and proteomics to identify a large repertoire of highly potent neutralizing nanobodies (Nbs) to the SARS-CoV-2 spike (S) protein receptor-binding domain (RBD). We discovered multiple elite Nbs with picomolar to femtomolar affinities that inhibit viral infection at sub-ng/ml concentration, more potent than some of the best human neutralizing antibodies. We determined a crystal structure of such an elite neutralizing Nb in complex with RBD. Structural proteomics and integrative modeling revealed multiple distinct and non-overlapping epitopes and indicated an array of potential neutralization mechanisms. Structural characterization facilitated the bioengineering of novel multivalent Nb constructs into multi-epitope cocktails that achieved ultrahigh neutralization potency (IC50s as low as 0.058 ng/ml) and may prevent mutational escape. These thermostable Nbs can be rapidly produced in bulk from microbes and resist lyophilization, and aerosolization. These promising agents are readily translated into efficient, cost-effective, and convenient therapeutics to help end this once-in-a-century health crisis.
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Affiliation(s)
| | - Sham Nambulli
- Center for Vaccine Research.,Department of Microbiology and Molecular Genetics School of Medicine
| | | | - Heng Liu
- Department of Pharmacology and Chemical Biology University of Pittsburgh, Pittsburgh, PA, USA
| | - Zhe Sang
- Department of Cell Biology.,Pitt/CMU Program for Computational Biology
| | - W Paul Duprex
- Center for Vaccine Research.,Department of Microbiology and Molecular Genetics School of Medicine
| | - Dina Schneidman-Duhovny
- School of Computer Science and Engineering, Institute of Life Sciences, The Hebrew University of Jerusalem, Israel
| | - Cheng Zhang
- Department of Pharmacology and Chemical Biology University of Pittsburgh, Pittsburgh, PA, USA
| | - Yi Shi
- Department of Cell Biology.,Pitt/CMU Program for Computational Biology
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43
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Schnirch L, Nadler-Holly M, Siao SW, Frese CK, Viner R, Liu F. Expanding the Depth and Sensitivity of Cross-Link Identification by Differential Ion Mobility Using High-Field Asymmetric Waveform Ion Mobility Spectrometry. Anal Chem 2020; 92:10495-10503. [PMID: 32643919 DOI: 10.1021/acs.analchem.0c01273] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
In cross-linking mass spectrometry (XL-MS), the depth and sensitivity of cross-link detection is often limited by the low abundance of cross-links compared to non-cross-linked peptides in the digestion mixture. To improve the identification efficiency of cross-links, here, we present a gas-phase separation strategy using high-field asymmetric waveform ion mobility spectrometry (FAIMS) coupled to the Orbitrap Tribrid mass spectrometers. By enabling an additional peptide separation step in the gas phase using the FAIMS device, we increase the number of cross-link identifications by 22% for a medium complex sample and 59% for strong cation exchange-fractionated HEK293T cell lysate in XL-MS experiments using disuccinimidyl sulfoxide (DSSO) cross-linker. When disuccinimidyl suberate (DSS) cross-linker is in use, we are able to boost cross-link identification by 89% for the medium and 100% for the high complex sample compared to the analyses without FAIMS. Furthermore, we show that, for medium complex samples, FAIMS enables the collection of single-shot XL-MS data with a comparable depth to the corresponding sample fractionated by chromatography-based approaches. Altogether, we demonstrate FAIMS is highly beneficial for XL-MS studies by expanding the proteome coverage of cross-links while improving the efficiency and confidence of cross-link identification.
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Affiliation(s)
- Lennart Schnirch
- Department of Chemical Biology, Leibniz-Forschungsinstitut für Molekulare Pharmakologie (FMP), Robert-Roessle-Str. 10, 13125 Berlin, Germany
| | - Michal Nadler-Holly
- Department of Chemical Biology, Leibniz-Forschungsinstitut für Molekulare Pharmakologie (FMP), Robert-Roessle-Str. 10, 13125 Berlin, Germany
| | - Siang-Wun Siao
- Department of Chemical Biology, Leibniz-Forschungsinstitut für Molekulare Pharmakologie (FMP), Robert-Roessle-Str. 10, 13125 Berlin, Germany.,Max Planck Unit for the Science of Pathogens, Charitéplatz 1, 10117 Berlin, Germany
| | - Christian K Frese
- Max Planck Unit for the Science of Pathogens, Charitéplatz 1, 10117 Berlin, Germany
| | - Rosa Viner
- Thermo Fisher Scientific, 355 River Oaks Pkwy., San Jose, California 95134, United States
| | - Fan Liu
- Department of Chemical Biology, Leibniz-Forschungsinstitut für Molekulare Pharmakologie (FMP), Robert-Roessle-Str. 10, 13125 Berlin, Germany
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44
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Liu XR, Zhang MM, Gross ML. Mass Spectrometry-Based Protein Footprinting for Higher-Order Structure Analysis: Fundamentals and Applications. Chem Rev 2020; 120:4355-4454. [PMID: 32319757 PMCID: PMC7531764 DOI: 10.1021/acs.chemrev.9b00815] [Citation(s) in RCA: 130] [Impact Index Per Article: 32.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Proteins adopt different higher-order structures (HOS) to enable their unique biological functions. Understanding the complexities of protein higher-order structures and dynamics requires integrated approaches, where mass spectrometry (MS) is now positioned to play a key role. One of those approaches is protein footprinting. Although the initial demonstration of footprinting was for the HOS determination of protein/nucleic acid binding, the concept was later adapted to MS-based protein HOS analysis, through which different covalent labeling approaches "mark" the solvent accessible surface area (SASA) of proteins to reflect protein HOS. Hydrogen-deuterium exchange (HDX), where deuterium in D2O replaces hydrogen of the backbone amides, is the most common example of footprinting. Its advantage is that the footprint reflects SASA and hydrogen bonding, whereas one drawback is the labeling is reversible. Another example of footprinting is slow irreversible labeling of functional groups on amino acid side chains by targeted reagents with high specificity, probing structural changes at selected sites. A third footprinting approach is by reactions with fast, irreversible labeling species that are highly reactive and footprint broadly several amino acid residue side chains on the time scale of submilliseconds. All of these covalent labeling approaches combine to constitute a problem-solving toolbox that enables mass spectrometry as a valuable tool for HOS elucidation. As there has been a growing need for MS-based protein footprinting in both academia and industry owing to its high throughput capability, prompt availability, and high spatial resolution, we present a summary of the history, descriptions, principles, mechanisms, and applications of these covalent labeling approaches. Moreover, their applications are highlighted according to the biological questions they can answer. This review is intended as a tutorial for MS-based protein HOS elucidation and as a reference for investigators seeking a MS-based tool to address structural questions in protein science.
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Affiliation(s)
| | | | - Michael L. Gross
- Department of Chemistry, Washington University in St. Louis, St. Louis, MO, USA, 63130
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45
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McCafferty CL, Verbeke EJ, Marcotte EM, Taylor DW. Structural Biology in the Multi-Omics Era. J Chem Inf Model 2020; 60:2424-2429. [PMID: 32129623 PMCID: PMC7254829 DOI: 10.1021/acs.jcim.9b01164] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Indexed: 12/12/2022]
Abstract
Rapid developments in cryogenic electron microscopy have opened new avenues to probe the structures of protein assemblies in their near native states. Recent studies have begun applying single -particle analysis to heterogeneous mixtures, revealing the potential of structural-omics approaches that combine the power of mass spectrometry and electron microscopy. Here we highlight advances and challenges in sample preparation, data processing, and molecular modeling for handling increasingly complex mixtures. Such advances will help structural-omics methods extend to cellular-level models of structural biology.
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Affiliation(s)
- Caitlyn L. McCafferty
- Department
of Molecular Biosciences, University of
Texas at Austin, Austin, Texas 78712, United States
| | - Eric J. Verbeke
- Department
of Molecular Biosciences, University of
Texas at Austin, Austin, Texas 78712, United States
| | - Edward M. Marcotte
- Department
of Molecular Biosciences, University of
Texas at Austin, Austin, Texas 78712, United States
- Institute
for Cellular and Molecular Biology, University
of Texas at Austin, Austin, Texas 78712, United States
- Center
for Systems and Synthetic Biology, University
of Texas at Austin, Austin, Texas 78712, United States
| | - David W. Taylor
- Department
of Molecular Biosciences, University of
Texas at Austin, Austin, Texas 78712, United States
- Institute
for Cellular and Molecular Biology, University
of Texas at Austin, Austin, Texas 78712, United States
- Center
for Systems and Synthetic Biology, University
of Texas at Austin, Austin, Texas 78712, United States
- LIVESTRONG
Cancer Institutes, Dell Medical School, Austin, Texas 78712, United States
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46
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Roel-Touris J, Bonvin AM. Coarse-grained (hybrid) integrative modeling of biomolecular interactions. Comput Struct Biotechnol J 2020; 18:1182-1190. [PMID: 32514329 PMCID: PMC7264466 DOI: 10.1016/j.csbj.2020.05.002] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Revised: 04/23/2020] [Accepted: 05/06/2020] [Indexed: 12/23/2022] Open
Abstract
The computational modeling field has vastly evolved over the past decades. The early developments of simplified protein systems represented a stepping stone towards establishing more efficient approaches to sample intricated conformational landscapes. Downscaling the level of resolution of biomolecules to coarser representations allows for studying protein structure, dynamics and interactions that are not accessible by classical atomistic approaches. The combination of different resolutions, namely hybrid modeling, has also been proved as an alternative when mixed levels of details are required. In this review, we provide an overview of coarse-grained/hybrid models focusing on their applicability in the modeling of biomolecular interactions. We give a detailed list of ready-to-use modeling software for studying biomolecular interactions allowing various levels of coarse-graining and provide examples of complexes determined by integrative coarse-grained/hybrid approaches in combination with experimental information.
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47
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Yu C, Novitsky EJ, Cheng NW, Rychnovsky SD, Huang L. Exploring Spacer Arm Structures for Designs of Asymmetric Sulfoxide-Containing MS-Cleavable Cross-Linkers. Anal Chem 2020; 92:6026-6033. [PMID: 32202417 PMCID: PMC7363200 DOI: 10.1021/acs.analchem.0c00298] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Cross-linking mass spectrometry (XL-MS) has become a powerful structural tool for defining protein-protein interactions (PPIs) and elucidating architectures of large protein assemblies. To advance XL-MS studies, we have previously developed a series of sulfoxide-containing MS-cleavable cross-linkers to facilitate the detection and identification of cross-linked peptides using multistage mass spectrometry (MSn). While current sulfoxide-based cross-linkers are effective for in vivo and in vitro XL-MS studies at the systems-level, new reagents are still needed to help expand PPI coverage. To this end, we have designed and synthesized six variable-length derivatives of disuccinimidyl sulfoxide (DSSO) to better understand the effects of spacer arm modulation on MS-cleavability, fragmentation characteristics, and MS identification of cross-linked peptides. In addition, the impact on cross-linking reactivity was evaluated. Moreover, alternative MS2-based workflows were explored to determine their feasibility for analyzing new sulfoxide-containing cross-linked products. Based on the results of synthetic peptides and a model protein, we have further demonstrated the robustness and predictability of sulfoxide chemistry in designing MS-cleavable cross-linkers. Importantly, we have identified a unique asymmetric design that exhibits preferential fragmentation of cross-links over peptide backbones, a desired feature for MSn analysis. This work has established a solid foundation for further development of sulfoxide-containing MS-cleavable cross-linkers with new functionalities.
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Affiliation(s)
- Clinton Yu
- Department of Physiology and Biophysics, University of California, Irvine, CA 92697
| | - Eric J. Novitsky
- Department of Chemistry, University of California, Irvine, CA 92697
| | - Nicholas W. Cheng
- Department of Physiology and Biophysics, University of California, Irvine, CA 92697
| | | | - Lan Huang
- Department of Physiology and Biophysics, University of California, Irvine, CA 92697
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48
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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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49
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How paired PSII-LHCII supercomplexes mediate the stacking of plant thylakoid membranes unveiled by structural mass-spectrometry. Nat Commun 2020; 11:1361. [PMID: 32170184 PMCID: PMC7069969 DOI: 10.1038/s41467-020-15184-1] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2019] [Accepted: 02/18/2020] [Indexed: 01/17/2023] Open
Abstract
Grana are a characteristic feature of higher plants’ thylakoid membranes, consisting of stacks of appressed membranes enriched in Photosystem II (PSII) and associated light-harvesting complex II (LHCII) proteins, together forming the PSII-LHCII supercomplex. Grana stacks undergo light-dependent structural changes, mainly by reorganizing the supramolecular structure of PSII-LHCII supercomplexes. LHCII is vital for grana formation, in which also PSII-LHCII supercomplexes are involved. By combining top-down and crosslinking mass spectrometry we uncover the spatial organization of paired PSII-LHCII supercomplexes within thylakoid membranes. The resulting model highlights a basic molecular mechanism whereby plants maintain grana stacking at changing light conditions. This mechanism relies on interactions between stroma-exposed N-terminal loops of LHCII trimers and Lhcb4 subunits facing each other in adjacent membranes. The combination of light-dependent LHCII N-terminal trimming and extensive N-terminal α-acetylation likely affects interactions between pairs of PSII-LHCII supercomplexes across the stromal gap, ultimately mediating membrane folding in grana stacks. The supramolecular organization of PSII-LHCII supercomplexes determines the plant thylakoid structure. Here, via structural mass spectrometry, Albanese et al. show how stroma-exposed N-termini of LHCII subunits, interacting with each other in adjacent membranes, can mediate membrane folding in grana stacks.
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50
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Joachimiak E, Waclawek E, Niziolek M, Osinka A, Fabczak H, Gaertig J, Wloga D. The LisH Domain-Containing N-Terminal Fragment is Important for the Localization, Dimerization, and Stability of Katnal2 in Tetrahymena. Cells 2020; 9:cells9020292. [PMID: 31991798 PMCID: PMC7072489 DOI: 10.3390/cells9020292] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Revised: 01/14/2020] [Accepted: 01/22/2020] [Indexed: 12/12/2022] Open
Abstract
Katanin-like 2 protein (Katnal2) orthologs have a tripartite domain organization. Two highly conserved regions, an N-terminal LisH (Lis-homology) domain and a C-terminal AAA catalytic domain, are separated by a less conserved linker. The AAA domain of Katnal2 shares the highest amino acid sequence homology with the AAA domain of the canonical katanin p60. Katnal2 orthologs are present in a wide range of eukaryotes, from protists to humans. In the ciliate Tetrahymena thermophila, a Katnal2 ortholog, Kat2, co-localizes with the microtubular structures, including basal bodies and ciliary outer doublets, and this co-localization is sensitive to levels of microtubule glutamylation. The functional analysis of Kat2 domains suggests that an N-terminal fragment containing a LisH domain plays a role in the subcellular localization, dimerization, and stability of Kat2.
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Affiliation(s)
- Ewa Joachimiak
- Laboratory of Cytoskeleton and Cilia Biology, Nencki Institute of Experimental Biology PAS, 3 Pasteur, 02-093 Warsaw, Poland; (E.J.); (E.W.); (M.N.); (A.O.); (H.F.)
| | - Ewa Waclawek
- Laboratory of Cytoskeleton and Cilia Biology, Nencki Institute of Experimental Biology PAS, 3 Pasteur, 02-093 Warsaw, Poland; (E.J.); (E.W.); (M.N.); (A.O.); (H.F.)
| | - Michal Niziolek
- Laboratory of Cytoskeleton and Cilia Biology, Nencki Institute of Experimental Biology PAS, 3 Pasteur, 02-093 Warsaw, Poland; (E.J.); (E.W.); (M.N.); (A.O.); (H.F.)
| | - Anna Osinka
- Laboratory of Cytoskeleton and Cilia Biology, Nencki Institute of Experimental Biology PAS, 3 Pasteur, 02-093 Warsaw, Poland; (E.J.); (E.W.); (M.N.); (A.O.); (H.F.)
| | - Hanna Fabczak
- Laboratory of Cytoskeleton and Cilia Biology, Nencki Institute of Experimental Biology PAS, 3 Pasteur, 02-093 Warsaw, Poland; (E.J.); (E.W.); (M.N.); (A.O.); (H.F.)
| | - Jacek Gaertig
- Department of Cellular Biology, University of Georgia, Athens, GA 30602, USA;
| | - Dorota Wloga
- Laboratory of Cytoskeleton and Cilia Biology, Nencki Institute of Experimental Biology PAS, 3 Pasteur, 02-093 Warsaw, Poland; (E.J.); (E.W.); (M.N.); (A.O.); (H.F.)
- Correspondence: ; Tel.: +48-(22)-5892338
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