1
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Riechmann C, Zhang P. Recent structural advances in bacterial chemotaxis signalling. Curr Opin Struct Biol 2023; 79:102565. [PMID: 36868078 PMCID: PMC10460253 DOI: 10.1016/j.sbi.2023.102565] [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: 10/16/2022] [Revised: 01/25/2023] [Accepted: 01/28/2023] [Indexed: 03/05/2023]
Abstract
Bacterial chemosensory arrays have served as a model system for in-situ structure determination, clearly cataloguing the improvement of cryo-electron tomography (cryoET) over the past decade. In recent years, this has culminated in an accurately fitted atomistic model for the full-length core signalling unit (CSU) and numerous insights into the function of the transmembrane receptors responsible for signal transduction. Here, we review the achievements of the latest structural advances in bacterial chemosensory arrays and the developments which have made such advances possible.
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Affiliation(s)
- Carlos Riechmann
- Division of Structural Biology, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
| | - Peijun Zhang
- Division of Structural Biology, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK; Diamond Light Source, Harwell Science and Innovation Campus, Didcot, OX11 0DE, UK; Chinese Academy of Medical Sciences Oxford Institute, University of Oxford, Oxford, OX3 7BN, UK.
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2
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Melo MCR, Bernardi RC. Fostering discoveries in the era of exascale computing: How the next generation of supercomputers empowers computational and experimental biophysics alike. Biophys J 2023:S0006-3495(23)00091-7. [PMID: 36738105 PMCID: PMC10398237 DOI: 10.1016/j.bpj.2023.01.042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 01/24/2023] [Accepted: 01/30/2023] [Indexed: 02/05/2023] Open
Abstract
Over a century ago, physicists started broadly relying on theoretical models to guide new experiments. Soon thereafter, chemists began doing the same. Now, biological research enters a new era when experiment and theory walk hand in hand. Novel software and specialized hardware became essential to understand experimental data and propose new models. In fact, current petascale computing resources already allow researchers to reach unprecedented levels of simulation throughput to connect in silico and in vitro experiments. The reduction in cost and improved access allowed a large number of research groups to adopt supercomputing resources and techniques. Here, we outline how large-scale computing has evolved to expand decades-old research, spark new research efforts, and continuously connect simulation and observation. For instance, multiple publicly and privately funded groups have dedicated extensive resources to develop artificial intelligence tools for computational biophysics, from accelerating quantum chemistry calculations to proposing protein structure models. Moreover, advances in computer hardware have accelerated data processing from single-molecule experimental observations and simulations of chemical reactions occurring throughout entire cells. The combination of software and hardware has opened the way for exascale computing and the production of the first public exascale supercomputer, Frontier, inaugurated by the Oak Ridge National Laboratory in 2022. Ultimately, the popularization and development of computational techniques and the training of researchers to use them will only accelerate the diversification of tools and learning resources for future generations.
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Affiliation(s)
- Marcelo C R Melo
- Auburn University, Department of Physics, Auburn University, Auburn, Alabama
| | - Rafael C Bernardi
- Auburn University, Department of Physics, Auburn University, Auburn, Alabama.
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3
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Träger S, Tamò G, Aydin D, Fonti G, Audagnotto M, Dal Peraro M. CLoNe: automated clustering based on local density neighborhoods for application to biomolecular structural ensembles. Bioinformatics 2021; 37:921-928. [PMID: 32821900 PMCID: PMC8128458 DOI: 10.1093/bioinformatics/btaa742] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Revised: 07/14/2020] [Accepted: 08/18/2020] [Indexed: 11/14/2022] Open
Abstract
Motivation Proteins are intrinsically dynamic entities. Flexibility sampling methods, such as molecular dynamics or those arising from integrative modeling strategies, are now commonplace and enable the study of molecular conformational landscapes in many contexts. Resulting structural ensembles increase in size as technological and algorithmic advancements take place, making their analysis increasingly demanding. In this regard, cluster analysis remains a go-to approach for their classification. However, many state-of-the-art algorithms are restricted to specific cluster properties. Combined with tedious parameter fine-tuning, cluster analysis of protein structural ensembles suffers from the lack of a generally applicable and easy to use clustering scheme. Results We present CLoNe, an original Python-based clustering scheme that builds on the Density Peaks algorithm of Rodriguez and Laio. CLoNe relies on a probabilistic analysis of local density distributions derived from nearest neighbors to find relevant clusters regardless of cluster shape, size, distribution and amount. We show its capabilities on many toy datasets with properties otherwise dividing state-of-the-art approaches and improves on the original algorithm in key aspects. Applied to structural ensembles, CLoNe was able to extract meaningful conformations from membrane binding events and ligand-binding pocket opening as well as identify dominant dimerization motifs or inter-domain organization. CLoNe additionally saves clusters as individual trajectories for further analysis and provides scripts for automated use with molecular visualization software. Availability and implementation www.epfl.ch/labs/lbm/resources, github.com/LBM-EPFL/CLoNe. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Sylvain Träger
- Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne 1025, Switzerland.,Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
| | - Giorgio Tamò
- Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne 1025, Switzerland.,Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
| | - Deniz Aydin
- Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne 1025, Switzerland.,Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
| | - Giulia Fonti
- Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne 1025, Switzerland.,Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
| | - Martina Audagnotto
- Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne 1025, Switzerland.,Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
| | - Matteo Dal Peraro
- Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne 1025, Switzerland.,Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
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4
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Matsunaga Y, Sugita Y. Use of single-molecule time-series data for refining conformational dynamics in molecular simulations. Curr Opin Struct Biol 2020; 61:153-159. [DOI: 10.1016/j.sbi.2019.12.022] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Revised: 12/24/2019] [Accepted: 12/27/2019] [Indexed: 12/18/2022]
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5
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Fraser JS, Lindorff-Larsen K, Bonomi M. What Will Computational Modeling Approaches Have to Say in the Era of Atomistic Cryo-EM Data? J Chem Inf Model 2020; 60:2410-2412. [PMID: 32090567 DOI: 10.1021/acs.jcim.0c00123] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Affiliation(s)
- James S Fraser
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, California 94107, United States
| | - Kresten Lindorff-Larsen
- Structural Biology and NMR Laboratory, Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, DK-2200 Copenhagen, Denmark
| | - Massimiliano Bonomi
- Structural Bioinformatics Unit, Department of Structural Biology and Chemistry; CNRS UMR 3528; C3BI, CNRS USR 3756; Institut Pasteur, 75015 Paris, France
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6
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Martínez M, Jiménez-Moreno A, Maluenda D, Ramírez-Aportela E, Melero R, Cuervo A, Conesa P, Del Caño L, Fonseca YC, Sánchez-García R, Strelak D, Conesa JJ, Fernández-Giménez E, de Isidro F, Sorzano COS, Carazo JM, Marabini R. Integration of Cryo-EM Model Building Software in Scipion. J Chem Inf Model 2020; 60:2533-2540. [PMID: 31994878 DOI: 10.1021/acs.jcim.9b01032] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Advances in cryo-electron microscopy (cryo-EM) have made it possible to obtain structures of large biological macromolecules at near-atomic resolution. This "resolution revolution" has encouraged the use and development of modeling tools able to produce high-quality atomic models from cryo-EM density maps. Unfortunately, many practical problems appear when combining different packages in the same processing workflow, which make difficult the use of these tools by non-experts and, therefore, reduce their utility. We present here a major extension of the image processing framework Scipion that provides inter-package integration in the model building area and full tracking of the complete workflow, from image processing to structure validation.
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Affiliation(s)
- M Martínez
- CNB-CSIC, C/Darwin 3, 28049 Madrid, Spain
| | | | - D Maluenda
- CNB-CSIC, C/Darwin 3, 28049 Madrid, Spain
| | | | - R Melero
- CNB-CSIC, C/Darwin 3, 28049 Madrid, Spain
| | - A Cuervo
- CNB-CSIC, C/Darwin 3, 28049 Madrid, Spain
| | - P Conesa
- CNB-CSIC, C/Darwin 3, 28049 Madrid, Spain
| | - L Del Caño
- CNB-CSIC, C/Darwin 3, 28049 Madrid, Spain
| | | | | | - D Strelak
- CNB-CSIC, C/Darwin 3, 28049 Madrid, Spain.,Institute of Computer Science, Masaryk University, Botanická 68a, 60200 Brno, Czech Republic
| | - J J Conesa
- CNB-CSIC, C/Darwin 3, 28049 Madrid, Spain
| | | | | | | | - J M Carazo
- CNB-CSIC, C/Darwin 3, 28049 Madrid, Spain
| | - R Marabini
- Escuela Politécnica, Universidad Autónoma de Madrid, C/Francisco Tomás y Valiente 11, 28049 Madrid, Spain
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7
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Burt A, Cassidy CK, Ames P, Bacia-Verloop M, Baulard M, Huard K, Luthey-Schulten Z, Desfosses A, Stansfeld PJ, Margolin W, Parkinson JS, Gutsche I. Complete structure of the chemosensory array core signalling unit in an E. coli minicell strain. Nat Commun 2020; 11:743. [PMID: 32029744 PMCID: PMC7005262 DOI: 10.1038/s41467-020-14350-9] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2019] [Accepted: 12/21/2019] [Indexed: 12/01/2022] Open
Abstract
Motile bacteria sense chemical gradients with transmembrane receptors organised in supramolecular signalling arrays. Understanding stimulus detection and transmission at the molecular level requires precise structural characterisation of the array building block known as a core signalling unit. Here we introduce an Escherichia coli strain that forms small minicells possessing extended and highly ordered chemosensory arrays. We use cryo-electron tomography and subtomogram averaging to provide a three-dimensional map of a complete core signalling unit, with visible densities corresponding to the HAMP and periplasmic domains. This map, combined with previously determined high resolution structures and molecular dynamics simulations, yields a molecular model of the transmembrane core signalling unit and enables spatial localisation of its individual domains. Our work thus offers a solid structural basis for the interpretation of a wide range of existing data and the design of further experiments to elucidate signalling mechanisms within the core signalling unit and larger array.
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Affiliation(s)
- Alister Burt
- Institut de Biologie Structurale, Université Grenoble Alpes, CEA, CNRS, IBS, 71 Avenue des martyrs, F-38044, Grenoble, France
| | - C Keith Cassidy
- Department of Biochemistry, University of Oxford, South Parks Road, Oxford, OX1 3QU, UK
| | - Peter Ames
- School of Biological Sciences, University of Utah, Salt Lake City, UT, 84112, USA
| | - Maria Bacia-Verloop
- Institut de Biologie Structurale, Université Grenoble Alpes, CEA, CNRS, IBS, 71 Avenue des martyrs, F-38044, Grenoble, France
| | - Megghane Baulard
- Institut de Biologie Structurale, Université Grenoble Alpes, CEA, CNRS, IBS, 71 Avenue des martyrs, F-38044, Grenoble, France
| | - Karine Huard
- Institut de Biologie Structurale, Université Grenoble Alpes, CEA, CNRS, IBS, 71 Avenue des martyrs, F-38044, Grenoble, France
| | - Zaida Luthey-Schulten
- Department of Chemistry, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Ambroise Desfosses
- Institut de Biologie Structurale, Université Grenoble Alpes, CEA, CNRS, IBS, 71 Avenue des martyrs, F-38044, Grenoble, France
| | - Phillip J Stansfeld
- Department of Biochemistry, University of Oxford, South Parks Road, Oxford, OX1 3QU, UK
| | - William Margolin
- Department of Microbiology & Molecular Genetics, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - John S Parkinson
- School of Biological Sciences, University of Utah, Salt Lake City, UT, 84112, USA
| | - Irina Gutsche
- Institut de Biologie Structurale, Université Grenoble Alpes, CEA, CNRS, IBS, 71 Avenue des martyrs, F-38044, Grenoble, France.
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8
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Cassidy CK, Himes BA, Sun D, Ma J, Zhao G, Parkinson JS, Stansfeld PJ, Luthey-Schulten Z, Zhang P. Structure and dynamics of the E. coli chemotaxis core signaling complex by cryo-electron tomography and molecular simulations. Commun Biol 2020; 3:24. [PMID: 31925330 PMCID: PMC6954272 DOI: 10.1038/s42003-019-0748-0] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2019] [Accepted: 12/19/2019] [Indexed: 01/08/2023] Open
Abstract
To enable the processing of chemical gradients, chemotactic bacteria possess large arrays of transmembrane chemoreceptors, the histidine kinase CheA, and the adaptor protein CheW, organized as coupled core-signaling units (CSU). Despite decades of study, important questions surrounding the molecular mechanisms of sensory signal transduction remain unresolved, owing especially to the lack of a high-resolution CSU structure. Here, we use cryo-electron tomography and sub-tomogram averaging to determine a structure of the Escherichia coli CSU at sub-nanometer resolution. Based on our experimental data, we use molecular simulations to construct an atomistic model of the CSU, enabling a detailed characterization of CheA conformational dynamics in its native structural context. We identify multiple, distinct conformations of the critical P4 domain as well as asymmetries in the localization of the P3 bundle, offering several novel insights into the CheA signaling mechanism.
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Affiliation(s)
- C Keith Cassidy
- Department of Biochemistry, University of Oxford, Oxford, OX1 3QU, UK.
- Department of Physics and Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA.
| | - Benjamin A Himes
- Department of Structural Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15260, USA
| | - Dapeng Sun
- Department of Structural Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15260, USA
| | - Jun Ma
- Department of Structural Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15260, USA
| | - Gongpu Zhao
- Department of Structural Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15260, USA
| | - John S Parkinson
- School of Biological Sciences, University of Utah, Salt Lake City, UT, 84112, USA
| | - Phillip J Stansfeld
- Department of Biochemistry, University of Oxford, Oxford, OX1 3QU, UK
- School of Life Sciences & Department of Chemistry, University of Warwick, Coventry, CV4 7AL, UK
| | - Zaida Luthey-Schulten
- Department of Physics and Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
- Department of Chemistry and Center for the Physics of Living Cells, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Peijun Zhang
- Department of Structural Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15260, USA.
- Division of Structural Biology, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK.
- Electron Bio-Imaging Centre, Diamond Light Sources, Harwell Science and Innovation Campus, Didcot, OX11 0DE, UK.
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9
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Yang W, Briegel A. Diversity of Bacterial Chemosensory Arrays. Trends Microbiol 2019; 28:68-80. [PMID: 31473052 DOI: 10.1016/j.tim.2019.08.002] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2019] [Revised: 07/15/2019] [Accepted: 08/01/2019] [Indexed: 02/01/2023]
Abstract
Chemotaxis is crucial for the survival of bacteria, and the signaling systems associated with it exhibit a high level of evolutionary conservation. The architecture of the chemosensory array and the signal transduction mechanisms have been extensively studied in Escherichia coli. More recent studies have revealed a vast diversity of the chemosensory system among bacteria. Unlike E. coli, some bacteria assemble more than one chemosensory array and respond to a broader spectrum of environmental and internal stimuli. These chemosensory arrays exhibit a great variability in terms of protein composition, cellular localization, and functional variability. Here, we present recent findings that emphasize the extent of diversity in chemosensory arrays and highlight the importance of studying chemosensory arrays in bacteria other than the common model organisms.
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Affiliation(s)
- Wen Yang
- Institute of Biology, Leiden University, Leiden, The Netherlands
| | - Ariane Briegel
- Institute of Biology, Leiden University, Leiden, The Netherlands.
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10
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Advances in cryo-electron tomography and subtomogram averaging and classification. Curr Opin Struct Biol 2019; 58:249-258. [PMID: 31280905 PMCID: PMC6863431 DOI: 10.1016/j.sbi.2019.05.021] [Citation(s) in RCA: 53] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2018] [Revised: 05/24/2019] [Accepted: 05/24/2019] [Indexed: 11/20/2022]
Abstract
Cryo-electron tomography (cryoET) subtomogram averaging has emerged as a structural biology method for sparse and heterogenerous sampls. CryoET subtomogram averaging enables in situ structure determination. CryoET subtomogram classification can delineate different conformational states of macromolecular complexes. Future developments in cryoET and correlative super resolution microscopy promises to bring unprecedented integration of cell biology and structural biology.
Cryo-electron tomography (cryoET) can provide 3D reconstructions, or tomograms, of pleomorphic objects such as organelles or cells in their close-to-native states. Subtomograms that contain repetitive structures can be further extracted and subjected to averaging and classification to improve resolution, and this process has become an emerging structural biology method referred to as cryoET subtomogram averaging and classification (cryoSTAC). Recent technical advances in cryoSTAC have had a profound impact on many fields in biology. Here, I review recent exciting work on several macromolecular assemblies demonstrating the power of cryoSTAC for in situ structure analysis and discuss challenges and future directions.
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11
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Yang W, Cassidy CK, Ames P, Diebolder CA, Schulten K, Luthey-Schulten Z, Parkinson JS, Briegel A. In Situ Conformational Changes of the Escherichia coli Serine Chemoreceptor in Different Signaling States. mBio 2019; 10:e00973-19. [PMID: 31266867 PMCID: PMC6606802 DOI: 10.1128/mbio.00973-19] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Accepted: 05/31/2019] [Indexed: 11/20/2022] Open
Abstract
Tsr, the serine chemoreceptor in Escherichia coli, transduces signals from a periplasmic ligand-binding site to its cytoplasmic tip, where it controls the activity of the CheA kinase. To function, Tsr forms trimers of homodimers (TODs), which associate in vivo with the CheA kinase and CheW coupling protein. Together, these proteins assemble into extended hexagonal arrays. Here, we use cryo-electron tomography and molecular dynamics simulation to study Tsr in the context of a near-native array, characterizing its signaling-related conformational changes at both the individual dimer and the trimer level. In particular, we show that individual Tsr dimers within a trimer exhibit asymmetric flexibilities that are a function of the signaling state, highlighting the effect of their different protein interactions at the receptor tips. We further reveal that the dimer compactness of the Tsr trimer changes between signaling states, transitioning at the glycine hinge from a compact conformation in the kinase-OFF state to an expanded conformation in the kinase-ON state. Hence, our results support a crucial role for the glycine hinge: to allow the receptor flexibility necessary to achieve different signaling states while also maintaining structural constraints imposed by the membrane and extended array architecture.IMPORTANCE In Escherichia coli, membrane-bound chemoreceptors, the histidine kinase CheA, and coupling protein CheW form highly ordered chemosensory arrays. In core signaling complexes, chemoreceptor trimers of dimers undergo conformational changes, induced by ligand binding and sensory adaptation, which regulate kinase activation. Here, we characterize by cryo-electron tomography the kinase-ON and kinase-OFF conformations of the E. coli serine receptor in its native array context. We found distinctive structural differences between the members of a receptor trimer, which contact different partners in the signaling unit, and structural differences between the ON and OFF signaling complexes. Our results provide new insights into the signaling mechanism of chemoreceptor arrays and suggest an important functional role for a previously postulated flexible region and glycine hinge in the receptor molecule.
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Affiliation(s)
- Wen Yang
- Institute of Biology, Leiden University, Leiden, The Netherlands
| | - C Keith Cassidy
- Department of Biochemistry, University of Oxford, Oxford, United Kingdom
- Department of Physics and Beckman Institute, University of Illinois Urbana-Champaign, Urbana, Illinois, USA
| | - Peter Ames
- School of Biological Sciences, University of Utah, Salt Lake City, Utah, USA
| | | | - Klaus Schulten
- Department of Physics and Beckman Institute, University of Illinois Urbana-Champaign, Urbana, Illinois, USA
| | - Zaida Luthey-Schulten
- Department of Chemistry and Center for the Physics of Living Cells, University of Illinois Urbana-Champaign, Urbana, Illinois, USA
| | - John S Parkinson
- School of Biological Sciences, University of Utah, Salt Lake City, Utah, USA
| | - Ariane Briegel
- Institute of Biology, Leiden University, Leiden, The Netherlands
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12
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Chen M, Baker ML. Automation and assessment of de novo modeling with Pathwalking in near atomic resolution cryoEM density maps. J Struct Biol 2018; 204:555-563. [DOI: 10.1016/j.jsb.2018.09.005] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2018] [Revised: 08/28/2018] [Accepted: 09/08/2018] [Indexed: 01/30/2023]
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13
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Tiemann JK, Rose AS, Ismer J, Darvish MD, Hilal T, Spahn CM, Hildebrand PW. FragFit: a web-application for interactive modeling of protein segments into cryo-EM density maps. Nucleic Acids Res 2018; 46:W310-W314. [PMID: 29788317 PMCID: PMC6030921 DOI: 10.1093/nar/gky424] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2018] [Accepted: 05/10/2018] [Indexed: 11/20/2022] Open
Abstract
Cryo-electron microscopy (cryo-EM) is a standard method to determine the three-dimensional structures of molecular complexes. However, easy to use tools for modeling of protein segments into cryo-EM maps are sparse. Here, we present the FragFit web-application, a web server for interactive modeling of segments of up to 35 amino acids length into cryo-EM density maps. The fragments are provided by a regularly updated database containing at the moment about 1 billion entries extracted from PDB structures and can be readily integrated into a protein structure. Fragments are selected based on geometric criteria, sequence similarity and fit into a given cryo-EM density map. Web-based molecular visualization with the NGL Viewer allows interactive selection of fragments. The FragFit web-application, accessible at http://proteinformatics.de/FragFit, is free and open to all users, without any login requirements.
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Affiliation(s)
- Johanna Ks Tiemann
- Institute of Medical Physics and Biophysics, Charité University Medicine Berlin, Berlin 10117, Germany.,Institute of Medical Physics and Biophysics, Medical University Leipzig, Leipzig, Sachsen 04107, Germany
| | - Alexander S Rose
- Institute of Medical Physics and Biophysics, Charité University Medicine Berlin, Berlin 10117, Germany
| | - Jochen Ismer
- Institute of Medical Physics and Biophysics, Charité University Medicine Berlin, Berlin 10117, Germany
| | - Mitra D Darvish
- Institute of Medical Physics and Biophysics, Charité University Medicine Berlin, Berlin 10117, Germany
| | - Tarek Hilal
- Institute of Medical Physics and Biophysics, Charité University Medicine Berlin, Berlin 10117, Germany
| | - Christian Mt Spahn
- Institute of Medical Physics and Biophysics, Charité University Medicine Berlin, Berlin 10117, Germany
| | - Peter W Hildebrand
- Institute of Medical Physics and Biophysics, Charité University Medicine Berlin, Berlin 10117, Germany.,Institute of Medical Physics and Biophysics, Medical University Leipzig, Leipzig, Sachsen 04107, Germany
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14
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Abou-Hamdan A, Belot L, Albertini A, Gaudin Y. Monomeric Intermediates Formed by Vesiculovirus Glycoprotein during Its Low-pH-induced Structural Transition. J Mol Biol 2018; 430:1685-1695. [PMID: 29678555 PMCID: PMC7126088 DOI: 10.1016/j.jmb.2018.04.015] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2018] [Revised: 04/06/2018] [Accepted: 04/10/2018] [Indexed: 01/26/2023]
Abstract
Vesiculovirus G is the prototype of class III viral fusion glycoproteins. The structures of both G pre- and post-fusion conformation have been determined. The structure of monomeric intermediates reveals the pathway of the transition. A fusion-loop-exposing antiparallel dimer may initiate the fusion process. Those data challenge the current model proposed for viral membrane fusion.
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Affiliation(s)
- Abbas Abou-Hamdan
- Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS, Univ. Paris-Sud, Université Paris-Saclay, 91198 Gif-sur-Yvette cedex, France
| | - Laura Belot
- Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS, Univ. Paris-Sud, Université Paris-Saclay, 91198 Gif-sur-Yvette cedex, France
| | - Aurélie Albertini
- Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS, Univ. Paris-Sud, Université Paris-Saclay, 91198 Gif-sur-Yvette cedex, France
| | - Yves Gaudin
- Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS, Univ. Paris-Sud, Université Paris-Saclay, 91198 Gif-sur-Yvette cedex, France.
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15
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Rigid-Body Fitting of Atomic Models on 3D Density Maps of Electron Microscopy. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2018; 1105:219-235. [PMID: 30617832 DOI: 10.1007/978-981-13-2200-6_14] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
Cryo electron microscopy has revolutionarily evolved for the determination of the 3D structure of macromolecular complexes. The modeling procedures on the 3D density maps of electron microscopy are roughly classified into three categories: fitting, de novo modeling and refinement. The registered atomic models from the maps have mostly been hand-built and auto-refined. Several programs aiming at automatic modeling have also been developed using various kinds of molecular representations. Among these three classes of the modeling procedures, the rigid body fitting is reviewed here, because it is the most basic modeling process applied before the other steps. The fitting problems are classified as the fittings of single subunit or multiple subunits, and the fittings on global or local parts of maps. A higher resolution map enables more local fitting. Various molecular representations have been employed in the fitting programs. A point and digital image models are generally used to represent molecules, but new representations, such as the Gaussian mixture model, have been applied recently.
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