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McCormick RA, Ralbovsky NM, Gilbraith W, Smith JP, Booksh KS. Analyzing atomic force microscopy images of virus-like particles by expectation-maximization. NPJ Vaccines 2024; 9:112. [PMID: 38902288 PMCID: PMC11190231 DOI: 10.1038/s41541-024-00871-7] [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: 05/05/2023] [Accepted: 03/28/2024] [Indexed: 06/22/2024] Open
Abstract
Analysis of virus-like particles (VLPs) is an essential task in optimizing their implementation as vaccine antigens for virus-initiated diseases. Interrogating VLP collections for elasticity by probing with a rigid atomic force microscopy (AFM) tip is a potential method for determining VLP morphological changes. During VLP morphological change, it is not expected that all VLPs would be in the same state. This leads to the open question of whether VLPs may change in a continuous or stepwise fashion. For continuous change, the statistical distribution of observed VLP properties would be expected as a single distribution, while stepwise change would lead to a multimodal distribution of properties. This study presents the application of a Gaussian mixture model (GMM), fit by the Expectation-Maximization (EM) algorithm, to identify different states of VLP morphological change observed by AFM imaging.
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Affiliation(s)
- Rachel A McCormick
- Department of Chemistry and Biochemistry, University of Delaware, Newark, DE, 19716, USA
| | - Nicole M Ralbovsky
- Analytical Research & Development, MRL, Merck & Co., Inc, West Point, PA, 19486, USA
| | - William Gilbraith
- Department of Chemistry and Biochemistry, University of Delaware, Newark, DE, 19716, USA
| | - Joseph P Smith
- Process Research & Development, MRL, Merck & Co., Inc, West Point, PA, 19486, USA.
| | - Karl S Booksh
- Department of Chemistry and Biochemistry, University of Delaware, Newark, DE, 19716, USA.
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2
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Flechsig H, Ando T. Protein dynamics by the combination of high-speed AFM and computational modeling. Curr Opin Struct Biol 2023; 80:102591. [PMID: 37075535 DOI: 10.1016/j.sbi.2023.102591] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Revised: 03/06/2023] [Accepted: 03/08/2023] [Indexed: 04/21/2023]
Abstract
High-speed atomic force microscopy (HS-AFM) allows direct observation of biological molecules in dynamic action. However, HS-AFM has no atomic resolution. This article reviews recent progress of computational methods to infer high-resolution information, including the construction of 3D atomistic structures, from experimentally acquired resolution-limited HS-AFM images.
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Affiliation(s)
- Holger Flechsig
- Nano Life Science Institute (WPI-NanoLSI), Kanazawa University, Kakuma-machi, Kanazawa, 920-1192, Japan
| | - Toshio Ando
- Nano Life Science Institute (WPI-NanoLSI), Kanazawa University, Kakuma-machi, Kanazawa, 920-1192, Japan.
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Amyot R, Kodera N, Flechsig H. BioAFMviewer software for simulation atomic force microscopy of molecular structures and conformational dynamics. J Struct Biol X 2023; 7:100086. [PMID: 36865763 PMCID: PMC9972558 DOI: 10.1016/j.yjsbx.2023.100086] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 02/09/2023] [Accepted: 02/11/2023] [Indexed: 02/15/2023] Open
Abstract
Atomic force microscopy (AFM) and high-speed scanning have significantly advanced real time observation of biomolecular dynamics, with applications ranging from single molecules to the cellular level. To facilitate the interpretation of resolution-limited imaging, post-experimental computational analysis plays an increasingly important role to understand AFM measurements. Data-driven simulation of AFM, computationally emulating experimental scanning, and automatized fitting has recently elevated the understanding of measured AFM topographies by inferring the underlying full 3D atomistic structures. Providing an interactive user-friendly interface for simulation AFM, the BioAFMviewer software has become an established tool within the Bio-AFM community, with a plethora of applications demonstrating how the obtained full atomistic information advances molecular understanding beyond topographic imaging. This graphical review illustrates the BioAFMviewer capacities and further emphasizes the importance of simulation AFM to complement experimental observations.
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Asi H, Dasgupta B, Nagai T, Miyashita O, Tama F. A hybrid approach to study large conformational transitions of biomolecules from single particle XFEL diffraction data. Front Mol Biosci 2022; 9:913860. [PMID: 36660427 PMCID: PMC9846856 DOI: 10.3389/fmolb.2022.913860] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 07/04/2022] [Indexed: 01/06/2023] Open
Abstract
X-ray free-electron laser (XFEL) is the latest generation of the X-ray source that could become an invaluable technique in structural biology. XFEL has ultrashort pulse duration, extreme peak brilliance, and high spatial coherence, which could enable the observation of the biological molecules in near nature state at room temperature without crystallization. However, for biological systems, due to their low diffraction power and complexity of sample delivery, experiments and data analysis are not straightforward, making it extremely challenging to reconstruct three-dimensional (3D) structures from single particle XFEL data. Given the current limitations to the amount and resolution of the data from such XFEL experiments, we propose a new hybrid approach for characterizing biomolecular conformational transitions by using a single 2D low-resolution XFEL diffraction pattern in combination with another known conformation. In our method, we represent the molecular structure with a coarse-grained model, the Gaussian mixture model, to describe large conformational transitions from low-resolution XFEL data. We obtain plausible 3D structural models that are consistent with the XFEL diffraction pattern by deforming an initial structural model to maximize the similarity between the target pattern and the simulated diffraction patterns from the candidate models. We tested the proposed algorithm on two biomolecules of different sizes with different complexities of conformational transitions, adenylate kinase, and elongation factor 2, using synthetic XFEL data. The results show that, with the proposed algorithm, we can successfully describe the conformational transitions by flexibly fitting the coarse-grained model of one conformation to become consistent with an XFEL diffraction pattern simulated from another conformation. In addition, we showed that the incident beam orientation has some effect on the accuracy of the 3D structure modeling and discussed the reasons for the inaccuracies for certain orientations. The proposed method could serve as an alternative approach for retrieving information on 3D conformational transitions from the XFEL diffraction patterns to interpret experimental data. Since the molecules are represented by Gaussian kernels and no atomic structure is needed in principle, such a method could also be used as a tool to seek initial models for 3D reconstruction algorithms.
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Affiliation(s)
- Han Asi
- Department of Physics, Nagoya University, Nagoya, Japan
| | - Bhaskar Dasgupta
- Division of Biological Data Science, Research Center for Advanced Science and Technology, The University of Tokyo, Meguro City, Japan
| | - Tetsuro Nagai
- Department of Advanced Materials Science, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan
| | - Osamu Miyashita
- RIKEN Center for Computational Science, Kobe, Japan,*Correspondence: Osamu Miyashita, ; Florence Tama,
| | - Florence Tama
- Department of Physics, Nagoya University, Nagoya, Japan,RIKEN Center for Computational Science, Kobe, Japan,Institute of Transformative Bio-Molecules, Nagoya University, Nagoya, Japan,*Correspondence: Osamu Miyashita, ; Florence Tama,
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Varikoti RA, Fonseka HYY, Kelly MS, Javidi A, Damre M, Mullen S, Nugent JL, Gonzales CM, Stan G, Dima RI. Exploring the Effect of Mechanical Anisotropy of Protein Structures in the Unfoldase Mechanism of AAA+ Molecular Machines. NANOMATERIALS 2022; 12:nano12111849. [PMID: 35683705 PMCID: PMC9182431 DOI: 10.3390/nano12111849] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/02/2022] [Revised: 05/25/2022] [Accepted: 05/25/2022] [Indexed: 02/06/2023]
Abstract
Essential cellular processes of microtubule disassembly and protein degradation, which span lengths from tens of μm to nm, are mediated by specialized molecular machines with similar hexameric structure and function. Our molecular simulations at atomistic and coarse-grained scales show that both the microtubule-severing protein spastin and the caseinolytic protease ClpY, accomplish spectacular unfolding of their diverse substrates, a microtubule lattice and dihydrofolate reductase (DHFR), by taking advantage of mechanical anisotropy in these proteins. Unfolding of wild-type DHFR requires disruption of mechanically strong β-sheet interfaces near each terminal, which yields branched pathways associated with unzipping along soft directions and shearing along strong directions. By contrast, unfolding of circular permutant DHFR variants involves single pathways due to softer mechanical interfaces near terminals, but translocation hindrance can arise from mechanical resistance of partially unfolded intermediates stabilized by β-sheets. For spastin, optimal severing action initiated by pulling on a tubulin subunit is achieved through specific orientation of the machine versus the substrate (microtubule lattice). Moreover, changes in the strength of the interactions between spastin and a microtubule filament, which can be driven by the tubulin code, lead to drastically different outcomes for the integrity of the hexameric structure of the machine.
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Affiliation(s)
- Rohith Anand Varikoti
- Department of Chemistry, University of Cincinnati, Cincinnati, OH 45221, USA; (R.A.V.); (H.Y.Y.F.); (M.S.K.); (M.D.); (J.L.N.IV)
| | - Hewafonsekage Yasan Y. Fonseka
- Department of Chemistry, University of Cincinnati, Cincinnati, OH 45221, USA; (R.A.V.); (H.Y.Y.F.); (M.S.K.); (M.D.); (J.L.N.IV)
| | - Maria S. Kelly
- Department of Chemistry, University of Cincinnati, Cincinnati, OH 45221, USA; (R.A.V.); (H.Y.Y.F.); (M.S.K.); (M.D.); (J.L.N.IV)
| | - Alex Javidi
- Data Sciences, Janssen Research and Development, Spring House, PA 19477, USA;
| | - Mangesh Damre
- Department of Chemistry, University of Cincinnati, Cincinnati, OH 45221, USA; (R.A.V.); (H.Y.Y.F.); (M.S.K.); (M.D.); (J.L.N.IV)
| | - Sarah Mullen
- Department of Chemistry, The College of Wooster, Wooster, OH 44691, USA;
| | - Jimmie L. Nugent
- Department of Chemistry, University of Cincinnati, Cincinnati, OH 45221, USA; (R.A.V.); (H.Y.Y.F.); (M.S.K.); (M.D.); (J.L.N.IV)
| | | | - George Stan
- Department of Chemistry, University of Cincinnati, Cincinnati, OH 45221, USA; (R.A.V.); (H.Y.Y.F.); (M.S.K.); (M.D.); (J.L.N.IV)
- Correspondence: (G.S.); (R.I.D.)
| | - Ruxandra I. Dima
- Department of Chemistry, University of Cincinnati, Cincinnati, OH 45221, USA; (R.A.V.); (H.Y.Y.F.); (M.S.K.); (M.D.); (J.L.N.IV)
- Correspondence: (G.S.); (R.I.D.)
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Amyot R, Marchesi A, Franz CM, Casuso I, Flechsig H. Simulation atomic force microscopy for atomic reconstruction of biomolecular structures from resolution-limited experimental images. PLoS Comput Biol 2022; 18:e1009970. [PMID: 35294442 PMCID: PMC8959186 DOI: 10.1371/journal.pcbi.1009970] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 03/28/2022] [Accepted: 02/25/2022] [Indexed: 11/18/2022] Open
Abstract
Atomic force microscopy (AFM) can visualize the dynamics of single biomolecules under near-physiological conditions. However, the scanning tip probes only the molecular surface with limited resolution, missing details required to fully deduce functional mechanisms from imaging alone. To overcome such drawbacks, we developed a computational framework to reconstruct 3D atomistic structures from AFM surface scans, employing simulation AFM and automatized fitting to experimental images. We provide applications to AFM images ranging from single molecular machines, protein filaments, to large-scale assemblies of 2D protein lattices, and demonstrate how the obtained full atomistic information advances the molecular understanding beyond the original topographic AFM image. We show that simulation AFM further allows for quantitative molecular feature assignment within measured AFM topographies. Implementation of the developed methods into the versatile interactive interface of the BioAFMviewer software, freely available at www.bioafmviewer.com, presents the opportunity for the broad Bio-AFM community to employ the enormous amount of existing structural and modeling data to facilitate the interpretation of resolution-limited AFM images.
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Affiliation(s)
- Romain Amyot
- Aix Marseille University, CNRS, INSERM, LAI, Turing Centre for Living Systems, Marseille, France
| | - Arin Marchesi
- Nano Life Science Institute (WPI-NanoLSI), Kanazawa University, Kakuma-machi, Kanazawa, Ishikawa, Japan
| | - Clemens M. Franz
- Nano Life Science Institute (WPI-NanoLSI), Kanazawa University, Kakuma-machi, Kanazawa, Ishikawa, Japan
| | - Ignacio Casuso
- Aix Marseille University, CNRS, INSERM, LAI, Turing Centre for Living Systems, Marseille, France
| | - Holger Flechsig
- Nano Life Science Institute (WPI-NanoLSI), Kanazawa University, Kakuma-machi, Kanazawa, Ishikawa, Japan
- * E-mail:
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