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Remis J, Petrov PN, Zhang JT, Axelrod JJ, Cheng H, Sandhaus S, Mueller H, Glaeser RM. Cryo-EM phase-plate images reveal unexpected levels of apparent specimen damage. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.04.606536. [PMID: 39149370 PMCID: PMC11326166 DOI: 10.1101/2024.08.04.606536] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/17/2024]
Abstract
Apoferritin (apoF) is commonly used as a test specimen in single-particle electron cryo-microscopy (cryo-EM), since it consistently produces density maps that go to 3 Å resolution or higher. When we imaged apoF with a laser phase plate (LPP), however, we observed more severe particle-to-particle variation in the images than we had previously thought to exist. Similarly, we found that images of ribulose bisphosphate carboxylase/oxygenase (rubisco) also exhibited a much greater amount of heterogeneity than expected. By comparison to simulations of images, we verified that the heterogeneity is not explained by the known features of the LPP, shot noise, or differences in particle orientation. We also demonstrate that our specimens are comparable to those previously used in the literature, based on using the final-reconstruction resolution as the metric for evaluation. All of this leads us to the hypothesis that the heterogeneity is due to damage that has occurred either during purification of the specimen or during preparation of the grids. It is not, however, our goal to explain the causes of heterogeneity; rather, we report that using the LPP has made the apparent damage too obvious to be ignored. In hindsight, similar heterogeneity can be seen in images of apoF and the 20S proteasome which others had recorded with a Volta phase plate. We therefore conclude that the increased contrast of phase-plate images (at low spatial frequencies) should also make it possible to visualize, on a single-particle basis, various forms of biologically functional heterogeneity in structure that had previously gone unnoticed.
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Affiliation(s)
- Jonathan Remis
- Department of Physics, University of California Berkeley, Berkeley, CA 94720, USA
| | - Petar N. Petrov
- Department of Physics, University of California Berkeley, Berkeley, CA 94720, USA
- Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720, USA
| | - Jessie T, Zhang
- Department of Physics, University of California Berkeley, Berkeley, CA 94720, USA
- Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720, USA
| | - Jeremy J. Axelrod
- Department of Physics, University of California Berkeley, Berkeley, CA 94720, USA
- Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720, USA
| | - Hang Cheng
- Department of Molecular and Cell Biology, University of California Berkeley, Berkeley, CA 94720, USA
- California Institute for Quantitative Biosciences, University of California Berkeley, Berkeley, CA 94720, USA
| | - Shahar Sandhaus
- Department of Physics, University of California Berkeley, Berkeley, CA 94720, USA
| | - Holger Mueller
- Department of Physics, University of California Berkeley, Berkeley, CA 94720, USA
- Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720, USA
| | - Robert M. Glaeser
- Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720, USA
- Department of Molecular and Cell Biology, University of California Berkeley, Berkeley, CA 94720, USA
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2
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Rangan R, Feathers R, Khavnekar S, Lerer A, Johnston JD, Kelley R, Obr M, Kotecha A, Zhong ED. CryoDRGN-ET: deep reconstructing generative networks for visualizing dynamic biomolecules inside cells. Nat Methods 2024; 21:1537-1545. [PMID: 39025970 DOI: 10.1038/s41592-024-02340-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2023] [Accepted: 06/06/2024] [Indexed: 07/20/2024]
Abstract
Advances in cryo-electron tomography (cryo-ET) have produced new opportunities to visualize the structures of dynamic macromolecules in native cellular environments. While cryo-ET can reveal structures at molecular resolution, image processing algorithms remain a bottleneck in resolving the heterogeneity of biomolecular structures in situ. Here, we introduce cryoDRGN-ET for heterogeneous reconstruction of cryo-ET subtomograms. CryoDRGN-ET learns a deep generative model of three-dimensional density maps directly from subtomogram tilt-series images and can capture states diverse in both composition and conformation. We validate this approach by recovering the known translational states in Mycoplasma pneumoniae ribosomes in situ. We then perform cryo-ET on cryogenic focused ion beam-milled Saccharomyces cerevisiae cells. CryoDRGN-ET reveals the structural landscape of S. cerevisiae ribosomes during translation and captures continuous motions of fatty acid synthase complexes inside cells. This method is openly available in the cryoDRGN software.
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Affiliation(s)
- Ramya Rangan
- Department of Computer Science, Princeton University, Princeton, NJ, USA
| | - Ryan Feathers
- Department of Computer Science, Princeton University, Princeton, NJ, USA
| | | | | | - Jake D Johnston
- Physiology and Cellular Biophysics, Columbia University, New York, NY, USA
- Simons Electron Microscopy Center, New York Structural Biology Center, New York, NY, USA
| | - Ron Kelley
- Materials and Structural Analysis Division, Thermo Fisher Scientific, Eindhoven, the Netherlands
| | - Martin Obr
- Materials and Structural Analysis Division, Thermo Fisher Scientific, Eindhoven, the Netherlands
| | - Abhay Kotecha
- Materials and Structural Analysis Division, Thermo Fisher Scientific, Eindhoven, the Netherlands.
| | - Ellen D Zhong
- Department of Computer Science, Princeton University, Princeton, NJ, USA.
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3
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Chung SC. Cryo-forum: A framework for orientation recovery with uncertainty measure with the application in cryo-EM image analysis. J Struct Biol 2024; 216:108058. [PMID: 38163450 DOI: 10.1016/j.jsb.2023.108058] [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: 08/09/2023] [Revised: 12/14/2023] [Accepted: 12/28/2023] [Indexed: 01/03/2024]
Abstract
In single-particle cryo-electron microscopy (cryo-EM), efficient determination of orientation parameters for particle images poses a significant challenge yet is crucial for reconstructing 3D structures. This task is complicated by the high noise levels in the datasets, which often include outliers, necessitating several time-consuming 2D clean-up processes. Recently, solutions based on deep learning have emerged, offering a more streamlined approach to the traditionally laborious task of orientation estimation. These solutions employ amortized inference, eliminating the need to estimate parameters individually for each image. However, these methods frequently overlook the presence of outliers and may not adequately concentrate on the components used within the network. This paper introduces a novel method using a 10-dimensional feature vector for orientation representation, extracting orientations as unit quaternions with an accompanying uncertainty metric. Furthermore, we propose a unique loss function that considers the pairwise distances between orientations, thereby enhancing the accuracy of our method. Finally, we also comprehensively evaluate the design choices in constructing the encoder network, a topic that has not received sufficient attention in the literature. Our numerical analysis demonstrates that our methodology effectively recovers orientations from 2D cryo-EM images in an end-to-end manner. Notably, the inclusion of uncertainty quantification allows for direct clean-up of the dataset at the 3D level. Lastly, we package our proposed methods into a user-friendly software suite named cryo-forum, designed for easy access by developers.
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Affiliation(s)
- Szu-Chi Chung
- Department of Applied Mathematics, National Sun Yat-sen University, No. 70, Lienhai Rd, Kaohsiung, Taiwan.
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4
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Lucas BA, Himes BA, Grigorieff N. Baited reconstruction with 2D template matching for high-resolution structure determination in vitro and in vivo without template bias. eLife 2023; 12:RP90486. [PMID: 38010355 PMCID: PMC10681363 DOI: 10.7554/elife.90486] [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: 11/29/2023] Open
Abstract
Previously we showed that 2D template matching (2DTM) can be used to localize macromolecular complexes in images recorded by cryogenic electron microscopy (cryo-EM) with high precision, even in the presence of noise and cellular background (Lucas et al., 2021; Lucas et al., 2022). Here, we show that once localized, these particles may be averaged together to generate high-resolution 3D reconstructions. However, regions included in the template may suffer from template bias, leading to inflated resolution estimates and making the interpretation of high-resolution features unreliable. We evaluate conditions that minimize template bias while retaining the benefits of high-precision localization, and we show that molecular features not present in the template can be reconstructed at high resolution from targets found by 2DTM, extending prior work at low-resolution. Moreover, we present a quantitative metric for template bias to aid the interpretation of 3D reconstructions calculated with particles localized using high-resolution templates and fine angular sampling.
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Affiliation(s)
- Bronwyn A Lucas
- RNA Therapeutics Institute, University of Massachusetts Chan Medical SchoolWorcesterUnited States
- Department of Molecular and Cell Biology, University of California BerkeleyBerkeleyUnited States
- Center for Computational Biology, University of California BerkeleyBerkeleyUnited States
| | - Benjamin A Himes
- RNA Therapeutics Institute, University of Massachusetts Chan Medical SchoolWorcesterUnited States
- Howard Hughes Medical InstituteChevy ChaseUnited States
| | - Nikolaus Grigorieff
- RNA Therapeutics Institute, University of Massachusetts Chan Medical SchoolWorcesterUnited States
- Howard Hughes Medical InstituteChevy ChaseUnited States
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5
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Rodríguez de Francisco B, Bezault A, Xu XP, Hanein D, Volkmann N. MEPSi: A tool for simulating tomograms of membrane-embedded proteins. J Struct Biol 2022; 214:107921. [PMID: 36372192 DOI: 10.1016/j.jsb.2022.107921] [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: 07/31/2022] [Revised: 10/27/2022] [Accepted: 11/05/2022] [Indexed: 11/11/2022]
Abstract
The throughput and fidelity of cryogenic cellular electron tomography (cryo-ET) is constantly increasing through advances in cryogenic electron microscope hardware, direct electron detection devices, and powerful image processing algorithms. However, the need for careful optimization of sample preparations and for access to expensive, high-end equipment, make cryo-ET a costly and time-consuming technique. Generally, only after the last step of the cryo-ET workflow, when reconstructed tomograms are available, it becomes clear whether the chosen imaging parameters were suitable for a specific type of sample in order to answer a specific biological question. Tools for a-priory assessment of the feasibility of samples to answer biological questions and how to optimize imaging parameters to do so would be a major advantage. Here we describe MEPSi (Membrane Embedded Protein Simulator), a simulation tool aimed at rapid and convenient evaluation and optimization of cryo-ET data acquisition parameters for studies of transmembrane proteins in their native environment. We demonstrate the utility of MEPSi by showing how to detangle the influence of different data collection parameters and different orientations in respect to tilt axis and electron beam for two examples: (1) simulated plasma membranes with embedded single-pass transmembrane αIIbβ3 integrin receptors and (2) simulated virus membranes with embedded SARS-CoV-2 spike proteins.
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Affiliation(s)
- Borja Rodríguez de Francisco
- Institut Pasteur, Université Paris Cité, CNRS UMR3528, Structural Studies of Macromolecular Machines in Cellulo Unit, Paris, France; Institut Pasteur, Université Paris Cité, CNRS UMR3528, Structural Image Analysis Unit, Paris, France
| | - Armel Bezault
- Institut Pasteur, Université Paris Cité, CNRS UMR3528, Structural Studies of Macromolecular Machines in Cellulo Unit, Paris, France; Institut Pasteur, Université Paris Cité, CNRS UMR3528, Structural Image Analysis Unit, Paris, France
| | | | - Dorit Hanein
- Institut Pasteur, Université Paris Cité, CNRS UMR3528, Structural Studies of Macromolecular Machines in Cellulo Unit, Paris, France; Scintillon Institute, San Diego, CA 92121, USA
| | - Niels Volkmann
- Institut Pasteur, Université Paris Cité, CNRS UMR3528, Structural Image Analysis Unit, Paris, France.
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6
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Elferich J, Schiroli G, Scadden DT, Grigorieff N. Defocus Corrected Large Area Cryo-EM (DeCo-LACE) for label-free detection of molecules across entire cell sections. eLife 2022; 11:e80980. [PMID: 36382886 PMCID: PMC9711527 DOI: 10.7554/elife.80980] [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: 06/10/2022] [Accepted: 11/15/2022] [Indexed: 11/17/2022] Open
Abstract
A major goal of biological imaging is localization of biomolecules inside a cell. Fluorescence microscopy can localize biomolecules inside whole cells and tissues, but its ability to count biomolecules and accuracy of the spatial coordinates is limited by the wavelength of visible light. Cryo-electron microscopy (cryo-EM) provides highly accurate position and orientation information of biomolecules but is often confined to small fields of view inside a cell, limiting biological context. In this study, we use a new data-acquisition scheme called Defocus-Corrected Large-Area cryo-EM (DeCo-LACE) to collect high-resolution images of entire sections (100- to 250-nm-thick lamellae) of neutrophil-like mouse cells, representing 1-2% of the total cellular volume. We use 2D template matching (2DTM) to determine localization and orientation of the large ribosomal subunit in these sections. These data provide maps of ribosomes across entire sections of mammalian cells. This high-throughput cryo-EM data collection approach together with 2DTM will advance visual proteomics and provide biological insight that cannot be obtained by other methods.
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Affiliation(s)
- Johannes Elferich
- RNA Therapeutics Institute, University of Massachusetts Chan Medical School, Howard Hughes Medical InstituteWorcesterUnited States
| | - Giulia Schiroli
- Department of Stem Cell and Regenerative Biology, Harvard UniversityCambridgeUnited States
- Harvard Stem Cell InstituteCambridgeUnited States
- Center for Regenerative Medicine, Massachusetts General HospitalBostonUnited States
| | - David T Scadden
- Department of Stem Cell and Regenerative Biology, Harvard UniversityCambridgeUnited States
- Harvard Stem Cell InstituteCambridgeUnited States
- Center for Regenerative Medicine, Massachusetts General HospitalBostonUnited States
| | - Nikolaus Grigorieff
- RNA Therapeutics Institute, University of Massachusetts Chan Medical School, Howard Hughes Medical InstituteWorcesterUnited States
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7
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Shi D, Huang R. Analysis and comparison of electron radiation damage assessments in Cryo-EM by single particle analysis and micro-crystal electron diffraction. Front Mol Biosci 2022; 9:988928. [PMID: 36275612 PMCID: PMC9585622 DOI: 10.3389/fmolb.2022.988928] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Accepted: 08/05/2022] [Indexed: 11/25/2022] Open
Abstract
Electron radiation damage to macromolecules is an inevitable resolution limit factor in all major structural determination applications using cryo-electron microscopy (cryo-EM). Single particle analysis (SPA) and micro-crystal electron diffraction (MicroED) have been employed to assess radiation damage with a variety of protein complexes. Although radiation induced sidechain density loss and resolution decay were observed by both methods, the minimum dose of electron irradiation reducing high-resolution limit reported by SPA is more than ten folds higher than measured by MicroED using the conventional dose concept, and there is a gap between the attained resolutions assessed by these two methods. We compared and analyzed these two approaches side-by-side in detail from several aspects to identify some crucial determinants and to explain this discrepancy. Probability of a high energy electron being inelastically scattered by a macromolecule is proportional to number of layers of the molecules in its transmission path. As a result, the same electron dose could induce much more site-specific damage to macromolecules in 3D protein crystal than single particle samples. Major differences in data collection and processing scheme are the key factors to different levels of sensitivity to radiation damage at high resolution between the two methods. High resolution electron diffraction in MicroED dataset is very sensitive to global damage to 3D protein crystals with low dose accumulation, and its intensity attenuation rates at atomic resolution shell could be applied for estimating ratio of damaged and total selected single particles for SPA. More in-depth systematically radiation damage assessments using SPA and MicroED will benefit all applications of cryo-EM, especially cellular structure analysis by tomography.
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Affiliation(s)
- Dan Shi
- Center for Structural Biology, Center for Cancer Research, National Cancer Institute, Frederick, MD, United States
- *Correspondence: Dan Shi,
| | - Rick Huang
- Laboratory of Cell Biology, Center for Cancer Research, National Cancer Institute, Bethesda, MD, United States
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8
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Wentinck K, Gogou C, Meijer DH. Putting on molecular weight: Enabling cryo-EM structure determination of sub-100-kDa proteins. Curr Res Struct Biol 2022; 4:332-337. [PMID: 36248264 PMCID: PMC9562432 DOI: 10.1016/j.crstbi.2022.09.005] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 09/22/2022] [Accepted: 09/25/2022] [Indexed: 11/17/2022] Open
Abstract
Significant advances in the past decade have enabled high-resolution structure determination of a vast variety of proteins by cryogenic electron microscopy single particle analysis. Despite improved sample preparation, next-generation imaging hardware, and advanced single particle analysis algorithms, small proteins remain elusive for reconstruction due to low signal-to-noise and lack of distinctive structural features. Multiple efforts have therefore been directed at the development of size-increase techniques for small proteins. Here we review the latest methods for increasing effective molecular weight of proteins <100 kDa through target protein binding or target protein fusion - specifically by using nanobody-based assemblies, fusion tags, and symmetric scaffolds. Finally, we summarize these state-of-the-art techniques into a decision-tree to facilitate the design of tailored future approaches, and thus for further exploration of ever-smaller proteins that make up the largest part of the human genome.
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Key Words
- BRIL, cytochromeb562 RIL
- DARPin, Design Ankyrin Repeat Protein
- Fab, antigen binding fragment
- GFP, Green Fluorecent Protein
- GPCR, G protein-coupled receptor
- MW, molecular weight
- Mb, megabody
- Nb, nanobody
- SNR, signal-to-noise ratio
- SPA, single particle analysis
- TM, transmembrane
- cryo-EM, cryogenic electron microscopy
- kDa, kiloDalton
- κOR ICL3, κ-opiod receptor intracellular loop 3
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9
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Lucas BA, Zhang K, Loerch S, Grigorieff N. In situ single particle classification reveals distinct 60S maturation intermediates in cells. eLife 2022; 11:79272. [PMID: 36005291 PMCID: PMC9444246 DOI: 10.7554/elife.79272] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 08/24/2022] [Indexed: 11/13/2022] Open
Abstract
Previously we showed that high-resolution template matching can localize ribosomes in two-dimensional electron cryo-microscopy (cryo-EM) images of untilted Mycoplasma pneumoniae cells with high precision (Lucas et al., 2021). Here we show that comparing the signal-to-noise ratio (SNR) observed with 2DTM using different templates relative to the same cellular target can correct for local variation in noise and differentiate related complexes in focused ion beam (FIB)-milled cell sections. We use a maximum likelihood approach to define the probability of each particle belonging to each class, thereby establishing a statistic to describe the confidence of our classification. We apply this method in two contexts to locate and classify related intermediate states of 60S ribosome biogenesis in the Saccharomyces cerevisiae cell nucleus. In the first, we separate the nuclear pre-60S population from the cytoplasmic mature 60S population, using the subcellular localization to validate assignment. In the second, we show that relative 2DTM SNRs can be used to separate mixed populations of nuclear pre-60S that are not visually separable. 2DTM can distinguish related molecular populations without the need to generate 3D reconstructions from the data to be classified, permitting classification even when only a few target particles exist in a cell.
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Affiliation(s)
- Bronwyn A Lucas
- RNA Therapeutics Institute, University of Massachusetts Medical School, Worcester, United States
| | - Kexin Zhang
- RNA Therapeutics Institute, University of Massachusetts Medical School, Worcester, United States
| | - Sarah Loerch
- Department of Chemistry and Biochemistry, University of California, Santa Cruz, Santa Cruz, United States
| | - Nikolaus Grigorieff
- RNA Therapeutics Institute, University of Massachusetts Medical School, Worcester, United States
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10
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Brown HG, Hanssen E. MeasureIce: accessible on-the-fly measurement of ice thickness in cryo-electron microscopy. Commun Biol 2022; 5:817. [PMID: 35965271 PMCID: PMC9376182 DOI: 10.1038/s42003-022-03698-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Accepted: 07/11/2022] [Indexed: 11/12/2022] Open
Abstract
Ice thickness is arguably one of the most important factors limiting the resolution of protein structures determined by cryo-electron microscopy (cryo-EM). The amorphous atomic structure of the ice that stabilizes and protects biological samples in cryo-EM grids also imprints some additional noise in cryo-EM images. Ice that is too thick jeopardizes the success of particle picking and reconstruction of the biomolecule in the worst case and, at best, deteriorates eventual map resolution. Minimizing the thickness of the ice layer and thus the magnitude of its noise contribution is thus imperative in cryo-EM grid preparation. In this paper we introduce MeasureIce, a simple, easy to use ice thickness measurement tool for screening and selecting acquisition areas of cryo-EM grids. We show that it is possible to simulate thickness-image intensity look-up tables, also usable in SerialEM and Leginon, using elementary scattering physics and thereby adapt the tool to any microscope without time consuming experimental calibration. We benchmark our approach using two alternative techniques: the “ice channel” technique and tilt-series tomography. We also demonstrate the utility of ice thickness measurement for selecting holes in gold grids containing an Equine apoferritin sample, achieving a 1.88 Ångstrom resolution in subsequent refinement of the atomic map. MeasureIce is an ice thickness measurement tool for screening and selecting acquisition areas of cryo-EM grids.
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Affiliation(s)
- Hamish G Brown
- Ian Holmes Imaging Center, Bio21 Molecular Science & Biotechnology Institute, University of Melbourne, Parkville, Victoria, Australia.
| | - Eric Hanssen
- Ian Holmes Imaging Center, Bio21 Molecular Science & Biotechnology Institute, University of Melbourne, Parkville, Victoria, Australia.,Department of Biochemistry and Pharmacology and ARC Industrial Transformation Training Center for Cryo-electron Microscopy of Membrane Proteins, The University of Melbourne, Parkville, Victoria, Australia
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