1
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Nabi IR, Cardoen B, Khater IM, Gao G, Wong TH, Hamarneh G. AI analysis of super-resolution microscopy: Biological discovery in the absence of ground truth. J Cell Biol 2024; 223:e202311073. [PMID: 38865088 PMCID: PMC11169916 DOI: 10.1083/jcb.202311073] [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: 11/15/2023] [Revised: 04/02/2024] [Accepted: 05/21/2024] [Indexed: 06/13/2024] Open
Abstract
Super-resolution microscopy, or nanoscopy, enables the use of fluorescent-based molecular localization tools to study molecular structure at the nanoscale level in the intact cell, bridging the mesoscale gap to classical structural biology methodologies. Analysis of super-resolution data by artificial intelligence (AI), such as machine learning, offers tremendous potential for the discovery of new biology, that, by definition, is not known and lacks ground truth. Herein, we describe the application of weakly supervised paradigms to super-resolution microscopy and its potential to enable the accelerated exploration of the nanoscale architecture of subcellular macromolecules and organelles.
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Affiliation(s)
- Ivan R. Nabi
- Department of Cellular and Physiological Sciences, Life Sciences Institute, University of British Columbia, Vancouver, Canada
- School of Biomedical Engineering, University of British Columbia, Vancouver, Canada
| | - Ben Cardoen
- School of Computing Science, Simon Fraser University, Burnaby, Canada
| | - Ismail M. Khater
- School of Computing Science, Simon Fraser University, Burnaby, Canada
- Department of Electrical and Computer Engineering, Faculty of Engineering and Technology, Birzeit University, Birzeit, Palestine
| | - Guang Gao
- Department of Cellular and Physiological Sciences, Life Sciences Institute, University of British Columbia, Vancouver, Canada
| | - Timothy H. Wong
- Department of Cellular and Physiological Sciences, Life Sciences Institute, University of British Columbia, Vancouver, Canada
| | - Ghassan Hamarneh
- School of Computing Science, Simon Fraser University, Burnaby, Canada
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2
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Liu J, Li Y, Chen T, Zhang F, Xu F. Machine Learning for Single-Molecule Localization Microscopy: From Data Analysis to Quantification. Anal Chem 2024. [PMID: 38946062 DOI: 10.1021/acs.analchem.3c05857] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
Single-molecule localization microscopy (SMLM) is a versatile tool for realizing nanoscale imaging with visible light and providing unprecedented opportunities to observe bioprocesses. The integration of machine learning with SMLM enhances data analysis by improving efficiency and accuracy. This tutorial aims to provide a comprehensive overview of the data analysis process and theoretical aspects of SMLM, while also highlighting the typical applications of machine learning in this field. By leveraging advanced analytical techniques, SMLM is becoming a powerful quantitative analysis tool for biological research.
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Affiliation(s)
- Jianli Liu
- School of Medical Technology, Beijing Institute of Technology, Beijing 100081, China
| | - Yumian Li
- Advanced Research Institute of Multidisciplinary Science, Beijing Institute of Technology, Beijing 100081, China
- School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China
| | - Tailong Chen
- Advanced Research Institute of Multidisciplinary Science, Beijing Institute of Technology, Beijing 100081, China
- School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China
| | - Fa Zhang
- School of Medical Technology, Beijing Institute of Technology, Beijing 100081, China
| | - Fan Xu
- Advanced Research Institute of Multidisciplinary Science, Beijing Institute of Technology, Beijing 100081, China
- School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China
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3
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Liu S, Chen J, Hellgoth J, Müller LR, Ferdman B, Karras C, Xiao D, Lidke KA, Heintzmann R, Shechtman Y, Li Y, Ries J. Universal inverse modeling of point spread functions for SMLM localization and microscope characterization. Nat Methods 2024; 21:1082-1093. [PMID: 38831208 DOI: 10.1038/s41592-024-02282-x] [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: 10/26/2023] [Accepted: 04/16/2024] [Indexed: 06/05/2024]
Abstract
The point spread function (PSF) of a microscope describes the image of a point emitter. Knowing the accurate PSF model is essential for various imaging tasks, including single-molecule localization, aberration correction and deconvolution. Here we present universal inverse modeling of point spread functions (uiPSF), a toolbox to infer accurate PSF models from microscopy data, using either image stacks of fluorescent beads or directly images of blinking fluorophores, the raw data in single-molecule localization microscopy (SMLM). Our modular framework is applicable to a variety of microscope modalities and the PSF model incorporates system- or sample-specific characteristics, for example, the bead size, field- and depth- dependent aberrations, and transformations among channels. We demonstrate its application in single or multiple channels or large field-of-view SMLM systems, 4Pi-SMLM, and lattice light-sheet microscopes using either bead data or single-molecule blinking data.
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Affiliation(s)
- Sheng Liu
- Department of Physics and Astronomy, University of New Mexico, Albuquerque, NM, USA
- European Molecular Biology Laboratory, Cell Biology and Biophysics, Heidelberg, Germany
| | - Jianwei Chen
- Department of Biomedical Engineering, Guangdong Provincial Key Laboratory of Advanced Biomaterials, Southern University of Science and Technology, Shenzhen, China
- Collaboration for joint PhD degree between Southern University of Science and Technology and Harbin Institute of Technology, Harbin, China
| | - Jonas Hellgoth
- European Molecular Biology Laboratory, Cell Biology and Biophysics, Heidelberg, Germany
- Faculty of Biosciences, Collaboration for joint PhD degree from EMBL and Heidelberg University, Heidelberg, Germany
| | - Lucas-Raphael Müller
- European Molecular Biology Laboratory, Cell Biology and Biophysics, Heidelberg, Germany
- Machine Learning in Science, Excellence Cluster Machine Learning, University of Tübingen, Tübingen, Germany
| | - Boris Ferdman
- Department of Biomedical Engineering, Technion-Israel Institute of Technology, Haifa, Israel
| | - Christian Karras
- Leibniz Institute of Photonic Technology, Jena, Germany
- JENOPTIK Optical Systems, Jena, Germany
| | - Dafei Xiao
- Russell Berrie Nanotechnology Institute, Technion-Israel Institute of Technology, Haifa, Israel
| | - Keith A Lidke
- Department of Physics and Astronomy, University of New Mexico, Albuquerque, NM, USA
| | - Rainer Heintzmann
- Leibniz Institute of Photonic Technology, Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller-University Jena, Jena, Germany
| | - Yoav Shechtman
- Department of Biomedical Engineering, Technion-Israel Institute of Technology, Haifa, Israel
- Department of Mechanical Engineering, The University of Texas at Austin, Austin, TX, USA
| | - Yiming Li
- Department of Biomedical Engineering, Guangdong Provincial Key Laboratory of Advanced Biomaterials, Southern University of Science and Technology, Shenzhen, China.
| | - Jonas Ries
- European Molecular Biology Laboratory, Cell Biology and Biophysics, Heidelberg, Germany.
- Max Perutz Labs, Vienna Biocenter Campus, Vienna, Austria.
- Department of Structural and Computational Biology, Center for Molecular Biology, University of Vienna, Vienna, Austria.
- Faculty of Physics, University of Vienna, Vienna, Austria.
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4
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Power RM, Tschanz A, Zimmermann T, Ries J. Build and operation of a custom 3D, multicolor, single-molecule localization microscope. Nat Protoc 2024:10.1038/s41596-024-00989-x. [PMID: 38702387 DOI: 10.1038/s41596-024-00989-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Accepted: 02/19/2024] [Indexed: 05/06/2024]
Abstract
Single-molecule localization microscopy (SMLM) enables imaging scientists to visualize biological structures with unprecedented resolution. Particularly powerful implementations of SMLM are capable of three-dimensional, multicolor and high-throughput imaging and can yield key biological insights. However, widespread access to these technologies is limited, primarily by the cost of commercial options and complexity of de novo development of custom systems. Here we provide a comprehensive guide for interested researchers who wish to establish a high-end, custom-built SMLM setup in their laboratories. We detail the initial configuration and subsequent assembly of the SMLM, including the instructions for the alignment of all the optical pathways, the software and hardware integration, and the operation of the instrument. We describe the validation steps, including the preparation and imaging of test and biological samples with structures of well-defined geometries, and assist the user in troubleshooting and benchmarking the system's performance. Additionally, we provide a walkthrough of the reconstruction of a super-resolved dataset from acquired raw images using the Super-resolution Microscopy Analysis Platform. Depending on the instrument configuration, the cost of the components is in the range US$95,000-180,000, similar to other open-source advanced SMLMs, and substantially lower than the cost of a commercial instrument. A builder with some experience of optical systems is expected to require 4-8 months from the start of the system construction to attain high-quality three-dimensional and multicolor biological images.
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Affiliation(s)
- Rory M Power
- EMBL Imaging Centre, EMBL Heidelberg, Heidelberg, Germany.
| | - Aline Tschanz
- Cell Biology and Biophysics Unit, EMBL Heidelberg, Heidelberg, Germany
| | - Timo Zimmermann
- EMBL Imaging Centre, EMBL Heidelberg, Heidelberg, Germany
- Cell Biology and Biophysics Unit, EMBL Heidelberg, Heidelberg, Germany
| | - Jonas Ries
- Cell Biology and Biophysics Unit, EMBL Heidelberg, Heidelberg, Germany.
- Max Perutz Labs, Vienna Biocenter Campus, Vienna, Austria.
- University of Vienna, Center for Molecular Biology, Department of Structural and Computational Biology, Vienna, Austria.
- University of Vienna, Faculty of Physics, Vienna, Austria.
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5
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Rames M, Kenison JP, Heineck D, Civitci F, Szczepaniak M, Zheng T, Shangguan J, Zhang Y, Tao K, Esener S, Nan X. Multiplexed and Millimeter-Scale Fluorescence Nanoscopy of Cells and Tissue Sections via Prism-Illumination and Microfluidics-Enhanced DNA-PAINT. CHEMICAL & BIOMEDICAL IMAGING 2023; 1:817-830. [PMID: 38155726 PMCID: PMC10751790 DOI: 10.1021/cbmi.3c00060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 07/24/2023] [Accepted: 08/18/2023] [Indexed: 12/30/2023]
Abstract
Fluorescence nanoscopy has become increasingly powerful for biomedical research, but it has historically afforded a small field-of-view (FOV) of around 50 μm × 50 μm at once and more recently up to ∼200 μm × 200 μm. Efforts to further increase the FOV in fluorescence nanoscopy have thus far relied on the use of fabricated waveguide substrates, adding cost and sample constraints to the applications. Here we report PRism-Illumination and Microfluidics-Enhanced DNA-PAINT (PRIME-PAINT) for multiplexed fluorescence nanoscopy across millimeter-scale FOVs. Built upon the well-established prism-type total internal reflection microscopy, PRIME-PAINT achieves robust single-molecule localization with up to ∼520 μm × 520 μm single FOVs and 25-40 nm lateral resolutions. Through stitching, nanoscopic imaging over mm2 sample areas can be completed in as little as 40 min per target. An on-stage microfluidics chamber facilitates probe exchange for multiplexing and enhances image quality, particularly for formalin-fixed paraffin-embedded (FFPE) tissue sections. We demonstrate the utility of PRIME-PAINT by analyzing ∼106 caveolae structures in ∼1,000 cells and imaging entire pancreatic cancer lesions from patient tissue biopsies. By imaging from nanometers to millimeters with multiplexity and broad sample compatibility, PRIME-PAINT will be useful for building multiscale, Google-Earth-like views of biological systems.
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Affiliation(s)
- Matthew
J. Rames
- Cancer
Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health & Science University, 2720 South Moody Avenue, Portland, Oregon 97201, United States
- Program
in Quantitative and Systems Biology, Department of Biomedical Engineering, Oregon Health & Science University, 2730 South Moody Avenue, Portland, Oregon 97201, United States
| | - John P. Kenison
- Cancer
Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health & Science University, 2720 South Moody Avenue, Portland, Oregon 97201, United States
| | - Daniel Heineck
- Cancer
Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health & Science University, 2720 South Moody Avenue, Portland, Oregon 97201, United States
- Program
in Quantitative and Systems Biology, Department of Biomedical Engineering, Oregon Health & Science University, 2730 South Moody Avenue, Portland, Oregon 97201, United States
| | - Fehmi Civitci
- Cancer
Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health & Science University, 2720 South Moody Avenue, Portland, Oregon 97201, United States
| | - Malwina Szczepaniak
- Program
in Quantitative and Systems Biology, Department of Biomedical Engineering, Oregon Health & Science University, 2730 South Moody Avenue, Portland, Oregon 97201, United States
| | - Ting Zheng
- Cancer
Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health & Science University, 2720 South Moody Avenue, Portland, Oregon 97201, United States
| | - Julia Shangguan
- Program
in Quantitative and Systems Biology, Department of Biomedical Engineering, Oregon Health & Science University, 2730 South Moody Avenue, Portland, Oregon 97201, United States
| | - Yujia Zhang
- Cancer
Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health & Science University, 2720 South Moody Avenue, Portland, Oregon 97201, United States
- Program
in Quantitative and Systems Biology, Department of Biomedical Engineering, Oregon Health & Science University, 2730 South Moody Avenue, Portland, Oregon 97201, United States
| | - Kai Tao
- Program
in Quantitative and Systems Biology, Department of Biomedical Engineering, Oregon Health & Science University, 2730 South Moody Avenue, Portland, Oregon 97201, United States
| | - Sadik Esener
- Cancer
Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health & Science University, 2720 South Moody Avenue, Portland, Oregon 97201, United States
- Program
in Quantitative and Systems Biology, Department of Biomedical Engineering, Oregon Health & Science University, 2730 South Moody Avenue, Portland, Oregon 97201, United States
| | - Xiaolin Nan
- Cancer
Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health & Science University, 2720 South Moody Avenue, Portland, Oregon 97201, United States
- Program
in Quantitative and Systems Biology, Department of Biomedical Engineering, Oregon Health & Science University, 2730 South Moody Avenue, Portland, Oregon 97201, United States
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6
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Haghparast S, Stallinga S, Rieger B. Detecting continuous structural heterogeneity in single-molecule localization microscopy data. Sci Rep 2023; 13:19800. [PMID: 37957186 PMCID: PMC10643625 DOI: 10.1038/s41598-023-46488-z] [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: 04/28/2023] [Accepted: 11/01/2023] [Indexed: 11/15/2023] Open
Abstract
Fusion of multiple chemically identical complexes, so-called particles, in localization microscopy, can improve the signal-to-noise ratio and overcome under-labeling. To this end, structural homogeneity of the data must be assumed. Biological heterogeneity, however, could be present in the data originating from distinct conformational variations or (continuous) variations in particle shapes. We present a prior-knowledge-free method for detecting continuous structural variations with localization microscopy. Detecting this heterogeneity leads to more faithful fusions and reconstructions of the localization microscopy data as their heterogeneity is taken into account. In experimental datasets, we show the continuous variation of the height of DNA origami tetrahedrons imaged with 3D PAINT and of the radius of Nuclear Pore Complexes imaged in 2D with STORM. In simulation, we study the impact on the heterogeneity detection pipeline of Degree Of Labeling and of structural variations in the form of two independent modes.
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Affiliation(s)
- Sobhan Haghparast
- Department of Imaging Physics, Delft University of Technology, 2628 CJ, Delft, The Netherlands
| | - Sjoerd Stallinga
- Department of Imaging Physics, Delft University of Technology, 2628 CJ, Delft, The Netherlands.
| | - Bernd Rieger
- Department of Imaging Physics, Delft University of Technology, 2628 CJ, Delft, The Netherlands.
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7
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Liu S, Chen J, Hellgoth J, Müller LR, Ferdman B, Karras C, Xiao D, Lidke KA, Heintzmann R, Shechtman Y, Li Y, Ries J. Universal inverse modelling of point spread functions for SMLM localization and microscope characterization. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.26.564064. [PMID: 37961269 PMCID: PMC10634843 DOI: 10.1101/2023.10.26.564064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
The point spread function (PSF) of a microscope describes the image of a point emitter. Knowing the accurate PSF model is essential for various imaging tasks, including single molecule localization, aberration correction and deconvolution. Here we present uiPSF (universal inverse modelling of Point Spread Functions), a toolbox to infer accurate PSF models from microscopy data, using either image stacks of fluorescent beads or directly images of blinking fluorophores, the raw data in single molecule localization microscopy (SMLM). The resulting PSF model enables accurate 3D super-resolution imaging using SMLM. Additionally, uiPSF can be used to characterize and optimize a microscope system by quantifying the aberrations, including field-dependent aberrations, and resolutions. Our modular framework is applicable to a variety of microscope modalities and the PSF model incorporates system or sample specific characteristics, e.g., the bead size, depth dependent aberrations and transformations among channels. We demonstrate its application in single or multiple channels or large field-of-view SMLM systems, 4Pi-SMLM, and lattice light-sheet microscopes using either bead data or single molecule blinking data.
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Affiliation(s)
- Sheng Liu
- Department of Physics and Astronomy, University of New Mexico, Albuquerque, NM, USA
| | - Jianwei Chen
- Department of Biomedical Engineering, Guangdong Provincial Key Laboratory of Advanced Biomaterials, Southern University of Science and Technology, Shenzhen, China
- Collaboration for joint PhD degree between Southern University of Science and Technology and Harbin Institute of Technology, Harbin, 150001, China
| | - Jonas Hellgoth
- European Molecular Biology Laboratory, Cell Biology and Biophysics, Heidelberg, Germany
| | - Lucas-Raphael Müller
- European Molecular Biology Laboratory, Cell Biology and Biophysics, Heidelberg, Germany
| | - Boris Ferdman
- Department of Biomedical Engineering, Technion–Israel Institute of Technology, Haifa, Israel
| | - Christian Karras
- Leibniz Institute of Photonic Technology, Albert-Einstein-Straße 9, 07745, Jena, Germany
- Currently at JENOPTIK Optical Systems GmbH, Jena, Germany
| | - Dafei Xiao
- Department of Biomedical Engineering, Technion–Israel Institute of Technology, Haifa, Israel
| | - Keith A. Lidke
- Department of Physics and Astronomy, University of New Mexico, Albuquerque, NM, USA
| | - Rainer Heintzmann
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller-University Jena, Jena, Germany
- Leibniz Institute of Photonic Technology, Albert-Einstein-Straße 9, 07745, Jena, Germany
| | - Yoav Shechtman
- Department of Biomedical Engineering, Technion–Israel Institute of Technology, Haifa, Israel
- Department of Mechanical Engineering, The University of Texas at Austin, Austin, TX, USA
| | - Yiming Li
- Department of Biomedical Engineering, Guangdong Provincial Key Laboratory of Advanced Biomaterials, Southern University of Science and Technology, Shenzhen, China
| | - Jonas Ries
- European Molecular Biology Laboratory, Cell Biology and Biophysics, Heidelberg, Germany
- Max Perutz Labs, Vienna Biocenter Campus (VBC), Dr.-Bohr-Gasse 9, 1030, Vienna, Austria
- University of Vienna, Center for Molecular Biology, Department of Structural and Computational Biology, Dr.-Bohr-Gasse 9, 1030, Vienna, Austria
- University of Vienna, Faculty of Physics, Boltzmanngasse 5, 1090 Vienna, Austria
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8
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Theiss M, Hériché JK, Russell C, Helekal D, Soppitt A, Ries J, Ellenberg J, Brazma A, Uhlmann V. Simulating structurally variable nuclear pore complexes for microscopy. Bioinformatics 2023; 39:btad587. [PMID: 37756700 PMCID: PMC10570993 DOI: 10.1093/bioinformatics/btad587] [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: 04/27/2023] [Revised: 09/08/2023] [Accepted: 09/22/2023] [Indexed: 09/29/2023] Open
Abstract
MOTIVATION The nuclear pore complex (NPC) is the only passageway for macromolecules between nucleus and cytoplasm, and an important reference standard in microscopy: it is massive and stereotypically arranged. The average architecture of NPC proteins has been resolved with pseudoatomic precision, however observed NPC heterogeneities evidence a high degree of divergence from this average. Single-molecule localization microscopy (SMLM) images NPCs at protein-level resolution, whereupon image analysis software studies NPC variability. However, the true picture of this variability is unknown. In quantitative image analysis experiments, it is thus difficult to distinguish intrinsically high SMLM noise from variability of the underlying structure. RESULTS We introduce CIR4MICS ('ceramics', Configurable, Irregular Rings FOR MICroscopy Simulations), a pipeline that synthesizes ground truth datasets of structurally variable NPCs based on architectural models of the true NPC. Users can select one or more N- or C-terminally tagged NPC proteins, and simulate a wide range of geometric variations. We also represent the NPC as a spring-model such that arbitrary deforming forces, of user-defined magnitudes, simulate irregularly shaped variations. Further, we provide annotated reference datasets of simulated human NPCs, which facilitate a side-by-side comparison with real data. To demonstrate, we synthetically replicate a geometric analysis of real NPC radii and reveal that a range of simulated variability parameters can lead to observed results. Our simulator is therefore valuable to test the capabilities of image analysis methods, as well as to inform experimentalists about the requirements of hypothesis-driven imaging studies. AVAILABILITY AND IMPLEMENTATION Code: https://github.com/uhlmanngroup/cir4mics. Simulated data: BioStudies S-BSST1058.
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Affiliation(s)
- Maria Theiss
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, CB10 1SD, United Kingdom
| | - Jean-Karim Hériché
- Cell Biology and Biophysics Unit, European Molecular Biology Laboratory (EMBL), Heidelberg 69117, Germany
| | - Craig Russell
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, CB10 1SD, United Kingdom
| | - David Helekal
- Centre for Doctoral Training in Mathematics for Real-World Systems, University of Warwick, Coventry CV4 7AL, United Kingdom
| | - Alisdair Soppitt
- EPSRC Centre for Doctoral Training in Modelling of Heterogeneous Systems, University of Warwick, Coventry CV4 7AL, United Kingdom
| | - Jonas Ries
- Cell Biology and Biophysics Unit, European Molecular Biology Laboratory (EMBL), Heidelberg 69117, Germany
- Max Perutz Labs, University of Vienna, Department of Structural and Computational Biology, Dr.-Bohr-Gasse 9, Vienna 1030, Austria
| | - Jan Ellenberg
- Cell Biology and Biophysics Unit, European Molecular Biology Laboratory (EMBL), Heidelberg 69117, Germany
| | - Alvis Brazma
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, CB10 1SD, United Kingdom
| | - Virginie Uhlmann
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, CB10 1SD, United Kingdom
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9
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Fernando SI, Martineau JT, Hobson RJ, Vu TN, Baker B, Mueller BD, Menon R, Jorgensen EM, Gerton JM. Simultaneous spectral differentiation of multiple fluorophores in super-resolution imaging using a glass phase plate. OPTICS EXPRESS 2023; 31:33565-33581. [PMID: 37859135 PMCID: PMC10544955 DOI: 10.1364/oe.499929] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 09/05/2023] [Accepted: 09/10/2023] [Indexed: 10/21/2023]
Abstract
By engineering the point-spread function (PSF) of single molecules, different fluorophore species can be imaged simultaneously and distinguished by their unique PSF patterns. Here, we insert a silicon-dioxide phase plate at the Fourier plane of the detection path of a wide-field fluorescence microscope to produce distinguishable PSFs (X-PSFs) at different wavelengths. We demonstrate that the resulting PSFs can be localized spatially and spectrally using a maximum-likelihood estimation algorithm and can be utilized for hyper-spectral super-resolution microscopy of biological samples. We produced superresolution images of fixed U2OS cells using X-PSFs for dSTORM imaging with simultaneous illumination of up to three fluorophore species. The species were distinguished only by the PSF pattern. We achieved ∼21-nm lateral localization precision (FWHM) and ∼17-nm axial precision (FWHM) with an average of 1,800 - 3,500 photons per PSF and a background as high as 130 - 400 photons per pixel. The modified PSF distinguished fluorescent probes with ∼80 nm separation between spectral peaks.
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Affiliation(s)
- Sanduni I. Fernando
- University of Utah Department of Physics and Astronomy, 201 James Fletcher Bldg. 115 S. 1400 E Salt Lake City, UT 84112-0830, USA
| | - Jason T. Martineau
- University of Utah Department of Physics and Astronomy, 201 James Fletcher Bldg. 115 S. 1400 E Salt Lake City, UT 84112-0830, USA
| | - Robert J. Hobson
- University of Utah School of Biological Sciences, 257 South 1400 East Salt Lake City, Utah 84112, USA
| | - Thien N. Vu
- University of Utah School of Biological Sciences, 257 South 1400 East Salt Lake City, Utah 84112, USA
| | - Brian Baker
- University of Utah Nanofab 36 S. Wasatch Drive, SMBB Room 2500 Salt Lake City, UT 84112, USA
| | - Brian D. Mueller
- University of Utah School of Biological Sciences, 257 South 1400 East Salt Lake City, Utah 84112, USA
| | - Rajesh Menon
- University of Utah Department of Electrical and Computer Engineering 50 S. Central Campus Drive, MEB Room 2110 Salt Lake City, UT 84112, USA
| | - Erik M. Jorgensen
- University of Utah School of Biological Sciences, 257 South 1400 East Salt Lake City, Utah 84112, USA
| | - Jordan M. Gerton
- University of Utah Department of Physics and Astronomy, 201 James Fletcher Bldg. 115 S. 1400 E Salt Lake City, UT 84112-0830, USA
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10
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Wang W, Jakobi A, Wu YL, Ries J, Stallinga S, Rieger B. Particle fusion of super-resolution data reveals the unit structure of Nup96 in Nuclear Pore Complex. Sci Rep 2023; 13:13327. [PMID: 37587192 PMCID: PMC10432550 DOI: 10.1038/s41598-023-39829-5] [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: 04/25/2023] [Accepted: 07/31/2023] [Indexed: 08/18/2023] Open
Abstract
Single molecule localization microscopy offers resolution nearly down to the molecular level with specific molecular labelling, and is thereby a promising tool for structural biology. In practice, however, the actual value to this field is limited primarily by incomplete fluorescent labelling of the structure. This missing information can be completed by merging information from many structurally identical particles in a particle fusion approach similar to cryo-EM single-particle analysis. In this paper, we present a data analysis of particle fusion results of fluorescently labelled Nup96 nucleoporins in the Nuclear Pore Complex to show that Nup96 occurs in a spatial arrangement of two rings of 8 units with two Nup96 copies per unit giving a total of 32 Nup96 copies per pore. We use Artificial Intelligence assisted modeling in Alphafold to extend the existing cryo-EM model of Nup96 to accurately pinpoint the positions of the fluorescent labels and show the accuracy of the match between fluorescent and cryo-EM data to be better than 3 nm in-plane and 5 nm out-of-plane.
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Affiliation(s)
- Wenxiu Wang
- Faculty of Applied Sciences, Delft University of Technology, Delft, The Netherlands
| | - Arjen Jakobi
- Faculty of Applied Sciences, Delft University of Technology, Delft, The Netherlands
| | - Yu-Le Wu
- Cell Biology and Biophysics Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
| | - Jonas Ries
- Department of Chromosome Biology, University of Vienna, Max-Perutz Labs, Center for Molecular Biology, Vienna, Austria
| | - Sjoerd Stallinga
- Faculty of Applied Sciences, Delft University of Technology, Delft, The Netherlands.
| | - Bernd Rieger
- Faculty of Applied Sciences, Delft University of Technology, Delft, The Netherlands.
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11
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Hugelier S, Kim H, Gyparaki MT, Bond C, Tang Q, Santiago-Ruiz AN, Porta S, Lakadamyali M. ECLiPSE: A Versatile Classification Technique for Structural and Morphological Analysis of Super-Resolution Microscopy Data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.10.540077. [PMID: 37215010 PMCID: PMC10197633 DOI: 10.1101/2023.05.10.540077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
We introduce a new automated machine learning analysis pipeline to precisely classify cellular structures captured through single molecule localization microscopy, which we call ECLiPSE (Enhanced Classification of Localized Pointclouds by Shape Extraction). ECLiPSE leverages 67 comprehensive shape descriptors encompassing geometric, boundary, skeleton and other properties, the majority of which are directly extracted from the localizations to accurately characterize individual structures. We validate ECLiPSE through unsupervised and supervised classification on a dataset featuring five distinct cellular structures, achieving exceptionally high classification accuracies nearing 100%. Moreover, we demonstrate the versatility of our approach by applying it to two novel biological applications: quantifying the clearance of tau protein aggregates, a critical marker for neurodegenerative diseases, and differentiating between two distinct morphological features (morphotypes) of TAR DNA-binding protein 43 proteinopathy, potentially associated to different TDP-43 strains, each exhibiting unique seeding and spreading properties. We anticipate that this versatile approach will significantly enhance the way we study cellular structures across various biological contexts, elucidating their roles in disease development and progression.
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Reinhardt SCM, Masullo LA, Baudrexel I, Steen PR, Kowalewski R, Eklund AS, Strauss S, Unterauer EM, Schlichthaerle T, Strauss MT, Klein C, Jungmann R. Ångström-resolution fluorescence microscopy. Nature 2023; 617:711-716. [PMID: 37225882 PMCID: PMC10208979 DOI: 10.1038/s41586-023-05925-9] [Citation(s) in RCA: 47] [Impact Index Per Article: 47.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 03/07/2023] [Indexed: 05/26/2023]
Abstract
Fluorescence microscopy, with its molecular specificity, is one of the major characterization methods used in the life sciences to understand complex biological systems. Super-resolution approaches1-6 can achieve resolution in cells in the range of 15 to 20 nm, but interactions between individual biomolecules occur at length scales below 10 nm and characterization of intramolecular structure requires Ångström resolution. State-of-the-art super-resolution implementations7-14 have demonstrated spatial resolutions down to 5 nm and localization precisions of 1 nm under certain in vitro conditions. However, such resolutions do not directly translate to experiments in cells, and Ångström resolution has not been demonstrated to date. Here we introdue a DNA-barcoding method, resolution enhancement by sequential imaging (RESI), that improves the resolution of fluorescence microscopy down to the Ångström scale using off-the-shelf fluorescence microscopy hardware and reagents. By sequentially imaging sparse target subsets at moderate spatial resolutions of >15 nm, we demonstrate that single-protein resolution can be achieved for biomolecules in whole intact cells. Furthermore, we experimentally resolve the DNA backbone distance of single bases in DNA origami with Ångström resolution. We use our method in a proof-of-principle demonstration to map the molecular arrangement of the immunotherapy target CD20 in situ in untreated and drug-treated cells, which opens possibilities for assessing the molecular mechanisms of targeted immunotherapy. These observations demonstrate that, by enabling intramolecular imaging under ambient conditions in whole intact cells, RESI closes the gap between super-resolution microscopy and structural biology studies and thus delivers information key to understanding complex biological systems.
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Affiliation(s)
- Susanne C M Reinhardt
- Max Planck Institute of Biochemistry, Planegg, Germany
- Faculty of Physics and Center for NanoScience, Ludwig Maximilian University, Munich, Germany
| | | | - Isabelle Baudrexel
- Max Planck Institute of Biochemistry, Planegg, Germany
- Department of Chemistry and Biochemistry, Ludwig Maximilian University, Munich, Germany
| | - Philipp R Steen
- Max Planck Institute of Biochemistry, Planegg, Germany
- Faculty of Physics and Center for NanoScience, Ludwig Maximilian University, Munich, Germany
| | - Rafal Kowalewski
- Max Planck Institute of Biochemistry, Planegg, Germany
- Faculty of Physics and Center for NanoScience, Ludwig Maximilian University, Munich, Germany
| | - Alexandra S Eklund
- Max Planck Institute of Biochemistry, Planegg, Germany
- Department of Chemistry and Biochemistry, Ludwig Maximilian University, Munich, Germany
| | - Sebastian Strauss
- Max Planck Institute of Biochemistry, Planegg, Germany
- Faculty of Physics and Center for NanoScience, Ludwig Maximilian University, Munich, Germany
| | - Eduard M Unterauer
- Max Planck Institute of Biochemistry, Planegg, Germany
- Faculty of Physics and Center for NanoScience, Ludwig Maximilian University, Munich, Germany
| | - Thomas Schlichthaerle
- Max Planck Institute of Biochemistry, Planegg, Germany
- Faculty of Physics and Center for NanoScience, Ludwig Maximilian University, Munich, Germany
| | - Maximilian T Strauss
- Max Planck Institute of Biochemistry, Planegg, Germany
- Faculty of Physics and Center for NanoScience, Ludwig Maximilian University, Munich, Germany
| | - Christian Klein
- Department of Chemistry and Biochemistry, Ludwig Maximilian University, Munich, Germany
- Roche Innovation Center Zurich, Roche Pharma Research and Early Development, Schlieren, Switzerland
| | - Ralf Jungmann
- Max Planck Institute of Biochemistry, Planegg, Germany.
- Faculty of Physics and Center for NanoScience, Ludwig Maximilian University, Munich, Germany.
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13
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Mund M, Tschanz A, Wu YL, Frey F, Mehl JL, Kaksonen M, Avinoam O, Schwarz US, Ries J. Clathrin coats partially preassemble and subsequently bend during endocytosis. J Cell Biol 2023; 222:213855. [PMID: 36734980 PMCID: PMC9929656 DOI: 10.1083/jcb.202206038] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Revised: 11/29/2022] [Accepted: 12/27/2022] [Indexed: 02/04/2023] Open
Abstract
Eukaryotic cells use clathrin-mediated endocytosis to take up a large range of extracellular cargo. During endocytosis, a clathrin coat forms on the plasma membrane, but it remains controversial when and how it is remodeled into a spherical vesicle. Here, we use 3D superresolution microscopy to determine the precise geometry of the clathrin coat at large numbers of endocytic sites. Through pseudo-temporal sorting, we determine the average trajectory of clathrin remodeling during endocytosis. We find that clathrin coats assemble first on flat membranes to 50% of the coat area before they become rapidly and continuously bent, and this mechanism is confirmed in three cell lines. We introduce the cooperative curvature model, which is based on positive feedback for curvature generation. It accurately describes the measured shapes and dynamics of the clathrin coat and could represent a general mechanism for clathrin coat remodeling on the plasma membrane.
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Affiliation(s)
- Markus Mund
- https://ror.org/03mstc592Cell Biology and Biophysics, European Molecular Biology Laboratory, Heidelberg, Germany,https://ror.org/01swzsf04Department of Biochemistry, University of Geneva, Geneva, Switzerland
| | - Aline Tschanz
- https://ror.org/03mstc592Cell Biology and Biophysics, European Molecular Biology Laboratory, Heidelberg, Germany,Candidate for Joint PhD Programme of EMBL and University of Heidelberg, Heidelberg, Germany
| | - Yu-Le Wu
- https://ror.org/03mstc592Cell Biology and Biophysics, European Molecular Biology Laboratory, Heidelberg, Germany,Candidate for Joint PhD Programme of EMBL and University of Heidelberg, Heidelberg, Germany
| | - Felix Frey
- https://ror.org/02e2c7k09Kavli Institute of Nanoscience, Department of Bionanoscience, Delft University of Technology, Delft, Netherlands
| | - Johanna L. Mehl
- https://ror.org/03mstc592Cell Biology and Biophysics, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Marko Kaksonen
- https://ror.org/01swzsf04Department of Biochemistry, University of Geneva, Geneva, Switzerland,NCCR Chemical Biology, University of Geneva, Geneva, Switzerland
| | - Ori Avinoam
- https://ror.org/03mstc592Cell Biology and Biophysics, European Molecular Biology Laboratory, Heidelberg, Germany,https://ror.org/0316ej306Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel
| | - Ulrich S. Schwarz
- https://ror.org/04rcqnp59Institute for Theoretical Physics and Bioquant, Heidelberg University, Heidelberg, Germany,Bioquant, Heidelberg University, Heidelberg, Germany
| | - Jonas Ries
- https://ror.org/03mstc592Cell Biology and Biophysics, European Molecular Biology Laboratory, Heidelberg, Germany,Correspondence to Jonas Ries:
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