1
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Senftleben ML, Bajor A, Hirata E, Abrahamsson S, Brismar H. Fast volumetric multifocus structured illumination microscopy of subcellular dynamics in living cells. BIOMEDICAL OPTICS EXPRESS 2024; 15:2281-2292. [PMID: 38633103 PMCID: PMC11019691 DOI: 10.1364/boe.516261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 02/21/2024] [Accepted: 03/04/2024] [Indexed: 04/19/2024]
Abstract
Studying the nanoscale dynamics of subcellular structures is possible with 2D structured illumination microscopy (SIM). The method allows for acquisition with improved resolution over typical widefield. For 3D samples, the acquisition speed is inherently limited by the need to acquire sequential two-dimensional planes to create a volume. Here, we present a development of multifocus SIM designed to provide high volumetric frame rate by using fast synchronized electro-optical components. We demonstrate the high volumetric imaging capacity of the microscope by recording the dynamics of microtubule and endoplasmatic reticulum in living cells at up to 2.3 super resolution volumes per second for a total volume of 30 × 30 × 1.8 µm3.
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Affiliation(s)
- Maximilian Lukas Senftleben
- Department of Applied Physics, KTH Royal Institute of Technology, Science for Life Laboratory, Stockholm, Sweden
| | - Antone Bajor
- Baskin School of Engineering, University of California Santa Cruz, 1156 High Street, Santa Cruz, 95064, CA, USA
| | - Eduardo Hirata
- Department of Applied Physics, KTH Royal Institute of Technology, Science for Life Laboratory, Stockholm, Sweden
| | - Sara Abrahamsson
- Baskin School of Engineering, University of California Santa Cruz, 1156 High Street, Santa Cruz, 95064, CA, USA
| | - Hjalmar Brismar
- Department of Applied Physics, KTH Royal Institute of Technology, Science for Life Laboratory, Stockholm, Sweden
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2
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Laine RF, Heil HS, Coelho S, Nixon-Abell J, Jimenez A, Wiesner T, Martínez D, Galgani T, Régnier L, Stubb A, Follain G, Webster S, Goyette J, Dauphin A, Salles A, Culley S, Jacquemet G, Hajj B, Leterrier C, Henriques R. High-fidelity 3D live-cell nanoscopy through data-driven enhanced super-resolution radial fluctuation. Nat Methods 2023; 20:1949-1956. [PMID: 37957430 PMCID: PMC10703683 DOI: 10.1038/s41592-023-02057-w] [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: 04/21/2022] [Accepted: 09/29/2023] [Indexed: 11/15/2023]
Abstract
Live-cell super-resolution microscopy enables the imaging of biological structure dynamics below the diffraction limit. Here we present enhanced super-resolution radial fluctuations (eSRRF), substantially improving image fidelity and resolution compared to the original SRRF method. eSRRF incorporates automated parameter optimization based on the data itself, giving insight into the trade-off between resolution and fidelity. We demonstrate eSRRF across a range of imaging modalities and biological systems. Notably, we extend eSRRF to three dimensions by combining it with multifocus microscopy. This realizes live-cell volumetric super-resolution imaging with an acquisition speed of ~1 volume per second. eSRRF provides an accessible super-resolution approach, maximizing information extraction across varied experimental conditions while minimizing artifacts. Its optimal parameter prediction strategy is generalizable, moving toward unbiased and optimized analyses in super-resolution microscopy.
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Affiliation(s)
- Romain F Laine
- Laboratory for Molecular Cell Biology, University College London, London, UK
- The Francis Crick Institute, London, UK
- Micrographia Bio, Translation and Innovation Hub, London, UK
| | - Hannah S Heil
- Optical Cell Biology, Instituto Gulbenkian de Ciência, Oeiras, Portugal
| | - Simao Coelho
- Optical Cell Biology, Instituto Gulbenkian de Ciência, Oeiras, Portugal
| | - Jonathon Nixon-Abell
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- Cambridge Institute for Medical Research, Cambridge Univeristy, Cambridge, UK
| | - Angélique Jimenez
- Aix-Marseille Université, CNRS, INP UMR7051, NeuroCyto, Marseille, France
| | - Theresa Wiesner
- Aix-Marseille Université, CNRS, INP UMR7051, NeuroCyto, Marseille, France
| | - Damián Martínez
- Optical Cell Biology, Instituto Gulbenkian de Ciência, Oeiras, Portugal
| | - Tommaso Galgani
- Laboratoire Physico-Chimie Curie, Institut Curie, PSL Research University, Sorbonne Université, CNRS UMR168, Paris, France
- Revvity Signals, Tres Cantos, Madrid, Spain
| | - Louise Régnier
- Laboratoire Physico-Chimie Curie, Institut Curie, PSL Research University, Sorbonne Université, CNRS UMR168, Paris, France
| | - Aki Stubb
- Turku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland
- Department of Cell and Tissue Dynamics, Max Planck Institute for Molecular Biomedicine, Munster, Germany
| | - Gautier Follain
- Turku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland
- Faculty of Science and Engineering, Cell Biology, Åbo Akademi University, Turku, Finland
| | - Samantha Webster
- EMBL Australia Node in Single Molecule Science, School of Biomedical Sciences, University of New South Wales, Sydney, New South Wales, Australia
| | - Jesse Goyette
- EMBL Australia Node in Single Molecule Science, School of Biomedical Sciences, University of New South Wales, Sydney, New South Wales, Australia
| | - Aurelien Dauphin
- Unite Genetique et Biologie du Développement U934, PICT-IBiSA, Institut Curie, INSERM, CNRS, PSL Research University, Paris, France
| | - Audrey Salles
- Institut Pasteur, Université Paris Cité, Unit of Technology and Service Photonic BioImaging (UTechS PBI), C2RT, Paris, France
| | - Siân Culley
- Laboratory for Molecular Cell Biology, University College London, London, UK
- Randall Centre for Cell and Molecular Biophysics, King's College London, Guy's Campus, London, UK
| | - Guillaume Jacquemet
- Turku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland
- Faculty of Science and Engineering, Cell Biology, Åbo Akademi University, Turku, Finland
- Turku Bioimaging, University of Turku and Åbo Akademi University, Turku, Finland
- InFLAMES Research Flagship Center, Åbo Akademi University, Turku, Finland
| | - Bassam Hajj
- Laboratoire Physico-Chimie Curie, Institut Curie, PSL Research University, Sorbonne Université, CNRS UMR168, Paris, France.
| | | | - Ricardo Henriques
- Laboratory for Molecular Cell Biology, University College London, London, UK.
- The Francis Crick Institute, London, UK.
- Optical Cell Biology, Instituto Gulbenkian de Ciência, Oeiras, Portugal.
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3
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Rationalized deep learning super-resolution microscopy for sustained live imaging of rapid subcellular processes. Nat Biotechnol 2023; 41:367-377. [PMID: 36203012 DOI: 10.1038/s41587-022-01471-3] [Citation(s) in RCA: 25] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Accepted: 08/12/2022] [Indexed: 12/12/2022]
Abstract
The goal when imaging bioprocesses with optical microscopy is to acquire the most spatiotemporal information with the least invasiveness. Deep neural networks have substantially improved optical microscopy, including image super-resolution and restoration, but still have substantial potential for artifacts. In this study, we developed rationalized deep learning (rDL) for structured illumination microscopy and lattice light sheet microscopy (LLSM) by incorporating prior knowledge of illumination patterns and, thereby, rationally guiding the network to denoise raw images. Here we demonstrate that rDL structured illumination microscopy eliminates spectral bias-induced resolution degradation and reduces model uncertainty by five-fold, improving the super-resolution information by more than ten-fold over other computational approaches. Moreover, rDL applied to LLSM enables self-supervised training by using the spatial or temporal continuity of noisy data itself, yielding results similar to those of supervised methods. We demonstrate the utility of rDL by imaging the rapid kinetics of motile cilia, nucleolar protein condensation during light-sensitive mitosis and long-term interactions between membranous and membrane-less organelles.
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4
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Portes M, Mangeat T, Escallier N, Dufrancais O, Raynaud-Messina B, Thibault C, Maridonneau-Parini I, Vérollet C, Poincloux R. Nanoscale architecture and coordination of actin cores within the sealing zone of human osteoclasts. eLife 2022; 11:75610. [PMID: 35727134 PMCID: PMC9255968 DOI: 10.7554/elife.75610] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Accepted: 06/20/2022] [Indexed: 11/13/2022] Open
Abstract
Osteoclasts are unique in their capacity to degrade bone tissue. To achieve this process, osteoclasts form a specific structure called the sealing zone, which creates a close contact with bone and confines the release of protons and hydrolases for bone degradation. The sealing zone is composed of actin structures called podosomes nested in a dense actin network. The organization of these actin structures inside the sealing zone at the nano scale is still unknown. Here, we combine cutting-edge microscopy methods to reveal the nanoscale architecture and dynamics of the sealing zone formed by human osteoclasts on bone surface. Random illumination microscopy allowed the identification and live imaging of densely packed actin cores within the sealing zone. A cross-correlation analysis of the fluctuations of actin content at these cores indicates that they are locally synchronized. Further examination shows that the sealing zone is composed of groups of synchronized cores linked by a-actinin1 positive filaments, and encircled by adhesion complexes. Thus, we propose that the confinement of bone degradation mediators is achieved through the coordination of islets of actin cores and not by the global coordination of all podosomal subunits forming the sealing zone.
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Affiliation(s)
- Marion Portes
- Institute de Pharmacologie et de Biologie Structurale (IPBS), Université de Toulouse, CNRS, UPS, Toulouse, France
| | - Thomas Mangeat
- Centre de Biologie Intégrative, Université de Toulouse, CNRS, Toulouse, France
| | - Natacha Escallier
- Institute de Pharmacologie et de Biologie Structurale (IPBS), Université de Toulouse, CNRS, UPS, Toulouse, France
| | - Ophélie Dufrancais
- Institute de Pharmacologie et de Biologie Structurale (IPBS), Université de Toulouse, CNRS, UPS, Toulouse, France
| | - Brigitte Raynaud-Messina
- Institute de Pharmacologie et de Biologie Structurale (IPBS), Université de Toulouse, CNRS, UPS, Toulouse, France
| | - Christophe Thibault
- Laboratoire d'analyse et d'architectures des systèmes (LAAS), Université de Toulouse, CNRS, Toulouse, France
| | - Isabelle Maridonneau-Parini
- Institute de Pharmacologie et de Biologie Structurale (IPBS), Université de Toulouse, CNRS, UPS, Toulouse, France
| | - Christel Vérollet
- Institute de Pharmacologie et de Biologie Structurale (IPBS), Université de Toulouse, CNRS, UPS, Toulouse, France
| | - Renaud Poincloux
- Institute de Pharmacologie et de Biologie Structurale (IPBS), Université de Toulouse, CNRS, UPS, Toulouse, France
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5
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Ma Y, Wang Y, Ma L, Zheng J, Liu M, Gao P. Reflectional quantitative phase-contrast microscopy (RQPCM) with annular epi-illumination. APPLIED OPTICS 2022; 61:3641-3647. [PMID: 36256403 DOI: 10.1364/ao.451761] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Accepted: 03/30/2022] [Indexed: 06/16/2023]
Abstract
Quantitative phase microscopy (QPM) is a label-free microscopic technique that exploits the phase of a wave passing through a sample; hence, it has been applied to many fields, including biomedical research and industrial inspection. However, the high spatiotemporal resolution imaging of reflective samples still challenges conventional transmission QPM. In this paper, we propose reflectional quantitative phase-contrast microscopy based on annular epi-illumination of light-emitting diodes. The unscattered wave from the sample is successively phase-retarded by 0, π/2, π, and 3π/2 through a spatial light modulator, and high-resolution phase-contrast images are obtained, revealing the finer structure or three-dimensional tomography of reflective samples. With this system, we have quantitatively obtained the contour of tissue slices and silicon semiconductor wafers. We believe that the proposed system will be very helpful for the high-resolution imaging of industrial devices and biomedical dynamics.
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6
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Xu F, Zhang J, Ding D, Liu W, Zheng C, Zhou S, Chen Y, Kuang C. Real-time reconstruction using electro-optics modulator-based structured illumination microscopy. OPTICS EXPRESS 2022; 30:13238-13251. [PMID: 35472941 DOI: 10.1364/oe.454982] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Accepted: 03/21/2022] [Indexed: 06/14/2023]
Abstract
Structured illumination microscopy (SIM), a super-resolution technology, has a wide range of applications in life sciences. In this study, we present an electro-optic high-speed phase-shift super-resolution microscopy imaging system including 2D SIM, total internal reflection fluorescence-SIM, and 3D SIM modes. This system uses galvanometers and an electro-optic modulator to flexibly and quickly control the phase and direction of structured illumination patterns. Moreover, its design consists of precise timing for improved acquisition speed and software architecture for real-time reconstruction. The highest acquisition rate achieved was 151 frames/s, while the highest real-time super-resolution reconstruction frame rate achieved was over 25 frames/s.
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7
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Manton JD. Answering some questions about structured illumination microscopy. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2022; 380:20210109. [PMID: 35152757 PMCID: PMC8841787 DOI: 10.1098/rsta.2021.0109] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Structured illumination microscopy (SIM) provides images of fluorescent objects at an enhanced resolution greater than that of conventional epifluorescence wide-field microscopy. Initially demonstrated in 1999 to enhance the lateral resolution twofold, it has since been extended to enhance axial resolution twofold (2008), applied to live-cell imaging (2009) and combined with myriad other techniques, including interferometric detection (2008), confocal microscopy (2010) and light sheet illumination (2012). Despite these impressive developments, SIM remains, perhaps, the most poorly understood 'super-resolution' method. In this article, we provide answers to the 13 questions regarding SIM proposed by Prakash et al. along with answers to a further three questions. After providing a general overview of the technique and its developments, we explain why SIM as normally used is still diffraction-limited. We then highlight the necessity for a non-polynomial, and not just nonlinear, response to the illuminating light in order to make SIM a true, diffraction-unlimited, super-resolution technique. In addition, we present a derivation of a real-space SIM reconstruction approach that can be used to process conventional SIM and image scanning microscopy (ISM) data and extended to process data with quasi-arbitrary illumination patterns. Finally, we provide a simple bibliometric analysis of SIM development over the past two decades and provide a short outlook on potential future work. This article is part of the Theo Murphy meeting issue 'Super-resolution structured illumination microscopy (part 2)'.
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Affiliation(s)
- James D. Manton
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, UK
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8
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Zeng H, Liu G, Zhao R. SIM reconstruction framework for high-speed multi-dimensional super-resolution imaging. OPTICS EXPRESS 2022; 30:10877-10898. [PMID: 35473044 DOI: 10.1364/oe.450136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 02/18/2022] [Indexed: 06/14/2023]
Abstract
Structured illumination microscopy (SIM) holds great promise for live cell imaging applications due to its potential to obtain multidimensional information such as intensity, spectrum and polarization (I, λ , p) at high spatial-temporal resolution, enabling the observation of more complex dynamic interactions between subcellular structures. However, the reconstruction results of polarized samples are prone to artifacts because all current SIM reconstruction frameworks use incomplete imaging models which neglect polarization modulation. Such polarization-related artifacts are especially prevalent for SIM reconstruction using a reduced number of raw images (RSIM) and severely undermine the ability of SIM to capture multi-dimensional information. Here, we report a new SIM reconstruction framework (PRSIM) that can recover multi-dimensional information (I, λ, p) using a reduced number of raw images. PRSIM adopts a complete imaging model that is versatile for normal and polarized samples and uses a frequency-domain iterative reconstruction algorithm for artifact-free super-resolution (SR) reconstruction. It can simultaneously obtain the SR spatial structure and polarization orientation of polarized samples using 6 raw SIM images and can perform SR reconstruction using 4 SIM images for normal samples. In addition, PRSIM has less spatial computational complexity and achieves reconstruction speeds tens of times higher than that of the state-of-the-art non-iterative RSIM, making it more suitable for large field-of-view imaging. Thus, PRSIM is expected to facilitate the development of SIM into an ultra-high-speed and multi-dimensional SR imaging tool.
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9
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Ma Y, Dai T, Lei Y, Zheng J, Liu M, Sui B, Smith ZJ, Chu K, Kong L, Gao P. Label-free imaging of intracellular organelle dynamics using flat-fielding quantitative phase contrast microscopy (FF-QPCM). OPTICS EXPRESS 2022; 30:9505-9520. [PMID: 35299377 DOI: 10.1364/oe.454023] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Accepted: 02/23/2022] [Indexed: 06/14/2023]
Abstract
Panoramic and long-term observation of nanosized organelle dynamics and interactions with high spatiotemporal resolution still hold great challenge for current imaging platforms. In this study, we propose a live-organelle imaging platform, where a flat-fielding quantitative phase contrast microscope (FF-QPCM) visualizes all the membrane-bound subcellular organelles, and an intermittent fluorescence channel assists in specific organelle identification. FF-QPCM features a high spatiotemporal resolution of 245 nm and 250 Hz and strong immunity against external disturbance. Thus, we could investigate several important dynamic processes of intracellular organelles from direct perspectives, including chromosome duplication in mitosis, mitochondrial fusion and fission, filaments, and vesicles' morphologies in apoptosis. Of note, we have captured, for the first time, a new type of mitochondrial fission (entitled mitochondrial disintegration), the generation and fusion process of vesicle-like organelles, as well as the mitochondrial vacuolization during necrosis. All these results bring us new insights into spatiotemporal dynamics and interactions among organelles, and hence aid us in understanding the real behaviors and functional implications of the organelles in cellular activities.
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10
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Wu J, Lu Z, Jiang D, Guo Y, Qiao H, Zhang Y, Zhu T, Cai Y, Zhang X, Zhanghao K, Xie H, Yan T, Zhang G, Li X, Jiang Z, Lin X, Fang L, Zhou B, Xi P, Fan J, Yu L, Dai Q. Iterative tomography with digital adaptive optics permits hour-long intravital observation of 3D subcellular dynamics at millisecond scale. Cell 2021; 184:3318-3332.e17. [PMID: 34038702 DOI: 10.1016/j.cell.2021.04.029] [Citation(s) in RCA: 64] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2020] [Revised: 01/04/2021] [Accepted: 04/16/2021] [Indexed: 01/03/2023]
Abstract
Long-term subcellular intravital imaging in mammals is vital to study diverse intercellular behaviors and organelle functions during native physiological processes. However, optical heterogeneity, tissue opacity, and phototoxicity pose great challenges. Here, we propose a computational imaging framework, termed digital adaptive optics scanning light-field mutual iterative tomography (DAOSLIMIT), featuring high-speed, high-resolution 3D imaging, tiled wavefront correction, and low phototoxicity with a compact system. By tomographic imaging of the entire volume simultaneously, we obtained volumetric imaging across 225 × 225 × 16 μm3, with a resolution of up to 220 nm laterally and 400 nm axially, at the millisecond scale, over hundreds of thousands of time points. To establish the capabilities, we investigated large-scale cell migration and neural activities in different species and observed various subcellular dynamics in mammals during neutrophil migration and tumor cell circulation.
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Affiliation(s)
- Jiamin Wu
- Department of Automation, Tsinghua University, Beijing 100084, China; Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing 100084, China; Beijing Key Laboratory of Multi-dimension & Multi-scale Computational Photography (MMCP), Tsinghua University, Beijing 100084, China; IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing 100084, China
| | - Zhi Lu
- Department of Automation, Tsinghua University, Beijing 100084, China; Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing 100084, China; Beijing Key Laboratory of Multi-dimension & Multi-scale Computational Photography (MMCP), Tsinghua University, Beijing 100084, China; IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing 100084, China
| | - Dong Jiang
- State Key Laboratory of Membrane Biology, Tsinghua University-Peking University Joint Center for Life Sciences, Beijing Frontier Research Center for Biological Structure, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Yuduo Guo
- Department of Electronic Engineering, Tsinghua University, Beijing 100084, China
| | - Hui Qiao
- Department of Automation, Tsinghua University, Beijing 100084, China; Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing 100084, China; Beijing Key Laboratory of Multi-dimension & Multi-scale Computational Photography (MMCP), Tsinghua University, Beijing 100084, China; IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing 100084, China
| | - Yi Zhang
- Department of Automation, Tsinghua University, Beijing 100084, China; Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing 100084, China; Beijing Key Laboratory of Multi-dimension & Multi-scale Computational Photography (MMCP), Tsinghua University, Beijing 100084, China
| | - Tianyi Zhu
- Department of Automation, Tsinghua University, Beijing 100084, China; Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing 100084, China; Beijing Key Laboratory of Multi-dimension & Multi-scale Computational Photography (MMCP), Tsinghua University, Beijing 100084, China
| | - Yeyi Cai
- Department of Automation, Tsinghua University, Beijing 100084, China; Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing 100084, China; Beijing Key Laboratory of Multi-dimension & Multi-scale Computational Photography (MMCP), Tsinghua University, Beijing 100084, China
| | - Xu Zhang
- Department of Automation, Tsinghua University, Beijing 100084, China; Beijing Institute of Collaborative Innovation, Beijing 100094, China
| | - Karl Zhanghao
- Department of Biomedical Engineering, College of Engineering, Peking University, Beijing 100871, China
| | - Hao Xie
- Department of Automation, Tsinghua University, Beijing 100084, China; Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing 100084, China; Beijing Key Laboratory of Multi-dimension & Multi-scale Computational Photography (MMCP), Tsinghua University, Beijing 100084, China; IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing 100084, China
| | - Tao Yan
- Department of Automation, Tsinghua University, Beijing 100084, China; Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing 100084, China; Beijing Key Laboratory of Multi-dimension & Multi-scale Computational Photography (MMCP), Tsinghua University, Beijing 100084, China
| | - Guoxun Zhang
- Department of Automation, Tsinghua University, Beijing 100084, China; Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing 100084, China; Beijing Key Laboratory of Multi-dimension & Multi-scale Computational Photography (MMCP), Tsinghua University, Beijing 100084, China
| | - Xiaoxu Li
- Department of Automation, Tsinghua University, Beijing 100084, China; Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing 100084, China; Beijing Key Laboratory of Multi-dimension & Multi-scale Computational Photography (MMCP), Tsinghua University, Beijing 100084, China
| | - Zheng Jiang
- State Key Laboratory of Membrane Biology, Tsinghua University-Peking University Joint Center for Life Sciences, Beijing Frontier Research Center for Biological Structure, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Xing Lin
- Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing 100084, China; Beijing Key Laboratory of Multi-dimension & Multi-scale Computational Photography (MMCP), Tsinghua University, Beijing 100084, China
| | - Lu Fang
- Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing 100084, China; Department of Electronic Engineering, Tsinghua University, Beijing 100084, China
| | - Bing Zhou
- Advanced Innovation Center for Big Data-based Precision Medicine, School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, China
| | - Peng Xi
- Department of Biomedical Engineering, College of Engineering, Peking University, Beijing 100871, China
| | - Jingtao Fan
- Department of Automation, Tsinghua University, Beijing 100084, China; Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing 100084, China; Beijing Key Laboratory of Multi-dimension & Multi-scale Computational Photography (MMCP), Tsinghua University, Beijing 100084, China; IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing 100084, China.
| | - Li Yu
- State Key Laboratory of Membrane Biology, Tsinghua University-Peking University Joint Center for Life Sciences, Beijing Frontier Research Center for Biological Structure, School of Life Sciences, Tsinghua University, Beijing 100084, China.
| | - Qionghai Dai
- Department of Automation, Tsinghua University, Beijing 100084, China; Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing 100084, China; Beijing Key Laboratory of Multi-dimension & Multi-scale Computational Photography (MMCP), Tsinghua University, Beijing 100084, China; IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing 100084, China.
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11
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Shi R, Li Y, Kong L. High-speed volumetric imaging in vivo based on structured illumination microscopy with interleaved reconstruction. JOURNAL OF BIOPHOTONICS 2021; 14:e202000513. [PMID: 33502121 DOI: 10.1002/jbio.202000513] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Revised: 01/21/2021] [Accepted: 01/24/2021] [Indexed: 06/12/2023]
Abstract
Wide-field fluorescence microscopy (WFFM) is widely adopted in biomedical studies, due to its high imaging speed over large field-of-views. However, WFFM is susceptible to out-of-focus background. To overcome this problem, structured illumination microscopy (SIM) was proposed as a wide-field, optical-sectioning technique, which needs multiple raw images for image reconstruction and thus has a lower imaging speed. Here we propose SIM with interleaved reconstruction, to make SIM of lossless speed. We apply this method in volumetric imaging of neural network dynamics in brains of zebrafish larva in vivo.
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Affiliation(s)
- Ruheng Shi
- State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University, Beijing, China
| | - Yuting Li
- State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University, Beijing, China
| | - Lingjie Kong
- State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University, Beijing, China
- IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, China
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12
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Gruebele M, Pielak GJ. Dynamical spectroscopy and microscopy of proteins in cells. Curr Opin Struct Biol 2021; 70:1-7. [PMID: 33662744 DOI: 10.1016/j.sbi.2021.02.001] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Accepted: 02/01/2021] [Indexed: 12/31/2022]
Abstract
With a strong understanding of how proteins fold in hand, it is now possible to ask how in-cell environments modulate their folding, binding and function. Studies accessing fast (ns to s) in-cell dynamics have accelerated over the past few years through a combination of in-cell NMR spectroscopy and time-resolved fluorescence microscopies. Here, we discuss this recent work and the emerging picture of protein surfaces as not just hydrophilic coats interfacing the solvent to the protein's core and functional regions, but as critical components in cells controlling protein mobility, function and communication with post-translational modifications.
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Affiliation(s)
- Martin Gruebele
- Department of Chemistry, Department of Physics, and Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.
| | - Gary J Pielak
- Departments of Chemistry, Biochemistry and Biophysics, University of North Carolina, Chapel Hill, NC 27599, USA.
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Boualam A, Rowlands CJ. Method for assessing the spatiotemporal resolution of structured illumination microscopy (SIM). BIOMEDICAL OPTICS EXPRESS 2021; 12:790-801. [PMID: 33680542 PMCID: PMC7901338 DOI: 10.1364/boe.403592] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Revised: 12/16/2020] [Accepted: 12/21/2020] [Indexed: 05/12/2023]
Abstract
A method is proposed for assessing the temporal resolution of structured illumination microscopy (SIM), by tracking the amplitude of different spatial frequency components over time, and comparing them to a temporally-oscillating ground-truth. This method is used to gain insight into the performance limits of SIM, along with alternative reconstruction techniques (termed 'rolling SIM') that claim to improve temporal resolution. Results show that the temporal resolution of SIM varies considerably between low and high spatial frequencies, and that, despite being used in several high profile papers and commercial microscope software, rolling SIM provides no increase in temporal resolution over conventional SIM.
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Li Z, Zhang Q, Chou SW, Newman Z, Turcotte R, Natan R, Dai Q, Isacoff EY, Ji N. Fast widefield imaging of neuronal structure and function with optical sectioning in vivo. SCIENCE ADVANCES 2020; 6:eaaz3870. [PMID: 32494711 PMCID: PMC7209992 DOI: 10.1126/sciadv.aaz3870] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/04/2019] [Accepted: 02/18/2020] [Indexed: 05/19/2023]
Abstract
Optical microscopy, owing to its noninvasiveness and subcellular resolution, enables in vivo visualization of neuronal structure and function in the physiological context. Optical-sectioning structured illumination microscopy (OS-SIM) is a widefield fluorescence imaging technique that uses structured illumination patterns to encode in-focus structures and optically sections 3D samples. However, its application to in vivo imaging has been limited. In this study, we optimized OS-SIM for in vivo neural imaging. We modified OS-SIM reconstruction algorithms to improve signal-to-noise ratio and correct motion-induced artifacts in live samples. Incorporating an adaptive optics (AO) module to OS-SIM, we found that correcting sample-induced optical aberrations was essential for achieving accurate structural and functional characterizations in vivo. With AO OS-SIM, we demonstrated fast, high-resolution in vivo imaging with optical sectioning for structural imaging of mouse cortical neurons and zebrafish larval motor neurons, and functional imaging of quantal synaptic transmission at Drosophila larval neuromuscular junctions.
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Affiliation(s)
- Ziwei Li
- Department of Physics, University of California, Berkeley, Berkeley, CA 94720, USA
- Department of Automation, Tsinghua University, Beijing 100084, China
| | - Qinrong Zhang
- Department of Physics, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Shih-Wei Chou
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Zachary Newman
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Raphaël Turcotte
- Department of Physics, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Ryan Natan
- Department of Physics, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Qionghai Dai
- Department of Automation, Tsinghua University, Beijing 100084, China
| | - Ehud Y. Isacoff
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA
- Bioscience Division, Lawrence Berkeley National Laboratory, Berkeley, Berkeley, CA 94720, USA
| | - Na Ji
- Department of Physics, University of California, Berkeley, Berkeley, CA 94720, USA
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
- Corresponding author.
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15
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Ma Y, Guo S, Pan Y, Fan R, Smith ZJ, Lane S, Chu K. Quantitative phase microscopy with enhanced contrast and improved resolution through ultra-oblique illumination (UO-QPM). JOURNAL OF BIOPHOTONICS 2019; 12:e201900011. [PMID: 31184803 DOI: 10.1002/jbio.201900011] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/10/2019] [Revised: 06/02/2019] [Accepted: 06/04/2019] [Indexed: 06/09/2023]
Abstract
Recent developments in phase contrast microscopy have enabled the label-free visualization of certain organelles due to their distinct morphological features, making this method an attractive alternative in the study of cellular dynamics. However tubular structures such as endoplasmic reticulum (ER) networks and complex dynamics such as the fusion and fission of mitochondria, due to their low phase contrast, still need fluorescent labeling to be adequately imaged. In this article, we report a quantitative phase microscope with ultra-oblique illumination that enables us to see those structures and their dynamics with high contrast for the first time without labeling. The imaging capability was validated through comparison to the fluorescence images with the same field-of-view. The high image resolution (~270 nm) was validated using both beads and cellular structures. Furthermore, we were able to record the vibration of ER networks at a frame rate of 250 Hz. We additionally show complex cellular processes such as remodeling of the mitochondria networks through fusion and fission and vesicle transportation along the ER without labels. Our high spatial and temporal resolution allowed us to observe mitochondria "spinning", which has not been reported before, further demonstrating the advantages of the proposed method.
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Affiliation(s)
- Ying Ma
- Hefei National Laboratory for Physical Sciences at the Microscale, University of Science and Technology of China, Anhui, Hefei, China
- University of Science and Technology of China, Department of Precision Machinery and Precision Instrumentation, Anhui, Hefei, China
| | - Siyue Guo
- Hefei National Laboratory for Physical Sciences at the Microscale, University of Science and Technology of China, Anhui, Hefei, China
- University of Science and Technology of China, Department of Precision Machinery and Precision Instrumentation, Anhui, Hefei, China
| | - Yang Pan
- Hefei National Laboratory for Physical Sciences at the Microscale, University of Science and Technology of China, Anhui, Hefei, China
- University of Science and Technology of China, Department of Precision Machinery and Precision Instrumentation, Anhui, Hefei, China
| | - Rong Fan
- Hefei National Laboratory for Physical Sciences at the Microscale, University of Science and Technology of China, Anhui, Hefei, China
| | - Zachary J Smith
- University of Science and Technology of China, Department of Precision Machinery and Precision Instrumentation, Anhui, Hefei, China
- Key Laboratory of Precision Scientific Instrumentation of Anhui Higher Education Institutes, University of Science and Technology of China, Anhui, Hefei, China
| | - Stephen Lane
- Center for Biophotonics, University of California, Davis, Sacramento, California
| | - Kaiqin Chu
- Hefei National Laboratory for Physical Sciences at the Microscale, University of Science and Technology of China, Anhui, Hefei, China
- University of Science and Technology of China, Department of Precision Machinery and Precision Instrumentation, Anhui, Hefei, China
- Key Laboratory of Precision Scientific Instrumentation of Anhui Higher Education Institutes, University of Science and Technology of China, Anhui, Hefei, China
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16
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Guo Y, Li D, Zhang S, Yang Y, Liu JJ, Wang X, Liu C, Milkie DE, Moore RP, Tulu US, Kiehart DP, Hu J, Lippincott-Schwartz J, Betzig E, Li D. Visualizing Intracellular Organelle and Cytoskeletal Interactions at Nanoscale Resolution on Millisecond Timescales. Cell 2018; 175:1430-1442.e17. [DOI: 10.1016/j.cell.2018.09.057] [Citation(s) in RCA: 290] [Impact Index Per Article: 48.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2018] [Revised: 07/21/2018] [Accepted: 09/26/2018] [Indexed: 11/26/2022]
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