1
|
Gao Z, Han K, Hua X, Liu W, Jia S. hydroSIM: super-resolution speckle illumination microscopy with a hydrogel diffuser. BIOMEDICAL OPTICS EXPRESS 2024; 15:3574-3585. [PMID: 38867780 PMCID: PMC11166422 DOI: 10.1364/boe.521521] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Revised: 03/27/2024] [Accepted: 04/18/2024] [Indexed: 06/14/2024]
Abstract
Super-resolution microscopy has emerged as an indispensable methodology for probing the intricacies of cellular biology. Structured illumination microscopy (SIM), in particular, offers an advantageous balance of spatial and temporal resolution, allowing for visualizing cellular processes with minimal disruption to biological specimens. However, the broader adoption of SIM remains hampered by the complexity of instrumentation and alignment. Here, we introduce speckle-illumination super-resolution microscopy using hydrogel diffusers (hydroSIM). The study utilizes the high scattering and optical transmissive properties of hydrogel materials and realizes a remarkably simplified approach to plug-in super-resolution imaging via a common epi-fluorescence platform. We demonstrate the hydroSIM system using various phantom and biological samples, and the results exhibited effective 3D resolution doubling, optical sectioning, and high contrast. We foresee hydroSIM, a cost-effective, biocompatible, and user-accessible super-resolution methodology, to significantly advance a wide range of biomedical imaging and applications.
Collapse
Affiliation(s)
- Zijun Gao
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia 30332, USA
- Parker H. Petit Institute for Bioengineering and Biosciences, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
- School of Materials Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
| | - Keyi Han
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia 30332, USA
| | - Xuanwen Hua
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia 30332, USA
| | - Wenhao Liu
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia 30332, USA
| | - Shu Jia
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia 30332, USA
- Parker H. Petit Institute for Bioengineering and Biosciences, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
| |
Collapse
|
2
|
Shroff H, Testa I, Jug F, Manley S. Live-cell imaging powered by computation. Nat Rev Mol Cell Biol 2024; 25:443-463. [PMID: 38378991 DOI: 10.1038/s41580-024-00702-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/10/2024] [Indexed: 02/22/2024]
Abstract
The proliferation of microscopy methods for live-cell imaging offers many new possibilities for users but can also be challenging to navigate. The prevailing challenge in live-cell fluorescence microscopy is capturing intra-cellular dynamics while preserving cell viability. Computational methods can help to address this challenge and are now shifting the boundaries of what is possible to capture in living systems. In this Review, we discuss these computational methods focusing on artificial intelligence-based approaches that can be layered on top of commonly used existing microscopies as well as hybrid methods that integrate computation and microscope hardware. We specifically discuss how computational approaches can improve the signal-to-noise ratio, spatial resolution, temporal resolution and multi-colour capacity of live-cell imaging.
Collapse
Affiliation(s)
- Hari Shroff
- Janelia Research Campus, Howard Hughes Medical Institute (HHMI), Ashburn, VA, USA
| | - Ilaria Testa
- Department of Applied Physics and Science for Life Laboratory, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Florian Jug
- Fondazione Human Technopole (HT), Milan, Italy
| | - Suliana Manley
- Institute of Physics, School of Basic Sciences, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland.
| |
Collapse
|
3
|
Miyoshi T, Vishwasrao H, Belyantseva I, Sajeevadathan M, Ishibashi Y, Adadey S, Harada N, Shroff H, Friedman T. Live-cell single-molecule fluorescence microscopy for protruding organelles reveals regulatory mechanisms of MYO7A-driven cargo transport in stereocilia of inner ear hair cells. RESEARCH SQUARE 2024:rs.3.rs-4369958. [PMID: 38826223 PMCID: PMC11142366 DOI: 10.21203/rs.3.rs-4369958/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Stereocilia are unidirectional F-actin-based cylindrical protrusions on the apical surface of inner ear hair cells and function as biological mechanosensors of sound and acceleration. Development of functional stereocilia requires motor activities of unconventional myosins to transport proteins necessary for elongating the F-actin cores and to assemble the mechanoelectrical transduction (MET) channel complex. However, how each myosin localizes in stereocilia using the energy from ATP hydrolysis is only partially understood. In this study, we develop a methodology for live-cell single-molecule fluorescence microscopy of organelles protruding from the apical surface using a dual-view light-sheet microscope, diSPIM. We demonstrate that MYO7A, a component of the MET machinery, traffics as a dimer in stereocilia. Movements of MYO7A are restricted when scaffolded by the plasma membrane and F-actin as mediated by MYO7A's interacting partners. Here, we discuss the technical details of our methodology and its future applications including analyses of cargo transportation in various organelles.
Collapse
Affiliation(s)
| | | | | | | | | | | | | | | | - Thomas Friedman
- National Institute on Deafness and Other Communication Disorders, NIH
| |
Collapse
|
4
|
Cao X, Li M, Li Q, Fan C, Sun J, Gao Z. Single-molecule localization microscopy at 2.4-fold resolution improvement with optical lattice pattern illumination. OPTICS EXPRESS 2024; 32:20218-20229. [PMID: 38859137 DOI: 10.1364/oe.514937] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Accepted: 03/27/2024] [Indexed: 06/12/2024]
Abstract
Traditional camera-based single-molecule localization microscopy (SMLM), with its high imaging resolution and localization throughput, has made significant advancements in biological and chemical researches. However, due to the limitation of the fluorescence signal-to-noise ratio (SNR) of a single molecule, its resolution is difficult to reach to 5 nm. Optical lattice produces a nondiffracting beam pattern that holds the potential to enhance microscope performance through its high contrast and penetration depth. Here, we propose a new method named LatticeFLUX which utilizes the wide-field optical lattice pattern illumination for individual molecule excitation and localization. We calculated the Cramér-Rao lower bound of LatticeFLUX resolution and proved that our method can improve the single molecule localization precision by 2.4 times compared with the traditional SMLM. We propose a scheme using 9-frame localization, which solves the problem of uneven lattice light illumination. Based on the experimental single-molecule fluorescence SNR, we coded the image reconstruction software to further verify the resolution enhancement capability of LatticeFLUX on simulated punctate DNA origami, line pairs, and cytoskeleton. LatticeFLUX confirms the feasibility of using 2D structured light illumination to obtain high single-molecule localization precision under high localization throughput. It paves the way for further implementation of ultra-high resolution full 3D structured-light-illuminated SMLM.
Collapse
|
5
|
Qiao C, Zeng Y, Meng Q, Chen X, Chen H, Jiang T, Wei R, Guo J, Fu W, Lu H, Li D, Wang Y, Qiao H, Wu J, Li D, Dai Q. Zero-shot learning enables instant denoising and super-resolution in optical fluorescence microscopy. Nat Commun 2024; 15:4180. [PMID: 38755148 PMCID: PMC11099110 DOI: 10.1038/s41467-024-48575-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Accepted: 05/07/2024] [Indexed: 05/18/2024] Open
Abstract
Computational super-resolution methods, including conventional analytical algorithms and deep learning models, have substantially improved optical microscopy. Among them, supervised deep neural networks have demonstrated outstanding performance, however, demanding abundant high-quality training data, which are laborious and even impractical to acquire due to the high dynamics of living cells. Here, we develop zero-shot deconvolution networks (ZS-DeconvNet) that instantly enhance the resolution of microscope images by more than 1.5-fold over the diffraction limit with 10-fold lower fluorescence than ordinary super-resolution imaging conditions, in an unsupervised manner without the need for either ground truths or additional data acquisition. We demonstrate the versatile applicability of ZS-DeconvNet on multiple imaging modalities, including total internal reflection fluorescence microscopy, three-dimensional wide-field microscopy, confocal microscopy, two-photon microscopy, lattice light-sheet microscopy, and multimodal structured illumination microscopy, which enables multi-color, long-term, super-resolution 2D/3D imaging of subcellular bioprocesses from mitotic single cells to multicellular embryos of mouse and C. elegans.
Collapse
Affiliation(s)
- Chang Qiao
- Department of Automation, Tsinghua University, 100084, Beijing, China
- Institute for Brain and Cognitive Sciences, Tsinghua University, 100084, Beijing, China
- Beijing Key Laboratory of Multi-dimension & Multi-scale Computational Photography, Tsinghua University, 100084, Beijing, China
- Beijing Laboratory of Brain and Cognitive Intelligence, Beijing Municipal Education Commission, 100010, Beijing, China
| | - Yunmin Zeng
- Department of Automation, Tsinghua University, 100084, Beijing, China
| | - Quan Meng
- National Laboratory of Biomacromolecules, New Cornerstone Science Laboratory, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, 100101, Beijing, China
- College of Life Sciences, University of Chinese Academy of Sciences, 100049, Beijing, China
| | - Xingye Chen
- Department of Automation, Tsinghua University, 100084, Beijing, China
- Institute for Brain and Cognitive Sciences, Tsinghua University, 100084, Beijing, China
- Beijing Key Laboratory of Multi-dimension & Multi-scale Computational Photography, Tsinghua University, 100084, Beijing, China
- Beijing Laboratory of Brain and Cognitive Intelligence, Beijing Municipal Education Commission, 100010, Beijing, China
- Research Institute for Frontier Science, Beihang University, 100191, Beijing, China
| | - Haoyu Chen
- National Laboratory of Biomacromolecules, New Cornerstone Science Laboratory, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, 100101, Beijing, China
- College of Life Sciences, University of Chinese Academy of Sciences, 100049, Beijing, China
| | - Tao Jiang
- National Laboratory of Biomacromolecules, New Cornerstone Science Laboratory, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, 100101, Beijing, China
- College of Life Sciences, University of Chinese Academy of Sciences, 100049, Beijing, China
| | - Rongfei Wei
- National Laboratory of Biomacromolecules, New Cornerstone Science Laboratory, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, 100101, Beijing, China
| | - Jiabao Guo
- National Laboratory of Biomacromolecules, New Cornerstone Science Laboratory, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, 100101, Beijing, China
- College of Life Sciences, University of Chinese Academy of Sciences, 100049, Beijing, China
| | - Wenfeng Fu
- National Laboratory of Biomacromolecules, New Cornerstone Science Laboratory, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, 100101, Beijing, China
- College of Life Sciences, University of Chinese Academy of Sciences, 100049, Beijing, China
| | - Huaide Lu
- National Laboratory of Biomacromolecules, New Cornerstone Science Laboratory, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, 100101, Beijing, China
- College of Life Sciences, University of Chinese Academy of Sciences, 100049, Beijing, China
| | - Di Li
- National Laboratory of Biomacromolecules, New Cornerstone Science Laboratory, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, 100101, Beijing, China
| | - Yuwang Wang
- Beijing National Research Center for Information Science and Technology, Tsinghua University, 100084, Beijing, China
| | - Hui Qiao
- Department of Automation, Tsinghua University, 100084, Beijing, China
- Institute for Brain and Cognitive Sciences, Tsinghua University, 100084, Beijing, China
- Beijing Key Laboratory of Multi-dimension & Multi-scale Computational Photography, Tsinghua University, 100084, Beijing, China
- Beijing Laboratory of Brain and Cognitive Intelligence, Beijing Municipal Education Commission, 100010, Beijing, China
| | - Jiamin Wu
- Department of Automation, Tsinghua University, 100084, Beijing, China
- Institute for Brain and Cognitive Sciences, Tsinghua University, 100084, Beijing, China
- Beijing Key Laboratory of Multi-dimension & Multi-scale Computational Photography, Tsinghua University, 100084, Beijing, China
- Beijing Laboratory of Brain and Cognitive Intelligence, Beijing Municipal Education Commission, 100010, Beijing, China
| | - Dong Li
- National Laboratory of Biomacromolecules, New Cornerstone Science Laboratory, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, 100101, Beijing, China.
- College of Life Sciences, University of Chinese Academy of Sciences, 100049, Beijing, China.
| | - Qionghai Dai
- Department of Automation, Tsinghua University, 100084, Beijing, China.
- Institute for Brain and Cognitive Sciences, Tsinghua University, 100084, Beijing, China.
- Beijing Key Laboratory of Multi-dimension & Multi-scale Computational Photography, Tsinghua University, 100084, Beijing, China.
- Beijing Laboratory of Brain and Cognitive Intelligence, Beijing Municipal Education Commission, 100010, Beijing, China.
| |
Collapse
|
6
|
Miyoshi T, Vishwasrao HD, Belyantseva IA, Sajeevadathan M, Ishibashi Y, Adadey SM, Harada N, Shroff H, Friedman TB. Live-cell single-molecule fluorescence microscopy for protruding organelles reveals regulatory mechanisms of MYO7A-driven cargo transport in stereocilia of inner ear hair cells. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.04.590649. [PMID: 38766013 PMCID: PMC11100596 DOI: 10.1101/2024.05.04.590649] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Stereocilia are unidirectional F-actin-based cylindrical protrusions on the apical surface of inner ear hair cells and function as biological mechanosensors of sound and acceleration. Development of functional stereocilia requires motor activities of unconventional myosins to transport proteins necessary for elongating the F-actin cores and to assemble the mechanoelectrical transduction (MET) channel complex. However, how each myosin localizes in stereocilia using the energy from ATP hydrolysis is only partially understood. In this study, we develop a methodology for live-cell single-molecule fluorescence microscopy of organelles protruding from the apical surface using a dual-view light-sheet microscope, diSPIM. We demonstrate that MYO7A, a component of the MET machinery, traffics as a dimer in stereocilia. Movements of MYO7A are restricted when scaffolded by the plasma membrane and F-actin as mediated by MYO7A's interacting partners. Here, we discuss the technical details of our methodology and its future applications including analyses of cargo transportation in various organelles.
Collapse
Affiliation(s)
- Takushi Miyoshi
- Laboratory of Molecular Genetics, National Institute on Deafness and Other Communication Disorders, National Institutes of Health, Bethesda, MD, 20892, USA
- Division of Molecular and Integrative Physiology, Department of Biomedical Sciences, Southern Illinois University School of Medicine, Carbondale, IL, 62901, USA
| | - Harshad D. Vishwasrao
- Advanced Imaging and Microscopy Resource, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Inna A. Belyantseva
- Laboratory of Molecular Genetics, National Institute on Deafness and Other Communication Disorders, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Mrudhula Sajeevadathan
- Division of Molecular and Integrative Physiology, Department of Biomedical Sciences, Southern Illinois University School of Medicine, Carbondale, IL, 62901, USA
| | - Yasuko Ishibashi
- Laboratory of Molecular Genetics, National Institute on Deafness and Other Communication Disorders, National Institutes of Health, Bethesda, MD, 20892, USA
- Inner Ear Gene Therapy Program, National Institute on Deafness and Other Communication Disorders, National Institute of Health, Bethesda, Maryland 20892, USA
| | - Samuel M. Adadey
- Laboratory of Molecular Genetics, National Institute on Deafness and Other Communication Disorders, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Narinobu Harada
- Hearing Research Laboratory, Harada ENT Clinic, Higashi-Osaka, Osaka, 577-0816, Japan
| | - Hari Shroff
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, 20147, USA
| | - Thomas B. Friedman
- Laboratory of Molecular Genetics, National Institute on Deafness and Other Communication Disorders, National Institutes of Health, Bethesda, MD, 20892, USA
| |
Collapse
|
7
|
Ma C, Tan W, He R, Yan B. Pretraining a foundation model for generalizable fluorescence microscopy-based image restoration. Nat Methods 2024:10.1038/s41592-024-02244-3. [PMID: 38609490 DOI: 10.1038/s41592-024-02244-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Accepted: 03/13/2024] [Indexed: 04/14/2024]
Abstract
Fluorescence microscopy-based image restoration has received widespread attention in the life sciences and has led to significant progress, benefiting from deep learning technology. However, most current task-specific methods have limited generalizability to different fluorescence microscopy-based image restoration problems. Here, we seek to improve generalizability and explore the potential of applying a pretrained foundation model to fluorescence microscopy-based image restoration. We provide a universal fluorescence microscopy-based image restoration (UniFMIR) model to address different restoration problems, and show that UniFMIR offers higher image restoration precision, better generalization and increased versatility. Demonstrations on five tasks and 14 datasets covering a wide range of microscopy imaging modalities and biological samples demonstrate that the pretrained UniFMIR can effectively transfer knowledge to a specific situation via fine-tuning, uncover clear nanoscale biomolecular structures and facilitate high-quality imaging. This work has the potential to inspire and trigger new research highlights for fluorescence microscopy-based image restoration.
Collapse
Affiliation(s)
- Chenxi Ma
- School of Computer Science, Shanghai Key Laboratory of Intelligent Information Processing, Fudan University, Shanghai, China
| | - Weimin Tan
- School of Computer Science, Shanghai Key Laboratory of Intelligent Information Processing, Fudan University, Shanghai, China
| | - Ruian He
- School of Computer Science, Shanghai Key Laboratory of Intelligent Information Processing, Fudan University, Shanghai, China
| | - Bo Yan
- School of Computer Science, Shanghai Key Laboratory of Intelligent Information Processing, Fudan University, Shanghai, China.
| |
Collapse
|
8
|
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.
Collapse
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
| |
Collapse
|
9
|
Chareyre S, Li X, Anjuwon-Foster BR, Updegrove TB, Clifford S, Brogan AP, Su Y, Zhang L, Chen J, Shroff H, Ramamurthi KS. Cell division machinery drives cell-specific gene activation during differentiation in Bacillus subtilis. Proc Natl Acad Sci U S A 2024; 121:e2400584121. [PMID: 38502707 PMCID: PMC10990147 DOI: 10.1073/pnas.2400584121] [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: 01/10/2024] [Accepted: 02/22/2024] [Indexed: 03/21/2024] Open
Abstract
When faced with starvation, the bacterium Bacillus subtilis transforms itself into a dormant cell type called a "spore". Sporulation initiates with an asymmetric division event, which requires the relocation of the core divisome components FtsA and FtsZ, after which the sigma factor σF is exclusively activated in the smaller daughter cell. Compartment-specific activation of σF requires the SpoIIE phosphatase, which displays a biased localization on one side of the asymmetric division septum and associates with the structural protein DivIVA, but the mechanism by which this preferential localization is achieved is unclear. Here, we isolated a variant of DivIVA that indiscriminately activates σF in both daughter cells due to promiscuous localization of SpoIIE, which was corrected by overproduction of FtsA and FtsZ. We propose that the core components of the redeployed cell division machinery drive the asymmetric localization of DivIVA and SpoIIE to trigger the initiation of the sporulation program.
Collapse
Affiliation(s)
- Sylvia Chareyre
- Laboratory of Molecular Biology, National Cancer Institute, NIH, Bethesda, MD20892
| | - Xuesong Li
- Laboratory of High Resolution Optical Imaging, National Institute of Biomedical Imaging and Bioengineering, NIH, Bethesda, MD20892
- HHMI, Ashburn, VA20147
| | | | - Taylor B. Updegrove
- Laboratory of Molecular Biology, National Cancer Institute, NIH, Bethesda, MD20892
| | - Sarah Clifford
- Laboratory of Molecular Biology, National Cancer Institute, NIH, Bethesda, MD20892
| | - Anna P. Brogan
- Laboratory of Molecular Biology, National Cancer Institute, NIH, Bethesda, MD20892
| | - Yijun Su
- Laboratory of High Resolution Optical Imaging, National Institute of Biomedical Imaging and Bioengineering, NIH, Bethesda, MD20892
- HHMI, Ashburn, VA20147
| | - Lixia Zhang
- Advanced Imaging and Microscopy Resource, NIH, Bethesda, MD20892
| | - Jiji Chen
- Advanced Imaging and Microscopy Resource, NIH, Bethesda, MD20892
| | - Hari Shroff
- Laboratory of High Resolution Optical Imaging, National Institute of Biomedical Imaging and Bioengineering, NIH, Bethesda, MD20892
- HHMI, Ashburn, VA20147
| | | |
Collapse
|
10
|
Matsuzaki T, Kawamura R, Yamamoto A, Takahashi H, Fujii M, Togo S, Yoneyama Y, Hakuno F, Takahashi SI, Suganuma M, Nakabayashi S, Sharma S, Gimzewski JK, Yoshikawa HY. Advanced Interferometry with 3-D Structured Illumination Reveals the Surface Fine Structure of Complex Biospecimens. J Phys Chem Lett 2024; 15:1097-1104. [PMID: 38262433 DOI: 10.1021/acs.jpclett.3c02767] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2024]
Abstract
Interference reflection microscopy (IRM) is a powerful, label-free technique to visualize the surface structure of biospecimens. However, stray light outside a focal plane obscures the surface fine structures beyond the diffraction limit (dxy ≈ 200 nm). Here, we developed an advanced interferometry approach to visualize the surface fine structure of complex biospecimens, ranging from protein assemblies to single cells. Compared to 2-D, our unique 3-D structure illumination introduced to IRM enabled successful visualization of fine structures and the dynamics of protein crystal growth under lateral (dx-y ≈ 110 nm) and axial (dx-z ≤ 5 nm) resolutions and dynamical adhesion of microtubule fiber networks with lateral resolution (dx-y ≈ 120 nm), 10 times greater than unstructured IRM (dx-y ≈ 1000 nm). Simultaneous reflection/fluorescence imaging provides new physical fingerprints for studying complex biospecimens and biological processes such as myogenic differentiation and highlights the potential use of advanced interferometry to study key nanostructures of complex biospecimens.
Collapse
Affiliation(s)
- Takahisa Matsuzaki
- Department of Applied Physics, Graduate School of Engineering, Osaka University, 2-1, Yamadaoka, Suita 565-0871, Japan
- Center for Future Innovation, Graduate School of Engineering, Osaka University, 2-1, Yamadaoka, Suita, Osaka 565-0871, Japan
| | - Ryuzo Kawamura
- Department of Chemistry, Saitama University, 255 Shimo-Okubo, Sakura-Ku, Saitama 338-8570, Japan
| | - Akihisa Yamamoto
- Center for Integrative Medicine and Physics, Institute for Advanced Study, Kyoto University, Kyoto 606-8501, Japan
| | - Hozumi Takahashi
- Department of Applied Physics, Graduate School of Engineering, Osaka University, 2-1, Yamadaoka, Suita 565-0871, Japan
| | - Mai Fujii
- Department of Chemistry, Saitama University, 255 Shimo-Okubo, Sakura-Ku, Saitama 338-8570, Japan
| | - Shodai Togo
- Department of Chemistry, Saitama University, 255 Shimo-Okubo, Sakura-Ku, Saitama 338-8570, Japan
| | - Yosuke Yoneyama
- Institute of Research, Tokyo Medical and Dental University (TMDU), 1-5-45 Yushima, bunkyo-Ku, Tokyo 113-8510, Japan
| | - Fumihiko Hakuno
- Institute of Research, Tokyo Medical and Dental University (TMDU), 1-5-45 Yushima, bunkyo-Ku, Tokyo 113-8510, Japan
| | - Shin-Ichiro Takahashi
- Departments of Animal Sciences and Applied Biological Chemistry, Graduate School of Agriculture and Life Sciences, The University of Tokyo, Bunkyo-Ku, Tokyo 113-8657, Japan
| | - Masami Suganuma
- Division of Strategic Research and Development, Graduate School of Science and Engineering, Saitama University, 255 Shimo-Okubo, Sakura-Ku, Saitama 338-8570, Japan
| | - Seiichiro Nakabayashi
- Division of Strategic Research and Development, Graduate School of Science and Engineering, Saitama University, 255 Shimo-Okubo, Sakura-Ku, Saitama 338-8570, Japan
| | - Shivani Sharma
- California NanoSystems Institute, University of California, Los Angeles, Los Angeles, California 90095, United States
- Pathology & Laboratory Medicine, David Geffen School of Medicine, Jonsson Comprehensive Cancer Center, University of California, Los Angeles, Los Angeles, California 90095, United States
| | - James K Gimzewski
- California NanoSystems Institute, University of California, Los Angeles, Los Angeles, California 90095, United States
- Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, California 90095-1569, United States
- WPI Center for Materials Nanoarchitectonics (MANA), National Institute for Materials Science (NIMS), Tsukuba 305-0044, Japan
| | - Hiroshi Y Yoshikawa
- Department of Applied Physics, Graduate School of Engineering, Osaka University, 2-1, Yamadaoka, Suita 565-0871, Japan
| |
Collapse
|
11
|
Gómez-de-Mariscal E, Del Rosario M, Pylvänäinen JW, Jacquemet G, Henriques R. Harnessing artificial intelligence to reduce phototoxicity in live imaging. J Cell Sci 2024; 137:jcs261545. [PMID: 38324353 PMCID: PMC10912813 DOI: 10.1242/jcs.261545] [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: 02/08/2024] Open
Abstract
Fluorescence microscopy is essential for studying living cells, tissues and organisms. However, the fluorescent light that switches on fluorescent molecules also harms the samples, jeopardizing the validity of results - particularly in techniques such as super-resolution microscopy, which demands extended illumination. Artificial intelligence (AI)-enabled software capable of denoising, image restoration, temporal interpolation or cross-modal style transfer has great potential to rescue live imaging data and limit photodamage. Yet we believe the focus should be on maintaining light-induced damage at levels that preserve natural cell behaviour. In this Opinion piece, we argue that a shift in role for AIs is needed - AI should be used to extract rich insights from gentle imaging rather than recover compromised data from harsh illumination. Although AI can enhance imaging, our ultimate goal should be to uncover biological truths, not just retrieve data. It is essential to prioritize minimizing photodamage over merely pushing technical limits. Our approach is aimed towards gentle acquisition and observation of undisturbed living systems, aligning with the essence of live-cell fluorescence microscopy.
Collapse
Affiliation(s)
| | | | - Joanna W. Pylvänäinen
- Faculty of Science and Engineering, Cell Biology, Åbo Akademi University, Turku 20500, Finland
| | - Guillaume Jacquemet
- Faculty of Science and Engineering, Cell Biology, Åbo Akademi University, Turku 20500, Finland
- Turku Bioscience Centre, University of Turku and Åbo Akademi University, Turku 20520, Finland
- Turku Bioimaging, University of Turku and Åbo Akademi University, Turku 20520, Finland
- InFLAMES Research Flagship Center, Åbo Akademi University, Turku 20100, Finland
| | - Ricardo Henriques
- Instituto Gulbenkian de Ciência, Oeiras 2780-156, Portugal
- UCL Laboratory for Molecular Cell Biology, University College London, London WC1E 6BT, UK
| |
Collapse
|
12
|
Johnson C, Guo M, Schneider MC, Su Y, Khuon S, Reiser N, Wu Y, La Riviere P, Shroff H. Phase diversity-based wavefront sensing for fluorescence microscopy. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.19.572369. [PMID: 38168170 PMCID: PMC10760184 DOI: 10.1101/2023.12.19.572369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
Fluorescence microscopy is an invaluable tool in biology, yet its performance is compromised when the wavefront of light is distorted due to optical imperfections or the refractile nature of the sample. Such optical aberrations can dramatically lower the information content of images by degrading image contrast, resolution, and signal. Adaptive optics (AO) methods can sense and subsequently cancel the aberrated wavefront, but are too complex, inefficient, slow, or expensive for routine adoption by most labs. Here we introduce a rapid, sensitive, and robust wavefront sensing scheme based on phase diversity, a method successfully deployed in astronomy but underused in microscopy. Our method enables accurate wavefront sensing to less than λ/35 root mean square (RMS) error with few measurements, and AO with no additional hardware besides a corrective element. After validating the method with simulations, we demonstrate calibration of a deformable mirror > 100-fold faster than comparable methods (corresponding to wavefront sensing on the ~100 ms scale), and sensing and subsequent correction of severe aberrations (RMS wavefront distortion exceeding λ/2), restoring diffraction-limited imaging on extended biological samples.
Collapse
Affiliation(s)
- Courtney Johnson
- Janelia Research Campus, Howard Hughes Medical Institute (HHMI), Ashburn, VA, USA
| | - Min Guo
- Current address: State Key Laboratory of Extreme Photonics and Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, China
- Laboratory of High Resolution Optical Imaging, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, Maryland, USA
| | | | - Yijun Su
- Janelia Research Campus, Howard Hughes Medical Institute (HHMI), Ashburn, VA, USA
- Laboratory of High Resolution Optical Imaging, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, Maryland, USA
| | - Satya Khuon
- Janelia Research Campus, Howard Hughes Medical Institute (HHMI), Ashburn, VA, USA
| | - Nikolaj Reiser
- Department of Radiology, University of Chicago, Chicago, IL, USA
| | - Yicong Wu
- Laboratory of High Resolution Optical Imaging, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, Maryland, USA
| | - Patrick La Riviere
- Department of Radiology, University of Chicago, Chicago, IL, USA
- MBL Fellows Program, Marine Biological Laboratory, Woods Hole, MA, USA
| | - Hari Shroff
- Janelia Research Campus, Howard Hughes Medical Institute (HHMI), Ashburn, VA, USA
- Laboratory of High Resolution Optical Imaging, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, Maryland, USA
- MBL Fellows Program, Marine Biological Laboratory, Woods Hole, MA, USA
| |
Collapse
|
13
|
Gardeazabal Rodriguez PF, Lilach Y, Ambegaonkar A, Vitali T, Jafri H, Sohn HW, Dalva M, Pierce S, Chung I. MAxSIM: multi-angle-crossing structured illumination microscopy with height-controlled mirror for 3D topological mapping of live cells. Commun Biol 2023; 6:1034. [PMID: 37828050 PMCID: PMC10570291 DOI: 10.1038/s42003-023-05380-2] [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: 01/04/2023] [Accepted: 09/21/2023] [Indexed: 10/14/2023] Open
Abstract
Mapping 3D plasma membrane topology in live cells can bring unprecedented insights into cell biology. Widefield-based super-resolution methods such as 3D-structured illumination microscopy (3D-SIM) can achieve twice the axial ( ~ 300 nm) and lateral ( ~ 100 nm) resolution of widefield microscopy in real time in live cells. However, twice-resolution enhancement cannot sufficiently visualize nanoscale fine structures of the plasma membrane. Axial interferometry methods including fluorescence light interference contrast microscopy and its derivatives (e.g., scanning angle interference microscopy) can determine nanoscale axial locations of proteins on and near the plasma membrane. Thus, by combining super-resolution lateral imaging of 2D-SIM with axial interferometry, we developed multi-angle-crossing structured illumination microscopy (MAxSIM) to generate multiple incident angles by fast, optoelectronic creation of diffraction patterns. Axial localization accuracy can be enhanced by placing cells on a bottom glass substrate, locating a custom height-controlled mirror (HCM) at a fixed axial position above the glass substrate, and optimizing the height reconstruction algorithm for noisy experimental data. The HCM also enables imaging of both the apical and basal surfaces of a cell. MAxSIM with HCM offers high-fidelity nanoscale 3D topological mapping of cell plasma membranes with near-real-time ( ~ 0.5 Hz) imaging of live cells and 3D single-molecule tracking.
Collapse
Affiliation(s)
| | - Yigal Lilach
- Nanofabrication and Imaging Center, George Washington University, Washington, DC, USA
| | - Abhijit Ambegaonkar
- Laboratory of Immunogenetics, National Institute of Allergy and Infectious Disease, National Institutes of Health, Rockville, MD, USA
| | - Teresa Vitali
- Department of Anatomy and Cell Biology, George Washington University, School of Medicine and Health Sciences, Washington, DC, USA
| | - Haani Jafri
- Department of Neuroscience, Thomas Jefferson University, Philadelphia, PA, USA
| | - Hae Won Sohn
- Laboratory of Immunogenetics, National Institute of Allergy and Infectious Disease, National Institutes of Health, Rockville, MD, USA
| | - Matthew Dalva
- Department of Neuroscience, Thomas Jefferson University, Philadelphia, PA, USA
- Department of Cell and Molecular Biology, Tulane University, New Orleans, LA, USA
| | - Susan Pierce
- Laboratory of Immunogenetics, National Institute of Allergy and Infectious Disease, National Institutes of Health, Rockville, MD, USA
| | - Inhee Chung
- Department of Anatomy and Cell Biology, George Washington University, School of Medicine and Health Sciences, Washington, DC, USA.
- Department of Biomedical Engineering, GW School of Engineering and Applied Science, George Washington University, Washington, DC, USA.
| |
Collapse
|
14
|
Yoon K, Han K, Tadesse K, Mandracchia B, Jia S. Simultaneous Multicolor Multifocal Scanning Microscopy. ACS PHOTONICS 2023; 10:3035-3041. [PMID: 37743934 PMCID: PMC10515623 DOI: 10.1021/acsphotonics.3c00205] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Indexed: 09/26/2023]
Abstract
Super-resolution fluorescence microscopy has revolutionized cell biology over the past decade, enabling the visualization of subcellular complexity with unparalleled clarity and detail. However, the rapid development of image-scanning-based super-resolution systems still restrains convenient access to commonly used instruments such as epi-fluorescence microscopes. Here, we present multifocal scanning microscopy (MSM) for super-resolution imaging with simultaneous multicolor acquisition and minimal instrumental complexity. MSM implements a stationary, interposed multifocal multicolor excitation by exploiting the motion of the specimens, realizing super-resolution microscopy through a general epi-fluorescence platform without compromising the image-scanning mechanism or inducing complex instrument alignment. The system is demonstrated with various phantom and biological specimens, and the results present effective resolution doubling, optical sectioning, and contrast enhancement. We anticipate MSM, as a highly accessible and compatible super-resolution technique, to offer a promising methodological pathway for broad cell biological discoveries.
Collapse
Affiliation(s)
- Kyungduck Yoon
- Wallace
H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia 30332, United States
- Parker
H. Petit Institute for Bioengineering and Biosciences, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
- George
W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Keyi Han
- Wallace
H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia 30332, United States
| | - Kidan Tadesse
- Wallace
H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia 30332, United States
- Parker
H. Petit Institute for Bioengineering and Biosciences, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Biagio Mandracchia
- Wallace
H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia 30332, United States
| | - Shu Jia
- Wallace
H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia 30332, United States
- Parker
H. Petit Institute for Bioengineering and Biosciences, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| |
Collapse
|
15
|
Ning K, Lu B, Wang X, Zhang X, Nie S, Jiang T, Li A, Fan G, Wang X, Luo Q, Gong H, Yuan J. Deep self-learning enables fast, high-fidelity isotropic resolution restoration for volumetric fluorescence microscopy. LIGHT, SCIENCE & APPLICATIONS 2023; 12:204. [PMID: 37640721 PMCID: PMC10462670 DOI: 10.1038/s41377-023-01230-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Revised: 07/04/2023] [Accepted: 07/12/2023] [Indexed: 08/31/2023]
Abstract
One intrinsic yet critical issue that troubles the field of fluorescence microscopy ever since its introduction is the unmatched resolution in the lateral and axial directions (i.e., resolution anisotropy), which severely deteriorates the quality, reconstruction, and analysis of 3D volume images. By leveraging the natural anisotropy, we present a deep self-learning method termed Self-Net that significantly improves the resolution of axial images by using the lateral images from the same raw dataset as rational targets. By incorporating unsupervised learning for realistic anisotropic degradation and supervised learning for high-fidelity isotropic recovery, our method can effectively suppress the hallucination with substantially enhanced image quality compared to previously reported methods. In the experiments, we show that Self-Net can reconstruct high-fidelity isotropic 3D images from organelle to tissue levels via raw images from various microscopy platforms, e.g., wide-field, laser-scanning, or super-resolution microscopy. For the first time, Self-Net enables isotropic whole-brain imaging at a voxel resolution of 0.2 × 0.2 × 0.2 μm3, which addresses the last-mile problem of data quality in single-neuron morphology visualization and reconstruction with minimal effort and cost. Overall, Self-Net is a promising approach to overcoming the inherent resolution anisotropy for all classes of 3D fluorescence microscopy.
Collapse
Affiliation(s)
- Kefu Ning
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
- HUST-Suzhou Institute for Brainsmatics, Suzhou, China
| | - Bolin Lu
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
- HUST-Suzhou Institute for Brainsmatics, Suzhou, China
| | - Xiaojun Wang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
- School of Biomedical Engineering, Hainan University, Haikou, China
| | - Xiaoyu Zhang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Shuo Nie
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Tao Jiang
- HUST-Suzhou Institute for Brainsmatics, Suzhou, China
| | - Anan Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
- HUST-Suzhou Institute for Brainsmatics, Suzhou, China
| | - Guoqing Fan
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaofeng Wang
- HUST-Suzhou Institute for Brainsmatics, Suzhou, China
| | - Qingming Luo
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
- HUST-Suzhou Institute for Brainsmatics, Suzhou, China
- School of Biomedical Engineering, Hainan University, Haikou, China
| | - Hui Gong
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China.
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China.
- HUST-Suzhou Institute for Brainsmatics, Suzhou, China.
| | - Jing Yuan
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China.
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China.
- HUST-Suzhou Institute for Brainsmatics, Suzhou, China.
| |
Collapse
|
16
|
Chareyre S, Li X, Anjuwon-Foster BR, Clifford S, Brogan A, Su Y, Shroff H, Ramamurthi KS. Cell division machinery drives cell-specific gene activation during bacterial differentiation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.10.552768. [PMID: 37790399 PMCID: PMC10542145 DOI: 10.1101/2023.08.10.552768] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
When faced with starvation, the bacterium Bacillus subtilis transforms itself into a dormant cell type called a "spore". Sporulation initiates with an asymmetric division event, which requires the relocation of the core divisome components FtsA and FtsZ, after which the sigma factor σF is exclusively activated in the smaller daughter cell. Compartment specific activation of σF requires the SpoIIE phosphatase, which displays a biased localization on one side of the asymmetric division septum and associates with the structural protein DivIVA, but the mechanism by which this preferential localization is achieved is unclear. Here, we isolated a variant of DivIVA that indiscriminately activates σF in both daughter cells due to promiscuous localization of SpoIIE, which was corrected by overproduction of FtsA and FtsZ. We propose that a unique feature of the sporulation septum, defined by the cell division machinery, drives the asymmetric localization of DivIVA and SpoIIE to trigger the initiation of the sporulation program.
Collapse
Affiliation(s)
- Sylvia Chareyre
- Laboratory of Molecular Biology, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Xuesong Li
- Laboratory of High Resolution Optical Imaging, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD, USA
- Janelia Research Campus, Howard Hughes Medical Institute (HHMI), Ashburn, VA, USA
| | - Brandon R Anjuwon-Foster
- Laboratory of Molecular Biology, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Sarah Clifford
- Laboratory of Molecular Biology, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Anna Brogan
- Laboratory of Molecular Biology, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Yijun Su
- Laboratory of High Resolution Optical Imaging, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD, USA
- Janelia Research Campus, Howard Hughes Medical Institute (HHMI), Ashburn, VA, USA
| | - Hari Shroff
- Laboratory of High Resolution Optical Imaging, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD, USA
- Janelia Research Campus, Howard Hughes Medical Institute (HHMI), Ashburn, VA, USA
| | - Kumaran S Ramamurthi
- Laboratory of Molecular Biology, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| |
Collapse
|
17
|
Cao R, Li Y, Chen X, Ge X, Li M, Guan M, Hou Y, Fu Y, Xu X, Leterrier C, Jiang S, Gao B, Xi P. Open-3DSIM: an open-source three-dimensional structured illumination microscopy reconstruction platform. Nat Methods 2023; 20:1183-1186. [PMID: 37474809 PMCID: PMC10406603 DOI: 10.1038/s41592-023-01958-0] [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: 12/01/2022] [Accepted: 06/12/2023] [Indexed: 07/22/2023]
Abstract
Open-3DSIM is an open-source reconstruction platform for three-dimensional structured illumination microscopy. We demonstrate its superior performance for artifact suppression and high-fidelity reconstruction relative to other algorithms on various specimens and over a range of signal-to-noise levels. Open-3DSIM also offers the capacity to extract dipole orientation, paving a new avenue for interpreting subcellular structures in six dimensions (xyzθλt). The platform is available as MATLAB code, a Fiji plugin and an Exe application to maximize user-friendliness.
Collapse
Affiliation(s)
- Ruijie Cao
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China
- National Biomedical Imaging Center, Peking University, Beijing, China
| | - Yaning Li
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China
- National Biomedical Imaging Center, Peking University, Beijing, China
| | - Xin Chen
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China
- National Biomedical Imaging Center, Peking University, Beijing, China
| | - Xichuan Ge
- Key Laboratory of Analytical Science and Technology of Hebei Province, College of Chemistry and Environment Science, Hebei University, Baoding, China
| | - Meiqi Li
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China
- National Biomedical Imaging Center, Peking University, Beijing, China
| | - Meiling Guan
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China
- National Biomedical Imaging Center, Peking University, Beijing, China
| | - Yiwei Hou
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China
- National Biomedical Imaging Center, Peking University, Beijing, China
| | - Yunzhe Fu
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China
- National Biomedical Imaging Center, Peking University, Beijing, China
| | - Xinzhu Xu
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China
- National Biomedical Imaging Center, Peking University, Beijing, China
| | | | - Shan Jiang
- Institute of Biomedical Engineering, Beijing Institute of Collaborative Innovation, Beijing, China
| | - Baoxiang Gao
- Key Laboratory of Analytical Science and Technology of Hebei Province, College of Chemistry and Environment Science, Hebei University, Baoding, China
| | - Peng Xi
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China.
- National Biomedical Imaging Center, Peking University, Beijing, China.
| |
Collapse
|
18
|
Zhang H, Wang J, Jin L, Zhu Y, Guo Y, Zhang M, Zhang Y, Wang Z, Su Y, Wu Y, Ji B, Toomre D, Liu X, Xu Y. Augmented Super-Resolution Radial Fluctuations (aSRRF) Pushing the Limits of Structured Illumination Microscopy. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.05.547885. [PMID: 37786707 PMCID: PMC10541617 DOI: 10.1101/2023.07.05.547885] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
Structured illumination microscopy (SIM) is a versatile super-resolution technique known for its compatibility with a wide range of probes and fast implementation. While 3D SIM is capable of achieving a spatial resolution of ∼120 nm laterally and ∼300 nm axially, attempting to further enhance the resolution through methods such as nonlinear SIM or 4-beam SIM introduces complexities in optical configurations, increased phototoxicity, and reduced temporal resolution. Here, we have developed a novel method that combines SIM with augmented super-resolution radial fluctuations (aSRRF) utilizing a single image through image augmentation. By applying aSRRF reconstruction to SIM images, we can enhance the SIM resolution to ∼50 nm isotopically, without requiring any modifications to the optical system or sample acquisition process. Additionaly, we have incorporated the aSRRF approach into an ImageJ plugin and demonstrated its versatility across various fluorescence microscopy images, showcasing a remarkable two-fold resolution increase.
Collapse
|
19
|
Du K, Zhou D, Zhou S, Zhang J, Liu Q, Bai X, Liu Q, Chen Y, Liu W, Kuang C. High-accuracy differential autofocus system with an electrically tunable lens. OPTICS LETTERS 2023; 48:2789-2792. [PMID: 37262211 DOI: 10.1364/ol.488673] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 04/19/2023] [Indexed: 06/03/2023]
Abstract
We propose a quasi-confocal microscopy autofocus system incorporating an electrically tunable lens (ETL) to achieve differential detection. The ETL changes its focal length to collect differential curves at speeds <300 Hz, allowing selective locking onto desired focal layers and high-speed differential operations close to the locked focal plane. By segmenting the system's pupil, the interference between the outgoing and incoming near-infrared beams is avoided, thereby greatly improving the signal-to-noise ratio. This ultra-sensitive system, with a focus drift accuracy better than 1/22 focal depth (∼20 nm @100× objective), provides a new, to the best of our knowledge, implementation pathway to meet the requirements of various microscopy techniques.
Collapse
|