1
|
Stegmeyer RI, Stasch M, Olesker D, Taylor JM, Mitchell TJ, Hosny NA, Kirschnick N, Spickermann G, Vestweber D, Volkery S. Intravital Microscopy With an Airy Beam Light Sheet Microscope Improves Temporal Resolution and Reduces Surgical Trauma. MICROSCOPY AND MICROANALYSIS : THE OFFICIAL JOURNAL OF MICROSCOPY SOCIETY OF AMERICA, MICROBEAM ANALYSIS SOCIETY, MICROSCOPICAL SOCIETY OF CANADA 2024:ozae099. [PMID: 39423019 DOI: 10.1093/mam/ozae099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/30/2024] [Revised: 08/15/2024] [Accepted: 09/06/2024] [Indexed: 10/21/2024]
Abstract
Intravital microscopy has emerged as a powerful imaging tool, which allows the visualization and precise understanding of rapid physiological processes at sites of inflammation in vivo, such as vascular permeability and leukocyte migration. Leukocyte interactions with the vascular endothelium can be characterized in the living organism in the murine cremaster muscle. Here, we present a microscopy technique using an Airy Beam Light Sheet microscope that has significant advantages over our previously used confocal microscopy systems. In comparison, the light sheet microscope offers near isotropic optical resolution and faster acquisition speed, while imaging a larger field of view. With less invasive surgery we can significantly reduce side effects such as bleeding, muscle twitching, and surgical inflammation. However, the increased acquisition speed requires exceptional tissue stability to avoid imaging artefacts. Since respiratory motion is transmitted to the tissue under investigation, we have developed a relocation algorithm that removes motion artefacts from our intravital microscopy images. Using these techniques, we are now able to obtain more detailed 3D time-lapse images of the cremaster vascular microcirculation, which allow us to observe the process of leukocyte emigration into the surrounding tissue with increased temporal resolution in comparison to our previous confocal approach.
Collapse
Affiliation(s)
- Rebekka I Stegmeyer
- Max Planck Institute for Molecular Biomedicine, Department Vascular Cell Biology, Röntgenstraße 20, 48161 Münster, North Rhine-Westphalia, Germany
| | - Malte Stasch
- Max Planck Institute for Molecular Biomedicine, BioOptic Service Unit, Röntgenstraße 20, 48161 Münster, North Rhine-Westphalia, Germany
| | - Daniel Olesker
- School of Physics and Astronomy, University of Glasgow, University Avenue B8 Kelvin Building, G12 8QQ, Glasgow, UK
- M Squared Life Limited, 14 East Bay Lane, The Press Centre, Here East, Queen Elizabeth Park, Stratford, E15 2GW, London, UK
| | - Jonathan M Taylor
- School of Physics and Astronomy, University of Glasgow, University Avenue B8 Kelvin Building, G12 8QQ, Glasgow, UK
| | - Thomas J Mitchell
- M Squared Life Limited, 14 East Bay Lane, The Press Centre, Here East, Queen Elizabeth Park, Stratford, E15 2GW, London, UK
| | - Neveen A Hosny
- M Squared Life Limited, 14 East Bay Lane, The Press Centre, Here East, Queen Elizabeth Park, Stratford, E15 2GW, London, UK
| | - Nils Kirschnick
- Max Planck Institute for Molecular Biomedicine, BioOptic Service Unit, Röntgenstraße 20, 48161 Münster, North Rhine-Westphalia, Germany
| | - Gunnar Spickermann
- M Squared Life Limited, 14 East Bay Lane, The Press Centre, Here East, Queen Elizabeth Park, Stratford, E15 2GW, London, UK
| | - Dietmar Vestweber
- Max Planck Institute for Molecular Biomedicine, Department Vascular Cell Biology, Röntgenstraße 20, 48161 Münster, North Rhine-Westphalia, Germany
| | - Stefan Volkery
- Max Planck Institute for Molecular Biomedicine, BioOptic Service Unit, Röntgenstraße 20, 48161 Münster, North Rhine-Westphalia, Germany
| |
Collapse
|
2
|
Xu C, Nedergaard M, Fowell DJ, Friedl P, Ji N. Multiphoton fluorescence microscopy for in vivo imaging. Cell 2024; 187:4458-4487. [PMID: 39178829 PMCID: PMC11373887 DOI: 10.1016/j.cell.2024.07.036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Revised: 07/18/2024] [Accepted: 07/22/2024] [Indexed: 08/26/2024]
Abstract
Multiphoton fluorescence microscopy (MPFM) has been a game-changer for optical imaging, particularly for studying biological tissues deep within living organisms. MPFM overcomes the strong scattering of light in heterogeneous tissue by utilizing nonlinear excitation that confines fluorescence emission mostly to the microscope focal volume. This enables high-resolution imaging deep within intact tissue and has opened new avenues for structural and functional studies. MPFM has found widespread applications and has led to numerous scientific discoveries and insights into complex biological processes. Today, MPFM is an indispensable tool in many research communities. Its versatility and effectiveness make it a go-to technique for researchers investigating biological phenomena at the cellular and subcellular levels in their native environments. In this Review, the principles, implementations, capabilities, and limitations of MPFM are presented. Three application areas of MPFM, neuroscience, cancer biology, and immunology, are reviewed in detail and serve as examples for applying MPFM to biological research.
Collapse
Affiliation(s)
- Chris Xu
- School of Applied and Engineering Physics, Cornell University, Ithaca, NY 14850, USA
| | - Maiken Nedergaard
- Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of Copenhagen, Nørre Alle 3B, 2200 Copenhagen, Denmark; University of Rochester Medical School, 601 Elmwood Avenue, Rochester, NY 14642, USA
| | - Deborah J Fowell
- Department of Microbiology & Immunology, Cornell University, Ithaca, NY 14853, USA
| | - Peter Friedl
- Department of Medical BioSciences, Radboud University Medical Centre, Geert Grooteplein 26-28, Nijmegen HB 6500, the Netherlands
| | - Na Ji
- Department of Neuroscience, Department of Physics, University of California Berkeley, Berkeley, CA 94720, USA.
| |
Collapse
|
3
|
Wang Y, Heymann F, Peiseler M. Intravital imaging: dynamic insights into liver immunity in health and disease. Gut 2024; 73:1364-1375. [PMID: 38777574 DOI: 10.1136/gutjnl-2023-331739] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Accepted: 05/09/2024] [Indexed: 05/25/2024]
Abstract
Inflammation is a critical component of most acute and chronic liver diseases. The liver is a unique immunological organ with a dense vascular network, leading to intense crosstalk between tissue-resident immune cells, passenger leucocytes and parenchymal cells. During acute and chronic liver diseases, the multifaceted immune response is involved in disease promoting and repair mechanisms, while upholding core liver immune functions. In recent years, single-cell technologies have unravelled a previously unknown heterogeneity of immune cells, reshaping the complexity of the hepatic immune response. However, inflammation is a dynamic biological process, encompassing various immune cells, orchestrated in temporal and spatial dimensions, and driven by multiorgan signals. Intravital microscopy (IVM) has emerged as a powerful tool to investigate immunity by visualising the dynamic interplay between different immune cells and their surroundings within a near-natural environment. In this review, we summarise the experimental considerations to perform IVM and highlight recent technological developments. Furthermore, we outline the unique contributions of IVM to our understanding of liver immunity. Through the lens of liver disease, we discuss novel immune-mediated disease mechanisms uncovered by imaging-based studies.
Collapse
Affiliation(s)
- Yuting Wang
- Department of Hepatology & Gastroenterology, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Felix Heymann
- Department of Hepatology & Gastroenterology, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Moritz Peiseler
- Department of Hepatology & Gastroenterology, Charité Universitätsmedizin Berlin, Berlin, Germany
- Berlin Institute of Health at Charité, Berlin, Germany
| |
Collapse
|
4
|
Mazzaglia C, Munir H, Lei IM, Gerigk M, Huang YYS, Shields JD. Modeling Structural Elements and Functional Responses to Lymphatic-Delivered Cues in a Murine Lymph Node on a Chip. Adv Healthc Mater 2024; 13:e2303720. [PMID: 38626388 DOI: 10.1002/adhm.202303720] [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: 10/26/2023] [Revised: 04/08/2024] [Indexed: 04/18/2024]
Abstract
Lymph nodes (LNs) are organs of the immune system, critical for maintenance of homeostasis and initiation of immune responses, yet there are few models that accurately recapitulate LN functions in vitro. To tackle this issue, an engineered murine LN (eLN) has been developed, replicating key cellular components of the mouse LN; incorporating primary murine lymphocytes, fibroblastic reticular cells, and lymphatic endothelial cells. T and B cell compartments are incorporated within the eLN that mimic LN cortex and paracortex architectures. When challenged, the eLN elicits both robust inflammatory responses and antigen-specific immune activation, showing that the system can differentiate between non specific and antigen-specific stimulation and can be monitored in real time. Beyond immune responses, this model also enables interrogation of changes in stromal cells, thus permitting investigations of all LN cellular components in homeostasis and different disease settings, such as cancer. Here, how LN behavior can be influenced by murine melanoma-derived factors is presented. In conclusion, the eLN model presents a promising platform for in vitro study of LN biology that will enhance understanding of stromal and immune responses in the murine LN, and in doing so will enable development of novel therapeutic strategies to improve LN responses in disease.
Collapse
Affiliation(s)
- Corrado Mazzaglia
- MRC Cancer Unit, University of Cambridge, Cambridge, CB2 0XZ, UK
- The Nanoscience Centre, University of Cambridge, Cambridge, CB3 0FF, UK
| | - Hafsa Munir
- Helmholtz Institute for Translational Oncology Mainz (HI-TRON Mainz), 55131, Mainz, Germany
- Division of Dermal Oncoimmunology, German Cancer Research Centre (DKFZ), 69120, Heidelberg, Germany
| | - Iek Man Lei
- Department of Engineering, University of Cambridge, Cambridge, CB2 1PZ, UK
| | - Magda Gerigk
- The Nanoscience Centre, University of Cambridge, Cambridge, CB3 0FF, UK
- Department of Engineering, University of Cambridge, Cambridge, CB2 1PZ, UK
| | - Yan Yan Shery Huang
- The Nanoscience Centre, University of Cambridge, Cambridge, CB3 0FF, UK
- Department of Engineering, University of Cambridge, Cambridge, CB2 1PZ, UK
| | - Jacqueline D Shields
- MRC Cancer Unit, University of Cambridge, Cambridge, CB2 0XZ, UK
- Translational Medical Sciences, School of Medicine, University of Nottingham Biodiscovery Institute, Nottingham, NG7 2RD, UK
| |
Collapse
|
5
|
Lu Z, Zuo S, Shi M, Fan J, Xie J, Xiao G, Yu L, Wu J, Dai Q. Long-term intravital subcellular imaging with confocal scanning light-field microscopy. Nat Biotechnol 2024:10.1038/s41587-024-02249-5. [PMID: 38802562 DOI: 10.1038/s41587-024-02249-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2023] [Accepted: 04/17/2024] [Indexed: 05/29/2024]
Abstract
Long-term observation of subcellular dynamics in living organisms is limited by background fluorescence originating from tissue scattering or dense labeling. Existing confocal approaches face an inevitable tradeoff among parallelization, resolution and phototoxicity. Here we present confocal scanning light-field microscopy (csLFM), which integrates axially elongated line-confocal illumination with the rolling shutter in scanning light-field microscopy (sLFM). csLFM enables high-fidelity, high-speed, three-dimensional (3D) imaging at near-diffraction-limit resolution with both optical sectioning and low phototoxicity. By simultaneous 3D excitation and detection, the excitation intensity can be reduced below 1 mW mm-2, with 15-fold higher signal-to-background ratio over sLFM. We imaged subcellular dynamics over 25,000 timeframes in optically challenging environments in different species, such as migrasome delivery in mouse spleen, retractosome generation in mouse liver and 3D voltage imaging in Drosophila. Moreover, csLFM facilitates high-fidelity, large-scale neural recording with reduced crosstalk, leading to high orientation selectivity to visual stimuli, similar to two-photon microscopy, which aids understanding of neural coding mechanisms.
Collapse
Affiliation(s)
- Zhi Lu
- Department of Automation, Tsinghua University, Beijing, China
- Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing, China
- Beijing Key Laboratory of Multi-dimension & Multi-scale Computational Photography (MMCP), Tsinghua University, Beijing, China
- IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, China
- Zhejiang Hehu Technology, Hangzhou, China
- Hangzhou Zhuoxi Institute of Brain and Intelligence, Hangzhou, China
| | - Siqing Zuo
- Department of Automation, Tsinghua University, Beijing, China
- Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing, China
- Beijing Key Laboratory of Multi-dimension & Multi-scale Computational Photography (MMCP), Tsinghua University, Beijing, China
- IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, China
| | - Minghui Shi
- 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, China
| | - Jiaqi Fan
- Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing, China
- Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China
| | - Jingyu Xie
- Department of Automation, Tsinghua University, Beijing, China
- Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing, China
| | - Guihua Xiao
- Department of Automation, Tsinghua University, Beijing, China
- Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing, 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, China.
| | - Jiamin Wu
- Department of Automation, Tsinghua University, Beijing, China.
- Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing, China.
- Beijing Key Laboratory of Multi-dimension & Multi-scale Computational Photography (MMCP), Tsinghua University, Beijing, China.
- IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, China.
- Shanghai AI Laboratory, Shanghai, China.
| | - Qionghai Dai
- Department of Automation, Tsinghua University, Beijing, China.
- Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing, China.
- Beijing Key Laboratory of Multi-dimension & Multi-scale Computational Photography (MMCP), Tsinghua University, Beijing, China.
- IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, China.
- Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing, China.
| |
Collapse
|
6
|
Schäfer PSL, Dimitrov D, Villablanca EJ, Saez-Rodriguez J. Integrating single-cell multi-omics and prior biological knowledge for a functional characterization of the immune system. Nat Immunol 2024; 25:405-417. [PMID: 38413722 DOI: 10.1038/s41590-024-01768-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 01/16/2024] [Indexed: 02/29/2024]
Abstract
The immune system comprises diverse specialized cell types that cooperate to defend the host against a wide range of pathogenic threats. Recent advancements in single-cell and spatial multi-omics technologies provide rich information about the molecular state of immune cells. Here, we review how the integration of single-cell and spatial multi-omics data with prior knowledge-gathered from decades of detailed biochemical studies-allows us to obtain functional insights, focusing on gene regulatory processes and cell-cell interactions. We present diverse applications in immunology and critically assess underlying assumptions and limitations. Finally, we offer a perspective on the ongoing technological and algorithmic developments that promise to get us closer to a systemic mechanistic understanding of the immune system.
Collapse
Affiliation(s)
- Philipp Sven Lars Schäfer
- Institute for Computational Bioscience, Faculty of Medicine and Heidelberg University Hospital, Heidelberg University, Heidelberg, Germany
| | - Daniel Dimitrov
- Institute for Computational Bioscience, Faculty of Medicine and Heidelberg University Hospital, Heidelberg University, Heidelberg, Germany
| | - Eduardo J Villablanca
- Division of Immunology and Allergy, Department of Medicine Solna, Karolinska Institute and Karolinska University Hospital, Stockholm, Sweden
- Center of Molecular Medicine, Stockholm, Sweden
| | - Julio Saez-Rodriguez
- Institute for Computational Bioscience, Faculty of Medicine and Heidelberg University Hospital, Heidelberg University, Heidelberg, Germany.
| |
Collapse
|
7
|
Wang J, Dong D, Zhao W, Wang J. Intravital microscopy visualizes innate immune crosstalk and function in tissue microenvironment. Eur J Immunol 2024; 54:e2350458. [PMID: 37830252 DOI: 10.1002/eji.202350458] [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: 03/01/2023] [Revised: 10/11/2023] [Accepted: 10/12/2023] [Indexed: 10/14/2023]
Abstract
Significant advances have been made in the field of intravital microscopy (IVM) on myeloid cells due to the growing number of validated fluorescent probes and reporter mice. IVM provides a visualization platform to directly observe cell behavior and deepen our understanding of cellular dynamics, heterogeneity, plasticity, and cell-cell communication in native tissue environments. This review outlines the current studies on the dynamic interaction and function of innate immune cells with a focus on those that are studied with IVM and covers the advances in data analysis with emerging artificial intelligence-based algorithms. Finally, the prospects of IVM on innate immune cells are discussed.
Collapse
Affiliation(s)
- Jin Wang
- Shanghai Institute of Immunology, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Dong Dong
- Shanghai Institute of Immunology, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Department of Thoracic Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Wenying Zhao
- Shanghai Institute of Immunology, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jing Wang
- Shanghai Institute of Immunology, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Center for Immune-related Diseases at Shanghai Institute of Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| |
Collapse
|
8
|
Peng X, Wang Y, Zhang J, Zhang Z, Qi S. Intravital imaging of the functions of immune cells in the tumor microenvironment during immunotherapy. Front Immunol 2023; 14:1288273. [PMID: 38124754 PMCID: PMC10730658 DOI: 10.3389/fimmu.2023.1288273] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Accepted: 11/20/2023] [Indexed: 12/23/2023] Open
Abstract
Cancer immunotherapy has developed rapidly in recent years and stands as one of the most promising techniques for combating cancer. To develop and optimize cancer immunotherapy, it is crucial to comprehend the interactions between immune cells and tumor cells in the tumor microenvironment (TME). The TME is complex, with the distribution and function of immune cells undergoing dynamic changes. There are several research techniques to study the TME, and intravital imaging emerges as a powerful tool for capturing the spatiotemporal dynamics, especially the movement behavior and the immune function of various immune cells in real physiological state. Intravital imaging has several advantages, such as high spatio-temporal resolution, multicolor, dynamic and 4D detection, making it an invaluable tool for visualizing the dynamic processes in the TME. This review summarizes the workflow for intravital imaging technology, multi-color labeling methods, optical imaging windows, methods of imaging data analysis and the latest research in visualizing the spatio-temporal dynamics and function of immune cells in the TME. It is essential to investigate the role played by immune cells in the tumor immune response through intravital imaging. The review deepens our understanding of the unique contribution of intravital imaging to improve the efficiency of cancer immunotherapy.
Collapse
Affiliation(s)
- Xuwen Peng
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yuke Wang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Jie Zhang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Zhihong Zhang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Shuhong Qi
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei, China
| |
Collapse
|
9
|
Abstract
Multiplex imaging has emerged as an invaluable tool for immune-oncologists and translational researchers, enabling them to examine intricate interactions among immune cells, stroma, matrix, and malignant cells within the tumor microenvironment (TME). It holds significant promise in the quest to discover improved biomarkers for treatment stratification and identify novel therapeutic targets. Nonetheless, several challenges exist in the realms of study design, experiment optimization, and data analysis. In this review, our aim is to present an overview of the utilization of multiplex imaging in immuno-oncology studies and inform novice researchers about the fundamental principles at each stage of the imaging and analysis process.
Collapse
Affiliation(s)
- Chen Zhao
- Thoracic and GI Malignancies Branch, CCR, NCI, Bethesda, Maryland, USA
- Lymphocyte Biology Section, Laboratory of Immune System Biology, NIAID, Bethesda, Maryland, USA
| | - Ronald N Germain
- Lymphocyte Biology Section, Laboratory of Immune System Biology, NIAID, Bethesda, Maryland, USA
| |
Collapse
|
10
|
Zhao Z, Zhou Y, Liu B, He J, Zhao J, Cai Y, Fan J, Li X, Wang Z, Lu Z, Wu J, Qi H, Dai Q. Two-photon synthetic aperture microscopy for minimally invasive fast 3D imaging of native subcellular behaviors in deep tissue. Cell 2023; 186:2475-2491.e22. [PMID: 37178688 DOI: 10.1016/j.cell.2023.04.016] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 02/21/2023] [Accepted: 04/10/2023] [Indexed: 05/15/2023]
Abstract
Holistic understanding of physio-pathological processes requires noninvasive 3D imaging in deep tissue across multiple spatial and temporal scales to link diverse transient subcellular behaviors with long-term physiogenesis. Despite broad applications of two-photon microscopy (TPM), there remains an inevitable tradeoff among spatiotemporal resolution, imaging volumes, and durations due to the point-scanning scheme, accumulated phototoxicity, and optical aberrations. Here, we harnessed the concept of synthetic aperture radar in TPM to achieve aberration-corrected 3D imaging of subcellular dynamics at a millisecond scale for over 100,000 large volumes in deep tissue, with three orders of magnitude reduction in photobleaching. With its advantages, we identified direct intercellular communications through migrasome generation following traumatic brain injury, visualized the formation process of germinal center in the mouse lymph node, and characterized heterogeneous cellular states in the mouse visual cortex, opening up a horizon for intravital imaging to understand the organizations and functions of biological systems at a holistic level.
Collapse
Affiliation(s)
- Zhifeng Zhao
- 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; Hangzhou Zhuoxi Institute of Brain and Intelligence, Hangzhou 311100, China
| | - Yiliang Zhou
- 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; Hangzhou Zhuoxi Institute of Brain and Intelligence, Hangzhou 311100, China
| | - Bo Liu
- Tsinghua-Peking Center for Life Sciences, Beijing 100084, China; Laboratory of Dynamic Immunobiology, Institute for Immunology, Tsinghua University, Beijing 100084, China; Department of Basic Medical Sciences, School of Medicine, Tsinghua University, Beijing 100084, China
| | - Jing He
- 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
| | - Jiayin Zhao
- 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; Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518071, 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; IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing 100084, 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
| | - Xinyang 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; Hangzhou Zhuoxi Institute of Brain and Intelligence, Hangzhou 311100, China; Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518071, China
| | - Zilin Wang
- Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing 100084, China; Department of Anesthesiology, the First Medical Center, Chinese PLA General Hospital, Beijing 100853, 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; Hangzhou Zhuoxi Institute of Brain and Intelligence, Hangzhou 311100, China
| | - 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.
| | - Hai Qi
- Tsinghua-Peking Center for Life Sciences, Beijing 100084, China; Laboratory of Dynamic Immunobiology, Institute for Immunology, Tsinghua University, Beijing 100084, China; Department of Basic Medical Sciences, School of Medicine, Tsinghua University, Beijing 100084, China; Beijing Key Laboratory for Immunological Research on Chronic Diseases, Tsinghua University, Beijing 100084, China; Beijing Frontier Research Center for Biological Structure, 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.
| |
Collapse
|
11
|
Dall’Olio L, Bolognesi M, Borghesi S, Cattoretti G, Castellani G. BRAQUE: Bayesian Reduction for Amplified Quantization in UMAP Embedding. ENTROPY (BASEL, SWITZERLAND) 2023; 25:354. [PMID: 36832720 PMCID: PMC9955093 DOI: 10.3390/e25020354] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Revised: 02/01/2023] [Accepted: 02/10/2023] [Indexed: 06/09/2023]
Abstract
Single-cell biology has revolutionized the way we understand biological processes. In this paper, we provide a more tailored approach to clustering and analyzing spatial single-cell data coming from immunofluorescence imaging techniques. We propose Bayesian Reduction for Amplified Quantization in UMAP Embedding (BRAQUE) as an integrative novel approach, from data preprocessing to phenotype classification. BRAQUE starts with an innovative preprocessing, named Lognormal Shrinkage, which is able to enhance input fragmentation by fitting a lognormal mixture model and shrink each component towards its median, in order to help further the clustering step in finding more separated and clear clusters. Then, BRAQUE's pipeline consists of a dimensionality reduction step performed using UMAP, and a clustering performed using HDBSCAN on UMAP embedding. In the end, clusters are assigned to a cell type by experts, using effects size measures to rank markers and identify characterizing markers (Tier 1), and possibly characterize markers (Tier 2). The number of total cell types in one lymph node detectable with these technologies is unknown and difficult to predict or estimate. Therefore, with BRAQUE, we achieved a higher granularity than other similar algorithms such as PhenoGraph, following the idea that merging similar clusters is easier than splitting unclear ones into clear subclusters.
Collapse
Affiliation(s)
- Lorenzo Dall’Olio
- Department of Physics and Astronomy, University of Bologna, 40127 Bologna, Italy
| | - Maddalena Bolognesi
- Department of Medicine and Surgery, University of Milano Bicocca, 20900 Monza, Italy
| | - Simone Borghesi
- Department of Mathematics and Applications, University of Milano Bicocca, 20126 Milan, Italy
| | - Giorgio Cattoretti
- Department of Medicine and Surgery, University of Milano Bicocca, 20900 Monza, Italy
| | - Gastone Castellani
- Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, 40127 Bologna, Italy
| |
Collapse
|
12
|
Konishi Y, Terai K. In vivo imaging of inflammatory response in cancer research. Inflamm Regen 2023; 43:10. [PMID: 36750856 PMCID: PMC9903460 DOI: 10.1186/s41232-023-00261-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Accepted: 01/27/2023] [Indexed: 02/09/2023] Open
Abstract
Inflammation can contribute to the development and progression of cancer. The inflammatory responses in the tumor microenvironment are shaped by complex sequences of dynamic intercellular cross-talks among diverse types of cells, and recapitulation of these dynamic events in vitro has yet to be achieved. Today, intravital microscopy with two-photon excitation microscopes (2P-IVM) is the mainstay technique for observing intercellular cross-talks in situ, unraveling cellular and molecular mechanisms in the context of their spatiotemporal dynamics. In this review, we summarize the current state of 2P-IVM with fluorescent indicators of signal transduction to reveal the cross-talks between cancer cells and surrounding cells including both immune and non-immune cells. We also discuss the potential application of red-shifted indicators along with optogenetic tools to 2P-IVM. In an era of single-cell transcriptomics and data-driven research, 2P-IVM will remain a key advantage in delivering the missing spatiotemporal context in the field of cancer research.
Collapse
Affiliation(s)
- Yoshinobu Konishi
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Kenta Terai
- Department of Pathology and Biology of Diseases, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
| |
Collapse
|
13
|
Lee SE, Rudd BD, Smith NL. Fate-mapping mice: new tools and technology for immune discovery. Trends Immunol 2022; 43:195-209. [PMID: 35094945 PMCID: PMC8882138 DOI: 10.1016/j.it.2022.01.004] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 01/04/2022] [Accepted: 01/05/2022] [Indexed: 12/20/2022]
Abstract
The fate-mapping mouse has become an essential tool in the immunologist's toolbox. Although traditionally used by developmental biologists to trace the origins of cells, immunologists are turning to fate-mapping to better understand the development and function of immune cells. Thus, an expansion in the variety of fate-mapping mouse models has occurred to answer fundamental questions about the immune system. These models are also being combined with new genetic tools to study cancer, infection, and autoimmunity. In this review, we summarize different types of fate-mapping mice and describe emerging technologies that might allow immunologists to leverage this valuable tool and expand our functional knowledge of the immune system.
Collapse
Affiliation(s)
- Scarlett E Lee
- Department of Microbiology and Immunology, Cornell University, Ithaca, NY 14850, USA
| | - Brian D Rudd
- Department of Microbiology and Immunology, Cornell University, Ithaca, NY 14850, USA
| | - Norah L Smith
- Department of Microbiology and Immunology, Cornell University, Ithaca, NY 14850, USA.
| |
Collapse
|