101
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Li Y, Ding Z, Deng L, Fan G, Zhang Q, Gong H, Li A, Yuan J, Chen J. Precision vibratome for high-speed ultrathin biotissue cutting and organ-wide imaging. iScience 2021; 24:103016. [PMID: 34522859 PMCID: PMC8426277 DOI: 10.1016/j.isci.2021.103016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Revised: 06/25/2021] [Accepted: 08/18/2021] [Indexed: 10/31/2022] Open
Abstract
Cutting tissues into ultrathin slices is highly desired in sectioning-based organ-wide imaging. However, it is difficult to perform tissue cutting at a high speed with excellent quality. Here, we design a precision vibratome based on a paired double parallelogram flexure, which enables a vibrating blade to move strictly along a straight line. Meanwhile, we develop a high-speed cutting method that does not compromise cutting quality, which the vibratome operated at a high frequency mode. The characterized parasitic motion errors of a 180-Hz vibratome were less than 300 nm. It achieved a cutting speed six times that of an 85-Hz vibratome with acceptable quality. The capacity of the vibratome was investigated by organ-wide imaging, and the results revealed that it can be adapted in different tissues, such as the mouse brain and liver. This new vibratome shows great potential in speeding up organ-wide imaging applications especially for large volume biotissues.
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Affiliation(s)
- Yafeng Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China.,MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China.,Innovation Institute, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Zhangheng Ding
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China.,MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Lei Deng
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China.,MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Guoqing Fan
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China.,MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Qi Zhang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China.,MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Hui Gong
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China.,MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China.,HUST-Suzhou Institute for Brainsmatics, Suzhou 215125, China
| | - Anan Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China.,MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China.,HUST-Suzhou Institute for Brainsmatics, Suzhou 215125, China
| | - Jing Yuan
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China.,MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China.,HUST-Suzhou Institute for Brainsmatics, Suzhou 215125, China
| | - Jianwei Chen
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China.,MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China.,HUST-Suzhou Institute for Brainsmatics, Suzhou 215125, China
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102
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Zhu J, Liu X, Deng Y, Li D, Yu T, Zhu D. Tissue optical clearing for 3D visualization of vascular networks: A review. Vascul Pharmacol 2021; 141:106905. [PMID: 34506969 DOI: 10.1016/j.vph.2021.106905] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Revised: 08/31/2021] [Accepted: 09/02/2021] [Indexed: 12/01/2022]
Abstract
Reconstruction of the vasculature of intact tissues/organs down to the capillary level is essential for understanding the development and remodeling of vascular networks under physiological and pathological conditions. Optical imaging techniques can provide sufficient resolution to distinguish small vessels with several microns, but the imaging depth is somewhat limited due to the high light scattering of opaque tissue. Recently, various tissue optical clearing methods have been developed to overcome light attenuation and improve the imaging depth both for ex-vivo and in-vivo visualizations. Tissue clearing combined with vessel labeling techniques and advanced optical tomography enables successful mapping of the vasculature of different tissues/organs, as well as dynamically monitoring vessel function under normal and pathological conditions. Here, we briefly introduce the commonly-used labeling strategies for entire vascular networks, the current tissue optical clearing techniques available for various tissues, as well as the advanced optical imaging techniques for fast, high-resolution structural and functional imaging for blood vessels. We also discuss the applications of these techniques in the 3D visualization of vascular networks in normal tissues, and the vascular remodeling in several typical pathological models in clinical research. This review is expected to provide valuable insights for researchers to study the potential mechanisms of various vessel-associated diseases using tissue optical clearing pipeline.
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Affiliation(s)
- Jingtan Zhu
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China; MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Xiaomei Liu
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China; MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Yating Deng
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China; MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Dongyu Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China; MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Tingting Yu
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China; MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China.
| | - Dan Zhu
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China; MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
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103
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Abstract
Tissue clearing increases the transparency of late developmental stages and enables deep imaging in fixed organisms. Successful implementation of these methodologies requires a good grasp of sample processing, imaging and the possibilities offered by image analysis. In this Primer, we highlight how tissue clearing can revolutionize the histological analysis of developmental processes and we advise on how to implement effective clearing protocols, imaging strategies and analysis methods for developmental biology.
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Affiliation(s)
| | - Nicolas Renier
- Sorbonne Université, Paris Brain Institute – ICM, INSERM, CNRS, AP-HP, Hôpital de la Pitié Salpêtrière, 75013 Paris, France
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104
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Application of a Tissue Clearing Method for the Analysis of Dopaminergic Axonal Projections. Methods Mol Biol 2021. [PMID: 34043200 DOI: 10.1007/978-1-0716-1495-2_14] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register]
Abstract
Parkinson's disease (PD) is a neurodegenerative disorder characterized with the progressive loss of dopaminergic (DA) neurons within the substantia nigra pars compacta (SNc). Quantitative analysis of neuronal loss including neuronal processes, axons and dendrites, would advance the understanding of the pathogenesis of PD. ScaleS, an aqueous tissue clearing method, provides stable tissue preservation while maintaining potent clearing capability, allowing quantitative three-dimensional (3D) imaging of biological tissues. In this chapter, we describe detailed procedures for 3D imaging of brain slice tissues with ScaleS technique. These include brain slice preparation, tissue clarification, chemical and immunohistochemical labeling (ChemScale and AbScale), and observation of labeled tissues using a confocal laser scanning microscope (CLSM).
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105
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Olianti C, Giardini F, Lazzeri E, Costantini I, Silvestri L, Coppini R, Cerbai E, Pavone FS, Sacconi L. Optical clearing in cardiac imaging: A comparative study. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2021; 168:10-17. [PMID: 34358555 DOI: 10.1016/j.pbiomolbio.2021.07.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Accepted: 07/29/2021] [Indexed: 10/20/2022]
Abstract
The optical clearing of the cardiac tissue has always been a challenging goal to obtain successful three-dimensional reconstructions of entire hearts. Typically, the developed protocols are targeted at the clearing of the brain; cardiac tissue requires proper arrangements to the original protocols, which are usually tough and time-consuming to figure out. Here, we present the application of three different clearing methodologies on mouse hearts: uDISCO, CLARITY, and SHIELD. For each approach, we describe the required optimizations that we have developed to improve the outcome; in particular, we focus on comparing the features of the tissue after the application of each methodology, especially in terms of tissue preservation, transparency, and staining. We found that the uDISCO protocol induces strong fiber delamination of the cardiac tissue, thus reducing the reliability of structural analyses. The CLARITY protocol confers a high level of transparency to the heart and allows deep penetration of the fluorescent dyes; however, it requires long times for the clearing and the tissue loses its robustness. The SHIELD methodology, indeed, is very promising for tissue maintenance since it preserves its consistency and provides ideal transparency, but further approaches are needed to obtain homogeneous staining of the whole heart. Since the CLARITY procedure, despite the disadvantages in terms of tissue preservation and timings, is actually the most suitable approach to image labeled samples in depth, we optimized and performed the methodology also on human cardiac tissue from control hearts and hearts with hypertrophic cardiomyopathy.
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Affiliation(s)
- Camilla Olianti
- European Laboratory for Non-Linear Spectroscopy, Sesto Fiorentino, 50019, Italy
| | - Francesco Giardini
- European Laboratory for Non-Linear Spectroscopy, Sesto Fiorentino, 50019, Italy
| | - Erica Lazzeri
- European Laboratory for Non-Linear Spectroscopy, Sesto Fiorentino, 50019, Italy
| | - Irene Costantini
- European Laboratory for Non-Linear Spectroscopy, Sesto Fiorentino, 50019, Italy; National Institute of Optics, National Research Council, Florence, 50125, Italy; Department of Biology, University of Florence, Sesto Fiorentino, 50019, Italy
| | - Ludovico Silvestri
- European Laboratory for Non-Linear Spectroscopy, Sesto Fiorentino, 50019, Italy; National Institute of Optics, National Research Council, Florence, 50125, Italy; Department of Physics and Astronomy, University of Florence, Sesto Fiorentino, 50019, Italy
| | - Raffaele Coppini
- Department of Neurosciences, Psychology, Drugs and Child Health, University of Florence, Italy
| | - Elisabetta Cerbai
- European Laboratory for Non-Linear Spectroscopy, Sesto Fiorentino, 50019, Italy; Department of Neurosciences, Psychology, Drugs and Child Health, University of Florence, Italy
| | - Francesco S Pavone
- European Laboratory for Non-Linear Spectroscopy, Sesto Fiorentino, 50019, Italy; National Institute of Optics, National Research Council, Florence, 50125, Italy; Department of Physics and Astronomy, University of Florence, Sesto Fiorentino, 50019, Italy
| | - Leonardo Sacconi
- European Laboratory for Non-Linear Spectroscopy, Sesto Fiorentino, 50019, Italy; National Institute of Optics, National Research Council, Florence, 50125, Italy; Institute for Experimental Cardiovascular Medicine, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
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106
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Hofmann J, Keppler SJ. Tissue clearing and 3D imaging - putting immune cells into context. J Cell Sci 2021; 134:271108. [PMID: 34342351 DOI: 10.1242/jcs.258494] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
A better understanding of cell-cell and cell-niche interactions is crucial to comprehend the complexity of inflammatory or pathophysiological scenarios such as tissue damage during viral infections, the tumour microenvironment and neuroinflammation. Optical clearing and 3D volumetric imaging of large tissue pieces or whole organs is a rapidly developing methodology that holds great promise for the in-depth study of cells in their natural surroundings. These methods have mostly been applied to image structural components such as endothelial cells and neuronal architecture. Recent work now highlights the possibility of studying immune cells in detail within their respective immune niches. This Review summarizes recent developments in tissue clearing methods and 3D imaging, with a focus on the localization and quantification of immune cells. We first provide background to the optical challenges involved and their solutions before discussing published protocols for tissue clearing, the limitations of 3D imaging of immune cells and image analysis. Furthermore, we highlight possible applications for tissue clearing and propose future developments for the analysis of immune cells within homeostatic or inflammatory immune niches.
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Affiliation(s)
- Julian Hofmann
- Institute for Clinical Chemistry and Pathobiochemistry, München rechts der Isar (MRI), Technical University Munich, 81675 Munich, Germany.,TranslaTUM, Center for Translational Cancer Research, Technical University Munich, 81675 Munich, Germany
| | - Selina J Keppler
- Institute for Clinical Chemistry and Pathobiochemistry, München rechts der Isar (MRI), Technical University Munich, 81675 Munich, Germany.,TranslaTUM, Center for Translational Cancer Research, Technical University Munich, 81675 Munich, Germany
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107
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Universal autofocus for quantitative volumetric microscopy of whole mouse brains. Nat Methods 2021; 18:953-958. [PMID: 34312564 DOI: 10.1038/s41592-021-01208-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Accepted: 06/14/2021] [Indexed: 11/08/2022]
Abstract
Unbiased quantitative analysis of macroscopic biological samples demands fast imaging systems capable of maintaining high resolution across large volumes. Here we introduce RAPID (rapid autofocusing via pupil-split image phase detection), a real-time autofocus method applicable in every widefield-based microscope. RAPID-enabled light-sheet microscopy reliably reconstructs intact, cleared mouse brains with subcellular resolution, and allowed us to characterize the three-dimensional (3D) spatial clustering of somatostatin-positive neurons in the whole encephalon, including densely labeled areas. Furthermore, it enabled 3D morphological analysis of microglia across the entire brain. Beyond light-sheet microscopy, we demonstrate that RAPID maintains high image quality in various settings, from in vivo fluorescence imaging to 3D tracking of fast-moving organisms. RAPID thus provides a flexible autofocus solution that is suitable for traditional automated microscopy tasks as well as for quantitative analysis of large biological specimens.
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108
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Anchang CG, Xu C, Raimondo MG, Atreya R, Maier A, Schett G, Zaburdaev V, Rauber S, Ramming A. The Potential of OMICs Technologies for the Treatment of Immune-Mediated Inflammatory Diseases. Int J Mol Sci 2021; 22:ijms22147506. [PMID: 34299122 PMCID: PMC8306614 DOI: 10.3390/ijms22147506] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2021] [Revised: 07/02/2021] [Accepted: 07/09/2021] [Indexed: 01/08/2023] Open
Abstract
Immune-mediated inflammatory diseases (IMIDs), such as inflammatory bowel diseases and inflammatory arthritis (e.g., rheumatoid arthritis, psoriatic arthritis), are marked by increasing worldwide incidence rates. Apart from irreversible damage of the affected tissue, the systemic nature of these diseases heightens the incidence of cardiovascular insults and colitis-associated neoplasia. Only 40–60% of patients respond to currently used standard-of-care immunotherapies. In addition to this limited long-term effectiveness, all current therapies have to be given on a lifelong basis as they are unable to specifically reprogram the inflammatory process and thus achieve a true cure of the disease. On the other hand, the development of various OMICs technologies is considered as “the great hope” for improving the treatment of IMIDs. This review sheds light on the progressive development and the numerous approaches from basic science that gradually lead to the transfer from “bench to bedside” and the implementation into general patient care procedures.
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Affiliation(s)
- Charles Gwellem Anchang
- Department of Internal Medicine 3—Rheumatology and Immunology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) and Universitätsklinikum, 91054 Erlangen, Germany; (C.G.A.); (C.X.); (M.G.R.); (G.S.); (S.R.)
| | - Cong Xu
- Department of Internal Medicine 3—Rheumatology and Immunology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) and Universitätsklinikum, 91054 Erlangen, Germany; (C.G.A.); (C.X.); (M.G.R.); (G.S.); (S.R.)
| | - Maria Gabriella Raimondo
- Department of Internal Medicine 3—Rheumatology and Immunology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) and Universitätsklinikum, 91054 Erlangen, Germany; (C.G.A.); (C.X.); (M.G.R.); (G.S.); (S.R.)
| | - Raja Atreya
- Department of Internal Medicine 1, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) and Universitätsklinikum, 91054 Erlangen, Germany;
| | - Andreas Maier
- Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91054 Erlangen, Germany;
| | - Georg Schett
- Department of Internal Medicine 3—Rheumatology and Immunology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) and Universitätsklinikum, 91054 Erlangen, Germany; (C.G.A.); (C.X.); (M.G.R.); (G.S.); (S.R.)
| | - Vasily Zaburdaev
- Max-Planck-Zentrum für Physik und Medizin, 91054 Erlangen, Germany;
- Department of Biology, Mathematics in Life Sciences, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91054 Erlangen, Germany
| | - Simon Rauber
- Department of Internal Medicine 3—Rheumatology and Immunology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) and Universitätsklinikum, 91054 Erlangen, Germany; (C.G.A.); (C.X.); (M.G.R.); (G.S.); (S.R.)
| | - Andreas Ramming
- Department of Internal Medicine 3—Rheumatology and Immunology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) and Universitätsklinikum, 91054 Erlangen, Germany; (C.G.A.); (C.X.); (M.G.R.); (G.S.); (S.R.)
- Correspondence: ; Tel.: +49-9131-8543048; Fax: +49-9131-8536448
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109
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Munck S, Swoger J, Coll-Lladó M, Gritti N, Vande Velde G. Maximizing content across scales: Moving multimodal microscopy and mesoscopy toward molecular imaging. Curr Opin Chem Biol 2021; 63:188-199. [PMID: 34198170 DOI: 10.1016/j.cbpa.2021.05.003] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Revised: 05/06/2021] [Accepted: 05/16/2021] [Indexed: 10/21/2022]
Abstract
Molecular imaging aims to depict the molecules in living patients. However, because this aim is still far beyond reach, patchworks of different solutions need to be used to tackle this overarching goal. From the vast toolbox of imaging techniques, we focus on those recent advances in optical microscopy that image molecules and cells at the submicron to centimeter scale. Mesoscopic imaging covers the "imaging gap" between techniques such as confocal microscopy and magnetic resonance imagingthat image entire live samples but with limited resolution. Microscopy focuses on the cellular level; mesoscopy visualizes the organization of molecules and cells into tissues and organs. The correlation between these techniques allows us to combine disciplines ranging from whole body imaging to basic research of model systems. We review current developments focused on improving microscopic and mesoscopic imaging technologies and on hardware and software that push the current sensitivity and resolution boundaries.
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Affiliation(s)
- Sebastian Munck
- VIB-KU Leuven Center for Brain & Disease Research, Light Microscopy Expertise Unit & VIB BioImaging Core, O&N4 Herestraat 49 box 602, Leuven, 3000, Belgium; KU Leuven Department of Neurosciences, Leuven Brain Institute, O&N4 Herestraat 49 box 602, Leuven, 3000, Belgium
| | - Jim Swoger
- European Molecular Biology Laboratory (EMBL) Barcelona, Barcelona, 08003, Spain
| | | | - Nicola Gritti
- European Molecular Biology Laboratory (EMBL) Barcelona, Barcelona, 08003, Spain
| | - Greetje Vande Velde
- Department of Imaging and Pathology, Faculty of Medicine, KU Leuven, Leuven, Belgium.
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110
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Susaki EA, Takasato M. Perspective: Extending the Utility of Three-Dimensional Organoids by Tissue Clearing Technologies. Front Cell Dev Biol 2021; 9:679226. [PMID: 34195197 PMCID: PMC8236633 DOI: 10.3389/fcell.2021.679226] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Accepted: 05/11/2021] [Indexed: 01/06/2023] Open
Abstract
An organoid, a self-organizing organ-like tissue developed from stem cells, can exhibit a miniaturized three-dimensional (3D) structure and part of the physiological functions of the original organ. Due to the reproducibility of tissue complexity and ease of handling, organoids have replaced real organs and animals for a variety of uses, such as investigations of the mechanisms of organogenesis and disease onset, and screening of drug effects and/or toxicity. The recent advent of tissue clearing and 3D imaging techniques have great potential contributions to organoid studies by allowing the collection and analysis of 3D images of whole organoids with a reasonable throughput and thus can expand the means of examining the 3D architecture, cellular components, and variability among organoids. Genetic and histological cell-labeling methods, together with organoid clearing, also allow visualization of critical structures and cellular components within organoids. The collected 3D data may enable image analysis to quantitatively assess structures within organoids and sensitively/effectively detect abnormalities caused by perturbations. These capabilities of tissue/organoid clearing and 3D imaging techniques not only extend the utility of organoids in basic biology but can also be applied for quality control of clinical organoid production and large-scale drug screening.
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Affiliation(s)
- Etsuo A. Susaki
- Department of Biochemistry and Systems Biomedicine, Graduate School of Medicine, Juntendo University, Tokyo, Japan
- Laboratory for Synthetic Biology, RIKEN Center for Biosystems Dynamics Research, Osaka, Japan
| | - Minoru Takasato
- Laboratory for Human Organogenesis, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan
- Laboratory of Molecular Cell Biology and Development, Department of Animal Development and Physiology, Graduate School of Biostudies, Kyoto University, Kyoto, Japan
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111
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Sands GB, Ashton JL, Trew ML, Baddeley D, Walton RD, Benoist D, Efimov IR, Smith NP, Bernus O, Smaill BH. It's clearly the heart! Optical transparency, cardiac tissue imaging, and computer modelling. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2021; 168:18-32. [PMID: 34126113 DOI: 10.1016/j.pbiomolbio.2021.06.005] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Revised: 05/10/2021] [Accepted: 06/07/2021] [Indexed: 12/19/2022]
Abstract
Recent developments in clearing and microscopy enable 3D imaging with cellular resolution up to the whole organ level. These methods have been used extensively in neurobiology, but their uptake in other fields has been much more limited. Application of this approach to the human heart and effective use of the data acquired present challenges of scale and complexity. Four interlinked issues need to be addressed: 1) efficient clearing and labelling of heart tissue, 2) fast microscopic imaging of human-scale samples, 3) handling and processing of multi-terabyte 3D images, and 4) extraction of structural information in computationally tractable structure-based models of cardiac function. Preliminary studies show that each of these requirements can be achieved with the appropriate application and development of existing technologies.
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Affiliation(s)
- Gregory B Sands
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand.
| | - Jesse L Ashton
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
| | - Mark L Trew
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
| | - David Baddeley
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand; Department of Cell Biology, Yale University, New Haven CT, 06520, USA
| | - Richard D Walton
- IHU Liryc, Fondation Bordeaux Université, Bordeaux, France; Univ. Bordeaux, Inserm, Centre de Recherche Cardio-Thoracique, U1045, 33000, Bordeaux, France
| | - David Benoist
- IHU Liryc, Fondation Bordeaux Université, Bordeaux, France; Univ. Bordeaux, Inserm, Centre de Recherche Cardio-Thoracique, U1045, 33000, Bordeaux, France
| | - Igor R Efimov
- IHU Liryc, Fondation Bordeaux Université, Bordeaux, France; Department of Biomedical Engineering, The George Washington University, Washington DC, 20052, USA
| | - Nicolas P Smith
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand; Queensland University of Technology, Brisbane 4000, Australia
| | - Olivier Bernus
- IHU Liryc, Fondation Bordeaux Université, Bordeaux, France; Univ. Bordeaux, Inserm, Centre de Recherche Cardio-Thoracique, U1045, 33000, Bordeaux, France
| | - Bruce H Smaill
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
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112
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Timonidis N, Tiesinga PHE. Progress towards a cellularly resolved mouse mesoconnectome is empowered by data fusion and new neuroanatomy techniques. Neurosci Biobehav Rev 2021; 128:569-591. [PMID: 34119523 DOI: 10.1016/j.neubiorev.2021.06.016] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 04/02/2021] [Accepted: 06/05/2021] [Indexed: 10/21/2022]
Abstract
Over the past decade there has been a rapid improvement in techniques for obtaining large-scale cellular level data related to the mouse brain connectome. However, a detailed mapping of cell-type-specific projection patterns is lacking, which would, for instance, allow us to study the role of circuit motifs in cognitive processes. In this work, we review advanced neuroanatomical and data fusion techniques within the context of a proposed Multimodal Connectomic Integration Framework for augmenting the cellularly resolved mouse mesoconnectome. First, we emphasize the importance of registering data modalities to a common reference atlas. We then review a number of novel experimental techniques that can provide data for characterizing cell-types in the mouse brain. Furthermore, we examine a number of data integration strategies, which involve fine-grained cell-type classification, spatial inference of cell densities, latent variable models for the mesoconnectome and multi-modal factorisation. Finally, we discuss a number of use cases which depend on connectome augmentation techniques, such as model simulations of functional connectivity and generating mechanistic hypotheses for animal disease models.
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Affiliation(s)
- Nestor Timonidis
- Neuroinformatics department, Donders Centre for Neuroscience, Radboud University Nijmegen, Heyendaalseweg 135, 6525 AJ Nijmegen, The Netherlands.
| | - Paul H E Tiesinga
- Neuroinformatics department, Donders Centre for Neuroscience, Radboud University Nijmegen, Heyendaalseweg 135, 6525 AJ Nijmegen, The Netherlands
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113
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Costantini I, Mazzamuto G, Roffilli M, Laurino A, Maria Castelli F, Neri M, Lughi G, Simonetto A, Lazzeri E, Pesce L, Destrieux C, Silvestri L, Conti V, Guerrini R, Saverio Pavone F. Large-scale, cell-resolution volumetric mapping allows layer-specific investigation of human brain cytoarchitecture. BIOMEDICAL OPTICS EXPRESS 2021; 12:3684-3699. [PMID: 34221688 PMCID: PMC8221968 DOI: 10.1364/boe.415555] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Revised: 03/23/2021] [Accepted: 03/30/2021] [Indexed: 06/01/2023]
Abstract
Although neuronal density analysis on human brain slices is available from stereological studies, data on the spatial distribution of neurons in 3D are still missing. Since the neuronal organization is very inhomogeneous in the cerebral cortex, it is critical to map all neurons in a given volume rather than relying on sparse sampling methods. To achieve this goal, we implement a new tissue transformation protocol to clear and label human brain tissues and we exploit the high-resolution optical sectioning of two-photon fluorescence microscopy to perform 3D mesoscopic reconstruction. We perform neuronal mapping of 100mm3 human brain samples and evaluate the volume and density distribution of neurons from various areas of the cortex originating from different subjects (young, adult, and elderly, both healthy and pathological). The quantitative evaluation of the density in combination with the mean volume of the thousands of neurons identified within the specimens, allow us to determine the layer-specific organization of the cerebral architecture.
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Affiliation(s)
- Irene Costantini
- European Laboratory for Non-Linear Spectroscopy (LENS), University of Florence, Sesto Fiorentino, Italy
- Department of Biology, University of Florence, Italy
- National Institute of Optics (INO), National Research Council (CNR), Sesto Fiorentino, Italy
- These authors contributed equally to this work
| | - Giacomo Mazzamuto
- European Laboratory for Non-Linear Spectroscopy (LENS), University of Florence, Sesto Fiorentino, Italy
- National Institute of Optics (INO), National Research Council (CNR), Sesto Fiorentino, Italy
- These authors contributed equally to this work
| | | | - Annunziatina Laurino
- European Laboratory for Non-Linear Spectroscopy (LENS), University of Florence, Sesto Fiorentino, Italy
- Present address: Department of Neurofarba, Section of Pharmacology and Toxicology, University of Florence, Italy
| | - Filippo Maria Castelli
- European Laboratory for Non-Linear Spectroscopy (LENS), University of Florence, Sesto Fiorentino, Italy
- Department of Physics, University of Florence, Italy
| | | | | | | | - Erica Lazzeri
- European Laboratory for Non-Linear Spectroscopy (LENS), University of Florence, Sesto Fiorentino, Italy
| | - Luca Pesce
- European Laboratory for Non-Linear Spectroscopy (LENS), University of Florence, Sesto Fiorentino, Italy
- Department of Physics, University of Florence, Italy
| | | | - Ludovico Silvestri
- European Laboratory for Non-Linear Spectroscopy (LENS), University of Florence, Sesto Fiorentino, Italy
- National Institute of Optics (INO), National Research Council (CNR), Sesto Fiorentino, Italy
- Department of Physics, University of Florence, Italy
| | - Valerio Conti
- Pediatric Neurology, Neurogenetics and Neurobiology Unit and Laboratories, A. Meyer Children’s Hospital, University of Florence, Florence, Italy
| | - Renzo Guerrini
- Pediatric Neurology, Neurogenetics and Neurobiology Unit and Laboratories, A. Meyer Children’s Hospital, University of Florence, Florence, Italy
| | - Francesco Saverio Pavone
- European Laboratory for Non-Linear Spectroscopy (LENS), University of Florence, Sesto Fiorentino, Italy
- National Institute of Optics (INO), National Research Council (CNR), Sesto Fiorentino, Italy
- Department of Physics, University of Florence, Italy
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114
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Borland D, McCormick CM, Patel NK, Krupa O, Mory JT, Beltran AA, Farah TM, Escobar-Tomlienovich CF, Olson SS, Kim M, Wu G, Stein JL. Segmentor: a tool for manual refinement of 3D microscopy annotations. BMC Bioinformatics 2021; 22:260. [PMID: 34022787 PMCID: PMC8141214 DOI: 10.1186/s12859-021-04202-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Accepted: 05/17/2021] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Recent advances in tissue clearing techniques, combined with high-speed image acquisition through light sheet microscopy, enable rapid three-dimensional (3D) imaging of biological specimens, such as whole mouse brains, in a matter of hours. Quantitative analysis of such 3D images can help us understand how changes in brain structure lead to differences in behavior or cognition, but distinguishing densely packed features of interest, such as nuclei, from background can be challenging. Recent deep learning-based nuclear segmentation algorithms show great promise for automated segmentation, but require large numbers of accurate manually labeled nuclei as training data. RESULTS We present Segmentor, an open-source tool for reliable, efficient, and user-friendly manual annotation and refinement of objects (e.g., nuclei) within 3D light sheet microscopy images. Segmentor employs a hybrid 2D-3D approach for visualizing and segmenting objects and contains features for automatic region splitting, designed specifically for streamlining the process of 3D segmentation of nuclei. We show that editing simultaneously in 2D and 3D using Segmentor significantly decreases time spent on manual annotations without affecting accuracy as compared to editing the same set of images with only 2D capabilities. CONCLUSIONS Segmentor is a tool for increased efficiency of manual annotation and refinement of 3D objects that can be used to train deep learning segmentation algorithms, and is available at https://www.nucleininja.org/ and https://github.com/RENCI/Segmentor .
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Affiliation(s)
- David Borland
- RENCI, University of North Carolina at Chapel Hill, 100 Europa Drive, Suite 540, Chapel Hill, NC, 27517, USA
| | - Carolyn M McCormick
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, 116 Manning Drive, CB# 7250, Chapel Hill, NC, 27599, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Niyanta K Patel
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, 116 Manning Drive, CB# 7250, Chapel Hill, NC, 27599, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Oleh Krupa
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, 116 Manning Drive, CB# 7250, Chapel Hill, NC, 27599, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Jessica T Mory
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, 116 Manning Drive, CB# 7250, Chapel Hill, NC, 27599, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Alvaro A Beltran
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, 116 Manning Drive, CB# 7250, Chapel Hill, NC, 27599, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Tala M Farah
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, 116 Manning Drive, CB# 7250, Chapel Hill, NC, 27599, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Carla F Escobar-Tomlienovich
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, 116 Manning Drive, CB# 7250, Chapel Hill, NC, 27599, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Sydney S Olson
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, 116 Manning Drive, CB# 7250, Chapel Hill, NC, 27599, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Minjeong Kim
- Department of Computer Science, University of North Carolina at Greensboro, Greensboro, NC, 27412, USA
| | - Guorong Wu
- Department of Psychiatry, University of North Carolina at Chapel Hill, 334 Emergency Room Drive, 343 Medical Wing C, Chapel Hill, NC, 27599, USA.
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
| | - Jason L Stein
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, 116 Manning Drive, CB# 7250, Chapel Hill, NC, 27599, USA.
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
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115
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Chen Y, Li X, Zhang D, Wang C, Feng R, Li X, Wen Y, Xu H, Zhang XS, Yang X, Chen Y, Feng Y, Zhou B, Chen BC, Lei K, Cai S, Jia JM, Gao L. A Versatile Tiling Light Sheet Microscope for Imaging of Cleared Tissues. Cell Rep 2021; 33:108349. [PMID: 33147464 DOI: 10.1016/j.celrep.2020.108349] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Revised: 08/13/2020] [Accepted: 10/13/2020] [Indexed: 01/14/2023] Open
Abstract
We present a tiling light sheet microscope compatible with all tissue clearing methods for rapid multicolor 3D imaging of cleared tissues with micron-scale (4 × 4 × 10 μm3) to submicron-scale (0.3 × 0.3 × 1 μm3) spatial resolution. The resolving ability is improved to sub-100 nm (70 × 70 × 200 nm3) via tissue expansion. The microscope uses tiling light sheets to achieve higher spatial resolution and better optical sectioning ability than conventional light sheet microscopes. The illumination light is phase modulated to adjust the position and intensity profile of the light sheet based on the desired spatial resolution and imaging speed and to keep the microscope aligned. The ability of the microscope to align via phase modulation alone also ensures its accuracy for multicolor 3D imaging and makes the microscope reliable and easy to operate. Here we describe the working principle and design of the microscope. We demonstrate its utility by imaging various cleared tissues.
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Affiliation(s)
- Yanlu Chen
- Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China; Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China
| | - Xiaoliang Li
- Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China
| | - Dongdong Zhang
- Key Laboratory of Growth Regulation and Translation Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Biology, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China; Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China
| | - Chunhui Wang
- Key Laboratory of Growth Regulation and Translation Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Biology, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China; Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China
| | - Ruili Feng
- Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China; Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China
| | - Xuzhao Li
- Key Laboratory of Growth Regulation and Translation Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Biology, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China; Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China
| | - Yao Wen
- Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China
| | - Hao Xu
- Key Laboratory of Growth Regulation and Translation Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Biology, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China; Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China
| | - Xinyi Shirley Zhang
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai 200031, China
| | - Xiao Yang
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences, Beijing Institute of Lifeomics, Beijing 102206, China
| | - Yongyi Chen
- Department of Clinical laboratory, Zhejiang Cancer Hospital, Hangzhou, Zhejiang 310000, China
| | - Yi Feng
- Department of Integrative Medicine and Neurobiology, School of Basic Medical Sciences, Fudan University, Shanghai 200032, China
| | - Bo Zhou
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai 200031, China
| | - Bi-Chang Chen
- Research Center for Applied Sciences, Academia Sinica, Taipei 11529, Taiwan
| | - Kai Lei
- Key Laboratory of Growth Regulation and Translation Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Biology, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China; Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China
| | - Shang Cai
- Key Laboratory of Growth Regulation and Translation Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Biology, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China; Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China.
| | - Jie-Min Jia
- Key Laboratory of Growth Regulation and Translation Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Biology, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China; Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China.
| | - Liang Gao
- Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China; Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China.
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116
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Taranda J, Turcan S. 3D Whole-Brain Imaging Approaches to Study Brain Tumors. Cancers (Basel) 2021; 13:cancers13081897. [PMID: 33920839 PMCID: PMC8071100 DOI: 10.3390/cancers13081897] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Revised: 04/05/2021] [Accepted: 04/09/2021] [Indexed: 02/06/2023] Open
Abstract
Simple Summary Brain tumors integrate into the brain and consist of tumor cells with different molecular alterations. During brain tumor pathogenesis, a variety of cell types surround the tumors to either inhibit or promote tumor growth. These cells are collectively referred to as the tumor microenvironment. Three-dimensional and/or longitudinal visualization approaches are needed to understand the growth of these tumors in time and space. In this review, we present three imaging modalities that are suitable or that can be adapted to study the volumetric distribution of malignant or tumor-associated cells in the brain. In addition, we highlight the potential clinical utility of some of the microscopy approaches for brain tumors using exemplars from solid tumors. Abstract Although our understanding of the two-dimensional state of brain tumors has greatly expanded, relatively little is known about their spatial structures. The interactions between tumor cells and the tumor microenvironment (TME) occur in a three-dimensional (3D) space. This volumetric distribution is important for elucidating tumor biology and predicting and monitoring response to therapy. While static 2D imaging modalities have been critical to our understanding of these tumors, studies using 3D imaging modalities are needed to understand how malignant cells co-opt the host brain. Here we summarize the preclinical utility of in vivo imaging using two-photon microscopy in brain tumors and present ex vivo approaches (light-sheet fluorescence microscopy and serial two-photon tomography) and highlight their current and potential utility in neuro-oncology using data from solid tumors or pathological brain as examples.
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117
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Costantini I, Baria E, Sorelli M, Matuschke F, Giardini F, Menzel M, Mazzamuto G, Silvestri L, Cicchi R, Amunts K, Axer M, Pavone FS. Autofluorescence enhancement for label-free imaging of myelinated fibers in mammalian brains. Sci Rep 2021; 11:8038. [PMID: 33850168 PMCID: PMC8044204 DOI: 10.1038/s41598-021-86092-7] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Accepted: 03/09/2021] [Indexed: 12/12/2022] Open
Abstract
Analyzing the structure of neuronal fibers with single axon resolution in large volumes is a challenge in connectomics. Different technologies try to address this goal; however, they are limited either by the ineffective labeling of the fibers or in the achievable resolution. The possibility of discriminating between different adjacent myelinated axons gives the opportunity of providing more information about the fiber composition and architecture within a specific area. Here, we propose MAGIC (Myelin Autofluorescence imaging by Glycerol Induced Contrast enhancement), a tissue preparation method to perform label-free fluorescence imaging of myelinated fibers that is user friendly and easy to handle. We exploit the high axial and radial resolution of two-photon fluorescence microscopy (TPFM) optical sectioning to decipher the mixture of various fiber orientations within the sample of interest. We demonstrate its broad applicability by performing mesoscopic reconstruction at a sub-micron resolution of mouse, rat, monkey, and human brain samples and by quantifying the different fiber organization in control and Reeler mouse's hippocampal sections. Our study provides a novel method for 3D label-free imaging of nerve fibers in fixed samples at high resolution, below micrometer level, that overcomes the limitation related to the myelinated axons exogenous labeling, improving the possibility of analyzing brain connectivity.
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Affiliation(s)
- Irene Costantini
- European Laboratory for Non-Linear Spectroscopy, University of Florence, Florence, Italy.
- Department of Biology, University of Florence, Florence, Italy.
- National Institute of Optics, National Research Council, Rome, Italy.
| | - Enrico Baria
- European Laboratory for Non-Linear Spectroscopy, University of Florence, Florence, Italy
- Department of Physics, University of Florence, Florence, Italy
| | - Michele Sorelli
- European Laboratory for Non-Linear Spectroscopy, University of Florence, Florence, Italy
- Department of Physics, University of Florence, Florence, Italy
| | - Felix Matuschke
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
| | - Francesco Giardini
- European Laboratory for Non-Linear Spectroscopy, University of Florence, Florence, Italy
| | - Miriam Menzel
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
| | - Giacomo Mazzamuto
- European Laboratory for Non-Linear Spectroscopy, University of Florence, Florence, Italy
- National Institute of Optics, National Research Council, Rome, Italy
| | - Ludovico Silvestri
- European Laboratory for Non-Linear Spectroscopy, University of Florence, Florence, Italy
- Department of Physics, University of Florence, Florence, Italy
| | - Riccardo Cicchi
- European Laboratory for Non-Linear Spectroscopy, University of Florence, Florence, Italy
- National Institute of Optics, National Research Council, Rome, Italy
| | - Katrin Amunts
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
- C. and O. Vogt Institute for Brain Research, University Hospital Düsseldorf, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
| | - Markus Axer
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
| | - Francesco Saverio Pavone
- European Laboratory for Non-Linear Spectroscopy, University of Florence, Florence, Italy
- National Institute of Optics, National Research Council, Rome, Italy
- Department of Physics, University of Florence, Florence, Italy
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118
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Zhan Y, Wu H, Liu L, Lin J, Zhang S. Organic solvent-based tissue clearing techniques and their applications. JOURNAL OF BIOPHOTONICS 2021; 14:e202000413. [PMID: 33715302 DOI: 10.1002/jbio.202000413] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 10/11/2020] [Revised: 03/05/2021] [Accepted: 03/05/2021] [Indexed: 02/05/2023]
Abstract
Revealing the true structure of tissues and organs with tissue slicing technology is difficult since images reconstructed in three dimensions are easily distorted. To address the limitations in tissue slicing technology, tissue clearing has been invented and has recently achieved significant progress in three-dimensional imaging. Currently, this technology can mainly be divided into two types: aqueous clearing methods and solvent-based clearing methods. As one of the important parts of this technology, organic solvent-based tissue clearing techniques have been widely applied because of their efficient clearing speed and high clearing intensity. This review introduces the primary organic solvent-based tissue clearing techniques and their applications.
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Affiliation(s)
- Yanjing Zhan
- State Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China
| | - Haoyan Wu
- State Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China
| | - Linfeng Liu
- State Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China
| | - Jie Lin
- Department of Oral Implantology, West China Hospital of Stomatology, Sichuan University, Chengdu, China
| | - Shiwen Zhang
- State Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China.,Department of Oral Implantology, West China Hospital of Stomatology, Sichuan University, Chengdu, China
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119
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Abstract
Advanced optical methods combined with various probes pave the way toward molecular imaging within living cells. However, major challenges are associated with the need to enhance the imaging resolution even further to the subcellular level for the imaging of larger tissues, as well as for in vivo studies. High scattering and absorption of opaque tissues limit the penetration of light into deep tissues and thus the optical imaging depth. Tissue optical clearing technique provides an innovative way to perform deep-tissue imaging. Recently, various optical clearing methods have been developed, which provide tissue clearing based on similar physical principles via different chemical approaches. Here, we introduce the mechanisms of the current clearing methods from fundamental physical and chemical perspectives, including the main physical principle, refractive index matching via various chemical approaches, such as dissociation of collagen, delipidation, decalcification, dehydration, and hyperhydration, to reduce scattering, as well as decolorization to reduce absorption.
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Affiliation(s)
- Tingting Yu
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Jingtan Zhu
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Dongyu Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Dan Zhu
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
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120
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Kobler O, Weiglein A, Hartung K, Chen YC, Gerber B, Thomas U. A quick and versatile protocol for the 3D visualization of transgene expression across the whole body of larval Drosophila. J Neurogenet 2021; 35:306-319. [PMID: 33688796 DOI: 10.1080/01677063.2021.1892096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
Larval Drosophila are used as a genetically accessible study case in many areas of biological research. Here we report a fast, robust and user-friendly procedure for the whole-body multi-fluorescence imaging of Drosophila larvae; the protocol has been optimized specifically for larvae by systematically tackling the pitfalls associated with clearing this small but cuticularized organism. Tests on various fluorescent proteins reveal that the recently introduced monomeric infrared fluorescent protein (mIFP) is particularly suitable for our approach. This approach comprises an effective, low-cost clearing protocol with minimal handling time and reduced toxicity in the reagents employed. It combines a success rate high enough to allow for small-scale screening approaches and a resolution sufficient for cellular-level analyses with light sheet and confocal microscopy. Given that publications and database documentations typically specify expression patterns of transgenic driver lines only within a given organ system of interest, the present procedure should be versatile enough to extend such documentation systematically to the whole body. As examples, the expression patterns of transgenic driver lines covering the majority of neurons, or subsets of chemosensory, central brain or motor neurons, are documented in the context of whole larval body volumes (using nsyb-Gal4, IR76b-Gal4, APL-Gal4 and mushroom body Kenyon cells, or OK371-Gal4, respectively). Notably, the presented protocol allows for triple-color fluorescence imaging with near-infrared, red and yellow fluorescent proteins.
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Affiliation(s)
- Oliver Kobler
- Leibniz Institute for Neurobiology, Combinatorial NeuroImaging Core Facility (CNI), Magdeburg, Germany
| | - Aliće Weiglein
- Department of Genetics of Learning and Memory, Leibniz Institute for Neurobiology, Magdeburg, Germany
| | - Kathrin Hartung
- Department of Neurochemistry and Molecular Biology, Leibniz Institute for Neurobiology, Magdeburg, Germany
| | - Yi-Chun Chen
- Department of Genetics of Learning and Memory, Leibniz Institute for Neurobiology, Magdeburg, Germany
| | - Bertram Gerber
- Department of Genetics of Learning and Memory, Leibniz Institute for Neurobiology, Magdeburg, Germany.,Institute of Biology, Otto von Guericke University, Magdeburg, Germany.,Center for Behavioral Brain Sciences, Otto von Guericke University, Magdeburg, Germany
| | - Ulrich Thomas
- Department of Neurochemistry and Molecular Biology, Leibniz Institute for Neurobiology, Magdeburg, Germany.,Department of Cellular Neuroscience, Leibniz Institute for Neurobiology, Magdeburg, Germany
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Preusser F, dos Santos N, Contzen J, Stachelscheid H, Costa ÉT, Mergenthaler P, Preibisch S. FRC-QE: a robust and comparable 3D microscopy image quality metric for cleared organoids. Bioinformatics 2021; 37:3088-3090. [PMID: 33693580 PMCID: PMC8479654 DOI: 10.1093/bioinformatics/btab160] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Revised: 02/04/2021] [Accepted: 03/04/2021] [Indexed: 02/02/2023] Open
Abstract
SUMMARY Here, we propose Fourier ring correlation-based quality estimation (FRC-QE) as a new metric for automated image quality estimation in 3D fluorescence microscopy acquisitions of cleared organoids that yields comparable measurements across experimental replicates, clearing protocols and works for different microscopy modalities. AVAILABILITY AND IMPLEMENTATION FRC-QE is written in ImgLib2/Java and provided as an easy-to-use and macro-scriptable plugin for Fiji. Code, documentation, sample images and further information can be found under https://github.com/PreibischLab/FRC-QE. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Friedrich Preusser
- Berlin Institute for Medical Systems Biology (BIMSB), Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin 10115, Germany
| | - Natália dos Santos
- Molecular Oncology Center, Hospital Sirio-Libanese, São Paulo, SP 01308-050, Brazil
| | - Jörg Contzen
- Department of Experimental Neurology, Center for Stroke Research Berlin, Charité – Universitätsmedizin Berlin, Berlin 10117, Germany
| | - Harald Stachelscheid
- Stem Cell Core Facility, Berlin Institute of Health at Charité – Universitätsmedizin Berlin, Berlin 13353, Germany
| | - Érico Tosoni Costa
- Molecular Oncology Center, Hospital Sirio-Libanese, São Paulo, SP 01308-050, Brazil
| | - Philipp Mergenthaler
- Department of Experimental Neurology, Center for Stroke Research Berlin, Charité – Universitätsmedizin Berlin, Berlin 10117, Germany,Department of Neurology, Charité – Universitätsmedizin Berlin, Berlin 10117, Germany,BIH Academy, Berlin Institute of Health at Charité –Universitätsmedizin Berlin, Berlin 10117, Germany,To whom correspondence should be addressed. or
| | - Stephan Preibisch
- Berlin Institute for Medical Systems Biology (BIMSB), Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin 10115, Germany,Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA,To whom correspondence should be addressed. or
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122
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Kubota SI, Takahashi K, Mano T, Matsumoto K, Katsumata T, Shi S, Tainaka K, Ueda HR, Ehata S, Miyazono K. Whole-organ analysis of TGF-β-mediated remodelling of the tumour microenvironment by tissue clearing. Commun Biol 2021; 4:294. [PMID: 33674758 PMCID: PMC7935961 DOI: 10.1038/s42003-021-01786-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Accepted: 02/02/2021] [Indexed: 01/06/2023] Open
Abstract
Tissue clearing is one of the most powerful strategies for a comprehensive analysis of disease progression. Here, we established an integrated pipeline that combines tissue clearing, 3D imaging, and machine learning and applied to a mouse tumour model of experimental lung metastasis using human lung adenocarcinoma A549 cells. This pipeline provided the spatial information of the tumour microenvironment. We further explored the role of transforming growth factor-β (TGF-β) in cancer metastasis. TGF-β-stimulated cancer cells enhanced metastatic colonization of unstimulated-cancer cells in vivo when both cells were mixed. RNA-sequencing analysis showed that expression of the genes related to coagulation and inflammation were up-regulated in TGF-β-stimulated cancer cells. Further, whole-organ analysis revealed accumulation of platelets or macrophages with TGF-β-stimulated cancer cells, suggesting that TGF-β might promote remodelling of the tumour microenvironment, enhancing the colonization of cancer cells. Hence, our integrated pipeline for 3D profiling will help the understanding of the tumour microenvironment.
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Affiliation(s)
- Shimpei I Kubota
- Department of Molecular Pathology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Kei Takahashi
- Department of Molecular Pathology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Tomoyuki Mano
- Department of Systems Pharmacology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Katsuhiko Matsumoto
- Laboratory for Synthetic Biology, RIKEN Quantitative Biology Center, Osaka, Japan
| | - Takahiro Katsumata
- Department of Systems Pharmacology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Shoi Shi
- Department of Systems Pharmacology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Kazuki Tainaka
- Brain Research Institute, Niigata University, Niigata, Japan
| | - Hiroki R Ueda
- Department of Systems Pharmacology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- Laboratory for Synthetic Biology, RIKEN Quantitative Biology Center, Osaka, Japan
| | - Shogo Ehata
- Department of Molecular Pathology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
- Environmental Science Center, The University of Tokyo, Tokyo, Japan.
| | - Kohei Miyazono
- Department of Molecular Pathology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
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123
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Wang X, Xiong H, Liu Y, Yang T, Li A, Huang F, Yin F, Su L, Liu L, Li N, Li L, Cheng S, Liu X, Lv X, Liu X, Chu J, Xu T, Xu F, Gong H, Luo Q, Yuan J, Zeng S. Chemical sectioning fluorescence tomography: high-throughput, high-contrast, multicolor, whole-brain imaging at subcellular resolution. Cell Rep 2021; 34:108709. [PMID: 33535048 DOI: 10.1016/j.celrep.2021.108709] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Revised: 10/18/2020] [Accepted: 01/08/2021] [Indexed: 01/23/2023] Open
Abstract
A thorough neuroanatomical study of the brain architecture is crucial for understanding its cellular compositions, connections, and working mechanisms. However, the fine- and multiscale features of neuron structures make it challenging for microscopic imaging, as it requires high contrast and high throughput simultaneously. Here, we propose chemical sectioning fluorescence tomography (CSFT) to solve this problem. By chemically switching OFF/ON the fluorescent state of the labeled proteins (FPs), we light only the top layer as thin as submicron for imaging without background interference. Combined with the wide-field fluorescence micro-optical sectioning tomography (fMOST) system, we have shown multicolor CSFT imaging. We also demonstrate mouse whole-brain imaging at the subcellular resolution, as well as the power for quantitative acquisition of synaptic-connection-related pyramidal dendritic spines and axon boutons on the brain-wide scale at the complete single-neuron level. We believe that the CSFT method would greatly facilitate our understanding of the brain-wide neuron networks.
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Affiliation(s)
- Xiaojun Wang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China; MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Hanqing Xiong
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China; MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Yurong Liu
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China; MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Tao Yang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China; MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Anan Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China; MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Fei Huang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China; MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Fangfang Yin
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China; MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Lei Su
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China; MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Ling Liu
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China; MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Ning Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China; MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Longhui Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China; MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Shenghua Cheng
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China; MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Xiaoxiang Liu
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China; MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Xiaohua Lv
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China; MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Xiuli Liu
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China; MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Jun Chu
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Tonghui Xu
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China; MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Fuqiang Xu
- State Key Laboratory of Magnetic Resonance and Atomic Molecular Physics, Key Laboratory of Magnetic Resonance in Biological Systems, Wuhan Institute of Physics and Mathematics, CAS Centre for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Wuhan 430071, China
| | - Hui Gong
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China; MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Qingming Luo
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China; MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Jing Yuan
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China; MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China.
| | - Shaoqun Zeng
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China; MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China.
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124
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Hofmann J, Gadjalova I, Mishra R, Ruland J, Keppler SJ. Efficient Tissue Clearing and Multi-Organ Volumetric Imaging Enable Quantitative Visualization of Sparse Immune Cell Populations During Inflammation. Front Immunol 2021; 11:599495. [PMID: 33569052 PMCID: PMC7869862 DOI: 10.3389/fimmu.2020.599495] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Accepted: 12/04/2020] [Indexed: 12/19/2022] Open
Abstract
Spatial information of cells in their tissue microenvironment is necessary to understand the complexity of pathophysiological processes. Volumetric imaging of cleared organs provides this information; however, current protocols are often elaborate, expensive, and organ specific. We developed a simplified, cost-effective, non-hazardous approach for efficient tissue clearing and multi-organ volumetric imaging (EMOVI). EMOVI enabled multiplexed antibody-based immunolabeling, provided adequate tissue transparency, maintained cellular morphology and preserved fluorochromes. Exemplarily, EMOVI allowed the detection and quantification of scarce cell populations during pneumonitis. EMOVI also permitted histo-cytometric analysis of MHC-II expressing cells, revealing distinct populations surrounding or infiltrating glomeruli of nephritic kidneys. Using EMOVI, we found widefield microscopy with real-time computational clearing as a valuable option for rapid image acquisition and detection of rare cellular events in cleared organs. EMOVI has the potential to make tissue clearing and volumetric imaging of immune cells applicable for a broad audience by facilitating flexibility in organ, fluorochrome and microscopy usage.
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Affiliation(s)
- Julian Hofmann
- Institute for Clinical Chemistry and Pathobiochemistry, München rechts der Isar (MRI), Technical University Munich, Munich, Germany.,TranslaTUM, Center for Translational Cancer Research, Technische Universität München, München, Germany
| | - Iana Gadjalova
- Institute for Clinical Chemistry and Pathobiochemistry, München rechts der Isar (MRI), Technical University Munich, Munich, Germany.,TranslaTUM, Center for Translational Cancer Research, Technische Universität München, München, Germany
| | - Ritu Mishra
- Institute for Clinical Chemistry and Pathobiochemistry, München rechts der Isar (MRI), Technical University Munich, Munich, Germany.,TranslaTUM, Center for Translational Cancer Research, Technische Universität München, München, Germany
| | - Jürgen Ruland
- Institute for Clinical Chemistry and Pathobiochemistry, München rechts der Isar (MRI), Technical University Munich, Munich, Germany.,TranslaTUM, Center for Translational Cancer Research, Technische Universität München, München, Germany
| | - Selina J Keppler
- Institute for Clinical Chemistry and Pathobiochemistry, München rechts der Isar (MRI), Technical University Munich, Munich, Germany.,TranslaTUM, Center for Translational Cancer Research, Technische Universität München, München, Germany
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125
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Zhao J, Lai HM, Qi Y, He D, Sun H. Current Status of Tissue Clearing and the Path Forward in Neuroscience. ACS Chem Neurosci 2021; 12:5-29. [PMID: 33326739 DOI: 10.1021/acschemneuro.0c00563] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Due to the complexity and limited availability of human brain tissues, for decades, pathologists have sought to maximize information gained from individual samples, based on which (patho)physiological processes could be inferred. Recently, new understandings of chemical and physical properties of biological tissues and multiple chemical profiling have given rise to the development of scalable tissue clearing methods allowing superior optical clearing of across-the-scale samples. In the past decade, tissue clearing techniques, molecular labeling methods, advanced laser scanning microscopes, and data visualization and analysis have become commonplace. Combined, they have made 3D visualization of brain tissues with unprecedented resolution and depth widely accessible. To facilitate further advancements and applications, here we provide a critical appraisal of these techniques. We propose a classification system of current tissue clearing and expansion methods that allows users to judge the applicability of individual ones to their questions, followed by a review of the current progress in molecular labeling, optical imaging, and data processing to demonstrate the whole 3D imaging pipeline based on tissue clearing and downstream techniques for visualizing the brain. We also raise the path forward of tissue-clearing-based imaging technology, that is, integrating with state-of-the-art techniques, such as multiplexing protein imaging, in situ signal amplification, RNA detection and sequencing, super-resolution imaging techniques, multiomics studies, and deep learning, for drawing the complete atlas of the human brain and building a 3D pathology platform for central nervous system disorders.
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Affiliation(s)
- Jiajia Zhao
- Department of Neurosurgery, The National Key Clinical Specialty, The Engineering Technology Research Center of Education Ministry of China, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Zhujiang Hospital, Southern Medical University, Guangzhou 510515, China
- The Second Clinical Medical College, Southern Medical University, Guangzhou 510515, China
| | - Hei Ming Lai
- Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, NT, Hong Kong SAR, China
| | - Yuwei Qi
- Department of Neurosurgery, The National Key Clinical Specialty, The Engineering Technology Research Center of Education Ministry of China, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Zhujiang Hospital, Southern Medical University, Guangzhou 510515, China
- The Second Clinical Medical College, Southern Medical University, Guangzhou 510515, China
| | - Dian He
- Department of Neurosurgery, The National Key Clinical Specialty, The Engineering Technology Research Center of Education Ministry of China, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Zhujiang Hospital, Southern Medical University, Guangzhou 510515, China
- The Second Clinical Medical College, Southern Medical University, Guangzhou 510515, China
| | - Haitao Sun
- Department of Neurosurgery, The National Key Clinical Specialty, The Engineering Technology Research Center of Education Ministry of China, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Zhujiang Hospital, Southern Medical University, Guangzhou 510515, China
- The Second Clinical Medical College, Southern Medical University, Guangzhou 510515, China
- Microbiome Medicine Center, Department of Laboratory Medicine, Clinical Biobank Center, Zhujiang Hospital, Southern Medical University, Guangzhou 510282, China
- Key Laboratory of Mental Health of the Ministry of Education, Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Southern Medical University, Guangzhou 510515, China
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126
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Zhou C, Zheng T, Luo T, Yan C, Sun Q, Ren M, Zhao P, Chen W, Ji B, Wang Z, Li A, Gong H, Li X. Continuous imaging of large-volume tissues with a machinable optical clearing method at subcellular resolution. BIOMEDICAL OPTICS EXPRESS 2020; 11:7132-7149. [PMID: 33408985 PMCID: PMC7747903 DOI: 10.1364/boe.405801] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Revised: 10/14/2020] [Accepted: 10/15/2020] [Indexed: 05/25/2023]
Abstract
Optical clearing methods are widely used for three-dimensional biological information acquisition in the whole organ. However, the imaging quality of cleared tissues is often limited by ununiformed tissue clearing. By combining tissue clearing with mechanical sectioning based whole organ imaging system, we can reduce the influence of light scattering and absorption on the tissue to get isotropic and high resolution in both superficial and deep layers. However, it remains challenging for optical cleared biological tissue to maintain good sectioning property. Here, we developed a clearing method named M-CUBIC (machinable CUBIC), which combined a modified CUBIC method with PNAGA (poly-N-acryloyl glycinamide) hydrogel embedding to transparentize tissue while improving its sectioning property. With high-throughput light-sheet tomography platform (HLTP) and fluorescent micro-optical sectioning tomography (fMOST), we acquired continuous datasets with subcellular resolution from intact mouse brains for single neuron tracing, as well as the fine vascular structure of kidneys. This method can be used to acquire microstructures of multiple types of biological organs with subcellular resolutions, which can facilitate biological research.
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Affiliation(s)
- Can Zhou
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan 430074, China
- These authors contributed equally
| | - Ting Zheng
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan 430074, China
- These authors contributed equally
| | - Ting Luo
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Cheng Yan
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Qingtao Sun
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan 430074, China
- HUST-Suzhou Institute for Brainsmatics, JITRI Institute for Brainsmatics, Suzhou 215123, China
| | - Miao Ren
- School of Biomedical Engineering, Hainan University, Haikou 570228, China
| | - Peilin Zhao
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Wu Chen
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Bingqing Ji
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Zhi Wang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Anan Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan 430074, China
- HUST-Suzhou Institute for Brainsmatics, JITRI Institute for Brainsmatics, Suzhou 215123, China
- CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Science, Shanghai 200031, China
| | - Hui Gong
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan 430074, China
- HUST-Suzhou Institute for Brainsmatics, JITRI Institute for Brainsmatics, Suzhou 215123, China
- CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Science, Shanghai 200031, China
| | - Xiangning Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan 430074, China
- HUST-Suzhou Institute for Brainsmatics, JITRI Institute for Brainsmatics, Suzhou 215123, China
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127
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Hoersting AK, Schmucker D. Axonal branch patterning and neuronal shape diversity: roles in developmental circuit assembly: Axonal branch patterning and neuronal shape diversity in developmental circuit assembly. Curr Opin Neurobiol 2020; 66:158-165. [PMID: 33232861 DOI: 10.1016/j.conb.2020.10.019] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Revised: 10/21/2020] [Accepted: 10/26/2020] [Indexed: 02/06/2023]
Abstract
Recent progress in human genetics and single cell sequencing rapidly expands the list of molecular factors that offer important new contributions to our understanding of brain wiring. Yet many new molecular factors are being discovered that have never been studied in the context of neuronal circuit development. This is clearly asking for increased efforts to better understand the developmental mechanisms of circuit assembly [1]. Moreover, recent studies characterizing the developmental causes of some psychiatric diseases show impressive progress in reaching cellular resolution in their analysis. They provide concrete support emphasizing the importance of axonal branching and synapse formation as a hotspot for potential defects. Inspired by these new studies we will discuss progress but also challenges in understanding how neurite branching and neuronal shape diversity itself impacts on specificity of neuronal circuit assembly. We discuss the idea that neuronal shape acquisition itself is a key specificity factor in neuronal circuit assembly.
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Affiliation(s)
| | - Dietmar Schmucker
- Life and Medical Sciences Institute (LIMES), University Bonn, Bonn, Germany; Center for Brain and Disease Research, VIB Leuven, University Leuven, Belgium.
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128
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Franceschini A, Costantini I, Pavone FS, Silvestri L. Dissecting Neuronal Activation on a Brain-Wide Scale With Immediate Early Genes. Front Neurosci 2020; 14:569517. [PMID: 33192255 PMCID: PMC7645181 DOI: 10.3389/fnins.2020.569517] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Accepted: 09/28/2020] [Indexed: 11/13/2022] Open
Abstract
Visualizing neuronal activation on a brain-wide scale yet with cellular resolution is a fundamental technical challenge for neuroscience. This would enable analyzing how different neuronal circuits are disrupted in pathology and how they could be rescued by pharmacological treatments. Although this goal would have appeared visionary a decade ago, recent technological advances make it eventually feasible. Here, we review the latest developments in the fields of genetics, sample preparation, imaging, and image analysis that could be combined to afford whole-brain cell-resolution activation mapping. We show how the different biochemical and optical methods have been coupled to study neuronal circuits at different spatial and temporal scales, and with cell-type specificity. The inventory of techniques presented here could be useful to find the tools best suited for a specific experiment. We envision that in the next years, mapping of neuronal activation could become routine in many laboratories, allowing dissecting the neuronal counterpart of behavior.
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Affiliation(s)
| | - Irene Costantini
- European Laboratory for Non-linear Spectroscopy (LENS), Sesto Fiorentino, Italy.,National Institute of Optics, National Research Council (INO-CNR), Sesto Fiorentino, Italy
| | - Francesco S Pavone
- European Laboratory for Non-linear Spectroscopy (LENS), Sesto Fiorentino, Italy.,National Institute of Optics, National Research Council (INO-CNR), Sesto Fiorentino, Italy.,Department of Physics and Astronomy, University of Florence, Florence, Italy
| | - Ludovico Silvestri
- European Laboratory for Non-linear Spectroscopy (LENS), Sesto Fiorentino, Italy.,National Institute of Optics, National Research Council (INO-CNR), Sesto Fiorentino, Italy.,Department of Physics and Astronomy, University of Florence, Florence, Italy
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129
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Gómez-Gaviro MV, Sanderson D, Ripoll J, Desco M. Biomedical Applications of Tissue Clearing and Three-Dimensional Imaging in Health and Disease. iScience 2020; 23:101432. [PMID: 32805648 PMCID: PMC7452225 DOI: 10.1016/j.isci.2020.101432] [Citation(s) in RCA: 54] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Revised: 07/29/2020] [Accepted: 07/30/2020] [Indexed: 12/27/2022] Open
Abstract
Three-dimensional (3D) optical imaging techniques can expand our knowledge about physiological and pathological processes that cannot be fully understood with 2D approaches. Standard diagnostic tests frequently are not sufficient to unequivocally determine the presence of a pathological condition. Whole-organ optical imaging requires tissue transparency, which can be achieved by using tissue clearing procedures enabling deeper image acquisition and therefore making possible the analysis of large-scale biological tissue samples. Here, we review currently available clearing agents, methods, and their application in imaging of physiological or pathological conditions in different animal and human organs. We also compare different optical tissue clearing methods discussing their advantages and disadvantages and review the use of different 3D imaging techniques for the visualization and image acquisition of cleared tissues. The use of optical tissue clearing resources for large-scale biological tissues 3D imaging paves the way for future applications in translational and clinical research.
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Affiliation(s)
- Maria Victoria Gómez-Gaviro
- Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Departamento de Bioingeniería e Ingeniería Aeroespacial, Universidad Carlos III de Madrid, Madrid, Spain.
| | - Daniel Sanderson
- Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain; Departamento de Bioingeniería e Ingeniería Aeroespacial, Universidad Carlos III de Madrid, Madrid, Spain
| | - Jorge Ripoll
- Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain; Departamento de Bioingeniería e Ingeniería Aeroespacial, Universidad Carlos III de Madrid, Madrid, Spain
| | - Manuel Desco
- Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Departamento de Bioingeniería e Ingeniería Aeroespacial, Universidad Carlos III de Madrid, Madrid, Spain; Centro Nacional de Investigaciones Cardiovasculares Carlos III, Madrid, Spain
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