1
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Szelenyi ER, Navarrete JS, Murry AD, Zhang Y, Girven KS, Kuo L, Cline MM, Bernstein MX, Burdyniuk M, Bowler B, Goodwin NL, Juarez B, Zweifel LS, Golden SA. An arginine-rich nuclear localization signal (ArgiNLS) strategy for streamlined image segmentation of single cells. Proc Natl Acad Sci U S A 2024; 121:e2320250121. [PMID: 39074275 PMCID: PMC11317604 DOI: 10.1073/pnas.2320250121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Accepted: 06/25/2024] [Indexed: 07/31/2024] Open
Abstract
High-throughput volumetric fluorescent microscopy pipelines can spatially integrate whole-brain structure and function at the foundational level of single cells. However, conventional fluorescent protein (FP) modifications used to discriminate single cells possess limited efficacy or are detrimental to cellular health. Here, we introduce a synthetic and nondeleterious nuclear localization signal (NLS) tag strategy, called "Arginine-rich NLS" (ArgiNLS), that optimizes genetic labeling and downstream image segmentation of single cells by restricting FP localization near-exclusively in the nucleus through a poly-arginine mechanism. A single N-terminal ArgiNLS tag provides modular nuclear restriction consistently across spectrally separate FP variants. ArgiNLS performance in vivo displays functional conservation across major cortical cell classes and in response to both local and systemic brain-wide AAV administration. Crucially, the high signal-to-noise ratio afforded by ArgiNLS enhances machine learning-automated segmentation of single cells due to rapid classifier training and enrichment of labeled cell detection within 2D brain sections or 3D volumetric whole-brain image datasets, derived from both staining-amplified and native signal. This genetic strategy provides a simple and flexible basis for precise image segmentation of genetically labeled single cells at scale and paired with behavioral procedures.
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Affiliation(s)
- Eric R. Szelenyi
- Center of Excellence in Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA98195
- Department of Biological Structure, University of Washington, Seattle, WA98195
| | - Jovana S. Navarrete
- Center of Excellence in Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA98195
- Department of Biological Structure, University of Washington, Seattle, WA98195
- Graduate Program in Neuroscience, University of Washington, Seattle, WA98195
| | - Alexandria D. Murry
- Center of Excellence in Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA98195
- Department of Biological Structure, University of Washington, Seattle, WA98195
| | - Yizhe Zhang
- Center of Excellence in Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA98195
- Department of Biological Structure, University of Washington, Seattle, WA98195
| | - Kasey S. Girven
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA 98195
| | - Lauren Kuo
- Center of Excellence in Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA98195
- Undergraduate Program in Biochemistry, University of Washington, Seattle, WA98195
| | - Marcella M. Cline
- Center of Excellence in Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA98195
- Department of Pharmacology, University of Washington, Seattle, WA98195
| | - Mollie X. Bernstein
- Center of Excellence in Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA98195
- Department of Pharmacology, University of Washington, Seattle, WA98195
| | | | - Bryce Bowler
- Department of Biological Structure, University of Washington, Seattle, WA98195
| | - Nastacia L. Goodwin
- Center of Excellence in Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA98195
- Department of Biological Structure, University of Washington, Seattle, WA98195
- Graduate Program in Neuroscience, University of Washington, Seattle, WA98195
| | - Barbara Juarez
- Center of Excellence in Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA98195
- Department of Pharmacology, University of Washington, Seattle, WA98195
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA98195
| | - Larry S. Zweifel
- Center of Excellence in Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA98195
- Department of Pharmacology, University of Washington, Seattle, WA98195
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA98195
| | - Sam A. Golden
- Center of Excellence in Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA98195
- Department of Biological Structure, University of Washington, Seattle, WA98195
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2
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Wang J, Xu X, Ye H, Zhang X, Shi G. Interferometric modulation for generating extended light sheet: improving field of view. JOURNAL OF BIOMEDICAL OPTICS 2024; 29:046501. [PMID: 38629030 PMCID: PMC11020319 DOI: 10.1117/1.jbo.29.4.046501] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 03/20/2024] [Accepted: 03/27/2024] [Indexed: 04/19/2024]
Abstract
Significance Light-sheet fluorescence microscopy (LSFM) has emerged as a powerful and versatile imaging technique renowned for its remarkable features, including high-speed 3D tomography, minimal photobleaching, and low phototoxicity. The interference light-sheet fluorescence microscope, with its larger field of view (FOV) and more uniform axial resolution, possesses significant potential for a wide range of applications in biology and medicine. Aim The aim of this study is to investigate the interference behavior among multiple light sheets (LSs) in LSFM and optimize the FOV and resolution of the light-sheet fluorescence microscope. Approach We conducted a detailed investigation of the interference effects among LSs through theoretical derivation and numerical simulations, aiming to find optimal parameters. Subsequently, we constructed a customized system of multi-LSFM that incorporates both interference light sheets (ILS) and noninterference light-sheet configurations. We performed beam imaging and microsphere imaging tests to evaluate the FOV and axial resolution of these systems. Results Using our custom-designed light-sheet fluorescence microscope, we captured the intensity distribution profiles of both interference and noninterference light sheets (NILS). Additionally, we conducted imaging tests on microspheres to assess their imaging outcomes. The ILS not only exhibits a larger FOV compared to the NILS but also demonstrates a more uniform axial resolution. Conclusions By effectively modulating the interference among multiple LSs, it is possible to optimize the intensity distribution of the LSs, expand the FOV, and achieve a more uniform axial resolution.
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Affiliation(s)
- Jixiang Wang
- University of Science and Technology of China, School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, Hefei, China
- Chinese Academy of Science, Suzhou Institute of Biomedical Engineering and Technology, Jiangsu Key Laboratory of Medical Optics, Suzhou, China
| | - Xin Xu
- University of Science and Technology of China, School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, Hefei, China
- Chinese Academy of Science, Suzhou Institute of Biomedical Engineering and Technology, Jiangsu Key Laboratory of Medical Optics, Suzhou, China
| | - Hong Ye
- Chinese Academy of Science, Suzhou Institute of Biomedical Engineering and Technology, Jiangsu Key Laboratory of Medical Optics, Suzhou, China
| | - Xin Zhang
- Chinese Academy of Science, Suzhou Institute of Biomedical Engineering and Technology, Jiangsu Key Laboratory of Medical Optics, Suzhou, China
| | - Guohua Shi
- University of Science and Technology of China, School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, Hefei, China
- Chinese Academy of Science, Suzhou Institute of Biomedical Engineering and Technology, Jiangsu Key Laboratory of Medical Optics, Suzhou, China
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3
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Soumier A, Lio G, Demily C. Current and future applications of light-sheet imaging for identifying molecular and developmental processes in autism spectrum disorders. Mol Psychiatry 2024:10.1038/s41380-024-02487-8. [PMID: 38443634 DOI: 10.1038/s41380-024-02487-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 02/09/2024] [Accepted: 02/13/2024] [Indexed: 03/07/2024]
Abstract
Autism spectrum disorder (ASD) is identified by a set of neurodevelopmental divergences that typically affect the social communication domain. ASD is also characterized by heterogeneous cognitive impairments and is associated with cooccurring physical and medical conditions. As behaviors emerge as the brain matures, it is particularly essential to identify any gaps in neurodevelopmental trajectories during early perinatal life. Here, we introduce the potential of light-sheet imaging for studying developmental biology and cross-scale interactions among genetic, cellular, molecular and macroscale levels of circuitry and connectivity. We first report the core principles of light-sheet imaging and the recent progress in studying brain development in preclinical animal models and human organoids. We also present studies using light-sheet imaging to understand the development and function of other organs, such as the skin and gastrointestinal tract. We also provide information on the potential of light-sheet imaging in preclinical drug development. Finally, we speculate on the translational benefits of light-sheet imaging for studying individual brain-body interactions in advancing ASD research and creating personalized interventions.
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Affiliation(s)
- Amelie Soumier
- Le Vinatier Hospital Center, 95 boulevard Pinel, 69675, Bron cedex, France.
- iMIND, Center of Excellence for Autism, 95 boulevard Pinel, 69675, Bron cedex, France.
- Institute of Cognitive Science Marc Jeannerod, CNRS, UMR 5229, 67 boulevard Pinel, 69675, Bron cedex, France.
- University Claude Bernard Lyon 1, 43 boulevard du 11 Novembre 1918, 69622, Villeurbanne cedex, France.
| | - Guillaume Lio
- Le Vinatier Hospital Center, 95 boulevard Pinel, 69675, Bron cedex, France
- iMIND, Center of Excellence for Autism, 95 boulevard Pinel, 69675, Bron cedex, France
- Institute of Cognitive Science Marc Jeannerod, CNRS, UMR 5229, 67 boulevard Pinel, 69675, Bron cedex, France
| | - Caroline Demily
- Le Vinatier Hospital Center, 95 boulevard Pinel, 69675, Bron cedex, France
- iMIND, Center of Excellence for Autism, 95 boulevard Pinel, 69675, Bron cedex, France
- Institute of Cognitive Science Marc Jeannerod, CNRS, UMR 5229, 67 boulevard Pinel, 69675, Bron cedex, France
- University Claude Bernard Lyon 1, 43 boulevard du 11 Novembre 1918, 69622, Villeurbanne cedex, France
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4
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Wang Z, Zhang J, Symvoulidis P, Guo W, Zhang L, Wilson MA, Boyden ES. Imaging the voltage of neurons distributed across entire brains of larval zebrafish. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.15.571964. [PMID: 38168290 PMCID: PMC10760087 DOI: 10.1101/2023.12.15.571964] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
Neurons interact in networks distributed throughout the brain. Although much effort has focused on whole-brain calcium imaging, recent advances in genetically encoded voltage indicators (GEVIs) raise the possibility of imaging voltage of neurons distributed across brains. To achieve this, a microscope must image at high volumetric rate and signal-to-noise ratio. We present a remote scanning light-sheet microscope capable of imaging GEVI-expressing neurons distributed throughout entire brains of larval zebrafish at a volumetric rate of 200.8 Hz. We measured voltage of ∼1/3 of the neurons of the brain, distributed throughout. We observed that neurons firing at different times during a sequence were located at different brain locations, for sequences elicited by a visual stimulus, which mapped onto locations throughout the optic tectum, as well as during stimulus-independent bursts, which mapped onto locations in the cerebellum and medulla. Whole-brain voltage imaging may open up frontiers in the fundamental operation of neural systems.
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5
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Szelenyi ER, Navarrete JS, Murry AD, Zhang Y, Girven KS, Kuo L, Cline MM, Bernstein MX, Burdyniuk M, Bowler B, Goodwin NL, Juarez B, Zweifel LS, Golden SA. An arginine-rich nuclear localization signal (ArgiNLS) strategy for streamlined image segmentation of single-cells. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.22.568319. [PMID: 38045271 PMCID: PMC10690249 DOI: 10.1101/2023.11.22.568319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
High-throughput volumetric fluorescent microscopy pipelines can spatially integrate whole-brain structure and function at the foundational level of single-cells. However, conventional fluorescent protein (FP) modifications used to discriminate single-cells possess limited efficacy or are detrimental to cellular health. Here, we introduce a synthetic and non-deleterious nuclear localization signal (NLS) tag strategy, called 'Arginine-rich NLS' (ArgiNLS), that optimizes genetic labeling and downstream image segmentation of single-cells by restricting FP localization near-exclusively in the nucleus through a poly-arginine mechanism. A single N-terminal ArgiNLS tag provides modular nuclear restriction consistently across spectrally separate FP variants. ArgiNLS performance in vivo displays functional conservation across major cortical cell classes, and in response to both local and systemic brain wide AAV administration. Crucially, the high signal-to-noise ratio afforded by ArgiNLS enhances ML-automated segmentation of single-cells due to rapid classifier training and enrichment of labeled cell detection within 2D brain sections or 3D volumetric whole-brain image datasets, derived from both staining-amplified and native signal. This genetic strategy provides a simple and flexible basis for precise image segmentation of genetically labeled single-cells at scale and paired with behavioral procedures.
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Affiliation(s)
- Eric R. Szelenyi
- University of Washington Center of Excellence in Neurobiology of Addiction, Pain, and Emotion (NAPE), Seattle, WA, USA
- University of Washington, Department of Biological Structure, Seattle, WA, USA
| | - Jovana S. Navarrete
- University of Washington Center of Excellence in Neurobiology of Addiction, Pain, and Emotion (NAPE), Seattle, WA, USA
- University of Washington, Department of Biological Structure, Seattle, WA, USA
- University of Washington, Graduate Program in Neuroscience, Seattle, WA, USA
| | - Alexandria D. Murry
- University of Washington Center of Excellence in Neurobiology of Addiction, Pain, and Emotion (NAPE), Seattle, WA, USA
- University of Washington, Department of Biological Structure, Seattle, WA, USA
| | - Yizhe Zhang
- University of Washington Center of Excellence in Neurobiology of Addiction, Pain, and Emotion (NAPE), Seattle, WA, USA
- University of Washington, Department of Biological Structure, Seattle, WA, USA
| | - Kasey S. Girven
- University of Washington, Department of Anesthesiology and Pain Medicine
| | - Lauren Kuo
- University of Washington Center of Excellence in Neurobiology of Addiction, Pain, and Emotion (NAPE), Seattle, WA, USA
- University of Washington Undergraduate Program in Biochemistry
- Allen Institute for Cell Science, Seattle, WA, USA
| | - Marcella M. Cline
- University of Washington Center of Excellence in Neurobiology of Addiction, Pain, and Emotion (NAPE), Seattle, WA, USA
- University of Washington, Department of Pharmacology, Seattle, WA, USA
- Cajal Neuroscience, Seattle, WA, USA
| | - Mollie X. Bernstein
- University of Washington Center of Excellence in Neurobiology of Addiction, Pain, and Emotion (NAPE), Seattle, WA, USA
- University of Washington, Department of Pharmacology, Seattle, WA, USA
| | | | - Bryce Bowler
- University of Washington, Department of Biological Structure, Seattle, WA, USA
| | - Nastacia L. Goodwin
- University of Washington Center of Excellence in Neurobiology of Addiction, Pain, and Emotion (NAPE), Seattle, WA, USA
- University of Washington, Department of Biological Structure, Seattle, WA, USA
- University of Washington, Graduate Program in Neuroscience, Seattle, WA, USA
| | - Barbara Juarez
- University of Washington Center of Excellence in Neurobiology of Addiction, Pain, and Emotion (NAPE), Seattle, WA, USA
- University of Washington, Department of Psychiatry and Behavioral Sciences, Seattle, WA, USA
- University of Washington, Department of Pharmacology, Seattle, WA, USA
- University of Maryland School of Medicine, Department of Neurobiology, Baltimore, MD, USA
| | - Larry S. Zweifel
- University of Washington Center of Excellence in Neurobiology of Addiction, Pain, and Emotion (NAPE), Seattle, WA, USA
- University of Washington, Department of Psychiatry and Behavioral Sciences, Seattle, WA, USA
- University of Washington, Department of Pharmacology, Seattle, WA, USA
| | - Sam A. Golden
- University of Washington Center of Excellence in Neurobiology of Addiction, Pain, and Emotion (NAPE), Seattle, WA, USA
- University of Washington, Department of Biological Structure, Seattle, WA, USA
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Barron-Ortiz D, Cadena-Nava RD, Pérez-Parets E, Licea-Rodriguez J, Gualda EJ, Hernandez-Cordero J, Loza-Alvarez P, Rocha-Mendoza I. Volumetric Temperature Mapping Using Light-Sheet Microscopy and Upconversion Fluorescence from Micro- and Nano-Rare Earth Composites. MICROMACHINES 2023; 14:2097. [PMID: 38004954 PMCID: PMC10673603 DOI: 10.3390/mi14112097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Revised: 11/09/2023] [Accepted: 11/13/2023] [Indexed: 11/26/2023]
Abstract
We present a combination of light-sheet excitation and two-dimensional fluorescence intensity ratio (FIR) measurements as a simple and promising technique for three-dimensional temperature mapping. The feasibility of this approach is demonstrated with samples fabricated with sodium yttrium fluoride nanoparticles co-doped with rare-earth ytterbium and erbium ions (NaYF4:Yb3+/Er3+) incorporated into polydimethylsiloxane (PDMS) as a host material. In addition, we also evaluate the technique using lipid-coated NaYF4:Yb3+/Er3+ nanoparticles immersed in agar. The composite materials show upconverted (UC) fluorescence bands when excited by a 980 nm near-infrared laser light-sheet. Using a single CMOS camera and a pair of interferometric optical filters to specifically image the two thermally-coupled bands (at 525 and 550 nm), the two-dimensional FIR and, hence, the temperature map can be readily obtained. The proposed method can take optically sectioned (confocal-like) images with good optical resolution over relatively large samples (up to the millimetric scale) for further 3D temperature reconstruction.
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Affiliation(s)
- Dannareli Barron-Ortiz
- Centro de Investigación Científica y de Educación Superior de Ensenada (CICESE), Carretera Ensenada-Tijuana, No. 3918, Zona Playitas, Ensenada 22860, Mexico;
| | - Ruben D. Cadena-Nava
- Centro de Nanociencias y Nanotecnología (CNyN), Universidad Nacional Autónoma de México (UNAM), Km 107 Carretera Tijuana-Ensenada, Pedregal Playitas, Ensenada 22860, Mexico;
| | - Enric Pérez-Parets
- ICFO-Institut de Ciencies Fotoniques, The Barcelona Institute of Science and Technology, Av. Carl Friedrich Gauss, 3, 08860 Castelldefels, Spain
| | - Jacob Licea-Rodriguez
- Centro de Investigación en Ingeniería y Ciencias Aplicadas (CIICAp), Universidad Autónoma del Estado de Morelos, Cuernavaca 62209, Mexico
| | - Emilio J. Gualda
- ICFO-Institut de Ciencies Fotoniques, The Barcelona Institute of Science and Technology, Av. Carl Friedrich Gauss, 3, 08860 Castelldefels, Spain
- Department of Agri-Food Engineering and Biotechnology (DEAB), Universitat Politècnica de Catalunya, Esteve Terradas 8, 08860 Castelldefels, Spain;
| | - Juan Hernandez-Cordero
- Instituto de Investigaciones en Materiales, Universidad Nacional Autónoma de México, A.P. 70-360, Mexico City 04510, Mexico;
| | - Pablo Loza-Alvarez
- ICFO-Institut de Ciencies Fotoniques, The Barcelona Institute of Science and Technology, Av. Carl Friedrich Gauss, 3, 08860 Castelldefels, Spain
| | - Israel Rocha-Mendoza
- Centro de Investigación Científica y de Educación Superior de Ensenada (CICESE), Carretera Ensenada-Tijuana, No. 3918, Zona Playitas, Ensenada 22860, Mexico;
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7
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Liu Y, Liu B, Green J, Duffy C, Song M, Lauderdale JD, Kner P. Volumetric light sheet imaging with adaptive optics correction. BIOMEDICAL OPTICS EXPRESS 2023; 14:1757-1771. [PMID: 37078033 PMCID: PMC10110302 DOI: 10.1364/boe.473237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 03/09/2023] [Accepted: 03/10/2023] [Indexed: 05/02/2023]
Abstract
Light sheet microscopy has developed quickly over the past decades and become a popular method for imaging live model organisms and other thick biological tissues. For rapid volumetric imaging, an electrically tunable lens can be used to rapidly change the imaging plane in the sample. For larger fields of view and higher NA objectives, the electrically tunable lens introduces aberrations in the system, particularly away from the nominal focus and off-axis. Here, we describe a system that employs an electrically tunable lens and adaptive optics to image over a volume of 499 × 499 × 192 μm3 with close to diffraction-limited resolution. Compared to the system without adaptive optics, the performance shows an increase in signal to background ratio by a factor of 3.5. While the system currently requires 7s/volume, it should be straightforward to increase the imaging speed to under 1s per volume.
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Affiliation(s)
- Yang Liu
- School of Electrical and Computer Engineering, University of Georgia, Athens, GA 30602, USA
| | - Bingxi Liu
- School of Electrical and Computer Engineering, University of Georgia, Athens, GA 30602, USA
| | - John Green
- School of Electrical and Computer Engineering, University of Georgia, Athens, GA 30602, USA
| | - Carly Duffy
- Dept. of Cellular Biology, University of Georgia, Athens, GA 30602, USA
| | - Ming Song
- School of Electrical and Computer Engineering, University of Georgia, Athens, GA 30602, USA
| | - James D. Lauderdale
- Dept. of Cellular Biology, University of Georgia, Athens, GA 30602, USA
- Neuroscience Division of the Biomedical Health Sciences Institute, University of Georgia, Athens, GA 30602, USA
| | - Peter Kner
- School of Electrical and Computer Engineering, University of Georgia, Athens, GA 30602, USA
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8
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Gu Q, Sarkar S, Raymick B, Kanungo J. Combining tissue clearing and Fluoro-Jade C labeling for neurotoxicity assessments. Exp Biol Med (Maywood) 2023; 248:605-611. [PMID: 37208909 PMCID: PMC10350804 DOI: 10.1177/15353702231165009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 03/02/2023] [Indexed: 05/21/2023] Open
Abstract
Tissue clearing refers to laboratory methods that make tissue transparent by chemical means. This approach allows the labeling, visualization, and analysis of specific targets without cutting the tissue into sections, thereby maintaining three-dimensional architecture. More than two dozen tissue-clearing methods have been developed by different research teams to date. While tissue clearing has been successfully applied in several studies concerning basic science or diseases, little is known about the utilization of tissue clearing for neurotoxicity evaluation. In this study, several tissue-clearing methods were combined with Fluoro-Jade C (FJ-C), a standard marker of neurodegeneration. The results suggest that some but not all tissue-clearing media are compatible with the FJ-C fluorophore. By utilizing a neurotoxicity animal model, the results further suggest that FJ-C labeling can be combined with tissue clearing for neurotoxicity assessments. This approach has the potential to be expanded further by combining multicolor labeling of molecular targets involved in the development and/or mechanisms of neurotoxicity and neurodegeneration.
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Affiliation(s)
- Qiang Gu
- Division of Neurotoxicology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR 72079, USA
| | - Sumit Sarkar
- Division of Neurotoxicology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR 72079, USA
| | - Bryan Raymick
- Division of Neurotoxicology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR 72079, USA
| | - Jyotshna Kanungo
- Division of Neurotoxicology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR 72079, USA
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9
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Stockhausen A, Rodriguez-Gatica JE, Schweihoff J, Schwarz MK, Kubitscheck U. Airy beam light sheet microscopy boosted by deep learning deconvolution. OPTICS EXPRESS 2023; 31:10918-10935. [PMID: 37157627 DOI: 10.1364/oe.485699] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
Common light sheet microscopy comes with a trade-off between light sheet width defining the optical sectioning and the usable field of view arising from the divergence of the illuminating Gaussian beam. To overcome this, low-diverging Airy beams have been introduced. Airy beams, however, exhibit side lobes degrading image contrast. Here, we constructed an Airy beam light sheet microscope, and developed a deep learning image deconvolution to remove the effects of the side lobes without knowledge of the point spread function. Using a generative adversarial network and high-quality training data, we significantly enhanced image contrast and improved the performance of a bicubic upscaling. We evaluated the performance with fluorescently labeled neurons in mouse brain tissue samples. We found that deep learning-based deconvolution was about 20-fold faster than the standard approach. The combination of Airy beam light sheet microscopy and deep learning deconvolution allows imaging large volumes rapidly and with high quality.
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10
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Wijesinghe P, Corsetti S, Chow DJX, Sakata S, Dunning KR, Dholakia K. Experimentally unsupervised deconvolution for light-sheet microscopy with propagation-invariant beams. LIGHT, SCIENCE & APPLICATIONS 2022; 11:319. [PMID: 36319636 PMCID: PMC9626625 DOI: 10.1038/s41377-022-00975-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Revised: 08/26/2022] [Accepted: 08/31/2022] [Indexed: 05/25/2023]
Abstract
Deconvolution is a challenging inverse problem, particularly in techniques that employ complex engineered point-spread functions, such as microscopy with propagation-invariant beams. Here, we present a deep-learning method for deconvolution that, in lieu of end-to-end training with ground truths, is trained using known physics of the imaging system. Specifically, we train a generative adversarial network with images generated with the known point-spread function of the system, and combine this with unpaired experimental data that preserve perceptual content. Our method rapidly and robustly deconvolves and super-resolves microscopy images, demonstrating a two-fold improvement in image contrast to conventional deconvolution methods. In contrast to common end-to-end networks that often require 1000-10,000s paired images, our method is experimentally unsupervised and can be trained solely on a few hundred regions of interest. We demonstrate its performance on light-sheet microscopy with propagation-invariant Airy beams in oocytes, preimplantation embryos and excised brain tissue, as well as illustrate its utility for Bessel-beam LSM. This method aims to democratise learned methods for deconvolution, as it does not require data acquisition outwith the conventional imaging protocol.
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Affiliation(s)
- Philip Wijesinghe
- SUPA, School of Physics and Astronomy, University of St Andrews, North Haugh, St Andrews, Fife, KY16 9SS, UK.
| | - Stella Corsetti
- SUPA, School of Physics and Astronomy, University of St Andrews, North Haugh, St Andrews, Fife, KY16 9SS, UK
| | - Darren J X Chow
- Robinson Research Institute, Adelaide Medical School, The University of Adelaide, Adelaide, SA, Australia
- Australian Research Council Centre of Excellence for Nanoscale BioPhotonics, The University of Adelaide, Adelaide, SA, Australia
- Institute for Photonics and Advanced Sensing, The University of Adelaide, Adelaide, SA, Australia
| | - Shuzo Sakata
- Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, G4 0RE, UK
| | - Kylie R Dunning
- Robinson Research Institute, Adelaide Medical School, The University of Adelaide, Adelaide, SA, Australia
- Australian Research Council Centre of Excellence for Nanoscale BioPhotonics, The University of Adelaide, Adelaide, SA, Australia
- Institute for Photonics and Advanced Sensing, The University of Adelaide, Adelaide, SA, Australia
| | - Kishan Dholakia
- SUPA, School of Physics and Astronomy, University of St Andrews, North Haugh, St Andrews, Fife, KY16 9SS, UK.
- School of Biological Sciences, The University of Adelaide, Adelaide, SA, Australia.
- Department of Physics, College of Science, Yonsei University, Seoul, 03722, South Korea.
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11
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Bennett HC, Kim Y. Advances in studying whole mouse brain vasculature using high-resolution 3D light microscopy imaging. NEUROPHOTONICS 2022; 9:021902. [PMID: 35402638 PMCID: PMC8983067 DOI: 10.1117/1.nph.9.2.021902] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 03/11/2022] [Indexed: 06/14/2023]
Abstract
Significance: The cerebrovasculature has become increasingly recognized as a major player in overall brain health and many brain disorders. Although there have been several landmark studies to understand details of these crucially important structures in an anatomically defined area, brain-wide examination of the whole cerebrovasculature, including microvessels, has been challenging. However, emerging techniques, including tissue processing and three-dimensional (3D) microscopy imaging, enable neuroscientists to examine the total vasculature in the entire mouse brain. Aim: Here, we aim to highlight advances in these high-resolution 3D mapping methods including block-face imaging and light sheet fluorescent microscopy. Approach: We summarize latest mapping tools to understand detailed anatomical arrangement of the cerebrovascular network and the organizing principles of the neurovascular unit (NVU) as a whole. Results: We discuss biological insights gained from studies using these imaging methods and how these tools can be used to advance our understanding of the cerebrovascular network and related cell types in the entire brain. Conclusions: This review article will help to understand recent advance in high-resolution NVU mapping in mice and provide perspective on future studies.
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Affiliation(s)
- Hannah C. Bennett
- The Pennsylvania State University, Department of Neural and Behavioral Sciences, Hershey, Pennsylvania, United States
| | - Yongsoo Kim
- The Pennsylvania State University, Department of Neural and Behavioral Sciences, Hershey, Pennsylvania, United States
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12
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Zeng C, Chen Z, Yang H, Fan Y, Fei L, Chen X, Zhang M. Advanced high resolution three-dimensional imaging to visualize the cerebral neurovascular network in stroke. Int J Biol Sci 2022; 18:552-571. [PMID: 35002509 PMCID: PMC8741851 DOI: 10.7150/ijbs.64373] [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: 07/01/2021] [Accepted: 10/28/2021] [Indexed: 11/05/2022] Open
Abstract
As an important method to accurately and timely diagnose stroke and study physiological characteristics and pathological mechanism in it, imaging technology has gone through more than a century of iteration. The interaction of cells densely packed in the brain is three-dimensional (3D), but the flat images brought by traditional visualization methods show only a few cells and ignore connections outside the slices. The increased resolution allows for a more microscopic and underlying view. Today's intuitive 3D imagings of micron or even nanometer scale are showing its essentiality in stroke. In recent years, 3D imaging technology has gained rapid development. With the overhaul of imaging mediums and the innovation of imaging mode, the resolution has been significantly improved, endowing researchers with the capability of holistic observation of a large volume, real-time monitoring of tiny voxels, and quantitative measurement of spatial parameters. In this review, we will summarize the current methods of high-resolution 3D imaging applied in stroke.
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Affiliation(s)
- Chudai Zeng
- Department of Neurology, Xiangya Hospital of Central South University, Changsha, Hunan, China, 410008.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China, 410008
| | - Zhuohui Chen
- Department of Neurology, Xiangya Hospital of Central South University, Changsha, Hunan, China, 410008.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China, 410008
| | - Haojun Yang
- Department of Neurology, Xiangya Hospital of Central South University, Changsha, Hunan, China, 410008.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China, 410008
| | - Yishu Fan
- Department of Neurology, Xiangya Hospital of Central South University, Changsha, Hunan, China, 410008.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China, 410008
| | - Lujing Fei
- Department of Neurology, Xiangya Hospital of Central South University, Changsha, Hunan, China, 410008.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China, 410008
| | - Xinghang Chen
- Department of Neurology, Xiangya Hospital of Central South University, Changsha, Hunan, China, 410008.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China, 410008
| | - Mengqi Zhang
- Department of Neurology, Xiangya Hospital of Central South University, Changsha, Hunan, China, 410008.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China, 410008
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13
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Newmaster KT, Kronman FA, Wu YT, Kim Y. Seeing the Forest and Its Trees Together: Implementing 3D Light Microscopy Pipelines for Cell Type Mapping in the Mouse Brain. Front Neuroanat 2022; 15:787601. [PMID: 35095432 PMCID: PMC8794814 DOI: 10.3389/fnana.2021.787601] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Accepted: 12/02/2021] [Indexed: 12/14/2022] Open
Abstract
The brain is composed of diverse neuronal and non-neuronal cell types with complex regional connectivity patterns that create the anatomical infrastructure underlying cognition. Remarkable advances in neuroscience techniques enable labeling and imaging of these individual cell types and their interactions throughout intact mammalian brains at a cellular resolution allowing neuroscientists to examine microscopic details in macroscopic brain circuits. Nevertheless, implementing these tools is fraught with many technical and analytical challenges with a need for high-level data analysis. Here we review key technical considerations for implementing a brain mapping pipeline using the mouse brain as a primary model system. Specifically, we provide practical details for choosing methods including cell type specific labeling, sample preparation (e.g., tissue clearing), microscopy modalities, image processing, and data analysis (e.g., image registration to standard atlases). We also highlight the need to develop better 3D atlases with standardized anatomical labels and nomenclature across species and developmental time points to extend the mapping to other species including humans and to facilitate data sharing, confederation, and integrative analysis. In summary, this review provides key elements and currently available resources to consider while developing and implementing high-resolution mapping methods.
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Affiliation(s)
- Kyra T Newmaster
- Department of Neural and Behavioral Sciences, The Pennsylvania State University, Hershey, PA, United States
| | - Fae A Kronman
- Department of Neural and Behavioral Sciences, The Pennsylvania State University, Hershey, PA, United States
| | - Yuan-Ting Wu
- Department of Neural and Behavioral Sciences, The Pennsylvania State University, Hershey, PA, United States
| | - Yongsoo Kim
- Department of Neural and Behavioral Sciences, The Pennsylvania State University, Hershey, PA, United States
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14
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Gagliano G, Nelson T, Saliba N, Vargas-Hernández S, Gustavsson AK. Light Sheet Illumination for 3D Single-Molecule Super-Resolution Imaging of Neuronal Synapses. Front Synaptic Neurosci 2021; 13:761530. [PMID: 34899261 PMCID: PMC8651567 DOI: 10.3389/fnsyn.2021.761530] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Accepted: 10/27/2021] [Indexed: 01/02/2023] Open
Abstract
The function of the neuronal synapse depends on the dynamics and interactions of individual molecules at the nanoscale. With the development of single-molecule super-resolution microscopy over the last decades, researchers now have a powerful and versatile imaging tool for mapping the molecular mechanisms behind the biological function. However, imaging of thicker samples, such as mammalian cells and tissue, in all three dimensions is still challenging due to increased fluorescence background and imaging volumes. The combination of single-molecule imaging with light sheet illumination is an emerging approach that allows for imaging of biological samples with reduced fluorescence background, photobleaching, and photodamage. In this review, we first present a brief overview of light sheet illumination and previous super-resolution techniques used for imaging of neurons and synapses. We then provide an in-depth technical review of the fundamental concepts and the current state of the art in the fields of three-dimensional single-molecule tracking and super-resolution imaging with light sheet illumination. We review how light sheet illumination can improve single-molecule tracking and super-resolution imaging in individual neurons and synapses, and we discuss emerging perspectives and new innovations that have the potential to enable and improve single-molecule imaging in brain tissue.
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Affiliation(s)
- Gabriella Gagliano
- Department of Chemistry, Rice University, Houston, TX, United States
- Applied Physics Program, Rice University, Houston, TX, United States
- Smalley-Curl Institute, Rice University, Houston, TX, United States
| | - Tyler Nelson
- Department of Chemistry, Rice University, Houston, TX, United States
- Applied Physics Program, Rice University, Houston, TX, United States
- Smalley-Curl Institute, Rice University, Houston, TX, United States
| | - Nahima Saliba
- Department of Chemistry, Rice University, Houston, TX, United States
| | - Sofía Vargas-Hernández
- Department of Chemistry, Rice University, Houston, TX, United States
- Systems, Synthetic, and Physical Biology Program, Rice University, Houston, TX, United States
- Institute of Biosciences & Bioengineering, Rice University, Houston, TX, United States
| | - Anna-Karin Gustavsson
- Department of Chemistry, Rice University, Houston, TX, United States
- Smalley-Curl Institute, Rice University, Houston, TX, United States
- Institute of Biosciences & Bioengineering, Rice University, Houston, TX, United States
- Department of Biosciences, Rice University, Houston, TX, United States
- Laboratory for Nanophotonics, Rice University, Houston, TX, United States
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15
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Weaver CJ, Poulain FE. From whole organism to ultrastructure: progress in axonal imaging for decoding circuit development. Development 2021; 148:271122. [PMID: 34328171 DOI: 10.1242/dev.199717] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Since the pioneering work of Ramón y Cajal, scientists have sought to unravel the complexities of axon development underlying neural circuit formation. Micrometer-scale axonal growth cones navigate to targets that are often centimeters away. To reach their targets, growth cones react to dynamic environmental cues that change in the order of seconds to days. Proper axon growth and guidance are essential to circuit formation, and progress in imaging has been integral to studying these processes. In particular, advances in high- and super-resolution microscopy provide the spatial and temporal resolution required for studying developing axons. In this Review, we describe how improved microscopy has revolutionized our understanding of axonal development. We discuss how novel technologies, specifically light-sheet and super-resolution microscopy, led to new discoveries at the cellular scale by imaging axon outgrowth and circuit wiring with extreme precision. We next examine how advanced microscopy broadened our understanding of the subcellular dynamics driving axon growth and guidance. We finally assess the current challenges that the field of axonal biology still faces for imaging axons, and examine how future technology could meet these needs.
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Affiliation(s)
- Cory J Weaver
- Department of Biological Sciences, University of South Carolina, Columbia, SC 29208, USA
| | - Fabienne E Poulain
- Department of Biological Sciences, University of South Carolina, Columbia, SC 29208, USA
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16
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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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17
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Daria VR, Castañares ML, Bachor HA. Spatio-temporal parameters for optical probing of neuronal activity. Biophys Rev 2021; 13:13-33. [PMID: 33747244 PMCID: PMC7930150 DOI: 10.1007/s12551-021-00780-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2020] [Accepted: 01/01/2021] [Indexed: 12/28/2022] Open
Abstract
The challenge to understand the complex neuronal circuit functions in the mammalian brain has brought about a revolution in light-based neurotechnologies and optogenetic tools. However, while recent seminal works have shown excellent insights on the processing of basic functions such as sensory perception, memory, and navigation, understanding more complex brain functions is still unattainable with current technologies. We are just scratching the surface, both literally and figuratively. Yet, the path towards fully understanding the brain is not totally uncertain. Recent rapid technological advancements have allowed us to analyze the processing of signals within dendritic arborizations of single neurons and within neuronal circuits. Understanding the circuit dynamics in the brain requires a good appreciation of the spatial and temporal properties of neuronal activity. Here, we assess the spatio-temporal parameters of neuronal responses and match them with suitable light-based neurotechnologies as well as photochemical and optogenetic tools. We focus on the spatial range that includes dendrites and certain brain regions (e.g., cortex and hippocampus) that constitute neuronal circuits. We also review some temporal characteristics of some proteins and ion channels responsible for certain neuronal functions. With the aid of the photochemical and optogenetic markers, we can use light to visualize the circuit dynamics of a functioning brain. The challenge to understand how the brain works continue to excite scientists as research questions begin to link macroscopic and microscopic units of brain circuits.
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Affiliation(s)
- Vincent R. Daria
- Research School of Physics, The Australian National University, Canberra, Australia
- John Curtin School of Medical Research, The Australian National University, Canberra, Australia
| | | | - Hans-A. Bachor
- Research School of Physics, The Australian National University, Canberra, Australia
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18
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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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19
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Timonidis N, Bakker R, Tiesinga P. Prediction of a Cell-Class-Specific Mouse Mesoconnectome Using Gene Expression Data. Neuroinformatics 2020; 18:611-626. [PMID: 32448958 PMCID: PMC7498447 DOI: 10.1007/s12021-020-09471-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
Reconstructing brain connectivity at sufficient resolution for computational models designed to study the biophysical mechanisms underlying cognitive processes is extremely challenging. For such a purpose, a mesoconnectome that includes laminar and cell-class specificity would be a major step forward. We analyzed the ability of gene expression patterns to predict cell-class and layer-specific projection patterns and assessed the functional annotations of the most predictive groups of genes. To achieve our goal we used publicly available volumetric gene expression and connectivity data and we trained computational models to learn and predict cell-class and layer-specific axonal projections using gene expression data. Predictions were done in two ways, namely predicting projection strengths using the expression of individual genes and using the co-expression of genes organized in spatial modules, as well as predicting binary forms of projection. For predicting the strength of projections, we found that ridge (L2-regularized) regression had the highest cross-validated accuracy with a median r2 score of 0.54 which corresponded for binarized predictions to a median area under the ROC value of 0.89. Next, we identified 200 spatial gene modules using a dictionary learning and sparse coding approach. We found that these modules yielded predictions of comparable accuracy, with a median r2 score of 0.51. Finally, a gene ontology enrichment analysis of the most predictive gene groups resulted in significant annotations related to postsynaptic function. Taken together, we have demonstrated a prediction workflow that can be used to perform multimodal data integration to improve the accuracy of the predicted mesoconnectome and support other neuroscience use cases.
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Affiliation(s)
- Nestor Timonidis
- Neuroinformatics Department, Donders Centre for Neuroscience, Radboud University Nijmegen, Heyendaalseweg 135, 6525, AJ, Nijmegen, the Netherlands.
| | - Rembrandt Bakker
- Neuroinformatics Department, Donders Centre for Neuroscience, Radboud University Nijmegen, Heyendaalseweg 135, 6525, AJ, Nijmegen, the Netherlands.,Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA BRAIN Institute I, Jülich Research Centre, Wilhelm-Johnen-Strasse, 52425, Jülich, Germany
| | - Paul Tiesinga
- Neuroinformatics Department, Donders Centre for Neuroscience, Radboud University Nijmegen, Heyendaalseweg 135, 6525, AJ, Nijmegen, the Netherlands
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20
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Fiedler S, Wünnemann H, Hofmann I, Theobalt N, Feuchtinger A, Walch A, Schwaiger J, Wanke R, Blutke A. A practical guide to unbiased quantitative morphological analyses of the gills of rainbow trout (Oncorhynchus mykiss) in ecotoxicological studies. PLoS One 2020; 15:e0243462. [PMID: 33296424 PMCID: PMC7725368 DOI: 10.1371/journal.pone.0243462] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Accepted: 11/21/2020] [Indexed: 12/28/2022] Open
Abstract
Rainbow trout (Oncorhynchus mykiss) are frequently used as experimental animals in ecotoxicological studies, in which they are experimentally exposed to defined concentrations of test substances, such as heavy metals, pesticides, or pharmaceuticals. Following exposure to a broad variety of aquatic pollutants, early morphologically detectable toxic effects often manifest in alterations of the gills. Suitable methods for an accurate and unbiased quantitative characterization of the type and the extent of morphological gill alterations are therefore essential prerequisites for recognition, objective evaluation and comparison of the severity of gill lesions. The aim of the present guidelines is to provide practicable, standardized and detailed protocols for the application of unbiased quantitative stereological analyses of relevant morphological parameters of the gills of rainbow trout. These gill parameters inter alia include the total volume of the primary and secondary gill lamellae, the surface area of the secondary gill lamellae epithelium (i.e., the respiratory surface) and the thickness of the diffusion barrier. The featured protocols are adapted to fish of frequently used body size classes (300-2000 g). They include well-established, conventional sampling methods, probes and test systems for unbiased quantitative stereological analyses of light- and electron microscopic 2-D gill sections, as well as the application of modern 3-D light sheet fluorescence microscopy (LSFM) of optically cleared gill samples as an innovative, fast and efficient quantitative morphological analysis approach. The methods shown here provide a basis for standardized and representative state-of-the-art quantitative morphological analyses of trout gills, ensuring the unbiasedness and reproducibility, as well as the intra- and inter-study comparability of analyses results. Their broad implementation will therefore significantly contribute to the reliable identification of no observed effect concentration (NOEC) limits in ecotoxicological studies and, moreover, to limit the number of experimental animals by reduction of unnecessary repetition of experiments.
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Affiliation(s)
- Sonja Fiedler
- Institute of Veterinary Pathology at the Center for Clinical Veterinary Medicine, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Hannah Wünnemann
- Unit 73 Aquatic Ecotoxicology, Microbial Ecology, Bavarian Environment Agency, Wielenbach, Germany
| | - Isabel Hofmann
- Institute of Veterinary Pathology at the Center for Clinical Veterinary Medicine, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Natalie Theobalt
- Institute of Veterinary Pathology at the Center for Clinical Veterinary Medicine, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Annette Feuchtinger
- Research Unit Analytical Pathology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Axel Walch
- Research Unit Analytical Pathology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Julia Schwaiger
- Unit 73 Aquatic Ecotoxicology, Microbial Ecology, Bavarian Environment Agency, Wielenbach, Germany
| | - Rüdiger Wanke
- Institute of Veterinary Pathology at the Center for Clinical Veterinary Medicine, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Andreas Blutke
- Research Unit Analytical Pathology, Helmholtz Zentrum München, Neuherberg, Germany
- * E-mail:
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21
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Stockhausen A, Bürgers J, Rodriguez-Gatica JE, Schweihoff J, Merkel R, Prigge JM, Schwarz MK, Kubitscheck U. Hard-wired lattice light-sheet microscopy for imaging of expanded samples. OPTICS EXPRESS 2020; 28:15587-15600. [PMID: 32403583 DOI: 10.1364/oe.393728] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/26/2020] [Accepted: 04/28/2020] [Indexed: 06/11/2023]
Abstract
Light-sheet fluorescence microscopy (LSFM) helps investigate small structures in developing cells and tissue for three-dimensional localization microscopy and large-field brain imaging in neuroscience. Lattice light-sheet microscopy is a recent development with great potential to improve axial resolution and usable field sizes, thus improving imaging speed. In contrast to the commonly employed Gaussian beams for light-sheet generation in conventional LSFM, in lattice light-sheet microscopy an array of low diverging Bessel beams with a suppressed side lobe structure is used. We developed a facile elementary lattice light-sheet microscope using a micro-fabricated fixed ring mask for lattice light-sheet generation. In our setup, optical hardware elements enable a stable and simple illumination path without the need for spatial light modulators. This setup, in combination with long-working distance objectives and the possibility for simultaneous dual-color imaging, provides optimal conditions for imaging extended optically cleared tissue samples. We here present experimental data of fluorescently stained neurons and neurites from mouse hippocampus following tissue expansion and demonstrate the high homogeneous resolution throughout the entire imaged volume. Utilizing our purpose-built lattice light-sheet microscope, we reached a homogeneous excitation and an axial resolution of 1.2 µm over a field of view of (333 µm)2.
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22
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Ultra-thin fluorocarbon foils optimise multiscale imaging of three-dimensional native and optically cleared specimens. Sci Rep 2019; 9:17292. [PMID: 31754183 PMCID: PMC6872575 DOI: 10.1038/s41598-019-53380-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2019] [Accepted: 10/31/2019] [Indexed: 01/09/2023] Open
Abstract
In three-dimensional light microscopy, the heterogeneity of the optical density in a specimen ultimately limits the achievable penetration depth and hence the three-dimensional resolution. The most direct approach to reduce aberrations, improve the contrast and achieve an optimal resolution is to minimise the impact of changes of the refractive index along an optical path. Many implementations of light sheet fluorescence microscopy operate with a large chamber filled with an aqueous immersion medium and a further inner container with the specimen embedded in a possibly entirely different non-aqueous medium. In order to minimise the impact of the latter on the optical quality of the images, we use multi-facetted cuvettes fabricated from vacuum-formed ultra-thin fluorocarbon (FEP) foils. The ultra-thin FEP-foil cuvettes have a wall thickness of about 10–12 µm. They are impermeable to liquids, but not to gases, inert, durable, mechanically stable and flexible. Importantly, the usually fragile specimen can remain in the same cuvette from seeding to fixation, clearing and observation, without the need to remove or remount it during any of these steps. We confirm the improved imaging performance of ultra-thin FEP-foil cuvettes with excellent quality images of whole organs such us mouse oocytes, of thick tissue sections from mouse brain and kidney as well as of dense pancreas and liver organoid clusters. Our ultra-thin FEP-foil cuvettes outperform many other sample-mounting techniques in terms of a full separation of the specimen from the immersion medium, compatibility with aqueous and organic clearing media, quick specimen mounting without hydrogel embedding and their applicability for multiple-view imaging and automated image segmentation. Additionally, we show that ultra-thin FEP foil cuvettes are suitable for seeding and growing organoids over a time period of at least ten days. The new cuvettes allow the fixation and staining of specimens inside the holder, preserving the delicate morphology of e.g. fragile, mono-layered three-dimensional organoids.
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