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Sorensen SA, Gouwens NW, Wang Y, Mallory M, Budzillo A, Dalley R, Lee B, Gliko O, Kuo HC, Kuang X, Mann R, Ahmadinia L, Alfiler L, Baftizadeh F, Baker K, Bannick S, Bertagnolli D, Bickley K, Bohn P, Brown D, Bomben J, Brouner K, Chen C, Chen K, Chvilicek M, Collman F, Daigle T, Dawes T, de Frates R, Dee N, DePartee M, Egdorf T, El-Hifnawi L, Enstrom R, Esposito L, Farrell C, Gala R, Glomb A, Gamlin C, Gary A, Goldy J, Gu H, Hadley K, Hawrylycz M, Henry A, Hill D, Hirokawa KE, Huang Z, Johnson K, Juneau Z, Kebede S, Kim L, Lee C, Lesnar P, Li A, Glomb A, Li Y, Liang E, Link K, Maxwell M, McGraw M, McMillen DA, Mukora A, Ng L, Ochoa T, Oldre A, Park D, Pom CA, Popovich Z, Potekhina L, Rajanbabu R, Ransford S, Reding M, Ruiz A, Sandman D, Siverts L, Smith KA, Stoecklin M, Sulc J, Tieu M, Ting J, Trinh J, Vargas S, Vumbaco D, Walker M, Wang M, Wanner A, Waters J, Williams G, Wilson J, Xiong W, Lein E, Berg J, Kalmbach B, Yao S, Gong H, Luo Q, Ng L, Sümbül U, Jarsky T, Yao Z, Tasic B, Zeng H. Connecting single-cell transcriptomes to projectomes in mouse visual cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.25.568393. [PMID: 38168270 PMCID: PMC10760188 DOI: 10.1101/2023.11.25.568393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
The mammalian brain is composed of diverse neuron types that play different functional roles. Recent single-cell RNA sequencing approaches have led to a whole brain taxonomy of transcriptomically-defined cell types, yet cell type definitions that include multiple cellular properties can offer additional insights into a neuron's role in brain circuits. While the Patch-seq method can investigate how transcriptomic properties relate to the local morphological and electrophysiological properties of cell types, linking transcriptomic identities to long-range projections is a major unresolved challenge. To address this, we collected coordinated Patch-seq and whole brain morphology data sets of excitatory neurons in mouse visual cortex. From the Patch-seq data, we defined 16 integrated morpho-electric-transcriptomic (MET)-types; in parallel, we reconstructed the complete morphologies of 300 neurons. We unified the two data sets with a multi-step classifier, to integrate cell type assignments and interrogate cross-modality relationships. We find that transcriptomic variations within and across MET-types correspond with morphological and electrophysiological phenotypes. In addition, this variation, along with the anatomical location of the cell, can be used to predict the projection targets of individual neurons. We also shed new light on infragranular cell types and circuits, including cell-type-specific, interhemispheric projections. With this approach, we establish a comprehensive, integrated taxonomy of excitatory neuron types in mouse visual cortex and create a system for integrated, high-dimensional cell type classification that can be extended to the whole brain and potentially across species.
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Affiliation(s)
| | | | - Yun Wang
- Allen Institute for Brain Science
| | | | | | | | | | | | | | - Xiuli Kuang
- School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, China
| | | | | | | | | | | | | | | | | | | | | | | | | | - Chao Chen
- School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, China
| | - Kai Chen
- School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, China
| | | | | | | | | | | | - Nick Dee
- Allen Institute for Brain Science
| | | | | | | | | | | | | | | | | | | | | | | | - Hong Gu
- Allen Institute for Brain Science
| | | | | | | | | | | | - Zili Huang
- School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, China
| | | | | | | | - Lisa Kim
- Allen Institute for Brain Science
| | | | | | - Anan Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, China
- HUST-Suzhou Institute for Brainsmatics, JITRI Institute for Brainsmatics, Suzhou, China
| | | | - Yaoyao Li
- School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, China
| | | | | | | | | | | | | | | | | | | | | | | | - Zoran Popovich
- University of Washington, Dept. of Computer Science and Engineering
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Wei Xiong
- School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, China
| | - Ed Lein
- Allen Institute for Brain Science
| | - Jim Berg
- Allen Institute for Brain Science
| | | | | | - Hui Gong
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, China
- HUST-Suzhou Institute for Brainsmatics, JITRI Institute for Brainsmatics, Suzhou, China
| | - Qingming Luo
- State Key Laboratory of Digital Medical Engineering, School of Biomedical Engineering, Hainan University, Haikou, China
| | - Lydia Ng
- Allen Institute for Brain Science
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2
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Ning K, Lu B, Wang X, Zhang X, Nie S, Jiang T, Li A, Fan G, Wang X, Luo Q, Gong H, Yuan J. Deep self-learning enables fast, high-fidelity isotropic resolution restoration for volumetric fluorescence microscopy. LIGHT, SCIENCE & APPLICATIONS 2023; 12:204. [PMID: 37640721 PMCID: PMC10462670 DOI: 10.1038/s41377-023-01230-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Revised: 07/04/2023] [Accepted: 07/12/2023] [Indexed: 08/31/2023]
Abstract
One intrinsic yet critical issue that troubles the field of fluorescence microscopy ever since its introduction is the unmatched resolution in the lateral and axial directions (i.e., resolution anisotropy), which severely deteriorates the quality, reconstruction, and analysis of 3D volume images. By leveraging the natural anisotropy, we present a deep self-learning method termed Self-Net that significantly improves the resolution of axial images by using the lateral images from the same raw dataset as rational targets. By incorporating unsupervised learning for realistic anisotropic degradation and supervised learning for high-fidelity isotropic recovery, our method can effectively suppress the hallucination with substantially enhanced image quality compared to previously reported methods. In the experiments, we show that Self-Net can reconstruct high-fidelity isotropic 3D images from organelle to tissue levels via raw images from various microscopy platforms, e.g., wide-field, laser-scanning, or super-resolution microscopy. For the first time, Self-Net enables isotropic whole-brain imaging at a voxel resolution of 0.2 × 0.2 × 0.2 μm3, which addresses the last-mile problem of data quality in single-neuron morphology visualization and reconstruction with minimal effort and cost. Overall, Self-Net is a promising approach to overcoming the inherent resolution anisotropy for all classes of 3D fluorescence microscopy.
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Affiliation(s)
- Kefu Ning
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
- HUST-Suzhou Institute for Brainsmatics, Suzhou, China
| | - Bolin Lu
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
- HUST-Suzhou Institute for Brainsmatics, Suzhou, China
| | - Xiaojun Wang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
- School of Biomedical Engineering, Hainan University, Haikou, China
| | - Xiaoyu Zhang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Shuo Nie
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Tao Jiang
- HUST-Suzhou Institute for Brainsmatics, Suzhou, China
| | - Anan Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
- HUST-Suzhou Institute for Brainsmatics, Suzhou, China
| | - Guoqing Fan
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaofeng Wang
- HUST-Suzhou Institute for Brainsmatics, Suzhou, China
| | - Qingming Luo
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
- HUST-Suzhou Institute for Brainsmatics, Suzhou, China
- School of Biomedical Engineering, Hainan University, Haikou, China
| | - Hui Gong
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China.
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China.
- HUST-Suzhou Institute for Brainsmatics, Suzhou, China.
| | - Jing Yuan
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China.
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China.
- HUST-Suzhou Institute for Brainsmatics, Suzhou, China.
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3
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Tian J, Chen Y, Jiang T, Jia X, Gong H, Li X. Low-temperature resin embedding of the whole brain for various precise structures dissection. iScience 2023; 26:106705. [PMID: 37216109 PMCID: PMC10192521 DOI: 10.1016/j.isci.2023.106705] [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: 12/23/2022] [Revised: 03/03/2023] [Accepted: 04/17/2023] [Indexed: 05/24/2023] Open
Abstract
Resin embedding combined with ultra-thin sectioning has been widely used in microscopic and electron imaging to acquire precise structural information of biological tissues. However, the existing embedding method was detrimental to quenchable fluorescent signals of precise structures and pH-insensitive fluorescent dyes. Here, we developed a low-temperature chemical polymerization method named HM20-T to maintain weak signals of various precise structures and to decrease background fluorescence. The fluorescence preservation ratio of green fluorescent protein (GFP) tagged presynaptic elements and tdTomato labeled axons doubled. The HM20-T method was suitable for a variety of fluorescent dyes, such as DyLight 488 conjugated Lycopersicon esculentum lectin. Moreover, the brains also retained immunoreactivity after embedding. In summary, the HM20-T method was suitable for the characterization of multi-color labeled precise structures, which would contribute to the acquisition of complete morphology of various biological tissues and to the investigation of composition and circuit connection in the whole brain.
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Affiliation(s)
- Jiaojiao Tian
- Britton Chance Center and MoE Key Laboratory for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China
- Department of Clinical Laboratory, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan, China
| | - Yingying Chen
- Britton Chance Center and MoE Key Laboratory for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Tao Jiang
- Research Unit of Multimodal Cross Scale Neural Signal Detection and Imaging, Chinese Academy of Medical Sciences, HUST-Suzhou Institute for Brainmatics, JITRI, Suzhou 215125, China
| | - Xueyan Jia
- Research Unit of Multimodal Cross Scale Neural Signal Detection and Imaging, Chinese Academy of Medical Sciences, HUST-Suzhou Institute for Brainmatics, JITRI, Suzhou 215125, China
| | - Hui Gong
- Britton Chance Center and MoE Key Laboratory for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and Imaging, Chinese Academy of Medical Sciences, HUST-Suzhou Institute for Brainmatics, JITRI, Suzhou 215125, China
| | - Xiangning Li
- Britton Chance Center and MoE Key Laboratory for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou 570228, China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and Imaging, Chinese Academy of Medical Sciences, HUST-Suzhou Institute for Brainmatics, JITRI, Suzhou 215125, China
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4
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Dissection of the long-range projections of specific neurons at the synaptic level in the whole mouse brain. Proc Natl Acad Sci U S A 2022; 119:e2202536119. [PMID: 36161898 PMCID: PMC9546530 DOI: 10.1073/pnas.2202536119] [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] [Indexed: 11/18/2022] Open
Abstract
Through synaptic connections, long-range circuits transmit information among neurons and connect different brain regions to form functional motifs and execute specific functions. Tracing the synaptic distribution of specific neurons requires submicron-level resolution information. However, it is a great challenge to map the synaptic terminals completely because these fine structures span multiple regions, even in the whole brain. Here, we develop a pipeline including viral tracing, sample embedding, fluorescent micro-optical sectional tomography, and big data processing. We mapped the whole-brain distribution and architecture of long projections of the parvalbumin neurons in the basal forebrain at the synaptic level. These neurons send massive projections to multiple downstream regions with subregional preference. With three-dimensional reconstruction in the targeted areas, we found that synaptic degeneration was inconsistent with the accumulation of amyloid-β plaques but was preferred in memory-related circuits, such as hippocampal formation and thalamus, but not in most hypothalamic nuclei in 8-month-old mice with five familial Alzheimer's disease mutations. Our pipeline provides a platform for generating a whole-brain atlas of cell-type-specific synaptic terminals in the physiological and pathological brain, which can provide an important resource for the study of the organizational logic of specific neural circuits and the circuitry changes in pathological conditions.
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5
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Arias A, Manubens-Gil L, Dierssen M. Fluorescent transgenic mouse models for whole-brain imaging in health and disease. Front Mol Neurosci 2022; 15:958222. [PMID: 36211979 PMCID: PMC9538927 DOI: 10.3389/fnmol.2022.958222] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 08/08/2022] [Indexed: 11/25/2022] Open
Abstract
A paradigm shift is occurring in neuroscience and in general in life sciences converting biomedical research from a descriptive discipline into a quantitative, predictive, actionable science. Living systems are becoming amenable to quantitative description, with profound consequences for our ability to predict biological phenomena. New experimental tools such as tissue clearing, whole-brain imaging, and genetic engineering technologies have opened the opportunity to embrace this new paradigm, allowing to extract anatomical features such as cell number, their full morphology, and even their structural connectivity. These tools will also allow the exploration of new features such as their geometrical arrangement, within and across brain regions. This would be especially important to better characterize brain function and pathological alterations in neurological, neurodevelopmental, and neurodegenerative disorders. New animal models for mapping fluorescent protein-expressing neurons and axon pathways in adult mice are key to this aim. As a result of both developments, relevant cell populations with endogenous fluorescence signals can be comprehensively and quantitatively mapped to whole-brain images acquired at submicron resolution. However, they present intrinsic limitations: weak fluorescent signals, unequal signal strength across the same cell type, lack of specificity of fluorescent labels, overlapping signals in cell types with dense labeling, or undetectable signal at distal parts of the neurons, among others. In this review, we discuss the recent advances in the development of fluorescent transgenic mouse models that overcome to some extent the technical and conceptual limitations and tradeoffs between different strategies. We also discuss the potential use of these strains for understanding disease.
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Affiliation(s)
- Adrian Arias
- Department of System Biology, Centre for Genomic Regulation, The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Linus Manubens-Gil
- Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Mara Dierssen
- Department of System Biology, Centre for Genomic Regulation, The Barcelona Institute of Science and Technology, Barcelona, Spain
- Department of Experimental and Health Sciences, University Pompeu Fabra, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Barcelona, Spain
- *Correspondence: Mara Dierssen,
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6
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Zhang H, Wang X, Guo W, Li A, Chen R, Huang F, Liu X, Chen Y, Li N, Liu X, Xu T, Xue Z, Zeng S. Cross-Streams Through the Ventral Posteromedial Thalamic Nucleus to Convey Vibrissal Information. Front Neuroanat 2021; 15:724861. [PMID: 34776879 PMCID: PMC8582278 DOI: 10.3389/fnana.2021.724861] [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: 06/14/2021] [Accepted: 09/17/2021] [Indexed: 11/13/2022] Open
Abstract
Whisker detection is crucial to adapt to the environment for some animals, but how the nervous system processes and integrates whisker information is still an open question. It is well-known that two main parallel pathways through Ventral posteromedial thalamic nucleus (VPM) ascend to the barrel cortex, and classical theory suggests that the cross-talk from trigeminal nucleus interpolaris (Sp5i) to principal nucleus (Pr5) between the main parallel pathways contributes to the multi-whisker integration in barrel columns. Moreover, some studies suggest there are other cross-streams between the parallel pathways. To confirm their existence, in this study we used a dual-viral labeling strategy and high-resolution, large-volume light imaging to get the complete morphology of individual VPM neurons and trace their projections. We found some new thalamocortical projections from the ventral lateral part of VPM (VPMvl) to barrel columns. In addition, the retrograde-viral labeling and imaging results showed there were the large trigeminothalamic projections from Sp5i to the dorsomedial section of VPM (VPMdm). Our results reveal new cross-streams between the parallel pathways through VPM, which may involve the execution of multi-whisker integration in barrel columns.
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Affiliation(s)
- Huimin Zhang
- Collaborative Innovation Center for Biomedical Engineering, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China.,Britton Chance Center and MOE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaojun Wang
- Collaborative Innovation Center for Biomedical Engineering, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China.,Britton Chance Center and MOE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Wenyan Guo
- Collaborative Innovation Center for Biomedical Engineering, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China.,Britton Chance Center and MOE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Anan Li
- Collaborative Innovation Center for Biomedical Engineering, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China.,Britton Chance Center and MOE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Ruixi Chen
- Collaborative Innovation Center for Biomedical Engineering, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China.,Britton Chance Center and MOE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Fei Huang
- Collaborative Innovation Center for Biomedical Engineering, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China.,Britton Chance Center and MOE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaoxiang Liu
- Collaborative Innovation Center for Biomedical Engineering, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China.,Britton Chance Center and MOE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Yijun Chen
- Collaborative Innovation Center for Biomedical Engineering, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China.,Britton Chance Center and MOE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Ning Li
- Collaborative Innovation Center for Biomedical Engineering, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China.,Britton Chance Center and MOE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Xiuli Liu
- Collaborative Innovation Center for Biomedical Engineering, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China.,Britton Chance Center and MOE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Tonghui Xu
- Department of Laboratory Animal Science, Fudan University, Shanghai, China
| | - Zheng Xue
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shaoqun Zeng
- Collaborative Innovation Center for Biomedical Engineering, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China.,Britton Chance Center and MOE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
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7
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Ren M, Tian J, Sun Q, Chen S, Luo T, Jia X, Jiang T, Luo Q, Gong H, Li X. Plastic embedding for precise imaging of large-scale biological tissues labeled with multiple fluorescent dyes and proteins. BIOMEDICAL OPTICS EXPRESS 2021; 12:6730-6745. [PMID: 34858677 PMCID: PMC8606158 DOI: 10.1364/boe.435120] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 09/03/2021] [Accepted: 09/15/2021] [Indexed: 06/13/2023]
Abstract
Resin embedding of multi-color labeled whole organs is the primary step to preserve structural information for visualization of fine structures in three dimensions. It is essential to study the morphological characteristics, spatial and positional relationships of the millions of neurons, and the intricate network of blood vessels with fluorescent labels in the brain. However, the current resin embedding method is inadequate because of incompatibilities with fluorescent dyes, making it difficult to reconstruct a variety of structures for the interpretation of their complex spatial relationships. We modified the resin embedding method for large biological tissues labeled with multiple fluorescent dyes and proteins through different labeling strategies. With TrueBlack as the background fluorescence inhibitor in the glycol methacrylate (GMA) embedding, we referred to the method as GMA-T (Glycol methacrylate with TB). In the GMA-T embedded mouse brains, structures labeled with fluorescent proteins and dyes were visualized in millimeter-scale networks with sub-cellular resolution, allowing quantitative analysis of different anatomical structures in the same brain, including neurons and blood vessels. In combination with high-resolution whole-brain imaging, it is possible to obtain a variety of fluorescence labeled structures in just a few days. We quantified the distribution and morphology of the tdTomato-labeled vasoactive intestinal polypeptide (VIP) neurons and the BSA-FITC labeled blood vessels in the same brain. These results demonstrated that VIP neurons and blood vessels have their own unique distribution patterns and morphological characteristics among cortical regions and different layers in cerebral cortex, and there was no significant correlation between VIP neurons and vessels. This approach provides a novel approach to study the interaction among different anatomical structures within large-volume biological samples labeled with multiple fluorescent dyes and proteins, which helps elucidating the complex anatomical characteristics of biological organs.
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Affiliation(s)
- Miao Ren
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou 570228, China
- These authors contributed equally to this paper
| | - Jiaojiao Tian
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China
- These authors contributed equally to this paper
| | - Qingtao Sun
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Siqi Chen
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Ting Luo
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Xueyan Jia
- HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou 215125, China
| | - Tao Jiang
- HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou 215125, China
| | - Qingming Luo
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou 570228, China
| | - Hui Gong
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China
- HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou 215125, China
| | - Xiangning Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China
- HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou 215125, China
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8
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Muñoz-Castañeda R, Zingg B, Matho KS, Chen X, Wang Q, Foster NN, Li A, Narasimhan A, Hirokawa KE, Huo B, Bannerjee S, Korobkova L, Park CS, Park YG, Bienkowski MS, Chon U, Wheeler DW, Li X, Wang Y, Naeemi M, Xie P, Liu L, Kelly K, An X, Attili SM, Bowman I, Bludova A, Cetin A, Ding L, Drewes R, D'Orazi F, Elowsky C, Fischer S, Galbavy W, Gao L, Gillis J, Groblewski PA, Gou L, Hahn JD, Hatfield JT, Hintiryan H, Huang JJ, Kondo H, Kuang X, Lesnar P, Li X, Li Y, Lin M, Lo D, Mizrachi J, Mok S, Nicovich PR, Palaniswamy R, Palmer J, Qi X, Shen E, Sun YC, Tao HW, Wakemen W, Wang Y, Yao S, Yuan J, Zhan H, Zhu M, Ng L, Zhang LI, Lim BK, Hawrylycz M, Gong H, Gee JC, Kim Y, Chung K, Yang XW, Peng H, Luo Q, Mitra PP, Zador AM, Zeng H, Ascoli GA, Josh Huang Z, Osten P, Harris JA, Dong HW. Cellular anatomy of the mouse primary motor cortex. Nature 2021; 598:159-166. [PMID: 34616071 PMCID: PMC8494646 DOI: 10.1038/s41586-021-03970-w] [Citation(s) in RCA: 94] [Impact Index Per Article: 31.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Accepted: 08/27/2021] [Indexed: 12/24/2022]
Abstract
An essential step toward understanding brain function is to establish a structural framework with cellular resolution on which multi-scale datasets spanning molecules, cells, circuits and systems can be integrated and interpreted1. Here, as part of the collaborative Brain Initiative Cell Census Network (BICCN), we derive a comprehensive cell type-based anatomical description of one exemplar brain structure, the mouse primary motor cortex, upper limb area (MOp-ul). Using genetic and viral labelling, barcoded anatomy resolved by sequencing, single-neuron reconstruction, whole-brain imaging and cloud-based neuroinformatics tools, we delineated the MOp-ul in 3D and refined its sublaminar organization. We defined around two dozen projection neuron types in the MOp-ul and derived an input-output wiring diagram, which will facilitate future analyses of motor control circuitry across molecular, cellular and system levels. This work provides a roadmap towards a comprehensive cellular-resolution description of mammalian brain architecture.
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Affiliation(s)
| | - Brian Zingg
- UCLA Brain Research and Artificial Intelligence Nexus, Department of Neurobiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- USC Stevens Neuroimaging and Informatics Institute (INI), Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | | | - Xiaoyin Chen
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Quanxin Wang
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Nicholas N Foster
- UCLA Brain Research and Artificial Intelligence Nexus, Department of Neurobiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- USC Stevens Neuroimaging and Informatics Institute (INI), Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | - Anan Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, China
- HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou, China
| | | | - Karla E Hirokawa
- Allen Institute for Brain Science, Seattle, WA, USA
- Cajal Neuroscience, Seattle, WA, USA
| | - Bingxing Huo
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | | | - Laura Korobkova
- USC Stevens Neuroimaging and Informatics Institute (INI), Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | - Chris Sin Park
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Young-Gyun Park
- Institute for Medical Engineering and Science, Department of Chemical Engineering, Picower Institute for Learning and Memory, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA
| | - Michael S Bienkowski
- USC Stevens Neuroimaging and Informatics Institute (INI), Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
- Department of Physiology and Neuroscience, Zilkha Neurogenetic Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, California, USA
| | - Uree Chon
- Department of Neural and Behavioral Sciences, College of Medicine, Penn State University, Hershey, PA, USA
| | - Diek W Wheeler
- Center for Neural Informatics, Structures and Plasticity, Bioengineering Department and Krasnow Institute for Advanced Study, George Mason University, Fairfax, VA, USA
| | - Xiangning Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, China
- HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou, China
| | - Yun Wang
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Peng Xie
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Lijuan Liu
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Kathleen Kelly
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Xu An
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
- Department of Neurobiology, Duke University School of Medicine, Durham, NC, USA
| | - Sarojini M Attili
- Center for Neural Informatics, Structures and Plasticity, Bioengineering Department and Krasnow Institute for Advanced Study, George Mason University, Fairfax, VA, USA
| | - Ian Bowman
- UCLA Brain Research and Artificial Intelligence Nexus, Department of Neurobiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- USC Stevens Neuroimaging and Informatics Institute (INI), Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | | | - Ali Cetin
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Liya Ding
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Rhonda Drewes
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | | | - Corey Elowsky
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | | | | | - Lei Gao
- UCLA Brain Research and Artificial Intelligence Nexus, Department of Neurobiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- USC Stevens Neuroimaging and Informatics Institute (INI), Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | - Jesse Gillis
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | | | - Lin Gou
- UCLA Brain Research and Artificial Intelligence Nexus, Department of Neurobiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- USC Stevens Neuroimaging and Informatics Institute (INI), Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | - Joel D Hahn
- Department of Biological Sciences, University of Southern California, Los Angeles, CA, USA
| | - Joshua T Hatfield
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
- Department of Neurobiology, Duke University School of Medicine, Durham, NC, USA
| | - Houri Hintiryan
- UCLA Brain Research and Artificial Intelligence Nexus, Department of Neurobiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- USC Stevens Neuroimaging and Informatics Institute (INI), Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | - Junxiang Jason Huang
- Center for Neural Circuits and Sensory Processing Disorders, Zilkha Neurogenetics Institute (ZNI), Department of Physiology and Neuroscience, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Hideki Kondo
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Xiuli Kuang
- School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, China
| | | | - Xu Li
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Yaoyao Li
- School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, China
| | - Mengkuan Lin
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Darrick Lo
- UCLA Brain Research and Artificial Intelligence Nexus, Department of Neurobiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- USC Stevens Neuroimaging and Informatics Institute (INI), Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | | | | | - Philip R Nicovich
- Allen Institute for Brain Science, Seattle, WA, USA
- Cajal Neuroscience, Seattle, WA, USA
| | | | - Jason Palmer
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Xiaoli Qi
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Elise Shen
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Yu-Chi Sun
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Huizhong W Tao
- Center for Neural Circuits and Sensory Processing Disorders, Zilkha Neurogenetics Institute (ZNI), Department of Physiology and Neuroscience, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | | | - Yimin Wang
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
- School of Computer Engineering and Science, Shanghai University, Shanghai, China
| | - Shenqin Yao
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Jing Yuan
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, China
- HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou, China
| | - Huiqing Zhan
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Muye Zhu
- UCLA Brain Research and Artificial Intelligence Nexus, Department of Neurobiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- USC Stevens Neuroimaging and Informatics Institute (INI), Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | - Lydia Ng
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Li I Zhang
- Center for Neural Circuits and Sensory Processing Disorders, Zilkha Neurogenetics Institute (ZNI), Department of Physiology and Neuroscience, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Byung Kook Lim
- HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou, China
- Division of Biological Science, Neurobiology section, University of California San Diego, San Diego, CA, USA
| | | | - Hui Gong
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, China
- HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou, China
| | - James C Gee
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Yongsoo Kim
- Department of Neural and Behavioral Sciences, College of Medicine, Penn State University, Hershey, PA, USA
| | - Kwanghun Chung
- Institute for Medical Engineering and Science, Department of Chemical Engineering, Picower Institute for Learning and Memory, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA
| | - X William Yang
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Hanchuan Peng
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Qingming Luo
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, China
- HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou, China
| | - Partha P Mitra
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | | | - Hongkui Zeng
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Giorgio A Ascoli
- Center for Neural Informatics, Structures and Plasticity, Bioengineering Department and Krasnow Institute for Advanced Study, George Mason University, Fairfax, VA, USA.
| | - Z Josh Huang
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA.
- Department of Neurobiology, Duke University School of Medicine, Durham, NC, USA.
| | - Pavel Osten
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA.
| | - Julie A Harris
- Allen Institute for Brain Science, Seattle, WA, USA.
- Cajal Neuroscience, Seattle, WA, USA.
| | - Hong-Wei Dong
- UCLA Brain Research and Artificial Intelligence Nexus, Department of Neurobiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
- USC Stevens Neuroimaging and Informatics Institute (INI), Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA.
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9
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Peng H, Xie P, Liu L, Kuang X, Wang Y, Qu L, Gong H, Jiang S, Li A, Ruan Z, Ding L, Yao Z, Chen C, Chen M, Daigle TL, Dalley R, Ding Z, Duan Y, Feiner A, He P, Hill C, Hirokawa KE, Hong G, Huang L, Kebede S, Kuo HC, Larsen R, Lesnar P, Li L, Li Q, Li X, Li Y, Li Y, Liu A, Lu D, Mok S, Ng L, Nguyen TN, Ouyang Q, Pan J, Shen E, Song Y, Sunkin SM, Tasic B, Veldman MB, Wakeman W, Wan W, Wang P, Wang Q, Wang T, Wang Y, Xiong F, Xiong W, Xu W, Ye M, Yin L, Yu Y, Yuan J, Yuan J, Yun Z, Zeng S, Zhang S, Zhao S, Zhao Z, Zhou Z, Huang ZJ, Esposito L, Hawrylycz MJ, Sorensen SA, Yang XW, Zheng Y, Gu Z, Xie W, Koch C, Luo Q, Harris JA, Wang Y, Zeng H. Morphological diversity of single neurons in molecularly defined cell types. Nature 2021; 598:174-181. [PMID: 34616072 PMCID: PMC8494643 DOI: 10.1038/s41586-021-03941-1] [Citation(s) in RCA: 144] [Impact Index Per Article: 48.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2020] [Accepted: 08/24/2021] [Indexed: 12/23/2022]
Abstract
Dendritic and axonal morphology reflects the input and output of neurons and is a defining feature of neuronal types1,2, yet our knowledge of its diversity remains limited. Here, to systematically examine complete single-neuron morphologies on a brain-wide scale, we established a pipeline encompassing sparse labelling, whole-brain imaging, reconstruction, registration and analysis. We fully reconstructed 1,741 neurons from cortex, claustrum, thalamus, striatum and other brain regions in mice. We identified 11 major projection neuron types with distinct morphological features and corresponding transcriptomic identities. Extensive projectional diversity was found within each of these major types, on the basis of which some types were clustered into more refined subtypes. This diversity follows a set of generalizable principles that govern long-range axonal projections at different levels, including molecular correspondence, divergent or convergent projection, axon termination pattern, regional specificity, topography, and individual cell variability. Although clear concordance with transcriptomic profiles is evident at the level of major projection type, fine-grained morphological diversity often does not readily correlate with transcriptomic subtypes derived from unsupervised clustering, highlighting the need for single-cell cross-modality studies. Overall, our study demonstrates the crucial need for quantitative description of complete single-cell anatomy in cell-type classification, as single-cell morphological diversity reveals a plethora of ways in which different cell types and their individual members may contribute to the configuration and function of their respective circuits.
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Affiliation(s)
- Hanchuan Peng
- Allen Institute for Brain Science, Seattle, WA, USA.
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China.
| | - Peng Xie
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Lijuan Liu
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
- Ministry of Education Key Laboratory of Developmental Genes and Human Disease, School of Life Science and Technology, Southeast University, Nanjing, China
| | - Xiuli Kuang
- School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, China
| | - Yimin Wang
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
- School of Computer Engineering and Science, Shanghai University, Shanghai, China
| | - Lei Qu
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
- Key Laboratory of Intelligent Computation and Signal Processing, Ministry of Education, Anhui University, Hefei, China
| | - Hui Gong
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, China
- HUST-Suzhou Institute for Brainsmatics, JITRI Institute for Brainsmatics, Suzhou, China
| | - Shengdian Jiang
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Anan Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, China
- HUST-Suzhou Institute for Brainsmatics, JITRI Institute for Brainsmatics, Suzhou, China
| | - Zongcai Ruan
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Liya Ding
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Zizhen Yao
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Chao Chen
- School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, China
| | - Mengya Chen
- School of Computer Engineering and Science, Shanghai University, Shanghai, China
| | | | | | - Zhangcan Ding
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Yanjun Duan
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Aaron Feiner
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Ping He
- School of Computer Engineering and Science, Shanghai University, Shanghai, China
| | - Chris Hill
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Karla E Hirokawa
- Allen Institute for Brain Science, Seattle, WA, USA
- Cajal Neuroscience, Seattle, WA, USA
| | - Guodong Hong
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
- Ministry of Education Key Laboratory of Developmental Genes and Human Disease, School of Life Science and Technology, Southeast University, Nanjing, China
| | - Lei Huang
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Sara Kebede
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | - Phil Lesnar
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Longfei Li
- Key Laboratory of Intelligent Computation and Signal Processing, Ministry of Education, Anhui University, Hefei, China
| | - Qi Li
- School of Computer Engineering and Science, Shanghai University, Shanghai, China
| | - Xiangning Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, China
- HUST-Suzhou Institute for Brainsmatics, JITRI Institute for Brainsmatics, Suzhou, China
| | - Yaoyao Li
- School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, China
| | - Yuanyuan Li
- Key Laboratory of Intelligent Computation and Signal Processing, Ministry of Education, Anhui University, Hefei, China
| | - An Liu
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
- Ministry of Education Key Laboratory of Developmental Genes and Human Disease, School of Life Science and Technology, Southeast University, Nanjing, China
| | | | | | - Lydia Ng
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Thuc Nghi Nguyen
- Allen Institute for Brain Science, Seattle, WA, USA
- Cajal Neuroscience, Seattle, WA, USA
| | - Qiang Ouyang
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Jintao Pan
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Elise Shen
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Yuanyuan Song
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | | | | | - Matthew B Veldman
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | | | - Wan Wan
- Key Laboratory of Intelligent Computation and Signal Processing, Ministry of Education, Anhui University, Hefei, China
| | - Peng Wang
- School of Computer Engineering and Science, Shanghai University, Shanghai, China
| | - Quanxin Wang
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Tao Wang
- Key Laboratory of Intelligent Computation and Signal Processing, Ministry of Education, Anhui University, Hefei, China
| | - Yaping Wang
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Feng Xiong
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Wei Xiong
- School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, China
| | - Wenjie Xu
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Min Ye
- School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, China
| | - Lulu Yin
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Yang Yu
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Jia Yuan
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
- Ministry of Education Key Laboratory of Developmental Genes and Human Disease, School of Life Science and Technology, Southeast University, Nanjing, China
| | - Jing Yuan
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, China
- HUST-Suzhou Institute for Brainsmatics, JITRI Institute for Brainsmatics, Suzhou, China
| | - Zhixi Yun
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Shaoqun Zeng
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, China
| | - Shichen Zhang
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Sujun Zhao
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Zijun Zhao
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Zhi Zhou
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Z Josh Huang
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
- Department of Neurobiology, Duke University School of Medicine, Durham, NC, USA
| | | | | | | | - X William Yang
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | | | - Zhongze Gu
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Wei Xie
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
- Ministry of Education Key Laboratory of Developmental Genes and Human Disease, School of Life Science and Technology, Southeast University, Nanjing, China
| | | | - Qingming Luo
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, China
- School of Biomedical Engineering, Hainan University, Haikou, China
| | - Julie A Harris
- Allen Institute for Brain Science, Seattle, WA, USA
- Cajal Neuroscience, Seattle, WA, USA
| | - Yun Wang
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Hongkui Zeng
- Allen Institute for Brain Science, Seattle, WA, USA.
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10
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Wang J, Sun P, Lv X, Jin S, Li A, Kuang J, Li N, Gang Y, Guo R, Zeng S, Xu F, Zhang YH. Divergent Projection Patterns Revealed by Reconstruction of Individual Neurons in Orbitofrontal Cortex. Neurosci Bull 2021; 37:461-477. [PMID: 33373031 PMCID: PMC8055809 DOI: 10.1007/s12264-020-00616-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2020] [Accepted: 08/02/2020] [Indexed: 12/29/2022] Open
Abstract
The orbitofrontal cortex (OFC) is involved in diverse brain functions via its extensive projections to multiple target regions. There is a growing understanding of the overall outputs of the OFC at the population level, but reports of the projection patterns of individual OFC neurons across different cortical layers remain rare. Here, by combining neuronal sparse and bright labeling with a whole-brain florescence imaging system (fMOST), we obtained an uninterrupted three-dimensional whole-brain dataset and achieved the full morphological reconstruction of 25 OFC pyramidal neurons. We compared the whole-brain projection targets of these individual OFC neurons in different cortical layers as well as in the same cortical layer. We found cortical layer-dependent projections characterized by divergent patterns for information delivery. Our study not only provides a structural basis for understanding the principles of laminar organizations in the OFC, but also provides clues for future functional and behavioral studies on OFC pyramidal neurons.
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Affiliation(s)
- Junjun Wang
- 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, 430074, China
| | - Pei Sun
- 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, 430074, China
| | - Xiaohua Lv
- 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, 430074, China
| | - Sen Jin
- Centre for Brain Science, 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
| | - 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, 430074, China
| | - Jianxia Kuang
- 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, 430074, China
| | - Ning 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, 430074, China
| | - Yadong Gang
- 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, 430074, China
| | - Rui Guo
- 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, 430074, China
| | - Shaoqun Zeng
- 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, 430074, China
| | - Fuqiang Xu
- Centre for Brain Science, 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
| | - Yu-Hui 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, 430074, China.
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11
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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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12
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Liu Y, Zhang H, Chen R, Wu Y, Yang X, Liu X, Zeng S, Guo W. UnaG as a reporter in adeno-associated virus-mediated gene transfer for biomedical imaging. JOURNAL OF BIOPHOTONICS 2020; 13:e202000182. [PMID: 32894647 DOI: 10.1002/jbio.202000182] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Revised: 08/21/2020] [Accepted: 09/02/2020] [Indexed: 06/11/2023]
Abstract
Adeno-associated virus (AAV) is one of the most common gene transfer vectors, but it has a limited capacity. A smaller fluorescent protein is urgently needed since it is more suitable to act as a reporter in AAV. In this study, a bilirubin-dependent reporter smaller than EGFP, termed UnaG, was found to have the ability to label the neurons of a mouse brain as clearly as EGFP without the addition of exogenous bilirubin. We also found that UnaG's pH tolerance is better than that of EGFP; however, its fluorescence recovery after protonated quenching is not as good as that of EGFP. In addition, UnaG preserved its fluorescence better than EGFP in SeeDB clearing. Taken together, this study demonstrates that UnaG can act as a small intrinsically fluorescent reporter in the mouse brain without an additional ligand, thus providing an alternative over EGFP for AAV-mediated neuron labeling in mammals.
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Affiliation(s)
- Yurong Liu
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China
- MOE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Huimin Zhang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China
- MOE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Ruixi Chen
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China
- MOE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Ying Wu
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China
- MOE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Xiong Yang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China
- MOE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Xiuli Liu
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China
- MOE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Shaoqun Zeng
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China
- MOE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Wenyan Guo
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China
- MOE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
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13
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Anatomically revealed morphological patterns of pyramidal neurons in layer 5 of the motor cortex. Sci Rep 2020; 10:7916. [PMID: 32405029 PMCID: PMC7220918 DOI: 10.1038/s41598-020-64665-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2019] [Accepted: 04/17/2020] [Indexed: 11/24/2022] Open
Abstract
Neuronal cell types are essential to the comprehensive understanding of the neuronal function and neuron can be categorized by their anatomical property. However, complete morphology data for neurons with a whole brain projection, for example the pyramidal neurons in the cortex, are sparse because it is difficult to trace the neuronal fibers across the whole brain and acquire the neuron morphology at the single axon resolution. Thus the cell types of pyramidal neurons have yet to be studied at the single axon resolution thoroughly. In this work, we acquire images for a Thy1 H-line mouse brain using a fluorescence micro-optical sectioning tomography system. Then we sample 42 pyramidal neurons whose somata are in the layer 5 of the motor cortex and reconstruct their morphology across the whole brain. Based on the reconstructed neuronal anatomy, we analyze the axonal and dendritic fibers of the neurons in addition to the soma spatial distributions, and identify two axonal projection pattern of pyramidal tract neurons and two dendritic spreading patterns of intratelencephalic neurons. The raw image data are available upon request as an additional asset to the community. The morphological patterns identified in this work can be a typical representation of neuron subtypes and reveal the possible input-output function of a single pyramidal neuron.
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14
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RecV recombinase system for in vivo targeted optogenomic modifications of single cells or cell populations. Nat Methods 2020; 17:422-429. [PMID: 32203389 PMCID: PMC7135964 DOI: 10.1038/s41592-020-0774-3] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2018] [Accepted: 02/11/2020] [Indexed: 11/11/2022]
Abstract
Brain circuits comprise vast numbers of intricately interconnected neurons with diverse molecular, anatomical and physiological properties. To allow “user-defined” targeting of individual neurons for structural and functional studies, we created light-inducible site-specific DNA recombinases (SSRs) based on Cre, Dre and Flp (RecVs). RecVs can induce genomic modifications by one-photon or two-photon light induction in vivo. They can produce targeted, sparse and strong labeling of individual neurons by modifying multiple loci within mouse and zebrafish genomes. In combination with other genetic strategies, they allow intersectional targeting of different neuronal classes. In the mouse cortex they enable sparse labeling and whole-brain morphological reconstructions of individual neurons. Furthermore, these enzymes allow single-cell two-photon targeted genetic modifications and can be used in combination with functional optical indicators with minimal interference. In summary, RecVs enable spatiotemporally-precise optogenomic modifications that can facilitate detailed single-cell analysis of neural circuits by linking genetic identity, morphology, connectivity and function.
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15
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Zhang Y, Jiang S, Xu Z, Gong H, Li A, Luo Q, Ren M, Li X, Wu H, Yuan J, Chen S. Pinpointing Morphology and Projection of Excitatory Neurons in Mouse Visual Cortex. Front Neurosci 2019; 13:912. [PMID: 31555081 PMCID: PMC6727359 DOI: 10.3389/fnins.2019.00912] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2019] [Accepted: 08/16/2019] [Indexed: 01/10/2023] Open
Abstract
The excitatory neurons in the visual cortex are of great significance for us in understanding brain functions. However, the diverse neuron types and their morphological properties have not been fully deciphered. In this paper, we applied the brain-wide positioning system (BPS) to image the entire brain of two Thy1-eYFP H-line male mice at 0.2 μm × 0.2 μm × 1 μm voxel resolution. A total of 103 neurons were reconstructed in layers 5 and 6 of the visual cortex with single-axon-level resolution. Based on the complete topology of neurons and the inherent positioning function of the imaging method, we classified the observed neurons into six types according to their apical dendrites and somata location: star pyramidal cells in layer 5 (L5-sp), slender-tufted pyramidal cells in layer 5 (L5-st), tufted pyramidal cells in layer 5 (L5-tt), spiny stellate-like cells in layer 6 (L6-ss), star pyramidal cells in layer 6 (L6-sp), and slender-tufted pyramidal cells in layer 6 (L6-st). By examining the axonal projection patterns of individual neurons, they can be categorized into three modes: ipsilateral circuit connection neurons, callosal projection neurons and corticofugal projection neurons. Correlating the two types of classifications, we have found that there are at least two projection modes comprised in the former defined neuron types except for L5-tt. On the other hand, each projection mode may consist of four dendritic types defined in this study. The axon projection mode only partially correlates with the apical dendrite feature. This work has demonstrated a paradigm for resolving the visual cortex through single-neuron-level quantification and has shown potential to be extended to reveal the connectome of other defined sensory and motor systems.
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Affiliation(s)
- Yalun Zhang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Siqi Jiang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Zhengchao Xu
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Hui Gong
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Anan Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Qingming Luo
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Miao Ren
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Xiangning Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Hao Wu
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Jing Yuan
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Shangbin Chen
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
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16
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Cheng S, Wang X, Liu Y, Su L, Quan T, Li N, Yin F, Xiong F, Liu X, Luo Q, Gong H, Zeng S. DeepBouton: Automated Identification of Single-Neuron Axonal Boutons at the Brain-Wide Scale. Front Neuroinform 2019; 13:25. [PMID: 31105547 PMCID: PMC6492499 DOI: 10.3389/fninf.2019.00025] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2018] [Accepted: 03/22/2019] [Indexed: 12/30/2022] Open
Abstract
Fine morphological reconstruction of individual neurons across the entire brain is essential for mapping brain circuits. Inference of presynaptic axonal boutons, as a key part of single-neuron fine reconstruction, is critical for interpreting the patterns of neural circuit wiring schemes. However, automated bouton identification remains challenging for current neuron reconstruction tools, as they focus mainly on neurite skeleton drawing and have difficulties accurately quantifying bouton morphology. Here, we developed an automated method for recognizing single-neuron axonal boutons in whole-brain fluorescence microscopy datasets. The method is based on deep convolutional neural networks and density-peak clustering. High-dimensional feature representations of bouton morphology can be learned adaptively through convolutional networks and used for bouton recognition and subtype classification. We demonstrate that the approach is effective for detecting single-neuron boutons at the brain-wide scale for both long-range pyramidal projection neurons and local interneurons.
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Affiliation(s)
- Shenghua Cheng
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China.,MoE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaojun Wang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China.,MoE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Yurong Liu
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China.,MoE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Lei Su
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China.,MoE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Tingwei Quan
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China.,MoE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Ning Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China.,MoE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Fangfang Yin
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China.,MoE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Feng Xiong
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China.,MoE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaomao Liu
- School of Mathematics and Statistics, Huazhong University of Science and Technology, Wuhan, China
| | - Qingming Luo
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China.,MoE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Hui Gong
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China.,MoE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Shaoqun Zeng
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China.,MoE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
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17
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Wang X, Tucciarone J, Jiang S, Yin F, Wang BS, Wang D, Jia Y, Jia X, Li Y, Yang T, Xu Z, Akram MA, Wang Y, Zeng S, Ascoli GA, Mitra P, Gong H, Luo Q, Huang ZJ. Genetic Single Neuron Anatomy Reveals Fine Granularity of Cortical Axo-Axonic Cells. Cell Rep 2019; 26:3145-3159.e5. [PMID: 30865900 PMCID: PMC7863572 DOI: 10.1016/j.celrep.2019.02.040] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2018] [Revised: 11/19/2018] [Accepted: 02/08/2019] [Indexed: 10/27/2022] Open
Abstract
Parsing diverse nerve cells into biological types is necessary for understanding neural circuit organization. Morphology is an intuitive criterion for neuronal classification and a proxy of connectivity, but morphological diversity and variability often preclude resolving the granularity of neuron types. Combining genetic labeling with high-resolution, large-volume light microscopy, we established a single neuron anatomy platform that resolves, registers, and quantifies complete neuron morphologies in the mouse brain. We discovered that cortical axo-axonic cells (AACs), a cardinal GABAergic interneuron type that controls pyramidal neuron (PyN) spiking at axon initial segments, consist of multiple subtypes distinguished by highly laminar-specific soma position and dendritic and axonal arborization patterns. Whereas the laminar arrangements of AAC dendrites reflect differential recruitment by input streams, the laminar distribution and local geometry of AAC axons enable differential innervation of PyN ensembles. This platform will facilitate genetically targeted, high-resolution, and scalable single neuron anatomy in the mouse brain.
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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, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Jason Tucciarone
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA; Program in Neuroscience and Medical Scientist Training Program, Stony Brook University, Stony Brook, NY 11790, USA
| | - Siqi Jiang
- 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, Collaborative Innovation Center for Biomedical Engineering, 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, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Bor-Shuen Wang
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Dingkang Wang
- Computer Science and Engineering Department, The Ohio State University, Columbus, OH 43221, USA
| | - Yao Jia
- 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, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Xueyan Jia
- 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, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Yuxin 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, Collaborative Innovation Center for Biomedical Engineering, 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, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Zhengchao 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, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Masood A Akram
- Center for Neural Informatics, Structures, and Plasticity, Krasnow Institute for Advanced Study, George Mason University, Fairfax, VA, USA
| | - Yusu Wang
- Computer Science and Engineering Department, The Ohio State University, Columbus, OH 43221, USA
| | - 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, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Giorgio A Ascoli
- Center for Neural Informatics, Structures, and Plasticity, Krasnow Institute for Advanced Study, George Mason University, Fairfax, VA, USA
| | - Partha Mitra
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - 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, Collaborative Innovation Center for Biomedical Engineering, 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, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China.
| | - Z Josh Huang
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA.
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18
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Ren M, Tian J, Zhao P, Luo J, Feng Z, Gong H, Li X. Simultaneous Acquisition of Multicolor Information From Neural Circuits in Resin-Embedded Samples. Front Neurosci 2018; 12:885. [PMID: 30555296 PMCID: PMC6284031 DOI: 10.3389/fnins.2018.00885] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2018] [Accepted: 11/13/2018] [Indexed: 11/13/2022] Open
Abstract
Resin embedding has been widely used for precise imaging of fluorescently labeled biological samples with optical and electron microscopy. The low preservation rate of fluorescence, especially for red fluorescent proteins, has limited the application of resin embedding in multifluorescent protein-labeled samples. Here, we optimized the embedding method to retain the intensity of multiple fluorescent proteins during resin embedding. By reducing the polymerization temperature from 50 to 35°C and adding a fluorescent protein protection reagent during the embedding process, we successfully increased the fluorescence preservation rate by nearly twofold for red fluorescent proteins, including tdTomato, mCherry, and DsRed. Meanwhile, the background fluorescence decreased significantly in the optimized embedding method. This method is suitable not only for red fluorescent protein-labeled samples but also for blue (BFP) and green fluorescent protein (GFP)-labeled samples. We embedded brains labeled with BFP, DsRed, and GFP via AAV and rabies virus and acquired the distribution of input neurons to different cortical areas. With GFP/tdTomato double-labeled samples in resin, we obtained the cholinergic projectome of the pedunculopontine tegmental nucleus (PPTg) and the distribution of cholinergic neurons at single-neuron resolution in the whole brain simultaneously. Input cholinergic terminals from the PPTg were found to innervate the cholinergic soma and fiber in the neocortex, basal forebrain and brainstem, indicating that local cholinergic neurons received long-range cholinergic modulation from the midbrain. Our optimized method is useful for embedding multicolor fluorescent protein-labeled samples to acquire multidimensional structural information on neural circuits at single-neuron resolution in the whole brain.
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Affiliation(s)
- Miao Ren
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China.,MoE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Jiaojiao Tian
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China.,MoE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Peilin Zhao
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China.,MoE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Jialiang Luo
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China.,MoE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Zhao Feng
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
| | - Hui Gong
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China.,MoE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China.,HUST-Suzhou Institute for Brainsmatics, Suzhou, China
| | - Xiangning Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China.,MoE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China.,HUST-Suzhou Institute for Brainsmatics, Suzhou, China
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19
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Lin R, Wang R, Yuan J, Feng Q, Zhou Y, Zeng S, Ren M, Jiang S, Ni H, Zhou C, Gong H, Luo M. Cell-type-specific and projection-specific brain-wide reconstruction of single neurons. Nat Methods 2018; 15:1033-1036. [PMID: 30455464 DOI: 10.1038/s41592-018-0184-y] [Citation(s) in RCA: 74] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2018] [Accepted: 08/31/2018] [Indexed: 11/09/2022]
Abstract
We developed a dual-adeno-associated-virus expression system that enables strong and sparse labeling of individual neurons with cell-type and projection specificity. We demonstrated its utility for whole-brain reconstruction of midbrain dopamine neurons and striatum-projecting cortical neurons. We further extended the labeling method for rapid reconstruction in cleared thick brain sections and simultaneous dual-color labeling. This labeling system may facilitate the process of generating mesoscale single-neuron projectomes of mammalian brains.
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Affiliation(s)
- Rui Lin
- School of Life Sciences, Peking University, Beijing, China.,National Institute of Biological Sciences, Beijing, China
| | - Ruiyu Wang
- School of Life Sciences, Peking University, Beijing, China.,National Institute of Biological Sciences, Beijing, China
| | - Jing Yuan
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China.,MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China.,HUST-Suzhou Institute for Brainsmatics, JITRI Institute for Brainsmatics, Suzhou, China
| | - Qiru Feng
- National Institute of Biological Sciences, Beijing, China.,School of Life Sciences, Tsinghua University, Beijing, China
| | - Youtong Zhou
- National Institute of Biological Sciences, Beijing, China
| | - Shaoqun Zeng
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China.,MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Miao Ren
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China.,MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Siqi Jiang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China.,MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Hong Ni
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China.,MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Can Zhou
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China.,MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Hui Gong
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China. .,MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China. .,HUST-Suzhou Institute for Brainsmatics, JITRI Institute for Brainsmatics, Suzhou, China.
| | - Minmin Luo
- National Institute of Biological Sciences, Beijing, China. .,School of Life Sciences, Tsinghua University, Beijing, China. .,Chinese Institute for Brain Research, Beijing, China.
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20
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Li L, Chen R, Liu X, Li N, Liu X, Wang X, Quan T, Lv X, Zeng S. Penetration model for chemical reactivation for resin-embedded green fluorescent protein imaging. JOURNAL OF BIOMEDICAL OPTICS 2018; 24:1-6. [PMID: 30484293 PMCID: PMC6992894 DOI: 10.1117/1.jbo.24.5.051406] [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: 08/18/2018] [Accepted: 11/07/2018] [Indexed: 06/09/2023]
Abstract
In the so-called surface microscopy, serial block-face imaging is combined with mechanic sectioning to obtain volumetric imaging. While mapping a resin-embedded green fluorescent protein (GFP)-labeled specimen, it has been recently reported that an alkaline buffer is used to chemically reactivate the protonated GFP molecules, and thus improve the signal-to-noise ratio. In such a procedure, the image quality is highly affected by the penetration rate of a solution. We propose a reliable penetration model to describe the penetration process of the solution into the resin. The experimental results are consistent with the parameters predicted using this model. Thus, this model provides a valuable theoretical explanation and aids in optimizing the system parameters for mapping resin-embedded GFP biological samples.
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Affiliation(s)
- Longhui Li
- Huazhong University of Science and Technology, Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Wuhan, Hubei, China
- Huazhong University of Science and Technology, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, MoE Key Laboratory for Biomedical Photonics, Wuhan, Hubei, China
| | - Ruixi Chen
- Huazhong University of Science and Technology, Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Wuhan, Hubei, China
- Huazhong University of Science and Technology, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, MoE Key Laboratory for Biomedical Photonics, Wuhan, Hubei, China
| | - Xiuli Liu
- Huazhong University of Science and Technology, Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Wuhan, Hubei, China
- Huazhong University of Science and Technology, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, MoE Key Laboratory for Biomedical Photonics, Wuhan, Hubei, China
| | - Ning Li
- Huazhong University of Science and Technology, Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Wuhan, Hubei, China
- Huazhong University of Science and Technology, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, MoE Key Laboratory for Biomedical Photonics, Wuhan, Hubei, China
| | - Xiaoxiang Liu
- Huazhong University of Science and Technology, Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Wuhan, Hubei, China
- Huazhong University of Science and Technology, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, MoE Key Laboratory for Biomedical Photonics, Wuhan, Hubei, China
| | - Xiaojun Wang
- Huazhong University of Science and Technology, Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Wuhan, Hubei, China
- Huazhong University of Science and Technology, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, MoE Key Laboratory for Biomedical Photonics, Wuhan, Hubei, China
| | - Tingwei Quan
- Huazhong University of Science and Technology, Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Wuhan, Hubei, China
- Huazhong University of Science and Technology, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, MoE Key Laboratory for Biomedical Photonics, Wuhan, Hubei, China
| | - Xiaohua Lv
- Huazhong University of Science and Technology, Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Wuhan, Hubei, China
- Huazhong University of Science and Technology, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, MoE Key Laboratory for Biomedical Photonics, Wuhan, Hubei, China
| | - Shaoqun Zeng
- Huazhong University of Science and Technology, Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Wuhan, Hubei, China
- Huazhong University of Science and Technology, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, MoE Key Laboratory for Biomedical Photonics, Wuhan, Hubei, China
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21
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Lin HM, Kuang JX, Sun P, Li N, Lv X, Zhang YH. Reconstruction of Intratelencephalic Neurons in the Mouse Secondary Motor Cortex Reveals the Diverse Projection Patterns of Single Neurons. Front Neuroanat 2018; 12:86. [PMID: 30425624 PMCID: PMC6218457 DOI: 10.3389/fnana.2018.00086] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2018] [Accepted: 10/01/2018] [Indexed: 12/13/2022] Open
Abstract
The secondary motor cortex (MOs) plays crucial roles in cognitive and executive processes and has reciprocal connections with numerous cortices in rodents. However, descriptions of the neuronal morphologies and projection patterns of the MOs at the level of a single neuron are lacking, severely hindering the comprehensive understanding of the wiring diagram of the MOs. Herein, we used a Cre-dependent adeno-associated virus (AAV) to fluorescently label ~80 pyramidal neurons nearby or in the MOs and acquired an uninterrupted whole-brain 3D dataset at a voxel resolution of 0.2 × 0.2 × 1 μm with a whole-brain fluorescence imaging system (fMOST). Based on our 3D dataset, we reconstructed the complete morphologies of 36 individual intratelencephalic (IT) neurons nearby or in the MOs and analyzed the projection patterns and projection strengths of these neurons at a single-neuron level based on several parameters, including the projection areas, the total number of branches, the fiber length, and the total number of terminal tips. We obtained a neuron with an axonal length of 318.43 mm, which is by far the longest reported axonal length. Our results show that all individual neurons in the MOs, regardless of whether they are located in layer 2/3 or layer 5, display diverse projection patterns and projection strengths, implying that these neurons might be involved in different brain circuits at different intensities. The results lay a solid foundation for exploring the relationship between neuronal morphologies and behavioral functions of the MOs at the level of a single neuron.
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Affiliation(s)
- Hui-Min Lin
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong, University of Science and Technology, Wuhan, China.,MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Jian-Xia Kuang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong, University of Science and Technology, Wuhan, China.,MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Pei Sun
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong, University of Science and Technology, Wuhan, China.,MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Ning Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong, University of Science and Technology, Wuhan, China.,MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaohua Lv
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong, University of Science and Technology, Wuhan, China.,MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Yu-Hui Zhang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong, University of Science and Technology, Wuhan, China.,MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
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22
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Yang X, Zhang Q, Huang F, Bai K, Guo Y, Zhang Y, Li N, Cui Y, Sun P, Zeng S, Lv X. High-throughput light sheet tomography platform for automated fast imaging of whole mouse brain. JOURNAL OF BIOPHOTONICS 2018; 11:e201800047. [PMID: 29752773 DOI: 10.1002/jbio.201800047] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/09/2018] [Accepted: 05/11/2018] [Indexed: 05/24/2023]
Abstract
Acquiring information of the neural structures in the whole-brain level is vital for systematically exploring mechanisms and principles of brain function and dysfunction. Most methods for whole brain imaging, while capable of capturing the complete morphology of neurons, usually involve complex sample preparation and several days of image acquisition. The whole process including optical clearing or resin embedding is time consuming for a quick survey of the distribution of specific neural circuits in the whole brain. Here, we develop a high-throughput light-sheet tomography platform (HLTP), which requires minimum sample preparation. This method does not require optical clearing for block face light sheet imaging. After fixation using paraformaldehyde, an aligned 3 dimensional image dataset of a whole mouse brain can be obtained within 5 hours at a voxel size of 1.30 × 1.30 × 0.92 μm. HLTP could be a very efficient tool for quick exploration and visualization of brain-wide distribution of specific neurons or neural circuits.
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Affiliation(s)
- Xiong Yang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- MOE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Qi Zhang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- MOE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Fei Huang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- MOE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Ke Bai
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- MOE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Yiming Guo
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- MOE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Yongsheng Zhang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- MOE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Ning Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- MOE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Yuting Cui
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- MOE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Pei Sun
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- MOE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Shaoqun Zeng
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- MOE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaohua Lv
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- MOE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
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23
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Zhang Q, Yang X, Hu Q, Bai K, Yin F, Li N, Gang Y, Wang X, Zeng S. High axial resolution imaging system for large volume tissues using combination of inclined selective plane illumination and mechanical sectioning. BIOMEDICAL OPTICS EXPRESS 2017; 8:5767-5775. [PMID: 29296503 PMCID: PMC5745118 DOI: 10.1364/boe.8.005767] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/10/2017] [Revised: 09/06/2017] [Accepted: 09/22/2017] [Indexed: 05/31/2023]
Abstract
To resolve fine structures of biological systems like neurons, it is required to realize microscopic imaging with sufficient spatial resolution in three dimensional systems. With regular optical imaging systems, high lateral resolution is accessible while high axial resolution is hard to achieve in a large volume. We introduce an imaging system for high 3D resolution fluorescence imaging of large volume tissues. Selective plane illumination was adopted to provide high axial resolution. A scientific CMOS working in sub-array mode kept the imaging area in the sample surface, which restrained the adverse effect of aberrations caused by inclined illumination. Plastic embedding and precise mechanical sectioning extended the axial range and eliminated distortion during the whole imaging process. The combination of these techniques enabled 3D high resolution imaging of large tissues. Fluorescent bead imaging showed resolutions of 0.59 μm, 0.47μm, and 0.59 μm in the x, y, and z directions, respectively. Data acquired from the volume sample of brain tissue demonstrated the applicability of this imaging system. Imaging of different depths showed uniform performance where details could be recognized in either the near-soma area or terminal area, and fine structures of neurons could be seen in both the xy and xz sections.
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Affiliation(s)
- Qi Zhang
- Collaborative Innovation Center for Biomedical Engineering, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
- Britton Chance Center and MOE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Xiong Yang
- Collaborative Innovation Center for Biomedical Engineering, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
- Britton Chance Center and MOE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Qinglei Hu
- Collaborative Innovation Center for Biomedical Engineering, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
- Britton Chance Center and MOE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Ke Bai
- Collaborative Innovation Center for Biomedical Engineering, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
- Britton Chance Center and MOE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Fangfang Yin
- Collaborative Innovation Center for Biomedical Engineering, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
- Britton Chance Center and MOE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Ning Li
- Collaborative Innovation Center for Biomedical Engineering, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
- Britton Chance Center and MOE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Yadong Gang
- Collaborative Innovation Center for Biomedical Engineering, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
- Britton Chance Center and MOE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Xiaojun Wang
- Collaborative Innovation Center for Biomedical Engineering, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
- Britton Chance Center and MOE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Shaoqun Zeng
- Collaborative Innovation Center for Biomedical Engineering, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
- Britton Chance Center and MOE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
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24
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Zhou H, Xiong Y, Wang Y, Wang X, Li P, Gang Y, Liu X, Zeng S. High-refractive index of acrylate embedding resin clarifies mouse brain tissue. JOURNAL OF BIOMEDICAL OPTICS 2017; 22:1-4. [PMID: 29148271 DOI: 10.1117/1.jbo.22.11.110503] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/05/2017] [Accepted: 10/06/2017] [Indexed: 06/07/2023]
Abstract
Biological tissue transparency combined with light-sheet fluorescence microscopy is a useful method for studying the neural structure of biological tissues. The development of light-sheet fluorescence microscopy also promotes progress in biological tissue clearing methods. The current clarifying methods mostly use liquid reagent to denature protein or remove lipids first, to eliminate or reduce the scattering index or refractive index of the biological tissue. However, denaturing protein and removing lipids require complex procedures or an extended time period. Therefore, here we have developed acrylate resin with a high refractive index, which causes clearing of biological tissue directly after polymerization. This method can improve endogenous fluorescence retention by adjusting the pH value of the resin monomer.
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Affiliation(s)
- Hongfu Zhou
- Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Britton, China
- Huazhong University of Science and Technology, Ministry of Education Key Laboratory for Biomedical P, China
| | - Yumiao Xiong
- Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Britton, China
- Huazhong University of Science and Technology, Ministry of Education Key Laboratory for Biomedical P, China
| | - Yu Wang
- Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Britton, China
- Huazhong University of Science and Technology, Ministry of Education Key Laboratory for Biomedical P, China
| | - Xiaojun Wang
- Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Britton, China
- Huazhong University of Science and Technology, Ministry of Education Key Laboratory for Biomedical P, China
| | - Pei Li
- Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Britton, China
- Huazhong University of Science and Technology, Ministry of Education Key Laboratory for Biomedical P, China
| | - Yadong Gang
- Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Britton, China
- Huazhong University of Science and Technology, Ministry of Education Key Laboratory for Biomedical P, China
| | - Xiuli Liu
- Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Britton, China
- Huazhong University of Science and Technology, Ministry of Education Key Laboratory for Biomedical P, China
| | - Shaoqun Zeng
- Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Britton, China
- Huazhong University of Science and Technology, Ministry of Education Key Laboratory for Biomedical P, China
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25
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Zhou H, Gang Y, Chen S, Wang Y, Xiong Y, Li L, Yin F, Liu Y, Liu X, Zeng S. Development of a neutral embedding resin for optical imaging of fluorescently labeled biological tissue. JOURNAL OF BIOMEDICAL OPTICS 2017; 22:1-7. [PMID: 29076308 DOI: 10.1117/1.jbo.22.10.106015] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/05/2017] [Accepted: 10/02/2017] [Indexed: 06/07/2023]
Abstract
Plastic embedding is widely applied in light microscopy analyses. Previous studies have shown that embedding agents and related techniques can greatly affect the quality of biological tissue embedding and fluorescent imaging. Specifically, it is difficult to preserve endogenous fluorescence using currently available acidic commercial embedding resins and related embedding techniques directly. Here, we developed a neutral embedding resin that improved the green fluorescent protein (GFP), yellow fluorescent protein (YFP), and DsRed fluorescent intensity without adjusting the pH value of monomers or reactivating fluorescence in lye. The embedding resin had a high degree of polymerization, and its fluorescence preservation ratios for GFP, YFP, and DsRed were 126.5%, 155.8%, and 218.4%, respectively.
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Affiliation(s)
- Hongfu Zhou
- Huazhong University of Science and Technology, Collaborative Innovation Center for Biomedical Engine, China
- Huazhong University of Science and Technology, School of Engineering Sciences, Britton Chance Center, China
| | - Yadong Gang
- Huazhong University of Science and Technology, Collaborative Innovation Center for Biomedical Engine, China
- Huazhong University of Science and Technology, School of Engineering Sciences, Britton Chance Center, China
| | - Shenghua Chen
- Huazhong University of Science and Technology, Collaborative Innovation Center for Biomedical Engine, China
- Huazhong University of Science and Technology, School of Engineering Sciences, Britton Chance Center, China
| | - Yu Wang
- Huazhong University of Science and Technology, Collaborative Innovation Center for Biomedical Engine, China
- Huazhong University of Science and Technology, School of Engineering Sciences, Britton Chance Center, China
| | - Yumiao Xiong
- Huazhong University of Science and Technology, Collaborative Innovation Center for Biomedical Engine, China
- Huazhong University of Science and Technology, School of Engineering Sciences, Britton Chance Center, China
| | - Longhui Li
- Huazhong University of Science and Technology, Collaborative Innovation Center for Biomedical Engine, China
- Huazhong University of Science and Technology, School of Engineering Sciences, Britton Chance Center, China
| | - Fangfang Yin
- Huazhong University of Science and Technology, Collaborative Innovation Center for Biomedical Engine, China
- Huazhong University of Science and Technology, School of Engineering Sciences, Britton Chance Center, China
| | - Yue Liu
- Huazhong University of Science and Technology, Collaborative Innovation Center for Biomedical Engine, China
- Huazhong University of Science and Technology, School of Engineering Sciences, Britton Chance Center, China
| | - Xiuli Liu
- Huazhong University of Science and Technology, Collaborative Innovation Center for Biomedical Engine, China
- Huazhong University of Science and Technology, School of Engineering Sciences, Britton Chance Center, China
| | - Shaoqun Zeng
- Huazhong University of Science and Technology, Collaborative Innovation Center for Biomedical Engine, China
- Huazhong University of Science and Technology, School of Engineering Sciences, Britton Chance Center, China
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26
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Gang Y, Liu X, Wang X, Zhang Q, Zhou H, Chen R, Liu L, Jia Y, Yin F, Rao G, Chen J, Zeng S. Plastic embedding immunolabeled large-volume samples for three-dimensional high-resolution imaging. BIOMEDICAL OPTICS EXPRESS 2017; 8:3583-3596. [PMID: 28856037 PMCID: PMC5560827 DOI: 10.1364/boe.8.003583] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2017] [Revised: 06/28/2017] [Accepted: 06/28/2017] [Indexed: 05/31/2023]
Abstract
High-resolution three-dimensional biomolecule distribution information of large samples is essential to understanding their biological structure and function. Here, we proposed a method combining large sample resin embedding with iDISCO immunofluorescence staining to acquire the profile of biomolecules with high spatial resolution. We evaluated the compatibility of plastic embedding with an iDISCO staining technique and found that the fluorophores and the neuronal fine structures could be well preserved in the Lowicryl HM20 resin, and that numerous antibodies and fluorescent tracers worked well upon Lowicryl HM20 resin embedding. Further, using fluorescence Micro-Optical sectioning tomography (fMOST) technology combined with ultra-thin slicing and imaging, we were able to image the immunolabeled large-volume tissues with high resolution.
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Affiliation(s)
- Yadong Gang
- Britton Chance Center for Biomedical Photonics, School of Engineering Sciences, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan 430074, China
- MOE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, Hubei 430074, China
- These authors contributed equally to this work
| | - Xiuli Liu
- Britton Chance Center for Biomedical Photonics, School of Engineering Sciences, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan 430074, China
- MOE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, Hubei 430074, China
- These authors contributed equally to this work
| | - Xiaojun Wang
- Britton Chance Center for Biomedical Photonics, School of Engineering Sciences, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan 430074, China
- MOE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, Hubei 430074, China
| | - Qi Zhang
- Britton Chance Center for Biomedical Photonics, School of Engineering Sciences, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan 430074, China
- MOE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, Hubei 430074, China
| | - Hongfu Zhou
- Britton Chance Center for Biomedical Photonics, School of Engineering Sciences, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan 430074, China
- MOE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, Hubei 430074, China
| | - Ruixi Chen
- Britton Chance Center for Biomedical Photonics, School of Engineering Sciences, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan 430074, China
- MOE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, Hubei 430074, China
| | - Ling Liu
- Britton Chance Center for Biomedical Photonics, School of Engineering Sciences, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan 430074, China
- MOE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, Hubei 430074, China
| | - Yao Jia
- Britton Chance Center for Biomedical Photonics, School of Engineering Sciences, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan 430074, China
- MOE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, Hubei 430074, China
| | - Fangfang Yin
- Britton Chance Center for Biomedical Photonics, School of Engineering Sciences, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan 430074, China
- MOE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, Hubei 430074, China
| | - Gong Rao
- Britton Chance Center for Biomedical Photonics, School of Engineering Sciences, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan 430074, China
- MOE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, Hubei 430074, China
| | - Jiadong Chen
- Department of Cell Biology and Program in Molecular Cell Biology, Key Laboratory of Medical Neurobiology of the Ministry of Health of China
- Second Affiliated Hospital, School of Medicine, Zhejiang University, Zhejiang 310058, China
| | - Shaoqun Zeng
- Britton Chance Center for Biomedical Photonics, School of Engineering Sciences, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan 430074, China
- MOE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, Hubei 430074, China
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27
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Guo W, Liu X, Liu Y, Gang Y, He X, Jia Y, Yin F, Li P, Huang F, Zhou H, Wang X, Gong H, Luo Q, Xu F, Zeng S. Chemical reactivation of resin-embedded pHuji adds red for simultaneous two-color imaging with EGFP. BIOMEDICAL OPTICS EXPRESS 2017; 8:3281-3288. [PMID: 28717566 PMCID: PMC5508827 DOI: 10.1364/boe.8.003281] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2017] [Revised: 06/02/2017] [Accepted: 06/11/2017] [Indexed: 06/07/2023]
Abstract
The pH-sensitive fluorescent proteins enabling chemical reactivation in resin are useful tools for fluorescence microimaging. EGFP or EYFP is good for such applications. For simultaneous two-color imaging, a suitable red fluorescent protein is an urgent need. Here a pH-sensitive red fluorescent protein, pHuji, is selected and verified to remain pH-sensitive in HM20 resin. We observe 183% fluorescence intensity of pHuji in resin-embeded mouse brain and 29.08-fold fluorescence intensity of reactivated pHuji compared to the quenched state. pHuji and EGFP can be quenched and chemically reactivated simultaneously in resin, thus enabling simultaneous two-color micro-optical sectioning tomography of resin-embedded mouse brain. This method may greatly facilitate the visualization of neuronal morphology and neural circuits to promote understanding of the structure and function of the brain.
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Affiliation(s)
- Wenyan Guo
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China
- Department of Biomedical Engineering, Key Laboratory for Biomedical Photonics of Ministry of Education, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China
| | - Xiuli Liu
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China
- Department of Biomedical Engineering, Key Laboratory for Biomedical Photonics of Ministry of Education, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China
| | - Yurong Liu
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China
- Department of Biomedical Engineering, Key Laboratory for Biomedical Photonics of Ministry of Education, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China
| | - Yadong Gang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China
- Department of Biomedical Engineering, Key Laboratory for Biomedical Photonics of Ministry of Education, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China
| | - Xiaobin He
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Brain Research Center, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, West No.30 Xiao Hong Shan, Wuhan 430071, China
| | - Yao Jia
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China
- Department of Biomedical Engineering, Key Laboratory for Biomedical Photonics of Ministry of Education, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China
| | - Fangfang Yin
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China
- Department of Biomedical Engineering, Key Laboratory for Biomedical Photonics of Ministry of Education, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China
| | - Pei Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China
- Department of Biomedical Engineering, Key Laboratory for Biomedical Photonics of Ministry of Education, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China
| | - Fei Huang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China
- Department of Biomedical Engineering, Key Laboratory for Biomedical Photonics of Ministry of Education, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China
| | - Hongfu Zhou
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China
- Department of Biomedical Engineering, Key Laboratory for Biomedical Photonics of Ministry of Education, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China
| | - Xiaojun Wang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China
- Department of Biomedical Engineering, Key Laboratory for Biomedical Photonics of Ministry of Education, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China
| | - Hui Gong
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China
- Department of Biomedical Engineering, Key Laboratory for Biomedical Photonics of Ministry of Education, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China
| | - Qingming Luo
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China
- Department of Biomedical Engineering, Key Laboratory for Biomedical Photonics of Ministry of Education, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China
| | - Fuqiang Xu
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China
- Department of Biomedical Engineering, Key Laboratory for Biomedical Photonics of Ministry of Education, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Brain Research Center, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, West No.30 Xiao Hong Shan, Wuhan 430071, China
| | - Shaoqun Zeng
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China
- Department of Biomedical Engineering, Key Laboratory for Biomedical Photonics of Ministry of Education, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China
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