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A combinatorial method to visualize the neuronal network in the mouse spinal cord: combination of a modified Golgi-Cox method and synchrotron radiation micro-computed tomography

Exploring the three-dimensional (3D) morphology of neurons is essential to understanding spinal cord function and associated diseases comprehensively. However, 3D imaging of the neuronal network in the broad region of the spinal cord at cellular resolution remains a challenge in the field of neurosc...

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Autores principales: Jiang, Liyuan, Cao, Yong, Yin, Xianzhen, Ni, Shuangfei, Li, Miao, Li, Chengjun, Luo, Zixiang, Lu, Hongbin, Hu, Jianzhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8062354/
https://www.ncbi.nlm.nih.gov/pubmed/33398435
http://dx.doi.org/10.1007/s00418-020-01949-8
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author Jiang, Liyuan
Cao, Yong
Yin, Xianzhen
Ni, Shuangfei
Li, Miao
Li, Chengjun
Luo, Zixiang
Lu, Hongbin
Hu, Jianzhong
author_facet Jiang, Liyuan
Cao, Yong
Yin, Xianzhen
Ni, Shuangfei
Li, Miao
Li, Chengjun
Luo, Zixiang
Lu, Hongbin
Hu, Jianzhong
author_sort Jiang, Liyuan
collection PubMed
description Exploring the three-dimensional (3D) morphology of neurons is essential to understanding spinal cord function and associated diseases comprehensively. However, 3D imaging of the neuronal network in the broad region of the spinal cord at cellular resolution remains a challenge in the field of neuroscience. In this study, to obtain high-resolution 3D imaging of a detailed neuronal network in the mass of the spinal cord, the combination of synchrotron radiation micro-computed tomography (SRμCT) and the Golgi-cox staining were used. We optimized the Golgi-Cox method (GCM) and developed a modified GCM (M-GCM), which improved background staining, reduced the number of artefacts, and diminished the impact of incomplete vasculature compared to the current GCM. Moreover, we achieved high-resolution 3D imaging of the detailed neuronal network in the spinal cord through the combination of SRμCT and M-GCM. Our results showed that the M-GCM increased the contrast between the neuronal structure and its surrounding extracellular matrix. Compared to the GCM, the M-GCM also diminished the impact of the artefacts and incomplete vasculature on the 3D image. Additionally, the 3D neuronal architecture was successfully quantified using a combination of SRμCT and M-GCM. The SRμCT was shown to be a valuable non-destructive tool for 3D visualization of the neuronal network in the broad 3D region of the spinal cord. Such a combinatorial method will, therefore, transform the presentation of Golgi staining from 2 to 3D, providing significant improvements in the 3D rendering of the neuronal network. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00418-020-01949-8.
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spelling pubmed-80623542021-05-05 A combinatorial method to visualize the neuronal network in the mouse spinal cord: combination of a modified Golgi-Cox method and synchrotron radiation micro-computed tomography Jiang, Liyuan Cao, Yong Yin, Xianzhen Ni, Shuangfei Li, Miao Li, Chengjun Luo, Zixiang Lu, Hongbin Hu, Jianzhong Histochem Cell Biol Original Paper Exploring the three-dimensional (3D) morphology of neurons is essential to understanding spinal cord function and associated diseases comprehensively. However, 3D imaging of the neuronal network in the broad region of the spinal cord at cellular resolution remains a challenge in the field of neuroscience. In this study, to obtain high-resolution 3D imaging of a detailed neuronal network in the mass of the spinal cord, the combination of synchrotron radiation micro-computed tomography (SRμCT) and the Golgi-cox staining were used. We optimized the Golgi-Cox method (GCM) and developed a modified GCM (M-GCM), which improved background staining, reduced the number of artefacts, and diminished the impact of incomplete vasculature compared to the current GCM. Moreover, we achieved high-resolution 3D imaging of the detailed neuronal network in the spinal cord through the combination of SRμCT and M-GCM. Our results showed that the M-GCM increased the contrast between the neuronal structure and its surrounding extracellular matrix. Compared to the GCM, the M-GCM also diminished the impact of the artefacts and incomplete vasculature on the 3D image. Additionally, the 3D neuronal architecture was successfully quantified using a combination of SRμCT and M-GCM. The SRμCT was shown to be a valuable non-destructive tool for 3D visualization of the neuronal network in the broad 3D region of the spinal cord. Such a combinatorial method will, therefore, transform the presentation of Golgi staining from 2 to 3D, providing significant improvements in the 3D rendering of the neuronal network. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00418-020-01949-8. Springer Berlin Heidelberg 2021-01-04 2021 /pmc/articles/PMC8062354/ /pubmed/33398435 http://dx.doi.org/10.1007/s00418-020-01949-8 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Paper
Jiang, Liyuan
Cao, Yong
Yin, Xianzhen
Ni, Shuangfei
Li, Miao
Li, Chengjun
Luo, Zixiang
Lu, Hongbin
Hu, Jianzhong
A combinatorial method to visualize the neuronal network in the mouse spinal cord: combination of a modified Golgi-Cox method and synchrotron radiation micro-computed tomography
title A combinatorial method to visualize the neuronal network in the mouse spinal cord: combination of a modified Golgi-Cox method and synchrotron radiation micro-computed tomography
title_full A combinatorial method to visualize the neuronal network in the mouse spinal cord: combination of a modified Golgi-Cox method and synchrotron radiation micro-computed tomography
title_fullStr A combinatorial method to visualize the neuronal network in the mouse spinal cord: combination of a modified Golgi-Cox method and synchrotron radiation micro-computed tomography
title_full_unstemmed A combinatorial method to visualize the neuronal network in the mouse spinal cord: combination of a modified Golgi-Cox method and synchrotron radiation micro-computed tomography
title_short A combinatorial method to visualize the neuronal network in the mouse spinal cord: combination of a modified Golgi-Cox method and synchrotron radiation micro-computed tomography
title_sort combinatorial method to visualize the neuronal network in the mouse spinal cord: combination of a modified golgi-cox method and synchrotron radiation micro-computed tomography
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8062354/
https://www.ncbi.nlm.nih.gov/pubmed/33398435
http://dx.doi.org/10.1007/s00418-020-01949-8
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