中国神经再生研究(英文版) ›› 2022, Vol. 17 ›› Issue (1): 113-114.doi: 10.4103/1673-5374.314307

• 观点:脑损伤修复保护与再生 • 上一篇    下一篇

用连接组学分析视网膜的神经变性

  

  • 出版日期:2022-01-05 发布日期:2021-09-18

Analyzing neural degeneration of the retina with connectomics

Charles L. Zucker*, John E. Dowling*   

  1. Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, USA
  • Online:2022-01-05 Published:2021-09-18
  • Contact: Charles L. Zucker, PhD, czucker@fas.harvard.edu; John E. Dowling, PhD, dowling@mcb.harvard.edu.
  • Supported by:
    This work was supported in part by the Lowy Medical Research Institute (LMRI) to JED, a Macular Foundation grant to CLZ, NIH grant EY030255 to JED & CLZ. 

摘要: Neural Regen Res:用连接组学分析神经变性和再生  
最近,已经开发出了一些电子显微镜技术,使数千个相对较大的序列段能够被收集,并以全电子显微镜分辨率高效成像,然后将图像缝合在一起,以产生三维体积。在这样的体积内,可以识别和映射每个亚细胞结构或细胞连接,即连接组学。这些方法为揭示大量神经组织提供了一个全面的视角。随着自动化技术的日益使用,现在可以使用大规模的串行电子显微镜来产生分辨率为4 nm或更高的不同脑区的重建。在这个决议中,可以看到兴奋性和抑制性化学突触;电突触(间隙连接)的存在,神经调节肽和生物胺的存在,以及局部微电路的识别。与各种类型的胶质细胞的关系也很容易被发现,并且可以分辨与血管元件和非神经元/胶质细胞类型相关的细胞。细胞器的精细结构,包括线粒体、内质网、溶酶体和自噬体,以及细胞骨架元素,都在这些技术的分辨率范围内。因此,从亚细胞器结构到细胞水平,到广域组织视角的连续尺度可以同时被观察和分析。这些技术已用于绘制3D神经再生图,研究小脑的发育复接。最近的研究表明,MacTel的一个潜在原因是氨基酸丝氨酸的合成和代谢途径。由于Müller细胞合成了视网膜丝氨酸,我们提出线粒体维持所需的丝氨酸缺乏会导致线粒体的改变,而线粒体的变化是导致MacTel发育的基础。
来自美国哈佛大学的John E. Dowling团队认为在细胞和组织水平上,已经发现了一个受神经退行性改变影响的区域之间的边界过渡区MacTel,该区域与周围区域并列,亚细胞(线粒体)变化更为微妙,但保持着接近正常的功能回路。在视网膜黄斑区,感光细胞的轴突(Henle纤维)和突触终末通常被Müller胶质细胞的过程包裹,将每个神经元与周围的邻居隔离开来。在这个MacTel过渡区的边界上,许多小胶质细胞渗透到细胞碎片和异位感光细胞体的岛屿上(通常只在位于Henle纤维层之上的外层核层内)。利用供者组织和细胞为基础的策略(例如,从供者诱导的多能干细胞中生长的人视网膜有机体),高通量靶向连接组学可以揭示干预措施可在多大程度上恢复或阻止病理发展。采用连接组学进行的超微结构分析提供了一个强有力的工具来研究大脑的正常功能结构,疾病或损伤后发生的变化,以及模型和患者系统中的恢复性努力如何以功能上有意义的方式使受损的电路恢复。
    文章在《中国神经再生研究(英文版)》杂志2022年 1 月 1 期发表。

https://orcid.org/0000-0002-2373-7481 (Charles L. Zucker); https://orcid.org/0000-0002-8441-6761 (John E. Dowling)

Abstract: Electron microscopy (EM) provides a unique ability to visualize structural detail with a resolution orders of magnitude better than other imaging techniques. Applied conventionally, its limitation is that each acquired image represents a small area with a section thickness significantly less than 100 nm. Recently, techniques have been developed that allow thousands of relatively large serial-sections to be collected and efficiently imaged at full EM resolution, with the images then being stitched back together to produce a 3D volume.  Within such a volume, every subcellular structure or cellular connection can be identified and mapped, i.e. connectomics. These methods offer the opportunity of revealing a comprehensive view of large volumes of neural tissue. With the increasing use of automated technologies, it is now possible to use large-scale serial-section electron microscopy to generate reconstructions of various brain regions with a resolution of 4 nm or better (Kasthuri et al., 2015; Baena et al., 2019). At this resolution, excitatory and inhibitory chemical synapses can be seen; the existence of electrical synapses (gap junctions), the presence of neuromodulatory peptides and biogenic amines, and the identification of local microcircuits can all be observed (Swanson and Lichtman, 2016).  Furthermore, relationships with various types of glial cells are readily seen, and cells associated with vascular elements and non-neuronal/glial cell types can be distinguished.  Further, the fine structure of organelles, including mitochondria, endoplasmic reticulum, lysosomes, and autophagosomes, along with cytoskeletal elements are within the resolution of these techniques. Thus, a continuum of scale, from sub-organelle structure, through the cellular level, up to a wide field tissue perspective can be viewed and analyzed simultaneously.  Such techniques have been used to map nerve regeneration in 3D (Leckenby et al., 2019), to investigate developmental rewiring in the cerebellum (Wilson et al., 2019); to explore the network connectivity in visual thalamus (Morgan and Lichtman, 2020), and to define the neuronal connectivity and relationships with glial cells in the human fovea (Dacey et al., 2017; Packer et al., 2017).