Large-scale EM data reveals myelinated axonal changes and altered connectivity in the corpus callosum of an autism mouse model.

IF 2.5 4区 医学 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Frontiers in Neuroinformatics Pub Date : 2025-04-11 eCollection Date: 2025-01-01 DOI:10.3389/fninf.2025.1563799
Guoqiang Zhao, Ao Cheng, Jiahao Shi, Peiyao Shi, Jun Guo, Chunying Yin, Hafsh Khan, Jiachi Chen, Pengcheng Wang, Jiao Chen, Ruobing Zhang
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引用次数: 0

Abstract

Introduction: Autism spectrum disorder (ASD) encompasses a diverse range of neurodevelopmental disorders with complex etiologies, including genetic, environmental, and neuroanatomical factors. While the exact mechanisms underlying ASD remain unclear, structural abnormalities in the brain offer valuable insights into its pathophysiology. The corpus callosum, the largest white matter tract in the brain, plays a crucial role in interhemispheric communication, and its structural abnormalities may contribute to ASD-related phenotypes.

Methods: To investigate the ultrastructural alterations in the corpus callosum associated with ASD, we utilized serial scanning electron microscopy (sSEM) in mice. A dataset of the entire sagittal sections of the corpus callosum from wild-type and Shank3B mutant mice was acquired at 4 nm resolution, enabling precise comparisons of myelinated axon properties. Leveraging a fine-tuned EM-SAM model for automated segmentation, we quantitatively analyzed key metrics, including G-ratio, myelin thickness, and axonal density.

Results: In the corpus callosum of Shank3B autism model mouse, we observed a significant increase in myelinated axon density, accompanied by thinner myelin sheaths compared to wild-type. Additionally, we identified abnormalities in the diameter distribution of myelinated axons and deviations in G-ratio. Notably, these ultrastructural alterations were widespread across the corpus callosum, suggesting a global disruption of myelinated axon integrity.

Discussion: This study provides novel insights into the microstructural abnormalities of the corpus callosum in ASD mouse, supporting the hypothesis that myelination deficits contribute to ASD-related communication impairments between brain hemispheres. However, given the structural focus of this study, further research integrating functional assessments is necessary to establish a direct link between these morphological changes and ASD-related neural dysfunction.

大规模EM数据揭示了自闭症小鼠模型胼胝体中髓鞘轴突的变化和连接的改变。
自闭症谱系障碍(ASD)包括多种神经发育障碍,其病因复杂,包括遗传、环境和神经解剖因素。虽然ASD的确切机制尚不清楚,但大脑结构异常为其病理生理学提供了有价值的见解。胼胝体是大脑中最大的白质束,在大脑半球间通讯中起着至关重要的作用,其结构异常可能导致自闭症相关表型。方法:应用连续扫描电镜(sSEM)观察ASD小鼠胼胝体超微结构的改变。我们获得了野生型和Shank3B突变小鼠胼胝体整个矢状面切片的数据集,分辨率为4 nm,可以精确比较髓鞘轴突的特性。利用微调的EM-SAM模型进行自动分割,我们定量分析了关键指标,包括g比、髓鞘厚度和轴突密度。结果:在Shank3B自闭症模型小鼠胼胝体中,与野生型相比,我们观察到髓鞘密度明显增加,髓鞘更薄。此外,我们还发现了髓鞘轴突直径分布的异常和g比的偏差。值得注意的是,这些超微结构改变在胼胝体中广泛存在,表明髓鞘轴突完整性的整体破坏。讨论:本研究为ASD小鼠胼胝体的微观结构异常提供了新的见解,支持了髓鞘形成缺陷导致ASD相关的大脑半球之间的交流障碍的假设。然而,鉴于本研究的结构重点,有必要进一步研究整合功能评估,以建立这些形态学变化与asd相关神经功能障碍之间的直接联系。
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来源期刊
Frontiers in Neuroinformatics
Frontiers in Neuroinformatics MATHEMATICAL & COMPUTATIONAL BIOLOGY-NEUROSCIENCES
CiteScore
4.80
自引率
5.70%
发文量
132
审稿时长
14 weeks
期刊介绍: Frontiers in Neuroinformatics publishes rigorously peer-reviewed research on the development and implementation of numerical/computational models and analytical tools used to share, integrate and analyze experimental data and advance theories of the nervous system functions. Specialty Chief Editors Jan G. Bjaalie at the University of Oslo and Sean L. Hill at the École Polytechnique Fédérale de Lausanne are supported by an outstanding Editorial Board of international experts. This multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics and the public worldwide. Neuroscience is being propelled into the information age as the volume of information explodes, demanding organization and synthesis. Novel synthesis approaches are opening up a new dimension for the exploration of the components of brain elements and systems and the vast number of variables that underlie their functions. Neural data is highly heterogeneous with complex inter-relations across multiple levels, driving the need for innovative organizing and synthesizing approaches from genes to cognition, and covering a range of species and disease states. Frontiers in Neuroinformatics therefore welcomes submissions on existing neuroscience databases, development of data and knowledge bases for all levels of neuroscience, applications and technologies that can facilitate data sharing (interoperability, formats, terminologies, and ontologies), and novel tools for data acquisition, analyses, visualization, and dissemination of nervous system data. Our journal welcomes submissions on new tools (software and hardware) that support brain modeling, and the merging of neuroscience databases with brain models used for simulation and visualization.
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