Establishing Common Coordinate Framework for Quantitative Cell Census in Developing Mouse Brains

建立小鼠大脑发育中定量细胞普查的通用坐标框架

基本信息

批准号：
10088508
负责人：
JAMES C GEE
金额：
$ 379.79万
依托单位：
PENNSYLVANIA STATE UNIV HERSHEY MED CTR
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-09-15 至 2024-09-14
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10088508
关键词：
3-Dimensional Acute Address Adopted Adult Age Anatomy Animal Model Apoptosis Architecture Atlases BRAIN initiative Birth Brain Brain Diseases Brain Mapping Brain region C57BL/6 Mouse Cell Density Cell Nucleus Cells Censuses Cessation of life Communities Complex Computer Analysis Coupled Cre driver Data Development Disease Embryo Embryology Fluorescence Microscopy Gene Expression Genetic Goals Histologic Image Imaging technology In Situ Knowledge Label Lectin Light Link Location Magnetic Resonance Imaging Maps Methods Microscopy Modernization Morphology Mus Neuroanatomy Neurons Neurosciences Ontology Parvalbumins Pattern Quantitative Evaluations Reporter Reproducibility Resolution Resources Scientist Somatostatin Stains Technology Three-Dimensional Image Three-Dimensional Imaging Time Tissues Training Vasoactive Intestinal Peptide Visualization analysis pipeline base brain cell cell type data integration data resource data sharing improved indexing microscopic imaging model development mouse model multimodality myelination neural circuit neurodevelopment neuroinformatics novel postnatal programs skills spatiotemporal three dimensional structure

项目摘要

Abstract Brain development is characterized by a diverse set of cell types that are born and connected into rapidly growing complex 3D structures across time. Quantitative understanding of cell type composition and distribution in different brain regions provides fundamental knowledge about the building blocks of the brain and serves as an essential baseline with which to assess changes that may occur in brain disorders. The importance of this information is reflected by the significant effort among the neuroscience community, including the creation of the BRAIN Initiative Cell Census Network, to improve our understanding of cell type compositions across different brain regions in the adult mouse brain. These efforts have been made possible and accelerated by technological advances in high-resolution 3D imaging coupled with computational analysis methods that can reveal cell type arrangement in the brain with unprecedented detail. For example, we developed a quantitative brain mapping method to uncover the spatial arrangement of GABAergic neuron subtypes in the adult mouse brain. For the adult mouse brain, the Allen Common Coordinate Framework (CCF) currently serves as the standard atlas resource with which to map and integrate results from different studies. The neuroscience community, on the other hand, does not have similar CCFs for the developing mouse brain. The lack of developmental CCFs significantly hinders progress on cell type mapping of the developing mouse brain by limiting the reproducibility and integration of data from different studies. To address this deficiency, we have assembled a highly synergistic, multi-institutional team with complementary skill sets to create developmental CCFs with associated ontology and true 3D anatomical labels while also demonstrating the application of our CCFs by generating quantitative mappings of GABAergic neurons in the developing mouse brain. Toward this end, we will first utilize MRI and light sheet fluorescent microscopy (LSFM) to develop high-resolution developmental CCFs at seven different developmental time points (E11.5, E13.5, E15.5, E18.5, P4, P14, and P56) with different cellular features, including total cell density, myelination, and neurovasculature. Second, we will create true 3D anatomical labels for the CCFs based on cellular and gene expression information, and build a comprehensive ontology that will allow anatomical region changes to be linked across development and maturation. Lastly, we will generate a cellular-resolution quantitative map of GABAergic neuronal subtypes using tissue clearing and LSFM imaging in developing mouse brains, which will serve as a substantial data resource to accelerate developmental neuroscience discovery. The successful completion of this project will enable a broad field of scientists to leverage modern brain mapping technologies more effectively in studying the developing mouse brain.

抽象的大脑发育的特点是一系列不同的细胞类型，这些细胞类型诞生并连接成快速生长的细胞。跨越时间的复杂 3D 结构。定量了解细胞类型组成和分布不同的大脑区域提供了有关大脑构建模块的基础知识，并充当评估大脑疾病可能发生的变化的基本基线。这一点的重要性信息反映在神经科学界的巨大努力中，包括创建 BRAIN Initiative 细胞普查网络，以提高我们对不同细胞类型组成的了解成年小鼠大脑中的大脑区域。这些努力是通过技术得以实现并加速的高分辨率 3D 成像技术的进步与可揭示细胞类型的计算分析方法相结合大脑中的排列方式前所未有的详细。例如，我们开发了定量大脑图谱揭示成年小鼠大脑中 GABA 能神经元亚型空间排列的方法。对于成年小鼠大脑，艾伦通用坐标框架（CCF）目前作为标准图集用于绘制和整合不同研究结果的资源。神经科学界，关于另一方面，对于发育中的小鼠大脑来说，并没有类似的 CCF。缺乏发展性CCF 通过限制重现性，严重阻碍发育中小鼠大脑细胞类型图谱的进展以及来自不同研究的数据的整合。为了解决这一缺陷，我们组建了一个高度协同的、具有互补技能的多机构团队，可创建具有相关本体的开发 CCF 和真正的 3D 解剖标签，同时还通过生成定量数据来展示我们的 CCF 的应用发育中的小鼠大脑中 GABA 能神经元的图谱。为此，我们将首先利用 MRI 光片荧光显微镜 (LSFM) 用于开发七种不同的高分辨率发育 CCF 具有不同细胞特征的发育时间点（E11.5、E13.5、E15.5、E18.5、P4、P14 和 P56），包括总细胞密度、髓鞘形成和神经血管系统。其次，我们将创建真正的 3D 解剖标签基于细胞和基因表达信息的CCF，并构建一个全面的本体论允许解剖区域的变化在发育和成熟过程中联系起来。最后，我们将生成一个使用组织透明化和 LSFM 成像绘制 GABA 能神经元亚型的细胞分辨率定量图开发小鼠大脑，这将作为加速发育的重要数据资源神经科学发现。该项目的成功完成将使广大科学家能够更有效地利用现代大脑图谱技术来研究发育中的小鼠大脑。