Towards quantitative cell type-based mapping of the whole mouse brain

迈向基于细胞类型的整个小鼠大脑的定量绘图

• 批准号: 8822445
• 负责人: Pavel Osten
• 金额: $ 133.92万
• 依托单位: COLD SPRING HARBOR LABORATORY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-26 至 2017-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8822445
• 关键词: Adult; Aging; Algorithms; Animals; Area; Atlases; Axon; Behavior Control; Behavioral; Brain; Brain Diseases; Brain imaging; Cell Count; Cell Density; Cells; Censuses; Characteristics; Cognitive; Communities; Computing Methodologies; Data; Data Set; Development; Disease; Female; Foundations; Gene Expression; Gene Expression Profile; Generations; Genes; Goals; Human; Image; Imagery; Individual; Internet; Interneurons; Knowledge; Label; Light; Literature; Location; Manuals; Maps; Methodology; Methods; Microscopy; Modeling; Molecular; Morphology; Motor; Mus; Names; Neuroglia; Neurons; Neurosciences; Parvalbumins; Pattern; Performance; Population; Proteins; Public Health; Reporter; Research Infrastructure; Resolution; Response to stimulus physiology; Schizophrenia; Sensory; Sex Characteristics; Solutions; Specificity; Staging; Statistical Methods; Structure; Work; base; brain cell; cell type; digital; imaging modality; male; neuroinformatics; optimism; prevent; public health relevance; recombinase; scale up; tomography; tool; two-photon; web site

 DESCRIPTION (provided by applicant): The mouse brain comprises ~70 million neurons and ~30 million glia and other cells. Neurons have been traditionally classified based on their morphology, connectivity, stimulus-response, gene expression, and location in the brain. While we know reasonably well the main cell types that are present at different brain locations, we have little quantitative knowledge about brainwide cell type distribution. In addition, cell type-based brainwide connectivity, especially at the level of projection patterns of single neurons, also remains largely unmapped. This knowledge gap prevents us from incorporating the accumulated cell type-based cellular data into comprehensive circuit models of mammalian brain function. Here we propose to develop a largely automated methodology for 1) quantitative "atlasing" of neuronal and glia cell types on the basis of their complete cell counts per anatomical regions in the whole mouse brain, and 2) complete tracing of axonal arborizations of identified neuronal cell types. The specific Aims are: Specific Aim 1 (FOA goals 1, 4-6): To develop a versatile platform for brainwide atlasing of molecularly defined cell types. Computational and statistical methods will be developed to obtain accurate cell numbers in whole brains of cell type-specific reporter mice imaged by serial two-photon (STP) tomography and registered to reference brain atlases. These methods will then be used to map the distribution of five different GABAergic cell types during development, in the adult male and female brain, and during aging. Specific Aim 2 (FOA goal 6): To enhance the throughput of cell type-based atlasing and connectivity mapping through the development of a second-generation imaging platform. A light-sheet fluorescent microscopy-based method, named Oblique Plane Tomography (OPT), will be developed for fast high- resolution imaging of CLARITY-treated mouse brains. Computational methods will be established to allow the use of OPT in cell type atlasing and projection tracing in the whole mouse brain. Specific Aim 3 (FOA goals 2-3): Neuroinformatics infrastructure: an integrated web portal for cell-type specific data, tools & analytics. The developed methods, including a statistical toolbox for online and offline analytics, and the data generated will be distributed via a public website that will also serve to integrate the relevant information on the molecular identity, location, connectivity and other cell type characteristics. Relevance to public health: We will establish an automated and quantitative approach to the study of cell type distribution and connectivity in the mouse brain. Our methods can be readily scaled up and applied to a broad range of cell type-specific studies of both normal brain functions and pathological conditions related to human brain disorders.

 描述（由申请人提供）：小鼠大脑包含约7000万个神经元和约3000万个神经胶质细胞和其他细胞。神经元传统上是根据其形态、连接性、刺激反应、基因表达和在大脑中的位置进行分类的。虽然我们相当清楚地知道存在于不同大脑位置的主要细胞类型，但我们对全脑细胞类型分布的定量知识很少。此外，基于细胞类型的全脑连通性，特别是在单个神经元的投射模式水平上，也在很大程度上未被映射。这种知识差距使我们无法将积累的基于细胞类型的细胞数据纳入哺乳动物大脑功能的全面电路模型中。 在这里，我们建议开发一个很大程度上自动化的方法，1）定量“图谱”的神经元和神经胶质细胞类型的基础上，他们的完整的细胞计数在整个小鼠大脑的解剖区域，和2）完整的跟踪轴突分支的神经元细胞类型。具体目标1（FOA目标1，4-6）：开发用于分子定义的细胞类型的全脑图谱的通用平台。将开发计算和统计方法，以获得通过连续双光子（STP）断层扫描成像并配准到参考脑图谱的细胞类型特异性报告小鼠全脑中的准确细胞数。然后，这些方法将用于绘制发育过程中，成年男性和女性大脑中以及衰老过程中五种不同GABA能细胞类型的分布。具体目标2（FOA目标6）：通过开发第二代成像平台，提高基于细胞类型的图谱和连通性映射的吞吐量。将开发一种基于光片荧光显微镜的方法，称为斜平面断层扫描（OPT），用于快速高分辨率成像经抗癫痫治疗的小鼠大脑。将建立计算方法，以允许在整个小鼠脑中的细胞类型图谱和投射追踪中使用OPT。具体目标3（FOA目标2-3）：神经信息学基础设施：细胞类型特定数据，工具和分析的集成门户网站。所开发的方法，包括用于在线和离线分析的统计工具箱， 所产生的数据将通过公共网站发布，该网站还将用于整合关于分子身份、位置、连接性和其他细胞类型特征的相关信息。与公共卫生的相关性：我们将建立一种自动化和定量的方法来研究小鼠大脑中的细胞类型分布和连接。我们的方法可以很容易地扩大规模，并适用于广泛的细胞类型的特定研究的正常脑功能和病理条件相关的人类大脑疾病。