Next-generation MORF Mice for Scalable Brainwide Morphological Mapping and Genetic Perturbation of Single Neurons

下一代 MORF 小鼠，用于可扩展的全脑形态映射和单神经元的遗传扰动

• 批准号: 10370248
• 负责人: Hong-Wei Dong
• 金额: $ 435.37万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-10 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10370248
• 关键词: 3-Dimensional; Address; Atlases; Axon; BRAIN initiative; Biological; Brain; Brain Mapping; Brain region; Cells; Cellular Morphology; Censuses; Cerebral hemisphere; Characteristics; Classification; DNA; Data; Data Analyses; Dendrites; Development; Disease; Drosophila genus; Feedback; Frequencies; Gene Activation; Gene Expression; Genes; Genetic; Genetic Models; Glutamates; Goals; Grant; Image; Individual; Information Technology; Intrinsic factor; Invertebrates; Label; Light; Link; Maps; Mediating; Membrane; Modeling; Molecular; Molecular Profiling; Morphology; Mosaicism; Motor Cortex; Mus; Neuroglia; Neurons; Organelles; Pattern; Physiology; Property; Proteins; Protocols documentation; Reporter; Reporter Genes; Resolution; Rodent; Role; Structure; Subcellular structure; Surveys; Synapses; System; Techniques; Technology; Testing; base; bioinformatics pipeline; brain cell; cell type; density; epigenome; epigenomics; experience; flexibility; genome editing; high resolution imaging; image registration; imaging informatics; informatics tool; innovation; molecular marker; mouse genetics; mouse model; neurotechnology; next generation; novel; presynaptic; programs; rapid growth; recombinase; reconstruction; response; selective expression; tissue processing; tool; transcriptomics

PROJECT SUMMARY A major challenge in studying the mammalian brain is to characterize the integrative properties of individual neurons, such as molecular profiles, complete morphology (dendrites, axons, synapses), connectivity, and activity; furthermore, this must be done at a scale that is commensurate with the goal of understanding all the neurons and their circuitry in the brain. While current single-cell transcriptomic and epigenomic profiling techniques are highly quantitative, scalable and informative, the technologies to study other neuronal cell-type defining properties(e.g. single-neuron brain-wide morphology and synaptic connectivity) are low throughput, labor intensive, poorly scalable and often yield partial data. Emerging neuronal cell type classification studies in invertebrates (e.g. Drosophila) and in rodents suggest that the neuronal morphological data such as axonal projection patterns are correlated, but may also be independent to the cell classes defined by single-cell gene expression. Thus, a complete and unbiased survey of mammalian neuronal cell census should include orthogonal data types consisting of both molecular profiles and brainwide morphology of single neurons. Finally, for emerging new cell types defined by unique transcriptomic profiles, the causal links between the cell-type-defining “neuronal identity” genes and other cell-type-specific features, such as morphology, synaptic connectivity and activity, remain elusive and cannot be readily characterized in a scalable manner. In this proposal (in response to RFA MH-21-140), we will address these challenges by building upon a novel neurotechnology called Mosaicism with Repeat Frameshift, or MORF. MORF mice can confer cell- type specific, sparse and brightly labeling of neurons and glia to illuminate their complete morphologies in the mouse brain. The innovative aspect of the MORF mice is the use of an out-of-frame mononucleotide repeat as a stochastic translational switch; and its random frameshift leads to the expression of an extremely bright membrane-bound immunoreporter protein in 1-5% of genetically-defined neurons. In this proposal, we will generate four next-generation MORF mouse models that will allow: (1). precise and sparse labeling of neuronal cell types based on two genetic drivers (i.e. two molecular markers that define the neuronal cell type); (2). Cre-dependent labeling of endogenous presynaptic proteins in sparsely labeled GABAergic and cortical glutamatergic neurons; (3). selective expression of genome-editing tools in genetically and sparsely labeled neurons to support perturbation and multiplex subcellular labeling; and (4). development of an innovative and integrative multiscale imaging and registration pipeline to provide proof-of-concept data that analyzes brainwide morphology and connectivity of genetically-defined single neurons. Together, our grant may help to develop generalizable, scalable and democratizable tools to advance the study of neuronal morphology, synapses and connectivity, and genetic perturbation. These tools will facilitate the construction of mammalian brain cell census and advance the study of brain development, function and disease at the resolution of single neurons.

项目总结 研究哺乳动物大脑的一个主要挑战是描述大脑的综合特性 单个神经元，如分子轮廓、完整的形态(树突、轴突、突触)， 连通性和活动；此外，这项工作的规模必须与以下目标相称 了解大脑中的所有神经元及其电路。而目前的单细胞转录和 表观基因组图谱技术是高度定量、可扩展和信息丰富的，是研究的技术 其他神经细胞类型定义特性(例如，单神经元全脑形态和突触连接) 吞吐量低、劳动密集型、可伸缩性差，通常会产生部分数据。新出现的神经细胞类型 无脊椎动物(如果蝇)和啮齿动物的分类研究表明，神经元形态 轴突投影模式等数据是相关的，但也可以独立于定义的像元类别 通过单细胞基因表达。因此，对哺乳动物神经细胞普查的完整和公正的调查 应包括由分子轮廓和单个分子的全脑形态组成的正交数据类型 神经元。最后，对于由独特的转录图谱定义的新兴新细胞类型， 定义细胞类型的“神经元同一性”基因和其他细胞类型特定的特征，如形态， 突触的连接性和活性，仍然难以捉摸，也不能轻易地以可扩展的方式描述。 在本提案中(针对RFA MH-21-140)，我们将通过以下方式应对这些挑战 一种新的神经技术，称为带有重复移码的嵌合体，或称Morf。Morf小鼠可以提供细胞- 神经元和神经胶质细胞类型特定、稀疏和明亮的标记，以阐明其完整的形态。 老鼠的大脑。Morf小鼠的创新方面是使用了框架外的单核苷酸 Repeat作为一种随机的平移开关，它的随机移码导致了一个极端的表达 在1-5%的遗传定义神经元中有明亮的膜结合免疫报告蛋白。在这项提案中，我们 将产生四个下一代Morf鼠标模型，将允许：(1)。精确和稀疏的标注 基于两个遗传驱动因素的神经细胞类型(即定义神经细胞类型的两个分子标记)； (2)。稀疏标记GABA能和皮质内内源性突触前蛋白的Cre依赖标记 谷氨酸能神经元；基因组编辑工具在基因稀疏标记系统中的选择性表达 支持扰动和多路亚细胞标记的神经元；以及(4)。开发一种创新的和 集成的多尺度成像和配准管道，可提供概念验证数据，用于全脑分析 遗传定义的单个神经元的形态和连通性。共同努力，我们的赠款可能有助于发展 可推广、可扩展和可民主化的工具，以推进神经元形态、突触和 连通性和遗传扰动。这些工具将促进哺乳动物脑细胞普查的构建 并在单个神经元的分辨率上推进脑发育、功能和疾病的研究。

项目成果

Epitope-preserving magnified analysis of proteome (eMAP).

• DOI: 10.1126/sciadv.abf6589
• 发表时间: 2021-11-12
• 期刊: Science advances
• 影响因子: 13.6
• 作者: Park J;Khan S;Yun DH;Ku T;Villa KL;Lee JE;Zhang Q;Park J;Feng G;Nedivi E;Chung K
• 通讯作者: Chung K