High-throughput single neuron resolution mapping of connecopathies in animal models of neurodevelopmental disorders

神经发育障碍动物模型中连接病的高通量单神经元分辨率图谱

• 批准号: 2887157
• 金额: --
• 依托单位: University of Edinburgh
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2887157
• 关键词: throughput; single; neuron; resolution; mapping

The specific patterns of connectivity between the billions of neurons in our brain is widely believed to determine how we think and how we differ as individuals. Behavioural abnormalities associated with neurodevelopmental disorders including autism spectrum disorder (ASD), are likely to result from aberrant wiring of neural networks, but how this happens is unclear. We know from functional imaging studies that ASDs involve hypo-connectivity amongst distant brain areas. Moreover, many genes associated with ASDs govern molecular mechanisms of brain wiring. But how connectopathies manifest at the level of connectivity between individual neurons and brain areas is unknown, limiting the progress towards revealing the mechanistic causes of the disorder1. Here, we propose to apply state-of-the art barcoding based connectomics approaches2 to distinguish single neuron level mechanisms for aberrant connectivity in rodent models of monogenic forms of ASD3. We will also be using novel spatial transcriptomics approaches to analyze the brain-wide changes in gene expression in the ASD animal models.We expect this approach to be transformative for autism research since it will generate single cell resolution connectome and gene expression profiles of neurotypical and ASD brains and will pin down specifically which pathways and neurons are vulnerable to hypo-connectivity and miswiring. Second, our approach is fast and scalable. It will be adaptable to all brain areas and all neurodevelopmental disorders where an animal model is available. This will enable establishing a profile of connectopathies across different animal models of neurodevelopmental disorders such as Rett syndrome and Fragile X, revealing common and disparate structural deficits. Finally, our work will be a critical starting point for development of clinical interventions.

我们大脑中数十亿神经元之间的特定连接模式被广泛认为决定了我们如何思考以及我们作为个体的差异。与包括自闭症谱系障碍（ASD）在内的神经发育障碍相关的行为异常可能是由神经网络的异常布线引起的，但这是如何发生的尚不清楚。我们从功能成像研究中了解到，ASD涉及遥远的大脑区域之间的连接不足。此外，许多与ASD相关的基因控制着大脑布线的分子机制。但是，连接性病变如何在单个神经元和大脑区域之间的连接水平上表现尚不清楚，这限制了揭示这种疾病的机械原因的进展。在这里，我们建议应用最先进的基于条形码的连接组学方法2来区分ASD 3单基因形式的啮齿动物模型中异常连接的单神经元水平机制。我们还将使用新的空间转录组学方法来分析ASD动物模型中全脑范围内基因表达的变化。我们希望这种方法对自闭症研究具有变革性意义，因为它将生成神经典型和ASD大脑的单细胞分辨率连接体和基因表达谱，并将具体确定哪些通路和神经元容易受到连接不足和错误连接的影响。其次，我们的方法快速且可扩展。它将适用于所有大脑区域和所有神经发育障碍，其中动物模型是可用的。这将能够在不同的神经发育障碍动物模型（如Rett综合征和脆性X）中建立连接病变的概况，揭示常见和不同的结构缺陷。最后，我们的工作将是临床干预措施发展的关键起点。