Cellular-resolution in situ transcriptomics of the mouse brain and Alzheimer's disease models

小鼠大脑和阿尔茨海默病模型的细胞分辨率原位转录组学

• 批准号: MR/V003402/1
• 负责人: Kenneth Harris
• 金额: $ 110.16万
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FV003402%2F1
• 关键词: Cellular; resolution; situ; transcriptomics; mouse

The brain is composed of hundreds of subtly-different cell types, spread over hundreds of distinct regions. The sensory, motor, and cognitive functions the brain produces, arise from circuits distributed globally across these regions. To understand brain function, it is therefore essential to understand the global spatial organization of its component cell types. Similarly, to understand how cognition can falter in disease conditions, it is essential to understand how pathologies affect circuits across the whole brain.Alzheimer's disease is a devastating disorder of brain function, with a tremendous and still growing social and economic cost. Although much research has focused on a small set of regions (the hippocampus and entorhinal cortex), Alzheimer's disease affects the whole brain. For example, drugs targeting a small but very specific circuit, the basal forebrain cholinergic system, are amongst the few treatments approved for relief of Alzheimer's symptoms. Many other specific brain regions are likely to be involved also, but an understanding of the brain-wide pathology of the disease is currently lacking. Each brain region contains many finely-distinguished subtypes of neurons, as well as other cell types such as microglia, astrocytes, oligodendrocytes, and vascular cells, which all likely play a role in the disease aetiology. Precious little information is available on how these fine subtypes are involved in the disease. This project will employ a new technology, called in situ transcriptomics, to understand the global structure of the brain, and it is disrupted by the pathologies underlying Alzheimer's disease, using mouse models. This technology can localize the expression of many genes simultaneously, to sub-micrometer resolution, in samples of any tissue from any species. Because different cell types express different combinatorial patterns of genes, parallel measurement of a cell's gene expression profiles allows fine cell type classification. Furthermore, because changes in cellular function are almost always reflected in changes in gene expression, applying the technology to disease models will allow scientists to understand how the function of each cell type changes under pathological conditions.The technology is still under development, and is currently found in only a few labs worldwide. Our group at UCL are one of the developers of the technology. We have recently developed it to a point where it can localize up to 1000 genes simultaneously at high efficiency, and automated it so that it can run at high enough throughput to process an entire mouse brain. We propose here to apply this newly-established technology at scale, to produce an entire atlas of expression of 1000 carefully chosen genes, at submicron resolution, across the whole mouse brain. We will use this to spatially localize all the brain's cell types (building on work from a previous non-spatial transcriptomic technology). We will then apply the same methodology to two mouse lines, that model the two main types of pathology underlying Alzheimer's disease: the APPNL-G-F amyloid model, and the THY-Tau22 model. This will enable us to see how multiple types of neuron and non-neurons across all brain regions are affected by the amyloid and tau pathologies. All data will be made freely available, enabling scientists worldwide to use it to guide new experiments and hypotheses regarding the function of the healthy and diseased brain. This will provide foundational information, greatly accelerating progress towards understanding not only Alzheimers but also a wide range of other neurological and psychiatric disorders of cognition including for example schizophrenia, depression, bipolar disorder, frontotemporal dementia, Parkinson's disease, and Huntington's disease.

大脑由数百种略有不同的细胞类型组成，分布在数百个不同的区域。大脑产生的感觉、运动和认知功能来自分布在全球这些区域的电路。因此，为了了解大脑功能，有必要了解其组成细胞类型的整体空间组织。同样，要了解疾病条件下认知能力如何衰退，就必须了解病理如何影响整个大脑的回路。阿尔茨海默病是一种破坏性的大脑功能障碍，造成巨大且仍在不断增长的社会和经济成本。尽管许多研究都集中在一小部分区域（海马体和内嗅皮层），但阿尔茨海默病影响整个大脑。例如，针对一个小但非常特殊的回路（基底前脑胆碱能系统）的药物是少数被批准用于缓解阿尔茨海默病症状的治疗方法之一。许多其他特定的大脑区域也可能参与其中，但目前缺乏对该疾病的全脑病理学的了解。每个大脑区域都包含许多精细区分的神经元亚型，以及其他细胞类型，如小胶质细胞、星形胶质细胞、少突胶质细胞和血管细胞，这些细胞都可能在疾病病因学中发挥作用。关于这些精细亚型如何参与该疾病的宝贵信息很少。该项目将采用一种称为原位转录组学的新技术，利用小鼠模型来了解大脑的整体结构，并通过阿尔茨海默病的病理学来破坏大脑的整体结构。该技术可以在任何物种的任何组织样本中以亚微米分辨率同时定位许多基因的表达。由于不同的细胞类型表达不同的基因组合模式，因此并行测量细胞的基因表达谱可以对细胞类型进行精细分类。此外，由于细胞功能的变化几乎总是反映在基因表达的变化中，因此将该技术应用于疾病模型将使科学家能够了解每种细胞类型的功能在病理条件下如何变化。该技术仍在开发中，目前正在开发中全球仅有少数实验室发现。我们伦敦大学学院的团队是该技术的开发者之一。我们最近将其开发到可以同时高效定位多达 1000 个基因的程度，并实现自动化，使其能够以足够高的吞吐量运行来处理整个小鼠大脑。我们在此建议大规模应用这项新建立的技术，以亚微米分辨率在整个小鼠大脑中生成 1000 个精心挑选的基因的完整表达图谱。我们将用它来空间定位所有大脑细胞类型（建立在以前的非空间转录组技术的基础上）。然后，我们将相同的方法应用于两个小鼠品系，模拟阿尔茨海默病的两种主要病理类型：APPNL-G-F 淀粉样蛋白模型和 THY-Tau22 模型。这将使我们能够了解所有大脑区域的多种类型的神经元和非神经元如何受到淀粉样蛋白和 tau 蛋白病理学的影响。所有数据都将免费提供，使世界各地的科学家能够利用它来指导有关健康和患病大脑功能的新实验和假设。这将提供基础信息，大大加快了解阿尔茨海默病以及其他广泛的神经和精神认知障碍，包括精神分裂症、抑郁症、双相情感障碍、额颞叶痴呆、帕金森病和亨廷顿病。