Single-cell multi-region dissection of AD-pathogen interactions for HSV-1 and CMV

摘要 阿尔茨海默氏病（AD）是一种神经退行性疾病，导致戏剧性的影响，受影响的 个人及其家庭。虽然对AD的遗传贡献的表征和潜在的 近年来，分子机制已经推进了对疾病的理解，但研究未能 找到导致疾病进展的确切机制。病原体对AD的潜在影响 介导了环境对AD遗传贡献的影响。在这里，我们直接解剖 病原体相关效应的贡献下至细胞类型特异性分子基础，通过系统分析， 计算整合和实验验证的转录签名在个人，大脑 区域和细胞类型。在目标1中，我们在人类、小鼠和人类iPSC脑类器官样本中使用scRNA-seq， AD感染单纯疱疹病毒1型或巨细胞病毒（HSV-1/CMV），产生数百万个单- 细胞（SC）水平映射，最终目标是转录图谱。在目标2中，我们分析了产生的数据集， 潜在的分子机制，使我们能够发现和汇聚基因，途径，细胞类型， 大脑区域与驱动病原体相关改变的功能和因果机制之间的关系。在目标3中，我们使用 我们完善的iPSC模型，以测试我们预测的机制与高通量和细胞类型 具体分析。由此产生的数据集，计算预测和实验支持的机制 将揭示AD病理学的病原体相关影响，并将有助于加深我们对AD的理解。 随着我们开发更个性化的治疗方法来治疗AD，

Abstract Alzheimer’s disease (AD) is a neurodegenerative disorder that leads to dramatic effects on the affected individuals and their families. While the characterization of the genetic contribution to AD and underlying molecular mechanisms has advanced the understanding of the disease in recent years, studies have failed to find definitive mechanisms that account for disease progression. The influence of pathogens on AD potentially mediates an environmental impact on the established genetic contributions to AD. Here, we directly dissect the contribution of pathogen-related effects down to the cell-type-specific molecular basis by systematic profiling, computational integration, and experimental validation of the transcriptional signatures across individuals, brain regions, and cell types. In Aim 1, we use scRNA-seq in human, mouse, and human iPSC brain organoid samples of AD that are infected with Herpes Simplex Virus 1 or Cytomegalovirus (HSV-1/CMV) to generate millions of single- cell (sc) level maps with the end goal of a transcriptional atlas. In Aim 2, we analyze the resulting datasets and underlying molecular mechanisms, enabling us to discover and converge genes, pathways, cell types, and brain regions to functional and causal mechanisms that drive pathogen-related alterations. In Aim 3, we use our well-established iPSC model to test our predicted mechanisms with both high-throughput and cell-type specific assays. The resulting datasets, computational predictions, and experimentally-supported mechanisms will shed light on the pathogen-related influences on AD pathology and will help deepen our understanding of the disease in general as we develop more personalized therapeutic approaches to treating AD.