Time-resolved single-cell analysis of neural cell differentiation in motor neuron disease

运动神经元疾病神经细胞分化的时间分辨单细胞分析

• 批准号: 2606573
• 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: 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=studentship-2606573
• 关键词: Time; resolved; single; cell; analysis

Amyotrophic Lateral Sclerosis (ALS) is a progressive motor neuron disease that is caused by the selective degeneration of the upper and lower motor neurons that eventually leads to paralysis. It is still elusive why motor neurons are so vulnerable, how early disease associated changes appear, and precisely how other supporting cells contribute to the disease.In this project we will investigate and characterise the earliest stages of the disease while focusing on specific cell types and genetic backgrounds. More specifically, we will be utilising induced pluripotent stem cells (iPSCs) from two familial ALS cohorts, sporadic cases of ALS and age-matched controls. These iPSCs will then be differentiated into motor neurons and astrocytes, with single cell RNA sequencing and protein-based assays then employed at key stages of the cell differentiations. In this way, we will be able to elucidate when the earliest disease associated changes occur and identify the key molecular changes relevant to the different cohorts. Together this will provide a time-resolved analysis of the earliest stages of disease using a clinically relevant human model system. Moreover, we will better understand at which stage diverse cell types become vulnerable in relation to diverse disease relevant genetics. Together this information will then be used to test putative therapeutic interventions at the early stages of the disease.

肌萎缩侧索硬化症（ALS）是一种进行性运动神经元疾病，其由上、下运动神经元的选择性变性引起，最终导致瘫痪。运动神经元为何如此脆弱，疾病早期相关变化如何出现，以及其他支持细胞如何对疾病做出贡献，目前仍是一个谜。在这个项目中，我们将研究和分析疾病的早期阶段，同时关注特定的细胞类型和遗传背景。更具体地说，我们将利用来自两个家族性ALS队列的诱导多能干细胞（iPSC），ALS的散发病例和年龄匹配的对照。然后，这些iPSC将分化为运动神经元和星形胶质细胞，然后在细胞分化的关键阶段进行单细胞RNA测序和基于蛋白质的测定。通过这种方式，我们将能够阐明何时发生最早的疾病相关变化，并确定与不同队列相关的关键分子变化。总之，这将使用临床相关的人类模型系统提供疾病最早阶段的时间分辨分析。此外，我们将更好地了解不同的细胞类型在哪个阶段变得与不同的疾病相关的遗传学脆弱。这些信息将一起用于在疾病的早期阶段测试假定的治疗干预措施。