Identifying the mechanisms of neuronal fate commitment during direct conversion

 描述(申请人提供)：通过转录因子的强制过表达将成纤维细胞直接转化为运动神经元，将使神经退行性疾病的研究和治疗药物的高通量鉴定成为可能。从肌萎缩侧索硬化症(ALS)患者分离的成纤维细胞中分离的诱导运动神经元(IMN)在体外概括了神经退行性变的过程。通过提供一种“盘子里的疾病”，iMN促进了对神经退化机制的研究，并允许相对快速地筛选和鉴定治疗化合物。然而，准确地对神经疾病进行建模依赖于强大、可靠的方法，这些方法可以有效地生成受疾病影响的不同神经亚群。到目前为止，皈依仍然是低效的，直接世系皈依的核心机制规则仍然没有定义。此外，许多与研究和治疗应用相关的细胞特性尚未确定。最后，成纤维细胞的起始群体如何影响这些神经元的转化、神经元特性和成熟度的问题还没有被探索。IMN的单细胞转录图谱将使我们能够完善我们对特定细胞亚群特有的协调表达模式的理解。单细胞分析解决了批量分析引入的偏差，其中 只有总体平均值才能被观察到，这使我们能够更可靠地识别命运的转录决定因素。使用单细胞转录图谱，我们的目标是对引导成纤维细胞转化为iMN的分子过程和细胞状态产生更好的机械性理解。此外，我们将利用已确定的命运转录决定因素进入合成电路，以提高转换效率和神经元成熟度。识别最优的转录图谱和分子转化规则将使复杂的合成电路的构建成为可能，这些电路将驱动细胞走向所需的命运。单细胞转录图谱数据可能提出了影响转化的一般机制，并可能解释细胞如何将复杂的细胞线索处理成强大的、长期的细胞身份。通过了解转化的分子机制，我们可以构建增强的重新编程策略，并潜在地阐明各种细胞类型的直接转化的一般原理，从而为治疗筛选和疾病和受损组织的替换提供广泛的疾病模型。

 DESCRIPTION (provided by applicant): Direct conversion of fibroblasts into motor neurons via the forced overexpression of transcription factors will enable both the study of neurodegenerative diseases and the high- throughput identification of therapeutics. Induced motor neurons (iMNs) converted from fibroblasts isolated from patients suffering from amyotrophic lateral sclerosis (ALS) recapitulate neurodegenerative processes in vitro. By providing a "disease in a dish," iMNs facilitate the study of the mechanisms of neurodegeneration and allow for the relatively rapid screening and identification of therapeutic compounds. However, accurately modeling neurological disorders relies on robust, reliable methods that efficiently generate the distinct neural subpopulations affected by the disease. Thus far, conversion remains inefficient, and the central mechanistic rules for direct lineage conversion remain undefined. Further, many cellular properties that are relevant for both research and therapeutic applications are uncharacterized. Finally, the question of how the starting population of fibroblasts influences the conversion, neuronal identity, and maturation of these neurons stands unexplored. Single-cell transcriptional profiling of iMNs will enable us to refine our understanding of the coordinated patterns of expression that are unique to particular subpopulations of cells. Single-cell profiling resolves bias introduced by bulk profiling, in which only the population average is observed, allowing us to more reliably identify transcriptional determinants of fate. Using single-cell transcriptional profiling, we aim to generate an improved mechanistic understanding of the molecular processes and cellular states that direct the conversion of fibroblasts into iMNs. Further, we will harness the identified transcriptional determinates of fate into synthetic circuits to enhance conversion efficiency and neuron maturity. Identifying optimal transcriptional profiles and the molecular rules of conversion will enable the construction of sophisticated synthetic circuits that drive cells toward desired fates. Single-cell transcriptional profiling data may suggest general mechanisms that influence conversion and may provide an explanation of how cells process complex sets of cellular cues into robust, long-term cellular identities. By understanding the molecular mechanisms of conversion, we can construct enhanced reprogramming strategies and potentially illuminate general principles for the direct conversion of a variety of cell types, enabling a broad range of disease models for therapeutic screens and the replacement of diseased and damaged tissues.