Identifying the mechanisms of neuronal fate commitment during direct conversion

 描述（由申请人提供）：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得能够进行神经变性疾病的研究和治疗剂的高通量鉴定。从肌萎缩侧索硬化症（ALS）患者分离的成纤维细胞转化的诱导运动神经元（iMN）在体外重演神经退行性过程。通过提供“盘中疾病”，iMN促进了神经变性机制的研究，并允许相对快速地筛选和鉴定治疗化合物。然而，准确建模神经系统疾病依赖于强大，可靠的方法，有效地产生不同的神经亚群受疾病的影响。到目前为止，转换仍然效率低下，直接谱系转换的中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被表征。最后，成纤维细胞的起始群体如何影响这些神经元的转化、神经元身份和成熟的问题尚未探索。iMN的单细胞转录谱分析将使我们能够完善我们对特定细胞亚群所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倚，其中 仅观察到群体平均值，这使我们能够更可靠地鉴定命运的转录决定因子。使用单细胞转录谱，我们的目标是产生一个改进的机制的理解的分子过程和细胞状态，直接转化成纤维细胞成iMN。此外，我们将利用已识别的命运转录决定因子合成电路，以提高转换效率和神经元成熟度。确定最佳的转录谱和转换的分子规则将使复杂的合成电路的建设，驱动细胞走向所需的命运。单细胞转录谱数据可能会提出影响转换的一般机制，并可能提供细胞如何处理复杂的细胞线索集到强大的，长期的细胞身份的解释。通过了解转化的分子机制，我们可以构建增强的重编程策略，并可能阐明各种细胞类型直接转化的一般原理，从而实现广泛的疾病模型，用于治疗筛选和替换患病和受损组织。

 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.