A single-cell platform to discover and study regulators of human development

人类多能干细胞（PSC）具有形成体内几乎任何细胞类型的潜力， 由于其在再生医学中的潜在应用， 以及最近通过重编程获得患者特异性干细胞的潜力， 将细胞转化为多能细胞。然而，在这种兴奋的阴影下， 人类发育生物学基础研究中的多能干细胞一直被忽视。这是 考虑到人类和小鼠之间的基本生理差异， 最接近的亲戚，通常进行这种研究。我未来研究的长期目标 计划是使用PSC来发现和表征新的调节因子（即基因，代谢物，生长因子， 非编码RNA）的人类发育过程。为了做到这一点，有必要 创建一个平台（一套方法和分析工具），以允许建模，跟踪和比较 人类干细胞在自然条件下和恒温控制条件下分化的途径。 为此，我将使用下一代单细胞分析仪器（CyTOF质谱细胞仪）， 我以前曾用于测量蛋白质表达水平，调节修饰，细胞周期和细胞 人类骨髓中大多数已知细胞类型对药物、细胞因子和生长的反应性死亡 这些因素来描述这个系统。我将首先创建一个多能细胞的单细胞模板， 使用标准分化条件进行分化。然后我将创建一套计算工具， 不仅考虑了细胞分化的动态性质，而且还能够比较 在不同研究者控制的条件下区分细胞类型。我会用稳定基因敲除 基于先前鉴定为在大肠杆菌中差异表达的蛋白质的靶向感兴趣基因的方法 人PSC与其分化的对应物。这条实验管道将建立一个新的， 独特的平台（数据收集方法、数据分析和解释方法以及概念验证 它的实施）的特征推定的细胞分化的调节。

Human pluripotent stem cells (PSCs), which have the potential to form virtually any cell type in the body, have been the subject of intense research focus due to their potential application to regenerative medicine and the more recent potential for patient specific stem cells via reprogramming, allowing differentiated adult cells to be turned into pluripotent ones. However, in the shadow of this excitement, the potential to exploit pluripotent stem cells for fundamental studies in human developmental biology has been overlooked. This is especially pertinent given the fundamental physiological differences between the human and mouse - the closest relative where such studies are typically carried out. The long-term goal of my future research program is to use PSCs to discover and characterize new regulators (i.e. genes, metabolites, growth factors, non-coding RNA) of the human developmental processes. In order to accomplish this it will be necessary to create a platform (set of methods and analytical tools) to allow the modeling, tracing, and comparison of the paths by which human stem cells differentiate under natural and investigator-controlled situations. To this end, I will use a next-generation single-cell analysis instrumentation (CyTOF mass cytometry), which I have previously used to measure levels of protein expression, regulatory modifications, cell cycle and cell death across most known cell types in human bone marrow in response to drugs, cytokines, and growth factors, to characterize this system. I will first create a single cell template of pluripotent cells undergoing differentiation using standard differentiation conditions. I will then create a set of computational tools that will not only take into consideration the dynamic nature of cellular differentiation, but also enable the comparison of differentiating cell-types in different investigator controlled conditions. I will use stable gene knockdown approaches to target genes of interest based on proteins previously identified as differentially expressed in human PSCs versus their differentiated counterparts. This pipeline of experimentation will establis a new and unique platform (a method for data collection, a method for data analysis and interpretation, and a proof-ofconcept of it's implementation) for the characterizing putative regulators of cellular differentiation.