Transcriptional Control During Erythropoiesis

红细胞生成是一个由转录因子相对水平的数量变化控制的动态过程。由于目前缺乏关于构成转录调控网络(TRN)的蛋白质的定量数据，大多数红细胞生成模型主要基于mRNA测量，通常不考虑特定转录因子的蛋白质水平的变化。这极大地限制了人们对红细胞生成和其他转录调控过程的理解，例如贝珠蛋白的表达，最终影响了纠正血红蛋白紊乱的能力。长期目标是破译控制健康和疾病中红细胞生成的TRN。这项建议的目的是通过将动态批量和单细胞TF蛋白丰度测量与其他转录相关组学数据相结合，显著扩展我们在红细胞生成过程中决定细胞命运的TRN模型。中心假设是，在分化的连续体中，转录因子的相对蛋白质水平是建立基因表达程序的关键参数，而红细胞生成是由特定因子组合的相对数量的逐步变化驱动的。其基本原理是，将TF蛋白质组的动态和定量性质整合到红细胞生成的扩展TRN中，将产生一个具有更高预测能力的模型，该模型将作为健康红细胞生成的基准，用于比较红系相关疾病的状态，并将有助于识别恢复正常红细胞生成的药理药物。设计了三个特定的目标：1)绝对量化红系生成过程中的转铁蛋白蛋白质组；2)确定单个细胞中多个转铁蛋白丰度的变化如何启动并逐渐加强沿红系轨迹的细胞命运决定；以及3)红系生成TRN的计算分析、建模和验证。对于第一个目标，定量质谱仪(MS)方法将被用来测量健康供者的HSPC体外红细胞生成过程中Tf蛋白质组的绝对水平。对于第二个目标，将使用互补的CyTOF和靶向MS蛋白质组学方法来估计单细胞中的TF蛋白丰度，并将使用其他单细胞组学技术来测量在体外红细胞生成过程中基因表达和TF基因组结合的变化。对于第三个目标，将利用TF蛋白丰度的测量和其他与转录相关的组学数据来建立红细胞生成的TRN模型。根据我们最近的结果，将对在红细胞生成过程中涉及转录调控的转录因子进行功能验证。这种方法是创新的，因为它使用了单细胞和批量蛋白质组学方法的新组合来量化原代人类细胞红细胞生成过程中大量的TF，并使用这些数据进行综合TRN建模。这项拟议的研究意义重大，因为它将阐明控制红细胞生成的复杂调控过程。最终，这些知识有可能指导新的治疗方法的设计，以重新建立贝型地中海贫血症患者适当的贝珠蛋白表达。

Erythropoiesis is a dynamic process governed by quantitative changes in the relative levels of transcription fac-tors (TFs). Due to the current paucity of quantitative data on the proteins that constitute the transcriptional regulatory network (TRN), most models of erythropoiesis are based primarily on mRNA measurements and do not typically consider changes in the protein levels of specific TFs. This significantly limits the understanding of erythropoiesis and other transcriptionally regulated processes such as ß-globin expression, ultimately impinging on the capacity to correct hemoglobin disorders. The long-term goal is to decipher the TRN that controls erythropoiesis in health and disease. The objective of this proposal is to significantly expand our TRN model for cell fate decision during erythropoiesis by integrating dynamic bulk and single cell TF protein abundance measurements with other transcription-relevant -omics data. The central hypothesis is that relative protein levels of TFs are critical parameters in the establishment of gene expression programs during the continuum of differentiation, and that erythropoiesis is driven by graded changes in the relative amounts of specific combinations of TFs. The rationale is that integration of the dynamic and quantitative nature of the TF proteome into an expanded TRN of erythropoiesis will yield a model with improved predictive power which will serve as a benchmark for healthy erythropoiesis against which to compare erythroid-related disease states, and will facilitate the identification of pharmacological agents to restore normal erythropoiesis. Three specific aims have been designed: 1) Absolute quantification of the TF proteome during erythropoiesis; 2) Determine how changes in the abundance of multiple TFs in single cells initiate and progressively reinforce cell fate decisions along the erythroid trajectory; and 3) Computational analysis, modeling and validation of the erythropoiesis TRN. For the first aim, quantitative mass spectrometry (MS) approaches will be used to measure absolute levels of the TF proteome during ex vivo erythropoiesis of HSPCs derived from healthy donors. For the second aim, complementary CyTOF and targeted-MS proteomic approaches will be used to estimate TF protein abundances in single cells, and other single cell –omics technologies will be used to measure changes in gene expression and TF genomic binding during ex vivo erythropoiesis. For the third aim, TRN models of erythropoiesis will be built utilizing measurements of TF protein abundances, and other transcription-relevant –omics data. Functional validation will be performed for TFs that have been implicated in transcriptional control during erythropoiesis based on our recent results. The approach is innovative because it uses a novel combination of single cell and bulk proteomics methodologies to quantify large numbers of TFs during erythropoiesis in primary human cells and uses the data for integrative TRN modeling. The proposed research is significant because it will illuminate complex regulatory processes that control erythropoiesis. Ultimately, such knowledge has the potential to guide the design of new therapeutics to re-establish proper ß-globin expression in ß-thalassemic patients.