Transcriptional Control During Erythropoiesis

红细胞生成过程中的转录控制

• 批准号: 10398185
• 负责人: Marjorie Carole Brand
• 金额: $ 63.29万
• 依托单位: INSTITUTE FOR SYSTEMS BIOLOGY
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-16 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10398185
• 关键词: Adult; Automobile Driving; Benchmarking; Binding; Blood; Cell Fate Control; Cell Surface Proteins; Cell model; Cell physiology; Cells; Chromatin; Complex; Computer Analysis; Data; Disease; Erythrocytes; Erythroid; Erythroid Cells; Erythropoiesis; FLI1 gene; Gene Expression; Genes; Genetic Transcription; Genomics; Goals; Health; Hematopoietic stem cells; Hemoglobin; Histones; Human; Joints; Knowledge; Mass Spectrum Analysis; Measurement; Measures; Messenger RNA; Methodology; Methods; Mission; Modeling; Nature; Outcome; Patients; Pharmacology; Population; Process; Production; Proteins; Proteome; Proteomics; Proxy; Public Health; Regulation; Research; Role; Specific qualifier value; System; Technology; Testing; Time; Transcript; Transcriptional Regulation; Umbilical Cord Blood; United States National Institutes of Health; Validation; Work; base; beta Globin; beta Thalassemia; comparative; design; dosage; experimental study; fetal; genome-wide; histone modification; human model; improved; in vivo; innovation; insight; network models; novel; novel therapeutic intervention; novel therapeutics; progenitor; programs; temporal measurement; transcription factor; transcription regulatory network; transcriptome

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.

红细胞生成是一个受转录因子相对水平变化控制的动态过程。由于目前缺乏有关构成转录调控网络（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TF蛋白质水平的变化。这显著限制了对红细胞生成和其他转录调节过程（如β-珠蛋白表达）的理解，最终影响了纠正血红蛋白病症的能力。长期目标是破译TRN，控制红细胞生成的健康和疾病。该提案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，显着扩展我们的TRN模型用于红细胞生成期间的细胞命运决定。中心假设是，相对蛋白水平的TF是关键参数，在建立基因表达程序在分化的连续过程中，红细胞生成是由梯度变化的TF的特定组合的相对量。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中将产生具有改善的预测能力的模型，该模型将用作健康红细胞生成的基准，与之比较红细胞相关的疾病状态，并将促进鉴定恢复正常红细胞生成的药理学试剂。已经设计了三个具体目标：1）在红细胞生成期间TF蛋白质组的绝对定量; 2）确定单细胞中多种TF丰度的变化如何启动并沿着红细胞轨迹逐渐加强细胞命运决定;和3）红细胞生成TRN的计算分析、建模和验证。对于第一个目标，将使用定量质谱法（MS）来测量来自健康供体的HSPC的离体红细胞生成期间TF蛋白质组的绝对水平。对于第二个目标，互补的CyTOF和靶向MS蛋白质组学方法将用于估计单细胞中TF蛋白质丰度，并且其他单细胞组学技术将用于测量离体红细胞生成期间基因表达和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转录相关组学数据建立红细胞生成的TRN模型。根据我们最近的结果，将对在红细胞生成过程中参与转录控制的TF进行功能验证。该方法是创新的，因为它使用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中红细胞生成期间的大量TF，并使用数据进行综合TRN建模。这项研究意义重大，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疗法的设计，以在β地中海贫血患者中重新建立适当的β珠蛋白表达。