Transcriptional Control During Erythropoiesis

红细胞生成过程中的转录控制

• 批准号: 10617700
• 负责人: Marjorie Carole Brand
• 金额: $ 61.65万
• 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/10617700
• 关键词: Adult; Anemia; 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; 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; 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; pharmacologic; progenitor; programs; stem cells; 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.

红细胞生成是一个动态过程，受转录因子（TFs）相对水平的定量变化控制。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的测量，通常不考虑特定tf蛋白水平的变化。这极大地限制了对红细胞生成和其他转录调控过程（如ß-球蛋白表达）的理解，最终影响了纠正血红蛋白紊乱的能力。长期目标是破译在健康和疾病中控制红细胞生成的TRN。本提案的目的是通过整合动态体和单细胞TF蛋白丰度测量与其他转录相关组学数据，显著扩展我们的红细胞生成过程中细胞命运决定的TRN模型。中心假设是，在分化连续过程中，tgf的相对蛋白水平是建立基因表达程序的关键参数，并且红细胞生成是由tgf的特定组合的相对量的分级变化驱动的。其基本原理是，将TF蛋白质组的动态和定量特性整合到扩大的红细胞生成TRN中，将产生具有改进预测能力的模型，该模型将作为健康红细胞生成的基准，用于比较红细胞相关疾病状态，并将有助于确定恢复正常红细胞生成的药物。设计了三个具体目标：1)红细胞生成过程中TF蛋白组的绝对定量；2)确定单个细胞中多个tf丰度的变化如何启动并逐步加强红细胞轨迹上的细胞命运决定；3)红细胞TRN的计算分析、建模和验证。对于第一个目标，定量质谱（MS）方法将用于测量来自健康供体的造血干细胞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，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蛋白的丰度，其他单细胞组学技术将用于测量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转录相关的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涉及转录控制的tf进行功能验证。该方法是创新的，因为它使用单细胞和大量蛋白质组学方法的新颖组合来量化人原代细胞红细胞生成过程中的大量tf，并使用数据进行综合TRN建模。提出的研究意义重大，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疗法的设计，以在地中海贫血患者中重新建立适当的ß-珠蛋白表达。