Transcriptional Control During Erythropoiesis

红细胞生成过程中的转录控制

• 批准号: 10200020
• 负责人: Marjorie Carole Brand
• 金额: $ 66.83万
• 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/10200020
• 关键词: Adult; Automobile Driving; Benchmarking; Binding; Biological Assay; Blood; Cell Fate Control; Cell model; Cell physiology; Cells; Cellular Indexing of Transcriptomes and Epitopes by Sequencing; ChIP-seq; Chromatin; Complex; Computer Analysis; Dancing; Data; Disease; Erythrocytes; Erythroid; Erythroid Cells; Erythropoiesis; FLI1 gene; Gene Expression; Genes; Genetic Transcription; Genomics; Goals; Health; Hematopoietic stem cells; Hemoglobin; Human; Joints; Knowledge; Mass Spectrum Analysis; Measurement; Measures; Messenger RNA; Methodology; Methods; Mission; Modeling; Monitor; Nature; Outcome; Patients; Pharmacology; Population; Process; Production; Proteins; Proteome; Proteomics; Proxy; Public Health; Reaction; Regulation; Research; Role; Specific qualifier value; System; Technology; Testing; Time; Transcript; Transcriptional Regulation; Umbilical Cord Blood; United States National Institutes of Health; Validation; Vision; Work; base; beta Globin; beta Thalassemia; comparative; design; dosage; experimental study; fetal; genome-wide; human model; improved; in vivo; innovation; network models; novel; novel therapeutic intervention; novel therapeutics; progenitor; programs; temporal measurement; transcription factor; transcriptome; transcriptomics

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 regu- latory 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 eryth- ropoiesis 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 measure- ments with other transcription-relevant -omics data. The central hypothesis is that the relative protein levels of TFs are critical parameters in the establishment of proper gene expression programs during the continuum of differentiation, and that erythropoiesis is driven by graded changes in the relative amounts of specific combina- tions of TFs. The rationale is that integration of the dynamic and quantitative nature of the TF proteome into an expanded TRN of erythropoiesis will result in 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 facili- tate 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 gradual 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, a high throughput quantitative mass spectrometry (MS) approach 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 combined to estimate TF protein abundances in single cells, with other single cell –omics technologies to measure changes in gene ex- pression and TF genomic binding during ex vivo erythropoiesis. Under the third aim, TRN models of erythropoi- esis 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 eryth- ropoiesis 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 illumi- nate 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，受转录因子相对水平的定量变化控制。 tors（TF）。由于目前缺乏关于构成转录调控的蛋白质的定量数据， 在细胞生长调控网络（TRN）中，大多数红细胞生成模型主要基于mRNA测量，并且不 通常考虑特定TF的蛋白质水平的变化。这极大地限制了对 红细胞生成和其他转录调节过程，如β-珠蛋白表达，最终影响 纠正血红蛋白紊乱的能力。长期目标是破译控制一切的TRN- 在健康和疾病中的作用。这个建议的目的是显着扩大我们的TRN模型的细胞 通过整合动态体积和单细胞TF蛋白丰度测量在红细胞生成期间的命运决定- 与其他转录相关组学数据进行比较。核心假设是， TF是在连续的基因表达过程中建立适当基因表达程序的关键参数。 分化，红细胞生成是由特定组合物的相对量的分级变化驱动的。 的TF。其基本原理是将TF蛋白质组的动态和定量性质整合到一个 扩展的红细胞生成TRN将导致具有改善的预测能力的模型，其将用作 健康红细胞生成的基准，以比较红细胞相关疾病状态，并将促进 鉴定恢复正常红细胞生成的药理学药物。三个具体目标是 设计：1）在红细胞生成过程中TF蛋白质组的绝对定量; 2）确定如何渐进地 单个细胞中多种TF丰度的变化启动并逐步加强细胞命运决定 沿着红细胞轨迹;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，将使用高通量定量质谱（MS）方法来测量 在源自健康供体的HSPC的离体红细胞生成期间TF蛋白质组的绝对水平。为 第二个目标是将互补的CyTOF和靶向MS蛋白质组学方法结合起来估计TF 单细胞中的蛋白质丰度，与其他单细胞组学技术来测量基因表达的变化， 在离体红细胞生成过程中表达和TF基因组结合。在第三个目标下，促红细胞生成素的TRN模型- 将利用TF蛋白丰度的测量和其他转录相关组学数据来构建ESIS。 将对在红细胞增殖过程中参与转录控制的TF进行功能验证。 根据我们最近的研究结果这种方法是创新的，因为它使用了一种新颖的组合， 细胞和大量蛋白质组学方法用于在原代人红细胞生成期间定量大量TF 细胞，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- 天然复杂的调控过程控制红细胞生成。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β-珠蛋白表达。