Comprehensive characterization of immune signaling networks in single-cells by joint quantification of proteins, protein complexes and mRNA

通过蛋白质、蛋白质复合物和 mRNA 的联合定量来全面表征单细胞中的免疫信号网络

• 批准号: 10636695
• 负责人: Marcus Ramsay Clark
• 金额: $ 67.31万
• 依托单位: UNIVERSITY OF CHICAGO
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-02-17 至 2028-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10636695
• 关键词: Adaptor Signaling Protein; Antigens; Autoimmunity; B cell differentiation; B-Cell Activation; B-Cell Antigen Receptor; B-Lymphocytes; Bar Codes; CD19 gene; CD22 gene; Cell physiology; Cells; Clinical Research; Complex; DNA; Data; Dendritic Cells; Development; Drug resistance; Endothelial Cells; Epithelial Cells; Event; Evolution; Exclusion; Gene Expression; Gene Expression Regulation; Genetic Transcription; Goals; Hematopoietic; Hematopoietic stem cells; Heterogeneity; Human; IRF3 gene; Immune; Immune signaling; Immunity; Individual; Infection; Inflammatory; Joints; Lung; MAP Kinase Gene; MAPK8 gene; MHC Class II Genes; Macrophage; Malignant Neoplasms; Maps; Measurement; Measures; Messenger RNA; Methods; Modeling; Mus; Noise; PIK3CG gene; Pathway interactions; Peripheral Blood Mononuclear Cell; Phosphotransferases; Population; Post-Translational Protein Processing; Process; Productivity; Proliferating; Proteins; Proteomics; RNA; Receptor Signaling; Rest; Signal Pathway; Signal Transduction; Signaling Protein; Specificity; Structure of germinal center of lymph node; Surface; T-Lymphocyte; TLR4 gene; Technology; Testing; Toll-like receptors; cell type; cytokine; experimental study; extracellular; granulocyte; granulocyte-monocyte progenitors; hematopoietic differentiation; immune activation; improved; insight; live cell imaging; mathematical model; member; monocyte; p38 Mitogen Activated Protein Kinase; progenitor; programs; protein complex; protein expression; receptor; response; single cell analysis; single cell mRNA sequencing; single cell sequencing; trafficking; transcription factor; transcriptome; tumor

Accurate and multiplexed characterization of proteins is essential to basic and clinical studies in immunity, infection, development, and cancer. Many processes in immune development, signal activation, and drug resistance are driven by a small subset of cells and variable activation of signaling pathways, necessitating single-cell measurements. Currently, there is high precision and throughput in measuring DNA/RNA in single cells, however a major technological gap exists in the measurement of proteins and especially their complexes in individual cells. High-throughput methods combining simultaneous measurement of proteins, complexes and mRNA are needed to better understand and model individual cellular responses, and to discover new cell states and functions. Our proposal has two, equally important, and synergistic goals: a) optimize/adapt a broadly applicable and practical technology that simultaneously measures proteins, protein-complexes and mRNA in thousands of individual cells (Aim 1), and b) study several key hypotheses on the function and evolution of signaling networks during immune development (Aims 2 and 3). Our technology, called Intracellular Proximity- Sequencing (iProx-seq), uses DNA barcoded proximity probes and single-cell sequencing for multiplexed measurement of proteins and their complexes. The number of protein complexes measured by iProx-seq scales quadratically: Targeting 100 proteins will enable the measurement of 5500 potential protein complexes in each cell. Protein quantification by sequencing has the additional benefit of transcriptome-wide mRNA measurements in the same cell, all using a robust and widely used sequencing pipeline. Extensive preliminary data we present demonstrated the feasibility of our entire technical approach and mechanistic studies. We will combine iProx-seq, live cell imaging and mathematical modeling and study key hypotheses in the differentiation of hematopoietic stem cells (HSCs) and B cells in the germinal center (see Aims 2 and 3). We will measure signaling receptors, adaptor proteins, transcription factors, cytokines, kinases, and protein modifications, and comprehensively characterize immune signaling networks NF-κB, MAPK, PI3K and IRF3 in single human and mouse HSCs, monocyte derived macrophages, granulocyte-monocyte progenitors, and germinal center B cells. Specific questions we will answer include: How do changes in receptor levels, receptor- coreceptor complexes, and intracellular complex formation explain single macrophage sensitivity to inflammatory TLR signals? How does the developmental remodeling of protein networks NF-κB, MAPK, PI3K and IRF3 regulate signal specificity across the hematopoietic lineage? What are the distinct proteomic and signaling states in the germinal center, and how do protein networks regulate the differentiation of B cells? Our proposal will result in a powerful and practical single-cell analysis technology and improved insight on the function and evolution of protein networks in immunity. Our results will make significant impact into the understanding of immune development, immune activation, and emergence of drug resistance.

蛋白质的准确和多重表征对于免疫学的基础和临床研究至关重要， 感染、发育和癌症。免疫发育、信号激活和药物治疗中的许多过程 耐药性是由一小部分细胞和信号通路的可变激活驱动的， 单细胞测量。目前，在单个细胞中测量DNA/RNA具有高精度和高通量， 然而，在蛋白质，特别是其复合物的测量方面存在着重大的技术差距 in individual个别cells细胞.结合蛋白质、复合物和蛋白质的同时测量的高通量方法 需要mRNA来更好地理解和模拟个体细胞反应，并发现新的细胞状态 和功能我们的建议有两个同样重要的协同目标：a）优化/适应广泛的 适用和实用的技术，同时测量蛋白质，蛋白质复合物和mRNA， 成千上万的单个细胞（目标1），和B）研究几个关键的假设的功能和演变， 免疫发育过程中的信号网络（目的2和3）。我们的技术叫做细胞内邻近 测序（iProx-seq），使用DNA条形码邻近探针和单细胞测序进行多重测序。 蛋白质及其复合物的测量。通过iProx-seq量表测量的蛋白质复合物数量 二次：靶向100个蛋白质将能够测量每个蛋白质中的5500个潜在蛋白质复合物。 cell.通过测序进行蛋白质定量具有转录组范围mRNA测量的额外益处 在同一个细胞中，所有这些都使用了一个强大的和广泛使用的测序管道。我们提供的大量初步数据 证明了我们整个技术方法和机理研究的可行性。 我们将结合联合收割机iProx-seq，活细胞成像和数学建模，并研究关键假设， 造血干细胞（HSC）和B细胞在生殖中心的分化（参见目的2和3）。我们将 测量信号受体、衔接蛋白、转录因子、细胞因子、激酶和蛋白质 修饰，并全面表征免疫信号网络NF-κB，MAPK，PI 3 K和IRF 3在 单个人和小鼠HSC、单核细胞衍生的巨噬细胞、粒细胞-单核细胞祖细胞，以及 生发中心B细胞。我们将回答的具体问题包括：如何改变受体水平，受体- 辅助受体复合物和细胞内复合物的形成解释了单个巨噬细胞对炎症的敏感性。 TLR信号？NF-κB B、MAPK、PI 3 K和IRF 3在蛋白质网络的发育重构中的作用 调节整个造血谱系的信号特异性？不同的蛋白质组和信号状态是什么 以及蛋白质网络如何调节B细胞的分化？我们的建议将 从而形成了强大而实用的单细胞分析技术，并提高了对功能的了解， 免疫系统中蛋白质网络的进化我们的研究结果将对理解 免疫发育、免疫激活和抗药性的出现。