Unbiased visualization of human ASC subsets

人类 ASC 子集的无偏见可视化

• 批准号: 9916109
• 负责人: Lisa Borghesi
• 金额: $ 18.86万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9916109
• 关键词: Antibodies; Antibody Repertoire; B-Lymphocytes; Biological Assay; Blood; Cell physiology; Characteristics; Clone Cells; Colon; Complex; Computational algorithm; Data; Disease; Drug or chemical Tissue Distribution; Environment; Exposure to; Flow Cytometry; Genetic Transcription; Gut Mucosa; Human; Human body; Humoral Immunities; Immune response; Immunoglobulin-Secreting Cells; Immunologics; In Vitro; Individual; Infection Control; Inguinal lymph node group; Intestines; Knowledge; Lead; Link; Longevity; Lung; Lymphoid Tissue; Maintenance; Maps; Mediator of activation protein; Mucous Membrane; Normal tissue morphology; Outcomes Research; Pathway interactions; Phenotype; Phosphoproteins; Plasma Cells; Population; Protocols documentation; Publishing; Serum; Signal Transduction; Site; Structure; Surface; Testing; Tissues; Vaccines; Validation; Visualization; data visualization; differential expression; draining lymph node; high dimensionality; human tissue; ileum; immunoregulation; improved; insight; jejunum; mesenteric lymph node; microbial; next generation; novel; pathogen; programs; protein expression; residence; stem; tissue resource; transcription factor; transcriptome sequencing

Abstract: Plasma cells (PC) are responsible for maintaining serum antibody levels to pathogen. However, a comprehensive spatial map of PC subsets across tissue compartments in the human body is lacking. As a consequence, our understanding of global PC population structure across different tissues within individuals and also between different individuals is murky. Using unique and rare-to-access human tissue resources along with high-dimensional flow cytometry, will test the hypothesis that PC subset composition can be predicted by tissue site and that long-lived PC (LLPC) engage survival programs that are tailored to each site of origin. In Aim 1, we will identify known and novel PC subsets in lymphoid and mucosal tissues from normal human donors using complex flow cytometry and unbiased computational algorithms. We will integrate phenotype with signaling status and establish PC functional capabilities. In Aim 2, we will perform Next Generation RNA-Sequencing and functional assays on long-lived PCs (LLPC) derived from two distinct tissue sites in order to uncover shared versus tissue-specific survival pathways. Results from this study will reveal the global population structure of PC subsets responsible for human humoral immunity and provide insights into how PCs control infections regionally and systemically.

摘要： 浆细胞（PC）负责维持血清中病原体抗体水平。但 缺乏人体组织区室中PC亚群的综合空间图。作为 因此，我们对个体内不同组织的全球PC群体结构的理解 不同的个体之间也是模糊的。使用独特和稀有的人体组织资源 沿着高维流式细胞术，将检验PC亚群组成可以被 根据组织部位预测，长寿命PC（LLPC）参与针对每个部位的生存计划 混元在目标1中，我们将从正常的淋巴和粘膜组织中鉴定已知的和新的PC亚群， 使用复杂的流式细胞术和无偏计算算法的人供体。我们将整合 表型与信号状态和建立PC功能能力。在目标2中，我们将执行Next 对来自两种不同组织的长寿命PC（LLPC）进行RNA测序和功能测定 位点，以揭示共享的与组织特异性的生存途径。这项研究的结果将揭示 负责人类体液免疫的PC亚群的全球人口结构，并提供对 PC如何控制区域和系统感染。