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.

抽象的： 浆细胞（PC）负责维持病原体的血清抗体水平。但是， 缺乏跨人体组织室跨组织室的PC子集的综合空间图。作为 结果，我们对个人内部不同组织中全球PC种群结构的理解 而且在不同的人之间也是模糊的。使用独特而罕见的人类组织资源 除了高维流式细胞仪外，还将检验以下假设：PC子集组成可以是 由组织部位预测和该长期PC（LLPC）参与每个站点量身定制的生存计划 起源。在AIM 1中，我们将确定正常淋巴机和粘膜组织中已知和新颖的PC子集 使用复杂的流式细胞仪和无偏的计算算法的人供体。我们将整合 具有信号状态并建立PC功能功能的表型。在AIM 2中，我们将执行下一个 从两个不同组织得出的长寿命PC（LLPC）上的生成RNA测序和功能测定 地点以发现共享与组织特异性生存途径。这项研究的结果将揭示 负责人类体液免疫的PC子集的全球人口结构，并为 PCS如何在区域和系统上控制感染。