Core C: Single Cell Phenotyping

核心 C：单细胞表型分析

• 批准号: 10317010
• 负责人: RUTH R MONTGOMERY
• 金额: $ 95.5万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-05-14 至 2021-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10317010
• 关键词: Antibodies; Behavior; Biological Assay; Biopsy; Blood; COVID-19; Cells; Cerebrospinal Fluid; Clinical; Collaborations; Computer Analysis; Custom; Cytometry; Data; Data Analyses; Data Management Resources; Detection; Disease; Disease Outcome; Flow Cytometry; Fluorescence; Gene Expression Profile; Genetic Transcription; Goals; Heavy Metals; Human; Image Cytometry; Immune; Immune response; Immunologic Markers; Immunologics; Immunophenotyping; Infection; Investigation; Ions; Label; Measurement; Measures; Molecular Profiling; National Institute of Allergy and Infectious Disease; Pathogenesis; Pathway interactions; Patients; Phenotype; Population; Reporting; Reproducibility; Research Project Grants; Resources; Sampling; Services; Signal Pathway; Signal Transduction; Specificity; Sputum; Standardization; Surface; Synovial Fluid; System; Techniques; Technology; Time; Tissues; Visualization; base; cell type; cohort; comparative; computerized tools; data integration; data management; data repository; dimensional analysis; erythema migrans; exhaustion; feeding; high dimensionality; human disease; innovation; interest; new technology; pathogen; response; sharing platform; single cell analysis; single cell technology; single-cell RNA sequencing; targeted sequencing; transcriptome; transcriptome sequencing; web interface

Abstract We propose to use a systems approach that combines well-defined cohorts with unbiased large-scale profiling to elucidate signatures defining immune responsiveness in the context of divergent disease outcomes. Standardization, both at the assay and analytical levels, will allow comparisons and integration of data across projects. To maximize the immune profiles of samples generated in our Projects—and the shared analysis and interpretation of data— we propose a Single Cell Phenotyping Core to conduct and analyze multiparameter immune markers using shared platforms. The platforms of the Core include mass cytometry (CyTOF) for multiparameter single cell analysis of samples from the Research Projects (Aim 1). This new technology, which overcomes many of the limitations of fluorescence-based flow cytometry, provides unprecedented cellular analysis of multiple cell populations simultaneously and is a powerful technique for translational investigations. Our core will support seamless web interface and in depth computational analysis needs of the projects (Aim 2). In addition, we will use nanowell-based single-cell analysis for multispectral imaging cytometry (MuSIC) to measure, analyze and report the surface expression of up to 16 markers on immunocytes in sorted populations of interest or in sparse samples, including synovial fluid and EM biopsies (Aim 3). Finally, we will extend the capabilities of the nanowell platform for performing single-cell RNA-sequencing, which provides a unique and unbiased approach for resolving heterogeneous subsets of immune cells (Aim 4). Array-wide RNA- sequencing of targeted cell types or sparse samples is an innovative platform to probe the intrinsic differences between cells of interest and to refine the molecular signatures of cells implicated in disease.

摘要 我们建议使用一个系统的方法，结合明确界定的队列与无偏的大规模 分析以阐明在不同疾病背景下定义免疫应答的特征 结果。在含量测定和分析水平上的标准化将允许进行比较， 跨项目的数据整合。为了最大限度地提高我们的样本的免疫特性， 项目-以及共享的数据分析和解释-我们提出了一个单细胞表型分析 核心使用共享平台进行和分析多参数免疫标记。的政策取向 核心包括用于对样本进行多参数单细胞分析的质谱细胞术（CyTOF）， 研究项目（目标1）。这项新技术克服了 基于荧光的流式细胞术，提供了前所未有的多个细胞群的细胞分析 同时，是一个强大的翻译研究技术。我们的核心将支持 无缝的网络界面和深入的计算分析项目的需要（目标2）。此外，本发明还提供了一种方法， 我们将使用用于多光谱成像细胞术（MuSIC）的基于细胞的单细胞分析来测量， 分析并报告分选的免疫细胞群体中免疫细胞上多达16种标志物的表面表达， 感兴趣或稀疏样本，包括滑液和EM活检（目标3）。最后，我们将扩展 用于进行单细胞RNA测序的PICELL平台的能力，其提供了独特的 和无偏的方法来解决免疫细胞的异质子集（目的4）。全阵列RNA- 靶向细胞类型或稀疏样品的测序是一种创新平台， 目的是为了确定感兴趣的细胞之间的差异，并细化与疾病有关的细胞的分子特征。