Identifying Rare Subtypes of CD8 T-cells Using Single Cell Reactors
Identifying Rare Subtypes of CD8 T-cells Using Single Cell Reactors
批准号:
9086041
负责人:
YONGWON CHOI
金额:
$15.38万
依托单位国家:
美国
项目类别:
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-04-15 至 2018-03-31
关键词:
AdoptionAreaArtsBacteriaBiological AssayCD8B1 geneCell RespirationCell SeparationCell SurvivalCell physiologyCellsCellular Metabolic ProcessCharacteristicsComputing MethodologiesCoupledDetectionDevicesDiseaseDyesEncapsulatedFatty AcidsFluorocarbonsFutureGenesGenetic ProgrammingGrowthHomeostasisImmuneImmune responseImmunotherapyIndividualInfectionInflammatoryLeadLectinLinkMalignant NeoplasmsMeasuresMemoryMetabolicMicrofluidic MicrochipsMicrofluidicsModelingMolecularMolecular ProfilingOilsPathway interactionsPhasePhysiologicalPopulationPopulation DynamicsProliferatingRoleSorting - Cell MovementSpeedStagingSurfaceSystemT cell differentiationT cell responseT-Cell ActivationT-LymphocyteT-Lymphocyte SubsetsTRAF6 geneTechniquesTestingVariantVirusWithdrawaladapter proteinadaptive immunitybasecell mediated immune responsecell typecytokinedetectorfatty acid metabolisminterestmetabolic profilemolecular markernovelprecursor cellprogramspublic health relevancereceptorresponsesecondary infectiontranscription factortranscriptometranscriptome sequencingtranscriptomics
中文摘要
描述(由申请人提供):了解免疫细胞的分子特征,如记忆细胞,对于理解适应性免疫反应至关重要。特别是,关于代谢变化是否能够驱动T细胞分化(如果是,如何驱动),或者更确切地说,这些变化是否只是在分化过程中遇到的外部因素(例如细胞因子)反应的副产品,我们仍然存在差距。此外,目前尚不清楚脂肪酸代谢机制的调节与关键细胞命运决定(S)之间是否存在直接的因果关系,该决定决定了从效应器到记忆细胞的转变,以及单个细胞的代谢状态是否可以与更大的群体动态相关。我们寻求确定一组分子标记,以便进行未来的功能测试,并确定这一至关重要的细胞类型的命运决定途径。为了克服单细胞分子图谱和标准代谢分析的局限性,我们将开发一种新型的微流控设备,使快速的单细胞代谢图谱和分选与单细胞转录组图谱相结合。利用这一设备,我们将根据CD8T细胞的代谢特征分离稀有的亚群,并为每个亚群确定分子标记。在目标1中,我们将开发一种用于快速单细胞代谢图谱和分选的微流控系统。具体地说,一种高速氟碳(FC)油
将开发与代谢功能染料探针和高含量检测器分选系统耦合的液滴细胞微流控装置。该设备将在速度、捕获效率、细胞活力、高速检测和分选方面进行优化。在目标2中,我们将使用单细胞RNAseq在应答程序中识别CD8T细胞亚群中的分子标记。为了实现这一目标,我们将把微流控设备与精选的功能染料结合起来,以表征单个细胞的代谢状态。代谢读数的分布将通过计算方法进行分析,以确定不同的亚群。这些代谢特征将被微流控设备以分类模式用于对细胞进行选通,由此产生的细胞亚群将通过单细胞RNAseq进行分析,以确定每个亚型的分子标记。这项研究的结果将导致未来对识别的分子在T细胞反应动力学中的作用的研究。了解T细胞功能亚型的分子基础不仅将增强我们对身体对疾病的反应的了解,还将导致在癌症免疫治疗等领域的翻译应用。
英文摘要
DESCRIPTION (provided by applicant): Understanding the molecular characteristics of immune cells, such as memory cells, is critical for understanding adaptive immune response. In particular, gaps remain concerning our understanding of whether metabolic changes can drive T cell differentiation (and if so, how), or rather, if these changes are simply by-products of responses to external factors (e.g., cytokines) encountered during the course of differentiation. Further, it remains unclear whether there exists a direct causal relationship between modulation of the fatty acid metabolizing machinery and the critical cell fate decision(s) dictating the transition from an effector to a memory cell, and whether metabolic states in individual cells can be correlated with larger population dynamics. We seek to identify a panel of molecular markers will allow future functional testing and identification of fate decision pathways for this criticaly important cell type. To overcome the limitations of single cell molecular profiling and standard metabolic assays, we will develop a novel microfluidics device that will enable rapid single cell metabolic profiling and sorting coupled to single cell transcriptome profiling. Utilizing this devie, we will isolate rare subpopulations of CD8 T cells by their metabolic signatures and identify molecular markers for each subpopulation. In Aim 1, we will develop a microfluidics system for rapid single cell metabolic profiling and sorting. Specifically, a high-speed fluorocarbon (FC) oil
droplet cell encapsulating microfluidics device coupled to metabolic functional dye probes and high-content detector sorting system will be developed. The device will be optimized for speed, capture efficiency, cell viability, high-speed detection, and sorting. In Aim 2, we will identify molecular markers in sub-population of CD8 T cells during response program using single cell RNASeq. To achieve this aim, we will couple the microfluidics device with select functional dyes to characterize individual cell's metabolic states. The profiles of the metabolic readouts will be analyzed by computational methods to identify distinct subpopulations. These metabolic signatures will be used to gate the cells by the microfluidics device in a sorting mode and the resulting subpopulations of cells will be analyzed by single cell RNASeq to identify molecular markers for each subtype. The results of this study will lead to future studies on the role of identified molecules in T cell response dynamics. Understanding the molecular basis of T cell functional subtypes will not only enhance understanding of our body's response to diseases, it will lead to translational applications in areas such as cancer immune-therapy.
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