An integrated multiplexed genomic assay for low input clinical samples1

 描述(申请人提供)：人类免疫系统的异质性对于保护我们免受无数病原体的侵袭是必不可少的，但也带来了测量挑战，因为我们通常必须将样本深入分析为异质混合物，或者只测量单细胞中的几个预先选择的变量。为了了解限制性临床免疫分离株的组成及其与疾病的关系，我们必须将基因组图谱的广度与单细胞分析的分辨率结合起来。新兴的单细胞图谱方法，如单细胞RNA-SEQ(scRNA-Seq)，为克服这些挑战提供了一个非同寻常的机会。在最近的概念验证研究中，我们将scRNA-Seq应用于小鼠免疫和人类肿瘤样本：我们开发了生成和分析scRNA-Seq数据的实验和计算方法，并使用它们检查来自不同系统和样本的50,000个细胞。然而，为了实现这些策略在翻译免疫学方面的前景，我们必须创建、优化和实施一个scRNA-Seq平台，该平台可以部署在从核心活检到FNAs再到体液的各种临床样本中。在这里，我们将优化当前的方案，以创建标准操作程序(SOP)，并将单个组件合并到一个标准化的管道中，该管道可以提供给免疫学社区。我们将包装和发布scRNA-Seq的SOP，并实现将单细胞基因组数据与更传统的免疫学测量相联系的协议，如FACS或CyTOF(目标1)。从我们积极的临床合作伙伴(权、佐科斯、沃克、泽维尔)那里，我们将收到各种IBD、HIV、TB和SLE的临床标本(包括活组织检查、PBMC、滑液)。我们将制定和部署实验方案，最好地从每种样本类型中提取分解的单个细胞，以便成功地进行scRNA-Seq(目标2)。我们将优化我们现有的QC、分析和可视化计算管道，将它们包装成一个精简的包，并将其作为公开可用的工具发布(AIM 3)。我们的项目将创建一个强大的单细胞转录组分析工作流程，适用于不同的临床样本类型，并可供整个免疫学社区使用。

 DESCRIPTION (provided by applicant): The heterogeneity of the human immune system is essential for protecting us against myriad pathogens, but also poses measurement challenges, since we typically must either deeply profile samples as heterogeneous mixtures or measure only a few pre-selected variables in single cells. To understand the composition of limiting clinical immune isolates and their relation to disease, we must combine the breadth of genomic profiling with the resolution of single cell assays. Emerging single-cell profiling methods, such a single-cell RNA-seq (scRNA-Seq), provide an extraordinary opportunity to overcome these challenges. In recent proof-of-concept studies, we applied scRNA-Seq to murine immune and human tumor samples: we developed experimental and computational approaches for generating and analyzing scRNA-Seq data, and used them to examine >50,000 cells from diverse systems and samples. However, to realize the promise of these strategies for translational immunology, we must create, optimize and implement a scRNA-Seq platform that can be deployed for diverse clinical samples from core biopsies to FNAs to fluids. Here, we will optimize current protocols to create standard operating procedures (SOPs) and merge individual components into a standardized pipeline that can be provided to the immunology community. We will wrap and release SOPs for scRNA-Seq and realize protocols for linking single cell genomic data to more conventional immunology measurement, such as FACS or CyTOF (Aim 1). From our driving clinical collaborators (Kwon, Tsokos, Walker, Xavier), we will receive diverse clinical specimens (including biopsies, PBMCs, synovial) in IBD, HIV, TB, and SLE. We will develop and deploy experimental protocols to best extract disaggregated individual cells from each sample type for successful scRNA-Seq (Aim 2). We will optimize our existing computational pipelines for QC, analysis and visualization, wrap them into a streamlined package, and release it as a publicly available tool (Aim 3). Our project will create a robust workflow for single-cell transcriptome analysis applicable across diverse clinical sample types, and accessible to the entire immunology community.