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Joint receptor and protein expression immunophenotyping through split-pool barcoding

通过分池条形码进行联合受体和蛋白质表达免疫表型

基本信息

批准号：
10625987
负责人：
Georg Seelig
金额：
$ 39.62万
依托单位：
UNIVERSITY OF WASHINGTON
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-04-01 至 2024-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10625987
关键词：
Acute Adaptive Immune System Antibodies B-Cell Antigen Receptor B-Lymphocytes Bar Codes Biological Assay Blood Blood specimen Bypass Cancer Patient Cell Nucleus Cell Separation Cell Surface Proteins Cell surface Cells Clonal Expansion Cytometry DNA Detection Disease Disease Marker Excision Flow Cytometry Future Gene Expression Genomics Goals Human Immune Immune response Immunology Immunophenotyping Immunotherapy Infiltration Joints Label Libraries Ligation Malignant Neoplasms Malignant neoplasm of lung Maps Methods Microfluidics Nucleic Acids Operative Surgical Procedures Phenotype Population Proteins RNA Reaction Renal carcinoma Research Resolution Reverse Transcription Role Sensitivity and Specificity Stains T cell response T-Lymphocyte Technology Therapeutic Transcript Tumor-infiltrating immune cells adaptive immune response cancer infiltrating T cells cell determination cell fixing cell type combinatorial cost experimental study high throughput technology improved indexing insight interest multimodality multiple omics multiplex detection peripheral blood protein expression receptor receptor expression response scale up sequencing platform single cell sequencing single-cell RNA sequencing targeted sequencing transcriptome transcriptome sequencing tumor tumor immunology

项目摘要

Single-cell immune repertoire sequencing can provide invaluable information about the response of the adaptive immune system to disease and therapy. However, existing approaches for pairing T-cell or B-cell receptor (TCR/BCR) sequences at the single-cell level are still relatively low throughput and costly. These limitations are particularly acute for methods that aim to combine receptor sequences with complementary cell-type information, as defined by cell-surface protein expression. Here, we propose to develop and validate an affordable high- throughput technology for simultaneous pairing of TCRs and determination of cell state based on cell surface protein expression. The proposed approach builds on Split Pool Ligation-based Transcriptome sequencing (SPLiT-seq), our recently developed single-cell sequencing method that is based on combinatorial indexing. The combinatorial indexing approach uses intact fixed cells or nuclei as ‘reaction vessels’ to physically partition nucleic acids of interest and bypass the need for microfluidic cell isolation. Cells undergo multiple rounds of splitting, barcoding, and re-pooling, generating cell-specific barcode combinations for each tagged molecule. Here, we will extend the SPLiT-seq workflow for use with DNA-barcoded antibodies and for the specific detection of TCR transcripts. We will demonstrate scaling up of the technology to sequence millions of cells in a single experiment – at least an order of magnitude greater throughput than currently available approaches. By combining combinatorial indexing with targeted detection of cell surface markers, which can provide high resolution cellular profiles with limited sequencing reads, and similarly targeted detection of adaptive immune repertoires, which we will also optimize for sequencing efficiency, we will overcome practical limitations imposed by sequencing cost. Throughput, accuracy and costs of this approach will be quantitatively compared with flow cytometry, mass cytometry, bulk TCR sequencing and the 10x Genomics single-cell sequencing platform. An ability to assess TCR sequences and cellular profiles on a large scale will permit tracking of clonal relationships and corresponding cellular profiles of T or B cells infiltrating tumors and in peripheral blood. This analysis will provide mechanistic insights into the roles of T and B cells in tumor-specific responses and allow for identification of therapeutically relevant T and B cell receptors. To demonstrate utility for the study of cancer, we will apply this approach to study paired human tumor and blood sample T cells from cancer patients undergoing tumor- resection surgeries.

单细胞免疫谱系测序可以提供有关适应性免疫应答的宝贵信息免疫系统对疾病和治疗的影响。然而，现有的配对T细胞或B细胞受体的方法单小区级别的(TCR/BCR)序列的吞吐量仍然相对较低且成本较高。这些限制是对于旨在将受体序列与互补的细胞类型信息相结合的方法尤其敏感，根据细胞表面蛋白的表达来定义。在这里，我们建议开发和验证一种负担得起的高- 基于细胞表面的TCR同时配对和细胞状态确定的吞吐量技术蛋白质表达。提出的方法建立在基于分离池连接的转录组测序的基础上 (Split-Seq)，我们最近开发的基于组合索引的单细胞测序方法。这个组合索引法利用完整的固定细胞或细胞核作为物理分割的“反应容器” 感兴趣的核酸并绕过了微流控细胞分离的需要。细胞经历多轮的分裂、条形码和重新合并，为每个标记的分子生成特定于细胞的条形码组合。在这里，我们将扩展Split-Seq工作流程，以用于DNA条形码抗体和特定检测 TCR成绩单。我们将演示该技术的扩展，以在单个细胞中对数百万个细胞进行测序实验--吞吐量至少比当前可用的方法高一个数量级。通过将组合索引与细胞表面标记的靶向检测相结合，可以提供高质量的通过有限的测序读数和类似的适应性免疫靶向检测来分辨细胞图谱曲目，我们还将对其进行优化以提高测序效率，我们将克服施加的实际限制通过测序成本。将该方法的吞吐量、准确度和成本与流量进行了定量比较细胞学、质量细胞术、批量TCR测序和10x基因组学单细胞测序平台。一个大规模评估TCR序列和细胞图谱的能力将允许跟踪克隆关系以及相应的浸润性肿瘤和外周血中T或B细胞的细胞图谱。这一分析将提供对T和B细胞在肿瘤特异性反应中的作用的机械性见解，并允许识别与治疗相关的T和B细胞受体。为了证明癌症研究的实用性，我们将应用这个研究人类肿瘤与肿瘤患者血液样本T细胞配对的方法切除手术。