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.

单细胞免疫毒品测序可以提供有关自适应响应的宝贵信息免疫系统疾病和治疗。但是，现有的配对T细胞或B细胞接收器的方法（TCR/BCR）单细胞水平的序列仍然相对较低且昂贵。这些限制是特别是旨在将接收器序列与完整细胞类型信息相结合的方法的急性，由细胞表面蛋白表达定义。在这里，我们建议开发和验证负担得起的高级用于简单配对TCR和基于细胞表面的细胞状态的吞吐量技术蛋白表达。所提出的方法建立在基于分裂池连接的转录组测序上（Split-Seq），我们最近开发的单细胞测序方法基于组合索引。这组合索引方法使用完整的固定细胞或核作为“反应血管”进行物理分配感兴趣的核酸并绕过对微流体细胞分离的需求。细胞经历多轮分裂，条形码和重新播放，为每个标记的分子生成细胞特异性条形码组合。在这里，我们将扩展拆分式工作流程，以与DNA-Barcoded抗体一起使用，并用于特定检测 TCR转录本。我们将展示该技术的扩展，以对单个单个细胞进行数百万个单元实验 - 至少比当前可用的方法大的吞吐量大。经过将组合索引与针对细胞表面标记的靶向检测相结合，这可以提供高分辨率的细胞曲线具有有限的测序读取，并类似地靶向自适应免疫我们还将为测序效率进行优化的曲目，我们将克服实施的限制通过测序成本。该方法的吞吐量，准确性和成本将与流量相比细胞仪，质量细胞仪，批量TCR测序和10倍基因组学单细胞测序平台。一个能够大规模评估TCR序列和细胞轮廓，将允许跟踪克隆关系 T或B细胞的相应细胞剖面浸润肿瘤和外周血中。该分析将会提供有关T和B细胞在肿瘤特异性反应中的作用的机械见解，并允许识别历史相关的T和B细胞受体。为了证明癌症研究的实用性，我们将应用研究接受肿瘤的癌症患者配对的人类肿瘤和血液样本T细胞的方法 - 切除手术。