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

• 批准号: 10375354
• 负责人: Georg Seelig
• 金额: $ 40.09万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 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/10375354
• 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; Cytometry; DNA; Detection; Disease; Disease Marker; Excision; Flow Cytometry; Future; Gene Expression; Genomics; Goals; Human; Immune; Immune response; Immunology; Immunophenotyping; Immunotherapy; Joints; Label; Libraries; Ligation; Malignant Neoplasms; Malignant neoplasm of lung; 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; base; cell determination; cell type; combinatorial; cost; experimental study; high throughput technology; 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

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.

单细胞免疫库测序可以提供关于适应性免疫应答的宝贵信息。 免疫系统疾病和治疗。然而，现有的用于配对T细胞或B细胞受体的方法， (TCR/BCR）序列仍然是相对低的吞吐量和昂贵的。这些限制是 对于旨在将联合收割机受体序列与互补细胞类型信息结合的方法来说尤其迫切， 如细胞表面蛋白表达所定义。在这里，我们建议开发和验证一个负担得起的高- 基于细胞表面同时配对TCR和确定细胞状态的吞吐量技术 蛋白质表达所提出的方法建立在基于分裂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。的 组合索引方法使用完整的固定细胞或细胞核作为“反应容器”来物理划分 目的核酸的分离，并绕过对微流体细胞分离的需要。细胞经历多轮的 拆分、条形码化和重新合并，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SPLiT-seq工作流程，用于DNA条形码抗体和特异性检测。 TCR转录本。我们将展示该技术的规模扩大，以在一个单一的细胞测序数百万个细胞。 实验-至少一个数量级以上的吞吐量比目前可用的方法。通过 将组合索引与细胞表面标志物的靶向检测相结合，这可以提供高的 有限测序读数的分辨率细胞谱，以及适应性免疫的类似靶向检测 库，我们也将优化测序效率，我们将克服实际限制 排序成本。将该方法的投入量、精度和成本与流量进行定量比较 流式细胞术、质谱流式细胞术、批量TCR测序和10 x Genomics单细胞测序平台。一个 大规模评估TCR序列和细胞谱的能力将允许追踪克隆关系 以及T或B细胞浸润肿瘤和外周血中的相应细胞谱。该分析将 为T细胞和B细胞在肿瘤特异性应答中的作用提供了机制性见解， 治疗相关的T和B细胞受体。为了证明癌症研究的实用性，我们将应用此 研究配对的人类肿瘤和血液样本T细胞的方法， 切除手术