Development of an emulsion-based method for repertoire-scale paired-chain T cell receptor sequencing

开发基于乳剂的全谱配对链 T 细胞受体测序方法

基本信息

批准号：
10371136
负责人：
Michael Birnbaum
金额：
$ 18.84万
依托单位：
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
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：
2021-03-12 至 2023-02-28
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10371136
关键词：
Algorithms Antigen Receptors Antigen Targeting Antigens Autoimmunity Bar Codes Benchmarking CD4 Positive T Lymphocytes CD8B1 gene Cell physiology Cells Computing Methodologies Cytotoxic T-Lymphocytes DNA Development Disease Emulsions Equipment Event Functional disorder Genes Genetic Recombination Genome Genomics Graft Rejection Health Human Hybrids Immune System Diseases Immune system Immunity Immunology Individual Infection Infection Control Innate Immune Response Link Major Histocompatibility Complex Malignant Neoplasms Mediator of activation protein Methodology Methods Modification Morbidity - disease rate Oligonucleotides Peptides Process Proteins Reagent Resources Sampling Series Specificity T Chain T cell receptor repertoire sequencing T-Cell Development T-Cell Receptor T-Lymphocyte T-cell receptor repertoire Techniques Technology Time Transcript V(D)J Recombination antigen-specific T cells base cell transformation combinatorial cost cost estimate data quality droplet sequencing immune function insight next generation sequencing novel novel strategies polypeptide response single cell analysis

项目摘要

Project Abstract T cell recognition of peptide-Major Histocompatibility Complexes is a key determinant of response to infection, cancer, and autoimmunity. While there have been recent technological advances that have enabled better tracking and analysis of the T cell receptor repertoire, these approaches are extremely resource intensive and/or have key technical limitations. Here, we propose a novel method that combines emulsion-based partitioning and computational sequence deconvolution to enable large-scale determination of the naive T cell repertoire at modest cost (estimated to be ~$1/3,000 cells at current reagent and sequencing costs, as compared to the ~$1/cell for current techniques). We will first develop and validate the experimental modifications to establish this technique, including development of low-cost DNA barcoding beads, formation of cell/bead emulsions, and efficient conversion and capture of TCR transcripts. We will then extend our previous computational approach to deconvolute pools of TCRα/TCRβ sequences, and validate our method on T cells obtained from healthy donors. In addition, we will extend our methodology to include oligonucleotide tagged pMHC multimers, enabling repertoire-scale tracking of TCRα/TCRβ-pMHC pairings. Together, these technologies will enable efforts to track the T cell repertoire at extremely large scale, an advance necessary for both mechanistic immunology and computational prediction of antigen reactivity.

项目摘要 T细胞识别肽 - 莫约尔组织相容性复合物是对感染的反应的关键决定剂，癌症和自身免疫性。虽然最近有技术进步可以更好 T细胞受体库的跟踪和分析，这些方法是极其资源密集型和/或有关键的技术限制。在这里，我们提出了一种新颖的方法，该方法结合了基于乳液的分区和计算序列反卷积以实现对天真T细胞库的大规模测定相比〜$ 1/cell用于当前技术）。我们将首先开发并验证实验修改以建立该技术，包括开发低成本DNA条形码珠，细胞/珠乳液的形成和 TCR转录本的有效转换和捕获。然后，我们将扩展我们以前的计算方法到TCRα/TCRβ序列的反应池，并验证我们从健康的T细胞上获得的方法捐助者。此外，我们将扩展我们的方法，以包括寡核苷酸标记的PMHC多聚体，启用 TCRα/TCRβ-PMHC配对的曲目规模跟踪。这些技术将共同努力追踪 T细胞库在极大的规模上，这是机械免疫学和抗原反应性的计算预测。