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 细胞对肽-主要组织相容性复合物的识别是对感染反应的关键决定因素，虽然最近的技术进步已经实现了更好的治疗。跟踪和分析 T 细胞受体库，这些方法资源极其密集和/或在这里，我们提出了一种结合了基于乳液的分配和计算序列反卷积能够大规模确定初始 T 细胞库成本适中（与目前的试剂和测序成本相比，估计约为 1/3,000 个细胞）当前技术约为 1 美元/细胞）我们将首先开发并验证实验修改以建立。该技术，包括低成本 DNA 条形码珠的开发、细胞/珠乳液的形成，以及然后我们将扩展我们之前的计算方法。对 TCRα/TCRβ 序列池进行解卷积，并在从健康人获得的 T 细胞上验证我们的方法此外，我们将扩展我们的方法，将寡核苷酸标记的 pMHC 多聚体纳入其中，从而实现这一目标。对 TCRα/TCRβ-pMHC 配对进行全范围追踪，这些技术将有助于追踪。极其大规模的 T 细胞库，这是机械免疫学和免疫学所必需的进步抗原反应性的计算预测。