Technologies for High-Throughput Mapping of Antigen Specificity to B-Cell-Receptor Sequence

B 细胞受体序列抗原特异性高通量作图技术

• 批准号: 10734412
• 负责人: Ivelin Georgiev
• 金额: $ 84.17万
• 依托单位: VANDERBILT UNIVERSITY MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-19 至 2028-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10734412
• 关键词: Address; Antibodies; Antibody Response; Antibody Specificity; Antigen Targeting; Antigens; Area; Autoimmunity; B-Cell Antigen Receptor; B-Lymphocytes; B-cell receptor repertoire sequencing; Bar Codes; Binding; Cardiovascular system; Cells; Cellular Structures; Communicable Diseases; Complex; Coronavirus; DNA; Data; Data Set; Development; Diagnostic; Disease; Effectiveness; Epitope Mapping; Epitopes; Event; Foundations; Generations; Goals; HIV-1; Hematology; High-Throughput Nucleotide Sequencing; Human; Immune; Immune response; Immune system; Immunodominant Antigens; Immunology; Individual; Infection; Libraries; Ligands; Light; Link; Malignant Neoplasms; Maps; Measures; Methods; Mining; Performance; Prevention; Process; Property; Resolution; Sampling; Specificity; System; Technology; Therapeutic antibodies; Time; Vaccines; Validation; adaptive immune response; antibody and antigen binding; antigen binding; experimental study; high throughput technology; nervous system disorder; new technology; next generation sequencing; novel; pathogen; screening; single cell technology; technology development; therapeutic target; virtual

Project Summary. The human immune system participates in complex interactions with virtually all other systems in the body. In particular, the B cell component of the adaptive immune response plays a role in various disease settings, including infectious disease, cancer, autoimmunity, cardiovascular, hematologic, neurologic diseases, and others. In addition, antibodies (a product of B cells) are effectively used in diagnostics, therapy, and prevention. Yet, despite decades of antibody discovery efforts, there is still very limited data linking human antibody sequence to antigen specificity (the preferential recognition of target antigens by a given antibody). One of the major reasons for such limited data is the fact that even high- throughput antibody sequence identification methods such as next-generation sequencing (NGS) of B cell receptor (BCR) sequences are generally decoupled from the process of antibody functional characterization. As a result, even though there are typically thousands to millions of antibody sequences within a single NGS dataset, functional information is obtained only for a handful of antibodies against not more than 2-3 target antigens at a time. To address these significant challenges for current technologies for B cell characterization and antibody discovery, our group has been focusing on the development of a single-cell technology that, for a given sample, enables the mapping of antibody sequence to antigen specificity from a single high-throughput experiment for a large number of antigens and B cells at a time. The technology, LIBRA-seq (LInking B-cell Receptor to Antigen specificity through sequencing), involves physically mixing a B cell sample with a (theoretically unlimited) pool of DNA-barcoded antigens, thus transforming B cell-antigen binding into a “sequenceable event”. In essence, LIBRA-seq offers all of the following features: (a) Characterization of thousands to tens of thousands of B cells at a time, at the single-cell level; (b) Screening against a large number of antigens at a time; (c) For each B cell, determination of the paired heavy-light chain BCR sequence; (d) For each B cell, generation of a high-resolution antigen specificity map. We initially validated LIBRA-seq in proof-of-concept studies in the context of HIV-1, and subsequently coronavirus, infection. These initial studies lay the foundation for generalizing the LIBRA-seq technology for application toward diverse antigen targets, and highlight areas for technology optimization, which will be the focus of this technology development proposal. In particular, here we propose to optimize LIBRA-seq for generalized application toward a broad diversity of antigen targets. Ultimately, the LIBRA-seq technology will have a long-lasting impact on both basic and applied immunology, helping revolutionize our understanding of antibody-antigen interactions and leading to the discovery of novel antibody therapeutics targeting a large variety of disease areas of biomedical significance.

项目摘要。人类免疫系统几乎参与了几乎所有其他的复杂互动 体内的系统。特别是，自适应免疫响应的B细胞成分在 各种疾病环境，包括传染病，癌症，自身免疫，心血管，血液学， 神经系统疾病等。另外，有效地用于 诊断，治疗和预防。然而，多斯特数十年来的抗体发现工作，仍然非常有 有限的数据将人类抗体序列与抗原特异性联系起来（靶标的首选识别 给定抗体的抗原）。这种有限数据的主要原因之一是，即使是高度的事实 吞吐抗体序列鉴定方法，例如B细胞的下一代测序（NGS） 受体（BCR）序列通常与抗体功能表征的过程分离。 结果，即使单个NGS中通常有数千至数百万的抗体序列 数据集，功能信息仅用于少数针对不超过2-3个目标的抗体 一次抗原。解决当前的B细胞表征的这些重大挑战 和抗体发现，我们的小组一直在关注单细胞技术的开发，该技术对于 给定样品，可以将抗体序列映射到来自单个高通量的抗原特异性 一次对大量抗原和B细胞进行实验。该技术，天秤座（链接B细胞） 通过测序对抗原特异性的受体），涉及将B细胞样品物理混合与A （在线无限的）DNA-barcoded抗原池，从而将B细胞抗原结合到A “可测试事件”。本质上，Libra-Seq提供以下所有功能：（a）表征 在单细胞水平上，数千至成千上万的B细胞； （b）对大型筛选 一次抗原数量； （c）对于每个B细胞，测定配对的重型链链BCR序列； （d）对于每个B细胞，生成高分辨率抗原特异性图。我们最初在 概念证明研究在HIV-1的背景下以及随后的冠状病毒感染。这些最初的研究 为将天秤座技术推广到用于潜水抗原目标的基础， 并突出了技术优化的领域，这将成为该技术开发的重点 提议。特别是，我们建议在这里优化库seq，以供广泛的广泛应用 抗原靶标的多样性。 最终，Libra-Seq技术将对基本和应用都产生持久的影响 免疫学，帮助彻底改变我们对抗体 - 抗原相互作用的理解，并导致 针对生物医学意义的各种疾病区域的新型抗体疗法的发现。