Repertoire-scale T cell antigen identification via peptide-MHC lentivirus display

项目摘要 多肽-主要组织相容性复合体(PMHC)抗原的T细胞受体(TCR)识别是必不可少的 适应性免疫的组成部分，影响传染病、癌症、移植和自身免疫。 维持抗原的特异性需要检测、产生和控制巨大的分子多样性。 每个人的T细胞谱系编码数百万个独特的TCR，以专门识别数万亿种可能的 人一生中可能遇到的pMHC抗原。使获得性免疫的分子多样性 如此有效也使其研究复杂化。新兴技术对T细胞识别的研究有所帮助，但 每种方法都专注于评估大量的pMHC或TCR序列，同时严格限制 由于无法直接链接TCR-pMHC信息，另一种的已检查变体数量。 为了了解对大型病原体或癌症的复杂免疫反应，或对许多抗原的反应 在系统层面上，需要一种技术来研究TCR-pMHC相互作用。 为了实现这一点，我们发现伪型慢病毒可以使用病毒上显示的pMHC 表面引导病毒进入，特别是表达同源TCR的T细胞。因此，我们建议创建 “慢病毒显示”pMHC文库，其中每个病毒显示并编码一个唯一的pMHC以启用可跟踪， T细胞抗原特异性感染。当它们与原代多克隆T细胞上的同源受体相互作用时， 这些病毒将整合使病毒进入的抗原的遗传信息，提供连锁的TCR- 可通过单细胞测序直接恢复的pMHC序列对。在这里，我们建议开发 这项技术研究了人类免疫识别中目前难以解决的三个应用领域：对 鼻病毒，跟踪人类牛痘疫苗组，并生成TCR-pMHC相互作用的广泛数据集，以帮助 T细胞反应的计算预测。如果成功，我们的工作可以很容易地推广和部署 用于关键的未得到满足的临床需求领域，如传染病和癌症，以及基本的 人类免疫学中的问题。

Project Abstract T cell receptor (TCR) recognition of peptide-Major Histocompatibility Complex (pMHC) antigens is an essential component of adaptive immunity, impacting infectious disease, cancer, transplantation, and autoimmunity. Maintaining antigen specificity requires the detection, generation, and control of immense molecular diversity. Each individual’s T cell repertoire encodes millions of unique TCRs to specifically identify the trillions of possible pMHC antigens that can be encountered in one’s lifetime. The molecular diversity that makes adaptive immunity so effective also complicates its study. Emerging technologies have aided in the study of T cell recognition, but each focuses upon assessing large numbers of either pMHC or TCR sequences while severely limiting the number of examined variants for the other due to the inability to directly link TCR-pMHC information. In order to understand complex immune responses to large pathogens or cancer, or responses to many antigens on a systems level, a technique enabling ‘repertoire vs repertoire’ study of TCR-pMHC interactions is required. To achieve this, we have discovered that pseudotyped lentiviruses can use pMHCs displayed on the virus surface to direct viral entry specifically to T cells that express a cognate TCR. We therefore propose creating ‘lentivirus displayed’ pMHC libraries, where each virus displays and encodes a unique pMHC to enable trackable, antigen-specific infection of T cells. Upon interacting with their cognate receptors on primary, polyclonal T cells, these viruses will integrate the genetic information of the antigen that enabled viral entry, providing linked TCR- pMHC sequence pairs that can be directly recovered via single-cell sequencing. Here, we propose developing this technique to study three currently intractable application areas in human immune recognition: responses to rhinoviruses, tracking the human vaccinome, and generating broad datasets of TCR-pMHC interactions to aid in the computational prediction of T cell responses. If successful, our work can be readily generalized and deployed for use in areas of key unmet clinical need, such as infectious disease and cancer, as well as for fundamental questions in human immunology.