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

项目摘要 肽-主要组织相容性复合物（pMHC）抗原的T细胞受体（TCR）识别是免疫调节的必要条件。 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细胞库编码数百万个独特的TCR，以特异性地识别数万亿个可能的免疫缺陷。 pMHC抗原，可以在一个人的一生中遇到。使适应性免疫的分子多样性 如此有效也使其研究复杂化。新兴技术有助于T细胞识别的研究，但 每一个都集中在评估大量的pMHC或TCR序列，同时严重限制了基因表达。 由于不能直接连接TCR-pMHC信息，另一个检查的变体数量。 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 在系统水平上，需要一种能够对TCR-pMHC相互作用进行“库对库”研究的技术。 为了实现这一点，我们发现假型慢病毒可以使用病毒上展示的pMHC 在一个实施方案中，所述抗原结合物结合到表面以特异性地引导病毒进入表达同源TCR的T细胞。因此，我们建议建立 “慢病毒展示”pMHC文库，其中每种病毒展示并编码独特的pMHC以使得能够追踪， T细胞的抗原特异性感染。在与原代多克隆T细胞上的同源受体相互作用后， 这些病毒将整合抗原的遗传信息，使病毒能够进入，提供连接的TCR- 可以通过单细胞测序直接回收的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三个目前难以解决的应用领域： 鼻病毒，跟踪人类疫苗组，并生成广泛的TCR-pMHC相互作用数据集，以帮助 T细胞反应的计算机预测。如果成功，我们的工作可以很容易地推广和部署 用于关键的未满足的临床需求领域，如传染病和癌症，以及用于基本的 人类免疫学的问题。

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.