Antibody display libraries for precision screening of antibody immune responses to SARS-CoV-2

项目摘要/摘要 本项目将确定新冠肺炎患者的抗体免疫特征，以加速 开发新的医疗干预措施。SARS-CoV-2在许多人中引起无症状或轻度疾病 这表明，有效的人类免疫反应可以完全预防疾病。然而，它 目前尚不清楚哪些免疫反应特征与疾病保护相关。要解决这个问题 问：在这里，我们将分析新冠肺炎患者的综合抗体免疫反应，并确定 抗体免疫的分子特征如何与新冠肺炎症状严重程度相关。 首先，我们将新冠肺炎患者队列中的抗体免疫库永生化到酵母展示库中 进行全面的体外功能筛选。新冠肺炎患者的B细胞样本将被分离并 乳化为单细胞进行天然抗体DNA的回收，将抗体基因转化为酵母 Fab展示平台，用于全套规模的抗体功能分析。将对抗体进行筛选以结合到 SARS-CoV-2尖峰三聚体，一个主要的中和靶点，也用于抑制ACE2与MAP的结合 人体免疫反应中的中和抗体。 我们还将挖掘我们的可再生抗体免疫库，以寻找可能与以下因素相关的更广泛的特征 新冠肺炎病情严重。我们将研究针对SARS-CoV-2广泛抗原和表位的抗体， 包括SPEK三聚体蛋白上的多个表位(如受体结合域、RBD、N端 结构域、NTD和S1区)和内部病毒蛋白(例如，核衣壳蛋白)。我们还将绘制 单个B细胞反应的分子特征(例如亲和力、基于竞争的表位映射和差异 结合不同的刺突蛋白构象)全面追踪抗SARS-CoV-2分子免疫 在人类队列中。我们将分析每个抗体克隆的遗传特征，以帮助阐明 中和抗体与非中和抗体作为潜在疾病相关。 最后，我们将对每个患者群体的抗体库进行大规模数据挖掘，以 确定可能区分轻微和严重SARS-CoV-2感染的关键分子特征。这些新的 分子尺度的相关性和潜在的生物标志物将提高基础和临床认识，以推动 新冠肺炎的预防和治疗。我们试图揭示新冠肺炎的关键免疫生物标记物 疾病的严重性和确定新的有效的抗体候选药物来治疗和预防新冠肺炎。

PROJECT SUMMARY/ABSTRACT This project will determine the antibody-based immune features in COVID-19 patients to accelerate the development of new medical interventions. SARS-CoV-2 causes asymptomatic or mild disease in many individuals, demonstrating that an effective human immune response can fully prevent disease. However, it remains unclear what immune response features are associated with protection from disease. To address this question, here we will analyze comprehensive antibody immune responses in COVID-19 patients and determine how the molecular features of antibody immunity correlate with COVID-19 symptom severity. First, we will immortalize antibody immune libraries from COVID-19 patient cohorts into yeast display libraries for comprehensive in vitro functional screening. B cell samples from COVID-19 patients will be isolated and emulsified as single cells for native antibody DNA recovery, and antibody genes will be transformed into a yeast Fab display platform for repertoire-scale antibody functional analyses. Antibodies will be screened for binding to the SARS-CoV-2 spike trimer, a dominant neutralization target, and also for inhibition of ACE2 binding to map neutralizing antibodies in human immune responses. We will also mine our renewable antibody immune libraries for broader features that may correlate with COVID-19 disease severity. We will investigate antibodies targeting broad SARS-CoV-2 antigens and epitopes, including multiple epitopes on the spike trimer protein (such as the receptor binding domain, RBD, the N terminal domain, NTD, and the S1 region) and internal viral proteins (e.g., nucleocapsid protein). We will also map the molecular features of single B cell responses (e.g. affinity, competition-based epitope mapping, and differential binding to different spike protein conformations) to comprehensively track anti-SARS-CoV-2 molecular immunity in a human cohort. We will analyze the genetic features of each antibody clone to help elucidate the balance of neutralizing vs. non-neutralizing antibodies as potential disease correlates. Finally, we will perform large-scale data mining of the antibody repertoires from each patient population to identify key molecular features that may distinguish mild and severe SARS-CoV-2 infections. These new molecular-scale correlates and potential biomarkers will improve basic and clinical understanding to advance COVID-19 preventions and therapies. We seek to reveal critical immune-based biomarkers of COVID-19 diseases severity and identify new potent antibody drug candidates to treat and prevent COVID-19.