flowBEAT: a multiparameter flow cytometry assay to discover longitudinal antibody responses associated with efficient recovery from COVID-19

项目摘要 建立针对SARS-CoV-2的有效抗体反应是抗击感染的关键。然而，在这方面， 并非所有针对病毒产生的抗体都具有保护性。最近的研究表明， 免疫球蛋白G（IgG）在自然感染期间针对SARS-CoV-2刺突蛋白（S）与疾病相关 严重性。由于其在宿主细胞感染中的受体结合作用而被突出显示的S蛋白仅代表了 SARS-CoV-2病毒可能编码29种蛋白质。事实上，最近的研究表明，SARS-CoV- ORF 3b、ORF 8、ORF 9 b和ORF 9 c等2种非结构蛋白具有抑制宿主抗病毒的能力 I型干扰素（IFN）并引发持续的抗体应答。这些发现提出了一个问题， 在感染早期产生的针对这些免疫调节病毒蛋白的抗体可以提供 预防严重的COVID-19。 除了对不同SARS-CoV-2蛋白的抗体特异性外，抗体同种型和 亚类也可以影响疾病的结果。然而，来自SARS-CoV-2- 感染的患者主要集中在IgG和IgM反应的S和核衣壳蛋白。在这一提议中， 我们的目标是通过开发一种新技术来解决这个问题，这种技术将允许同时测量 针对24种SARS-CoV-2的8种抗体同种型和亚类（IgM、IgG 1、IgG 2、IgG 3、IgG 4、IgA 1、IgA 2、IgE） 和地方性HCoV编码的蛋白质，包括针对来自新出现的病毒变体的蛋白质，所有这些都在一个单一的 多重测定（Aim 1）。我们将应用这项技术，即flowBEAT（基于流式细胞术的微珠 检测抗原特异性抗体同种型的测定），以从纵向研究中收集的600份血清样品 （6个时间点; ≥ 6个月）的100例COVID-19患者的良好特征队列， 或严重症状（目标2）。我们假设，轻度但不严重的COVID-19患者将在早期表现出 和针对免疫调节性病毒蛋白，特别是针对病毒蛋白的持续抗体亚类 已知抑制干扰素反应。 我们希望这项研究能提供一个深入的广度（类型，特异性和寿命）， 针对24种SARS-CoV-2和HCoV编码蛋白的抗体应答， 从COVID-19中有效恢复。我们的研究还可以为正在进行和未来的疫苗开发提供信息， 鉴定在康复患者中产生持久和保护性抗体亚类的蛋白质。 最后，flowBEAT灵活的模块化功能可以快速适应抗体的宽度研究 几乎所有疾病的反应。

Project Summary Mounting an effective antibody response against SARS-CoV-2 is key to fight off the infection. However, not all antibodies produced against the virus are protective. Recent studies show that high titers of immunoglobulin G (IgG) against the SARS-CoV-2 Spike (S) protein during natural infection correlate with disease severity. The S protein, highlighted due to its receptor-binding role in host cell infection, represents only one of potentially 29 proteins that are encoded by the SARS-CoV-2 virus. In fact, recent studies show that SARS-CoV- 2 non-structural proteins, including ORF3b, ORF8, ORF9b, and ORF9c, have the ability to suppress host antiviral type-I interferon (IFN) and elicit sustained antibody responses. These findings raise the question of whether antibodies produced against these immunomodulatory viral proteins early during the infection could provide protection against severe COVID-19. In addition to the antibody specificity to different SARS-CoV-2 proteins, the antibody isotype and subclass can also influence the disease outcome. However, much of the serology data from SARS-CoV-2- infected patients mainly focus on IgG and IgM responses to S and nucleocapsid proteins only. In this proposal, we aim to tackle this problem by developing a new technology that will allow for simultaneous measurement of 8 antibody isotypes and subclasses (IgM, IgG1, IgG2, IgG3, IgG4, IgA1, IgA2, IgE) against 24 SARS-CoV-2 and endemic HCoV-encoded proteins, including against proteins from emerging virus variants, all in a single multiplexed assay (Aim 1). We will apply this technology, namely flowBEAT (flow cytometry-based BEads assay to detect Antigen-specific antibody isoTypes), to 600 serum samples collected from a longitudinal study (6 timepoints; ≥ 6 months) of a well-characterized cohort of 100 COVID-19 patients presenting with either mild or severe symptoms (Aim 2). We hypothesize that mild, but not severe, COVID-19 patients will show an early and sustained antibody subclass against immunomodulatory viral proteins, particularly against viral proteins known to suppress IFN responses. We expect this study to provide an in-depth view of the breadth (type, specificity, and longevity) of antibody responses mounted against 24 SARS-CoV-2- and HCoV-encoded proteins that are associated with efficient recovery from COVID-19. Our study can also inform on ongoing and future vaccine development by identifying proteins that generate long-lasting and protective antibody subclasses in the recovered patients. Finally, the flexible modular feature of flowBEAT can quickly be adapted to study the breadth of antibody responses in virtually any disease.