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的有效抗体反应是抵御感染的关键。然而， 并不是所有针对该病毒的抗体都具有保护性。最近的研究表明，高滴度的 自然感染时抗SARS-CoV-2 S蛋白(S)免疫球蛋白G与疾病的关系 严肃性。S蛋白，由于其在宿主细胞感染中的受体结合作用而被强调，仅代表 可能有29种蛋白质由SARS-CoV-2病毒编码。事实上，最近的研究表明，SARS-CoV- 2种非结构蛋白，包括ORF3b、ORF8、ORF9b和ORF9c，具有抑制宿主抗病毒的能力 I型干扰素(干扰素)和诱导持续的抗体反应。这些发现提出了一个问题，即 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 严防严重新冠肺炎。 除了对不同SARS-CoV-2蛋白的抗体特异性外，抗体同型和 亚类也会影响疾病的转归。然而，SARS-CoV-2的许多血清学数据- 感染的患者主要集中在对S和核衣壳蛋白的免疫球蛋白和免疫球蛋白反应。在这份提案中， 我们的目标是通过开发一种新技术来解决这个问题，该技术将允许同时测量 24株SARS-CoV-2的8种抗体亚型(IgM、IgG1、IgG2、IgG3、IgG4、IgA1、IgA2、IgE) 和地方性HCoV编码的蛋白质，包括针对新出现的病毒变体的蛋白质，所有这些都在一个单一的 多重分析(目标1)。我们将应用这项技术，即Flow BEAT(基于流式细胞仪的珠子 对从一项纵向研究中收集的600份血清样本进行检测抗原特异性抗体亚型的方法 (6个时间点；≥6个月) 或严重症状(目标2)。我们假设，轻度但不严重的新冠肺炎患者将出现早期 和针对免疫调节病毒蛋白的持续抗体亚类，特别是针对病毒蛋白的抗体亚类 已知可抑制干扰素反应。 我们希望这项研究能够深入了解人类免疫缺陷的广度(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 从新冠肺炎高效回收。我们的研究还可以通过以下方式告知正在进行的和未来的疫苗开发 确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，flow BEAT灵活的模块化特性可以快速地适应于抗体广度的研究 几乎在任何疾病中都有反应。

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.