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

flowBEAT：一种多参数流式细胞术检测，用于发现与 COVID-19 有效恢复相关的纵向抗体反应

• 批准号: 10355136
• 负责人: Eliver Ghosn
• 金额: $ 23.22万
• 依托单位: EMORY UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-11-01 至 2023-10-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10355136
• 关键词: 2019-nCoV; Address; Animal Model; Antibodies; Antibody Response; Antibody Specificity; Antibody titer measurement; Biological Assay; COVID-19; COVID-19 mortality; COVID-19 patient; COVID-19 severity; Cells; Coronavirus; Data; Disease; Disease Outcome; Flow Cytometry; Fluorescence; Future; HIV; Human; IgA1; IgA2; IgE; IgG1; IgG2; IgG3; IgG4; Immune response; Immunoglobulin A; Immunoglobulin G; Immunoglobulin M; Individual; Infection; Interferon Type I; Interferons; Knowledge; Label; Longevity; Longitudinal Studies; Measurement; Measures; Methods; Microspheres; Nonstructural Protein; Nucleocapsid Proteins; Pathogenesis; Patients; Prevalence; Proteins; Recovery; Research Personnel; Role; SARS-CoV-2 spike protein; SARS-CoV-2 variant; Sampling; Serology; Serology test; Serum; Severity of illness; Specificity; Symptoms; System; Technology; Variant; Viral Proteins; Virus; antigen detection; base; cohort; falls; fighting; flexibility; high dimensionality; human coronavirus; immunoregulation; improved; light scattering; multiplex assay; mutant; new technology; novel; pandemic disease; prevent; receptor binding; response; severe COVID-19; vaccine development; virtual; 2019-nCoV; Address; Animal Model; Antibodies; Antibody Response; Antibody Specificity; Antibody titer measurement; Biological Assay; COVID-19; COVID-19 mortality; COVID-19 patient; COVID-19 severity; Cells; Coronavirus; Data; Disease; Disease Outcome; Flow Cytometry; Fluorescence; Future; HIV; Human; IgA1; IgA2; IgE; IgG1; IgG2; IgG3; IgG4; Immune response; Immunoglobulin A; Immunoglobulin G; Immunoglobulin M; Individual; Infection; Interferon Type I; Interferons; Knowledge; Label; Longevity; Longitudinal Studies; Measurement; Measures; Methods; Microspheres; Nonstructural Protein; Nucleocapsid Proteins; Pathogenesis; Patients; Prevalence; Proteins; Recovery; Research Personnel; Role; SARS-CoV-2 spike protein; SARS-CoV-2 variant; Sampling; Serology; Serology test; Serum; Severity of illness; Specificity; Symptoms; System; Technology; Variant; Viral Proteins; Virus; antigen detection; base; cohort; falls; fighting; flexibility; high dimensionality; human coronavirus; immunoregulation; improved; light scattering; multiplex assay; mutant; new technology; novel; pandemic disease; prevent; receptor binding; response; severe COVID-19; vaccine development; virtual

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.

项目摘要 对SARS-COV-2进行有效的抗体反应是抵抗感染的关键。然而， 并非所有针对病毒产生的抗体受到保护。最近的研究表明，很高的滴度 自然感染期间针对SARS-COV-2蛋白质的免疫球蛋白G（IgG）与疾病相关 严重程度。 S蛋白由于其受体结合在宿主细胞感染中的作用而突出显示，仅代表其中之一 可能由SARS-COV-2病毒编码的29种蛋白质。实际上，最近的研究表明SARS-COV- 2个非结构性蛋白质，包括ORF3B，ORF8，ORF9B和ORF9C，具有抑制宿主抗病毒的能力 I型干扰素（IFN）并引起持续的抗体反应。这些发现提出了一个问题，即是否 感染期间早期针对这些免疫调节病毒蛋白产生的抗体可以提供 防止严重的Covid-19。 除了对不同SARS-COV-2蛋白的抗体特异性，抗体同种型和 子类也会影响疾病结果。但是，来自SARS-COV-2-的许多血清学数据 感染的患者主要关注IgG和IgM对S和核素蛋白的反应。在此提案中， 我们旨在通过开发一种新技术来解决这个问题，该技术将允许对 8抗体同种型和亚类（IgM，IgG1，IgG2，IgG3，IgG4，IgA1，Iga1，IgA2，IgE） 和内细胞HCOV编码的蛋白质，包括针对新兴病毒变体的蛋白 多路复用测定（AIM 1）。我们将应用这项技术，即FlowBeat（基于流式细胞仪的珠子 检测抗原特异性抗体同种型的测定），从纵向研究中收集的600种血清样品 （6个时间点；≥6个月）的100例Covid-19患者的特征良好的队列 或严重的症状（AIM 2）。我们假设这种轻度但不重要的COVID-19患者将表现出早期 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 已知可以抑制IFN响应。 我们希望这项研究能够深入了解广度（类型，特异性和寿命） 与24个SARS-COV-2-和HCOV编码的蛋白相关的抗体反应 从Covid-19中有效恢复。我们的研究还可以通过 鉴定蛋白质在恢复的患者中产生持久和保护的抗体亚类。 最后，可以迅速适应流动的柔性模块化特征，以研究抗体的广度 几乎任何疾病的反应。