New Technology for High-Resolution Antibody Profiling for SARS-CoV-2

SARS-CoV-2 高分辨率抗体分析新技术

• 批准号: 10686794
• 负责人: Mark Lim
• 金额: $ 97.86万
• 依托单位: AMBERGEN, INC
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-19 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10686794
• 关键词: 2019-nCoV; Acute; Address; Analysis of Variance; Antibodies; Antibody Response; Antigens; Binding; Biological Assay; Boston; COVID-19; COVID-19 pandemic; COVID-19 patient; Characteristics; Classification; Collaborations; Coupled; Cross Reactions; Device or Instrument Development; Diagnostic; Dimensions; Disease; Epitopes; Evaluation; Feasibility Studies; Fluorescence; Human; IgG1; Immobilization; Immune; Immune response; Immunoglobulin Isotypes; Individual; Inflammatory Response; Label; Laboratories; Link; Long COVID; Mass Spectrum Analysis; Measures; Methods; Microbiology; Modeling; Nature; Noise; Outcome; Patients; Persons; Phase; Physics; Physiological; Physiology; Play; Postdoctoral Fellow; ROC Curve; Reagent; Reporting; Research; Research Personnel; Resolution; SARS-CoV-2 B.1.617.2; SARS-CoV-2 antibody; SARS-CoV-2 antigen; SARS-CoV-2 exposure; Sampling; Sensitivity and Specificity; Serology; Serum; Severity of illness; Signal Transduction; Structure; System; Technology; Universities; Vaccination; Vaccines; Validation; Variant; Viral Antigens; Virus; Work; antigen binding; breakthrough infection; cohort; design; distinguished professor; effective therapy; glycosylation; improved; mass spectrometric imaging; medical schools; new technology; pandemic disease; pathogen; predictive modeling; professor; prognostic; response; severe COVID-19; success; tool; trait; two-dimensional; vaccine hesitancy; virus infection mechanism

Summary/Abstract The SARS-CoV-2 virus has infected to date 35 million and killed over 600,000 persons in the U.S. alone. Despite initial success of the vaccines, the emergence of increasingly more infectious variants such as the delta variant, coupled with vaccine hesitancy and insufficiently effective therapies, has resulted in a continued and deepening national and world-wide pandemic crisis. Moreover, a significant fraction of COVID-19 patients (~35%), even those who are initially asymptomatic, suffer long-term debilitating effects (“long-COVID”). Recent reports correlate the structure of specific SARS-CoV-2 induced antibodies with potentially lethal proinflammatory responses in acute COVID-19. Studies have also linked the antibody response to long-COVID. Moreover, the nature of the antibody response to vaccination correlates with breakthrough infections. Thus, the ability to rapidly perform high- resolution, highly multiplexed antibody response profiling can provide an essential tool, ultimately leading to more effective diagnostics, prognostics, vaccines and treatments for both acute and long-term disease. However, current antibody profiling methods produce a very limited view of the humoral repertoire. To address this unmet need, AmberGen proposes to further develop in Phase II its mass spectrometric bead-array technology for in-depth immune-profiling, termed PC-BAMS-IP™. This will provide researchers with a new and powerful tool for high- resolution antibody profiling which unlike current technology facilitates 2-dimensions of multiplexing. This is accomplished using arrayed photocleavable mass-tag (PC-MT) encoded beads bearing viral antigens to bind serum antibodies, along with a range of PC-MT encoded probes to simultaneously measure the full breadth of bead-bound antibody types. Mass spectrometry imaging (MSI) of the bead-arrays facilitates the decoding of thousands of different PC-MTs, thereby revealing the full complexity of the antibody response and a means to correlate it with disease severity/outcome. Feasibility studies focused on SARS-CoV-2 demonstrate the ability of PC-BAMS-IP™ to perform simultaneous 2-dimensional antibody profiling of both the Fab traits (antigen binding function) and Fc traits (immune effector function). The proposed 2-year Phase II project will expand on this progress, including: i) design, synthesis and evaluation of 25 plug-and-play PC-MT encoded beads for SARS-CoV-2 antigen immobilization and 25 PC-MT probes to simultaneously query a range of Fc traits of the bead-bound serum antibodies; ii) initial validation of the PC-BAMS-IP™ assay using control and COVID-19 convalescent sera, including comparison to Luminex® xMAP® technology, the existing gold-standard for 1-dimensional multiplex antibody profiling; and iii) demonstrate that PC-BAMS-IP™ can distinguish severe and mild COVID-19. This work will be facilitated by our continued collaboration with leading experts including Prof. Cathy Costello (BU, world- renowned mass spectrometry expert), Dr. Jason Amsden (Duke University, mass spectrometric instrument development), Prof. Rahm Gummuluru (BU, Vice Chair of Microbiology, a leading virologist), and Prof. Plamen Ivanov (BU, Director, Keck Laboratory for Network Physiology, advanced statistical physics).

总结/摘要 迄今为止，仅在美国，SARS-CoV-2病毒就感染了3500万人，造成60多万人死亡。尽管 疫苗的初步成功，传染性越来越强的变种（例如Delta变种）的出现， 再加上疫苗犹豫和有效治疗不足，导致了持续和深化的 国家和世界范围的流行病危机。此外，很大一部分COVID-19患者（约35%），即使是那些 最初无症状的患者遭受长期衰弱效应（“长期COVID”）。最近的报告表明， 在急性炎症反应中具有潜在致死性的SARS-CoV-2诱导的特异性抗体的结构 2019冠状病毒病。研究还将抗体反应与长期COVID联系起来。此外，抗体的性质 对疫苗接种的反应与突破性感染相关。因此，快速执行高- 高分辨率，高度多重抗体反应谱可以提供一个重要的工具，最终导致更多的 对急性和长期疾病的有效诊断、免疫、疫苗和治疗。但目前的 抗体谱分析方法对体液库的了解非常有限。为了解决这一未满足的需求， AmberGen建议在第二阶段进一步开发其质谱珠阵列技术， 免疫分析，称为PC-BAMS-IP™。这将为研究人员提供一个新的强大的工具，高- 与当前技术不同，其有利于2维多路复用。这是 使用带有病毒抗原的阵列式光可裂解质量标签（PC-MT）编码珠粒结合血清 抗体，沿着一系列PC-MT编码的探针，以同时测量珠结合的完整宽度。 抗体类型珠阵列的质谱成像（MSI）促进了对数千个 不同的PC-MT，从而揭示了抗体反应的全部复杂性和将其与 疾病严重程度/结局。针对SARS-CoV-2的可行性研究证明了PC-BAMS-IP™能够 同时进行Fab性状（抗原结合功能）和Fc 免疫效应功能（Immune Effect Function）拟议的两年期第二阶段项目将扩大这一进展，包括： 25个即插即用的SARS-CoV-2抗原PC-MT编码微球的设计、合成和评价 固定和25个PC-MT探针，以同时查询珠结合血清的一系列Fc特征 抗体; ii）使用对照和COVID-19恢复期血清对PC-BAMS-IP™测定进行初始验证， 包括与Luminex® xMAP®技术的比较，Luminex® xMAP®技术是现有的一维多路复用的黄金标准 抗体谱分析;和iii）证明PC-BAMS-IP™可以区分严重和轻度COVID-19。这项工作 将通过我们与包括Cathy Costello教授（BU，世界- 著名质谱专家），Jason Amsden博士（杜克大学，质谱仪器 拉姆Gummuluru教授（BU，微生物学副主席，领先的病毒学家）和Plamen教授 Ivanov（BU，Keck网络生理学实验室主任，高级统计物理学）。