Designer DNA Nanostructure Based Biosensing for Rapid COVID19 Detection and Monitoring using Saliva Sample

基于 DNA 纳米结构的设计生物传感，使用唾液样本快速检测和监测新冠肺炎

基本信息

批准号：
10266426
负责人：
Xiaohu Yao
金额：
$ 125.8万
依托单位：
ATOM BIOWORKS INC
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-12-21 至 2023-11-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10266426
关键词：
2019-nCoV Affect Affinity Americas Antibody Response Antigens Architecture Avidity Binding Biochemistry Biological Assay Biological Markers Biosensing Techniques Biosensor Blood Coagulation Disorders Blood Volume Blood coagulation COVID-19 assay COVID-19 detection COVID-19 diagnostic COVID-19 monitoring COVID-19 pandemic Cells Cessation of life Chronic Disease Clinical Communicable Diseases Complex Computer software Contact Tracing DNA Data Analytics Dengue Virus Detection Development Devices Diabetes Mellitus Diagnostic Diagnostic tests Disease Education Epitopes Future Hand Heart failure Hospitals Hypertension Illinois Immunoassay Impairment Individual Infection Infectious Agent Infrastructure Laboratories Lead Link Location Louisiana Medical Device Modality Molecular Monitor Nanostructures Patients Pattern Persons Physicians Pilot Projects Plasma Preparation Quarantine Rapid diagnostics Reagent Recommendation Research Reverse Transcriptase Polymerase Chain Reaction Risk Running SARS-CoV-2 infection Saliva Sampling Schools Sensitivity and Specificity Site Small Business Technology Transfer Research Societies Specificity Surface Surface Antigens Symptoms System Testing Time Universities Urine Validation Viral Viral Load result Virion Virus Whole Blood antibody detection aptamer base biomarker panel cost cost effective design detection assay detection platform diagnostic assay diagnostic platform experience heart function improved innovation instrument multidisciplinary novel novel strategies pandemic disease particle pathogen pathogenic virus prototype pulmonary function rapid testing response saliva sample salivary assay sample collection viral detection

项目摘要

ABSTRACT A Novel Saliva-Based Aptamer Detection Assay for SARS-CoV-2 Infection (RFA-OD-20-021 STTR Application) Automated, rapid diagnostics with little sample collection and preparation are needed to identify and trace affected persons in times when hyper-infectious pathogens cause pandemics. Frequent, low cost and highly scalable testing is the only way to gain visibility on the magnitude of the pandemic and ultimately control the spread of the disease. We propose the development of a unique system that can cheaply and readily detect SARS-CoV-2 in saliva samples. The development of a system that uses saliva present an opportunity to readily test patients using a sample that is easily collected and harbors high concentration of viral particles. The SARS-CoV-2 pandemic has predominantly affected individuals with pre-existing conditions such as clotting disorders, diabetes, hypertension or other chronic diseases. Patients with these pre-existing conditions who then are infected have exacerbated symptoms and complications that can lead to death. For example, many patients that have succumbed to SARS-CoV-2 infection have developed blood clots that have impaired pulmonary or cardiac function and ultimately cardiac failure. A rapid diagnostic using easily collected samples (e.g. saliva) would allow for infections to be identified sooner, therapies to be administered quicker, treatment to be monitored, and ultimately leading to fewer individuals that succumb to the infection. We outline a novel DNA Star biosensing approach based on the fact that viruses, such as SARS- CoV-2, express unique spatial patterns of antigens on their surfaces, facilitating multivalent binding to host cells for infection. These configurations of epitopes drive the high sensitivity and specificity of our assay. Based on this naturally occurring binding mechanism, we developed a rational design approach producing pattern matching designer DNA architecture for viral sensing. A proof-of-concept Dengue virus (DENV) rapid diagnostics was developed to demonstrate its power: DENV surface antigens present the most complex geometric pattern among all known pathogens, a DNA star linked 10-aptamers nanostructure that offers polyvalent, spatial DENV- epitope pattern matching interactions has provided high DENV-binding avidity and specificity, increasing affinity by ~1,000× compared to the conventional aptamer approach which relies on monovalent aptamer-epitope interactions. Our POCT diagnostics detected intact DENV virions in patient samples with PCR equivalent sensitivity in <2 mins at a cost <$0.15. Current RT-PCR molecular test are suited to large, centralized laboratories, and difficult to scale for rapid testing of samples and delivery of results to clinicians and patients. Immunoassay tests have lower sensitivity, and patients need to develop a response to the virus in order to detect the antibody response. Our “DNA star” biosensor-based rapid diagnostics will provide the infrastructure for real time SARS-CoV-2 diagnostics that is easy to use (instrument-free), faster (sample to results in minutes) and cost effective (~$3 per test).

抽象的新型基于唾液的核酸适体检测方法检测 SARS-CoV-2 感染（RFA-OD-20-021 STTR 申请）需要进行自动化、快速诊断，只需少量样本收集和制备即可识别并在高传染性病原体引起流行病时追踪受影响的人。低成本和高度可扩展的测试是了解问题规模的唯一方法我们建议开发一种流行病并最终控制疾病的传播。独特的系统可以廉价且轻松地检测唾液样本中的 SARS-CoV-2。使用唾液的系统的开发提供了使用唾液轻松测试患者的机会易于收集且含有高浓度病毒颗粒的样本。 SARS-CoV-2 大流行主要影响已有疾病的个体例如凝血障碍、糖尿病、高血压或其他慢性疾病患者。先前存在的疾病，然后被感染，会加剧症状和并发症，例如，许多死于 SARS-CoV-2 感染的患者。出现血栓，损害肺或心脏功能，最终使用容易采集的样本（例如唾液）进行快速诊断将允许更快地发现感染，更快地实施治疗，监测治疗，最终导致死于感染的人数减少。我们概述了一种新颖的 DNA Star 生物传感方法，该方法基于病毒（例如 SARS- CoV-2，在其表面表达抗原的独特空间模式，促进多价与宿主细胞结合进行感染。基于这种自然发生的结合机制，我们开发了一种方法。理性设计方法产生模式匹配设计师 DNA 架构用于病毒传感。开发了一种概念验证的登革热病毒 (DENV) 快速诊断方法来证明其力量：DENV 表面抗原呈现出所有已知抗原中最复杂的几何图案病原体，一种 DNA 星连接的 10 适体纳米结构，提供多价、空间 DENV- 表位模式匹配相互作用提供了高 DENV 结合亲和力和特异性，与依赖于的传统适体方法相比，亲和力增加约 1,000 倍我们的 POCT 诊断检测到完整的 DENV 病毒粒子。在 <2 分钟内获得具有与 PCR 同等灵敏度的患者样本，成本 <0.15 美元。目前的 RT-PCR 分子检测适用于大型集中实验室，且难以规模化用于快速检测样品并向教区居民和患者提供结果。敏感性较低，患者需要对病毒产生反应才能检测到我们基于“DNA 星”生物传感器的快速诊断将提供抗体反应。用于实时 SARS-CoV-2 诊断的基础设施，易于使用（无仪器），速度更快（从样品到结果仅需几分钟）且具有成本效益（每次测试约 3 美元）。