Rational design of a novel rapid diagnostic tool for coccidioidomycosis

合理设计新型球孢子菌病快速诊断工具

基本信息

批准号：
10668184
负责人：
Bridget Marie Barker
金额：
$ 25.6万
依托单位：
NORTHERN ARIZONA UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-01-23 至 2024-12-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10668184
关键词：
Affinity Animals Anti-Bacterial Agents Antibodies Antifungal Agents Antigens Area Bioinformatics Biological Biological Assay Biological Markers Biosensor Blood Centers for Disease Control and Prevention (U.S.)Central America Clinical Clinical Trials Coccidioides Coccidioides immitis Coccidioides posadasii Coccidioidomycosis Coupled Data Data Analyses Dependence Detection Development Diagnosis Diagnostic Diagnostic tests Disease Engineering Escherichia coli Evaluation Filtration Future Gene Proteins Genes Genomics Goals Harvest Health Care Costs Human Hydrocortisone Imagery Immune response In Vitro Incidence Industry Infection Intellectual Property Laboratories Length of Stay Marketing Methodology Methods Molecular Mus Mycoses Outcome Study Patient-Focused Outcomes Patients Performance Phase Polymers Process Protein Secretion Proteins Provider Rapid diagnostics Recombinant Proteins Recombinants Reporting Reproducibility Research Resource-limited setting Sampling Serodiagnoses Serum Soil South America Southwestern United States Specificity Structure of parenchyma of lung Symptoms System Techniques Testing Transcript United States Up-Regulation Validation accurate diagnosis antibody test antigen diagnostic antigen test bacterial community bioelectronics biomarker validation candidate selection community acquired pneumonia cost desert fever design detection limit diagnostic assay diagnostic tool effective therapy experimental study fungus genomic data imprint improved in silico in vivo innovation interdisciplinary approach manufacture model organism novel novel diagnostics novel strategies pathogenic fungus peripheral blood radiological imaging rapid diagnosis rational design reagent testing screening sensor statistics synthetic antibodies synthetic biology time use transcriptome sequencing

项目摘要

Coccidioides immitis and C. posadasii are two species of soil fungi that cause the disease coccidioidomycosis, (or Valley fever), whose incidence has increased 587% over the last 20 years and now causes over 150,000 new infections in the United States annually. The Centers for Disease Control and Prevention (CDC) report that average cost for treating Valley fever is over $50,000 per patient and delays or misdiagnosis of Valley fever result in an average of $590,000 in extra healthcare costs, including extensive hospital stays and a lifetime of treatment. Current Valley fever diagnostic tests are based on proprietary antibodies or antigens, which may not be easily accessed. We propose that advanced genomic analyses of these fungal pathogens can support the identification of new biomarkers and embody the foundational framework that is necessary for development of new diagnostic tools. We aim to improve the diagnostics available for detection of Coccidioides spp. by analyzing existing genomic data and using in silico predictions to identify several putative antigens that are highly expressed during host infection and would likely interact with the host. We will express these novel antigens along with standard control CF and TP antigens from Coccidioides in a model organism (Escherichia coli) and use the protein products to create an electrochemical sensor Molecularly Imprinted Polymer (MIP) diagnostic assay. MIPs are a polymer that has been processed using a molecular imprinting technique which leaves cavities in the polymer matrix with high affinity for a chosen ‘template’ molecule (in our case the antigens expressed by E. coli). When paired with an electrochemical biosensor, MIPs can be the basis for a low-cost diagnostic tool because they mimic biological recognition well enough to be called ‘synthetic antibodies.’ In total, this proposal represents a unique pairing of advanced genomic data analysis and novel diagnostic development in an important, yet understudied, fungal pathogen.

球虫毒素侵入炎和opadasii是两种导致疾病球虫菌病的土壤真菌，（或山谷发烧），其事件在过去20年中增加了587％，现在造成超过150,000 每年在美国的新感染。疾病控制与预防中心（CDC）报告说治疗山谷发烧的平均费用超过每位患者50,000美元，延迟或山谷热诊断导致平均额外的医疗保健费用为590,000美元，包括大量住院和一生治疗。当前的山谷热诊断测试基于专有抗体或抗原，这可能不是很容易访问。我们建议这些真菌病原体的高级基因组分析可以支持识别新的生物标志物并体现开发的基础框架新的诊断工具。我们旨在改善可用于检测球虫菌SPP的诊断。通过分析现有的基因组数据并在计算机预测中使用以识别几种推定的抗原在宿主感染期间表示，可能与宿主相互作用。我们将表达这些新颖的抗原与模型生物体中球球菌的标准对照CF和TP抗原一起（大肠杆菌）和使用蛋白质产物创建电化学传感器分子印刷聚合物（MIP）诊断测定。 MIPS是一种使用分子烙印技术处理的聚合物在对选择的“模板”分子的高亲和力的聚合物基质中（在我们的情况下，抗原由大肠杆菌）。当与电化学生物传感器配对时，MIP可以成为低成本诊断工具的基础因为它们很好地模仿了生物学识别，足以称为“合成抗体”。总的来说代表了高级基因组数据分析和新型诊断发展的独特配对重要但很了解真菌病原体。