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.

Coccidioides immitis 和 C. posadasii 是引起球孢子菌病的两种土壤真菌，（或谷热），其发病率在过去 20 年中增加了 587%，目前已导致超过 150,000 人死亡美国疾病控制与预防中心 (CDC) 每年都会报告新感染病例。治疗山谷热的平均费用为每位患者超过 50,000 美元，并且山谷热的延误或误诊平均导致 590,000 美元的额外医疗费用，包括长期住院和终生目前的谷热诊断测试基于专有抗体或抗原，但可能并非如此。我们建议对这些真菌病原体进行先进的基因组分析可以支持识别新的生物标志物并体现开发所需的基础框架我们的目标是通过分析来改进可用于检测球孢子菌的诊断方法。现有的基因组数据并使用计算机预测来识别几种高度可靠的推定抗原在宿主感染期间表达并可能与宿主相互作用。我们将表达这些新抗原。以及模型生物体（大肠杆菌）中球孢子菌的标准对照 CF 和 TP 抗原以及使用蛋白质产品创建电化学传感器分子印迹聚合物 (MIP) 诊断 MIP 是一种使用分子印迹技术加工而成的聚合物，会留下空腔。在聚合物基质中对选定的“模板”分子具有高亲和力（在我们的例子中，抗原表达为当与电化学生物传感器配合使用时，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识别，可以被称为“合成抗体”。总的来说，这个提议代表了先进的基因组数据分析和新颖的诊断开发的独特组合重要但尚未得到充分研究的真菌病原体。