Development of a screening diagnostic for the detection of viruses and bacteria from body fluids that utilizes the unparalleled structural characterization of mass spectrometry

利用无与伦比的质谱结构表征，开发用于检测体液中病毒和细菌的筛查诊断方法

• 批准号: 10728116
• 负责人: Aaron T Timperman
• 金额: $ 24.14万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-23 至 2025-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10728116
• 关键词: 2019-nCoV; Amino Acid Sequence; Analytical Chemistry; Bacteria; Biological; Biological Assay; Biological Markers; Biomedical Engineering; Body Fluids; Bronchoalveolar Lavage Fluid; COVID-19 detection; Clinical; Communicable Diseases; Coronavirus; Custom; Data; Databases; Detection; Development; Diagnostic; Disease; Early Diagnosis; Engineering; Family; Goals; Health; Healthcare; Human; Human body; Immune system; Infection; Injections; Ions; Label; Liquid substance; Mass Spectrum Analysis; Measures; Medicine; Methods; Microbe; Microbiology; Microfluidics; Modeling; Molds; Monitor; Outcome; Pathogen detection; Pathogenicity; Pennsylvania; Peptides; Performance; Periodicals; Phylogenetic Analysis; Preventive Medicine; Proteins; Proteome; Proteomics; Rapid diagnostics; Reporting; Research; Research Personnel; Respiratory Disease; Reverse Transcriptase Polymerase Chain Reaction; Ribosomal RNA; SARS-CoV-2 variant; Saliva; Sampling; Scanning; Speed; Stable Isotope Labeling; System; Technology; Testing; Universities; Validation; Variant; Viral; Viral Load result; Viral Proteins; Virus; Work; ancestry analysis; clinical diagnosis; clinical diagnostics; clinically relevant; communicable disease diagnosis; computerized data processing; data acquisition; design; detection limit; detection method; diagnostic screening; diagnostic strategy; diagnostic value; disease diagnosis; improved; improved outcome; innovation; mass spectrometer; metaproteomics; microbial; microbiome; microorganism; oral microbiome; pandemic disease; pathogen; pathogenic bacteria; pathogenic virus; personalized approach; personalized medicine; respiratory; respiratory microbiome; response; saliva sample; screening; specific biomarkers; variants of concern; viral detection; virology

Project Summary/Abstract The long-term goal of this project is to develop of a rapid, inexpensive, and sensitive screening diagnostic based on an innovative broad proteomic approach to improve our ability to diagnose infectious disease, monitor changes in the microbiome, measure the state of the host immune system, and identify disease specific biomarkers. Specifically, the initiative will provide proof of principle for a method to achieve simultaneous multi-pathogen detection and deep proteomic microbiome characterization. We will work to detect the presence of several hundred pathogens while also identifying thousands of microbes at clinically relevant levels. The short amino acid sequences or peptides from the proteins will provide markers that range from the virus variant level, such as SARS- CoV-2 variants of concern, to the family level, such as coronaviridae. In developing this diagnostic, a key challenge is to maximize the sensitivity of peptide marker detection while analyzing for many clinically relevant viruses and bacteria. We will therefore compare the performance of (a) a data-dependent acquisition method that searches a custom database and (b) a data-independent acquisition method that can identify thousands of proteins. The proposed study will begin with the analysis of approximately twenty model pathogens before proceeding to the more ambitious analysis of more than 230 oro-respiratory samples. We will assess the primary factors that determine the performance of each method and use our milestones to select one approach for further development. In the end, this research will demonstrate the feasibility of a broad protein-based screening diagnostic that can detect numerous pathogens and provide microbiome profiling to ultimately improve the diagnosis of disease and assessment of human health. The project team includes researchers with diverse expertise from Penn Engineering, Microbiology, and Penn Medicine.

项目摘要/摘要 该项目的长期目标是开发一种快速、廉价和灵敏的筛查方法 基于创新的广泛蛋白质组学方法的诊断，以提高我们的诊断能力 传染病，监测微生物群的变化，测量宿主免疫系统的状态， 并确定疾病特异性生物标记物。具体地说，该倡议将为 一种实现多病原同时检测和深层蛋白质组微生物组的方法 人物刻画。我们将致力于检测数百种病原体的存在，同时还 在临床相关水平鉴定数以千计的微生物。短氨基酸序列或 来自蛋白质的多肽将提供从病毒变异水平的标记，例如SARS- CoV-2变异株令人担忧，到家庭层面，如冠状病毒科。在开发这种诊断方法时，一个关键 挑战是最大限度地提高多肽标志物检测的灵敏度，同时分析许多临床 相关病毒和细菌。因此，我们将比较(A)依赖于数据的 搜索定制数据库的获取方法和(B)独立于数据的获取方法 可以识别数千种蛋白质。拟议的研究将从以下方面开始分析 大约20个模型病原体，然后进行更雄心勃勃的分析 230份口气样本。我们将评估决定每个组件性能的主要因素 方法，并使用我们的里程碑选择一种方法进行进一步开发。到头来，这 研究将证明广泛的基于蛋白质的筛查诊断的可行性，这种筛查诊断可以检测到 多种病原体，并提供微生物组图谱，最终提高疾病的诊断 以及对人类健康的评估。项目团队包括具有不同专业知识的研究人员 宾夕法尼亚大学工程学、微生物学和宾夕法尼亚大学医学院。