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.

项目概要/摘要 该项目的长期目标是开发一种快速、廉价且灵敏的筛查方法 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，监测微生物组的变化，测量宿主免疫系统的状态， 并识别疾病特异性生物标志物。具体来说，该倡议将为 实现同时多病原体检测和深层蛋白质组微生物组的方法 表征。我们将努力检测数百种病原体的存在，同时 识别临床相关水平的数千种微生物。短氨基酸序列或 来自蛋白质的肽将提供从病毒变体水平到范围的标记，例如 SARS- 值得关注的 CoV-2 变体，达到科水平，例如冠状病毒科。在开发这种诊断方法时，一个关键 面临的挑战是在分析许多临床肽标记物时最大限度地提高肽标记物检测的灵敏度 相关病毒和细菌。因此，我们将比较（a）数据依赖的性能 搜索自定义数据库的采集方法和 (b) 与数据无关的采集方法 可以识别数千种蛋白质。拟议的研究将从分析开始 在对超过 20 种病原体进行更雄心勃勃的分析之前 230 个口腔呼吸道样本。我们将评估决定每个性能的主要因素 方法并使用我们的里程碑来选择一种方法进行进一步开发。最后，这 研究将证明基于蛋白质的广泛筛查诊断的可行性，该诊断可以检测 多种病原体并提供微生物组分析以最终改善疾病的诊断 和人类健康评估。该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。