Culture Independent Leptospira Comparative Whole Genome Analysis

培养独立的钩端螺旋体比较全基因组分析

• 批准号: 10287936
• 负责人: Michael A Matthias
• 金额: $ 25.13万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-01 至 2023-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10287936
• 关键词: Acute; Acute Renal Failure with Renal Papillary Necrosis; Ambulatory Care Facilities; Biological Assay; Biology; Candidate Disease Gene; Case Fatality Rates; Cholera; Classification; Clinical; Clinical Data; Clinical Management; Complication; Comprehension; Cytotoxin; Data; Development; Diagnostic; Diagnostic tests; Disease; Disease Management; Disease Outbreaks; Epidemic; Epidemiology; Fatality rate; Fever; Floods; Funding; Genes; Genome; Geography; Hospitalization; Human; Hurricane; Infection; Knowledge; Laboratories; Leptospira; Leptospira interrogans; Leptospirosis; Link; Metadata; Myocardial; Organism; Outcome; Pathogenesis; Pathogenicity; Patients; Prognostic Marker; Prospective Studies; Proteins; Public Health; Puerto Rico; Risk; Risk Assessment; Sample Size; Sampling; Serotyping; Serum; Shotguns; Sister; Source; Sri Lanka; Time; Typhoid Fever; Undifferentiated; United States National Institutes of Health; Validation; Virulence; Work; analytical tool; antigen detection; assay development; base; biobank; burden of illness; clinical risk; comparative; cost; diagnostic biomarker; disability-adjusted life years; disease phenotype; epidemiologic data; gene discovery; genome analysis; improved; insight; metagenomic sequencing; novel strategies; programs; rapid test; success; trend; whole genome; years of life lost

PROJECT SUMMARY This study is the culmination of years of careful preliminary work spent developing and validating a versatile CWGA workflow that both improves upon the quality and reliability of available Leptospira genome data and is capable of producing (and analyzing) these data directly from clinical samples — a crucial advance, as most current studies avoid the cost of Leptospira culture. Crucial gaps in our understanding of Leptospira virulence and pathogenetic mechanisms of disease persist due to the restricted scope, debatable quality and inherent bias of publicly available genome data that blunt the power of CWGA. Our first objective here is to apply this new approach to SMS data generated from a large biobank of 592 de-identified acute human serum samples (with relevant demographic, clinical and epidemiological metadata) to identify Leptospira genes, with appropriate sample distribution linked, linked to severe complications and poor outcomes (and) of human leptospirosis presuming that these include reliable diagnostic targets and risk assessment markers (“prognostic indicators”). Biobank sera originate from a recent NIH/NIIAID-funded prospective study of human leptospirosis in Sri Lanka and include >400 from laboratory confirmed leptospirosis cases from which we obtained 25 Leptospira isolates belonging to 5 discrete species and comprising at least 12 previously unreported serotypes. The low culture success rate (<6%) — further confirmation of the desperate need for analytical tools that avoid Leptospira culture — prompted development of a culture independent CWGA workflow featured in the current study. Next, reliable candidate genes so identified will be used as substrates for qPCR assay development with subsequent cross validation against a second large biobank of unrelated sera derived from a recent flood associated outbreak of leptospirosis in Puerto Rico. Our success here should lay the groundwork for rapid development of antigen-detection diagnostic tests and would have an immediate and profound impact on the Leptospira field. Moreover, untethered from the inefficiency and bias of Leptospira culture, CWGA offers unprecedented insight into fundamental Leptospira biology.

项目摘要 这项研究是多年来精心准备工作的结果，这些工作用于开发和验证一种多功能的 CWGA工作流程，既提高了可用钩端螺旋体基因组数据的质量和可靠性， 能够直接从临床样本中产生（和分析）这些数据-这是一个至关重要的进步，因为大多数 目前的研究避免了钩端螺旋体培养的成本。我们对钩端螺旋体毒力的理解存在重大差距， 疾病的发病机制持续存在，由于有限的范围，有争议的质量和固有的偏见， 公开可用的基因组数据，削弱了CWGA的力量。我们的第一个目标是应用这个新的 从592个去识别急性人血清样本的大型生物库中生成的SMS数据的方法（ 相关的人口统计学、临床和流行病学元数据），以确定钩端螺旋体基因， 样本分布相关，与人类钩端螺旋体病的严重并发症和不良结局（和）相关 假定这些包括可靠的诊断目标和风险评估标记（“预后指标”）。 生物样本库血清来源于最近NIH/NIIAID资助的斯里兰卡人钩端螺旋体病前瞻性研究 包括>400例实验室确诊的钩端螺旋体病病例，从中我们获得了25株钩端螺旋体分离株 属于5个离散的物种并且包含至少12种先前未报道的血清型。低文化 成功率（<6%）-进一步证实迫切需要避免钩端螺旋体培养的分析工具 - 促进了当前研究中的文化独立CWGA工作流程的发展。接下来， 如此鉴定的可靠候选基因将用作qPCR测定开发的底物， 与第二个大型生物样本库的交叉验证，该样本库包含来自最近洪水相关爆发的不相关血清 波多黎各的钩端螺旋体病。 我们在这方面的成功应该为抗原检测诊断测试的快速发展奠定基础 并将对钩端螺旋体领域产生直接而深远的影响。此外，不受 低效率和偏见的钩端螺旋体培养，CWGA提供了前所未有的洞察基本钩端螺旋体 生物学