I-Corps: Next-Gen Diagnostics

I-Corps：下一代诊断

• 批准号: 1334101
• 负责人: Keith Crandall
• 金额: $ 5万
• 依托单位: George Washington University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-04-15 至 2014-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1334101&HistoricalAwards=false
• 关键词: Corps; Next; Gen; Diagnostics

Researchers have developed a sequencing application and associated bioinformatics techniques to rapidly and accurately identify pathogens. Data and samples are analyzed using the research team's bioinformatic approach that uses a Bayesian reassignment model to accurately identify pathogens to a known database with 1) high accuracy, even 2) with low coverage, and 3) with mixed samples, 4) no need for sequence assembly, and 5) report back not only accurate species diagnostics, but also relevant information on antibiotic/antiviral resistance mutations. Most approaches currently used rely on old microbiology techniques for growing cultures from samples (a week long process) and identifying pathogens through visual inspection. This approach has the added advantage, because it is a genomic approach, of also providing insights into drug resistance through the identification of drug resistant variants thus better informing treatment options.Accurate and rapid pathogen diagnostics is critical to a number of areas of commercial importance including food safety, human health, and veterinary medicine. This approach has the potential to revolutionize pathogen diagnostics in multiple areas including food safety, hospital hygiene, veterinary care, and human health. The approach used by the research team has the potential to be more rapid, accurate, and cost-effective. It capitalizes on next-generation sequence data to characterize the diversity and extent of pathogen infection.

研究人员开发了一种测序应用程序和相关的生物信息学技术，以快速和准确地识别病原体。数据和样本使用研究团队的生物信息学方法进行分析，该方法使用贝叶斯重新分配模型来准确地将病原体识别到已知数据库中，1)高精度，甚至2)低覆盖率，3)混合样本，4)不需要序列组装，5)不仅报告准确的物种诊断，而且报告抗生素/抗病毒耐药性突变的相关信息。目前使用的大多数方法依赖于旧的微生物技术，从样本中培养培养物(长达一周的过程)，并通过肉眼检查识别病原体。这种方法还有一个额外的优势，因为它是一种基因组方法，通过识别耐药变异来提供对耐药性的洞察，从而更好地指导治疗选择。准确和快速的病原体诊断对于包括食品安全、人类健康和兽医在内的许多商业重要领域至关重要。这种方法有可能在包括食品安全、医院卫生、兽医护理和人类健康在内的多个领域的病原体诊断方面发生革命性的变化。研究团队使用的方法有可能更快、更准确、更具成本效益。它利用下一代序列数据来表征病原体感染的多样性和程度。