Exploiting Viral Genomics to Understand Disease

利用病毒基因组学来了解疾病

• 批准号: 8831594
• 负责人: Suman Ranjan Das
• 金额: $ 289.5万
• 依托单位: J. CRAIG VENTER INSTITUTE, INC.
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/8831594
• 关键词: Algorithms; Animal Viruses; Animals; Antiviral Agents; Antiviral resistance; Bioinformatics; Bioterrorism; Communicable Diseases; Communities; Data; Data Set; Disease; Disease Outbreaks; Epidemic; Evolution; Family; Genetic Recombination; Genetic Variation; Genome; Genomic approach; Genomics; Human; Human Virus; Immune response; Institutes; National Institute of Allergy and Infectious Disease; Pathogenesis; Phylogenetic Analysis; Public Health; Research Project Grants; Sequence Analysis; Vaccines; Viral; Viral Pathogenesis; Virus; Virus Diseases; deep sequencing; genome sequencing; metagenomic sequencing; microbiome; next generation sequencing; novel; pandemic disease; pandemic preparedness; pathogen; response; transcriptomics; transmission process

Research' Project 1 focuses on significant endemic viral pathogens from humans and viruses from animal hosts that have strong zoonotic potential. High-throughput whole-genome next-generation sequencing (NGS), combined with bioinformatics algorithms, will be used to sequence and analyze the genomes from more than 10,000 strains representing seven viral species. This will characterize the genetic diversity over a range of virus families, including many NIAID priority pathogens, to understand critical evolutionary mechanisms central to viral evolution, pathogenesis, transmission, and/or antiviral resistance. Specifically we aim to: 1) compare and contrast the genetic diversity and evolutionary dynamics of viruses circulating within and/or between humans and animal reservoirs, 2) elucidate viral-host-microbiome determinants that influence viral pathogenesis, and 3) perform deep sequencing to understand intra-host viral diversity, transmission dynamics, and antiviral resistance. Collectively, this project will use multiple genomics approaches (e.g., genomic sequencing, metagenomics, and transcriptomics) to provide the scientific community with genomic data sets of broad use from important viral families. These data will be analyzed using phylogenetics and other bioinformatics algorithms to show the spatial and temporal evolution of these pathogens. Finally, the data generated will identify, track, and predict antigenic drift/shift, recombination, escape from natural or vaccine-induced host immune responses, antiviral resistance, inter- and intra-species transmission, and the response of a host's commensal microbiota to viral infection. The information generated from these studies will help us to produce superior vaccines and antivirals, and the data sets will prove critical for rapid responses to the emergence of novel pathogens (i.e., pandemic preparedness) that arise naturally or as a result of bioterrorism.

研究项目1的重点是来自人类和动物的重要地方性病毒病原体 具有很强的人畜共患病潜力的宿主。高通量全基因组下一代测序 (NGS)结合生物信息学算法，将用于测序和分析来自 超过10，000株代表7种病毒。这将描述遗传多样性超过一个 一系列病毒家族，包括许多NIAID优先病原体，以了解关键的进化 病毒进化、发病机制、传播和/或抗病毒抗性的核心机制。另外还 目的是：1）比较和对比病毒的遗传多样性和进化动力学， 和/或人与动物储库之间，2）阐明病毒-宿主-微生物组决定因子， 影响病毒发病机制，以及3）进行深度测序以了解宿主内病毒多样性， 传播动力学和抗病毒耐药性。 总的来说，该项目将使用多种基因组学方法（例如，基因组测序，宏基因组学， 和转录组学），为科学界提供广泛使用的基因组数据集， 病毒家族。这些数据将使用遗传学和其他生物信息学算法进行分析， 这些病原体的时空演变最后，生成的数据将识别、跟踪和 预测抗原漂移/转移、重组、逃避天然或疫苗诱导的宿主免疫应答， 抗病毒耐药性、种间和种内传播以及宿主的免疫应答 微生物群到病毒感染。从这些研究中产生的信息将帮助我们生产出上级 疫苗和抗病毒药物，数据集将被证明是对新出现的快速反应至关重要。 病原体（即，大流行病的准备），自然产生的或由于生物恐怖主义。