A method for the culture-free discovery and host affiliation of novel viruses from metagenomic samples

一种从宏基因组样本中无需培养地发现新型病毒并确定其宿主归属的方法

• 批准号: 10259447
• 负责人: Ivan Liachko
• 金额: $ 82.04万
• 依托单位: PHASE GENOMICS, INC.
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-02-08 至 2023-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10259447
• 关键词: Affect; Antimicrobial Resistance; Bacteria; Bacteriophages; Biology; Biotechnology; Cells; Chemistry; Communicable Diseases; Communities; Complex; Computer software; Computing Methodologies; Consumption; DNA; DNA Sequence; Data; Data Analyses; Databases; Development; Disease; Ecosystem; Feces; Genome; Genomics; Health; Hi-C; Horizontal Gene Transfer; Human; Human Microbiome; Internet; Libraries; Ligation; Lytic; Measurement; Metabolism; Metagenomics; Methodology; Methods; Microbe; Microbiology; Online Systems; Outcome; Phase; Planets; Play; Population; Predatory Behavior; Preparation; Reagent; Recovery; Reporting; Research; Resistance to infection; Retinal blind spot; Role; Safety; Sampling; Satellite Viruses; Series; Shapes; Site; Technology; Therapeutic; Time; Viral; Viral Genome; Virus; Virus-like particle; Visualization; Work; base; computational platform; contig; crosslink; data quality; experimental study; fecal transplantation; genome analysis; improved; in vivo; interest; metagenome; microbial; microbial community; microbial host; microbiome; microorganism; next generation sequencing; novel; novel strategies; novel virus; particle; resistance gene; restriction enzyme; tool; transmission process; user-friendly; vector; web portal; web-based tool

ABSTRACT In this application, we propose to develop a novel reagent kit and accompanying analytic software platform that employs Hi-C technology for a user-friendly method to assemble viral genomes from metagenomic samples and associate these viruses with their microbial hosts. This product enables culture-free discovery of phages and quantitative measurement of their host range directly in mixed microbial communities. Bacteriophages are viruses that infect bacteria; they shape microbial ecosystems through predation on hosts and through horizontal gene transfer. They are also an important vector in the transmission of anti-microbial resistance. Despite their potent impact on microbial biology, only a tiny proportion of phage genomes are represented in public databases in part because of the difficulty of isolating phage whose hosts are not culturable laboratory settings. This limitation in our ability to understand viral biology has important impacts on emerging biotechnology applications including fecal microbiota transplantation and phage therapy as well as wide-ranging effects on microbiological research. We propose to develop a novel computational approach combined with improved experimental methods to deconvolute viral genomes and perform host attribution from whole microbiome samples without culturing. At the core of this approach is utilization of proximity ligation methods (Hi-C) which physically associates DNA sequences present within intact microbes. This provides direct physical evidence of the contiguity of viral genome sequences and host affiliation information that is not achievable by any other method. The outcome of this direct-to-Phase II proposal would be a combination of kit and user-facing computational platform that would empower both the sophisticated next-generation-sequencing biologist and the sequencing novice to ask important questions about viruses in their microbial community of interest. Aim 1 focuses on computational methods improve the recovery of viral genomes from metagenomic data. Aim 2 develops methodologies to enhance viral Hi-C chemistry. These two aims work together synergistically enhance data quality. Finally, Aim 3 develops a computational platform for data analysis through a web portal where results could be visualized directly via web browser or raw data downloaded for further exploration. Upon completion we will have developed a first-in-class commercial platform to discover viral genomes and identify their hosts from complex microbial communities.

抽象的 在此应用程序中，我们建议开发一个新颖的试剂盒和随附的分析软件平台 采用HI-C技术用于用户友好的方法来从宏基因组样品和 将这些病毒与它们的微生物宿主相关联。该产品可以无文化发现噬菌体和 在混合微生物群落中直接对其宿主范围进行定量测量。 噬菌体是感染细菌的病毒。它们通过宿主的捕食来塑造微生物生态系统 并通过水平基因转移。它们也是抗微生物传播的重要载体 反抗。尽管它们对微生物生物学的有效影响，但只有一小部分的噬菌体基因组是 在公共数据库中代表的部分原因是难以隔离噬菌体的宿主是无法培养的 实验室环境。我们理解病毒生物学能力的这种局限性对新兴产生了重要影响 生物技术应用，包括粪便微生物群移植和噬菌体疗法以及广泛的范围 对微生物研究的影响。 我们建议开发一种新型的计算方法，并结合改进的实验方法 反应病毒基因组并从整个微生物组样品中执行宿主归因，而无需培养。在 这种方法的核心是利用接近连接方法（HI-C），该方法与DNA进行了物理关联 完整微生物中存在的序列。这提供了病毒连续性的直接物理证据 基因组序列和主机隶属信息通过任何其他方法都无法实现。 该直接到相位II提案的结果将是套件和面向用户的计算的结合 平台将赋予先进的下一代生物学家和测序的能力 新手问有关其感兴趣的微生物社区中有关病毒的重要问题。 AIM 1专注于 计算方法改善了从元基因组数据中恢复病毒基因组。 AIM 2发展 增强病毒HI-C化学的方法。这两个目标共同协同增强数据 质量。最后，AIM 3通过Web门户开发了用于数据分析的计算平台，结果 可以通过Web浏览器或下载的原始数据直接可视化，以进行进一步探索。完成后 我们将开发一个一流的商业平台，以发现病毒基因组并识别其宿主 来自复杂的微生物社区。