COMPUTATIONAL FRAMEWORKS FOR PHAGE DISCOVERY, ECOLOGY, AND DYNAMICS FROM METAGENOMES

项目概要/摘要 宏基因组测序对于人类微生物组变得越来越重要 研究。人类微生物群由有益和致病的丰富生态系统组成 影响人类健康的微生物和噬菌体。然而， 由于大多数噬菌体无法分离，因此对噬菌体的研究仍然很少 在实验室里。因此，独立于培养的组学方法，例如 宏基因组学正在成为直接研究噬菌体的重要工具 来自混合社区。然而，病毒学的一个重大挑战是相对 缺乏高质量的生物信息学工具来研究噬菌体 宏基因组数据与可用于原核生物的此类工具的丰富程度进行了比较。 我们将开发几种新颖的算法来研究噬菌体和 他们的生态学来自宏基因组数据，包括发现新的未开垦的 噬菌体、噬菌体群体基因组学、噬菌体分类学、噬菌体：宿主和 噬菌体：代谢相互作用以及整合噬菌体的动力学。我们的 方法将通过开放获取的开发和发布而正式化 基于FAIR（公平、可访问、可互操作、可重用）的数据库和软件 数据原则，这将使研究中的基本问题成为可能 噬菌体生态学调控人类健康。展示实用性和广泛性 我们的方法研究噬菌体的适用性，我们将把它们应用到不同的领域 来自公开来源的人类微生物组的宏基因组数据集 可用数据和一些现有的合作。虽然我们的方法是设计的 对于从宏基因组数据研究噬菌体，它们也可以应用 广泛用于所有病毒的研究，包括来自宏转录组的RNA噬菌体 感染真核生物的数据和病毒。成功完成该项目将 提供可扩展的生物信息学方法，可广泛应用于研究 来自宏基因组数据的噬菌体。

Project Summary/Abstract Metagenomics sequencing is increasingly becoming important for human microbiome research. Human microbiomes comprise a rich ecosystem of beneficial and pathogenic microorganisms and bacteriophages that can influence human health. Yet, bacteriophages remain poorly studied because most bacteriophages cannot be isolated in a laboratory. As a result, cultivation-independent omics approaches such as metagenomics are emerging as important tools for studying bacteriophages directly from mixed communities. However, a significant challenge in virology is the relative absence of high-quality bioinformatics tools to enable the study of bacteriophages from metagenomics data compared to the abundance of such tools available for prokaryotes. We will develop several novel algorithms to enable the study of bacteriophages and their ecology from metagenomics data, including for the discovery of novel uncultivated phages, phage population genomics, phage taxonomy, phage:host and phage:metabolism interactions, and the dynamics of integrated phages. Our approaches will be formalized through the development and release of open access databases and software based on FAIR (Fair, Accessible, Interoperable, Reusable) data principles, which will enable investigation of fundamental questions in bacteriophage ecology governing human health. To demonstrate the utility and wide applicability of our methods to study bacteriophages, we will apply them on a diverse group of metagenome data sets from human microbiomes sourced from publicly available data and several existing collaborations. While our approaches are designed for the study of bacteriophages from metagenome data, they can also be applied broadly towards the study of all viruses including RNA phages from metatranscriptomic data and viruses infecting eukaryotes. Successfully accomplishing this project will provide scalable bioinformatics approaches that can be widely applied to the study of bacteriophages from metagenomics data.