人体噬菌体的时空间传递及其与宿主交互响应的研究

Considering the effect of phages on flora balance and gene delivery, human microbiome has been surveyed from a new perspective and the role of phages played in micro-ecosystems and human health were considered. However, existing tools of phage analysis mostly rely on database of annotated viral genomes, and novel phage identification still has difficulties. The diversities and genetic variations of virome were usually neglected by these tools, which severely limited the research on human phage. This project plans to develop identification technologies of phages and their bacterial hosts, including high-throughput methods of scanning lysogenic phage based on graph theory, de novo phage recognition based on bacterial acquired immune elements, and phage-host mating strategy based on machine learning algorithms. By using such technologies, phages and their bacterial hosts would be identified from metagenomic sequencing data of HMP and paired samples from four typical body sites and one-year longitudinal sampling. Additionally, we will explore the composition and variation of phage communities, and track their temporal and spatial transmission between individuals and body sites. Finally, replacement of bacterial immune elements response to phage exposure, restriction site modification of phages avoiding bacterial immune, phage spread between bacteria and across body sites, in addition to the potential effects of virulence factors and antibiotic resistances carried by phages would also be investigated. It is expected to unveil the distribution and transmission of phages in human micro-ecosystem and over time, as well as the interactions across phages, bacteria and human, and toward a better understanding of the complex relationship between microbiome and human health.

鉴于噬菌体在菌群平衡及基因传递方面的作用，研究者开始关注它们在微生态系统及人体健康中扮演的角色。现有分析工具多依赖已知数据信息，对未知噬菌体的辨识存在困难，严重限制了人体噬菌体研究的发展。本项目拟从开发噬菌体及其宿主序列的新型识别方法入手，建立基于图论的溶原噬菌体高通量筛选技术、基于获得性免疫元件的从头识别和基于深度学习算法的噬菌体与宿主菌联配策略。利用构建的新型计算方法，从人体微生物组及四个典型身体位点配对、一年时间梯度采样的宏基因组测序数据中识别噬菌体及其宿主，探寻群落组成与差异及交流，追踪位点间的时空间传递。重点分析细菌免疫元件更替对噬菌体暴露的响应，噬菌体避免宿主菌免疫的酶切位点修饰，及其携带的毒力因子和耐药基因等对人体的潜在效应。预期揭示噬菌体在人体微环境及随时间的分布传递规律，以及噬菌体与细菌及人类宿主间的交互及影响，为解析微生物间复杂相互作用、全面理解人体微生物组提供帮助。

噬菌体是人体微生物组中的特殊群体以及病毒组的主要成分。它们与细菌宿主之间发生复杂的相互作用，直接或间接地对人体健康产生影响。近年来，越来越多的人体微生物研究开始关注噬菌体，探索它们在菌群调控及与宿主交互中扮演的角色。但由于其高水平的变异和遗传多样性，大部分寄居在人体中的噬菌体，在现存的病毒数据库中缺少同源序列，导致未能被有效认识。本项目以建立识别噬菌体及其宿主联配信号的计算方法为基础，开展噬菌体在不同人群和部位配对样本中分布和传递规律的研究，进而通过纵向追踪多位点群落动态变化，对人体噬菌体群落组成、菌群调控及基因功能方面进行研究。项目搭建了一套从宏基因组中从头识别接头区序列、前间区序列、联配噬菌体及其细菌宿主的方法，能够从微生物组学数据中准确识别噬菌体序列，辅以GC含量和覆盖度信息，可以快速、准确地从海量组学数据中挖掘出噬菌体及其宿主菌基因组，为利用高通量测序方法大规模发掘新噬菌体以及人体病毒组研究提供了方法借鉴。项目获得了4个身体部位6种类型486个样本共3.85 Tb的宏基因组自测数据集，绘制了最早占据人体生境的先锋噬菌体与病毒组的全景，从顺产新生儿的口腔检测到了更多的阴道噬菌体，主要是乳酸杆菌噬菌体，提出了人体最初的噬菌体沿着阴道-口腔线路迅速扩散的观点。项目同时整理建立了一个涵盖50余个公共测序项目10134个样本和相应信息的宏基因组数据集，解析了不同地域、生理状态和环境暴露的人群之间以及人体部位之间噬菌体群落分布及其基因组结构和辅助代谢基因的特征，揭示了噬菌体与细菌宿主及完整微生物群落之间互作和时空间动态的规律，阐示了噬菌体在人体共生微生物群落中发挥的潜在调控功能，提升了我们对噬菌体调控菌群、辅助代谢及影响健康的理解能力，为利用噬菌体控制菌群靶向维护健康奠定了理论基础。

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