Sorbonne Université, CNRS, Institut de Biologie Paris Seine (IBPS), Laboratoire Evolution Paris Seine, F-75005 Paris, France.
Microbiol Spectr. 2018 Apr;6(2). doi: 10.1128/microbiolspec.MTBP-0008-2016.
Understanding how an animal organism and its gut microbes form an integrated biological organization, known as a holobiont, is becoming a central issue in biological studies. Such an organization inevitably involves a complex web of transmission processes that occur on different scales in time and space, across microbes and hosts. Network-based models are introduced in this chapter to tackle aspects of this complexity and to better take into account vertical and horizontal dimensions of transmission. Two types of network-based models are presented, sequence similarity networks and bipartite graphs. One interest of these networks is that they can consider a rich diversity of important players in microbial evolution that are usually excluded from evolutionary studies, like plasmids and viruses. These methods bring forward the notion of "gene externalization," which is defined as the presence of redundant copies of prokaryotic genes on mobile genetic elements (MGEs), and therefore emphasizes a related although distinct process from lateral gene transfer between microbial cells. This chapter introduces guidelines to the construction of these networks, reviews their analysis, and illustrates their possible biological interpretations and uses. The application to human gut microbiomes shows that sequences present in a higher diversity of MGEs have both biased functions and a broader microbial and human host range. These results suggest that an "externalized gut metagenome" is partly common to humans and benefits the gut microbial community. We conclude that testing relationships between microbial genes, microbes, and their animal hosts, using network-based methods, could help to unravel additional mechanisms of transmission in holobionts.
理解动物机体及其肠道微生物如何形成一个被称为整体生物的整合生物组织，正成为生物学研究的一个核心问题。这种组织不可避免地涉及到一个复杂的传播过程网络，这些过程在时间和空间上跨越微生物和宿主发生在不同的尺度上。本章引入基于网络的模型来解决这种复杂性的各个方面，并更好地考虑到传播的垂直和水平维度。本章介绍了两种基于网络的模型，序列相似性网络和二分图。这些网络的一个有趣之处在于，它们可以考虑微生物进化中许多通常被排除在进化研究之外的重要参与者，如质粒和病毒。这些方法提出了“基因外化”的概念，它被定义为原核基因在移动遗传元件（MGE）上存在冗余拷贝，因此强调了与微生物细胞之间的横向基因转移相关但不同的过程。本章介绍了构建这些网络的指南，回顾了它们的分析，并举例说明了它们可能的生物学解释和用途。对人类肠道微生物组的应用表明，在更高多样性的 MGE 中存在的序列既有偏向的功能，又有更广泛的微生物和人类宿主范围。这些结果表明，一个“外化的肠道宏基因组”在某种程度上是人类共有的，并有益于肠道微生物群落。我们得出结论，使用基于网络的方法来测试微生物基因、微生物及其动物宿主之间的关系，可以帮助揭示整体生物中更多的传播机制。
