Untangling the complex geographic and evolutionary patterns of microbes

微生物的微小尺寸掩盖了它们非凡的复杂性。尽管它们的大小，大多数微生物有几千个基因编码广泛的代谢和细胞功能，一些通过横向基因转移（LGT）过程从远亲获得。抗生素耐药性的传播和对污染场地等挑战性环境的适应是微生物LGT对社会影响的特别引人注目的例子。LGT的一个后果是，建立一个生命之树来了解微生物的进化可能是不可能的，或者是一个毫无意义的练习，因为如此多的遗传信息已经在遥远的谱系之间共享。我提出的研究的第一部分将解决这个问题，通过使用新的标准来组装对LGT的影响更具抵抗力的树，并通过开发系统发育网络方法来有效地显示垂直（父母到后代）和横向连接。这项工作的一个关键目标是用一个尽管复杂性增加但可以理解的网络来取代经典的生命树。 微生物很少单独行动：相反，它们通常存在于包含从极端环境中的少数不同物种到我们肠道，土壤和海洋中的数百或潜在数千种的社区中。微生物群落的成员可以决定其功能;例如，不同的群落与各种类型的微生物疾病的不同临床结果相关。我们开发了GenGIS，一个地理信息系统，让用户测试假设的微生物群落结构和潜在的影响因素之间的关系，使用用户提出的地理梯度。该提案的第二部分将扩展GenGIS，以评估所有可能的简单梯度和更复杂梯度的一个大子集，将扩散模式与地理和环境因素联系起来。微生物使地球上所有其他生命成为可能，我们的方法将有助于了解可能导致这些基本社区发生变化的关键影响和风险因素。

The tiny size of microorganisms belies their extraordinary complexity. In spite of their size, most microbes have several thousand genes that encode a wide range of metabolic and cellular functions, some acquired from distant relatives through the process of lateral gene transfer (LGT). The spread of antibiotic resistance and adaptation to challenging environments such as polluted sites are particularly compelling examples of the impact of microbial LGT on society. One consequence of LGT is that building a Tree of Life to understand the evolution of microorganisms may be impossible or a meaningless exercise, since so much genetic information has been shared between distant lineages. The first part of my proposed research will address this question, by using new criteria to assemble trees that are more resistant to the effects of LGT, and by developing phylogenetic network approaches that can effectively show both vertical (parent-to-offspring) and lateral connections. A key objective of this work will be to replace the canonical Tree of Life with a network that is understandable in spite of its increased complexity. Microbes rarely act alone: instead they are commonly found in communities containing anywhere from a handful of different species in extreme environments, to hundreds or potentially thousands in our gut, in soil, and in the sea. The membership of a microbial community can determine its function; for example, different communities are associated with different clinical outcomes in various types of microbial disease. We have developed GenGIS, a geographic information system that lets a user test hypotheses about the relationship between microbial community structure and potential influencing factors using user-proposed geographic gradients. The second part of this proposal will extend GenGIS to evaluate all possible simple gradients and a large subset of more-complex ones, to relate patterns of dispersal to geographic and environmental factors. Microbes make all other life on Earth possible, and our approaches will help to understand critical influencing and risk factors that can lead to changes in these fundamental communities.