Integrating time, function, phylogenetics and genome dynamics to redefine microbial diversity

整合时间、功能、系统发育学和基因组动力学，重新定义微生物多样性

• 批准号: RGPIN-2017-05141
• 负责人: Beiko, Robert
• 金额: $ 2.91万
• 依托单位: Dalhousie University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=687810
• 关键词: Integrating; time; function; phylogenetics; genome

Thanks to advances in DNA sequencing technology and bioinformatics, we know more about microorganisms and microbial communities than ever before. Work in the last thirty years has revealed a stunning diversity of microbes in every habitat on Earth, and researchers are now trying to connect this diversity to ecosystem function in settings as varied as wastewater reactors and the human gut. Understanding the microbes in a given habitat (the microbiome) opens up new applications including mitigation of human disease and remediation of contaminated sites.******Although this “microbial revolution” has great promise, researchers struggle to understand the microbiome in depth. The remarkable diversity of microbial species, which can exceed 1,000 in a single environmental sample, is a significant barrier to understanding the ecology of a system. Many habitats also contain millions of distinct microbial genes, a number that dwarfs the 20,000-25,000 genes in the human genome. However, the most critical limiting factor is that we don't know what patterns to look for when we examine microbial communities. Methods that presuppose natural groupings such as species inevitably miss important patterns in the data, and we need to expand our microbiomics toolbox with new representations of microbial diversity.******My research program is concerned with diversity and evolution of the microbiome. This proposal encompasses two complementary projects that will advance our ability to deconstruct and describe microbial communities. First, we will develop new ecological models that treat individual genes as species, and represent an organism as an entire ecosystem in which these genes interact. This “gene ecology” model will allow us to map traditional concepts such as diversity, dispersal, and competition into the study of microbial genomes. Second, we will develop new definitions of biodiversity units that are based on covariance through time, co-occurrence in multiple habitats, similar functions and ecological roles, as well as traditional taxonomic similarity. These new definitions will produce a prohibitively large number of candidate units, and we will develop new approaches to identify and interpret the candidates that are most relevant to a particular ecological question.******Microbial gene ecology will provide a better understanding of the complex interactions between gene products in the microbiome, and an expanded set of candidate units will help us better evaluate changes in microbial community composition. Taken together, these techniques will tell us which members of a microbial community are playing which roles, how different members of the community are interacting with one another, and how communities are likely to respond to changes in their environment. This understanding will be essential as we try to develop microbial solutions to a host of problems in human health and the environment.

由于DNA测序技术和生物信息学的进步，我们比以往任何时候都更了解微生物和微生物群落。过去30年的研究揭示了地球上每个栖息地中微生物的惊人多样性，研究人员现在正试图将这种多样性与从废水反应堆到人类肠道等各种环境中的生态系统功能联系起来。了解特定栖息地(微生物组)中的微生物开辟了新的应用领域，包括缓解人类疾病和修复受污染的地点。*尽管这场“微生物革命”前景光明，但研究人员仍难以深入了解微生物组。微生物物种的显著多样性，在一个环境样本中可以超过1000个，这是理解一个系统生态的一个重要障碍。许多栖息地还包含数百万个不同的微生物基因，这个数字使人类基因组中的20,000-25,000个基因相形见绌。然而，最关键的限制因素是，当我们检查微生物群落时，我们不知道要寻找什么模式。以物种等自然分类为前提的方法不可避免地遗漏了数据中的重要模式，我们需要用微生物多样性的新表示来扩展我们的微生物学工具箱。我的研究计划与微生物组的多样性和进化有关。这项提议包括两个互补的项目，它们将提高我们解构和描述微生物群落的能力。首先，我们将开发新的生态模型，将单个基因视为物种，并将有机体表示为这些基因相互作用的整个生态系统。这一“基因生态”模型将允许我们将多样性、扩散和竞争等传统概念映射到微生物基因组的研究中。第二，我们将制定新的生物多样性单位定义，这些单位基于随时间的协方差、多个生境中的共生、相似的功能和生态角色以及传统的分类相似性。这些新的定义将产生令人望而却步的大量候选单元，我们将开发新的方法来识别和解释与特定生态问题最相关的候选单元。微生物基因生态学将提供更好的理解微生物组中基因产物之间的复杂相互作用，而一组扩大的候选单元将帮助我们更好地评估微生物群落组成的变化。综上所述，这些技术将告诉我们微生物群落的哪些成员扮演着哪些角色，群落的不同成员如何相互作用，以及群落可能如何应对环境的变化。当我们试图为人类健康和环境中的一系列问题开发微生物解决方案时，这种理解将是至关重要的。