DISSERTATION RESEARCH: A trait-based approach for understanding the relationship between microbial community assembly and metabolic function

论文研究：一种基于性状的方法，用于理解微生物群落组装与代谢功能之间的关系

• 批准号: 1701467
• 负责人: Vincent Denef
• 金额: $ 1.86万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-06-15 至 2019-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1701467&HistoricalAwards=false
• 关键词: DISSERTATION; RESEARCH; trait; based; approach

Bacteria compose the majority of the planetary biodiversity and inhabit almost every corner of our planet. Bacteria are the engines that drive Earth's biogeochemical cycles and help to sustain life. Scientific papers are published daily on what types of bacteria live in every imaginable ecosystem. Scientists have found patterns of bacteria community composition in relation to environmental (e.g. temperature, pH, etc.) or host (e.g. disease history, cancer state, etc.) characteristics, but the underlying reasons for the observed patterns remain unclear. Connecting these patterns to a general conceptual framework of how microbes interact with each other and their environment will help scientists to better manage microbes in systems that directly affect people such as human pathogens and wastewater treatment plants. This research will be a step towards addressing this gap in knowledge by adapting frameworks developed in plant systems based on functional characteristics (traits) to microbial ecology, allowing examination of connections between lake bacterial diversity and ecosystems processes using a mechanistic approach. A computational workflow of this project's analysis will be publicly available and used to create open access online educational tools to aid in teaching computational analyses, scientific reproducibility, and programming literacy. Finally, this workflow will be put together to teach a half day workshop at the Ecological Society of America conference. This research examines how the relationship between bacterial diversity and secondary productivity is constrained by the traits that determine community assembly. Through a comparative genomic analysis of published and newly reconstructed bacterial genomes from environmental genomic data, this project will identify DNA-inferred (a) response traits that control the differences in bacterial community composition and (b) effect traits that determine the presence or absence of a diversity-productivity relationship. The identified genes and inferred traits will help expand current understanding of how bacterial community assembly and processes affect ecosystem function. This understanding will improve linkages between microbial community and ecosystem ecology principles.

细菌构成了地球生物多样性的大部分，几乎栖息在地球的每个角落。 细菌是驱动地球生物地球化学循环并帮助维持生命的引擎。 每天都会发表关于每种可以想象的生态系统中生活着哪些类型的细菌的科学论文。科学家们发现了与环境（例如温度、pH 等）或宿主（例如疾病史、癌症状态等）特征相关的细菌群落组成模式，但观察到的模式的根本原因仍不清楚。将这些模式与微生物之间及其环境如何相互作用的一般概念框架联系起来，将有助于科学家更好地管理直接影响人类的系统中的微生物，例如人类病原体和废水处理厂。 这项研究将根据微生物生态学的功能特征（性状）调整植物系统中开发的框架，从而朝着解决这一知识差距迈出一步，从而能够使用机械方法检查湖泊细菌多样性与生态系统过程之间的联系。 该项目分析的计算工作流程将公开，并用于创建开放获取的在线教育工具，以帮助教授计算分析、科学再现性和编程素养。最后，该工作流程将整合在一起，在美国生态学会会议上举办半天的研讨会。 这项研究探讨了细菌多样性和次级生产力之间的关系如何受到决定群落组装的特征的限制。通过对环境基因组数据中已发表的和新重建的细菌基因组进行比较基因组分析，该项目将识别 DNA 推断的 (a) 控制细菌群落组成差异的反应特征和 (b) 决定多样性-生产力关系是否存在的效应特征。 已识别的基因和推断的特征将有助于扩大目前对细菌群落组装和过程如何影响生态系统功能的理解。 这种理解将改善微生物群落和生态系统生态学原理之间的联系。