globalchange  > 全球变化的国际研究计划
项目编号: 1701467
项目名称:
DISSERTATION RESEARCH: A trait-based approach for understanding the relationship between microbial community assembly and metabolic function
作者: Vincent Denef
承担单位: University of Michigan Ann Arbor
批准年: 2017
开始日期: 2017-06-15
结束日期: 2019-05-31
资助金额: 18610
资助来源: US-NSF
项目类别: Standard Grant
国家: US
语种: 英语
特色学科分类: Biological Sciences - Environmental Biology
英文关键词: bacterium ; pattern ; trait ; research ; reason ; biogeochemical cycle ; bacterial genome ; microbial ecology ; programming literacy ; teaching computational analysis ; computational workflow ; environmental genomic datum ; cancer state ; scientific papers ; wastewater treatment plant ; comparative genomic analysis ; disease history ; planetary biodiversity ; general conceptual framework ; secondary productivity ; mechanistic approach ; imaginable ecosystem ; plant system ; ecosystem function ; bacterial community assembly ; open access online educational tool ; america conference ; effect trait ; response trait ; bacterial diversity ; microbial community ; ecological society ; lake bacterial diversity ; diversity-productivity relationship ; current understanding ; bacterial community composition ; bacterium community composition ; day workshop ; human pathogen ; functional characteristic ; community assembly
英文摘要: 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.
资源类型: 项目
标识符: http://119.78.100.158/handle/2HF3EXSE/90017
Appears in Collections:全球变化的国际研究计划
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Vincent Denef. DISSERTATION RESEARCH: A trait-based approach for understanding the relationship between microbial community assembly and metabolic function. 2017-01-01.
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