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StressChip as a High-Throughput Tool for Assessing Microbial Community Responses to Environmental Stresses

机译:StressChip作为评估微生物群落对环境压力反应的高通量工具

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摘要

Microbial community responses to environmental stresses are critical for microbial growth, survival, and adaptation. To fill major gaps in our ability to discern the influence of environmental changes on microbial communities from engineered and natural environments, a functional gene-based microarray, termed StressChip, has been developed. First, 46 functional genes involved in microbial responses to environmental stresses such as changes to temperature, osmolarity, oxidative status, nutrient limitation, or general stress response were selected and curated. A total of 22,855 probes were designed, covering 79,628 coding sequences from 985 bacterial, 76 archaeal, and 59 eukaryotic species/strains. Probe specificity was computationally verified. Second, the usefulness of functional genes as indicators of stress response was examined by surveying their distribution in metagenome data sets. The abundance of individual stress response genes is consistent with expected distributions based on respective habitats. Third, the StressChip was used to analyze marine microbial communities from the Deepwater Horizon oil spill. That functional stress response genes were detected in higher abundance (p < 0.05) in oil plume compared to nonplume samples indicated shifts in community composition and structure, consistent with previous results. In summary, StressChip provides a new tool for accessing microbial community functional structure and responses to environmental changes.
机译:微生物群落对环境压力的反应对于微生物的生长,存活和适应至关重要。为了弥补我们从工程环境和自然环境中识别环境变化对微生物群落影响的能力方面的主要空白,已开发出一种基于功能基因的微阵列,称为StressChip。首先,选择并整理了涉及微生物对环境压力(例如温度,渗透压,氧化状态,营养限制或一般压力反应)的响应的46个功能基因。共设计了22855个探针,涵盖来自985个细菌,76个古细菌和59个真核物种/菌株的79628个编码序列。探针特异性已通过计算验证。其次,通过调查功能基因在元基因组数据集中的分布,检查了功能基因作为应激反应指标的有用性。单个应激反应基因的丰度与基于各自生境的预期分布相一致。第三,StressChip用于分析“深水地平线”溢油中的海洋微生物群落。与非软泥样品相比,在油羽中检出的功能性应激反应基因丰度更高(p <0.05),表明群落组成和结构发生了变化,与先前的结果一致。总之,StressChip提供了一种新的工具来访问微生物群落功能结构和对环境变化的响应。

著录项

  • 来源
    《Environmental Science & Technology》 |2013年第17期|9841-9849|共9页
  • 作者单位

    Institute for Environmental Genomics, Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma 73019, United States;

    Institute for Environmental Genomics, Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma 73019, United States;

    Institute for Environmental Genomics, Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma 73019, United States;

    Institute for Environmental Genomics, Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma 73019, United States,College of Life Sciences, Zhejiang University, Hangzhou 310058, China;

    Institute for Environmental Genomics, Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma 73019, United States;

    Institute for Environmental Genomics, Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma 73019, United States;

    Institute for Environmental Genomics, Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma 73019, United States;

    Institute for Environmental Genomics, Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma 73019, United States;

    Institute for Environmental Genomics, Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma 73019, United States;

    Department of Civil and Environmental Engineering, The University of Tennessee, Knoxville, Tennessee 37996, United States,Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831-6342, United States;

    Physical Biosciences Division and Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States;

    Institute for Environmental Genomics, Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma 73019, United States,Earth Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States,State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
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  • 正文语种 eng
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