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椒江口海域沉积物微生物群落及其对环境因子的响应
Study on Sedimental Microbial Community and Its Response to Environment Factors in Jiaojiang Estuary
投稿时间:2016-05-27  修订日期:2016-08-01
DOI:10.19316/j.issn.1002-6002.2017.06.12
中文关键词:  宏基因组  高通量测序  海洋沉积物  微生物群落  椒江口
英文关键词:metagenomics  high throughout sequencing  marine sediment  microbial community  Jiaojiang Estuary
基金项目:国家重点研发计划(2016YFC1401603);国家自然科学基金资助项目(41206186);浙江省科技厅公益重点项目(2014C23002);浙江省环保厅科研项目(2012A033,2013A020,2016A012)
作者单位
黄备 浙江省舟山海洋生态环境监测站, 浙江 舟山 316021 
邵君波 浙江省舟山海洋生态环境监测站, 浙江 舟山 316021 
周斌 杭州师范大学, 浙江 杭州 311121 
孟伟杰 浙江省舟山海洋生态环境监测站, 浙江 舟山 316021 
罗韩燕 浙江省舟山海洋生态环境监测站, 浙江 舟山 316021 
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中文摘要:
      微生物群落在有机污染物生物地球化学循环中起着十分关键的作用。微生物群落结构和多样性及其变化在一定程度上反映了土壤的质量。宏基因组学能够在整体水平解析微生物群落结构,真实地揭示原位环境中微生物群落的复杂性和多样性。应用Illumina MiSeq宏基因组高通量测序技术,在椒江口海域沉积物中鉴定得到古菌和细菌共33门类,变形菌门为明显的优势门类,其序列数占总数的62.1%。其他较为丰富的门类包括绿弯菌门、放线菌门、拟杆菌门。采用mothur软件计算Ace、Chao、Shannon、Simpson指数,结果发现,Ace、Chao的均值分别为511、518,Shannon在5.0左右,Simpson接近于0.02,显示出海域沉积物中微生物多样性较高且差异较小。通过微生物门类多样性与环境因子的相关性分析发现,PCB101、盐度和γ-氯丹对微生物门水平的群落分布具有显著性影响。计算微生物门类组成与环境因子间Spearman相关系数并绘图分析,温度、盐度、pH与多个微生物门类的组成和分布呈现明显的相关关系。
英文摘要:
      Microbial community plays key role in biogeochemical cycles of organic pollutants. Their community structure, diversity, and the changes reflect certain aspects of sediment quality. Metagenomics can reveal the integrate community structure, and unveil the insitu complexity and diversity of environmental microbial community. In this study, metagenomic analysis based on the Illumina Miseq high throughput sequencing technology was applied in Jiaojiang Estuary. A total of 33 phyla of Archaea and Bacteria were detected from the sediment samples. Proteobacteria was the dominant group, comprising 62.1% of the total sequences. Other abundant groups include phylum Chloroflexi, Actinobacteria, and Bacteroidetes. The ace, chao, shannon, and simpson diversity index were calculated using mothur software. The average value of ace and chao index was 511 and 518, respectively. The shannon diversity index was around 5.0 for all the samples, and the simpson index was close to 0.02. These indices indicated high microbial community diversity in the area, with little difference among sampling stations. The RDA analysis based on the phylum level microbial diversity and environment factors revealed that PCB101, salinity, and γ-chlordane showed significant influences on the distribution of microbial community. The spearman correlation analysis and its derived heat map indicated significant correlations between temperature, salinity, and pH, and the composition and distribution of microbial community.
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