研究报告

  • 郑远,李玉英,丁传雨,任学敏,陈兆进.能源植物修复镉污染土壤对根际细菌网络结构的影响[J].环境科学学报,2016,36(7):2605-2612

  • 能源植物修复镉污染土壤对根际细菌网络结构的影响
  • Effects of bioenergy cropping on rhizosphere bacteria networks structure in Cd-contaminated soil
  • 基金项目:南阳师范学院高层次人才科研启动费资助项目(No.ZX2014069,ZX2014066);河南省教育厅高等学校重点科研项目(No.16A210012,14A180015);国家自然科学基金项目(No.31401307,31400264)
  • 作者
  • 单位
  • 郑远
  • 南阳师范学院农业工程学院, 南阳 473061
  • 李玉英
  • 南阳师范学院农业工程学院, 南阳 473061
  • 丁传雨
  • 南阳师范学院农业工程学院, 南阳 473061
  • 任学敏
  • 南阳师范学院农业工程学院, 南阳 473061
  • 陈兆进
  • 南阳师范学院农业工程学院, 南阳 473061
  • 摘要:选取油脂类能源植物大豆和碳水化合物类能源植物玉米,采用高通量测序方法研究大豆、玉米修复Cd污染土壤过程中根际土壤细菌群落组成,基于高通量测序数据采用分子生态网络分析细菌相互作用。结果表明,50 mg·kg-1 Cd污染土壤中两种植物根部Cd浓度和积累量最高,转移系数TF分别为玉米0.78和大豆0.35.基于细菌16S rRNA基因的群落分析表明,大豆、玉米根际土壤细菌主要包括Proteobacteria(变形菌门)、Acidobacteria(酸杆菌门)31个门细菌组成,大豆、玉米种植均能影响土壤细菌群落组成,能影响Candidate division TM7 norank、Acidimicrobiales norank、Sphingomonas等丰度。分子生态网络分析表明种植大豆和玉米增加了细菌之间的相互作用,导致其网络结构更为复杂,关键细菌从不种植物处理的1个增加到种植大豆的6个和种植玉米的10个。
  • Abstract:This study aimed at elucidating the bacterial community composition and interactions in rhizosphere soils of two types of bioenergy crops (high starch crop-maize, oilseed crop-soybean) by using high-throughput sequencing and molecular ecological networks in the phytoremediation of Cd-contaminated soils. Cd concentration and uptake in the roots of maize and soybean plants were significantly higher than that in the stems and leaves of the plants. The translocation factors of maize and soybean plants were 0.78 and 0.35, respectively. The diversity of rhizosphere bacteria isolated from maize and soybean plants was evaluated by using high-throughput sequencing in the phytoremediation of the Cd-contaminated soils. Using Illumina MiSeq sequencing, a set of more than 32,386 effective sequence tags was obtained for each sample. Phylogenetic analysis based on 16S rDNA sequences showed that the rhizosphere bacteria could be divided into 31 major phylogenetic groups by phyla. The dominant phylogenetic groups included Proteobacteria, Acidobacteria, Gemmatimonadetes, Actinobacteria, and Bacteroidetes. Based on the principal coordinate analysis (PCoA) and UPGMA, the bacterial community composition was found to be primarily affected by bioenergy cropping. At the genus level, the relative abundance of Candidate division TM7 norank, Acidimicrobiales norank, and Sphingomonas species were affected by bioenergy cropping. Molecular ecological network analysis was then developed by a random matrix theory (RMT)-based conceptual framework. One key bacterium was present under the non-cropping treatment, whereas six and ten key bacteria were present under the soybean and maize cropping systems. In conclusion, bioenergy cropping can alter the bacterial interactions in soil microbial communities.

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