Changes in Bacterial Community Structure and Abundance in Agricultural Soils under Varying Levels of Arsenic Contamination
Changes in Bacterial Community Structure and Abundance in Agricultural Soils under Varying Levels of Arsenic Contamination
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DOI：
10.1080/01490451.2012.746407
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发表时间：
2013-08-09
影响因子：
2.3
通讯作者：
Liu, Chia-Chuan
中科院分区：
文献类型：
--
作者：
Das, Suvendu;Jean, Jiin-Shuh;Liu, Chia-Chuan
用于灌溉农作物的地下水的砷污染是亚洲几个农业重要地区的一个主要问题。评估高污染场地的细菌群落组成可以确定新的生物修复策略。在这项研究中，基于16S rRNA基因的聚合酶链反应-变性梯度凝胶电泳（PCR-DGGE）和最可能的数量聚合酶链反应（MPN-PCR），评估了印度恰蒂斯加尔邦Ambagarh Chauki区块不同砷污染水平的农业土壤中的细菌群落结构和丰度。结果表明，砷污染土壤细菌群落以-变形菌门（36%）、-变形菌门（21%）、-变形菌门（11%）、-变形菌门（11%）和拟杆菌门（11%）为主。高砷污染土壤的细菌组成与低砷污染土壤有显著差异。变形菌门似乎对砷污染更有抵抗力，而拟杆菌门和硝基螺旋门对砷污染更敏感。随着砷毒性的增加，MPN-PCR测定的细菌丰度显著降低。典型对应分析（CCA）结果表明，除As外，Pb、U、Cu、Ni、Sn、Zn和Zr等微量金属对不同砷污染水平下农业土壤细菌结构多样性的影响也显著（p < 0.01）。
Arsenic contamination from groundwater used to irrigate crops is a major issue across several agriculturally important areas of Asia. Assessing bacterial community composition in highly contaminated sites could lead to the identification of novel bioremediation strategies. In this study, the bacterial community structure and abundance are assessed in agricultural soils with varying levels of arsenic contamination at Ambagarh Chauki block, Chhattisgarh, India, based on polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE) of the 16S rRNA gene and the most probable number-polymerase chain reaction (MPN-PCR). The results revealed that the bacterial communities of arsenic-contaminated soils are dominated by -proteobacteria (36%), -proteobacteria (21%), -proteobacteria (11%), -proteobacteria (11%), and Bacteroidetes (11%). The bacterial composition of high arsenic-contaminated soils differed significantly from that of low arsenic-contaminated soils. The Proteobacteria appeared to be more resistant to arsenic contamination, while the Bacteroidetes and Nitrospirae were more sensitive to it. The bacterial abundance determined by MPN-PCR decreased significantly as As-toxicity increased. In addition to As, other trace metals, like Pb, U, Cu, Ni, Sn, Zn and Zr, significantly (p < 0.01) explain the changes in bacterial structural diversity in agricultural soils with different level of arsenic contamination, as determined by canonical correspondence analysis (CCA).