Depth-resolved microbial community analyses in two contrasting soil cores contaminated by antimony and arsenic

阅读量:

250

作者:

E XiaoV KruminsT XiaoY DongS TangZ NingZ HuangW Sun

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摘要:

Investigation of microbial communities of soils contaminated by antimony (Sb) and arsenic (As) is necessary to obtain knowledge for their bioremediation. However, little is known about the depth profiles of microbial community composition and structure in Sb and As contaminated soils. Our previous studies have suggested that historical factors (i.e., soil and sediment) play important roles in governing microbial community structure and composition. Here, we selected two different types of soil (flooded paddy soil versus dry corn field soil) with co-contamination of Sb and As to study interactions between these metalloids, geochemical parameters and the soil microbiota as well as microbial metabolism in response to Sb and As contamination. Comprehensive geochemical analyses and 16S rRNA amplicon sequencing were used to shed light on the interactions of the microbial communities with their environments. A wide diversity of taxonomical groups was present in both soil cores, and many were significantly correlated with geochemical parameters. Canonical correspondence analysis (CCA) and co-occurrence networks further elucidated the impact of geochemical parameters (including Sb and As contamination fractions and sulfate, TOC, Eh, and pH) on vertical distribution of soil microbial communities. Metagenomes predicted from the 16S data using PICRUSt included arsenic metabolism genes such as arsenate reductase ( ArsC ), arsenite oxidase small subunit ( AoxA and AoxB ), and arsenite transporter ( ArsA and ACR3). In addition, predicted abundances of arsenate reductase ( ArsC ) and arsenite oxidase ( AoxA and AoxB ) genes were significantly correlated with Sb contamination fractions, These results suggest potential As biogeochemical cycling in both soil cores and potentially dynamic Sb biogeochemical cycling as well.

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DOI:

10.1016/j.envpol.2016.11.071

被引量:

9

年份:

2017

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