Abstract

Copper mine tailings are causing great environmental concern nowadays due to their high contents of heavy metals. These hazards may release to air, water, and soil, posing great threat to the living organisms in the surroundings. In the present work, we profiled the heavy metal contents, microbiome and resistome of a mine tailing in Dexing Copper Mine, which is the largest open-pit copper mine in China. A total of 39.75Gb clean data was generated by metagenomics sequencing and taxonomy analysis revealed Actinobacteria, Proteobacteria, Acidobacteria, Euryarchaeota, and Nitrospirae as the most abundant phylum in this tailing. In general, 76 heavy metal resistance genes (HMRGs) and 194 antimicrobial resistance genes (ARGs) were identified with merA and rpoB2 as the most abundant HMRG and ARG, respectively. We also compared the differences of heavy metal concentrations among the six sampling sites in the same tailing and found that significant differences exited in copper and zinc. Hierarchical cluster analysis showed that the samples from the six sampling sites were clustering in two groups based on heavy metal concentrations. Accordingly, clustering based on microbial composition and relative abundances of resistance genes exhibited the same clustering pattern, indicating a possible shaping influence of heavy metals on the microbiome and resistome in this tailing. Our work presented heavy metal contents, microbial composition and resistance genes in a copper mine tailing of the largest copper mine in China, and these data will of great use in the surveillance, maintenance, and remediation of this tailing.

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