16s rDNA based microbial diversity analysis of eleven acid mine drainages obtained from three Chinese copper mines

• Published in: Journal of Central South University of Technology. Science & technology of mining and metallurgy 2011-12, Vol.18 (6), p.1930-1939
• Main Authors: Xie, Jian-ping, Jiang, Hong-chen, Liu, Xin-xing, Liu, Xue-duan, Zhou, Ji-zhong, Qiu, Guan-zhou
• Format: Article
• Language: English
• Subjects: Engineering; Metallic Materials
• ISSN: 1005-9784; 1993-0666
• DOI: 10.1007/s11771-011-0925-x

Eleven acid mine drainage (AMD) samples were obtained from southeast of China for the analysis of the microbial communities diversity, and the relationship with geochemical variables and spatial distance by using a culture-independent 16S rDNA gene phylogenetic analysis approach and multivariate analysis respectively. The principle component analysis (PCA) of geochemical variables shows that eleven AMDs can be clustered into two groups, relative high and low metal rich (RHMR and RLMR) AMDs. Total 1 691 clone sequences are obtained and the detrended correspondence analysis (DCA) of operational taxonomic units (OTUs) shows that, γ-Proteobacteria , Acidobacteria , Actinobacteria , Cyanobacteria , Firmicutes and Nitrospirae are dominant species in RHMR AMDs. In contrast, α-Proteobacteria, β - Proteobacteria , Planctomycetes and Bacteriodetes are dominant species in RLMR AMD. Results also show that high-abundance putative iron-oxidizing and only putative sulfur-oxidizing microorganisms are found in RHMR AMD. Multivariate analysis shows that both geochemical variables ( r =0.429 3, P =0.037 7) and spatial distance ( r =0.321 3, P =0.018 1) are significantly positively correlated with microbial community and pH, Mg, Fe, S, Cu and Ca are key geochemistry factors in shaping microbial community. Variance partitioning analysis shows that geochemical variables and spatial distance can explain most (92%) of the variation.