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Appl Microbiol Biotechnol. 2016 Oct;100(19):8523-35. doi: 10.1007/s00253-016-7653-y. Epub 2016 Jun 9.

Characterization of the microbial community composition and the distribution of Fe-metabolizing bacteria in a creek contaminated by acid mine drainage.

Sun W1,2,3, Xiao E1,4, Krumins V5, Dong Y6, Xiao T7,8, Ning Z1, Chen H1,4, Xiao Q1,4.

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State Key Laboratory of Environmental Geochemistry, Chinese Academy of Sciences, 99 Lincheng Road West, Guiyang, 550081, Guizhou Province, People's Republic of China.
Department of Biochemistry and Microbiology, Rutgers University, New Brunswick, NJ, 08901, USA.
Guangdong Institute of Eco-environment and Soil Sciences, Guangzhou, 510650, China.
University of Chinese Academy of Sciences, Beijing, 100049, China.
Department of Environmental Sciences, Rutgers University, New Brunswick, NJ, 08901, USA.
Department of Geology, University of Illinois-Urbana Champaign, Urbana, IL, 61801, USA.
State Key Laboratory of Environmental Geochemistry, Chinese Academy of Sciences, 99 Lincheng Road West, Guiyang, 550081, Guizhou Province, People's Republic of China.
Innovation Center and Key Laboratory of Waters Safety & Protection in the Pearl River Delta, Ministry of Education, Guangzhou University, Guangzhou, 510006, China.


A small watershed heavily contaminated by long-term acid mine drainage (AMD) from an upstream abandoned coal mine was selected to study the microbial community developed in such extreme system. The watershed consists of AMD-contaminated creek, adjacent contaminated soils, and a small cascade aeration unit constructed downstream, which provide an excellent contaminated site to study the microbial response in diverse extreme AMD-polluted environments. The results showed that the innate microbial communities were dominated by acidophilic bacteria, especially acidophilic Fe-metabolizing bacteria, suggesting that Fe and pH are the primary environmental factors in governing the indigenous microbial communities. The distribution of Fe-metabolizing bacteria showed distinct site-specific patterns. A pronounced shift from diverse communities in the upstream to Proteobacteria-dominated communities in the downstream was observed in the ecosystem. This location-specific trend was more apparent at genus level. In the upstream samples (sampling sites just below the coal mining adit), a number of Fe(II)-oxidizing bacteria such as Alicyclobacillus spp., Metallibacterium spp., and Acidithrix spp. were dominant, while Halomonas spp. were the major Fe(II)-oxidizing bacteria observed in downstream samples. Additionally, Acidiphilium, an Fe(III)-reducing bacterium, was enriched in the upstream samples, while Shewanella spp. were the dominant Fe(III)-reducing bacteria in downstream samples. Further investigation using linear discriminant analysis (LDA) effect size (LEfSe), principal coordinate analysis (PCoA), and unweighted pair group method with arithmetic mean (UPGMA) clustering confirmed the difference of microbial communities between upstream and downstream samples. Canonical correspondence analysis (CCA) and Spearman's rank correlation indicate that total organic carbon (TOC) content is the primary environmental parameter in structuring the indigenous microbial communities, suggesting that the microbial communities are shaped by three major environmental parameters (i.e., Fe, pH, and TOC). These findings were beneficial to a better understanding of natural attenuation of AMD.


Fe cycling; Fe(II)-oxidizing bacteria; Fe(III)-reducing bacteria; High-throughput sequencing

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