期刊
ENVIRONMENTAL TECHNOLOGY
卷 33, 期 14, 页码 1629-1640出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/09593330.2011.641036
关键词
uranium; microbial diversity; metal reduction; nitrate; LIBSHUFF
资金
- United States Department of Energy (US-DOE), Office of Biological and Environmental Research
- US-DOE Faculty and Student Teams (FaST)
- Office for the Vice President for Research (OVPR) of the University of Michigan
To understand the link between bacterial diversity and geochemistry in uranium-contaminated groundwater, microbial communities were assessed based on clone libraries of 16S rDNA genes from the USDOE Oak Ridge Field Research Centre (FRC) site. Four groundwater wells (GW835, GW836, FW113-47 and FW215-49) with a wide range of pH (3 to 7), nitrate (44 to 23,400 mg L-1), uranium (0.73 to 60.36 mg L-1) and other metal contamination, were investigated. Results indicated that bacterial diversity correlated with the geochemistry of the groundwater. Microbial diversity decreased in relation to the contamination levels of the wells. The highly contaminated well (FW113-47) had lower gene diversity than less contaminated wells (FW215-49, GW835 and GW836). The high concentrations of contaminants present in well FW113-47 stimulated the growth of organisms capable of reducing uranium (Shewanella and Pseudomonas), nitrate (Pseudomonas, Rhodanobacter and Xanthomonas) and iron (Stenotrophomonas), and which were unique to this well. The clone libraries consisted primarily of sequences closely related to the phylum Proteobacteria, with FW-113-47 almost exclusively containing this phylum. Metal-reducing bacteria were present in all four wells, which may suggest that there is potential for successful bioremediation of the groundwater at the Oak Ridge FRC. The microbial community information gained from this study and previous studies at the site can be used to develop predictive multivariate and geographical information system (GIS) based models for microbial populations at the Oak Ridge FRC. This will allow for a better understanding of what organisms are likely to occur where and when, based on geochemistry, and how these organisms relate to bioremediation processes at the site.
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