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GeoChip Analysis of Subsurface Microbial Communities Impacted by Heavy Metal and Nitrate Contamination

  • Author(s): Waldron, P.J.
  • Nostrand, J.D. Van
  • Watson, D.B.
  • He, Z.
  • Wu, L.Y.
  • Jardine, P.
  • Hazen, T.C.
  • Zhou, J.
  • et al.
Abstract

The objective of this study is to examine the bacterial community structure in wells of varying heavy metal and acid contamination to determine which contaminants have the greatest effect. Five monitoring wells and an uncontaminated background well from the Field Research Center (FRC) site of the U.S. DOE ERSP (Environmental Remediation Science Program) at Oak Ridge, Tennessee, were sampled to provide a gradient of groundwater nitrate, pH and uranium concentrations. DNA from these samples was analyzed with a comprehensive functional gene array containing 24,243 probes for >10,000 genes involved in carbon, sulfur, nitrogen, and metal cycling. Genes with the highest signal intensities from each sample were correlated with the groundwater geochemistry of that well. Wells with similar geochemical profiles had greater gene overlap than dissimilar wells. A higher percentage of nitrogen fixation genes were detected in groundwater with lower nitrate concentrations, while the percentage of nitrate reduction genes generally decreased with decreasing nitrate. Wells with elevated sulfate concentrations had a greater percentage of genes dedicated to sulfate reduction, and higher signal intensities for dsrAB genes than the background, indicating a greater abundance of those genes. Contaminated wells did not have a higher percentage of metal reduction and resistance genes than the background, but the total signal intensity of those genes was 1.4- to 2.3-fold greater than the background, indicating that metal-related genes were more prevalent in the contaminated wells. Uranium, nitrate and sulfate were identified by CCA as important factors in determining community structure. This study provides an overall view of the functional genes present in a highly contaminated environment, and shows the differences in functional populations between wells with varying contamination. As indicated by this work, contaminant level has significant effects on bacterial community structure, the knowledge of which may be important in planning and implementing successful bioremediation strategies in the future.

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