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Functional gene array-based analysis of microbial community structure in a gradient of nitrate and heavy metal contaminated groundwaters

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

Six groundwater monitoring wells from the Field Research Center, site of the U.S. DOE Environmental Remediation Science Program (ERSP) at the Oak Ridge Reservation, Oak Ridge, TN, were selected to compose a gradient of pH (3.25 - 7.11), nitrate (1.2 - 41,790 mg/l) and heavy metal contamination (0 - 500 mg/l U; 0 - 39896 mg/l Tc). To determine the functional populations of bacteria present within the gradient, DNA was extracted from groundwater and analyzed with a functional gene array containing 2,006 gene probes for the detection of genes involved in metal-resistance, sulfate-reduction, contaminant degradation and carbon and nitrogen cycling. The signal intensities for each probe were used to measure community diversity and were correlated to the geochemical profile of each well. Diversity decreased in relation to the level of contamination within each well, and each community exhibited a different distribution of genes. Heatmaps of metal resistance genes and nirK and nirS genes indicate that highly contaminated wells had lower gene diversity, but greater signal intensity for detected genes. Wells with the highest sulfate concentrations had the greatest diversity and signal intensity for dsrAB genes. A greater number of carbon fixation genes (cbbL, cbbM) were detected than fermentation genes (FTHFS) in all wells. A variety of organic contaminant degradation genes were detected. Results of Mantel tests and canonical correspondence analysis indicate that nitrate, sulfate, pH, uranium and technetium have a significant (p = 0.05) effect on bacterial community structure. This study provides an overall picture of bacterial community structure in contaminated environments across many different functional genes and shows that diversity can vary widely in relation to the degree of contamination.

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