Functional gene array-based analysis of microbial community structure in groundwater with gradient of contaminant levels

To understand how contaminants affect microbial community diversity, heterogeneity, and functional structure, six groundwater monitoring wells from the Field Research Center of the U.S. Department of Energy Environmental Remediation Science Program (ERSP; Oak Ridge, TN), with a wide range of pH, nit...

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Veröffentlicht in:Environmental science & technology 2009-04, Vol.43 (10)
Hauptverfasser: Wu, Liyou, Van Nostrand, Joy, Schadt, Christopher Warren, Watson, David B, Jardine, Philip M, Palumbo, Anthony Vito, Hazen, Terry, Zhou, Jizhong
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Sprache:eng
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Zusammenfassung:To understand how contaminants affect microbial community diversity, heterogeneity, and functional structure, six groundwater monitoring wells from the Field Research Center of the U.S. Department of Energy Environmental Remediation Science Program (ERSP; Oak Ridge, TN), with a wide range of pH, nitrate, and heavy metal contamination were investigated. DNA from the groundwater community was analyzed with a functional gene array containing 2006 probes to detect genes involved in metal resistance, sulfate reduction, organic contaminant degradation, and carbon and nitrogen cycling. Microbial diversity decreased in relation to the contamination levels of the wells. Highly contaminated wells had lower gene diversity but greater signal intensity than the pristine well. The microbial composition was heterogeneous, with 17?70% overlap between different wells. Metal-resistant and metal-reducing microorganisms were detected in both contaminated and pristine wells, suggesting the potential for successful bioremediation of metal-contaminated groundwaters. In addition, results of Mantel tests and canonical correspondence analysis indicate that nitrate, sulfate, pH, uranium, and technetium have a significant (p < 0.05) effect on microbial community structure. This study provides an overall picture of microbial community structure in contaminated environments with functional gene arrays by showing that diversity and heterogeneity can vary greatly in relation to contamination.
ISSN:0013-936X
1520-5851