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Title: Application of Nonlinear Analysis Methods for Identifying Relationships Between Microbial Community Structure and Groundwater Geochemistry

Abstract

The relationship between groundwater geochemistry and microbial community structure can be complex and difficult to assess. We applied nonlinear and generalized linear data analysis methods to relate microbial biomarkers (phospholipids fatty acids, PLFA) to groundwater geochemical characteristics at the Shiprock uranium mill tailings disposal site that is primarily contaminated by uranium, sulfate, and nitrate. First, predictive models were constructed using feedforward artificial neural networks (NN) to predict PLFA classes from geochemistry. To reduce the danger of overfitting, parsimonious NN architectures were selected based on pruning of hidden nodes and elimination of redundant predictor (geochemical) variables. The resulting NN models greatly outperformed the generalized linear models. Sensitivity analysis indicated that tritium, which was indicative of riverine influences, and uranium were important in predicting the distributions of the PLFA classes. In contrast, nitrate concentration and inorganic carbon were least important, and total ionic strength was of intermediate importance. Second, nonlinear principal components (NPC) were extracted from the PLFA data using a variant of the feedforward NN. The NPC grouped the samples according to similar geochemistry. PLFA indicators of Gram-negative bacteria and eukaryotes were associated with the groups of wells with lower levels of contamination. The more contaminated samples contained microbial communities thatmore » were predominated by terminally branched saturates and branched monounsaturates that are indicative of metal reducers, actinomycetes, and Gram-positive bacteria. These results indicate that the microbial community at the site is coupled to the geochemistry and knowledge of the geochemistry allows prediction of the community composition.« less

Authors:
; ; ; ; ; ; ;
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
882104
Report Number(s):
PNNL-SA-49253
Journal ID: ISSN 0095-3628; MCBEBU; KP1301010; TRN: US0603185
DOE Contract Number:
AC05-76RL01830
Resource Type:
Journal Article
Resource Relation:
Journal Name: Microbial Ecology; Journal Volume: 51; Journal Issue: 2
Country of Publication:
United States
Language:
English
Subject:
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS; BACTERIA; CARBON; CARBOXYLIC ACIDS; CONTAMINATION; DATA ANALYSIS; FEED MATERIALS PLANTS; FORECASTING; GEOCHEMISTRY; NEURAL NETWORKS; NITRATES; PHOSPHOLIPIDS; SENSITIVITY ANALYSIS; TAILINGS; TRITIUM; URANIUM

Citation Formats

Schryver, Jack C., Brandt, Craig C., Pfiffner, Susan M., Palumbo, A V., Peacock, Aaron D., White, David C., McKinley, James P., and Long, Philip E. Application of Nonlinear Analysis Methods for Identifying Relationships Between Microbial Community Structure and Groundwater Geochemistry. United States: N. p., 2006. Web. doi:10.1007/s00248-004-0137-0.
Schryver, Jack C., Brandt, Craig C., Pfiffner, Susan M., Palumbo, A V., Peacock, Aaron D., White, David C., McKinley, James P., & Long, Philip E. Application of Nonlinear Analysis Methods for Identifying Relationships Between Microbial Community Structure and Groundwater Geochemistry. United States. doi:10.1007/s00248-004-0137-0.
Schryver, Jack C., Brandt, Craig C., Pfiffner, Susan M., Palumbo, A V., Peacock, Aaron D., White, David C., McKinley, James P., and Long, Philip E. Wed . "Application of Nonlinear Analysis Methods for Identifying Relationships Between Microbial Community Structure and Groundwater Geochemistry". United States. doi:10.1007/s00248-004-0137-0.
@article{osti_882104,
title = {Application of Nonlinear Analysis Methods for Identifying Relationships Between Microbial Community Structure and Groundwater Geochemistry},
author = {Schryver, Jack C. and Brandt, Craig C. and Pfiffner, Susan M. and Palumbo, A V. and Peacock, Aaron D. and White, David C. and McKinley, James P. and Long, Philip E.},
abstractNote = {The relationship between groundwater geochemistry and microbial community structure can be complex and difficult to assess. We applied nonlinear and generalized linear data analysis methods to relate microbial biomarkers (phospholipids fatty acids, PLFA) to groundwater geochemical characteristics at the Shiprock uranium mill tailings disposal site that is primarily contaminated by uranium, sulfate, and nitrate. First, predictive models were constructed using feedforward artificial neural networks (NN) to predict PLFA classes from geochemistry. To reduce the danger of overfitting, parsimonious NN architectures were selected based on pruning of hidden nodes and elimination of redundant predictor (geochemical) variables. The resulting NN models greatly outperformed the generalized linear models. Sensitivity analysis indicated that tritium, which was indicative of riverine influences, and uranium were important in predicting the distributions of the PLFA classes. In contrast, nitrate concentration and inorganic carbon were least important, and total ionic strength was of intermediate importance. Second, nonlinear principal components (NPC) were extracted from the PLFA data using a variant of the feedforward NN. The NPC grouped the samples according to similar geochemistry. PLFA indicators of Gram-negative bacteria and eukaryotes were associated with the groups of wells with lower levels of contamination. The more contaminated samples contained microbial communities that were predominated by terminally branched saturates and branched monounsaturates that are indicative of metal reducers, actinomycetes, and Gram-positive bacteria. These results indicate that the microbial community at the site is coupled to the geochemistry and knowledge of the geochemistry allows prediction of the community composition.},
doi = {10.1007/s00248-004-0137-0},
journal = {Microbial Ecology},
number = 2,
volume = 51,
place = {United States},
year = {Wed Feb 01 00:00:00 EST 2006},
month = {Wed Feb 01 00:00:00 EST 2006}
}
  • Systematic flow-through column experiments were conducted using sediments and ground water collected from different subsurface localities at the U.S. Department of Energy’s Integrated Field Research Challenge site in Rifle, Colorado. The principal purpose of this study is to gain a better understanding of the interactive effects of groundwater geochemistry, sediment mineralogy, and indigenous bacterial community structures on the efficacy of uranium removal from the groundwater with/without acetate amendment. Overall, we find that the subtle variations in the sediments’ mineralogy, particle size, redox conditions, as well as contents of metal(loid) co-contaminants showed a pronounced effect on the associated bacterial population andmore » composition, which mainly determines the system’s performance with respect to uranium removal. Positive relationship was identified between the abundance of dissimilatory sulfate-reduction genes (i.e., drsA), markers of sulfate-reducing bacteria, and the sediments’ propensity to sequester aqueous uranium. In contrast, no obvious connections were observed between the abundance of common iron-reducing bacteria, e.g., Geobacter spp., and the sediments’ ability to sequester uranium. In the sediments with low bacterial biomass and the absence of sulfate-reducing conditions, abiotic adsorption onto mineral surfaces such as phyllosilicates likely played a relatively major role in the attenuation of aqueous uranium; however, in these scenarios, acetate amendment induced detectable rebounds in the effluent uranium concentrations. The results of this study suggest that reductive immobilization of uranium can be achieved under predominantly sulfate-reducing conditions, and provide insight into the integrated roles of various biogeochemical components in long-term uranium sequestration.« less
  • Systematic flow-through column experiments were conducted using sediments and ground water collected from different subsurface localities at the U.S. Department of Energy's Integrated Field Research Challenge site in Rifle, Colorado. The principal purpose of this study is to gain a better understanding of the interactive effects of groundwater geochemistry, sediment mineralogy, and indigenous bacterial community structures on the efficacy of uranium removal from the groundwater with/without acetate amendment. Overall, we find that the subtle variations in the sediments' mineralogy, particle size, redox conditions, as well as contents of metal(loid) co-contaminants showed a pronounced effect on the associated bacterial population andmore » composition, which mainly determines the system's performance with respect to uranium removal. Positive relationship was identified between the abundance of dissimilatory sulfate-reduction genes (i.e., drsA), markers of sulfatereducing bacteria, and the sediments' propensity to sequester aqueous uranium. In contrast, no obvious connections were observed between the abundance of common iron-reducing bacteria, e.g., Geobacter spp., and the sediments' ability to sequester uranium. In the sediments with low bacterial biomass and the absence of sulfate-reducing conditions, abiotic adsorption onto mineral surfaces such as phyllosilicates likely played a relatively major role in the attenuation of aqueous uranium; however, in these scenarios, acetate amendment induced detectable rebounds in the effluent uranium concentrations. The results of this study suggest that reductive immobilization of uranium can be achieved under predominantly sulfate-reducing conditions, and provide insight into the integrated roles of various biogeochemical components in long-term uranium sequestration.« less
  • Systematic flow-through column experiments were conducted using sediments and ground water collected from different subsurface localities at the U.S. Department of Energy's Integrated Field Research Challenge site in Rifle, Colorado. The principal purpose of this study is to gain a better understanding of the interactive effects of groundwater geochemistry, sediment mineralogy, and indigenous bacterial community structures on the efficacy of uranium removal from the groundwater with/without acetate amendment. Overall, we find that the subtle variations in the sediments' mineralogy, redox conditions, as well as contents of metal(loid) co-contaminants showed a pronounced effect on the associated bacterial population and composition, whichmore » mainly determines the system's performance with respect to uranium removal. Positive relationship was identified between the abundance of dissimilatory sulfate-reduction genes (i.e., drsA), markers of sulfate-reducing bacteria, and the sediments' propensity to sequester aqueous uranium. In contrast, no obvious connections were observed between the abundance of common iron-reducing bacteria, e.g., Geobacter spp., and the sediments' ability to sequester uranium. In the sediments with low bacterial biomass and the absence of sulfate-reducing conditions, abiotic adsorption onto mineral surfaces such as phyllosilicates likely played a relatively major role in the attenuation of aqueous uranium; however, in these scenarios, acetate amendment induced detectable rebounds in the effluent uranium concentrations. Lastly, the results of this study suggest that immobilization of uranium can be achieved under predominantly sulfate-reducing conditions, and provide insight into the integrated roles of various biogeochemical components in long-term uranium sequestration.« less
  • 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 butmore » 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.« less