Significant association between sulfate-reducing bacteria and uranium-reducing microbial communities as revealed by a combined massively parallel sequencing-indicator species approach

Abstract

Massively parallel sequencing has provided a more affordable and high-throughput method to study microbial communities, although it has mostly been used in an exploratory fashion. We combined pyrosequencing with a strict indicator species statistical analysis to test if bacteria specifically responded to ethanol injection that successfully promoted dissimilatory uranium(VI) reduction in the subsurface of a uranium contamination plume at the Oak Ridge Field Research Center in Tennessee. Remediation was achieved with a hydraulic flow control consisting of an inner loop, where ethanol was injected, and an outer loop for flow-field protection. This strategy reduced uranium concentrations in groundwater to levels below 0.126 μM and created geochemical gradients in electron donors from the inner-loop injection well toward the outer loop and downgradient flow path. Our analysis with 15 sediment samples from the entire test area found significant indicator species that showed a high degree of adaptation to the three different hydrochemical-created conditions. Castellaniella and Rhodanobacter characterized areas with low pH, heavy metals, and low bioactivity, while sulfate-, Fe(III)-, and U(VI)-reducing bacteria (Desulfovibrio, Anaeromyxobacter, and Desulfosporosinus) were indicators of areas where U(VI) reduction occurred. The abundance of these bacteria, as well as the Fe(III) and U(VI) reducer Geobacter, correlated with the hydraulic connectivity to the substrate injection site, suggesting that the selected populations were a direct response to electron donor addition by the groundwater flow path. A false-discovery-rate approach was implemented to discard false-positive results by chance, given the large amount of data compared.

FIG. 1.

Scheme of the well system in Area 3, Oak Ridge National Laboratory, DOE. Hydrology connectivity is shown with the spatial distributions of bromide recovery (as percent, in color) and mean travel times (contour lines with units of hours). (A) Horizontal plane at the 13-m depth below ground; (B) cross-vertical section along injection and extraction wells; (C) cross-vertical section along MLS wells. The horizontal distance (m) is measured from outer-loop injection well FW024 eastwards (x) or northwards (y). z is the depth below ground (m). The well system included inner-loop injection well FW104 and extraction well FW026 for ethanol injection, outer-loop injection well FW024 and extraction well FW103 for hydraulic protection, and downgradient well FW105. The multilevel sample wells are FW100, FW101, and FW102; and the −1, −2, −3, and −4 levels were used for monitoring. The electron donor (ethanol) was injected into the inner loop at well FW104.

FIG. 2.

Clustering of samples by geochemical and microbiological characteristics. (A) Clustering by microbial community structure using a Chao-Sorensen distance and average-neighbor algorithm. Samples grouped in four clusters: cluster L comprised wells with low levels of bioactivity and low levels of connectivity to the injection well. Cluster H has the most active communities and the highest connectivity. Clusters M1 and M2 contained wells with medium activity. In clusters H, M1, and M2, the subgroups seemed to be influenced by pH. The pH values for each well are also shown. (B) Clustering by geochemical composition. Colinear variables were eliminated after correlation analysis (data not shown); and only the data for pH, sulfate, nitrate, COD (as an indirect indicator of organic matter), and tracer recovery were used for analysis with a previous z-score transformation. Cluster affiliations by microbial community structure are marked as follows: ▪, H cluster; ★, L cluster; ▴, M1 cluster; •, M2 cluster. Hierarchical clustering used an average-neighbor algorithm.

FIG. 3.

Location of maximum abundance for uranium-reducing genera along the connectivity gradient. Since relative abundances among the different groups varied by up to 20 times, the ratios of abundance to the maximum abundance for the selected group (percent) are plotted. Tracer recovery values (percent) at each well are also presented.