Characterization of subsurface media from locations up- and down-gradient of a uranium-contaminated aquifer.

The processing of sediment to accurately characterize the spatially-resolved depth profiles of geophysical and geochemical properties along with signatures of microbial density and activity remains a challenge especially in complex contaminated areas. This study processed cores from two sediment boreholes from background and contaminated core sediments and surrounding groundwater. Fresh core sediments were compared by depth to capture the changes in sediment structure, sediment minerals, biomass, and pore water geochemistry in terms of major and trace elements including pollutants, cations, anions, and organic acids. Soil porewater samples were matched to groundwater level, flow rate, and preferential flows and compared to homogenized groundwater-only samples from neighboring monitoring wells. Groundwater analysis of nearby wells only revealed high sulfate and nitrate concentrations while the same analysis using sediment pore water samples with depth was able to suggest areas high in sulfate- and nitrate-reducing bacteria based on their decreased concentration and production of reduced by-products that could not be seen in the groundwater samples. Positive correlations among porewater content, total organic carbon, trace metals and clay minerals revealed a more complicated relationship among contaminant, sediment texture, groundwater table, and biomass. The fluctuating capillary interface had high concentrations of Fe and Mn-oxides combined with trace elements including U, Th, Sr, Ba, Cu, and Co. This suggests the mobility of potentially hazardous elements, sediment structure, and biogeochemical factors are all linked together to impact microbial communities, emphasizing that solid interfaces play an important role in determining the abundance of bacteria in the sediments

Replicates, read numbers and other important experimental design considerations for microbial RNA-seq identified using Bacillus thuringiensis datasets

RNA-seq is being used increasingly for gene expression studies and it is revolutionizing the fields of genomics and transcriptomics. However, the field of RNA-seq analysis is still evolving. Therefore, we specifically designed this study to contain large numbers of reads and four biological replicates per condition so we could alter these parameters and assess their impact on differential expression results. Bacillus thuringiensis strains ATCC10792 and CT43 were grown in two Luria broth medium lots on four dates and transcriptomics data were generated using one lane of sequence output from an Illumina HiSeq2000 instrument for each of the 32 samples, which were then analyzed using DESeq2. Genome coverages across samples ranged from 87-465X with medium lots and culture dates identified as major variation sources. Significantly differentially expressed genes (5% FDR, two-fold change) were detected for cultures grown using different medium lots and between different dates. The highly differentially expressed iron acquisition and metabolism genes, were a likely consequence of differing amounts of iron in the two media lots. Indeed, in this study RNA-seq was a tool for predictive biology since we hypothesized and confirmed the two LB medium lots had different iron contents (~twofold differences). This study shows that the noise in data can be controlled and minimized with appropriate experimental design and by having the appropriate number of replicates and reads for the system being studied. We outline parameters for an efficient and cost effective microbial transcriptomics study

Molybdenum Availability Is Key to Nitrate Removal in Contaminated Groundwater Environments.

The concentrations of molybdenum (Mo) and 25 other metals were measured in groundwater samples from 80 wells on the Oak Ridge Reservation (ORR) (Oak Ridge, TN), many of which are contaminated with nitrate, as well as uranium and various other metals. The concentrations of nitrate and uranium were in the ranges of 0.1 μM to 230 mM and <0.2 nM to 580 μM, respectively. Almost all metals examined had significantly greater median concentrations in a subset of wells that were highly contaminated with uranium (≥126 nM). They included cadmium, manganese, and cobalt, which were 1,300- to 2,700-fold higher. A notable exception, however, was Mo, which had a lower median concentration in the uranium-contaminated wells. This is significant, because Mo is essential in the dissimilatory nitrate reduction branch of the global nitrogen cycle. It is required at the catalytic site of nitrate reductase, the enzyme that reduces nitrate to nitrite. Moreover, more than 85% of the groundwater samples contained less than 10 nM Mo, whereas concentrations of 10 to 100 nM Mo were required for efficient growth by nitrate reduction for two Pseudomonas strains isolated from ORR wells and by a model denitrifier, Pseudomonas stutzeri RCH2. Higher concentrations of Mo tended to inhibit the growth of these strains due to the accumulation of toxic concentrations of nitrite, and this effect was exacerbated at high nitrate concentrations. The relevance of these results to a Mo-based nitrate removal strategy and the potential community-driving role that Mo plays in contaminated environments are discussed

Natural bacterial communities serve as quantitative geochemical biosensors.

UnlabelledBiological sensors can be engineered to measure a wide range of environmental conditions. Here we show that statistical analysis of DNA from natural microbial communities can be used to accurately identify environmental contaminants, including uranium and nitrate at a nuclear waste site. In addition to contamination, sequence data from the 16S rRNA gene alone can quantitatively predict a rich catalogue of 26 geochemical features collected from 93 wells with highly differing geochemistry characteristics. We extend this approach to identify sites contaminated with hydrocarbons from the Deepwater Horizon oil spill, finding that altered bacterial communities encode a memory of prior contamination, even after the contaminants themselves have been fully degraded. We show that the bacterial strains that are most useful for detecting oil and uranium are known to interact with these substrates, indicating that this statistical approach uncovers ecologically meaningful interactions consistent with previous experimental observations. Future efforts should focus on evaluating the geographical generalizability of these associations. Taken as a whole, these results indicate that ubiquitous, natural bacterial communities can be used as in situ environmental sensors that respond to and capture perturbations caused by human impacts. These in situ biosensors rely on environmental selection rather than directed engineering, and so this approach could be rapidly deployed and scaled as sequencing technology continues to become faster, simpler, and less expensive.ImportanceHere we show that DNA from natural bacterial communities can be used as a quantitative biosensor to accurately distinguish unpolluted sites from those contaminated with uranium, nitrate, or oil. These results indicate that bacterial communities can be used as environmental sensors that respond to and capture perturbations caused by human impacts

Natural Bacterial Communities Serve as Quantitative Geochemical Biosensors

Biological sensors can be engineered to measure a wide range of environmental conditions. Here we show that statistical analysis of DNA from natural microbial communities can be used to accurately identify environmental contaminants, including uranium and nitrate at a nuclear waste site. In addition to contamination, sequence data from the 16S rRNA gene alone can quantitatively predict a rich catalogue of 26 geochemical features collected from 93 wells with highly differing geochemistry characteristics. We extend this approach to identify sites contaminated with hydrocarbons from the Deepwater Horizon oil spill, finding that altered bacterial communities encode a memory of prior contamination, even after the contaminants themselves have been fully degraded. We show that the bacterial strains that are most useful for detecting oil and uranium are known to interact with these substrates, indicating that this statistical approach uncovers ecologically meaningful interactions consistent with previous experimental observations. Future efforts should focus on evaluating the geographical generalizability of these associations. Taken as a whole, these results indicate that ubiquitous, natural bacterial communities can be used as in situ environmental sensors that respond to and capture perturbations caused by human impacts. These in situ biosensors rely on environmental selection rather than directed engineering, and so this approach could be rapidly deployed and scaled as sequencing technology continues to become faster, simpler, and less expensive

Characterization of subsurface media from locations up- and down-gradient of a uranium-contaminated aquifer.

The processing of sediment to accurately characterize the spatially-resolved depth profiles of geophysical and geochemical properties along with signatures of microbial density and activity remains a challenge especially in complex contaminated areas. This study processed cores from two sediment boreholes from background and contaminated core sediments and surrounding groundwater. Fresh core sediments were compared by depth to capture the changes in sediment structure, sediment minerals, biomass, and pore water geochemistry in terms of major and trace elements including pollutants, cations, anions, and organic acids. Soil porewater samples were matched to groundwater level, flow rate, and preferential flows and compared to homogenized groundwater-only samples from neighboring monitoring wells. Groundwater analysis of nearby wells only revealed high sulfate and nitrate concentrations while the same analysis using sediment pore water samples with depth was able to suggest areas high in sulfate- and nitrate-reducing bacteria based on their decreased concentration and production of reduced by-products that could not be seen in the groundwater samples. Positive correlations among porewater content, total organic carbon, trace metals and clay minerals revealed a more complicated relationship among contaminant, sediment texture, groundwater table, and biomass. The fluctuating capillary interface had high concentrations of Fe and Mn-oxides combined with trace elements including U, Th, Sr, Ba, Cu, and Co. This suggests the mobility of potentially hazardous elements, sediment structure, and biogeochemical factors are all linked together to impact microbial communities, emphasizing that solid interfaces play an important role in determining the abundance of bacteria in the sediments

Temporal Dynamics of In-Field Bioreactor Populations Reflect the Groundwater System and Respond Predictably to Perturbation

Temporal variability complicates testing the influences of environmental variability on microbial community structure and thus function. An in-field bioreactor system was developed to assess oxic versus anoxic manipulations on <i>in situ</i> groundwater communities. Each sample was sequenced (16S SSU rRNA genes, average 10,000 reads), and biogeochemical parameters are monitored by quantifying 53 metals, 12 organic acids, 14 anions, and 3 sugars. Changes in dissolved oxygen (DO), pH, and other variables were similar across bioreactors. Sequencing revealed a complex community that fluctuated in-step with the groundwater community and responded to DO. This also directly influenced the pH, and so the biotic impacts of DO and pH shifts are correlated. A null model demonstrated that bioreactor communities were driven in part not only by experimental conditions but also by stochastic variability and did not accurately capture alterations in diversity during perturbations. We identified two groups of abundant OTUs important to this system; one was abundant in high DO and pH and contained heterotrophs and oxidizers of iron, nitrite, and ammonium, whereas the other was abundant in low DO with the capability to reduce nitrate. In-field bioreactors are a powerful tool for capturing natural microbial community responses to alterations in geochemical factors beyond the bulk phase