Browsing by Author "Elias, Dwayne A."

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Characterization of subsurface media from locations up- and down-gradient of a uranium-contaminated aquifer
(Elsevier BV, 2020-05) Moon, Ji-Won; Paradis, Charles J.; Joyner, Dominique C.; von Netzer, Frederick; Majumder, Erica L.; Dixon, Emma R.; Podar, Mircea; Ge, Xiaoxuan; Walian, Peter J.; Smith, Heidi J.; Wu, Xiaoqin; Zane, Grant M.; Walker, Kathleen F.; Thorgersen, Michael P.; Poole, Farris L. II; Lui, Lauren M.; Adams, Benjamin G.; De León, Kara B.; Brewer, Sheridan S.; Williams, Daniel E.; Lowe, Kenneth A.; Rodriguez, Miguel; Mehlhorn, Tonia L.; Pfiffner, Susan M.; Chakraborty, Romy; Arkin, Adam P.; Wall, Judy D.; Fields, Matthew W.; Adams, Michael W.W.; Stahl, David A.; Elias, Dwayne A.; Hazen, Terry C.
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.
Complete genome sequence of Pelosinus fermentans JBW45, a member of a remarkably competitive group of Negativicutes in the Firmicutes Phylum
(2015-09) Bowen De León, Kara; Utturkar, S. M.; Camilleri, Laura B.; Elias, Dwayne A.; Arkin, Adam P.; Fields, Matthew W.; Brown, S. D.; Wall, Judy D.
The genome of Pelosinus fermentans JBW45, isolated from a chromium-contaminated site in Hanford, Washington, USA, has been completed with PacBio sequencing. Nine copies of the rRNA gene operon and multiple transposase genes with identical sequences resulted in breaks in the original draft genome and may suggest genomic instability of JBW45.
Expression profiling of hypothetical genes in Desulfovibrio vulgaris leads to improved functional annotation
(2009-03) Elias, Dwayne A.; Mukhopadhyay, A.; Joachimiak, M. P.; Drury, Elliott C.; Redding, Alyssa M.; Yen, Huei-Che B.; Fields, Matthew W.; Hazen, Terry C.; Arkin, Adam P.; Keasling, J. D.; Wall, Judy D.
Hypothetical (HyP) and conserved HyP genes account for >30% of sequenced bacterial genomes. For the sulfate-reducing bacterium Desulfovibrio vulgaris Hildenborough, 347 of the 3634 genes were annotated as conserved HyP (9.5%) along with 887 HyP genes (24.4%). Given the large fraction of the genome, it is plausible that some of these genes serve critical cellular roles. The study goals were to determine which genes were expressed and provide a more functionally based annotation. To accomplish this, expression profiles of 1234 HyP and conserved genes were used from transcriptomic datasets of 11 environmental stresses, complemented with shotgun LCâ€“MS/MS and AMT tag proteomic data. Genes were divided into putatively polycistronic operons and those predicted to be monocistronic, then classified by basal expression levels and grouped according to changes in expression for one or multiple stresses. One thousand two hundred and twelve of these genes were transcribed with 786 producing detectable proteins. There was no evidence for expression of 17 predicted genes. Except for the latter, monocistronic gene annotation was expanded using the above criteria along with matching Clusters of Orthologous Groups. Polycistronic genes were annotated in the same manner with inferences from their proximity to more confidently annotated genes. Two targeted deletion mutants were used as test cases to determine the relevance of the inferred functional annotations.
Impact of hydrologic boundaries on microbial planktonic and biofilm communities in shallow terrestrial subsurface environments
(2018-09) Smith, Heidi J.; Zelaya, Anna J.; De León, Kara B.; Chakraborty, R.; Elias, Dwayne A.; Hazen, Terry C.; Arkin, Adam P.; Cunningham, Alfred B.; Fields, Matthew W.
Subsurface environments contain a large proportion of planetary microbial biomass and harbor diverse communities responsible for mediating biogeochemical cycles important to groundwater used by human society for consumption, irrigation, agriculture and industry. Within the saturated zone, capillary fringe and vadose zones, microorganisms can reside in two distinct phases (planktonic or biofilm), and significant differences in community composition, structure and activity between free-living and attached communities are commonly accepted. However, largely due to sampling constraints and the challenges of working with solid substrata, the contribution of each phase to subsurface processes is largely unresolved. Here, we synthesize current information on the diversity and activity of shallow freshwater subsurface habitats, discuss the challenges associated with sampling planktonic and biofilm communities across spatial, temporal and geological gradients, and discuss how biofilms may be constrained within shallow terrestrial subsurface aquifers. We suggest that merging traditional activity measurements and sequencing/-omics technologies with hydrological parameters important to sediment biofilm assembly and stability will help delineate key system parameters. Ultimately, integration will enhance our understanding of shallow subsurface ecophysiology in terms of bulk-flow through porous media and distinguish the respective activities of sessile microbial communities from more transient planktonic communities to ecosystem service and maintenance.
Microbial Functional Gene Diversity Predicts Groundwater Contamination and Ecosystem Functioning
(2018-02) He, Zhili; Zhang, Ping; Wu, Linwei; Rocha, Andrea M.; Tu, Qichao; Shi, Zhou; Wu, Bo; Qin, Yujia; Wang, Jianjun; Yan, Qingyun; Curtis, Daniel; Ning, Daliang; Van Nostrand, Joy D.; Wu, Liyou; Yang, Yunfeng; Elias, Dwayne A.; Watson, David B.; Adams, Michael W. W.; Fields, Matthew W.; Alm, Eric J.; Hazen, Terry C.; Adams, Paul D.; Arkin, Adam P.; Zhou, Jizhong
Contamination from anthropogenic activities has significantly impacted Earth\'s biosphere. However, knowledge about how environmental contamination affects the biodiversity of groundwater microbiomes and ecosystem functioning remains very limited. Here, we used a comprehensive functional gene array to analyze groundwater microbiomes from 69 wells at the Oak Ridge Field Research Center (Oak Ridge, TN), representing a wide pH range and uranium, nitrate, and other contaminants. We hypothesized that the functional diversity of groundwater microbiomes would decrease as environmental contamination (e.g., uranium or nitrate) increased or at low or high pH, while some specific populations capable of utilizing or resistant to those contaminants would increase, and thus, such key microbial functional genes and/or populations could be used to predict groundwater contamination and ecosystem functioning. Our results indicated that functional richness/diversity decreased as uranium (but not nitrate) increased in groundwater. In addition, about 5.9% of specific key functional populations targeted by a comprehensive functional gene array (GeoChip 5) increased significantly (P < 0.05) as uranium or nitrate increased, and their changes could be used to successfully predict uranium and nitrate contamination and ecosystem functioning. This study indicates great potential for using microbial functional genes to predict environmental contamination and ecosystem functioning.IMPORTANCE Disentangling the relationships between biodiversity and ecosystem functioning is an important but poorly understood topic in ecology. Predicting ecosystem functioning on the basis of biodiversity is even more difficult, particularly with microbial biomarkers. As an exploratory effort, this study used key microbial functional genes as biomarkers to provide predictive understanding of environmental contamination and ecosystem functioning. The results indicated that the overall functional gene richness/diversity decreased as uranium increased in groundwater, while specific key microbial guilds increased significantly as uranium or nitrate increased. These key microbial functional genes could be used to successfully predict environmental contamination and ecosystem functioning. This study represents a significant advance in using functional gene markers to predict the spatial distribution of environmental contaminants and ecosystem functioning toward predictive microbial ecology, which is an ultimate goal of microbial ecology.
Natural bacterial communities serve as quantitative geochemical biosensors
(2015-03) Smith, Mark B.; Rocha, Andrea M.; Smillie, C. S.; Olesen, S. W.; Paradis, C.; Wu, Liyou; Campbell, J. H.; Fortney, J. L.; Mehlhorn, T. L.; Lowe, K. A.; Earle, J. E.; Phillips, J.; Techtmann, S. M.; Joyner, D. C.; Elias, Dwayne A.; Bailey, K. L.; Hurt, R. A. Jr.; Preheim, S. P.; Sanders, M. C.; Yang, Joy; Mueller, M. A.; Brooks, S.; Watson, David B.; Zhang, Ping; He, Zhili; Dubinsky, E. A.; Adams, P. D.; Arkin, Adam P.; Fields, Matthew W.; Zhou, Jizhong; Alm, E. J.; Hazen, Terry C.
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. IMPORTANCE Here 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.