Browsing by Author "Wu, Liyou"

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Comparative metagenomics reveals impact of contaminants on groundwater microbiomes
(2015-10) Hemme, C. L.; Tu, Qichao; Shi, Zhou; Qin, Yujia; Gao, W.; Deng, Ye; VanNostrand, J. D.; Wu, Liyou; He, Zhili; Chain, P. S.; Fields, Matthew W.; Rubin, E. M.; Tiedje, J. M.; Hazen, Terry C.; Arkin, Adam P.; Zhou, Jizhong
To understand patterns of geochemical cycling in pristine versus contaminated groundwater ecosystems, pristine shallow groundwater (FW301) and contaminated groundwater (FW106) samples from the Oak Ridge Integrated Field Research Center (OR-IFRC) were sequenced and compared to each other to determine phylogenetic and metabolic difference between the communities. Proteobacteria (e.g., Burkholderia, Pseudomonas) are the most abundant lineages in the pristine community, though a significant proportion ( >55%) of the community is composed of poorly characterized low abundance (individually <1%) lineages. The phylogenetic diversity of the pristine community contributed to a broader diversity of metabolic networks than the contaminated community. In addition, the pristine community encodes redundant and mostly complete geochemical cycles distributed over multiple lineages and appears capable of a wide range of metabolic activities. In contrast, many geochemical cycles in the contaminated community appear truncated or minimized due to decreased biodiversity and dominance by Rhodanobacter populations capable of surviving the combination of stresses at the site. These results indicate that the pristine site contains more robust and encodes more functional redundancy than the stressed community, which contributes to more efficient nutrient cycling and adaptability than the stressed community.
Dynamic Succession of Groundwater Sulfate-Reducing Communities during Prolonged Reduction of Uranium in a Contaminated Aquifer
(2017-04) Zhang, Ping; He, Zhili; Van Nostrand, Joy D.; Qin, Yujia; Deng, Ye; Wu, Liyou; Tu, Qichao; Wang, Jianjun; Schadt, Christopher W.; Fields, Matthew W.; Hazen, Terry C.; Arkin, Adam P.; Stahl, David A.; Zhou, Jizhong
To further understand the diversity and dynamics of SRB in response to substrate amendment, we sequenced genes coding for the dissimilatory sulfite reductase (dsrA) in groundwater samples collected after an emulsified vegetable oil (EVO) amendment, which sustained U(VI)-reducing conditions for one year in a fast-flowing aquifer. EVO amendment significantly altered the composition of groundwater SRB communities. Sequences having no closely related-described species dominated (80%) the indigenous SRB communities in nonamended wells. After EVO amendment, Desulfococcus, Desulfobacterium, and Desulfovibrio, known for long-chain-fatty-acid, short-chain-fatty-acid and H2 oxidation and U(VI) reduction, became dominant accounting for 7 ± 2%, 21 ± 8%, and 55 ± 8% of the SRB communities, respectively. Succession of these SRB at different bioactivity stages based on redox substrates/products (acetate, SO4–2, U(VI), NO3–, Fe(II), and Mn(II)) was observed. Desulfovibrio and Desulfococcus dominated SRB communities at 4–31 days, whereas Desulfobacterium became dominant at 80–140 days. By the end of the experiment (day 269), the abundance of these SRB decreased but the overall diversity of groundwater SRB was still higher than non-EVO controls. Up to 62% of the SRB community changes could be explained by groundwater geochemical variables, including those redox substrates/products. A significant (P < 0.001) correlation was observed between groundwater U(VI) concentrations and Desulfovibrio abundance. Our results showed that the members of SRB and their dynamics were correlated significantly with slow EVO biodegradation, electron donor production and maintenance of U(VI)-reducing conditions in the aquifer.
In situ bioreduction of uranium (VI) in situ and stability of immobilized uranium: Impact of dissolved oxygen
(2007-08) Wu, Wei-Min; Carley, Jack; Luo, Jian; Ginder-Vogel, Matthew A.; Cardenas, Erick; Leigh, Mary Beth; Hwang, Chiachi; Kelly, Shelly D.; Ruan, Chuanmin; Wu, Liyou; Nostrand, Joy V.; Gentry, Terry J.; Lowe, K. A.; Mehlhorn, T. L.; Carroll, Sue L.; Luo, Wensui; Fields, Matthew W.; Gu, Baohua; Watson, David B.; Kemner, K. M.; Marsh, Terence; Tiedje, J. M.; Zhou, Jizhong; Fendorf, Scott; Kitanidis, Peter K.; Jardine, Phil M.; Criddle, Craig S.
Groundwater within Area 3 of the U.S. Department of Energy (DOE) Environmental Remediation Sciences Program (ERSP) Field Research Center at Oak Ridge, TN (ORFRC) contains up to 135 microM uranium as U(VI). Through a series of experiments at a pilot scale test facility, we explored the lower limits of groundwater U(VI) that can be achieved by in-situ biostimulation and the effects of dissolved oxygen on immobilized uranium. Weekly 2-day additions of ethanol over a 2-year period stimulated growth of denitrifying, Fe(III)-reducing, and sulfate-reducing bacteria, and immobilization of uranium as U(IV), with dissolved uranium concentrations decreasing to low levels. Following sulfite addition to remove dissolved oxygen, aqueous U(VI) concentrations fell below the U.S. Environmental Protection Agengy maximum contaminant limit (MCL) for drinking water (< 30/microg L(-1) or 0.126 microM). Under anaerobic conditions, these low concentrations were stable, even in the absence of added ethanol. However, when sulfite additions stopped, and dissolved oxygen (4.0-5.5 mg L(-1)) entered the injection well, spatially variable changes in aqueous U(VI) occurred over a 60 day period, with concentrations increasing rapidly from < 0.13 to 2.0 microM at a multilevel sampling (MLS) well located close to the injection well, but changing little at an MLS well located further away. Resumption of ethanol addition restored reduction of Fe(III), sulfate, and U(VI) within 36 h. After 2 years of ethanol addition, X-ray absorption near-edge structure spectroscopy (XANES) analyses indicated that U(IV) comprised 60-80% of the total uranium in sediment samples. Atthe completion of the project (day 1260), U concentrations in MLS wells were less than 0.1 microM. The microbial community at MLS wells with low U(VI) contained bacteria that are known to reduce uranium, including Desulfovibrio spp. and Geobacter spp., in both sediment and groundwater. The dominant Fe(III)-reducing species were Geothrix spp.
Metagenomic insights into evolution of a heavy metal-contaminated groundwater microbial community
(2010-02) Hemme, C. L.; Deng, Ye; Gentry, Terry J.; Fields, Matthew W.; Wu, Liyou; Barua, Sutapa; Barry, Kerrie; Tringe, Susannah G.; Watson, David B.; He, Zhili; Hazen, Terry C.; Tiedje, J. M.; Rubin, E. M.; Zhou, Jizhong
Understanding adaptation of biological communities to environmental change is a central issue in ecology and evolution. Metagenomic analysis of a stressed groundwater microbial community reveals that prolonged exposure to high concentrations of heavy metals, nitric acid and organic solvents (B50 years) has resulted in a massive decrease in species and allelic diversity as well as a significant loss of metabolic diversity. Although the surviving microbial community possesses all metabolic pathways necessary for survival and growth in such an extreme environment, its structure is very simple, primarily composed of clonal denitrifying c- and b-proteobacterial populations. The resulting community is overabundant in key genes conferring resistance to specific stresses including nitrate, heavy metals and acetone. Evolutionary analysis indicates that lateral gene transfer could have a key function in rapid response and adaptation to environmental contamination. The results presented in this study have important implications in understanding, assessing and predicting the impacts of human-induced activities on microbial communities ranging from human health to agriculture to environmental management, and their responses to environmental changes.
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.