Browsing by Author "Wang, Jianjun"

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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.
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.