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

King, Andrew J.; Preheim, Sarah P.; Bailey, Kathryn L.; Robeson, Michael S.; Roy Chowdhury, Taniya; Crable, Bryan R.; Hurt, Richard A.; Mehlhorn, Tonia; Lowe, Kenneth A.; Phelps, Tommy J.; Palumbo, Anthony V.; Brandt, Craig C.; Brown, Steven D.; Podar, Mircea; Zhang, Ping; Lancaster, W. Andrew; Poole, Farris; Watson, David B.; W. Fields, Matthew; Chandonia, John-Marc; Alm, Eric J.; Zhou, Jizhong; Adams, Michael W.  W.; Hazen, Terry C.; Arkin, Adam P.; Elias, Dwayne A.

doi:10.1021/acs.est.6b04751

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

Journal Article · Mon Jan 23 00:00:00 EST 2017 · Environmental Science and Technology

DOI:https://doi.org/10.1021/acs.est.6b04751· OSTI ID:1348330

King, Andrew J. ^[1]; Preheim, Sarah P. ^[2]; Bailey, Kathryn L. ^[1];

^[3]; Roy Chowdhury, Taniya ^[1]; Crable, Bryan R. ^[1]; Hurt, Richard A. ^[4]; Mehlhorn, Tonia ^[1]; Lowe, Kenneth A. ^[1]; Phelps, Tommy J. ^[1]; Palumbo, Anthony V. ^[1]; Brandt, Craig C. ^[1]; Brown, Steven D. ^[4]; Podar, Mircea ^[4];

^[5]; Lancaster, W. Andrew ^[6]; Poole, Farris ^[6];

^[1];

^[7]; Chandonia, John-Marc ^[8] more »

Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Johns Hopkins Univ., Baltimore, MD (United States)
Colorado State Univ., Fort Collins, CO (United States)
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Univ. of Tennessee, Knoxville, TN (United States)
Univ. of Oklahoma, Norman, OK (United States)
Univ. of Georgia, Athens, GA (United States)
Montana State Univ., Bozeman, MT (United States)
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)

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 in situ 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.

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Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

Grant/Contract Number:: AC05-00OR22725; AC02-05CH11231

OSTI ID:: 1348330

Alternate ID(s):: OSTI ID: 1476466

Journal Information:: Environmental Science and Technology, Vol. 51, Issue 5; ISSN 0013-936X

Publisher:: American Chemical Society (ACS)Copyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 10 works

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

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