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Title: 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, andmore » so this approach could be rapidly deployed and scaled as sequencing technology continues to become faster, simpler, and less expensive. 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.« less
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  1. Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
  2. Oak Ridge National Laboratory, Oak Ridge, TN (United States). Environmental Sciences Division.
  3. Univ. of Knoxville, Knoxville, TN (United States)
  4. Univ. of Oklahoma, Norman, OK (United States)
  5. Oak Ridge National Laboratory, Oak Ridge, TN (United States), Biosciences Division.
  6. Lawrence Berkeley National Laboratory, Berkeley, California, (United States)
Publication Date:
OSTI Identifier:
Grant/Contract Number:
AC02-05CH11231; AC05-00OR22725
Accepted Manuscript
Journal Name:
mBio (Online)
Additional Journal Information:
Journal Name: mBio (Online); Journal Volume: 6; Journal Issue: 3; Journal ID: ISSN 2150-7511
American Society for Microbiology
Research Org:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Org:
USDOE Office of Science (SC)
Country of Publication:
United States