Microbial Community Analysis of a Coastal Salt Marsh Affected by the Deepwater Horizon Oil Spill
Abstract
Coastal salt marshes are highly sensitive wetland ecosystems that can sustain long-term impacts from anthropogenic events such as oil spills. In this study, we examined the microbial communities of a Gulf of Mexico coastal salt marsh during and after the influx of petroleum hydrocarbons following the Deepwater Horizon oil spill. Total hydrocarbon concentrations in salt marsh sediments were highest in June and July 2010 and decreased in September 2010. Coupled PhyloChip and GeoChip microarray analyses demonstrated that the microbial community structure and function of the extant salt marsh hydrocarbon-degrading microbial populations changed significantly during the study. The relative richness and abundance of phyla containing previously described hydrocarbon-degrading bacteria (Proteobacteria, Bacteroidetes, and Actinobacteria) increased in hydrocarbon-contaminated sediments and then decreased once hydrocarbons were below detection. Firmicutes, however, continued to increase in relative richness and abundance after hydrocarbon concentrations were below detection. Functional genes involved in hydrocarbon degradation were enriched in hydrocarbon-contaminated sediments then declined significantly (p<0.05) once hydrocarbon concentrations decreased. A greater decrease in hydrocarbon concentrations among marsh grass sediments compared to inlet sediments (lacking marsh grass) suggests that the marsh rhizosphere microbial communities could also be contributing to hydrocarbon degradation. The results of this study provide a comprehensive view ofmore »
- Authors:
-
- University of Alabama, Tuscaloosa, AL (United States)
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- University of Tennessee, Knoxville, TN (United States)
- University of Oklahoma, Norman, OK (United States)
- Publication Date:
- Research Org.:
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Biological and Environmental Research (BER); National Science Foundation (NSF); Dauphin Island Sea Laboratory/Marine Environmental Science Consortium
- OSTI Identifier:
- 1627535
- Grant/Contract Number:
- AC02-05CH11231; 1042743; T4-005UA
- Resource Type:
- Accepted Manuscript
- Journal Name:
- PLoS ONE
- Additional Journal Information:
- Journal Volume: 7; Journal Issue: 7; Journal ID: ISSN 1932-6203
- Publisher:
- Public Library of Science
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 59 BASIC BIOLOGICAL SCIENCES; 54 ENVIRONMENTAL SCIENCES; sediment; marshes; inlets; hydrocarbons; oils; oil spills; tar; community structure
Citation Formats
Beazley, Melanie J., Martinez, Robert J., Rajan, Suja, Powell, Jessica, Piceno, Yvette M., Tom, Lauren M., Andersen, Gary L., Hazen, Terry C., Van Nostrand, Joy D., Zhou, Jizhong, Mortazavi, Behzad, and Sobecky, Patricia A. Microbial Community Analysis of a Coastal Salt Marsh Affected by the Deepwater Horizon Oil Spill. United States: N. p., 2012.
Web. doi:10.1371/journal.pone.0041305.
Beazley, Melanie J., Martinez, Robert J., Rajan, Suja, Powell, Jessica, Piceno, Yvette M., Tom, Lauren M., Andersen, Gary L., Hazen, Terry C., Van Nostrand, Joy D., Zhou, Jizhong, Mortazavi, Behzad, & Sobecky, Patricia A. Microbial Community Analysis of a Coastal Salt Marsh Affected by the Deepwater Horizon Oil Spill. United States. https://doi.org/10.1371/journal.pone.0041305
Beazley, Melanie J., Martinez, Robert J., Rajan, Suja, Powell, Jessica, Piceno, Yvette M., Tom, Lauren M., Andersen, Gary L., Hazen, Terry C., Van Nostrand, Joy D., Zhou, Jizhong, Mortazavi, Behzad, and Sobecky, Patricia A. Wed .
"Microbial Community Analysis of a Coastal Salt Marsh Affected by the Deepwater Horizon Oil Spill". United States. https://doi.org/10.1371/journal.pone.0041305. https://www.osti.gov/servlets/purl/1627535.
@article{osti_1627535,
title = {Microbial Community Analysis of a Coastal Salt Marsh Affected by the Deepwater Horizon Oil Spill},
author = {Beazley, Melanie J. and Martinez, Robert J. and Rajan, Suja and Powell, Jessica and Piceno, Yvette M. and Tom, Lauren M. and Andersen, Gary L. and Hazen, Terry C. and Van Nostrand, Joy D. and Zhou, Jizhong and Mortazavi, Behzad and Sobecky, Patricia A.},
abstractNote = {Coastal salt marshes are highly sensitive wetland ecosystems that can sustain long-term impacts from anthropogenic events such as oil spills. In this study, we examined the microbial communities of a Gulf of Mexico coastal salt marsh during and after the influx of petroleum hydrocarbons following the Deepwater Horizon oil spill. Total hydrocarbon concentrations in salt marsh sediments were highest in June and July 2010 and decreased in September 2010. Coupled PhyloChip and GeoChip microarray analyses demonstrated that the microbial community structure and function of the extant salt marsh hydrocarbon-degrading microbial populations changed significantly during the study. The relative richness and abundance of phyla containing previously described hydrocarbon-degrading bacteria (Proteobacteria, Bacteroidetes, and Actinobacteria) increased in hydrocarbon-contaminated sediments and then decreased once hydrocarbons were below detection. Firmicutes, however, continued to increase in relative richness and abundance after hydrocarbon concentrations were below detection. Functional genes involved in hydrocarbon degradation were enriched in hydrocarbon-contaminated sediments then declined significantly (p<0.05) once hydrocarbon concentrations decreased. A greater decrease in hydrocarbon concentrations among marsh grass sediments compared to inlet sediments (lacking marsh grass) suggests that the marsh rhizosphere microbial communities could also be contributing to hydrocarbon degradation. The results of this study provide a comprehensive view of microbial community structural and functional dynamics within perturbed salt marsh ecosystems.},
doi = {10.1371/journal.pone.0041305},
journal = {PLoS ONE},
number = 7,
volume = 7,
place = {United States},
year = {Wed Jul 18 00:00:00 EDT 2012},
month = {Wed Jul 18 00:00:00 EDT 2012}
}
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