Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/105014
Title: Using meta‐omics of contaminated sediments to monitor changes in pathways relevant to climate regulation
Authors: Kelaher, Brendan P.
Birrer, Simone C.
Dafforn, Katherine A.
Sun, Melanie Y.
Potts, Jaimie
Scanes, Peter
Simpson, Stuart L.
Kjelleberg, Staffan
Swarup, Sanjay
Steinberg, Peter
Johnston, Emma L.
Williams, Rohan Benjamin Hugh
Keywords: Nitrogen Cycle
DRNTU::Engineering::Environmental engineering
Denitrification
Issue Date: 2018
Source: Birrer, S. C., Dafforn, K. A., Sun, M. Y., Williams, R. B. H., Potts, J., Scanes, P., . . . Johnston, E. L. (2019). Using meta‐omics of contaminated sediments to monitor changes in pathways relevant to climate regulation. Environmental Microbiology, 21(1), 389-401. doi:10.1111/1462-2920.14470
Series/Report no.: Environmental Microbiology
Abstract: Microbially mediated biogeochemical processes are crucial for climate regulation and may be disrupted by anthropogenic contaminants. To better manage contaminants, we need tools that make real‐time causal links between stressors and altered microbial functions, and the potential consequences for ecosystem services such as climate regulation. In a manipulative field experiment, we used metatranscriptomics to investigate the impact of excess organic enrichment and metal contamination on the gene expression of nitrogen and sulfur metabolisms in coastal sediments. Our gene expression data suggest that excess organic enrichment results in (i) higher transcript levels of genes involved in the production of toxic ammonia and hydrogen sulfide and (ii) lower transcript levels associated with the degradation of a greenhouse gas (nitrous oxide). However, metal contamination did not have any significant impact on gene expression. We reveal the genetic mechanisms that may lead to altered productivity and greenhouse gas production in coastal sediments due to anthropogenic contaminants. Our data highlight the applicability of metatranscriptomics as a management tool that provides an immense breadth of information and can identify potentially impacted process measurements that need further investigation.
URI: https://hdl.handle.net/10356/105014
http://hdl.handle.net/10220/48643
ISSN: 1462-2912
DOI: 10.1111/1462-2920.14470
Rights: © 2018 Society for Applied Microbiology and John Wiley & Sons Ltd. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
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