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Denitrification potential of the eastern oyster microbiome using a 16S rRNA gene based metabolic inference approach
The eastern oyster (Crassostrea virginica) is a foundation species providing significant ecosystem services. However, the roles of oyster microbiomes have not been integrated into any of the services, particularly nitrogen removal through denitrification. We investigated the composition and denitrif...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5608302/ https://www.ncbi.nlm.nih.gov/pubmed/28934286 http://dx.doi.org/10.1371/journal.pone.0185071 |
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author | Arfken, Ann Song, Bongkeun Bowman, Jeff S. Piehler, Michael |
author_facet | Arfken, Ann Song, Bongkeun Bowman, Jeff S. Piehler, Michael |
author_sort | Arfken, Ann |
collection | PubMed |
description | The eastern oyster (Crassostrea virginica) is a foundation species providing significant ecosystem services. However, the roles of oyster microbiomes have not been integrated into any of the services, particularly nitrogen removal through denitrification. We investigated the composition and denitrification potential of oyster microbiomes with an approach that combined 16S rRNA gene analysis, metabolic inference, qPCR of the nitrous oxide reductase gene (nosZ), and N(2) flux measurements. Microbiomes of the oyster digestive gland, the oyster shell, and sediments adjacent to the oyster reef were examined based on next generation sequencing (NGS) of 16S rRNA gene amplicons. Denitrification potentials of the microbiomes were determined by metabolic inferences using a customized denitrification gene and genome database with the paprica (PAthway PRediction by phylogenetIC plAcement) bioinformatics pipeline. Denitrification genes examined included nitrite reductase (nirS and nirK) and nitrous oxide reductase (nosZ), which was further subdivided by genotype into clade I (nosZI) or clade II (nosZII). Continuous flow through experiments measuring N(2) fluxes were conducted with the oysters, shells, and sediments to compare denitrification activities. Paprica properly classified the composition of microbiomes, showing similar classification results from Silva, Greengenes and RDP databases. Microbiomes of the oyster digestive glands and shells were quite different from each other and from the sediments. The relative abundance of denitrifying bacteria inferred by paprica was higher in oysters and shells than in sediments suggesting that oysters act as hotspots for denitrification in the marine environment. Similarly, the inferred nosZI gene abundances were also higher in the oyster and shell microbiomes than in the sediment microbiome. Gene abundances for nosZI were verified with qPCR of nosZI genes, which showed a significant positive correlation (F(1,7) = 14.7, p = 6.0x10(-3), R(2) = 0.68). N(2) flux rates were significantly higher in the oyster (364.4 ± 23.5 μmol N-N(2) m(-2) h(-1)) and oyster shell (355.3 ± 6.4 μmol N-N(2) m(-2) h(-1)) compared to the sediment (270.5 ± 20.1 μmol N-N(2) m(-2) h(-1)). Thus, bacteria carrying nosZI genes were found to be an important denitrifier, facilitating nitrogen removal in oyster reefs. In addition, this is the first study to validate the use of 16S gene based metabolic inference as a method for determining microbiome function, such as denitrification, by comparing inference results with qPCR gene quantification and rate measurements. |
format | Online Article Text |
id | pubmed-5608302 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-56083022017-10-09 Denitrification potential of the eastern oyster microbiome using a 16S rRNA gene based metabolic inference approach Arfken, Ann Song, Bongkeun Bowman, Jeff S. Piehler, Michael PLoS One Research Article The eastern oyster (Crassostrea virginica) is a foundation species providing significant ecosystem services. However, the roles of oyster microbiomes have not been integrated into any of the services, particularly nitrogen removal through denitrification. We investigated the composition and denitrification potential of oyster microbiomes with an approach that combined 16S rRNA gene analysis, metabolic inference, qPCR of the nitrous oxide reductase gene (nosZ), and N(2) flux measurements. Microbiomes of the oyster digestive gland, the oyster shell, and sediments adjacent to the oyster reef were examined based on next generation sequencing (NGS) of 16S rRNA gene amplicons. Denitrification potentials of the microbiomes were determined by metabolic inferences using a customized denitrification gene and genome database with the paprica (PAthway PRediction by phylogenetIC plAcement) bioinformatics pipeline. Denitrification genes examined included nitrite reductase (nirS and nirK) and nitrous oxide reductase (nosZ), which was further subdivided by genotype into clade I (nosZI) or clade II (nosZII). Continuous flow through experiments measuring N(2) fluxes were conducted with the oysters, shells, and sediments to compare denitrification activities. Paprica properly classified the composition of microbiomes, showing similar classification results from Silva, Greengenes and RDP databases. Microbiomes of the oyster digestive glands and shells were quite different from each other and from the sediments. The relative abundance of denitrifying bacteria inferred by paprica was higher in oysters and shells than in sediments suggesting that oysters act as hotspots for denitrification in the marine environment. Similarly, the inferred nosZI gene abundances were also higher in the oyster and shell microbiomes than in the sediment microbiome. Gene abundances for nosZI were verified with qPCR of nosZI genes, which showed a significant positive correlation (F(1,7) = 14.7, p = 6.0x10(-3), R(2) = 0.68). N(2) flux rates were significantly higher in the oyster (364.4 ± 23.5 μmol N-N(2) m(-2) h(-1)) and oyster shell (355.3 ± 6.4 μmol N-N(2) m(-2) h(-1)) compared to the sediment (270.5 ± 20.1 μmol N-N(2) m(-2) h(-1)). Thus, bacteria carrying nosZI genes were found to be an important denitrifier, facilitating nitrogen removal in oyster reefs. In addition, this is the first study to validate the use of 16S gene based metabolic inference as a method for determining microbiome function, such as denitrification, by comparing inference results with qPCR gene quantification and rate measurements. Public Library of Science 2017-09-21 /pmc/articles/PMC5608302/ /pubmed/28934286 http://dx.doi.org/10.1371/journal.pone.0185071 Text en © 2017 Arfken et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Arfken, Ann Song, Bongkeun Bowman, Jeff S. Piehler, Michael Denitrification potential of the eastern oyster microbiome using a 16S rRNA gene based metabolic inference approach |
title | Denitrification potential of the eastern oyster microbiome using a 16S rRNA gene based metabolic inference approach |
title_full | Denitrification potential of the eastern oyster microbiome using a 16S rRNA gene based metabolic inference approach |
title_fullStr | Denitrification potential of the eastern oyster microbiome using a 16S rRNA gene based metabolic inference approach |
title_full_unstemmed | Denitrification potential of the eastern oyster microbiome using a 16S rRNA gene based metabolic inference approach |
title_short | Denitrification potential of the eastern oyster microbiome using a 16S rRNA gene based metabolic inference approach |
title_sort | denitrification potential of the eastern oyster microbiome using a 16s rrna gene based metabolic inference approach |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5608302/ https://www.ncbi.nlm.nih.gov/pubmed/28934286 http://dx.doi.org/10.1371/journal.pone.0185071 |
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