Denitrification potential of the eastern oyster microbiome using a 16S rRNA gene based metabolic inference approach

TitleDenitrification potential of the eastern oyster microbiome using a 16S rRNA gene based metabolic inference approach
Publication TypeJournal Article
Year of Publication2017
AuthorsArfken A., Song B., Bowman J.S, Piehler M.
JournalPlos One
Volume12
Date Published2017/09
Type of ArticleArticle
ISBN Number1932-6203
Accession NumberWOS:000411339900083
Keywordsbacterial communities; bay estuary; crassostrea-gigas; diversity; mediterranean sea; new-zealand; nitrification; nitrous-oxide reductase; pacific oysters; sediment
Abstract

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,F-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 mu mol N-N-2 m(-2) h(-1)) and oyster shell (355.3 +/- 6.4 mu mol N-N-2 m(-2) h(-1)) compared to the sediment (270.5 +/- 20.1 mu mol 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.

DOI10.1371/journal.pone.0185071
Student Publication: 
No
sharknado