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

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 N2 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 N2 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 (F1,7 = 14.7, p = 6.0x10-3, R2 = 0.68). N2 flux rates were significantly higher in the oyster (364.4 ± 23.5 μmol N-N2 m-2 h-1) and oyster shell (355.3 ± 6.4 μmol N-N2 m-2 h-1) compared to the sediment (270.5 ± 20.1 μmol N-N2 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.

Fig 1. Average relative abundances of bacterial families in the oyster-related microbiomes, classified by different reference databases.

Families with ≥ 1% relative abundance in samples are shown. Shell microbiome consists of shell (live) and shell (only) treatments.

Fig 2. Principal coordinate analysis (PCoA) of oyster-related microbiomes.

PCoA based on 16S rRNA gene sequences using Bray-Curtis similarity matrix.

Fig 3. Predicted average relative abundances of denitrification genes by paprica for oyster-related microbiomes.

Shell microbiome includes shell (live) and shell (only) treatments. Each full circle represents a relative abundance of 26.1%.

Fig 4. Predicted relative abundances of genes nosZI and nosZII by paprica in oyster-related microbiomes.

Shell microbiome includes both shell (live) and shell (only) treatments.

Fig 5. N₂ flux measurements from oysters, shell only, and sediment treatments using a continuous flow through design.

For each treatment n = 3 and error bars represent ± s.d. (*) significance p < 0.05.

Fig 6. Average predicted relative abundances of total (A) nosZ, (B) nosZI, and (C) nosZII by paprica for oyster-related microbiomes.

Digestive gland combined with shell (live) to form oyster microbiome. Shell (only) forms shell microbiome. For each treatment n = 3 and error bars represent ± s.d.

Fig 7. Linear regression comparing predicted and quantified relative abundances of nosZI genes for shell (live), shell (only) and sediment microbiomes.

Predicted relative abundances based on paprica inferred nosZI gene abundances relative to 16S gene abundances. Quantified relative abundances based on qPCR of nosZI gene copy numbers relative to 16S gene copy numbers.