|Chee Sanford, Joanne|
Submitted to: mBio
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/8/2014
Publication Date: 6/3/2014
Citation: Orellana, L.H., Rodriguez-R, L.M., Higgins, S., Chee-Sanford, J.C., Sanford, R.A., Ritalahti, K.M., Loeffler, F.E., Konstantinidis, K.T. 2014. Detecting nitrous oxide reductase (nosZ) genes in soil metagenomes: method development and implications for the nitrogen cycle. mBio. 5(3):e01193-14. Interpretive Summary: The presence of microbial populations in soil that mediate the reduction of nitrous oxide (N2O), a potent greenhouse gas, is not fully characterized due to recent discovery of many diverse bacteria that harbor atypical NosZ, the enzyme responsible for N2O reduction. These atypical NosZ populations differ from the typical denitrifying microorganisms that have been well studied and previously thought to account for the flux of N2O in the environment. Using new genetic sequencing technology, whole genomes (metagenomes) from two soil types (sand and silt loam) were analyzed for the abundance and diversity of both typical and atypical nosZ genes. First, a new computational search tool was developed to allow the nosZ genes to be accurately detected among the large pool of DNA present in soils, and second, using this tool to determine the types and amounts of each nosZ group. In total, 71 distinct nosZ genes were detected from both soils, and more signficantly, 70% of these genes were in the atypical nosZ group. Further, about 12% of the atypical nosZ genes were assigned to the bacterial genus Anaeromyxobacter, a non-denitrifier that is found broadly in many different environmental systems, and in high abundance compared to other types of bacteria. To demonstrate the further utility of the computational approach developed here, metagenome data from other soils that are made available to the public were analyzed and we found that 11 of 15 soils showed the atypical nosZ outnumbered the typical nosZ group. The significance of this study reveals a serious gap in the accounting of N2O reduction in most soils, where bacterial populations that harbor the atypical nosZ genes may be more important in the mitigation of N2O emissions and suggest these populations along with previously known populations of denitrifiers harboring typical nosZ genes both need to be accounted for to accurately predict N2O flux in soils.
Technical Abstract: Incomplete denitrification in soils represents a major source of nitrous oxide (N2O), a potent greenhouse gas. The key enzyme for mitigating N2O emissions is NosZ, which catalyzes N2O reduction to N2 and is generally attributed to denitrifiers. We recently described an “atypical” functional NosZ enzyme encoded by both denitrifiers and non denitrifiers, which was missed in previous environmental surveys (Sanford et al., PNAS 109:19709-19714, 2012, doi:10.1073/pnas.1211238109). Here, we analyzed the abundance and diversity of both nosZ types in whole-genome shotgun metagenomes from sandy and silty loam agricultural soils that typify the Midwest U.S.A. corn belt. First, different search algorithms and parameters for detecting nosZ metagenomic reads were evaluated based on in silico generated (mock) metagenomes. Using the defined cut-offs, 71 distinct alleles (95% amino acid identity level) encoding typical or atypical nosZ were detected in both soil types. Remarkably, more than 70% of the total nosZ reads in both soils were classified as atypical, emphasizing that prior surveys underestimated the true nosZ abundance. About 12% of the total nosZ reads were taxonomically assigned to the Anaeromyxobacter genus, indicating the potential relevance of non-denitrifiers for N2O reduction. Further analyses revealed that atypical nosZ genes outnumbered typical genes in most publicly available soil metagenomes (11 out of 15), underscoring their ecological importance. Therefore, this study provided a bioinformatics strategy to reliably detect target genes in complex short-read metagenomes, and suggested that the analysis of both typical and atypical nosZ is required to understand and predict N2O flux in soils.