ena-STUDY-CORNELL UNIVERSITY-31-08-2018-16:17:25:584-42
Metagenomic analysis reveals distinct patterns of denitrification gene abundance across soil moisture, nitrate gradients
Relationships among denitrifying soil microbial communities, environmental factors, and denitrification rates are difficult to identify due to complex interactions between the environment and denitrifiers as well as the diversity of denitrifier genotypes and phenotypes. Using metagenomic analysis, this study provides an unbiased estimate of the relative abundance for all denitrification genes in a small headwater catchment with predominantly agricultural or forest land cover. This information was paired with 16S amplicon sequencing, environmental measurements, and denitrification end product measurements in order to elucidate the complex relationships mentioned above. Distinct patterns of denitrification gene abundance were observed at the landscape scale. One subset of denitrification genes, nirS, nosZ, and cNor, were found to co-occur at sites with environmental conditions most favorable for denitrification, indicating that specialized denitrifying communities exist at these sites. Moreover, the genes nirK and qNor were found to show a negative correlation with the previously mentioned gene subset. Soils with higher levels of nirS, nosZ, and cNor were observed to have higher denitrification process rates. This work demonstrates that the information gained from analysis of denitrifier communities via metagenomics can provide unique insights that can help identify denitrification hotspots at the landscape scale.
Relationships among denitrifying soil microbial communities, environmental factors, and denitrification rates are difficult to identify due to complex interactions between the environment and denitrifiers as well as the diversity of denitrifier genotypes and phenotypes. Using metagenomic analysis, this study provides an unbiased estimate of the relative abundance for all denitrification genes in a small headwater catchment with predominantly agricultural or forest land cover. This information was paired with 16S amplicon sequencing, environmental measurements, and denitrification end product measurements in order to elucidate the complex relationships mentioned above. Distinct patterns of denitrification gene abundance were observed at the landscape scale. One subset of denitrification genes, nirS, nosZ, and cNor, were found to co-occur at sites with environmental conditions most favorable for denitrification, indicating that specialized denitrifying communities exist at these sites. Moreover, the genes nirK and qNor were found to show a negative correlation with the previously mentioned gene subset. Soils with higher levels of nirS, nosZ, and cNor were observed to have higher denitrification process rates. This work demonstrates that the information gained from analysis of denitrifier communities via metagenomics can provide unique insights that can help identify denitrification hotspots at the landscape scale.