Molecular Biomarkers and Influential Factors of Denitrification in a Full-Scale Biological Nitrogen Removal Plant

Three denitrifying bacteria, Paracoccus spp., Thauera spp., Pseudomonas-like spp., and two functional genes, nitrate reductase (narG and napA), were studied as potential biomarkers for total nitrogen removal. These bacterial genera and the functional genes showed significant negative correlations with total nitrogen in the effluent (TN_eff). Thauera spp. had the highest correlation (r = -0.793, p < 0.001) with TN_eff, and narG-like and napA genes also showed significant correlations (r = -0.663 and -0.643, respectively), suggesting functional genes have equal validity to 16S rRNA genes in monitoring denitrification performance. The most explanatory variables were a combination of constituents, with temperature emerging as the most important in Pearson's correlation and redundancy analysis. Thauera spp. had the highest correlation with temperature (r = 0.739) followed closely by Paracoccus spp. (r = 0.705). Denitrification was also significantly affected by pH (r = 0.369), solids retention time (r = -0.377), total nitrogen_in (r = 0.635), and organic matter in the influent (biochemical oxygen demand and chemical oxygen demand; r = 0.320 and 0.522, respectively). Our data verified that major denitrifiers' 16S rRNA genes and nitrate reductase genes were better biomarkers than the biomass concentration, and any of the biomarkers could track denitrification in real time.