## 4 Discussion
A single clone grouped in unknown cluster V, sharing 83% protein sequence identity with _Chloroflexi bacterium_[39], which is an autotrophic denitrifier whose performance seems to benefit from nitrate removal. Similarly, members of unique cluster III were also observed in the QL-V sample (20%), together with members of the two dominant unique clusters (I and III) (Figure 3C). The sequences in cluster II shared 73-88% protein sequence identity with sequences retrieved from activated sludge in municipal wastewater and coastal wetlands [9]. Five clones were grouped in cluster V, sharing 77-89% protein sequence identity with sequences retrieved from terrestrial subsurface sediments [40]. These _nir_-based phylogenetic trees revealed important patterns and distributions in the denitrifying community in three different environments providing different nitrogen sources (Figures 3 and 4). The majority of _nirS_ clones were found in subclusters within the major clusters formed by unknown denitrifying bacteria, and did not cluster with any known denitrifying bacteria. In contrast, the clones retrieved from the higher-nitrogen QH-V and SR-W samples clustered with more known denitrifying bacteria than those from QL-H. The distribution and diversity of _nirK_-dependent denitrifiers in the various habitats were similar to those of the _nirS_-dependent denitrifiers. This indicates that the three sediments contained unique denitrifiers, which were unknown among previously reported denitrifiers. These results suggest that the distributions and abundances of some denitrifying bacteria correlated with the bioavailability of nitrogen and carbon, whereas the distributions of others (e.g., _nirS_ clusters I and V, and _nirK_ cluster AOB) correlated negatively with the carbon and nitrogen sources. Undeniably, some unique clusters were not detected in the two most extreme environments (the most and least eutrophic) from which our samples were drawn, suggesting that they may only occur at very low levels. Previous studies have shown that long-term supplementation with organic fertilizer or the addition of root-derived carbon only slightly affected the denitrifier community structure [1]. Therefore, the distribution of denitrifier clusters may reflect their adaptation to the various intermediate or hybrid environmental conditions they encounter [23; 41]. Notably, the qPCR analysis showed that the _hao_ gene abundances in all three samples were significantly higher than the _nirS_ gene abundances by orders of magnitude. Compared with the 16S rDNA detected in the environmental habitats, the relative abundances of the _hao_ gene in samples QL-H, QL-V, and SR-W were 5.23%, 5.97%, and 13.60%, respectively, whereas the relative abundances of the _nirS_ gene were 0.54%, 0.44%, and 0.13%, respectively (Figure 6B). The highest abundance of the _hao_ gene was detected in sample SR-W from a river containing domestic sewage, where the higher ammonia nitrogen and eutrophication caused nitrifying bacteria to be the dominant bacteria. Notably, the numbers of denitrifying bacterial _nirS_ genes were lower than the free-living ones at the closest-to-lake site. Previous studies have shown that total inorganic nitrogen, ammonium, and the organic content are important factors affecting community structures, denitrification rates, and Nir abundance of environmental microbes [25]. With the high concentration of ammonium in the SR-W sample, the accumulation of nitrate and nitrite was significantly higher than in the samples of lake water. Nitrate and nitrite also strongly affect denitrification richness [42], which is consistent with the results for the n-damo enrichments [43]. Environmental factors correlated differently and even oppositely with the 16S rDNA and denitrifier-specific sequences in the three samples, indicating that their influence on the nitrifying and denitrifying community structures is very complex.