Denitrifier abundance and community composition linked to denitrification potential in river sediments

• Published in: Environmental science and pollution research international 2021-10, Vol.28 (37), p.51928-51939
• Main Authors: Zhang, Mingzhu, Daraz, Umar, Sun, Qingye, Chen, Piaoxue, Wei, Xuhao
• Format: Article
• Language: English
• Subjects: Abundance; Acetylene; Aquatic ecosystems; Aquatic Pollution; Atmospheric Protection/Air Quality Control/Air Pollution; Bacteria; Bioremediation; Community composition; Composition; Denitration; Denitrification; Earth and Environmental Science; Ecotoxicology; Environment; Environmental Chemistry; Environmental Health; Environmental science; Fluvial sediments; Genes; Next-generation sequencing; Nitrogen dioxide; Research Article; Rivers; rRNA 16S; Sediment samplers; Sediments; Spatial distribution; Systems analysis; Thiobacillus; Waste Water Technology; Water Management; Water Pollution Control
• ISSN: 0944-1344; 1614-7499
• DOI: 10.1007/s11356-021-14348-w

Denitrification in river sediments plays a very important role in removing nitrogen in aquatic ecosystem. To gain insight into the key factors driving denitrification at large spatial scales, a total of 135 sediment samples were collected from Huaihe River and its branches located in the northern of Anhui province. Bacterial community composition and denitrifying functional genes ( nirS , nirK , and nosZ ) were measured by high-throughput sequencing and real-time PCR approaches. Potential denitrification rate (PDR) was measured by acetylene inhibition method, which varied from 0.01 to 15.69 μg N g −1 h −1 . The sequencing results based on 16S rRNA gene found that the main denitrification bacterial taxa included Bacillus , Thiobacillus , Acinetobacter , Halomonas , Denitratisoma , Pseudomonas , Rhodanobacter , and Thauera . Therein, Thiobacillus might play key roles in the denitrification. Total nitrogen and N:P ratio were the only chemical factors related with all denitrification genes. Furthermore, nirS gene abundance could be more susceptible to environmental parameters compared with nirK and nosZ genes. Canonical correspondence analysis indicated that NO 3 − , NO 2 − , NH 4 + and IP had the significant impacts on the nirS -encoding bacterial community and spatial distributions. There was a significantly positive correlation between Thiobacillus and nirS gene. We considered that higher numbers of nosZ appeared in nutrient rich sediments. More strikingly, PDR was positively correlated with the abundance of three functional genes. Random forest analysis showed that NH 4 + was the most powerful predictor of PDR. These findings can yield practical and important reference for the bioremediation or evaluation of wetland systems.