| 1 | NirS-type denitrifying bacteria in aerobic water layers of two drinking water reservoirs: Insights into the abundance, community diversity and co-existence model显示文摘The nirS-type denitrifying bacterial community is the main drivers of the nitrogen loss process in drinking water reservoir ecosystems.The temporal patterns in nirS gene abundance and nirS-type denitrifying bacterial community harbored in aerobic water layers of drinking water reservoirs have not been studied well.In this study,quantitative polymerase chain reaction(qPCR)and Illumina Miseq sequencing were employed to explore the nirS gene abundance and denitrifying bacterial community structure in two drinking water reservoirs.The overall results showed that the water quality parameters in two reservoirs had obvious differences.The qPCR results suggested that nirS gene abundance ranged from(2.61±0.12)×10^(5) to(3.68±0.16)×10^(5) copies/mL and(3.01±0.12)×10^(5) to(5.36±0.31)×10^(5) copies/mL in Jinpen and Lijiahe reservoirs,respectively.The sequencing results revealed that Paracoccus sp.,Azoarcus sp.,Dechloromonas sp.and Thauera sp.were the dominant genera observed.At species level,Cupriavidus necator,Dechloromonas sp.R-28400,Paracoccus denitrificans and Pseudomonas stutzeri accounted for more proportions in two reservoirs.More importantly,the co-occurrence network analysis demonstrated that Paracoccus sp.R-24615 and Staphylococcus sp.N23 were the keystone species observed in Jinpen and Lijiahe reservoirs,respectively.Redundancy analysis indicated that water quality(particularly turbidity,water temperature,pH and Chlorophyll a)and sampling time had significant influence on the nirS-type denitrifying bacterial community in both reservoirs.These results will shed new lights on exploring the dynamics of nirS-type denitrifying bacteria in aerobic water layers of drinking water reservoirs. | Haihan Zhang Yinjie Shi Tinglin Huang Rongrong Zong Zhenfang Zhao BenMa Nan Li Shangye Yang Mengqiao Liu | 2023 | Journal of Environmental Sciences2023，，2： | 1 |
| 2 | Multivariate statistical and bioinformatic analyses for the seasonal variations of actinobacterial community structures in a drinking water reservoir显示文摘Actinobacterial community is a conspicuous part of aquatic ecosystems and displays an important role in the case of biogeochemical cycle,but little is known about the seasonal variation of actinobacterial community in reservoir ecological environment.In this study,the high-throughput techniques were used to investigate the structure of the aquatic actinobacterial community and its inducing water quality parameters in different seasons.The results showed that the highest diversity and abundance of actinobacterial community occurred in winter,with Sporichthya(45.42%)being the most abundant genus and Rhodococcus sp.(29.32%)being the most abundant species.Network analysis and correlation analysis suggested that in autumn the dynamics of actinobacterial community were infuenced by more factors and Nocardioides sp.SX2R5S2 was the potential keystone species which was negatively correlated with temperature(R=-0.72,P<0.05).Changes in environmental factors could significantly affect the changes in actinobacterial community,and the dynamics of temperature,dissolved oxygen(DO),and turbidity are potential conspicuous factors infuencing seasonal actinobacterial community trends.The partial least squares path modeling further elucidated that the combined effects of DO and temperature not only in the diversity of actinobacterial community but also in other water qualities,while the physiochemical parameters(path coefficient=1.571,P<0.05)was strong environmental factors in natural mixture period.These results strengthen our understanding of the dynamics and structures of actinobacterial community in the drinking water reservoirs and provide scientific guidance for further water quality management and protection in water sources. | Haihan Zhang Sixuan Pan BenMa Tinglin Huang Dmitry B.Kosolapov Manli Ma Xiang Liu Huan Liu Xiaoyan Liu | 2024 | Journal of Environmental Sciences2024，，3： | 0 |
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