4.7 Article

Assembly mechanism and co-occurrence patterns of DNRA microbial communities and imprint of nitrate reduction in the Songhua River sediments of China's largest old industrial base

期刊

JOURNAL OF ENVIRONMENTAL MANAGEMENT
卷 322, 期 -, 页码 -

出版社

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jenvman.2022.116091

关键词

Songhua river basin; DNRA; Community assembly; Stochastic processes; Co-occurrence patterns

资金

  1. National Key R&D Program of China [2018YFF0213406]
  2. National Natural Science Foundation of China [22076100]
  3. Taishan Scholar Youth Expert Program of Shandong Province [tsqn201909005]
  4. Key Research & Developmental Program of Shandong Province [2021CXGC011202]
  5. Young Scholars Program of Shandong University [2020QNQT012]
  6. Open Project of State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology [ES201909]
  7. Qingdao Science and Technology Huimin Demonstration Guide Project [20-3-4-4-nsh]
  8. Jinan Science and Technology Research Leader Studio Project [2020GXRC054]

向作者/读者索取更多资源

This study explores the assembly mechanisms and co-occurrence patterns of DNRA microbial communities and the impact of nitrate reduction in Songhua River Basin. The results indicate that DNRA microbial communities are influenced by environmental factors and stochastic processes, with the Geobacteraceae playing a key role in DNRA and the overall bacterial community.
Dissimilatory nitrate reduction to ammonium (DNRA) reduces nitrate to ammonium nitrogen instead of nitrogen gas, which is an important internal linking process of nitrogen cycle. No literature has reported the assembly mechanism of DNRA microbial communities. Here, the deep assembly mechanisms and co-occurrence patterns of DNRA microbial communities and imprint of nitrate reduction in Songhua River Basin (an inland river located in northeastern China) were studied. The DNRA potential rates were detected at six sampling sites, ranging from 0.25 +/- 0.23 to 4.22 +/- 0.61 mu mol N/L/h, accounting for 33.07% to 98.08% of the total nitrate reduction. Spearman analysis indicated that the nrfA gene abundance was significantly positively correlated with the concentration of total nitrogen (TN) in sediments (p < 0.05), suggesting that nutrient inputs may enhance the metabolic potential of DNRA bacteria. Co-occurrence network and Spearman correlation analyses showed that the DNRA rates were significantly correlated with the abundance of keystone species, but not with the dominant genera (p < 0.05). Variance partitioning analysis (VPA) revealed that sediment physicochemical properties and spatial factors explained only 21.07% and 14.51% of the DNRA community variation. Null model and neutral community model both revealed stochastic processes play a major role in shaping DNRA microbial community structure. The drift was the most important process, explaining 36.36% of the community variation, followed by homogeneous selection and homogenizing dispersal, which accounted for 27.27% and 22.73%, respectively. Additionally, Geobacteraceae played an important role in DNRA and the entire bacterial community in Songhua River. This study explored the underestimated DNRA process and the deep community assembly mechanisms, which will contribute to understanding nitrate conversion and the impact of nitrogen pollution on microbial communities of river sediments in cold regions.

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