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Distinct distribution patterns of proteobacterial nirK- and nirS-type denitrifiers in the Yellow River estuary, China.

Authors
  • Li, Fenge1, 2
  • Li, Mingcong1, 2
  • Shi, Wenchong1, 2
  • Li, Han1, 2
  • Sun, Zhongtao2
  • Gao, Zheng1, 2, 3
  • 1 a State Key Laboratory of Crop Biology, Shandong Agricultural University, Tai'an, People's Republic of China. , (China)
  • 2 b College of Life Sciences, Shandong Agricultural University, Tai'an, People's Republic of China. , (China)
  • 3 c State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai, People's Republic of China. , (China)
Type
Published Article
Journal
Canadian Journal of Microbiology
Publisher
Canadian Science Publishing
Publication Date
Aug 01, 2017
Volume
63
Issue
8
Pages
708–718
Identifiers
DOI: 10.1139/cjm-2017-0053
PMID: 28414921
Source
Medline
Keywords
License
Unknown

Abstract

Denitrification is considered to be the critical process in removing reactive nitrogen in estuarine ecosystems. In the present study, the abundance, diversity, and community structure of nirK- and nirS-type denitrifiers were compared in sediments from the Yellow River estuary. Quantitative polymerase chain reaction showed that the 2 types of denitrifiers exhibited different distribution patterns among the samples, indicating their distinct habitat preference. Phylogenetic analysis revealed that most of the sequences from clusters I, III, IV, and V for nirK-type denitrifiers were dominant and were distributed at sites where dissolved oxygen (DO) was lower, and the sequences in the other clusters were dominant at sites with higher DO. However, there was no spatially heterogeneous distribution for the nirS-type denitrifier community. Canonical correlation analysis and correlation analysis demonstrated that the community structure of nirK was more responsive to environmental factors than was that of nirS. Inversely, the abundance and α-diversity targeting nirS gene could be more easily influenced by environmental parameters. These findings can extend our current knowledge about the distribution patterns of denitrifying bacteria and provide a basic theoretical reference for the dynamics of denitrifying communities in estuarine ecosystem of China.

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