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The correlation analyses of bacterial community composition and spatial factors between freshwater and sediment in Poyang Lake wetland by using artificial neural network (ANN) modeling

  • Environmental Microbiology - Research Paper
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Abstract

As one of the most important components of the lake ecosystem, microorganisms from the freshwater and sediment play an important role in many ecological processes. However, the difference and correlation of bacterial community between these two niches were not clear. This study investigated the diversity of microbial community of freshwater and sediment samples from fifteen locations in Poyang Lake wetland. The correlation between the bacterial community and physicochemical property of Poyang Lake wetland was analyzed by artificial neural network (ANN). Our results demonstrated that the freshwater and sediment bacterial community were dominated by groups of the Bacteroidetes (23.33%) and β-Proteobacteria (22.54%) separately, whereas, Canalipalpata, Bacillariophyta, Gemmatimonadetes, and Verrucomicrobia were detected in freshwater niches only. Phylogenetic analysis further indicated that bacterial composition in freshwater significantly differed with the sediment niches. There are 34 unique species accounted for 85% in fresh water samples and 28 unique species accounted for 82% in sediment samples. Cluster analysis further proved that all the samples from freshwater niches clustered closely together, far from the rest sediment samples. ANN analysis revealed that the freshwater with high N and P nutrients will greatly increase the diversity of the bacterial communities. In general, both environmental physicochemical properties, not each factor independently, contributed to the shift in the bacterial community structure. The five tributaries (Gan, Fu, Xin, Rao, Xiu Rivers) play a vital role in shaping the bacterial communities of Poyang Lake. This study provides new insights for understanding of microbial community compositions and structures of Poyang Lake wetland.

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Abbreviations

DGGE:

Denaturing gradient gel electrophoresis

WD:

Water depth

TRA:

Transparency

TEM:

Water temperature

NTU:

Turbidity

DO:

Dissolved oxygen

CON:

Conductivity

ORP:

Oxidation-reduction potential

PAR:

Photosynthetically active radiation

CHL:

Chlorophyll content

TDS:

Total dissolved solid

SAL:

Salinity

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Acknowledgments

The authors are grateful to the anonymous reviewers and the editor for their constructive suggestions and professional editing.

Funding

This work was financially supported by the National Natural Science Foundation of China (Program No. 41601338), Natural Science Basic Research Plan in Shaanxi Province of China (Program No. 2018JQ4019 and 2020JM-110), the Fundamental Research Funds for the Central Universities (Program No. 3102018zy042), and National Training Programs of Innovation and Entrepreneurship for Undergraduates (S201910699176).

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Authors and Affiliations

  1. School of Chemistry and Chemical Engineering, Northwestern Polytechnical University, Xi’An, 710129, China

    Ran Sun, Lin Fan, Zixia Qiao, Xiaoyan Liu, Sihai Hu, Yaoguo Wu & Xiaohui Mi

  2. School of Ecology and Environment, Northwestern Polytechnical University, Xi’An, 710129, China

    Ran Sun & Ruiwu Wang

  3. Institute of Microbiology, Jiangxi Academy of Sciences, Nanchang, 330029, China

    Zuxin Tu & Guohua Zheng

  4. Key Laboratory of Poyang Lake, Jiangxi Academy of Sciences, Nanchang, 330029, China

    Guohua Zheng

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  1. Ran Sun
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Correspondence to Yaoguo Wu or Ruiwu Wang.

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Sun, R., Tu, Z., Fan, L. et al. The correlation analyses of bacterial community composition and spatial factors between freshwater and sediment in Poyang Lake wetland by using artificial neural network (ANN) modeling. Braz J Microbiol 51, 1191–1207 (2020). https://doi.org/10.1007/s42770-020-00285-2

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