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

• Published in: Brazilian journal of microbiology Vol. 51; no. 3; pp. 1191 - 1207
• Main Authors: Sun, Ran, Tu, Zuxin, Fan, Lin, Qiao, Zixia, Liu, Xiaoyan, Hu, Sihai, Zheng, Guohua, Wu, Yaoguo, Wang, Ruiwu, Mi, Xiaohui
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.09.2020; Springer Nature B.V
• Subjects: Aquatic ecosystems; Artificial neural networks; Bacteria; Bacteria - classification; Bacteria - genetics; Bacteria - isolation & purification; Biomedical and Life Sciences; China; Cluster analysis; Community composition; Community structure; Composition; Correlation analysis; Environmental Microbiology - Research Paper; Food Microbiology; Fresh water; Freshwater ecosystems; Freshwater microorganisms; Geologic Sediments - chemistry; Geologic Sediments - microbiology; Lake sediments; Lakes; Lakes - chemistry; Lakes - microbiology; Life Sciences; Medical Microbiology; Microbial Ecology; Microbial Genetics and Genomics; Microbiology; Microbiota; Microorganisms; Mycology; Neural networks; Neural Networks, Computer; Niches; Nitrogen - analysis; Nitrogen - metabolism; Nutrients; Phosphorus - analysis; Phosphorus - metabolism; Phylogeny; Physicochemical properties; Sediment samplers; Sediments; Tributaries; Water analysis; Water sampling; Wetlands; China; Poyang Lake; Phylogenetic analysis; Denaturing gradient gel electrophoresis; Artificial neural network; Bacterial community composition; Poyang Lake
• ISSN: 1517-8382; 1678-4405
• DOI: 10.1007/s42770-020-00285-2

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.