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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.

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.

SUBMITTER: Sun R

PROVIDER: S-EPMC7455635 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:In river-lake systems, sediment and water column are two distinct habitats harboring different bacterial communities which play a crucial role in biogeochemical processes. In this study, we employed Phylogenetic Investigation of Communities by Reconstruction of Unobserved States to assess the potential functions and functional redundancy of the bacterial communities in sediment and water in a eutrophic river-lake ecosystem, Poyang Lake in China. Bacterial communities in sediment and water had distinct potential functions of carbon, nitrogen, and sulfur metabolisms as well as phosphorus cycle, while the differences between rivers and the lake were inconspicuous. Bacterial communities in sediment had a higher relative abundance of genes associated with carbohydrate metabolism, carbon fixation pathways in prokaryotes, methane metabolism, anammox, nitrogen fixation, and dissimilatory sulfate reduction than that of water column. Bacterial communities in water column were higher in lipid metabolism, assimilatory nitrate reduction, dissimilatory nitrate reduction, phosphonate degradation, and assimilatory sulfate reduction than that of sediment bacterial communities. Furthermore, the variations in functional composition were closely associated to the variations in taxonomic composition in both habitats. In general, the bacterial communities in water column had a lower functional redundancy than in sediment. Moreover, comparing to the overall functions, bacterial communities had a lower functional redundancy of nitrogen metabolism and phosphorus cycle in water column and lower functional redundancy of nitrogen metabolism in sediment. Distance-based redundancy analysis and mantel test revealed close correlations between nutrient factors and functional compositions. The results suggested that bacterial communities in this eutrophic river-lake system of Poyang Lake were vulnerable to nutrient perturbations, especially the bacterial communities in water column. The results enriched our understanding of the bacterial communities and major biogeochemical processes in the eutrophic river-lake ecosystems.

Dataset Information

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.

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