Thu, Aug 05, 2021:On Demand
Background/Question/Methods
Uncontrolled urbanization and industrialization has led to increasing contamination and environmental deterioration of river water and sediment. The adverse impact of urban and industrial effluents on the river can have negative impact on microbial communities, causing changes in the biogeochemical cycling and water quality. In this study we analyzed the microbial diversity across different zones of Kanawha River and correlations with environmental factors using 16S rRNA sequencing (Illumina MiSeq v2), bioinformatics (QIIME 2.0, R version 4.0.4 and Cytoscape), and chemical (Aurora1030D Total Organic Carbon Analyzer, and Dionex Ion Chromatography system) analysis of 30 sediment samples from three locations (Kanawha Falls [less urbanized], Magic Island [commercial and residential] and Blaine Island [industrial]. Samples were taken at different depths, 0 – 5 cm and 5 – 10 cm. Statistical analysis included CCA, and Spearman’s correlations to evaluate effects of chemical parameters on microbial communities, and UniFrac analysis based on phylogenetic distance and multivariate regression tree analysis to compare microbial community diversity between samples or sites. Taxonomic classification was done with Silva 138 database.
Results/Conclusions Taxonomic analysis grouped the sequences into 1347 species, belonging to 509 families and 383 orders. The results of Unifrac analysis revealed that the 30 samples were divided into three groups, corresponding to the three sampling locations with a clear separation of the sediment layers. A Venn diagram demonstrated that these three sites have a unique species that are specific for the chemical environment in which they are living (Kanawha Falls [16 % unique], Magic Island [24 %] and Blaine Island [13 %]). The chemical profiles were quite different between sites. According to CCA, Al, NH4, SO4, Fe, and NO3 are the compounds that have most effect on microbial communities. The most affected orders across the locations are Burkolderiales, Bacteroidales, Spingobacteriales, Bathyarchaea, GIF9, sva0485, MSBL9, Methanomicrobiales, Spirochaetales, Syntrophales and Geobacterales. Network analysis (based on Spearman’s correlation) showed that the microbial community structure is different in each location, suggesting that the chemical profile of the river sediment in these sites play an important ecological role in structuring the communities. These results shed light on understanding how the structure of microbial communities is determined by the chemical composition of urban river environments. Funding by USDA-NIFA-2019-38821-29065
Results/Conclusions Taxonomic analysis grouped the sequences into 1347 species, belonging to 509 families and 383 orders. The results of Unifrac analysis revealed that the 30 samples were divided into three groups, corresponding to the three sampling locations with a clear separation of the sediment layers. A Venn diagram demonstrated that these three sites have a unique species that are specific for the chemical environment in which they are living (Kanawha Falls [16 % unique], Magic Island [24 %] and Blaine Island [13 %]). The chemical profiles were quite different between sites. According to CCA, Al, NH4, SO4, Fe, and NO3 are the compounds that have most effect on microbial communities. The most affected orders across the locations are Burkolderiales, Bacteroidales, Spingobacteriales, Bathyarchaea, GIF9, sva0485, MSBL9, Methanomicrobiales, Spirochaetales, Syntrophales and Geobacterales. Network analysis (based on Spearman’s correlation) showed that the microbial community structure is different in each location, suggesting that the chemical profile of the river sediment in these sites play an important ecological role in structuring the communities. These results shed light on understanding how the structure of microbial communities is determined by the chemical composition of urban river environments. Funding by USDA-NIFA-2019-38821-29065