Analysis of microbial diversity and functions in sediments and overlying water of the Shiliu River.

Background: With the acceleration of urbanization, urban rivers have become a significant component of the urban ecosystem, attracting considerable attention regarding their ecological status and biodiversity. This study focuses on the Shiliu River, aiming to analyze the microbial diversity and functions present in the overlying water and sediments of severely polluted areas.

Methods: This study investigated the Shiliu River. In August 2024, sediment and overlying water samples were collected from its severely polluted reaches. The NextSeq 2000 PE300 platform was employed for sequencing to detect bacterial and fungal taxa abundances. PICRUSt and FUNGuild predicted sample functional abundances using bacterial 16S rRNA and fungal internal transcribed spacer (ITS) gene sequences, respectively.

Results: The findings demonstrate that sediments exhibit higher bacterial and fungal richness than overlying water, with significant discrepancies in bacterial and fungal community compositions. Dominant taxa differ at both phylum and genus levels: in sediments, the predominant bacterial phylum is Proteobacteria and genus norank_, while the dominant fungal phylum is Rozellomycota and genus unclassified_. In overlying water, the bacterial phylum remains Proteobacteria but the dominant genus shifts to , whereas fungal phyla and genera (Rozellomycota and unclassified_) are consistent with sediments. Kyoto Encyclopedia of Genes and Genomes (KEGG) functional annotation identifies 25 metabolic pathways, with amino acid metabolism-related genes showing the highest abundance in both environments. Clusters of Orthologous Genes (COG) annotation reveals the highest abundance of [R] General function prediction in both sample groups, and FUNGuild analysis indicates that Animal Endosymbiont-Animal Pathogen-Plant Pathogen-Undefined Saprotroph is the most prevalent functional category in both sediments and overlying water. This study provides a microbiological foundation by clarifying microbial community structures (dominant phyla, functional taxa), decoding pollutant-degrading metabolic potentials (N/C cycling pathways), and identifying river health ecological indicators. This enables targeted bioremediation strategies (., sediment microbial consortia for nutrient removal) and integrates microbial ecological data into urban river restoration.

Conclusions: This study reveals the microbial community structures in the sediments and overlying water of the polluted Shiliu River, finding diverse patterns with higher richness in sediments, Proteobacteria and Ascomycota as dominants. Shared taxa have different abundances, indicating niche differentiation. Sediments have enriched nitrogen/carbon cycling pathways for pollutant degradation. These results offer a microbiological basis for urban river restoration, identify bioremediation-target taxa, and stress the integration of microbial ecology into pollution management.