Urban rivers in rapidly developing tropical cities represent critical interfaces between human activities and natural ecosystems, yet they face dual pressures from increasing pollutant inputs and pathogen enrichment. This study investigated the Mirongo River in Mwanza, Tanzania, by integrating 16S rRNA high-throughput sequencing with the MBPD pathogen database to systematically analyze the composition, network structure, and environmental drivers of pathogenic microbial communities. The results indicated degraded water quality in the Mirongo River, characterized by evident eutrophication and organic pollution. Regarding pathogenic community composition, zoonotic pathogens exhibited the highest abundance (33-64%), whereas animal-associated pathogens showed the greatest diversity. Plant pathogens demonstrated the lowest overall abundance and diversity. Co-occurrence network analysis revealed that positive correlations dominated network connections. Animal-associated pathogens exhibited superiority in node number and network transitivity, indicating their key role in maintaining community structural stability. Zoonotic pathogens displayed prominence in betweenness centrality, serving as critical connectors and information carriers. Plant pathogens were primarily distributed at the network periphery. Environmental factor analysis indicated that COD and temperature were associated with the distribution patterns of pathogenic microbial communities. At the genus level, Acinetobacter was positively correlated with total nitrogen and COD, whereas Exiguobacterium was negatively correlated with total nitrogen and total phosphorus. These findings suggest that pollutant inputs and water quality gradients jointly regulate the distribution patterns of pathogenic communities in tropical urban rivers. Overall, this study provides baseline information on the distribution patterns and environmental associations of potentially pathogenic microorganisms in a tropical urban river, contributing to microbial monitoring and water quality management.
Shi et al. (Sat,) studied this question.