Microbial Community Structure and Bacterial Lineages Associated with Sulfonamides Resistance in Anthropogenic Impacted Larut River

Antimicrobial resistance in southeast Asian water environments: A systematic review of current evidence and future research directions

Antimicrobial resistance has been a serious and complex issue for over a decade. Although research on antimicrobial resistance (AMR) has mainly focused on clinical and animal samples as essential for treatment, the AMR situation in aquatic environments may vary and have complicated patterns according to geographical area. Therefore, this study aimed to examine recent literature on the current situation and identify gaps in the AMR research on freshwater, seawater, and wastewater in Southeast Asia. The PubMed, Scopus, and ScienceDirect databases were searched for relevant publications published from January 2013 to June 2023 that focused on antimicrobial resistance bacteria (ARB) and antimicrobial resistance genes (ARGs) among water sources. Based on the inclusion criteria, the final screening included 41 studies, with acceptable agreement assessed using Cohen's inter-examiner kappa equal to 0.866. This review found that 23 out of 41 included studies investigated ARGs and ARB reservoirs in freshwater rather than in seawater and wastewater, and it frequently found that Escherichia coli was a predominant indicator in AMR detection conducted by both phenotypic and genotypic methods. Different ARGs, such as blaTEM, sul1, and tetA genes, were found to be at a high prevalence in wastewater, freshwater, and seawater. Existing evidence highlights the importance of wastewater management and constant water monitoring in preventing AMR dissemination and strengthening effective mitigation strategies. This review may be beneficial for updating current evidence and providing a framework for spreading ARB and ARGs, particularly region-specific water sources. Future AMR research should include samples from various water systems, such as drinking water or seawater, to generate contextually appropriate results. Robust evidence regarding standard detection methods is required for prospective-era work to raise practical policies and alerts for developing microbial source tracking and identifying sources of contamination-specific indicators in aquatic environment markers.

Environmental DNA metabarcoding reveals the impacts of anthropogenic pollution on multitrophic aquatic communities across an urban river of western China

Anthropogenic activities are intensively affecting the structure and function of biological communities in river ecosystems. The effects of anthropogenic pollution on single-trophic community have been widely explored, but their effects on the structures and co-occurrence patterns of multitrophic communities remain largely unknown. In this study, we collected 13 water samples from the Neijiang River in Chengdu City of China, and identified totally 2352 bacterial, 207 algal, 204 macroinvertebrate, and 33 fish species based on the eDNA metabarcoding to systematically investigate the responses of multitrophic communities to environmental stressors. We observed significant variations in bacterial, algal, and macroinvertebrate community structures (except fish) with the pollution levels in the river. Network analyses indicated a more intensive interspecific co-occurrence pattern at high pollution level. Although taxonomic diversity of the multitrophic communities varied insignificantly, phylogenetic diversities of fish and algae showed significantly positive and negative associations with the pollution levels, respectively. We demonstrated the primary role of environmental filtering in driving the structures of bacteria, algae, and macroinvertebrates, while the fish was more controlled by dispersal limitation. Nitrogen was identified as the most important factor impacting the multitrophic community, where bacterial composition was mostly associated with NO₃^--N, algal spatial differentiation with TN, and macroinvertebrate and fish with NH₄⁺-N. Further partial least-squares path model confirmed more important effect of environmental variables on the relative abundance of bacteria and algae, while macroinvertebrate and fish communities were directly driven by the algae-mediated pathway in the food web. Our study highlighted the necessity of integrated consideration of multitrophic biodiversity for riverine pollution management, and emphasized the importance of controlling nitrogen inputs targeting a healthy ecosystem.