Integrative genome-centric metagenomics for surface water surveillance: Elucidating microbiomes, antimicrobial resistance, and their associations

Abstract

Surface water ecosystems are intimately intertwined with anthropogenic activities and have significant public health implications as primary sources of irrigation water in agricultural production. Our extensive metagenomic analysis examined 404 surface water samples from four different geological regions in Chile and Brazil, spanning irrigation canals (n = 135), rivers (n = 121), creeks (n = 74), reservoirs (n = 66), and ponds (n = 8). Overall, 50.25 % of the surface water samples contained at least one of the pathogenic or contaminant bacterial genera (Salmonella: 29.21 %; Listeria: 6.19 %; Escherichia: 35.64 %). Furthermore, a total of 1,582 antimicrobial resistance (AMR) gene clusters encoding resistance to 25 antimicrobial classes were identified, with samples from Brazil exhibiting an elevated AMR burden. Samples from stagnant water sources were characterized by dominant Cyanobacteriota populations, resulting in significantly reduced biodiversity and more uniform community compositions. A significant association between taxonomic composition and the resistome was supported by a Procrustes analysis (p < 0.001). Notably, regional signatures were observed regarding the taxonomic and resistome profiles, as samples from the same region clustered together on both ordinates. Additionally, network analysis illuminated the intricate links between taxonomy and AMR at the contig level. Our deep sequencing efforts not only mapped the microbial landscape but also expanded the genomic catalog with newly characterized metagenome-assembled genomes (MAGs), boosting the classification of reads by 12.85 %. In conclusion, this study underscores the value of metagenomic approaches in surveillance of surface waters, enhancing our understanding of microbial and AMR dynamics with far-reaching public health and ecological ramifications.