Global environmental resistome: Distinction and connectivity across diverse habitats benchmarked by metagenomic analyses. (15th May 2023)

• Record Type: Journal Article
• Authors: Yin, Xiaole; Li, Liguan; Chen, Xi; Liu, Yang-Yu; Lam, Tommy Tsan-Yuk; Topp, Edward; Zhang, Tong
• Is Part Of: Water research. Volume 235(2023)
• Publication Date: 2023-05-15
• Subjects: Water -- Pollution -- Research -- Periodicals; 363.7394
• DOI: 10.1016/j.watres.2023.119875
• Languages: English
• ISSNs: 0043-1354

Abstract

Highlights: Resistome was most diverse in wastewater while most abundant in fecal samples. Industrial, urban, agricultural, and natural environments were surveyed globally. Bacterial composition was significantly correlated with ARGs across most habitats. A microbial source tracking model regarding resistome has been developed for MST v2.0. Emerging mobilizable ARGs: mcr and tet(X) in these habitats were benchmarked. Abstract: The widely distributed antibiotic resistance genes (ARGs) were unevenly proliferated in various habitats. Great endeavors are needed to resolve the resistome features that can differentiate or connect different habitats. This study retrieved a broad spectrum of resistome profiles from 1723 metagenomes categorized into 13 habitats, encompassing industrial, urban, agricultural, and natural environments, and spanning most continents and oceans. The resistome features (ARG types, subtypes, indicator ARGs, and emerging mobilizable ARGs: mcr and tet(X) ) in these habitats were benchmarked via a standardized workflow. We found that wastewater and wastewater treatment works were characterized to be reservoirs of more diverse genotypes of ARGs than any other habitats including human and livestock fecal samples, while fecal samples were with higher ARG abundance. Bacterial taxonomy composition was significantly correlated with resistome composition across most habitats. Moreover, the source-sink connectivities were disentangled by developing the resistome-based microbial attribution prediction model. Environmental surveys with standardized bioinformatic workflow proposed in this study will help comprehensively understand the transfer of ARGs in the environment, thus prioritizing the critical environments with high risks for intervention to tackle the problem of ARGs. Graphical abstract: Image, graphical abstract