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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., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Crown Copyright © 2023. Published by Elsevier Ltd. All rights reserved.)

Motivation: Much global attention has been paid to antibiotic resistance in monitoring its emergence, accumulation and dissemination. For rapid characterization and quantification of antibiotic resistance genes (ARGs) in metagenomic datasets, an online analysis pipeline, ARGs-OAP has been developed consisting of a database termed Structured Antibiotic Resistance Genes (the SARG) with a hierarchical structure (ARGs type-subtype-reference sequence)., Results: The new release of the database, termed SARG version 2.0, contains sequences not only from CARD and ARDB databases, but also carefully selected and curated sequences from the latest protein collection of the NCBI-NR database, to keep up to date with the increasing number of ARG deposited sequences. SARG v2.0 has tripled the sequences of the first version and demonstrated improved coverage of ARGs detection in metagenomes from various environmental samples. In addition to annotation of high-throughput raw reads using a similarity search strategy, ARGs-OAP v2.0 now provides model-based identification of assembled sequences using SARGfam, a high-quality profile Hidden Markov Model (HMM), containing profiles of ARG subtypes. Additionally, ARGs-OAP v2.0 improves cell number quantification by using the average coverage of essential single copy marker genes, as an option in addition to the previous method based on the 16S rRNA gene., Availability and Implementation: ARGs-OAP can be accessed through http://smile.hku.hk/SARGs. The database could be downloaded from the same site. Source codes for this study can be downloaded from https://github.com/xiaole99/ARGs-OAP-v2.0., Supplementary Information: Supplementary data are available at Bioinformatics online.

Emergence of new antibiotic resistance bacteria poses a serious threat to human health, which is largely attributed to the evolution and spread of antibiotic resistance genes (ARGs). In this work, a metagenomics-guided strategy consisting of metagenomic analysis and function validation was proposed for rapidly identifying novel ARGs from hot spots of ARG dissemination, such as wastewater treatment plants (WWTPs) and animal feces. We used an antibiotic resistance gene database to annotate 76 putative β-lactam resistance genes from the metagenomes of sludge and chicken feces. Among these 76 candidate genes, 25 target genes that shared 40~70% amino acid identity to known β-lactamases were cloned by PCR from the metagenomes. Their resistances to four β-lactam antibiotics were further demonstrated. Furthermore, the validated ARGs were used as the reference sequences to identify novel ARGs in eight environmental samples, suggesting the necessity of re-examining the profiles of ARGs in environmental samples using the validated novel ARG sequences. This metagenomics-guided pipeline does not rely on the activity of ARGs during the initial screening process and may specifically select novel ARG sequences for function validation, which make it suitable for the high-throughput screening of novel ARGs from environmental metagenomes.