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HT-ARGfinder: A Comprehensive Pipeline for Identifying Horizontally Transferred Antibiotic Resistance Genes and Directionality in Metagenomic Sequencing Data
Title: HT-ARGfinder: A Comprehensive Pipeline for Identifying Horizontally Transferred Antibiotic Resistance Genes and Directionality in Metagenomic Sequencing Data
Antibiotic resistance is a continually rising threat to global health. A primary driver of the evolution of new strains of resistant pathogens is the horizontal gene transfer (HGT) of antibiotic resistance genes (ARGs). However, identifying and quantifying ARGs subject to HGT remains a significant challenge. Here, we introduce HT-ARGfinder (horizontally transferred ARG finder), a pipeline that detects and enumerates horizontally transferred ARGs in metagenomic data while also estimating the directionality of transfer. To demonstrate the pipeline, we applied it to an array of publicly-available wastewater metagenomes, including hospital sewage. We compare the horizontally transferred ARGs detected across various sample types and estimate their directionality of transfer among donors and recipients. This study introduces a comprehensive tool to track mobile ARGs in wastewater and other aquatic environments. more »« less
WWTPs have been regarded as an important hot spot of ARGs. The discharge point of WWTP effluent, where ARGs may be horizontally transferred from bacteria of treated wastewater to bacteria of receiving water, is an important interface between the human-dominated ecosystem and the natural environment.
Majeed, Haniyyah J.; Riquelme, Maria V.; Davis, Benjamin C.; Gupta, Suraj; Angeles, Luisa; Aga, Diana S.; Garner, Emily; Pruden, Amy; Vikesland, Peter J.(
, Frontiers in Microbiology)
null
(Ed.)
Wastewater treatment plants (WWTPs) receive a confluence of sewage containing antimicrobials, antibiotic resistant bacteria, antibiotic resistance genes (ARGs), and pathogens and thus are a key point of interest for antibiotic resistance surveillance. WWTP monitoring has the potential to inform with respect to the antibiotic resistance status of the community served as well as the potential for ARGs to escape treatment. However, there is lack of agreement regarding suitable sampling frequencies and monitoring targets to facilitate comparison within and among individual WWTPs. The objective of this study was to comprehensively evaluate patterns in metagenomic-derived indicators of antibiotic resistance through various stages of treatment at a conventional WWTP for the purpose of informing local monitoring approaches that are also informative for global comparison. Relative abundance of total ARGs decreased by ∼50% from the influent to the effluent, with each sampling location defined by a unique resistome (i.e., total ARG) composition. However, 90% of the ARGs found in the effluent were also detected in the influent, while the effluent ARG-pathogen taxonomic linkage patterns identified in assembled metagenomes were more similar to patterns in regional clinical surveillance data than the patterns identified in the influent. Analysis of core and discriminatory resistomes and general ARG trends across the eight sampling events (i.e., tendency to be removed, increase, decrease, or be found in the effluent only), along with quantification of ARGs of clinical concern, aided in identifying candidate ARGs for surveillance. Relative resistome risk characterization further provided a comprehensive metric for predicting the relative mobility of ARGs and likelihood of being carried in pathogens and can help to prioritize where to focus future monitoring and mitigation. Most antibiotics that were subject to regional resistance testing were also found in the WWTP, with the total antibiotic load decreasing by ∼40–50%, but no strong correlations were found between antibiotics and corresponding ARGs. Overall, this study provides insight into how metagenomic data can be collected and analyzed for surveillance of antibiotic resistance at WWTPs, suggesting that effluent is a beneficial monitoring point with relevance both to the local clinical condition and for assessing efficacy of wastewater treatment in reducing risk of disseminating antibiotic resistance.
Al-Faliti, Mitham; Wang, Phillip; Smith, Adam L; Delgado_Vela, Jeseth(
, Water Research)
Phage emit communication signals that inform their lytic and lysogenic life cycles. However, little is known regarding the abundance and diversity of the genes associated with phage communication systems in wastewater treatment microbial communities. This study focused on phage communities within two distinct biochemical wastewater environments, specifically aerobic membrane bioreactors (AeMBRs) and anaerobic membrane bioreactors (AnMBRs) exposed to varying antibiotic concentrations. Metagenomic data from the bench-scale systems were analyzed to explore phage phylogeny, life cycles, and genetic capacity for antimicrobial resistance and quorum sensing. Two dominant phage families, Schitoviridae and Peduoviridae, exhibited redox-dependent dynamics. Schitoviridae prevailed in anaerobic conditions, while Peduoviridae dominated in aerobic conditions. Notably, the abundance of lytic and lysogenic proteins varied across conditions, suggesting the coexistence of both life cycles. Furthermore, the presence of antibiotic resistance genes (ARGs) within viral contigs highlighted the potential for phage to transfer ARGs in AeMBRs. Finally, quorum sensing genes in the virome of AeMBRs indicated possible molecular signaling between phage and bacteria. Overall, this study provides insights into the dynamics of viral communities across varied redox conditions in MBRs. These findings shed light on phage life cycles, and auxiliary genetic capacity such as antibiotic resistance and bacterial quorum sensing within wastewater treatment microbial communities.
With growing calls for increased surveillance of antibiotic resistance as an escalating global health threat, improved bioinformatic tools are needed for tracking antibiotic resistance genes (ARGs) across One Health domains. Most studies to date profile ARGs using sequence homology, but such approaches provide limited information about the broader context or function of the ARG in bacterial genomes. Here we introduce a new pipeline for identifying ARGs in genomic data that employs machine learning analysis of Protein-Protein Interaction Networks (PPINs) as a means to improve predictions of ARGs while also providing vital information about the context, such as gene mobility. A random forest model was trained to effectively differentiate between ARGs and nonARGs and was validated using the PPINs of ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, andEnterobacter cloacae), which represent urgent threats to human health because they tend to be multi-antibiotic resistant. The pipeline exhibited robustness in discriminating ARGs from nonARGs, achieving an average area under the precision-recall curve of 88%. We further identified that the neighbors of ARGs, i.e., genes connected to ARGs by only one edge, were disproportionately associated with mobile genetic elements, which is consistent with the understanding that ARGs tend to be mobile compared to randomly sampled genes in the PPINs. This pipeline showcases the utility of PPINs in discerning distinctive characteristics of ARGs within a broader genomic context and in differentiating ARGs from nonARGs through network-based attributes and interaction patterns. The code for running the pipeline is publicly available athttps://github.com/NazifaMoumi/PPI-ARG-ESKAPE
Milligan, Erin G.; Calarco, Jeanette; Davis, Benjamin C.; Keenum, Ishi M.; Liguori, Krista; Pruden, Amy; Harwood, Valerie J.(
, Current Environmental Health Reports)
AbstractPurpose of Review
Mounting evidence indicates that habitats such as wastewater and environmental waters are pathways for the spread of antibiotic-resistant bacteria (ARB) and mobile antibiotic resistance genes (ARGs). We identified antibiotic-resistant members of the generaAcinetobacter,Aeromonas, andPseudomonasas key opportunistic pathogens that grow or persist in built (e.g., wastewater) or natural aquatic environments. Effective methods for monitoring these ARB in the environment are needed to understand their influence on dissemination of ARB and ARGs, but standard methods have not been developed. This systematic review considers peer-reviewed papers where the ARB above were cultured from wastewater or surface water, focusing on the accuracy of current methodologies.
Recent Findings
Recent studies suggest that many clinically important ARGs were originally acquired from environmental microorganisms.Acinetobacter,Aeromonas,andPseudomonasspecies are of interest because their ability to persist and grow in the environment provides opportunities to engage in horizontal gene transfer with other environmental bacteria. Pathogenic strains of these organisms resistant to multiple, clinically relevant drug classes have been identified as an urgent threat. However, culture methods for these bacteria were generally developed for clinical samples and are not well-vetted for environmental samples.
Summary
The search criteria yielded 60 peer-reviewed articles over the past 20 years, which reported a wide variety of methods for isolation, confirmation, and antibiotic resistance assays. Based on a systematic comparison of the reported methods, we suggest a path forward for standardizing methodologies for monitoring antibiotic resistant strains of these bacteria in water environments.
@article{osti_10336989,
place = {Country unknown/Code not available},
title = {HT-ARGfinder: A Comprehensive Pipeline for Identifying Horizontally Transferred Antibiotic Resistance Genes and Directionality in Metagenomic Sequencing Data},
url = {https://par.nsf.gov/biblio/10336989},
DOI = {10.3389/fenvs.2022.901917},
abstractNote = {Antibiotic resistance is a continually rising threat to global health. A primary driver of the evolution of new strains of resistant pathogens is the horizontal gene transfer (HGT) of antibiotic resistance genes (ARGs). However, identifying and quantifying ARGs subject to HGT remains a significant challenge. Here, we introduce HT-ARGfinder (horizontally transferred ARG finder), a pipeline that detects and enumerates horizontally transferred ARGs in metagenomic data while also estimating the directionality of transfer. To demonstrate the pipeline, we applied it to an array of publicly-available wastewater metagenomes, including hospital sewage. We compare the horizontally transferred ARGs detected across various sample types and estimate their directionality of transfer among donors and recipients. This study introduces a comprehensive tool to track mobile ARGs in wastewater and other aquatic environments.},
journal = {Frontiers in Environmental Science},
volume = {10},
author = {Das, Badhan and Emon, Muhit Islam and Moumi, Nazifa Ahmed and Sein, Justin and Pruden, Amy and Heath, Lenwood S. and Zhang, Liqing},
}
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