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Abstract While numerous environmental factors contribute to the spread of antibiotic resistance genes (ARGs), quantifying their relative contributions remains a fundamental challenge. Similarly, it is important to differentiate acute human health risks from environmental exposure, versus broader ecological risk of ARG evolution and spread across microbial taxa. Recent studies have proposed various methods for achieving such aims. Here, we introduce MetaCompare 2.0, which improves upon original MetaCompare pipeline by differentiating indicators of human health resistome risk (potential for human pathogens of acute resistance concern to acquire ARGs) from ecological resistome risk (overall mobility of ARGs and potential for pathogen acquisition). The updated pipeline's sensitivity was demonstrated by analyzing diverse publicly-available metagenomes from wastewater, surface water, soil, sediment, human gut, and synthetic microbial communities. MetaCompare 2.0 provided distinct rankings of the metagenomes according to both human health resistome risk and ecological resistome risk, with both scores trending higher when influenced by anthropogenic impact or other stress. We evaluated the robustness of the pipeline to sequence assembly methods, sequencing depth, contig count, and metagenomic library coverage bias. The risk scores were remarkably consistent despite variations in these technological aspects. We packaged the improved pipeline into a publicly-available web service (http://metacompare.cs.vt.edu/) that provides an easy-to-use interface for computing resistome risk scores and visualizing results. 

Abstract BackgroundWhile there is increasing recognition of numerous environmental contributions to the spread of antibiotic resistance, quantifying the relative contributions of various sources remains a fundamental challenge. Similarly, there is a need to differentiate acute human health risks corresponding to exposure to a given environment, versus broader ecological risk of evolution and spread of antibiotic resistance genes (ARGs) across microbial taxa. Recent studies have proposed various methods of harnessing the rich information housed by metagenomic data for achieving such aims. Here, we introduce MetaCompare 2.0, which improves upon the original MetaCompare pipeline by differentiating indicators of human health resistome risk (i.e., potential for human pathogens to acquire ARGs) from ecological resistome risk (i.e., overall mobility of ARGs across a given microbiome). ResultsTo demonstrate the sensitivity of the MetaCompare 2.0 pipeline, we analyzed publicly available metagenomes representing a broad array of environments, including wastewater, surface water, soil, sediment, and human gut. We also assessed the effect of sequence assembly methods on the risk scores. We further evaluated the robustness of the pipeline to sequencing depth, contig count, and metagenomic library coverage bias through comparative analysis of a range of subsamples extracted from a set of deeply sequenced wastewater metagenomes. The analysis utilizing samples from different environments demonstrated that MetaCompare 2.0 consistently produces lower risk scores for environments with little human influence and higher risk scores for human contaminated environments affected by pollution or other stressors. We found that the ranks of risk scores were not measurably affected by different assemblers employed. The Meta-Compare 2.0 risk scores were remarkably consistent despite varying sequencing depth, contig count, and coverage. ConclusionMetaCompare 2.0 successfully ranked a wide array of environments according to both human health and ecological resistome risks, with both scores being strongly impacted by anthropogenic stress. We packaged the improved pipeline into a publicly-available web service that provides an easy-to-use interface for computing resistome risk scores and visualizing results. The web service is available athttp://metacompare.cs.vt.edu/ 

ABSTRACT Escherichia coliis a promising subject for globally coordinated surveillance of antimicrobial resistance (AMR) in water environments due to its clinical relevance and widespread use as an indicator of fecal contamination. Cefotaxime-resistantE. coliwas recently evaluated favorably for this purpose by the World Health Organization TriCycle Protocol, which specifies tryptone bile x-glucuronide (TBX) medium and incubation at 35°C. We assessed comparability with the U.S. Environmental Protection Agency-approved method forE. coliquantification, which uses membrane-thermotolerantE. coli(mTEC) agar and incubation at 44.5°C, in terms of recovery ofE. coliand cefotaxime-resistantE. colifrom wastewater influent and surface waters. TotalE. coliconcentrations in wastewater influent were 10⁶–10⁸CFU/100 mL, while cefotaxime-resistantE. coliwere ~100-fold lower. TotalE. coliin surface waters were ~10²CFU/100 mL, and cefotaxime-resistant isolates were near the limit of detection (0.4 CFU/100 mL). Total and putative cefotaxime-resistantE. coliconcentrations did not differ significantly between media or by incubation method; however, colonies isolated on mTEC were more frequently confirmed to species (97.1%) compared to those from TBX (92.5%). Incubation in a water bath at 44.5°C significantly decreased non-specific background growth and improved confirmation frequency on both media (97.4%) compared to incubation at 35°C (92.3%). This study helps to advance globally coordinated AMR in water environments and suggests that the TriCycle Protocol is adaptable to other standard methods that may be required in different locales, while also offering a means to improve specificity by decreasing the frequency of false-positive identification of cefotaxime-resistantE. coliby modifying incubation conditions.IMPORTANCEAs antibiotic-resistant bacteria in water environments are increasingly recognized as contributors to the global antibiotic resistance crisis, the need for a monitoring subject that captures antibiotic resistance trends on a global scale increases. The World Health Organization TriCycle Protocol proposes the use of cefotaxime-resistantEscherichia coliisolated on tryptone bile x-glucuronide agar. The U.S. Environmental Protection Agency (USEPA) criteria for safe recreational waters also useE. colias an indicator but specify the use of mTEC agar at a higher incubation temperature (44.5°C vs 35°C). We assessed the comparability of these methods for isolating total and cefotaxime-resistantE. coli, finding overall good agreement and performance, but significantly higher specificity towardE. coliselection with the use of the USEPA incubation protocol and mTEC agar. This study is the first to directly compare these methods and provides evidence that the methods may be used interchangeably for global surveillance of antibiotic resistance in the environment. 

Abstract Activated sludge is the centerpiece of biological wastewater treatment, as it facilitates removal of sewage-associated pollutants, fecal bacteria, and pathogens from wastewater through semi-controlled microbial ecology. It has been hypothesized that horizontal gene transfer facilitates the spread of antibiotic resistance genes within the wastewater treatment plant, in part because of the presence of residual antibiotics in sewage. However, there has been surprisingly little evidence to suggest that sewage-associated antibiotics select for resistance at wastewater treatment plants via horizontal gene transfer or otherwise. We addressed the role of sewage-associated antibiotics in promoting antibiotic resistance using lab-scale sequencing batch reactors fed field-collected wastewater, metagenomic sequencing, and our recently developed bioinformatic tool Kairos. Here, we found confirmatory evidence that fluctuating levels of antibiotics in sewage are associated with horizontal gene transfer of antibiotic resistance genes, microbial ecology, and microdiversity-level differences in resistance gene fate in activated sludge. 

Abstract Purpose of ReviewMounting 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 FindingsRecent 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. SummaryThe 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. 

Abstract Polar regions are relatively isolated from human activity and thus could offer insight into anthropogenic and ecological drivers of the spread of antibiotic resistance. Plasmids are of particular interest in this context given the central role that they are thought to play in the dissemination of antibiotic resistance genes (ARGs). However, plasmidomes are challenging to profile in environmental samples. The objective of this study was to compare various aspects of the plasmidome associated with glacial ice and adjacent aquatic environments across the high Arctic archipelago of Svalbard, representing a gradient of anthropogenic inputs and specific treated and untreated wastewater outflows to the sea. We accessed plasmidomes by applying enrichment cultures, plasmid isolation and shotgun Illumina sequencing of environmental samples. We examined the abundance and diversity of ARGs and other stress‐response genes that might be co/cross‐selected or co‐transported in these environments, including biocide resistance genes (BRGs), metal resistance genes (MRGs), virulence genes (VGs) and integrons. We found striking differences between glacial ice and aquatic environments in terms of the ARGs carried by plasmids. We found a strong correlation between MRGs and ARGs in plasmids in the wastewaters and fjords. Alternatively, in glacial ice, VGs and BRGs genes were dominant, suggesting that glacial ice may be a repository of pathogenic strains. Moreover, ARGs were not found within the cassettes of integrons carried by the plasmids, which is suggestive of unique adaptive features of the microbial communities to their extreme environment. This study provides insight into the role of plasmids in facilitating bacterial adaptation to Arctic ecosystems as well as in shaping corresponding resistomes. Increasing human activity, warming of Arctic regions and associated increases in the meltwater run‐off from glaciers could contribute to the release and spread of plasmid‐related genes from Svalbard to the broader pool of ARGs in the Arctic Ocean. 

Antibiotic resistance (AR) presents a global health challenge, necessitating an improved understanding of the ecology, evolution, and dissemination of antibiotic resistance genes (ARGs). Several tools, databases, and algorithms are now available to facilitate the identification of ARGs in metagenomic sequencing data; however, direct annotation of short-read data provides limited contextual information. Knowledge of whether an ARG is carried in the chromosome or on a specific mobile genetic element (MGE) is critical to understanding mobility, persistence, and potential for co-selection. Here we developed ARGContextProfiler, a pipeline designed to extract and visualize ARG genomic contexts. By leveraging the assembly graph for genomic neighborhood extraction and validating contexts through read mapping, ARGContextProfiler minimizes chimeric errors that are a common artifact of assembly outputs. Testing on real, synthetic, and semi-synthetic data, including long-read sequencing data from environmental samples, demonstrated that ARGContextProfiler offers superior accuracy, precision, and sensitivity compared to conventional assembly-based methods. ARGContextProfiler thus provides a powerful tool for uncovering the genomic context of ARGs in metagenomic sequencing data, which can be of value to both fundamental and applied research aimed at understanding and stemming the spread of AR. The source code of ARGContextProfiler is publicly available atGitHub.