Recommendations for the use of metagenomics for routine monitoring of antibiotic resistance in wastewater and impacted aquatic environments

Davis, Benjamin C.; Brown, Connor; Gupta, Suraj; Calarco, Jeanette; Liguori, Krista; Milligan, Erin; Harwood, Valerie J.; Pruden, Amy; Keenum, Ishi

doi:10.1080/10643389.2023.2181620

Cited by 12 publications

(7 citation statements)

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“…Such an approach is best applied when there are multiple points of comparison through time and space. Still, if the desire is to obtain deeper ecological insight, then metagenomic measures will provide a more comprehensive picture [ 54 ], but they are more costly and require more specialized expertise. Correspondingly, there has been a convergence of recent efforts to develop tools for classifying environmental metagenomes in terms of their “resistome risk” that take into consideration the total numbers of ARGs, their clinical relevance, their presence on a mobile genetic element, and their likelihood of being carried by or transferred to a pathogen [ 55 , 56 ].…”

Section: Discussionmentioning

confidence: 99%

“…Correspondingly, there has been a convergence of recent efforts to develop tools for classifying environmental metagenomes in terms of their “resistome risk” that take into consideration the total numbers of ARGs, their clinical relevance, their presence on a mobile genetic element, and their likelihood of being carried by or transferred to a pathogen [ 55 , 56 ]. Such metagenomic analytical tools similarly use denominators such as annotated 16S rRNA genes or numbers of sequencing reads [ 54 ].…”

Section: Discussionmentioning

confidence: 99%

“…There are efforts to advance metagenomic-based surveillance of AMR in wastewater, which would provide the advantage of simultaneous non-targeted detection of ARGs, mobile genetic elements, and pathogens [ 5 , 58 , 61 ]. There is a substantial trade-off in terms of the cost of metagenomics; however, even with the deepest sequencing, the detection limit will be on the order of 2-log higher than that of qPCR [ 54 ].…”

Section: Discussionmentioning

confidence: 99%

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Comparison of Cefotaxime-Resistant Escherichia coli and sul1 and intI1 by qPCR for Monitoring of Antibiotic Resistance of Wastewater, Surface Water, and Recycled Water

Liguori,

Calarco,

Maldonado Rivera

et al. 2023

Antibiotics

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Awareness of the need for surveillance of antimicrobial resistance (AMR) in water environments is growing, but there is uncertainty regarding appropriate monitoring targets. Adapting culture-based fecal indicator monitoring to include antibiotics in the media provides a potentially low-tech and accessible option, while quantitative polymerase chain reaction (qPCR) targeting key genes of interest provides a broad, quantitative measure across the microbial community. The purpose of this study was to compare findings obtained from the culture of cefotaxime-resistant (cefR) Escherichia coli with two qPCR methods for quantification of antibiotic resistance genes across wastewater, recycled water, and surface waters. The culture method was a modification of US EPA Method 1603 for E. coli, in which cefotaxime is included in the medium to capture cefR strains, while qPCR methods quantified sul1 and intI1. A common standard operating procedure for each target was applied to samples collected by six water utilities across the United States and processed by two laboratories. The methods performed consistently, and all three measures reflected the same overarching trends across water types. The qPCR detection of sul1 yielded the widest dynamic range of measurement as an AMR indicator (7-log versus 3.5-log for cefR E. coli), while intI1 was the most frequently detected target (99% versus 96.5% and 50.8% for sul1 and cefR E. coli, respectively). All methods produced comparable measurements between labs (p < 0.05, Kruskal–Wallis). Further study is needed to consider how relevant each measure is to capturing hot spots for the evolution and dissemination of AMR in the environment and as indicators of AMR-associated human health risk.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Comparison of Cefotaxime-Resistant Escherichia coli and sul1 and intI1 by qPCR for Monitoring of Antibiotic Resistance of Wastewater, Surface Water, and Recycled Water

Liguori,

Calarco,

Maldonado Rivera

et al. 2023

Antibiotics

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“…In small datasets with low-frequency outcomes, a collapsing method limits bias resulting from such amplification of positives. Finally, many studies of AMR and virulence genes from environmental samples exclusively use molecular methods, making it difficult to tell what bacteria are carrying the genes and whether the bacteria are viable [43]. One advantage of this study is that all tested bacteria were originally isolated by culture.…”

Section: Discussionmentioning

confidence: 99%

Relating Antimicrobial Resistance and Virulence in Surface-Water E. coli

LaMontagne,

Christenson,

Rogers

et al. 2023

Microorganisms

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The role of the environment in the emergence and spread of antimicrobial resistance (AMR) is being increasingly recognized, raising questions about the public health risks associated with environmental AMR. Yet, little is known about pathogenicity among resistant bacteria in environmental systems. Existing studies on the association between AMR and virulence are contradictory, as fitness costs and genetic co-occurrence can be opposing influences. Using Escherichia coli isolated from surface waters in eastern North Carolina, we compared virulence gene prevalence between isolates resistant and susceptible to antibiotics. We also compared the prevalence of isolates from sub-watersheds with or without commercial hog operations (CHOs). Isolates that had previously been evaluated for phenotypic AMR were paired by matching isolates resistant to any tested antibiotic with fully susceptible isolates from the same sample date and site, forming 87 pairs. These 174 isolates were evaluated by conventional PCR for seven virulence genes (bfp, fimH, cnf-1, STa (estA), EAST-1 (astA), eae, and hlyA). One gene, fimH, was found in 93.1% of isolates. Excluding fimH, at least one virulence gene was detected in 24.7% of isolates. Significant negative associations were found between resistance to at least one antibiotic and presence of at least one virulence gene, tetracycline resistance and presence of a virulence gene, resistance and STa presence, and tetracycline resistance and STa presence. No significant associations were found between CHO presence and virulence, though some sub-significant associations merit further study. This work builds our understanding of factors controlling AMR dissemination through the environment and potential health risks.

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“…Contemporary environmental metagenomic data sets typically consist of a number of short read sequence files, typically generated by Illumina sequencing producing files ranging in size up to 100 Gbp (Gigabase pairs) ( Davis et al, 2023 ), each representing either a Processing such datasets requires significant computational analysis. This typically needs to be organized in a bioinformatics pipeline that consists of selected software tools, which are mutually connected custom scripts.…”

Section: Introductionmentioning

confidence: 99%

ARGem: a new metagenomics pipeline for antibiotic resistance genes: metadata, analysis, and visualization

Liang,

Zhang,

Kim

et al. 2023

Front. Genet.

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Antibiotic resistance is of crucial interest to both human and animal medicine. It has been recognized that increased environmental monitoring of antibiotic resistance is needed. Metagenomic DNA sequencing is becoming an attractive method to profile antibiotic resistance genes (ARGs), including a special focus on pathogens. A number of computational pipelines are available and under development to support environmental ARG monitoring; the pipeline we present here is promising for general adoption for the purpose of harmonized global monitoring. Specifically, ARGem is a user-friendly pipeline that provides full-service analysis, from the initial DNA short reads to the final visualization of results. The capture of extensive metadata is also facilitated to support comparability across projects and broader monitoring goals. The ARGem pipeline offers efficient analysis of a modest number of samples along with affordable computational components, though the throughput could be increased through cloud resources, based on the user’s configuration. The pipeline components were carefully assessed and selected to satisfy tradeoffs, balancing efficiency and flexibility. It was essential to provide a step to perform short read assembly in a reasonable time frame to ensure accurate annotation of identified ARGs. Comprehensive ARG and mobile genetic element databases are included in ARGem for annotation support. ARGem further includes an expandable set of analysis tools that include statistical and network analysis and supports various useful visualization techniques, including Cytoscape visualization of co-occurrence and correlation networks. The performance and flexibility of the ARGem pipeline is demonstrated with analysis of aquatic metagenomes. The pipeline is freely available at https://github.com/xlxlxlx/ARGem.

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Recommendations for the use of metagenomics for routine monitoring of antibiotic resistance in wastewater and impacted aquatic environments

Cited by 12 publications

References 130 publications

Comparison of Cefotaxime-Resistant Escherichia coli and sul1 and intI1 by qPCR for Monitoring of Antibiotic Resistance of Wastewater, Surface Water, and Recycled Water

Comparison of Cefotaxime-Resistant Escherichia coli and sul1 and intI1 by qPCR for Monitoring of Antibiotic Resistance of Wastewater, Surface Water, and Recycled Water

Relating Antimicrobial Resistance and Virulence in Surface-Water E. coli

ARGem: a new metagenomics pipeline for antibiotic resistance genes: metadata, analysis, and visualization

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