Toward a Universal Unit for Quantification of Antibiotic Resistance Genes in Environmental Samples

Ranking the risk of antibiotic resistance genes by metagenomic and multifactorial analysis in hospital wastewater systems

Antimicrobial resistance poses a serious threat to human health. Hospital wastewater system (HWS) is an important source of antibiotic resistance genes (ARGs). The risk of ARGs in HWS is still an under-researched area. In this study, we collected publicly metagenomic datasets of 71 hospital wastewater samples from 18 hospitals in 13 cities. A total of 9838 contigs were identified to carry 383 unique ARGs across all samples, of which 2946 contigs were plasmid-like sequences. Concurrently, the primary hosts of ARGs within HWS were found to be Escherichia coli and Klebsiella pneumoniae. To further evaluate the risk of each ARG subtype, we proposed a risk assessment framework based on the importance of corresponding antibiotics as defined by the WHO and three other indicators - ARG abundance (A), mobility (M), and host pathogenicity (P). Ninety ARGs were identified as R1 ARGs having high-risk scores, which meant having a high abundance, high mobility, and carried by pathogens in HWS. Furthermore, 25% to 49% of genomes from critically important pathogens accessed from NCBI carried R1 ARGs. A significantly higher number of R1 ARGs was carried by pathogens in the effluents of municipal wastewater treatment plants from NCBI, highlighting the role of R1 ARGS in accelerating health and environmental risks.

Spatiotemporal Changes of Antibiotic Resistance, Potential Pathogens, and Health Risk in Kindergarten Dust

The microorganisms present in kindergartens are extremely important for children's health during their three-year preschool education. To assess the risk of outdoor dust in kindergartens, the antibiotic resistome and potential pathogens were investigated in dust samples collected from 59 kindergartens in Xiamen, southeast China in both the winter and summer. Both high-throughput quantitative PCR and metagenome analysis revealed a higher richness and abundance of antibiotic resistance genes (ARGs) in winter (P < 0.05). Besides, the bloom of ARGs and potential pathogens was evident in the urban kindergartens. The co-occurrence patterns among ARGs, mobile genetic elements (MGEs), and potential pathogens suggested some bacterial pathogens were potential hosts of ARGs and MGEs. We found a large number of high-risk ARGs in the dust; the richness and abundance of high-risk ARGs were higher in winter and urban kindergartens compared to in summer and peri-urban kindergartens, respectively. The results of the co-occurrence patterns and high-risk ARGs jointly reveal that urbanization will significantly increase the threat of urban dust to human beings and their risks will be higher in winter. This study unveils the close association between ARGs/mobile ARGs and potential pathogens and emphasizes that we should pay more attention to the health risks induced by their combination.

Integrating global microbiome data into antibiotic resistance assessment in large rivers

Rivers are important in spreading antimicrobial resistance (AMR). Assessing AMR risk in large rivers is challenged by large spatial scale and numerous contamination sources. Integrating river resistome data into a global framework may help addressing this difficulty. Here, we conducted an omics-based assessment of AMR in a large river (i.e. the Pearl River in China) with global microbiome data. Results showed that antibiotic resistome in river water and sediment was more diversified than that in other rivers, with contamination levels in some river reaches higher than global baselines. Discharge of WWTP effluent and landfill waste drove AMR prevalence in the river, and the resistome level was highly associated with human and animal sources. Detection of 54 risk rank I ARGs and emerging mobilizable mcr and tet(X) highlighted AMR risk in the river reaches with high human population density and livestock pollution. Florfenicol-resistant floR therein deserved priority concerns due to its high detection frequency, dissimilar phylogenetic distance, mobilizable potential, and presence in multiple pathogens. Co-sharing of ARGs across taxonomic ranks implied their transfer potentials in the community. By comparing with global genomic data, we found that Burkholderiaceae, Enterobacteriaceae, Moraxellaceae and Pseudomonadaceae were important potential ARG-carrying bacteria in the river, and WHO priority carbapenem-resistant Enterobacteriaceae, A. baumannii and P. aeruginosa should be included in future surveillance. Collectively, the findings from this study provide an omics-benchmarked assessment strategy for public risk associated with AMR in large rivers.

Mechanisms Underlying the Overlooked Chiral Fungicide-Driven Enantioselective Proliferation of Antibiotic Resistance in Earthworm Intestinal Microbiome

From a "One Health" perspective, the global threat of antibiotic resistance genes (ARGs) is associated with modern agriculture practices including agrochemicals application. Chiral fungicides account for a considerable proportion of wildly used agrochemicals; however, whether and how their enantiomers lead to differential proliferation of antibiotic resistance in agricultural environments remain overlooked. Focused on the soil-earthworm ecosystem, we for the first time deciphered the mechanisms underlying the enantioselective proliferation of antibiotic resistance driven by the enantiomers of a typical chiral fungicide mandipropamid (i.e., R-MDP and S-MDP) utilizing a multiomic approach. Time-series metagenomic analysis revealed that R-MDP led to a significant enhancement of ARGs with potential mobility (particularly the plasmid-borne ARGs) in the earthworm intestinal microbiome. We further demonstrated that R-MDP induced a concentration-dependent facilitation of plasmid-mediated ARG transfer among microbes. In addition, transcriptomic analysis with verification identified the key aspects involved, where R-MDP enhanced cell membrane permeability, transfer ability, biofilm formation and quorum sensing, rebalanced energy production, and decreased cell mobility versus S-MDP. Overall, the findings provide novel insights into the enantioselective disruption of microbiome and resistome in earthworm gut by chiral fungicides and offer significant contributions to the comprehensive risk assessment of chiral agrochemicals in agroecosystems.

D-Ring Modifications of Tetracyclines Determine Their Ability to Induce Resistance Genes in the Environment

The widespread utilization of tetracyclines (TCs) in agriculture and medicine has led to the borderless spread of tetracycline resistance in humans, animals, and the environment, posing huge risks to both the ecosystem and human society. Changes in the functional group modifications resulted in a higher bacteriostatic efficacy of the new generation of TCs, but their effect on the emergence and evolution of antibiotic resistance genes (ARGs) is not yet known. To this end, four TCs from three generations were chosen to compare their structural effects on influencing the evolution of ARGs in soil microbial communities. The findings revealed that low-generation TCs, such as tetracycline and oxytetracycline, exhibited a greater propensity to stimulate the production and proliferation of ARGs than did high-generation tigecycline. Molecular docking analysis demonstrated that modifications of the D-ring functional group determined the binding capacity of TCs to the substrate-binding pocket of transcriptional regulators and efflux pumps mainly involved in drug resistance. This can be further evidenced by reverse transcription-quantitative polymerase chain reaction quantification and intracellular antibiotic accumulation assessment. This study sheds light on the mechanism of the structural effect of antibiotic-induced ARG production from the perspective of compound-protein binding, therefore providing theoretical support for controlling the dissemination of antibiotic resistance.

Combating antibiotic resistance using wastewater surveillance: Significance, applications, challenges, and future directions

The global increase of antibiotic resistance (AR) and resistant infections call for effective surveillance methods for understanding and mitigating (re)-emerging public health risks. Wastewater surveillance (WS) of antibiotic resistance is an emerging, but currently under-utilized decision-support tool in public health systems. Recent years have witnessed an increase in evidence linking antibiotic resistance in wastewaters to that of the community. To date, very few comprehensive reviews exist on the application of WS to understand AR and resistant infections in population. Current and emerging AR detection methods, and their merits and limitations are discussed. Wastewater surveillance has several merits relative to individual testing, including; (1) low per capita testing cost, (2) high spatial coverage, (3) low requirement for diagnostic equipment, and (4) detection of health threats ahead of real outbreaks. The applications of WS as an early warning system and decision support tool to understand and mitigate AR are discussed. Wastewater surveillance could be a tool of choice in low-income settings lacking resources and diagnostic facilities for individual testing. To demonstrate the utility of WS, empirical evidence from field case studies is presented. However, constraints still exist, including; (1) lack of standardized protocols, (2) the clinical utility and sensitivity of WS-based data, (3) uncertainties in relating WS data to pathogenic and virulent bacteria, and (4) whether or not AR in stools and ultimately wastewater represent the complete human resistome. Finally, further prospects are presented, include knowledge gaps on; (1) development of low-cost biosensors for AR, (2) development of WS protocols (sampling, processing, interpretation), (3) further pilot scale studies to understand the opportunities and limits of WS, and (4) development of computer-based analytical tools to facilitate rapid data collection, visualization and interpretation. Therefore, the present paper discusses the principles, opportunities, and constraints of wastewater surveillance applications to understand AR and safeguard public health.

What is the functional reach of wastewater surveillance for respiratory viruses, pathogenic viruses of concern, and bacterial antibiotic resistance genes of interest?

BACKGROUND

Despite a clear appreciation of the impact of human pathogens on community health, efforts to understand pathogen dynamics within populations often follow a narrow-targeted approach and rely on the deployment of specific molecular probes for quantitative detection or rely on clinical detection and reporting.

MAIN TEXT

Genomic analysis of wastewater samples for the broad detection of viruses, bacteria, fungi, and antibiotic resistance genes of interest/concern is inherently difficult, and while deep sequencing of wastewater provides a wealth of information, a robust and cooperative foundation is needed to support healthier communities. In addition to furthering the capacity of high-throughput sequencing wastewater-based epidemiology to detect human pathogens in an unbiased and agnostic manner, it is critical that collaborative networks among public health agencies, researchers, and community stakeholders be fostered to prepare communities for future public health emergencies or for the next pandemic. A more inclusive public health infrastructure must be built for better data reporting where there is a global human health risk burden.

CONCLUSIONS

As wastewater platforms continue to be developed and refined, high-throughput sequencing of human pathogens in wastewater samples will emerge as a gold standard for understanding community health.

Comparison of concentration and extraction workflows for qPCR quantification of intI1 and vanA in untreated wastewater

Quantitative polymerase chain reaction (qPCR) measurement of antibiotic resistance genes (ARGs) in untreated municipal wastewater may prove useful in combating the antimicrobial resistance crisis. However, harmonizing and optimizing qPCR-based workflows is essential to facilitate comparisons across studies, and includes achieving highly-effective ARG capture through efficient concentration and extraction procedures. In the current study, combinations of sample volume, membrane types and DNA extraction kits within filtration and centrifugation-based workflows were used to quantify 16S ribosomal RNA (16S rRNA), class 1 integron-integrase gene (intI1) and an ARG encoding resistance to vancomycin (vanA) in untreated wastewater sampled from three wastewater treatment plants (WWTPs). Highly abundant 16S rRNA and intI1 were detected in 100 % of samples from all three WWTPs using both 2 and 20 mL sample volumes, while lower prevalence vanA was only detected when using the 20 mL volume. When filtering 2 mL of wastewater, workflows with 0.20-/0.40-μm polycarbonate (PC) membranes generally yielded greater concentrations of the three targets than workflows with 0.22-/0.45-μm mixed cellulose ester (MCE) membranes. The improved performance was diminished when the sample volume was increased to 20 mL. Consistently greater concentrations of 16S rRNA, intI1 and vanA were yielded by filtration-based workflows using PC membranes combined with a DNeasy PowerWater (DPW) Kit, regardless of the sample volume used, and centrifugation-based workflows with DNeasy Blood & Tissue Kit for 2-mL wastewater extractions. Within the filtration-based workflows, the DPW kit yielded more detection and quantifiable results for less abundant vanA than the DNeasy PowerSoil Pro Kit and FastDNA™ SPIN Kit for Soil. These findings indicate that the performance of qPCR-based workflows for surveillance of ARGs in wastewater varies across targets, sample volumes, concentration methods and extraction kits. Workflows must be carefully considered and validated considering the target ARGs to be monitored.

Key taxa and mobilome-mediated responses co-reshape the soil antibiotic resistome under dazomet fumigation stress

Agrochemicals are emergingly being implicated in the widespread dissemination of antibiotic resistance genes (ARGs) in agroecosystems. However, minimal research exists on the disturbance of fumigant on soil ARGs. Focusing on a typical fumigant dazomet in a simulated soil microcosm, we characterized the dazomet-triggered timely response and longstanding dynamic of ARGs at one-fold and two-fold field recommended doses using metagenome and quantitative PCR. Dazomet treatments reduced 13.17%-69.98% of absolute abundance of 16S rRNA gene and targeted ARGs, but, awfully, boosted diversity and relative abundance of ARGs up to 1.33-1.60 and 1.62-1.90 folds, respectively. Approximately 77.28% of changes in relative abundance of ARGs could be explained by bacterial community and mobile genetic elements (MGEs). Mechanistically, primary hosts of ARGs shifted from Proteobacteria (control) to Firmicutes and Actinobacteria (treatments) accompanied with corresponding changes in their abundance by combining community analysis, host tracking analysis and antibiotic resistant bacteria assay. Meanwhile, dazomet exposure significantly increased the incidence of MGEs and stimulated the conjugation of antibiotic-resistant plasmid. In addition, absolute abundance of targeted ARGs gradually recovered in the post-fumigation stage. Collectively, our results elucidate the dazomet-triggered emergence and spread of soil ARGs and highlight the importance of navigating toward rational use of fumigant in agricultural fields.

Candidate biomarkers of antibiotic resistance for the monitoring of wastewater and the downstream environment

Urban wastewater treatment plants (UWTPs) are essential for reducing the pollutants load and protecting water bodies. However, wastewater catchment areas and UWTPs emit continuously antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs), with recognized impacts on the downstream environments. Recently, the European Commission recommended to monitor antibiotic resistance in UWTPs serving more than 100 000 population equivalents. Antibiotic resistance monitoring in environmental samples can be challenging. The expected complexity of these systems can jeopardize the interpretation capacity regarding, for instance, wastewater treatment efficiency, impacts of environmental contamination, or risks due to human exposure. Simplified monitoring frameworks will be essential for the successful implementation of analytical procedures, data analysis, and data sharing. This study aimed to test a set of biomarkers representative of ARG contamination, selected based on their frequent human association and, simultaneously, rare presence in pristine environments. In addition to the 16S rRNA gene, ten potential biomarkers (intI1, sul1, ermB, ermF, aph(3'')-Ib, qacEΔ1, uidA, mefC, tetX, and crAssphage) were monitored in DNA extracts (n = 116) from raw wastewater, activated sludge, treated wastewater, and surface water (upstream and downstream of UWTPs) samples collected in the Czech Republic, Denmark, Israel, the Netherlands, and Portugal. Each biomarker was sensitive enough to measure decreases (on average by up to 2.5 log-units gene copy/mL) from raw wastewater to surface water, with variations in the same order of magnitude as for the 16S rRNA gene. The use of the 10 biomarkers allowed the typing of water samples whose origin or quality could be predicted in a blind test. The results show that, based on appropriate biomarkers, qPCR can be used for a cost-effective and technically accessible approach to monitoring wastewater and the downstream environment.

Occurrence and Removal of Antibiotic Resistance in Nationwide Hospital Wastewater Deciphered by Metagenomics Approach - China, 2018-2022

What is already known about this topic?

Hospital wastewater represents a significant conduit for the dissemination of antibiotic resistance genes (ARGs), including those that are of clinical importance. Yet, the variation in antibiotic resistance on a national level, which can be influenced by regional differences, has not been thoroughly elucidated.

What is added by this report?

Uniform methodologies were employed to analyze data from various provincial-level administrative divisions in China, aiming to investigate the patterns of antibiotic resistance across these regions. This analysis illuminated the location preferences of clinically ARGs on plasmids. Additionally, our study uncovered regional variations in the presumed bacterial hosts of ARGs at the genus level.

What are the implications for public health practice?

This investigation has shed light on the nationwide prevalence of ARGs in hospital wastewater in China, uncovering the significant ecological and public health risks associated with the disposal of such effluents.