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

Decrypting the viral community in aerobic activated sludge reactors treating antibiotic production wastewater

Viruses are the most abundant yet understudied members that may influence microbial metabolism in activated sludge treating antibiotic production wastewater. This study comprehensively investigated virome community characteristics under the selection pressure of nine types and different concentrations of antibiotics using a metagenomics approach. Of the 15,514 total viral operational taxonomic units (tOTUs) recovered, only 37.5 % were annotated. Antibiotics altered the original viral community structure in activated sludge. The proportion of some pathogenic viral families, including Herpesviridae_like, increased significantly in reactors treating erythromycin production wastewater. In total, 16.5 % of the tOTUs were associated with two or more hosts. tOTUs rarely carried antibiotic resistance genes (ARGs), and the ARG types in the tOTUs did not match the ARGs carried by the bacterial hosts. This suggests that transduction contributes little to the horizontal ARG transfer. Auxiliary metabolic genes (AMGs) were prevalent in tOTUs, and those involved in folate biosynthesis were particularly abundant, indicating their potential to mitigate antibiotic-induced host damage. This study provides comprehensive insights into the virome community in activated sludge treating antibiotic production wastewater and sheds light on the potential role of viral AMGs in mitigating antibiotic-induced stress.

Potential of nature-based solutions to reduce antibiotics, antimicrobial resistance, and pathogens in aquatic ecosystems. a critical review

This comprehensive scientific review evaluates the effectiveness of nature-based solutions (NBS) in reducing antibiotics (ABs), combating antimicrobial resistance (AMR), and controlling pathogens in various aquatic environments at different river catchment levels. It covers conventional and innovative treatment wetland configurations for wastewater treatment to reduce pollutant discharge into the aquatic ecosystems as well as exploring how river restoration and saltmarshes can enhance pollutant removal. Through the analysis of experimental studies and case examples, the review shows NBS's potential for providing sustainable and cost-effective solutions to improve the health of aquatic ecosystems. It also evaluates the use of diagnostic indicators to predict NBS effectiveness in removing specific pollutants such as ABs and AMR. The review concludes that NBS are feasible for addressing the new challenges stemming from human activities such as the presence of ABs, AMR and pathogens, contributing to a better understanding of NBS, highlighting success stories, addressing knowledge gaps, and providing recommendations for future research and implementation.

The integration of omics and cultivation-dependent methods could effectively determine the biological risks associated with the utilization of soil conditioners in agriculture

In the circular economy, reusing agricultural residues, treated biowaste, and sewage sludges-commonly referred to as soil conditioners-in agriculture is essential for converting waste into valuable resources. However, these materials can also contribute to the spread of antimicrobial-resistant pathogens in treated soils. In this study, we analyzed different soil conditioners categorized into five groups: compost from source-separated biowaste and green waste, agro-industrial digestate, digestate from anaerobic digestion of source-separated biowaste, compost from biowaste digestate, and sludges from wastewater treatment plants. Under Italian law, only the first two categories are approved for agricultural use, despite Regulation 1009/2019/EU allowing the use of digestate from anaerobic digestion of source-separated biowaste in CE-marked fertilizers. We examined the bacterial community and associated resistome of each sample using metagenomic approaches. Additionally, we detected and isolated various pathogens to provide a comprehensive understanding of the potential risks associated with sludge application in agriculture. The compost samples exhibited higher bacterial diversity and a greater abundance of potentially pathogenic bacteria compared to other samples, except for wastewater treatment plant sludges, which had the highest frequency of Salmonella isolation and resistome diversity. Our findings suggest integrating omics and cultivation-dependent methods to accurately assess the biological risks of using sludge in agriculture.

SiO2 nanoparticles can enhance nitrogen retention and reduce copper resistance genes during aerobic composting of swine manure

SiO2 nanoparticles (SiO2 NPs) are low-cost, environmentally friendly materials with significant potential to remove pollutants from complex environments. In this study, SiO2 NPs were used for the first time as an additive in aerobic composting to enhance nitrogen retention and reduce the expression of copper resistance genes. The addition of 0.5 g kg-1 SiO2 NPs effectively reduced nitrogen loss by 72.33 % by decreasing denitrification genes (nosZ, nirK, and napA) and increasing nitrogen fixation gene (nifH). The dominant factors affecting nitrification and denitrification genes were Firmicutes and C/N ratio. Additionally, SiO2 NPs decreased copper resistance genes by 28.96 % - 37.52 % in compost products. Copper resistance genes decreased most in the treatment with 0.5 g kg-1 SiO2 NPs. In summary, 0.5 g kg-1 SiO2 NPs have the potential to reduce copper resistance genes and enhance nitrogen retention during aerobic composting, which may be used to improve compost quality.

Vertical variation of antibiotic resistance genes and their interaction with environmental nutrients in sediments of Taihu lake

Antibiotic resistance is a growing environmental issue. As a sink for antibiotic resistance genes (ARGs), lake surface sediments are well known for the spread of ARGs. However, the distribution pattern of ARGs and their relationship with environmental factors in vertical sediment layers are unclear. In this study, we investigated the resistome distribution in sediment cores from Taihu Lake using metagenomic analysis. The results showed that the abundance of total ARGs increased by 153% as the sediment depth rose from 0 to 50 cm, and the ARG Shannon index significantly increased. Among all the ARG types, efflux pump genes (e.g., mexT and mexW) were dominant, especially in 40-50 cm sediment. The variation in ARG with depth described above was related to the changes in bacterial adaptation to environmental gradients. Specifically, sulfate and nitrate concentrations decreased with depth, and random forest analysis showed that they were the main factors affecting the changes in ARG abundance. Environmental factors were also found to indirectly impact the distribution of ARGs by affecting the bacterial community. Potential sulfate-reducing gene/nitrate-reducing gene-ARG co-hosts were annotated through metagenomic assembly. The dominant co-hosts, Curvibacter, and Comamonas, which were enriched in deeper sediments, may have contributed to the enrichment of ARGs in deep sediments. Overall, our findings demonstrated that bacterial-mediated sulfate and nitrate reduction was closely related to sediment resistance, which provided new insights into the control of antibiotic resistance.

Seasonal dynamics of antibiotic resistance genes and mobile genetic elements in a subtropical coastal ecosystem: Implications for environmental health risks

Antibiotic resistance poses a considerable global public health concern, leading to heightened rates of illness and mortality. However, the impact of seasonal variations and environmental factors on the health risks associated with antibiotic resistance genes (ARGs) and their assembly mechanisms is not fully understood. Based on metagenomic sequencing, this study investigated the antibiotic resistome, mobile genetic elements (MGEs), and microbiomes in a subtropical coastal ecosystem of the Beibu Gulf, China, over autumn and winter, and explored the factors influencing seasonal changes in ARG and MGE abundance and diversity. Results indicated that ARG abundance and diversity were higher in winter than in autumn, with beta-lactam and multidrug resistance genes being the most diverse and abundant, respectively. Similarly, MGE abundance and diversity increased in winter and were strongly correlated with ARGs. In contrast, more pronounced associations between microbial communities, especially archaea, and the antibiotic resistome were observed in autumn than in winter. The co-occurrence network identified multiple interactions between MGEs and various multidrug efflux pumps in winter, suggesting a potential for ARG dissemination. Multivariate correlation analyses and path modeling indicated that environmental factors driving microbial community changes predominantly influenced antibiotic resistome assembly in autumn, while the relative importance of MGEs increased significantly in winter. These findings suggest an elevated health risk associated with antimicrobial resistance in the Beibu Gulf during winter, attributed to the dissemination of ARGs by horizontal gene transfer. The observed seasonal variations highlight the dynamic nature of antibiotic resistance dissemination in coastal ecosystems, emphasizing the need for comprehensive surveillance and management measures to address the growing threat of antimicrobial resistance in vulnerable environments.

A rapid approach with machine learning for quantifying the relative burden of antimicrobial resistance in natural aquatic environments

The massive use and discharge of antibiotics have led to increasing concerns about antimicrobial resistance (AMR) in natural aquatic environments. Since the dose-response mechanisms of pathogens with AMR have not yet been fully understood, and the antibiotic resistance genes and bacteria-related data collection via field sampling and laboratory testing is time-consuming and expensive, designing a rapid approach to quantify the burden of AMR in the natural aquatic environment has become a challenge. To cope with such a challenge, a new approach involving an integrated machine-learning framework was developed by investigating the associations between the relative burden of AMR and easily accessible variables (i.e., relevant environmental variables and adjacent land-use patterns). The results, based on a real-world case analysis, demonstrate that the quantification speed has been reduced from 3-7 days, which is typical for traditional measurement procedures with field sampling and laboratory testing, to approximately 0.5 hours using the new approach. Moreover, all five metrics for AMR relative burden quantification exceed the threshold level of 85%, with F1-score surpassing 0.92. Compared to logistic regression, decision trees, and basic random forest, the adaptive random forest model within the framework significantly improves quantification accuracy without sacrificing model interpretability. Two environmental variables, dissolved oxygen and resistivity, along with the proportion of green areas were identified as three key feature variables for the rapid quantification. This study contributes to the enrichment of burden analyses and management practices for rapid quantification of the relative burden of AMR without dose-response information.

Biochar and theaflavins mitigate the antibiotic resistome and antibiotic-resistant pathogens in a soil-lettuce continuum

Antibiotic resistance can be transferred into the food chain, leading to increased risks to human health from ready-to-eat vegetables. Mitigating the transmission of antibiotic resistance from soil to vegetables by green materials is of great significance. Here, we deciphered the roles of biochar and theaflavins in mitigating antibiotic resistance genes (ARGs) and antibiotic-resistant pathogens (ARPs) in a soil-lettuce continuum. Metagenomic results showed that biochar led to a significant decrease in the abundance of ARGs in lettuce leaves, while theaflavins contributed to a significant reduction in the diversity and abundance of ARGs in soil, particularly targeting dominant ARG types such as sulfonamide and aminoglycoside resistance genes. Meanwhile, biochar and theaflavins alleviated the potential mobility of ARGs, in lettuce leaves and soil, respectively, including the spread of ARGs to human pathogens. In addition, the diversity of ARG hosts was reduced in the soil-lettuce continuum and ARPs were not detected in lettuce leaves after the application of biochar or theaflavins. Overall, this study provides a novel perspective on green materials for mitigating the antibiotic resistome and ARPs in the soil-lettuce continuum, contributing to food security and human health.

Melon: metagenomic long-read-based taxonomic identification and quantification using marker genes

Long-read sequencing holds great potential for characterizing complex microbial communities, yet taxonomic profiling tools designed specifically for long reads remain lacking. We introduce Melon, a novel marker-based taxonomic profiler that capitalizes on the unique attributes of long reads. Melon employs a two-stage classification scheme to reduce computational time and is equipped with an expectation-maximization-based post-correction module to handle ambiguous reads. Melon achieves superior performance compared to existing tools in both mock and simulated samples. Using wastewater metagenomic samples, we demonstrate the applicability of Melon by showing it provides reliable estimates of overall genome copies, and species-level taxonomic profiles.

Mechanisms linking triclocarban biotransformation to functional response and antimicrobial resistome evolution in wastewater treatment systems

Evaluating the role of antimicrobials biotransformation in the regulation of metabolic functions and antimicrobial resistance evolution in wastewater biotreatment systems is crucial to ensuring water security. However, the associated mechanisms remain poorly understood. Here, we investigate triclocarban (TCC, one of the typical antimicrobials) biotransformation mechanisms and the dynamic evolution of systemic function disturbance and antimicrobial resistance risk in a complex anaerobic hydrolytic acidification (HA)-anoxic (ANO)/oxic (O) process. We mined key functional genes involved in the TCC upstream (reductive dechlorination and amide bonds hydrolysis) and downstream (chloroanilines catabolism) biotransformation pathways by metagenomic sequencing. Acute and chronic stress of TCC inhibit the production of volatile fatty acids (VFAs), NH4+ assimilation, and nitrification. The biotransformation of TCC via a single pathway cannot effectively relieve the inhibition of metabolic functions (e.g., carbon and nitrogen transformation and cycling) and enrichment of antimicrobial resistance genes (ARGs). Importantly, the coexistence of TCC reductive dechlorination and hydrolysis pathways and subsequent ring-opening catabolism play a critical role for stabilization of systemic metabolic functions and partial control of antimicrobial resistance risk. This study provides new insights into the mechanisms linking TCC biotransformation to the dynamic evolution of systemic functions and risks, and highlights critical regulatory information for enhanced control of TCC risks in complex biotreatment systems.

Metagenomic insights into ecological risk of antibiotic resistome and mobilome in riverine plastisphere under impact of urbanization

Microplastics (MPs) are of increasing concern due to their role as reservoirs for antibiotic resistance genes (ARGs) and pathogens. To date, few studies have explored the influence of anthropogenic activities on ARGs and mobile genetic elements (MGEs) within various riverine MPs, in comparison to their natural counterparts. Here an in-situ incubation was conducted along heavily anthropogenically-impacted Houxi River to characterize the geographical pattern of antibiotic resistome, mobilome and pathogens inhabiting MPs- and leaf-biofilms. The metagenomics result showed a clear urbanization-driven profile in the distribution of ARGs, MGEs and pathogens, with their abundances sharply increasing 4.77 to 19.90 times from sparsely to densely populated regions. The significant correlation between human fecal marker crAssphage and ARG (R2 = 0.67, P=0.003) indicated the influence of anthropogenic activity on ARG proliferation in plastisphere and natural leaf surfaces. And mantel tests and random forest analysis revealed the impact of 17 socio-environmental factors, e.g., population density, antibiotic concentrations, and pore volume of materials, on the dissemination of ARGs. Partial least squares-path modeling further unveiled that intensifying human activities not only directly boosted ARGs abundance but also exerted a comparable indirect impact on ARGs propagation. Furthermore, the polyvinylchloride plastisphere created a pathogen-friendly habitat, harboring higher abundances of ARGs and MGEs, while polylactic acid are not likely to serve as vectors for pathogens in river, with a lower resistome risk score than that in leaf-biofilms. This study highlights the diverse ecological risks associated with the dissemination of ARGs and pathogens in varied MPs, offering insights for the policymaking of usage and control of plastics within urbanization.

Occurrence and distribution of antibiotic pollution and antibiotic resistance genes in seagrass meadow sediments based on metagenomics

Seagrass meadows are one of the most important coastal ecosystems that provide essential ecological and economic services. The contamination levels of antibiotic and antibiotic resistance genes (ARGs) in coastal ecosystems are severely elevated owing to anthropogenic disturbances, such as terrestrial input, aquaculture effluent, and sewage discharge. However, few studies have focused on the occurrence and distribution of antibiotics and their corresponding ARGs in this habitat. Thus, we investigated the antibiotic and ARGs profiles, microbial communities, and ARG-carrying host bacteria in typical seagrass meadow sediments collected from Swan Lake, Caofeidian shoal harbor, Qingdao Bay, and Sishili Bay in the Bohai Sea and northern Yellow Sea. The total concentrations of 30 detected antibiotics ranged from 99.35 to 478.02 μg/kg, tetracyclines were more prevalent than other antibiotics. Metagenomic analyses showed that 342 ARG subtypes associated with 22 ARG types were identified in the seagrass meadow sediments. Multidrug resistance genes and RanA were the most dominant ARG types and subtypes, respectively. Co-occurrence network analysis revealed that Halioglobus, Zeaxanthinibacter, and Aureitalea may be potential hosts at the genus level, and the relative abundances of these bacteria were higher in Sishili Bay than those in other areas. This study provided important insights into the pollution status of antibiotics and ARGs in typical seagrass meadow sediments. Effective management should be performed to control the potential ecological health risks in seagrass meadow ecosystems.

Metagenomic Insights into Potential Impacts of Antibacterial Biosynthesis and Anthropogenic Activity on Nationwide Soil Resistome

The presence of antibiotic resistance genes (ARGs) in soils has received extensive attention regarding its impacts on environmental, animal, and human systems under One Health. However, the health risks of soil ARGs and microbial determinants of soil resistomes remain poorly understood. Here, a nationwide metagenomic investigation of ARGs in cropland and forest soils in China was conducted. The findings indicated that the abundance and richness of high-risk (i.e., mobilizable, pathogen-carriable and clinically relevant) ARGs in cropland soils were 25.7 times and 8.4 times higher, respectively, compared to those identified in forest soils, suggesting the contribution of agricultural practices to the elevated risk level of soil resistomes. The biosynthetic potential of antibacterials best explained the total ARG abundance (Mantel's r = 0.52, p < 0.001) when compared with environmental variables and anthropogenic disturbance. Both microbial producers' self-resistance and antagonistic interactions contributed to the ARG abundance, of which self-resistance ARGs account for 14.1 %- 35.1 % in abundance. With the increased biosynthetic potential of antibacterials, the antagonistic interactions within the microbial community were greatly enhanced, leading to a significant increase in ARG abundance. Overall, these findings advance our understanding of the emergence and dissemination of soil ARGs and provide critical implications for the risk control of soil resistomes.

Metagenomic approach revealed the mobility and co-occurrence of antibiotic resistomes between non-intensive aquaculture environment and human

BACKGROUND

Aquaculture is an important food source worldwide. The extensive use of antibiotics in intensive large-scale farms has resulted in resistance development. Non-intensive aquaculture is another aquatic feeding model that is conducive to ecological protection and closely related to the natural environment. However, the transmission of resistomes in non-intensive aquaculture has not been well characterized. Moreover, the influence of aquaculture resistomes on human health needs to be further understood. Here, metagenomic approach was employed to identify the mobility of aquaculture resistomes and estimate the potential risks to human health.

RESULTS

The results demonstrated that antibiotic resistance genes (ARGs) were widely present in non-intensive aquaculture systems and the multidrug type was most abundant accounting for 34%. ARGs of non-intensive aquaculture environments were mainly shaped by microbial communities accounting for 51%. Seventy-seven genera and 36 mobile genetic elements (MGEs) were significantly associated with 23 ARG types (p < 0.05) according to network analysis. Six ARGs were defined as core ARGs (top 3% most abundant with occurrence frequency > 80%) which occupied 40% of ARG abundance in fish gut samples. Seventy-one ARG-carrying contigs were identified and 75% of them carried MGEs simultaneously. The qacEdelta1 and sul1 formed a stable combination and were detected simultaneously in aquaculture environments and humans. Additionally, 475 high-quality metagenomic-assembled genomes (MAGs) were recovered and 81 MAGs carried ARGs. The multidrug and bacitracin resistance genes were the most abundant ARG types carried by MAGs. Strikingly, Fusobacterium_A (opportunistic human pathogen) carrying ARGs and MGEs were identified in both the aquaculture system and human guts, which indicated the potential risks of ARG transfer.

CONCLUSIONS

The mobility and pathogenicity of aquaculture resistomes were explored by a metagenomic approach. Given the observed co-occurrence of resistomes between the aquaculture environment and human, more stringent regulation of resistomes in non-intensive aquaculture systems may be required. Video Abstract.

Filling the Knowledge Gap Regarding Microbial Occupational Exposure Assessment in Waste Water Treatment Plants: A Scoping Review

BACKGROUND

Wastewater treatment plants (WWTPs) are crucial in the scope of European Commission circular economy implementation. However, bioaerosol production may be a hazard for occupational and public health. A scoping review regarding microbial contamination exposure assessment in WWTPs was performed.

METHODS

This study was performed through PRISMA methodology in PubMed, Scopus and Web of Science.

RESULTS

28 papers were selected for data extraction. The WWTPs' most common sampled sites are the aeration tank (42.86%), sludge dewatering basin (21.43%) and grit chamber. Air sampling is the preferred sampling technique and culture-based methods were the most frequently employed assays. Staphylococcus sp. (21.43%), Bacillus sp. (7.14%), Clostridium sp. (3.57%), Escherichia sp. (7.14%) and Legionella sp. (3.57%) were the most isolated bacteria and Aspergillus sp. (17.86%), Cladosporium sp. (10.71%) and Alternaria sp. (10.71%) dominated the fungal presence.

CONCLUSIONS

This study allowed the identification of the following needs: (a) common protocol from the field (sampling campaign) to the lab (assays to employ); (b) standardized contextual information to be retrieved allowing a proper risk control and management; (c) the selection of the most suitable microbial targets to serve as indicators of harmful microbial exposure. Filling these gaps with further studies will help to provide robust science to policy makers and stakeholders.

Discovery of sulfonamide resistance genes in deep groundwater below Patna, India

Global usage of pharmaceuticals has led to the proliferation of bacteria that are resistant to antimicrobial treatments, creating a substantial public health challenge. Here, we investigate the emergence of sulfonamide resistance genes in groundwater and surface water in Patna, a rapidly developing city in Bihar, India. We report the first quantification of three sulfonamide resistance genes (sulI, sulII and sulIII) in groundwater (12-107 m in depth) in India. The mean relative abundance of gene copies was found to be sulI (2.4 × 10-2 copies/16S rRNA gene) > sulII (5.4 × 10-3 copies/16S rRNA gene) > sulIII (2.4 × 10-3 copies/16S rRNA gene) in groundwater (n = 15) and surface water (n = 3). A comparison between antimicrobial resistance (AMR) genes and wastewater indicators, particularly tryptophan:fulvic-like fluorescence, suggests that wastewater was associated with AMR gene prevalence. Urban drainage channels, containing hospital and domestic wastes, are likely a substantial source of antimicrobial resistance in groundwater and surface water, including the Ganges (Ganga) River. This study is a reference point for decision-makers in the fight against antimicrobial resistance because it quantifies and determines potential sources of AMR genes in Indian groundwater.

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.

Roadmap to tackle antibiotic resistance in the environment under the One Health framework

Antibiotic resistance has been recognized as a major challenge worldwide for humans. "One Health" has been recognized as a key concept for containment of antibiotic resistance. Under the framework, the role of the environment in the development of antibiotic resistance genes (ARGs) has become increasingly obvious. Despite numerous efforts, response to antibiotic resistance is considered to be inadequate, which is probably due to the lack of a clear roadmap. Here, we propose a "One Health" roadmap to combat antibiotic resistance in the environment through (1) understanding environmental resistome. The environmental gene pool has long been recognized as the single largest reservoir of both known and novel ARGs. (2) Standardizing ARG quantification. Systematic joint efforts based on standardized quantification are urgently needed to understand the true tempospatial profiles of the environmental resistome. (3) Identifying mechanisms of resistome development. Horizontal gene transfer and co-selection have been recognized as the two main mechanisms contributing to the environmental resistome. (4) Establishing a risk-assessment framework. The first critical step for large-scale cost-effective targeted ARG management in the environment is the risk assessment to identify the priority ARGs for control. (5) Formulating regulatory standards. By correlating the environmental ARG profile with public health, we may identify the indicator ARGs that can be integrated into current environmental quality standards. (6) Developing control strategies. Systematic analysis of available control technologies is required to identify the most feasible ones to curtail the spread of ARGs in the environment. The proposed roadmap under the "One Health" framework provides a guide to tackle antibiotic resistance in the environment.