Global diversity and commonality of the antimicrobial resistome in activated sludge in wastewater treatment plants

Global diversity and commonality of the antimicrobial resistome in activated sludge in wastewater treatment plants | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Global diversity and commonality of the antimicrobial resistome in activated sludge in wastewater treatment plants Ryo Honda, Muhammad Sabar, Yuta Morinaga, Taichi Kani, Norihisa MATSUURA, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6210263/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Activated sludge in wastewater treatment plants (WWTPs) is a significant source and reservoir of antimicrobial resistance (AMR), potentially emanating from the human-associated sources into the environment through wastewater treatment effluent and biosolid applications. This study aimed to explore the global diversity and determinants of AMR within activated sludge. Metagenomic analysis of 181 samples from WWTPs in the USA, Europe, Japan, and China revealed a globally conserved set of antimicrobial resistance genes (ARGs) in activated sludge, distinct from those in wastewater. Notably, specific ARGs, such as AAC(6’)-Ib7 , sul1 , and qacEdelta1 were more abundant in activated sludge than in wastewater, suggesting that the selective growth of aerobic bacteria harboring these ARGs drives resistome formation. Furthermore, some ARGs associated with clinically important antimicrobials persisted from influent wastewater independent of microbial population dynamics. A strong correlation between ARG and mobile genetic element (MGE) abundances underscored the potential for ARG mobility within activated sludge. Biological sciences/Microbiology/Environmental microbiology/Water microbiology Biological sciences/Microbiology/Antimicrobials/Antimicrobial resistance Antibiotic resistance gene (ARG) mobile genetic element (MGE) wastewater treatment plant (WWTP) metagenomics One Health interfaces Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 INTRODUCTION Antimicrobial resistance (AMR) poses a significant global public health challenge, recognized by the World Health Organization (WHO) as one of the top 10 global threats, with substantial repercussions on public health 1 . The scarcity of new antimicrobial developments, coupled with prolonged illness from the ineffectiveness of last-resort antibiotics, is projected to result in serious health burdens in the coming decades 2,3 . AMR was associated with an estimated 4.95 million deaths globally in 2019 4 , with projections suggesting up to 10 million deaths annually by 2050 5 . Given its widespread prevalence in human, animal, and environmental domains, adopting the "One Health" approach, which seeks to balance and optimize the health of people, animals, and the environment, is imperative. 6,7 . In the environmental domain, wastewater is a crucial conduit for the dissemination of AMR from human sources into the environment. While wastewater treatment plants (WWTPs) act as defensive barriers against AMR spread, they can also act as a reservoir, retaining AMR within activated sludge and potentially discharging it into the environment via treated effluent 8-10 and application to agricultural land 11,12 . Since influent wastewater reflects the gut microbiome of the population, WWTPs become hubs for a diverse array of antimicrobial resistance genes (ARGs) originating from human sources 13,14 . Recent global research has highlighted the diversity of antimicrobial resistome in wastewater, linking it to the socioeconomic, health, and environmental factors of various countries 15-17 . Moreover, WWTPs offer a conducive environment for the selection and enrichment of ARGs, facilitated by bacterial exposure to residue pharmaceuticals, heavy metals, disinfectants, and reactive oxygen species within activated sludge 18,19 . Mobile genetic elements (MGEs) further facilitate the enrichment of AMR in activated sludge through the horizontal gene transfer (HGT) of the ARGs 20 . Beyond the diversity of the resistome in influent wastewater, the variability in selective pressure across WWTPs would lead to diverse resistome in activated sludge across different locations and countries. Despite its significance as an environmental reservoir of AMR, the global diversity and determinants of antimicrobial resistome within activated sludge remains underexplored, even though it plays crucial role in dispersing ARGs through WWTP effluent and its application to agricultural land. The objective of this study is to clarify the diversity and commonality of the antimicrobial resistome in activated sludge on a continental scale, aiming to illuminate the determinants of resistome variation. We collected metagenomic data from activated sludge samples at various sites across the USA, Europe, China, and Japan (Figure 1a) and analyzed to identify a core resistome commonly abundant across continents, as well as ARGs that are locally abundant in each country. Additionally, we investigated the associations between ARGs, MGEs, and microbial communities to uncover potential key drivers behind the selection and enrichment of ARGs in activated sludge. Our findings highlight the critical role of activated sludge as a key environmental reservoir of AMR on a global scale. RESULTS Total ARG abundance and presence of core ARGs Activated sludge consistently exhibited lower and less variable total ARG abundance compared to influent wastewater across countries. Average total ARG abundances per 16S bacterial population were 0.11±0.007 in activated sludge and 0.28±0.01 in influent wastewater (Fig. 1b). Total ARG abundances in activated sludges were homogeneous in Europe, the eastern USA, and Japan in winter, while they exhibited a larger variance in the western USA, Japan in summer, and China. In contrast, ARG abundance in wastewater was highly variable in European countries, the USA, and China, compared to Japan (Fig. 1b). Among all 660 ARGs detected in activated sludge, 25.0% were found commonly in at least one WWTP across all countries (Fig. 1c & 1d). In contrast, a greater number of ARGs were detected in wastewater than in activated sludge across all continents. Among all 892 ARGs detected in wastewater, 31.2% were commonly found in at least one WWTP across all countries (Fig. 1e). These results indicate that activated sludge exhibited relatively less diversity of ARGs, while influent wastewater demonstrated a greater regional variation of the detected ARGs. Furthermore, high commonality of ARG composition across countries was observed in both activated sludge and influent wastewater by the presence of core ARGs, which were commonly abundant across continents. It is noteworthy that a limited number of ARGs were found dominant within each drug class independent of the country (Fig. 2). For example, OXA was commonly found in most activated sludge and wastewater in all countries among ARGs on cephalosporins (Fig. 2a). Similarly, sul1 among sulfonamides and ermF among macrolide, lincosamide and streptogramin (MLS) were found as the core ARGs dominant in both activated sludge and wastewater in all continents (Figs. 2e and 2g). This result indicates that these core ARGs are widespread in wastewater across continents and persistent in activated sludge. Meanwhile, some ARGs exhibited a contrast in their abundance by activated sludge and wastewater. Some of the core ARGs, e.g., sul1 , qacEdelta1 , AAC(6’)-Ib7 , were frequently dominant in activated sludge with significantly higher proportion than in wastewater (Fig. 3), suggesting that these ARGs were enriched in activated sludge, as discussed below. Notably, the limited number of ARGs occupied almost half of the total ARG abundance in activated sludge consistently across all continents studied. Commonly abundant ARGs, such as OXA , aadA6, sul1 , qacEdelta1 , AAC(6’)-Ib7 , constituted an average of 35% (± 6.6% SD) of the total ARG abundance in activated sludge of all countries, while their abundance in wastewater averaged 22% (± 5.5% SD) (Fig. 3; Supplementary Table 2). In activated sludge, sul1 and qacEdelta1 emerge as the most abundant ARGs across most regions. The persistence of sulfonamide resistance genes is reportedly associated with the stability and widespread presence of sulfonamide antibiotics within wastewater treatment 21 , 22 . In addition, qacEdelta1 , as known as ARG on quaternary ammonium compound (QAC), exhibited conspicuous abundance where sul1 is high, reflecting their potential co-selection. The qacEdelta1 variant is dominant in diverse gene cassettes due to ancestral features of class 1 integrons 23 . Gene cassettes carrying sul1 frequently harbor qacEdelta at the 3’ conserved segment and open reading frame 5 of class 1 integron 24 – 26 . Due to their high abundance in various water bodies, sul1 and qacEdelta1 are listed as candidate gene markers of AMR monitoring in aquatic environments 9 , 27 . However, their abundance was quite low in activated sludge in the western USA (Fig. 3). The localization of these gene should be considered when sul1 and qacEdelta1 are applied as ARG monitoring markers. Conversely, the proportions of ermB , tet(Q) , and aadA11 in activated sludge were significantly reduced from those in influent wastewater, suggesting that persistence in wastewater treatment systems depends on the specific ARGs (Fig. 3; Supplementary Table 2). In summary, several core ARGs, including OXA , aadA6, ermF , were commonly abundant among both activated sludge and wastewater across continents, while several ARGs, i.e., sul1 , qacEdelta1 , AAC(6’)-Ib7 , were prevalent only in activated sludge. Particularly within activated sludge, these core ARGs occupied higher dominance than in wastewater, leading to less diversity among countries than in wastewater. Locality of antimicrobial resistome across continents Despite the high abundance of common ARGs, antimicrobial resistome in activated sludge and wastewater also exhibited locality among countries. Principal component analysis (PCA) demonstrated a relative difference in ARG composition between activated sludge and wastewater across continents (Fig. 4a). Activated sludge exhibited positive PC1 scores, characterized by ARGs on the efflux pump ( Mex , Mux , and sme families) with highly positive PC1 loadings (Supplementary Table 3a). Most of these efflux ARGs featuring activated sludge conferred resistance to macrolide, fluoroquinolone, and either aminoglycoside or tetracycline. Additionally, some efflux ARGs (e.g., MexY and MexB ) confer universal resistance to a broad spectrum of antimicrobials and other cell stressors (e.g., heavy metals, toxic trace chemicals, and oxidative stress by aeration), suggesting the occurrence of co-selection of AMR in the wastewater treatment systems 19 , 28 , 29 . On the contrary, wastewater exhibited negative PC1 scores, which are characterized predominantly by ARGs that confer resistance to clinically important drugs including cephamycin, fluoroquinolone, cephalosporin, and macrolide (e.g., TolC , gadX , marA , and Acr and emr families) with highly negative PC1 loadings (Supplementary Table 3b). This relative distinction of antimicrobial resistome between activated sludge and wastewater was consistent with a previous study in Japan 30 . Moreover, continental diversity, which were represented by PC2, among activated sludge was relatively smaller than in wastewater (Fig. 4a). The lower variety of resistome in activated sludge than in untreated wastewater was also observed in local-scale studies 30 – 32 . Overall, activated sludge exhibited less locality of resistome compared to wastewater. Although its resistome partly reflect that in wastewater, the majority of ARG composition in activated sludge was occupied by the commonly abundant core ARGs regardless of the country. In this study, the impacts of process configurations in WWTPs across countries were not clearly elucidated because most of the sequence data acquired from the INSDC databases lacked process information in their metadata. However, process configuration is not likely the primary determinants on resistome in activated sludge, compared to country-scale difference and seasonality. For example, activated sludges in Japan exhibited independent clusters from Europe and varied by season (Fig. 4b), even though they were collected from five WWTPs using different process configurations 30 . In summary, notable uniformity was underscored in the activated sludge resistome, revealing less continental variation compared to untreated wastewater. This emphasizes the persistent integration of specific ARGs within wastewater treatment systems, independent of locality of abundant ARGs in influent wastewater. Associations of ARGs with microbial community and MGEs Several ARG groups were associated with microbes inhabiting different environmental conditions. High correlations were found between the relative abundance of certain ARG groups and specific phylogenetic classes (Fig. 5a). According to the correlation patterns, the microbial community in activated sludge and influent wastewater could be divided into four major microbial groups: (group A) anaerobic bacteria abundant in gut microbiome (including Clostridia , Gammaproteobacteria , Bacilli , Fusobacteriia , and Synergistia ); (group B) anaerobic pathogens and major classes found in mesophilic and thermophilic anaerobic digestion systems (such as Campylobacteria, Bacteroidia, Spirochaetia , Methanomicrobia , Thermotogae , and Thermoanaerobaculia ); (group C) aquatic and soil prokaryotes (including Chloroflexia and Polyangia ); and (group D) aerobic heterotrophs commonly inhabiting activated sludge (including Alphaproteobacteria, Actinobacteria, Verrucomicrobiae, and Oligoflexia ) (Fig. 5b). Importantly, the anaerobic microbial groups A demonstrated high correlations with ARGs associated with clinically important drugs, including cephalosporin, quinolone, tetracycline, macrolide ( EreD , mef family), and aminoglycoside ( AAC(6’) and APH families). These bacterial classes were reportedly abundant in the gut microbiome 33 , 34 and were also found abundant in influent wastewater in this study (Supplementary Fig. 3). Hence, these microbes, which harbored ARGs associated with clinically important drugs, were enriched by exposure to antimicrobials in the human gut and discharged into influent wastewater. In contrast, the aerobic microbial groups C and D exhibited converse patterns, where high correlations were observed with ARGs on multidrug efflux ( Mex, Mux , and sme families) and sulfonamide ( sul1 and sul2 ). Particularly, the microbial group D mainly comprised aerobic heterotrophs abundant in activated sludge 35 . The observed high correlations of these microbial groups with multidrug-efflux genes of the Mex family imply co-selection of AMR by exposure to various cell stresses while they were retained as activated sludge in wastewater treatment systems 19 , 28 , 29 . Among the microbial group B, it is noteworthy that Campylobacteria exhibited remarkably high correlations with several ARGs of clinical concern, including CTX-M , GES , MOX , and VEB on cephalosporins, EreD , mefH , and ErmG on macrolides, QnrS and QnrVC on quinolones, tetE on tetracycline, and AAC(6’) family on aminoglycoside. Campylobacter is known as a food-borne gastrointestinal pathogen, which is often transmitted to humans through the consumption of meat such as poultry 36 . Recently, an increasing trend of AMR, particularly to quinolones and macrolides, among Campylobacter in both swine and human samples has been reported worldwide 37 . The high association of Campylobacter with these ARGs in wastewater was possibly because antimicrobial-resistant Campylobacter enriched by antimicrobial use at livestock farms transferred to the human gut via food consumption, then discharged into wastewater. Consequently, the different patterns of correlations among these microbial groups imply that different traits were conferred, reflecting their fate of exposure to different selective pressures. Importantly, among the core ARGs abundant in activated sludge, sul1 , and AAC(6’)-Ib7 exhibited a high correlation with aerobic heterotrophs, suggesting their collective role in harboring and preserving the core ARGs in activated sludge. MGE is another potential factor of AMR dissemination in wastewater and its treatment systems in addition to selective growth by microbial traits. The abundance of MGE in activated sludge and wastewater exhibited notable variations among different countries. The average total MGE abundance per 16S bacterial population were 1.1±0.07 in sludge and 2.23±0.08 in wastewater (Fig. 6a). Activated sludge consistently exhibited lower and less variable total MGE abundance compared to influent wastewater across all countries, mirroring the patterns observed in total ARG abundance (Fig. 1b). Moreover, the total MGE abundance showed a significantly high correlation with total ARG abundance in both activated sludge and wastewater (Fig. 6b), emphasizing the close association between ARGs and MGEs in wastewater treatment systems. These results underscore the significant influence of MGEs in facilitating ARG dissemination in both activated sludge and influent wastewater regardless of country. Among the 120 MGEs identified across countries, the insertion sequence IS91 and a tnpA were remarkably predominant in both activated sludge and influent wastewater (Supplementary Fig. 2a). The IS91 family is a member of ISCRs which mediates the construction of complex class 1 integrons conferring an array of ARGs 38 and reportedly associated with carbapenemase-resistant genes ( IMP , OXA , NDM ) in plasmids and chromosomes 39 – 41 . On the other hand, an integrase intI1 was also abundantly present in activated sludge at proportions following these MGEs, despite insignificant relative abundance in wastewater. The intI1 is embedded in a class 1 integron, which harbors a gene cassette of various ARGs and facilitates the HGT of ARGs in WWTPs 42 . In this study, both IS91 and intI1 are highly correlated with ARGs on cephalosporins ( IMP ), sulfonamide ( sul1 and sul2 ), aminoglycoside ( aadA family) and multidrug efflux ( sme , Mex , and Mux family) (Supplementary Fig. 2b), suggesting these ARGs were associated by these MGE and potentially mobile among microbiomes. Relatively higher proportions of IS91 and intI1 in activated sludge than in wastewater implies that activated sludge afforded selective conditions for microbes harboring these MGEs. In summary, the observed correlations of total abundance of ARG and MGE suggested the significant role of MGEs in dissemination of ARGs in activated sludge and influent wastewater. Specific MGEs, including intI1 and IS91 , were commonly abundant in activated sludge and wastewater regardless of countries, suggesting inter-continental commonality in their roles in the dissemination of ARGs. DISCUSSION This study illustrated the global diversity and commonality of ARGs in activated sludge from WWTPs across continents. Activated sludge consistently exhibited lower and less variable total ARG abundance compared to influent wastewater. This suggests that the activated sludge in WWTPs serves as a more uniform and stable reservoir of ARGs across different geographical locations. Moreover, several factors shaping the resistome in activated sludge were suggested. The ARG compositions in activated sludge were influenced by locality rather than by the process configurations of WWTPs. The difference in featuring ARGs among countries is partly explained by impacts of influent wastewater, which were influenced by the clinical use of antibiotics in the country. For example, greater prescriptions of lincosamide and tetracycline per population in the USA than in Japan likely resulted in a relatively higher proportion of lincosamide resistance genes in the analyzed wastewater in the USA (Fig. 6c) 43 – 46 . As highlighted in previous studies, wastewater resistome reflected popularly prescribed antimicrobials in clinical settings of the country 15 , 16 , 47 , 48 . Among core ARGs abundant in influent wastewater, OXA and aadA6 were also found in activated sludge as most abundant ARG on each drug class, suggesting their persistence within WWTPs (Figs. 2 and 3). These results demonstrate that clinical use of antimicrobials partly reflects on the locality of resistome in wastewater, thereby activated sludge. In contrast, several ARGs, i.e., AAC(6’)-Ib7 on aminoglycoside and qacEdelta on QAC antiseptics, were found predominantly in activated sludge but less in influent wastewater (Figs. 2 and 3). The prevalence of these core ARGs in activated sludge suggests that these ARGs were enriched and reserved selectively in wastewater treatment systems. Since typical retention time of activated sludge in a wastewater treatment system ranges 3 to 14 days, activated sludge is continuously diluted with wastewater at the dilution rate of 0.07 to 0.33 day − 1 . Hence, abundance of a certain ARG in activated sludge would be equal to that in influent wastewater unless the ARG does not increase their number at a higher rate than the dilution rate of activated sludge. Therefore, higher abundance of these particular ARGs in activated sludge than influent wastewater demonstrated that these ARGs had been multiplied in activated sludge due to some specific mechanisms. Horizontal gene transfer is one of the possible mechanisms to disseminate ARGs in microbial community. However, the estimated multiplying rate by HGT according to past in vitro studies ranges 4.0×10 − 13 to 0.18 day − 1 , which are mostly slower than the dilution rate of activated sludge (Supplementary Table 9) 49 – 54 . Therefore, HGT alone cannot explain the retention of these ARGs in activated sludge. The other mechanism of ARG replication is cell growth of bacteria harboring these ARG. Specific growth rates of sludge microbes are potentially 0.25 to 2.6 day − 1 according to Sozen et al. (1998) 55 by assuming BOD = 5 mg/L in activated sludge. Since the potential growth rate of sludge microbes is substantially higher than the dilution rate of activated sludge and HGT rates, cell growth is more likely to be the primary driver to retain these specific ARGs in activated sludge. HGT would be the major mechanism of ARG dissemination in biofilms and sediments, where bacterial retention time is much longer to allow slow growth. However, contribution of HGT would be relatively smaller in activated sludge with shorter retention time, where a faster replication is required to remain in the system. The correlation analysis of ARGs with microbial communities also supports this hypothesis. The core ARGs prevalent only in activated sludge were highly correlated with abundances of aerobic heterotrophs inhabiting activated sludge (Fig. 5), implying that these ARGs were harbored by these bacteria that grow competitively within the sludge microbiome. The competitive growth is not necessarily caused by exposure to antimicrobials or other cell stressors but can be any growth conditions (e.g. temperature, redox conditions, etc.) that facilitate competition and survival of species harboring ARGs. In a wastewater treatment system, a shift of growth conditions from anaerobic in wastewater to aerobic in activated sludge stimulates the proliferation of aerobic heterotrophs and relative depopulation of anaerobic gut microbiome. If aerobic heterotrophs and anaerobic gut microbiome innately confer different ARGs, the shift of the microbial population would appear as the shift of the antimicrobial resistome, even though other selective pressures (e.g., by antimicrobials) are absent. On the other hand, it is still veiled how these ARGs were initially conferred by bacteria retained in activated sludge. Even with its low frequency, several evidence in this study suggested certain impacts of HGT on antimicrobial resistome of activated sludge. The high correlation between total ARG abundance and MGE abundance was observed in activated sludge, highlighting the essential role of MGEs, i.e., intI1 and IS91 , in facilitating the horizontal gene transfer of ARGs. The high correlations of these ARGs with MGEs of intI1 and IS91 support the historical acquisition of these ARGs by sludge microbes rather than inherent traits, which subsequently increase their population in activated sludge. In conclusion, the cross-continental analysis of antimicrobial resistome revealed that activated sludge serves as an environmental reservoir of the several specific ARGs on macrolide, aminoglycoside, sulfonamide, which are mostly common across countries and more abundant than in wastewater. Association of the resistome with the microbial community and MGEs suggested that activated sludge retains such a unique resistome as a consequence of several mechanisms. The major mechanism of proliferation of the specific ARGs in activated sludge is selective growth of aerobic heterotrophs that innately confer the ARGs incorporated in MGEs. Another major mechanism is that ARGs on clinically important antimicrobials harbored by anaerobic bacteria in influent wastewater inflow and persistently present in wastewater treatment systems independent of microbial population dynamics. Contribution of HGT to enrichment of the core ARGs within activated sludge is estimated low although it may have been associated with the acquisition of the ARGs by bacteria at a certain point in the past. These findings provide a mechanistic understanding of the role of activated sludge as an environmental reservoir, harboring a globally conserved set of ARGs. These insights contribute to a better understanding of dynamics of the AMR dissemination and its effective control strategies from the human domain into the environment, particularly through wastewater treatment effluent and biosolid application. MATERIALS AND METHODS Collection of metagenomic datasets of activated sludge and influent wastewater Metagenomic sequence datasets obtained from WWTPs in various countries were systematically retrieved from sequence read archives (SRAs) of NCBI, ENA, and DDBJ. The selection criteria were as follows: (I) the sample was taken at a full-scale WWTP, (II) sampling was conducted between 2015 and 2019 (III) paired-end sequence data with length 150–200 bp was obtained by Illumina HiSeq or a compatible sequencer system, (IV) sequence data has a sufficient size at least 3.0 Gb, and (IV) metadata contains the location information of the WWTP. The sequence data in Japan were obtained in the previous study 30 . Finally, a total of 57 datasets of activated sludge samples were obtained from the USA (n = 7), Europe (n = 33), China (n = 5), and Japan (n = 12). Additionally, a total of 124 datasets of influent wastewater were obtained from the USA (n = 7), Europe (n = 84), China (n = 23), and Japan (n = 10) (Fig. 1a). Sample information and accession IDs of the sequence datasets are summarized in Supplementary Table 1. Sequence data analysis for ARG and MGE profiles Before resistome and mobilome analysis, quality trimming of the sequence data was performed by removing adapter sequences and low-quality reads using Fastp 0.23.3 56 . Quality-trimmed metagenomic reads were directly used (without matching paired ends) for identifying ARGs by BLASTn against the Comprehensive Antibiotic Resistance Database (CARD) ver. 3.2.6 ( https://card.mcmaster.ca/ ) 57 with the E-value cutoff at 1 × 10 − 5 . The BLAST output was first aggregated to create a raw ARG profile, cataloging ARGs with corresponding read counts in each sample. To mitigate gene length bias in read counts, normalization to reads per kilobase (RPK) was conducted based on the subject sequence length ( slen ) in the CARD database. Aggregation of RPK counts for gene variants into gene groups (e.g. OXA) was performed following the approach outlined by Sabar et al. (2023) 9 . The ARG composition of each sample was determined by the proportion of each ARG, calculated as the ratio of the RPK of each ARG to the total RPK of all ARGs in the sample. The bacterial community in each sample was identified using Kraken2 ver. 2.1.2 58 using the k-mer index from the SILVA 138 database ( https://www.arb-silva.de/documentation/release-138/ ). The classification results were summarized in the relative abundance of each taxon by Bracken 2.8 59 . The read count of the 16S rRNA gene was also normalized as RPK based on the 1,541-bp length of the 16S rRNA gene of E. coli 60 . The total ARG abundance of each sample was computed as the ratio of the total RPK of all ARGs to the RPK of the 16S rRNA gene. For mobile genetic elements (MGEs), merged pair-end reads were identified by BLASTn against the MGE database 61 ( https://github.com/KatariinaParnanen/MobileGeneticElementDatabase ), with an E-value cutoff at 1 × 10 − 5 . The MGE database encompasses 2,706 non-redundant sequences of over 270 gene types, including transposases, plasmids, integrases, insertion elements, and qacEdelta. The BLAST output for each sample was aggregated into an MGE profile in the same manner as the ARG profile. Read counts of the MGEs were normalized as RPK based on the slen of the MGE in the database. The MGE composition of each sample was determined as the proportion of each MGE to the total RPK of all MGEs in a sample. The total abundance of MGEs for each sample was calculated as the ratio of the total RPK of all MGEs to the RPK of the 16S rRNA gene. The entire set of scripts for the bioinformatic workflow has been deposited on GitHub ( https://github.com/ryohonda-hub/END-AMR-Asia ). To exclude the divergence in the sequencing depth among samples, ARGs and MGEs with proportions exceeding the cutoff criterion at 0.01% were included for further analysis. Multivariant analysis The antimicrobial resistome and microbial community in each sample underwent comparative assessment through principal component analysis (PCA) using R version 4.3.2. For ARG composition, PCA was performed on the proportion of ARGs, with scaling to represent their relative changes. For the microbial community, PCA was performed on the relative abundance of each genus with scaling. 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Effects of stress and other environmental factors on horizontal plasmid transfer assessed by direct quantification of discrete transfer events. FEMS microbiology ecology 59, 718–728 (2007). Hutinel, M., Fick, J., Larsson, D. J. & Flach, C.-F. Investigating the effects of municipal and hospital wastewaters on horizontal gene transfer. Environmental Pollution 276, 116733 (2021). Jutkina, J., Rutgersson, C., Flach, C.-F. & Larsson, D. J. An assay for determining minimal concentrations of antibiotics that drive horizontal transfer of resistance. Science of the Total Environment 548, 131–138 (2016). Mishra, S., Klümper, U., Voolaid, V., Berendonk, T. U. & Kneis, D. Simultaneous estimation of parameters governing the vertical and horizontal transfer of antibiotic resistance genes. Science of the Total Environment 798, 149174 (2021). Sözen, S., Çokgör, E. U., Orhon, D. & Henze, M. Respirometric analysis of activated sludge behaviour—II. Heterotrophic growth under aerobic and anoxic conditions. Water research 32, 476–488 (1998). Chen, S., Zhou, Y., Chen, Y. & Gu, J. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics 34, i884-i890 (2018). Jia, B. et al. CARD 2017: expansion and model-centric curation of the comprehensive antibiotic resistance database. Nucleic acids research, gkw1004 (2016). Wood, D. E., Lu, J. & Langmead, B. Improved metagenomic analysis with Kraken 2. Genome biology 20, 1–13 (2019). Lu, J., Breitwieser, F. P., Thielen, P. & Salzberg, S. L. Bracken: estimating species abundance in metagenomics data. PeerJ Computer Science 3, e104 (2017). Brosius, J., Palmer, M. L., Kennedy, P. J. & Noller, H. F. Complete nucleotide sequence of a 16S ribosomal RNA gene from Escherichia coli. Proceedings of the National Academy of Sciences 75, 4801–4805 (1978). Pärnänen, K. et al. Maternal gut and breast milk microbiota affect infant gut antibiotic resistome and mobile genetic elements. Nature Communications 9, 3891 (2018). Additional Declarations There is NO Competing Interest. Supplementary Files Supplementary250312v2.pdf Supplementary Figures and Tables Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6210263","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":477403364,"identity":"c1a2ca86-87e5-4e02-a025-00c3e2ef9314","order_by":0,"name":"Ryo 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11:18:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2034271,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6210263/v1/77aeffc3-f83c-4973-958c-964f3cb6487c.pdf"},{"id":85665021,"identity":"7ef7cb89-e416-41fc-81db-c6e8832a18cf","added_by":"auto","created_at":"2025-06-30 12:38:01","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":12598645,"visible":true,"origin":"","legend":"Supplementary Figures and Tables","description":"","filename":"Supplementary250312v2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6210263/v1/fed1bdcd4e82ac84054ba2b2.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Global diversity and commonality of the antimicrobial resistome in activated sludge in wastewater treatment plants","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eAntimicrobial resistance (AMR) poses a significant global public health challenge, recognized by the World Health Organization (WHO) as one of the top 10 global threats, with substantial repercussions on public health\u0026nbsp;\u003csup\u003e1\u003c/sup\u003e. The scarcity of new antimicrobial developments, coupled with prolonged illness from the ineffectiveness of last-resort antibiotics, is projected to result in serious health burdens in the coming decades \u003csup\u003e2,3\u003c/sup\u003e. AMR was associated with an estimated 4.95 million deaths globally in 2019 \u003csup\u003e4\u003c/sup\u003e, with projections suggesting up to 10 million deaths annually by 2050 \u003csup\u003e5\u003c/sup\u003e. Given its widespread prevalence in human, animal, and environmental domains, adopting the \u0026quot;One Health\u0026quot; approach, which seeks to balance and optimize the health of people, animals, and the environment, is imperative. \u003csup\u003e6,7\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eIn the environmental domain, wastewater is a crucial conduit for the dissemination of AMR from human sources into the environment. While wastewater treatment plants (WWTPs) act as defensive barriers against AMR spread, they can also act as a reservoir, retaining AMR within activated sludge and potentially discharging it into the environment via treated effluent\u0026nbsp;\u003csup\u003e8-10\u003c/sup\u003e and application to agricultural land \u003csup\u003e11,12\u003c/sup\u003e. Since influent wastewater reflects the gut microbiome of the population, WWTPs become hubs for a diverse array of antimicrobial resistance genes (ARGs) originating from human sources \u003csup\u003e13,14\u003c/sup\u003e. Recent global research has highlighted the diversity of antimicrobial resistome in wastewater, linking it to the socioeconomic, health, and environmental factors of various countries \u003csup\u003e15-17\u003c/sup\u003e. Moreover, WWTPs offer a conducive environment for the selection and enrichment of ARGs, facilitated by bacterial exposure to residue pharmaceuticals, heavy metals, disinfectants, and reactive oxygen species within activated sludge \u003csup\u003e18,19\u003c/sup\u003e. Mobile genetic elements (MGEs) further facilitate the enrichment of AMR in activated sludge through the horizontal gene transfer (HGT) of the ARGs \u003csup\u003e20\u003c/sup\u003e. Beyond the diversity of the resistome in influent wastewater, the variability in selective pressure across WWTPs would lead to diverse resistome in activated sludge across different locations and countries. Despite its significance as an environmental reservoir of AMR, the global diversity and determinants of antimicrobial resistome within activated sludge remains underexplored, even though it plays crucial role in dispersing ARGs through WWTP effluent and its application to agricultural land.\u003c/p\u003e\n\u003cp\u003eThe objective of this study is to clarify the diversity and commonality of the antimicrobial resistome in activated sludge on a continental scale, aiming to illuminate the determinants of resistome variation. We collected metagenomic data from activated sludge samples at various sites across the USA, Europe, China, and Japan (Figure 1a) and analyzed to identify a core resistome commonly abundant across continents, as well as ARGs that are locally abundant in each country. Additionally, we investigated the associations between ARGs, MGEs, and microbial communities to uncover potential key drivers behind the selection and enrichment of ARGs in activated sludge. Our findings highlight the critical role of activated sludge as a key environmental reservoir of AMR on a global scale.\u0026nbsp;\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003eTotal ARG abundance and presence of core ARGs\u003c/h2\u003e \u003cp\u003eActivated sludge consistently exhibited lower and less variable total ARG abundance compared to influent wastewater across countries. Average total ARG abundances per 16S bacterial population were 0.11\u0026plusmn;0.007 in activated sludge and 0.28\u0026plusmn;0.01 in influent wastewater (Fig.\u0026nbsp;1b). Total ARG abundances in activated sludges were homogeneous in Europe, the eastern USA, and Japan in winter, while they exhibited a larger variance in the western USA, Japan in summer, and China. In contrast, ARG abundance in wastewater was highly variable in European countries, the USA, and China, compared to Japan (Fig.\u0026nbsp;1b). Among all 660 ARGs detected in activated sludge, 25.0% were found commonly in at least one WWTP across all countries (Fig.\u0026nbsp;1c \u0026amp; 1d). In contrast, a greater number of ARGs were detected in wastewater than in activated sludge across all continents. Among all 892 ARGs detected in wastewater, 31.2% were commonly found in at least one WWTP across all countries (Fig.\u0026nbsp;1e). These results indicate that activated sludge exhibited relatively less diversity of ARGs, while influent wastewater demonstrated a greater regional variation of the detected ARGs.\u003c/p\u003e \u003cp\u003eFurthermore, high commonality of ARG composition across countries was observed in both activated sludge and influent wastewater by the presence of core ARGs, which were commonly abundant across continents. It is noteworthy that a limited number of ARGs were found dominant within each drug class independent of the country (Fig.\u0026nbsp;2). For example, \u003cem\u003eOXA\u003c/em\u003e was commonly found in most activated sludge and wastewater in all countries among ARGs on cephalosporins (Fig.\u0026nbsp;2a). Similarly, \u003cem\u003esul1\u003c/em\u003e among sulfonamides and \u003cem\u003eermF\u003c/em\u003e among macrolide, lincosamide and streptogramin (MLS) were found as the core ARGs dominant in both activated sludge and wastewater in all continents (Figs.\u0026nbsp;2e and 2g). This result indicates that these core ARGs are widespread in wastewater across continents and persistent in activated sludge. Meanwhile, some ARGs exhibited a contrast in their abundance by activated sludge and wastewater. Some of the core ARGs, e.g., \u003cem\u003esul1\u003c/em\u003e, \u003cem\u003eqacEdelta1\u003c/em\u003e, \u003cem\u003eAAC(6\u0026rsquo;)-Ib7\u003c/em\u003e, were frequently dominant in activated sludge with significantly higher proportion than in wastewater (Fig.\u0026nbsp;3), suggesting that these ARGs were enriched in activated sludge, as discussed below. Notably, the limited number of ARGs occupied almost half of the total ARG abundance in activated sludge consistently across all continents studied. Commonly abundant ARGs, such as \u003cem\u003eOXA\u003c/em\u003e, \u003cem\u003eaadA6, sul1\u003c/em\u003e, \u003cem\u003eqacEdelta1\u003c/em\u003e, \u003cem\u003eAAC(6\u0026rsquo;)-Ib7\u003c/em\u003e, constituted an average of 35% (\u0026plusmn; 6.6% SD) of the total ARG abundance in activated sludge of all countries, while their abundance in wastewater averaged 22% (\u0026plusmn; 5.5% SD) (Fig.\u0026nbsp;3; Supplementary Table\u0026nbsp;2). In activated sludge, \u003cem\u003esul1\u003c/em\u003e and \u003cem\u003eqacEdelta1\u003c/em\u003e emerge as the most abundant ARGs across most regions. The persistence of sulfonamide resistance genes is reportedly associated with the stability and widespread presence of sulfonamide antibiotics within wastewater treatment \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. In addition, \u003cem\u003eqacEdelta1\u003c/em\u003e, as known as ARG on quaternary ammonium compound (QAC), exhibited conspicuous abundance where \u003cem\u003esul1\u003c/em\u003e is high, reflecting their potential co-selection. The \u003cem\u003eqacEdelta1\u003c/em\u003e variant is dominant in diverse gene cassettes due to ancestral features of class 1 integrons \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. Gene cassettes carrying \u003cem\u003esul1\u003c/em\u003e frequently harbor \u003cem\u003eqacEdelta\u003c/em\u003e at the 3\u0026rsquo; conserved segment and open reading frame 5 of class 1 integron \u003csup\u003e\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Due to their high abundance in various water bodies, \u003cem\u003esul1\u003c/em\u003e and \u003cem\u003eqacEdelta1\u003c/em\u003e are listed as candidate gene markers of AMR monitoring in aquatic environments \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. However, their abundance was quite low in activated sludge in the western USA (Fig.\u0026nbsp;3). The localization of these gene should be considered when \u003cem\u003esul1\u003c/em\u003e and \u003cem\u003eqacEdelta1\u003c/em\u003e are applied as ARG monitoring markers. Conversely, the proportions of \u003cem\u003eermB\u003c/em\u003e, \u003cem\u003etet(Q)\u003c/em\u003e, and \u003cem\u003eaadA11\u003c/em\u003e in activated sludge were significantly reduced from those in influent wastewater, suggesting that persistence in wastewater treatment systems depends on the specific ARGs (Fig.\u0026nbsp;3; Supplementary Table\u0026nbsp;2). In summary, several core ARGs, including \u003cem\u003eOXA\u003c/em\u003e, \u003cem\u003eaadA6, ermF\u003c/em\u003e, were commonly abundant among both activated sludge and wastewater across continents, while several ARGs, i.e., \u003cem\u003esul1\u003c/em\u003e, \u003cem\u003eqacEdelta1\u003c/em\u003e, \u003cem\u003eAAC(6\u0026rsquo;)-Ib7\u003c/em\u003e, were prevalent only in activated sludge. Particularly within activated sludge, these core ARGs occupied higher dominance than in wastewater, leading to less diversity among countries than in wastewater.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eLocality of antimicrobial resistome across continents\u003c/h2\u003e \u003cp\u003eDespite the high abundance of common ARGs, antimicrobial resistome in activated sludge and wastewater also exhibited locality among countries. Principal component analysis (PCA) demonstrated a relative difference in ARG composition between activated sludge and wastewater across continents (Fig.\u0026nbsp;4a). Activated sludge exhibited positive PC1 scores, characterized by ARGs on the efflux pump (\u003cem\u003eMex\u003c/em\u003e, \u003cem\u003eMux\u003c/em\u003e, and \u003cem\u003esme\u003c/em\u003e families) with highly positive PC1 loadings (Supplementary Table\u0026nbsp;3a). Most of these efflux ARGs featuring activated sludge conferred resistance to macrolide, fluoroquinolone, and either aminoglycoside or tetracycline. Additionally, some efflux ARGs (e.g., \u003cem\u003eMexY\u003c/em\u003e and \u003cem\u003eMexB\u003c/em\u003e) confer universal resistance to a broad spectrum of antimicrobials and other cell stressors (e.g., heavy metals, toxic trace chemicals, and oxidative stress by aeration), suggesting the occurrence of co-selection of AMR in the wastewater treatment systems \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. On the contrary, wastewater exhibited negative PC1 scores, which are characterized predominantly by ARGs that confer resistance to clinically important drugs including cephamycin, fluoroquinolone, cephalosporin, and macrolide (e.g., \u003cem\u003eTolC\u003c/em\u003e, \u003cem\u003egadX\u003c/em\u003e, \u003cem\u003emarA\u003c/em\u003e, and \u003cem\u003eAcr\u003c/em\u003e and \u003cem\u003eemr\u003c/em\u003e families) with highly negative PC1 loadings (Supplementary Table\u0026nbsp;3b). This relative distinction of antimicrobial resistome between activated sludge and wastewater was consistent with a previous study in Japan \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Moreover, continental diversity, which were represented by PC2, among activated sludge was relatively smaller than in wastewater (Fig.\u0026nbsp;4a). The lower variety of resistome in activated sludge than in untreated wastewater was also observed in local-scale studies \u003csup\u003e\u003cspan additionalcitationids=\"CR31\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOverall, activated sludge exhibited less locality of resistome compared to wastewater. Although its resistome partly reflect that in wastewater, the majority of ARG composition in activated sludge was occupied by the commonly abundant core ARGs regardless of the country. In this study, the impacts of process configurations in WWTPs across countries were not clearly elucidated because most of the sequence data acquired from the INSDC databases lacked process information in their metadata. However, process configuration is not likely the primary determinants on resistome in activated sludge, compared to country-scale difference and seasonality. For example, activated sludges in Japan exhibited independent clusters from Europe and varied by season (Fig.\u0026nbsp;4b), even though they were collected from five WWTPs using different process configurations \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. In summary, notable uniformity was underscored in the activated sludge resistome, revealing less continental variation compared to untreated wastewater. This emphasizes the persistent integration of specific ARGs within wastewater treatment systems, independent of locality of abundant ARGs in influent wastewater.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAssociations of ARGs with microbial community and MGEs\u003c/h3\u003e\n\u003cp\u003eSeveral ARG groups were associated with microbes inhabiting different environmental conditions. High correlations were found between the relative abundance of certain ARG groups and specific phylogenetic classes (Fig.\u0026nbsp;5a). According to the correlation patterns, the microbial community in activated sludge and influent wastewater could be divided into four major microbial groups: (group A) anaerobic bacteria abundant in gut microbiome (including \u003cem\u003eClostridia\u003c/em\u003e, \u003cem\u003eGammaproteobacteria\u003c/em\u003e, \u003cem\u003eBacilli\u003c/em\u003e, \u003cem\u003eFusobacteriia\u003c/em\u003e, and \u003cem\u003eSynergistia\u003c/em\u003e); (group B) anaerobic pathogens and major classes found in mesophilic and thermophilic anaerobic digestion systems (such as \u003cem\u003eCampylobacteria, Bacteroidia, Spirochaetia\u003c/em\u003e, \u003cem\u003eMethanomicrobia\u003c/em\u003e, \u003cem\u003eThermotogae\u003c/em\u003e, and \u003cem\u003eThermoanaerobaculia\u003c/em\u003e); (group C) aquatic and soil prokaryotes (including \u003cem\u003eChloroflexia\u003c/em\u003e and \u003cem\u003ePolyangia\u003c/em\u003e); and (group D) aerobic heterotrophs commonly inhabiting activated sludge (including \u003cem\u003eAlphaproteobacteria, Actinobacteria, Verrucomicrobiae, and Oligoflexia\u003c/em\u003e) (Fig.\u0026nbsp;5b). Importantly, the anaerobic microbial groups A demonstrated high correlations with ARGs associated with clinically important drugs, including cephalosporin, quinolone, tetracycline, macrolide (\u003cem\u003eEreD\u003c/em\u003e, \u003cem\u003emef\u003c/em\u003e family), and aminoglycoside (\u003cem\u003eAAC(6\u0026rsquo;)\u003c/em\u003e and \u003cem\u003eAPH\u003c/em\u003e families). These bacterial classes were reportedly abundant in the gut microbiome \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e and were also found abundant in influent wastewater in this study (Supplementary Fig.\u0026nbsp;3). Hence, these microbes, which harbored ARGs associated with clinically important drugs, were enriched by exposure to antimicrobials in the human gut and discharged into influent wastewater. In contrast, the aerobic microbial groups C and D exhibited converse patterns, where high correlations were observed with ARGs on multidrug efflux (\u003cem\u003eMex, Mux\u003c/em\u003e, and \u003cem\u003esme\u003c/em\u003e families) and sulfonamide (\u003cem\u003esul1\u003c/em\u003e and \u003cem\u003esul2\u003c/em\u003e). Particularly, the microbial group D mainly comprised aerobic heterotrophs abundant in activated sludge \u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. The observed high correlations of these microbial groups with multidrug-efflux genes of the \u003cem\u003eMex\u003c/em\u003e family imply co-selection of AMR by exposure to various cell stresses while they were retained as activated sludge in wastewater treatment systems \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAmong the microbial group B, it is noteworthy that \u003cem\u003eCampylobacteria\u003c/em\u003e exhibited remarkably high correlations with several ARGs of clinical concern, including \u003cem\u003eCTX-M\u003c/em\u003e, \u003cem\u003eGES\u003c/em\u003e, \u003cem\u003eMOX\u003c/em\u003e, and \u003cem\u003eVEB\u003c/em\u003e on cephalosporins, \u003cem\u003eEreD\u003c/em\u003e, \u003cem\u003emefH\u003c/em\u003e, and \u003cem\u003eErmG\u003c/em\u003e on macrolides, \u003cem\u003eQnrS\u003c/em\u003e and \u003cem\u003eQnrVC\u003c/em\u003e on quinolones, \u003cem\u003etetE\u003c/em\u003e on tetracycline, and \u003cem\u003eAAC(6\u0026rsquo;) family\u003c/em\u003e on aminoglycoside. \u003cem\u003eCampylobacter\u003c/em\u003e is known as a food-borne gastrointestinal pathogen, which is often transmitted to humans through the consumption of meat such as poultry \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. Recently, an increasing trend of AMR, particularly to quinolones and macrolides, among \u003cem\u003eCampylobacter\u003c/em\u003e in both swine and human samples has been reported worldwide \u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. The high association of \u003cem\u003eCampylobacter\u003c/em\u003e with these ARGs in wastewater was possibly because antimicrobial-resistant \u003cem\u003eCampylobacter\u003c/em\u003e enriched by antimicrobial use at livestock farms transferred to the human gut via food consumption, then discharged into wastewater. Consequently, the different patterns of correlations among these microbial groups imply that different traits were conferred, reflecting their fate of exposure to different selective pressures. Importantly, among the core ARGs abundant in activated sludge, \u003cem\u003esul1\u003c/em\u003e, and \u003cem\u003eAAC(6\u0026rsquo;)-Ib7\u003c/em\u003e exhibited a high correlation with aerobic heterotrophs, suggesting their collective role in harboring and preserving the core ARGs in activated sludge.\u003c/p\u003e \u003cp\u003eMGE is another potential factor of AMR dissemination in wastewater and its treatment systems in addition to selective growth by microbial traits. The abundance of MGE in activated sludge and wastewater exhibited notable variations among different countries. The average total MGE abundance per 16S bacterial population were 1.1\u0026plusmn;0.07 in sludge and 2.23\u0026plusmn;0.08 in wastewater (Fig.\u0026nbsp;6a). Activated sludge consistently exhibited lower and less variable total MGE abundance compared to influent wastewater across all countries, mirroring the patterns observed in total ARG abundance (Fig.\u0026nbsp;1b). Moreover, the total MGE abundance showed a significantly high correlation with total ARG abundance in both activated sludge and wastewater (Fig.\u0026nbsp;6b), emphasizing the close association between ARGs and MGEs in wastewater treatment systems. These results underscore the significant influence of MGEs in facilitating ARG dissemination in both activated sludge and influent wastewater regardless of country. Among the 120 MGEs identified across countries, the insertion sequence \u003cem\u003eIS91\u003c/em\u003e and \u003cem\u003ea tnpA\u003c/em\u003e were remarkably predominant in both activated sludge and influent wastewater (Supplementary Fig.\u0026nbsp;2a). The IS91 family is a member of ISCRs which mediates the construction of complex class 1 integrons conferring an array of ARGs \u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e and reportedly associated with carbapenemase-resistant genes (\u003cem\u003eIMP\u003c/em\u003e, \u003cem\u003eOXA\u003c/em\u003e, \u003cem\u003eNDM\u003c/em\u003e) in plasmids and chromosomes \u003csup\u003e\u003cspan additionalcitationids=\"CR40\" citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. On the other hand, an integrase \u003cem\u003eintI1\u003c/em\u003e was also abundantly present in activated sludge at proportions following these MGEs, despite insignificant relative abundance in wastewater. The \u003cem\u003eintI1\u003c/em\u003e is embedded in a class 1 integron, which harbors a gene cassette of various ARGs and facilitates the HGT of ARGs in WWTPs \u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. In this study, both \u003cem\u003eIS91\u003c/em\u003e and \u003cem\u003eintI1\u003c/em\u003e are highly correlated with ARGs on cephalosporins (\u003cem\u003eIMP\u003c/em\u003e), sulfonamide (\u003cem\u003esul1\u003c/em\u003e and \u003cem\u003esul2\u003c/em\u003e), aminoglycoside (\u003cem\u003eaadA\u003c/em\u003e family) and multidrug efflux (\u003cem\u003esme\u003c/em\u003e, \u003cem\u003eMex\u003c/em\u003e, and \u003cem\u003eMux\u003c/em\u003e family) (Supplementary Fig.\u0026nbsp;2b), suggesting these ARGs were associated by these MGE and potentially mobile among microbiomes. Relatively higher proportions of \u003cem\u003eIS91\u003c/em\u003e and \u003cem\u003eintI1\u003c/em\u003e in activated sludge than in wastewater implies that activated sludge afforded selective conditions for microbes harboring these MGEs. In summary, the observed correlations of total abundance of ARG and MGE suggested the significant role of MGEs in dissemination of ARGs in activated sludge and influent wastewater. Specific MGEs, including \u003cem\u003eintI1\u003c/em\u003e and \u003cem\u003eIS91\u003c/em\u003e, were commonly abundant in activated sludge and wastewater regardless of countries, suggesting inter-continental commonality in their roles in the dissemination of ARGs.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study illustrated the global diversity and commonality of ARGs in activated sludge from WWTPs across continents. Activated sludge consistently exhibited lower and less variable total ARG abundance compared to influent wastewater. This suggests that the activated sludge in WWTPs serves as a more uniform and stable reservoir of ARGs across different geographical locations. Moreover, several factors shaping the resistome in activated sludge were suggested. The ARG compositions in activated sludge were influenced by locality rather than by the process configurations of WWTPs. The difference in featuring ARGs among countries is partly explained by impacts of influent wastewater, which were influenced by the clinical use of antibiotics in the country. For example, greater prescriptions of lincosamide and tetracycline per population in the USA than in Japan likely resulted in a relatively higher proportion of lincosamide resistance genes in the analyzed wastewater in the USA (Fig.\u0026nbsp;6c) \u003csup\u003e\u003cspan additionalcitationids=\"CR44 CR45\" citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. As highlighted in previous studies, wastewater resistome reflected popularly prescribed antimicrobials in clinical settings of the country \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e,\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. Among core ARGs abundant in influent wastewater, \u003cem\u003eOXA\u003c/em\u003e and \u003cem\u003eaadA6\u003c/em\u003e were also found in activated sludge as most abundant ARG on each drug class, suggesting their persistence within WWTPs (Figs.\u0026nbsp;2 and 3). These results demonstrate that clinical use of antimicrobials partly reflects on the locality of resistome in wastewater, thereby activated sludge.\u003c/p\u003e \u003cp\u003eIn contrast, several ARGs, i.e., \u003cem\u003eAAC(6\u0026rsquo;)-Ib7\u003c/em\u003e on aminoglycoside and \u003cem\u003eqacEdelta\u003c/em\u003e on QAC antiseptics, were found predominantly in activated sludge but less in influent wastewater (Figs.\u0026nbsp;2 and 3). The prevalence of these core ARGs in activated sludge suggests that these ARGs were enriched and reserved selectively in wastewater treatment systems. Since typical retention time of activated sludge in a wastewater treatment system ranges 3 to 14 days, activated sludge is continuously diluted with wastewater at the dilution rate of 0.07 to 0.33 day\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Hence, abundance of a certain ARG in activated sludge would be equal to that in influent wastewater unless the ARG does not increase their number at a higher rate than the dilution rate of activated sludge. Therefore, higher abundance of these particular ARGs in activated sludge than influent wastewater demonstrated that these ARGs had been multiplied in activated sludge due to some specific mechanisms. Horizontal gene transfer is one of the possible mechanisms to disseminate ARGs in microbial community. However, the estimated multiplying rate by HGT according to past \u003cem\u003ein vitro\u003c/em\u003e studies ranges 4.0\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;13\u003c/sup\u003e to 0.18 day\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, which are mostly slower than the dilution rate of activated sludge (Supplementary Table\u0026nbsp;9) \u003csup\u003e\u003cspan additionalcitationids=\"CR50 CR51 CR52 CR53\" citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. Therefore, HGT alone cannot explain the retention of these ARGs in activated sludge. The other mechanism of ARG replication is cell growth of bacteria harboring these ARG. Specific growth rates of sludge microbes are potentially 0.25 to 2.6 day\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e according to Sozen et al. (1998) \u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e by assuming BOD\u0026thinsp;=\u0026thinsp;5 mg/L in activated sludge. Since the potential growth rate of sludge microbes is substantially higher than the dilution rate of activated sludge and HGT rates, cell growth is more likely to be the primary driver to retain these specific ARGs in activated sludge. HGT would be the major mechanism of ARG dissemination in biofilms and sediments, where bacterial retention time is much longer to allow slow growth. However, contribution of HGT would be relatively smaller in activated sludge with shorter retention time, where a faster replication is required to remain in the system. The correlation analysis of ARGs with microbial communities also supports this hypothesis. The core ARGs prevalent only in activated sludge were highly correlated with abundances of aerobic heterotrophs inhabiting activated sludge (Fig.\u0026nbsp;5), implying that these ARGs were harbored by these bacteria that grow competitively within the sludge microbiome. The competitive growth is not necessarily caused by exposure to antimicrobials or other cell stressors but can be any growth conditions (e.g. temperature, redox conditions, etc.) that facilitate competition and survival of species harboring ARGs. In a wastewater treatment system, a shift of growth conditions from anaerobic in wastewater to aerobic in activated sludge stimulates the proliferation of aerobic heterotrophs and relative depopulation of anaerobic gut microbiome. If aerobic heterotrophs and anaerobic gut microbiome innately confer different ARGs, the shift of the microbial population would appear as the shift of the antimicrobial resistome, even though other selective pressures (e.g., by antimicrobials) are absent. On the other hand, it is still veiled how these ARGs were initially conferred by bacteria retained in activated sludge. Even with its low frequency, several evidence in this study suggested certain impacts of HGT on antimicrobial resistome of activated sludge. The high correlation between total ARG abundance and MGE abundance was observed in activated sludge, highlighting the essential role of MGEs, i.e., \u003cem\u003eintI1\u003c/em\u003e and \u003cem\u003eIS91\u003c/em\u003e, in facilitating the horizontal gene transfer of ARGs. The high correlations of these ARGs with MGEs of \u003cem\u003eintI1\u003c/em\u003e and \u003cem\u003eIS91\u003c/em\u003e support the historical acquisition of these ARGs by sludge microbes rather than inherent traits, which subsequently increase their population in activated sludge.\u003c/p\u003e \u003cp\u003eIn conclusion, the cross-continental analysis of antimicrobial resistome revealed that activated sludge serves as an environmental reservoir of the several specific ARGs on macrolide, aminoglycoside, sulfonamide, which are mostly common across countries and more abundant than in wastewater. Association of the resistome with the microbial community and MGEs suggested that activated sludge retains such a unique resistome as a consequence of several mechanisms. The major mechanism of proliferation of the specific ARGs in activated sludge is selective growth of aerobic heterotrophs that innately confer the ARGs incorporated in MGEs. Another major mechanism is that ARGs on clinically important antimicrobials harbored by anaerobic bacteria in influent wastewater inflow and persistently present in wastewater treatment systems independent of microbial population dynamics. Contribution of HGT to enrichment of the core ARGs within activated sludge is estimated low although it may have been associated with the acquisition of the ARGs by bacteria at a certain point in the past. These findings provide a mechanistic understanding of the role of activated sludge as an environmental reservoir, harboring a globally conserved set of ARGs. These insights contribute to a better understanding of dynamics of the AMR dissemination and its effective control strategies from the human domain into the environment, particularly through wastewater treatment effluent and biosolid application.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eCollection of metagenomic datasets of activated sludge and influent wastewater\u003c/h2\u003e \u003cp\u003eMetagenomic sequence datasets obtained from WWTPs in various countries were systematically retrieved from sequence read archives (SRAs) of NCBI, ENA, and DDBJ. The selection criteria were as follows: (I) the sample was taken at a full-scale WWTP, (II) sampling was conducted between 2015 and 2019 (III) paired-end sequence data with length 150\u0026ndash;200 bp was obtained by Illumina HiSeq or a compatible sequencer system, (IV) sequence data has a sufficient size at least 3.0 Gb, and (IV) metadata contains the location information of the WWTP. The sequence data in Japan were obtained in the previous study \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Finally, a total of 57 datasets of activated sludge samples were obtained from the USA (n\u0026thinsp;=\u0026thinsp;7), Europe (n\u0026thinsp;=\u0026thinsp;33), China (n\u0026thinsp;=\u0026thinsp;5), and Japan (n\u0026thinsp;=\u0026thinsp;12). Additionally, a total of 124 datasets of influent wastewater were obtained from the USA (n\u0026thinsp;=\u0026thinsp;7), Europe (n\u0026thinsp;=\u0026thinsp;84), China (n\u0026thinsp;=\u0026thinsp;23), and Japan (n\u0026thinsp;=\u0026thinsp;10) (Fig.\u0026nbsp;1a). Sample information and accession IDs of the sequence datasets are summarized in Supplementary Table\u0026nbsp;1.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSequence data analysis for ARG and MGE profiles\u003c/h2\u003e \u003cp\u003eBefore resistome and mobilome analysis, quality trimming of the sequence data was performed by removing adapter sequences and low-quality reads using Fastp 0.23.3 \u003csup\u003e56\u003c/sup\u003e. Quality-trimmed metagenomic reads were directly used (without matching paired ends) for identifying ARGs by BLASTn against the Comprehensive Antibiotic Resistance Database (CARD) ver. 3.2.6 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://card.mcmaster.ca/\u003c/span\u003e\u003cspan address=\"https://card.mcmaster.ca/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) \u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e with the E-value cutoff at 1 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e. The BLAST output was first aggregated to create a raw ARG profile, cataloging ARGs with corresponding read counts in each sample. To mitigate gene length bias in read counts, normalization to reads per kilobase (RPK) was conducted based on the subject sequence length (\u003cem\u003eslen\u003c/em\u003e) in the CARD database. Aggregation of RPK counts for gene variants into gene groups (e.g. OXA) was performed following the approach outlined by Sabar et al. (2023) \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. The ARG composition of each sample was determined by the proportion of each ARG, calculated as the ratio of the RPK of each ARG to the total RPK of all ARGs in the sample. The bacterial community in each sample was identified using Kraken2 ver. 2.1.2 \u003csup\u003e58\u003c/sup\u003e using the k-mer index from the SILVA 138 database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.arb-silva.de/documentation/release-138/\u003c/span\u003e\u003cspan address=\"https://www.arb-silva.de/documentation/release-138/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The classification results were summarized in the relative abundance of each taxon by Bracken 2.8 \u003csup\u003e59\u003c/sup\u003e. The read count of the 16S rRNA gene was also normalized as RPK based on the 1,541-bp length of the 16S rRNA gene of \u003cem\u003eE. coli\u003c/em\u003e \u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e. The total ARG abundance of each sample was computed as the ratio of the total RPK of all ARGs to the RPK of the 16S rRNA gene.\u003c/p\u003e \u003cp\u003eFor mobile genetic elements (MGEs), merged pair-end reads were identified by BLASTn against the MGE database \u003csup\u003e\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/KatariinaParnanen/MobileGeneticElementDatabase\u003c/span\u003e\u003cspan address=\"https://github.com/KatariinaParnanen/MobileGeneticElementDatabase\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), with an E-value cutoff at 1 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e. The MGE database encompasses 2,706 non-redundant sequences of over 270 gene types, including transposases, plasmids, integrases, insertion elements, and qacEdelta. The BLAST output for each sample was aggregated into an MGE profile in the same manner as the ARG profile. Read counts of the MGEs were normalized as RPK based on the \u003cem\u003eslen\u003c/em\u003e of the MGE in the database. The MGE composition of each sample was determined as the proportion of each MGE to the total RPK of all MGEs in a sample. The total abundance of MGEs for each sample was calculated as the ratio of the total RPK of all MGEs to the RPK of the 16S rRNA gene. The entire set of scripts for the bioinformatic workflow has been deposited on GitHub (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/ryohonda-hub/END-AMR-Asia\u003c/span\u003e\u003cspan address=\"https://github.com/ryohonda-hub/END-AMR-Asia\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). To exclude the divergence in the sequencing depth among samples, ARGs and MGEs with proportions exceeding the cutoff criterion at 0.01% were included for further analysis.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMultivariant analysis\u003c/h3\u003e\n\u003cp\u003eThe antimicrobial resistome and microbial community in each sample underwent comparative assessment through principal component analysis (PCA) using R version 4.3.2. For ARG composition, PCA was performed on the proportion of ARGs, with scaling to represent their relative changes. For the microbial community, PCA was performed on the relative abundance of each genus with scaling. Additionally, Pearson's correlation analysis was performed using Python between the proportion of ARGs and the abundance of class-level microbial community, which were present at \u0026gt;\u0026thinsp;0.001% of abundance in at least one of the samples.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eACKNOWLEDGEMENTS\u003c/h2\u003e \u003cp\u003eThis study was financially supported by JST CREST Program (Grant No. JPMJCR20H1), JSPS KAKENHI fund (Grant Nos. 18KK0114, 21KK0073, 23H01535), and Kurita Water and Environment Foundation (Grant No. 22T007). Computations were partially performed on the NIG supercomputer at ROIS National Institute of Genetics.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eThangaraju, P. \u0026amp; Venkatesan, S. WHO Ten threats to global health in 2019: Antimicrobial resistance. 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Nature Communications 9, 3891 (2018).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Antibiotic resistance gene (ARG), mobile genetic element (MGE), wastewater treatment plant (WWTP), metagenomics, One Health interfaces","lastPublishedDoi":"10.21203/rs.3.rs-6210263/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6210263/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eActivated sludge in wastewater treatment plants (WWTPs) is a significant source and reservoir of antimicrobial resistance (AMR), potentially emanating from the human-associated sources into the environment through wastewater treatment effluent and biosolid applications. This study aimed to explore the global diversity and determinants of AMR within activated sludge. Metagenomic analysis of 181 samples from WWTPs in the USA, Europe, Japan, and China revealed a globally conserved set of antimicrobial resistance genes (ARGs) in activated sludge, distinct from those in wastewater. Notably, specific ARGs, such as \u003cem\u003eAAC(6\u0026rsquo;)-Ib7\u003c/em\u003e, \u003cem\u003esul1\u003c/em\u003e, and \u003cem\u003eqacEdelta1\u003c/em\u003e were more abundant in activated sludge than in wastewater, suggesting that the selective growth of aerobic bacteria harboring these ARGs drives resistome formation. Furthermore, some ARGs associated with clinically important antimicrobials persisted from influent wastewater independent of microbial population dynamics. A strong correlation between ARG and mobile genetic element (MGE) abundances underscored the potential for ARG mobility within activated sludge.\u003c/p\u003e","manuscriptTitle":"Global diversity and commonality of the antimicrobial resistome in activated sludge in wastewater treatment plants","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-30 12:37:56","doi":"10.21203/rs.3.rs-6210263/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1a699513-9a63-45f7-a9f4-b06822c9910f","owner":[],"postedDate":"June 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":50697348,"name":"Biological sciences/Microbiology/Environmental microbiology/Water microbiology"},{"id":50697349,"name":"Biological sciences/Microbiology/Antimicrobials/Antimicrobial resistance"}],"tags":[],"updatedAt":"2025-10-07T11:10:17+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-30 12:37:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6210263","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6210263","identity":"rs-6210263","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}