Next Article in Journal
Surveillance and Genomic Analysis of Third-Generation Cephalosporin-Resistant and Carbapenem-Resistant Klebsiella pneumoniae Complex in Germany
Next Article in Special Issue
Three Distinct Annotation Platforms Differ in Detection of Antimicrobial Resistance Genes in Long-Read, Short-Read, and Hybrid Sequences Derived from Total Genomic DNA or from Purified Plasmid DNA
Previous Article in Journal
Comparison of Antimicrobial Resistances in Escherichia coli from Conventionally and Organic Farmed Poultry from Germany
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Comprehensive Genome and Plasmidome Analysis of Antimicrobial Resistant Bacteria in Wastewater Treatment Plant Effluent of Tokyo

Pathogen Genomics Center, National Institute of Infectious Diseases, Shinjyuku-ku, Tokyo 162-8640, Japan
*
Author to whom correspondence should be addressed.
Antibiotics 2022, 11(10), 1283; https://doi.org/10.3390/antibiotics11101283
Submission received: 30 August 2022 / Revised: 16 September 2022 / Accepted: 16 September 2022 / Published: 21 September 2022
(This article belongs to the Special Issue Advances in Plasmid Mediated Antimicrobial Resistance)

Abstract

:
To characterize environmental antimicrobial resistance (AMR) in urban areas, extended-spectrum β-lactamase- (ESBL)/carbapenemase-producing bacteria (EPB/CPB, respectively) from urban wastewater treatment plant effluents in Tokyo were isolated on CHROMagar ESBL plate. Complete genome sequence analysis, including plasmids, indicated that 126 CTX-M-positive isolates (31%) were identified among the 404 obtained isolates. The CTX-M-9 group was predominant (n = 65, 52%), followed by the CTX-M-1 group (n = 44, 35%). Comparative genome analysis revealed that CTX-M-27-positive E. coli O16:H5-ST131-fimH41 exhibited a stable genome structure and clonal-global dissemination. Plasmidome network analysis revealed that 304 complete plasmid sequences among 85 isolates were grouped into 14 incompatibility (Inc) network communities (Co1 to Co14). Co10 consisted of primarily IncFIA/IncFIB plasmids harboring blaCTX-M in E. coli, whereas Co12 consisted primarily of IncFIA(HI1)/Inc FIB(K) plasmids harboring blaCTX-M, blaKPC, and blaGES in Klebsiella spp. Co11 was markedly located around Co10 and Co12. Co11 exhibited blaCTX-M, blaKPC, and blaNDM, and was mainly detected in E. coli and Klebsiella spp. from human and animal sources, suggesting a mutual role of Co11 in horizontal gene transfer between E. coli and Klebsiella spp. This comprehensive resistome analysis uncovers the mode of relational transfer among bacterial species, highlighting the potential source of AMR burden on public health in urban communities.

1. Introduction

The World Health Organization has endorsed a global action plan for antimicrobial resistance (AMR), which calls upon all nations to adopt mitigation strategies [1]. However, there is still a need to fully understand the ecology and evolution of AMR based on a one-health approach. In particular, the properties of the microbial resistome in ecosystems dominated by humans and how to monitor such environmental factors to evaluate their potential risk for promoting the evolution of AMR have to be sufficiently characterized. Instead of the limited nosocomial AMR surveillance, sewage AMR surveillance could highlight a broader picture of the global burden of AMR, including local-specific features, such as urban, suburban, industrial, and agricultural, based on the one-health approach.
There is a growing concern for sludge management due to the high levels of contaminants, and the design of current wastewater treatment plants (WWTPs) does not restrict the elimination of emerging contaminants and their metabolites [2]. These contaminants are released into rivers or streams as sewage effluents without interruption. The prevalence of AMR bacteria (ARB) and AMR genes (ARGs) in rivers would increase downstream of WWTPs because of effluents [3,4]. Indeed, the high density of bacteria in WWTPs could provide an optimum environment for horizontal gene transfer (HGT) between human pathogens and environmental bacteria [5]. Moreover, such environmental bacteria persist in the environment and later they might transfer back such genes to clinically relevant pathogens [6]. Therefore, wastewater and active sludge in WWTPs can act as reservoirs and environmental suppliers of antibiotic resistance, implying that they are hotspots for HGT under the selective pressure of antibiotics, disinfectants, and metals, even at low concentrations, enabling the dissemination of antibiotic resistance genes among different bacterial species. ARGs are located in multidrug-resistance (MDR) plasmids, which could have been transferred into broad recipient targets among different Proteobacteria strains, indicating a high possibility of HGT among bacteria in wastewater [7].
Thus far, the potential correlation between the integron intI1 and anthropogenic pollution in WWTPs has been documented among the main hotspots of ARGs in the environment [8]. The importance of the synergy between plasmids and ARGs with flanking insertion sequences (ISs) has also been documented to potentiate the emergence of MDR-hypervirulent clones between WWTP- and human/animal-associated bacteria [5]. Ekanzala et al. reported that hospital wastewater showed significantly higher environmental resistome risk scores than all other assessed matrices [9,10], suggesting that hospital wastewater, effluent, and sewage sludge should be subjected to stringent mitigation measures to minimize such dissemination. Therefore, urban WWTPs are among the main sources of ARB and ARGs released into the environment [11]. However, the evolution of resistance and the spread of ARGs in WWTPs have not been widely researched and clearly evidenced.
Regarding a comprehensive global plasmidome analysis, Redondo-Salvo et al. characterized the global map of all publicly available over 10,000 reference prokaryotic plasmid sequences, including Proteobacteria, Firmicutes, Actinobacteria, Spirochaetes, Cyanobacteria, and Archaea [12,13]. Global analysis showed that more than 60% of the plasmids were grouped with host ranges beyond the species barrier, although plasmid transmission was constrained by taxonomic boundaries. Another report using long-read sequencing and an improved bioinformatics workflow for global sewage samples revealed marked AMR transmission among plasmids in complex untreated domestic sewage [13].
In this study, we characterized the complete genome sequences of extended-spectrum β-lactamase (ESBL)-or carbapenemase-producing bacteria (EPB or CPB) isolated from urban WWTP effluents in Tokyo. We have analyzed a marked genomic feature of CTX-M-positive Enterobacterales isolates that could be reflected in the urban areas of Tokyo as AMR surveillance. In addition, we determined the complete genome sequence of AMR plasmids in the EPB/CPB isolates to perform accurate gene network analysis (plasmidome analysis) to assess plasmid transmission among bacterial species.

2. Results

2.1. Bacterial Proportion in WWTP Effluents Genome Analysis of ESBL/Carbapenemase-Producing Bacteria (EPB and CPB) Isolated from WWTP Effluents and Environment

Sewage effluent samples were collected from eight WWTP sites along the Tama River, Tokyo Bay, and the recreational beach area (BEC1) [14]. EPB and CPB from fresh 50-mL samples of each effluent (Figure 1). CHROMagar ESBL selection demonstrated that potential clinically pathogenic Enterobacterales (E. coli, Enterobacter, and Klebsiella spp.) were observed in approximately 400 colonies from the effluents of WP4, WP5, and WP8 at all tested sampling times (Figure 1). More than a hundred typical chromogenic colonies, sufficient to characterize environmental pollution due to EPB and CPB, were isolated at each sampling time (Table 1). Whole-genome sequencing of all marked isolates (Table S2) showed that 126 CTX-M-positive isolates were identified (31% in total; Table 1). The CTX-M-9 group (blaCTX-M-9, blaCTX-M-13, blaCTX-M-14, blaCTX-M-24, blaCTX-M-27, blaCTX-M-65, and blaCTX-M-213) was the predominant group with 68 isolates (54%), and the second was the CTX-M-1 group (blaCTX-M-3, blaCTX-M-15, and blaCTX-M-55) with 44 isolates (35%), following CTX-M-2 group (blaCTX-M-2) with 11 isolates (9%), and CTX-M-8 group (blaCTX-M-8) with three isolates (2%) (Table S2). The EPB and CPB isolates on CHROMagar ESBL and its sequence type (ST) are summarized in Table S3. Eighteen CPB isolates (six blaIMP-positive, eight blaKPC-positive, and two blaNDM-positive) were identified (Table 1).

2.2. E. coli ST131

Among the 71 E. coli isolates, ST131 was the predominant ST (n = 11 isolates) and CTX-M-27-positive E. coli ST131 (n = 9 isolates) was the most predominant, following CTX-M-3- or CTX-M-15-positive E. coli ST131 (n = 1 isolate each) (Table S2).
Core-genome single-nucleotide variation (SNV) phylogeny (see the detailed procedures in Figure S1) of the ST131 isolates were compared with publicly available E. coli ST131 draft or complete genome sequences (315 strains; see Table S4), suggesting that the four subclonal types of ST131 were primarily identified from the WWTP effluents, two isolates of ST131-fimH41 with blaCTX-M-27, seven isolates of ST131-fimH30 with blaCTX-M-27, one isolate of ST131-fimH30 with blaCTX-M-3, and one isolate of ST131-fimH30 with blaCTX-M-15 (Figure 2).
One isolate (WP5-S18-ESBL-09) of O16:H5-ST131-fimH41 with blaCTX-M-27 exhibited marked clonality, showing less than 12 SNVs with clinical isolates from several countries (Southeast Asia, EU, and Oceania) (Figure 3A). Genome recombination and pan-genome analysis suggested that the genome structure of these strains was very stable, except for some ARGs that were transferred with conjugative plasmids (Figure 3B).
Three isolates of ST131-fimH30 with blaCTX-M-27 (WP3-S18-ESBL-08, WP3-W18-ESBL-07, and WP3-W18-ESBL-09) exhibited marked clonality, with 8–13 SNVs to the clinical isolate SAMD00126441 in Japan (Figure 2), suggesting that a clinically potential subclone (O25:H4-ST131-fimH30 with blaCTX-M-27) [18] has been detected in WWTP effluent in Japan.

2.3. Other E. coli ST Isolates

E. coli ST38 (n = 10 isolates), ST10 (n = 5 isolates), ST602 (n = 5 isolates), ST405 (n = 4 isolates), ST69 (n = 3 isolates), and ST648 (n = 3 isolates) were also detected in this study (Tables S2 and S3). The core genome SNV phylogeny for each ST isolate, including publicly available strains (Table S4), suggests that CTX-M-14 is one of the major CTX-M variants in E. coli ST38, ST69, ST405, and ST648 (Figure 4).
For instance, all E. coli ST38 isolates (n = 10) were ST38-fimH5- and CTX-M-14-positive. However, these were classified into different serotypes (O86:H18 and O50/O2:H30), suggesting that at least two major serotypes of E. coli clones could play a pivotal role as hosts for blaCTX-M-14 gene dissemination in the global environment (Figure 4, panel ST38).
Regarding E. coli ST69 (n = 3 isolates), WP8-W19-ESBL-06 exhibited O15:H18-ST69-fimH27 types and CTX-M-14 positivity, and its clonal dissemination in Europe and North America. In contrast, the other two isolates of ST69 (WP7-S17-ESBL-01 and WP8-S17-ESBL-12) exhibited CTX-M-14-positive but distinct serotypes (O25:H4 and O15:H18, respectively), and their relative host clones harbored different CTX-M genes, such as blaCTX-M-15 or blaCTX-M-27 (Figure 4, panel ST69). This indicated that these two CTX-M-14-positive ST69 isolates could be unique compared to other ST69 isolates in other countries, suggesting that the blaCTX-M-14 gene was recently acquired in E. coli ST69 in Japan.
With respect to E. coli ST405 (n = 4 isolates), most ST405 isolates, including publicly available genomes, exhibited O102:H6-ST405-fimH27 and carried multiple CTX-M types. Two isolates (WP7-S18-ESBL-07 and WP7-S18-ESBL-09) exhibited distinct serotypes O45:H6 from other ST405 isolates. These two isolates showed the most similar genome SNV profile as SAMD00126438 (Human in Japan, Table S4) and SAMD00076210 (sewage in Japan, Table S4), suggesting that CTX-M-14-positive O45:H6-ST405-fimH27 E. coli isolate could be notable in Japan (Figure 4, panel ST405).
Regarding E. coli ST10 (n = 5 isolates), four isolates were CTX-M-positive, whereas all four carried distinct CTX-M genes (CTX-M-8, -14, -15, and -55). Most ST10 isolates, including those with publicly available genomes, exhibited O12:H4-ST10-fimH27 and were isolated mainly from the Asian continent (Figure 4, panel ST10).
Regarding E. coli ST602 (n = 5 isolates), four isolates appeared to be clones because they were isolated from the same sample (WP2-W18-CRE-xx stands for isolate ID with meropenem selection at the WWTP WP2 site in winter 2018). The inclusion of publicly available ST602 genomes indicated that the CTX-M-27-positive O9:H9-ST602-fimH86 isolate could be notable in Japan (Figure 4, panel ST602).
Regarding E. coli ST648 (n = 3 isolates), most ST648 isolates, including publicly available genomes, exhibited variable types, carrying mainly CTX-M-14 and -15 (Figure 4, panel ST648).

2.4. Other CTX-M Positive Bacteria

Among the 88 isolates of Aeromonas species (Table 1), three isolates of A. hydrophila, seven isolates of A. caviae, one isolate of A. media, and four isolates of A. veronii were identified as CTX-M producers (Table S2). Although four isolates of CTX-M-14 producing A. caviae were detected in different WWTP effluents (WP2, 4, and 7), core-genome SNV phylogeny revealed that they were clonal in 21 SNVs with the same recombination and pangenome regions (Figure 5A), suggesting that the A. caviae clone may be successfully predominating in the general WWTP environment in Tokyo but not in WWTPs at specific locations.
Among the 48 isolates of Klebsiella species (Table 1), eight isolates of K. pneumoniae, seven isolates of K. quasipneumoniae, two isolates of K. variicola, and seven isolates of other Klebsiella spp. were identified as CTX-M producers (Table S2). Core-genome SNV phylogeny revealed that four isolates of CTX-M-3-producing K. quasipneumoniae ST668 exhibited clonality in 14 SNVs and shared similar recombination and pan-genome regions (Figure 5B), although these isolates were obtained from the same place (WP5) but at different sampling times (summer 2017, summer 2018, and winter 2019), suggesting that the ST668 clone may remain in active sludge at WP5 for at least one year and more.

2.5. Plasmidome Analysis of EPB and CPB Isolated from WWTP Effluents and Environment

ESBL and carbapenemase β-lactamase genes were acquired by conjugative plasmid transfer among variable strains from the Proteobacteria group. Genetic network analysis among AMR plasmids could be useful to uncover the modes of relational transfer and trace dissemination. Of the 404 EPB/CPB isolates (Table 1), 85 were identified as complete genome sequences in this study (Table S2). Moreover, out of the 304 complete plasmid sequences from the 85 strains described above, 73 β-lactamase-positive plasmids (Table S5) were subjected to plasmidome network analysis based on orthologous analysis (see details in Figure S2). To characterize global ARG dissemination through plasmid transfer, 758 publicly available complete plasmid sequences showing a clear description of the isolation and source were selected from 19,904 complete plasmid sequences. A total of 831 complete plasmids (73 in this study and 758 in the public domain; see Table S6) were subjected to pangenome analysis using Roary and NMDS (vegan in the R package), and the results revealed that 14 communities were classified and clustered (Figure 6).
Most network communities (Co) showed notable incompatibility (Inc) replicon-dependent distribution, suggesting that the network analysis was well-performed based on the genetic features of each Inc replicon. The major Co comprised Co10, Co11, and Co12 of the shared 423 plasmids among the tested 831 plasmids. Co10 was primarily IncFIA and IncFIB (AP001918) replicon plasmids harboring the blaCTX-M gene in E. coli from human sources, whereas Co12 was primarily IncFIA(HI1) and Inc FIB(K) replicon plasmids harboring blaCTX-M, blaKPC, and blaGES genes in Klebsiella spp. from human sources (Figure 6).
This network analysis highlighted the potential mutual role of Co11 plasmids between Co10 and Co12 plasmids because Co11 plasmids are placed around Co10 and next to Co12 (upper-left panel in Figure 6). Co11 is primarily rich in IncFII, Inc FII(pHN7A8), IncX1, and IncN replicon plasmids harboring blaCTX-M, blaKPC, and blaNDM genes, and are mainly detected in E. coli and Klebsiella spp. from human and animal sources. Therefore, Co11 plasmids may contribute to the horizontal ARG transfer between E. coli and Klebsiella spp.
Regarding other notable co-exhibiting specific replicon and host bacteria, Co3 of comprised IncHI2 and IncHI2A replicon plasmids harboring blaCTX-M and blaIMP genes and was mainly detected in Enterobacter species (E. cloacae, 8; E. hormaechei, 6; E. asburiae, 3; others, 1) from human sources. Co4 comprised IncB/O/K/Z and IncI1-gamma replicon plasmids harboring the blaCTX-M gene and were primarily detected in E. coli from human, environmental, and animal sources. Co6 comprised of an IncP6 replicon plasmid harboring blaGES and blaKPC genes and was primarily detected in Aeromonas, Enterobacter, and Klebsiella spp. from environmental sources.
The gene-specific distribution of carbapenemase genes was as follows: blaIMP in Co1 and Co3; blaKPC in Co6, Co8, and Co12 and blaNDM in Co5, Co11, and Co13. Such ARG distribution may be involved in the plasmid replicon and its bacterial hosts.

3. Discussion

Here, we characterized WWTP-related EPB and its plasmids based on the complete genome sequences. Urban WWTP effluents could be a potential source of AMR burden. Therefore, there is concern that hospital [19] and community [20] effluents include a considerable proportion of ARGs in the environment. Among potential healthy EPB carriers, globally disseminated E. coli ST131 clones should first be investigated. This study suggests that multiple ST131 clones in WWTP effluents harbor the currently prevalent CTX-M variants (Figure 2). E. coli O16:H5-ST131-fimH41 with blaCTX-M-27 was identified as a marked clone (Figure 3). Indeed, CTX-M-27-positive E. coli ST131 has been increasing in China [21], EU [22], Australia [23], New Zealand [23], and Japan [24], which has been speculated by the observation that CTX-M-27 might exhibit a higher hydrolyzing activity against ceftazidime compared with CTX-M-14 [25]. In contrast to ST131 with blaCTX-M-27, other E. coli STs still harbor blaCTX-M-14, which has been the predominant variant since the early 20th century in Japan [24], suggesting that the other STs have not shifted to acquire more potential CTX-M-27 thus far.
Plasmidome network analysis (Figure 6) exhibited a good approach for illuminating bacterial communication through plasmid-based HGT. This study highlights bacterial species-dependent plasmid tropism and compatibility among distinct species. The blaCTX-M variants were identified in widely variable plasmids, whereas carbapenemase genes (blaNDM, blaKPC, and blaIMP) showed a typical plasmid replicon with a specific distribution, suggesting that the region-specific distribution of carbapenemase [26] may be associated with its locality [27]. In particular, specific blaIMP-containing integrons are markedly circulating among different bacteria in countries, such as Japan, Australia, and Thailand [27]. It has been reported that IMP-6-positive CPB clinical isolates are predominantly disseminated among chromosomally distinct isolates through the pKPI-6-related plasmid (IncN replicon [28]) in Japan [29]. Although IMP is the most predominant type of carbapenemase in clinical CPB in Japan, apart from clinical settings, we have reported the KPC-2 or NDM-5-positive WWTP-effluent isolates, i.e., the complete genome sequences of KPC-2-positive Klebsiella pneumoniae GSU10-3 [15], KPC-2-positive Aeromonas hydrophila GSH8-2 [16], KPC-2-positive Aeromonas caviae GSH8M-1 [16], and NDM-5- and CTX-M-55-coproducing E. coli GSH8M-2 [17] were determined. Overall, WWTP monitoring is an ideal approach to identify non-clinical but marked ARBs for the prediction of future clonal expansion from local to global dissemination.
According to the European Centre for Disease Prevention and Control, a significant proportion of antibiotics consumed by humans are in the community rather than in healthcare settings [30], suggesting that outpatient therapy could be the most effective factor in increasing the proportion of antimicrobials, selected ARGs, and ARB in WWTP. Therefore, a nation (or region)-wide survey of the resistome in WWTP effluents could provide a rapid and efficient method for assessing the environmental AMR burden in urban populations. To date, the healthy carriage rate of EPB has been rising worldwide. In Japan, the detection rate of EPB was reported to be 12.2% in healthy adult volunteers [31] and 15.6% in healthy food handlers [32]. As the number of EPB-positive healthy carriers has been increasing worldwide, Japan is no exception to the issue of increasing AMR healthy carriers. According to the Japan Nosocomial Infections Surveillance (JANIS), clinical reports of antibiotic-resistant gram-negative bacteria are increasing (https://janis.mhlw.go.jp/english/index.asp (accessed on 29 August 2022)). As suggested in this study, the whole genome sequence of the obtained ARBs (Table 1) and its plasmidome profiles in WWTP (Figure 6) could then reflect the structure and diversity of ARBs in the gastrointestinal tracts of urban residents within the WWTP catchment area.
The risk assessment of transmission of AMR vectors/reservoirs from the environment to humans cannot be adapted from the model for pathogens because most AMR vectors/reservoirs are supposed to be composed of non- or low-pathogenic bacterial species. As colonization may be asymptomatic in most humans, this may cause further dissemination under frequent abuse of antimicrobials in clinical use, leading to an underestimation of the extent of transmission of ARB from the environment to humans, as well as from humans to humans in the community. Therefore, they can colonize humans without notable symptoms, resulting in a healthy carrier [33]. Members of the family Enterobacterales and genera, such as Aeromonas, Acinetobacter, and Pseudomonas have been frequently documented as carriers of ESBL and carbapenemase genes in wastewater samples, and some of them may act as vectors for HGT [34]. Indeed, this study identified the clonal dissemination of CTX-M-14-positive Aeromonas caviae isolates at different WWTP sites (Figure 5A), indicating that such low-pathogenic Aeromonas spp. could be a potential reservoir for AMR dissemination. Therefore, reservoir ARBs should be considered in the overall AMR risk assessment.

4. Materials and Methods

4.1. Sample Collection

Sewage effluent samples were collected from eight WWTPs (WP1–WP9 and WP6 were treated as missing numbers owing to incorrect sampling locations) along the Tama River and around Tokyo Bay (Table S1). Surface water from a recreational beach (BEC1) was used as the environmental control sample (Table S1). Sampling was conducted during the summer and winter seasons for 2 years between August 2017 and February 2019 (Table S1). The sampling procedure is summarized in Figure 1. A fresh 50 mL of effluent was centrifuged at 7000× g for 3 min, and the cell pellet was resuspended with residual water, followed by spreading all suspensions on CHROMagar ESBL plates (CHROMagar, Paris, France). The plates were then incubated at 36 °C for 24 h (Figure 1). Suspected colonies of Escherichia coli, Klebsiella, Enterobacter, Aeromonas, and Pseudomonas (Figure 1) were isolated as single clones, followed by whole-genome sequencing. In addition to EPB, CPB was isolated as described previously [15]. Briefly, 500 mL of effluent was filtered, and the membrane was incubated in 20 mL of Luria–Bertani (LB) broth supplemented with 1 mg/L meropenem at 37 °C for 14 h, after which the culture was spread on CHROMagar ESBL plates (CHROMagar, Paris, France).

4.2. Whole-Genome Sequencing of Bacterial Isolates

To determine the complete genome sequence, long-read sequencing data of isolated bacterial genomes were produced with more than 100-fold coverage and assembled using Flye version 2.5 [35]. Primary error correction using long reads was performed using Minimap version 0.2-r124 [36] and Racon version 1.1.0 [37], followed by circularization using Circlator version 1.5.3 [38]. The remaining error of the tentative complete circular sequences was corrected using Pilon version 1.18 with Illumina short reads [39]. Short plasmids (<10 kb) were assembled using A5-miseq version 20140604, using unmapped short reads against chromosomal and long plasmid sequences. The draft genome sequence was assembled using A5-miseq with only Illumina short-read data. Gene annotation was performed using DFAST version 1.2.3 [40] with the following databases: DFAST default database, ResFinder database [41], bacterial antimicrobial resistance reference gene (BARRG) database (PRJNA313047), and Virulence Factors Database [42]. Multilocus sequence typing (MLST) was performed using “mlst” program version 2.16.2 (Seemann T, mlst Github https://github.com/tseemann/mlst (accessed on 29 August 2022)) with PubMLST database (https://pubmlst.org/ (accessed on 29 August 2022)). Plasmid replicon typing was performed using the ABRicate program version 0.3 (Seemann T, Abricate, Github https://github.com/tseemann/abricate (accessed on 29 August 2022)) with the PlasmidFinder database [43].

4.3. SNV Phylogenetic Analysis and Pan-Genome Analysis

A flowchart of the single nucleotide variation (SNV) phylogenetic analysis is summarized in Figure S1. Assembly data and/or Illumina raw reads of four species (E. coli, Aeromonas caviae, and Klebsiella quasipneumoniae) were retrieved from the NCBI database. If assembly data were not deposited in the NCBI assembly database, the raw sequence data downloaded from the SRA database were assembled using SKESA version 2.3.0 [44]. MinHash sketch for each genome sequence in this study (n = 53) and NCBI data (n = 76,449) were constructed using the sourmash program version 2.0.0a4 [45] with the following parameters: compute -k 21 -scaled 4000. The MinHash sketch database was built using the sourmash program (parameter: index -k 21) with the NCBI dataset, followed by a MinHash search against 53 genome sequences. The collected dataset was analyzed for core genome SNV and pan-genome analyses for each species or sequence type (ST). In SNV analysis, the longest chromosomal sequences from this study were selected as the reference sequences. Repeat and prophage regions of the reference sequences were analyzed using NUCmer (MUMmer 3.0) [46] and prophet [47] programs, respectively. If the available data were only contig sequences from the NCBI database, the SimSeq program (https://github.com/jstjohn/SimSeq (accessed on 1 April 2018)) was used to construct simulated 150-mer paired-end reads with a 200 bp insert length. Read mapping was performed using BWA-MEM [48] with default parameters against reference chromosomal sequences, followed by variant calling using VarScan version 2.3.4 [49]. SNVs on repeat and predicted prophage regions were removed, and recombination regions were predicted using the Gubbins software [50], followed by filtering SNVs on recombination regions. Core genome SNV phylogenetic analysis was performed by the approximate maximum likelihood phylogenetic method using FastTree v2.1.10 [51], followed by visualization using Fandango version 1.3.0 [52] and interactive tree of life (iTOL) version 3 [53]. SNV network analysis was performed using the median joining network method and TCS network method of PopART (http://popart.otago.ac.nz (accessed on 29 August 2022)). Pan-genome analysis of predicted open reading frames (ORFs) was performed using Roary version 3.12.0 with default parameters [54].

4.4. Plasmidome Analysis

The flowchart for the plasmidome phylogenetic analysis is summarized in Figure S2. Complete plasmid sequences were retrieved from the NCBI database as of November 2019, followed by re-annotation and ARG detection using DFAST with the ResFinder and BARRG databases. A plasmid database of the nucleotide and protein sequences was constructed using BLAST. For plasmidome analysis, complete plasmids in the public database were selected according to the following criteria: (i) ≥90% nucleotide sequence identity and ≤1 × e−100 e-value against β-lactamase gene-positive complete plasmids revealed in this study, (ii) sharing ≥10 ORFs (≥99% identity) against these plasmids, (iii) presence of ARGs, and (iv) existence of metadata related to the isolation source. Pan-genome analysis using the collected plasmids was performed using Roary version 3.12.0 [54] with a parameter of 99% BLASTP percentage identity cutoff, followed by the construction of a distance matrix using the R package “proxy” with edge weights of plasmids sharing ≥ 10 ORFs. NMDS and community structure analysis were performed by “vegan” and “igraph” of R package, respectively. Plasmid data were visualized using Cytoscape version 3.7.2.

5. Conclusions

Urban WWTP effluents, even with proper treatment, may cause AMR burden with a high frequency of acquired ARGs in the environment. The dissemination of ARB/Gs in the environment might increase the risk of infectious diseases [55], but there is little direct evidence regarding their epidemiological effects. This study revealed resistome analysis based on complete genome sequencing and subsequent plasmidome analysis of EPB/CPB isolated from WWTP effluents, suggesting that every urban community, including hospitals, healthy carriers, and travelers, can be a potential source of ARGs. WWTP is speculated to be hotspots where various bacteria can acquire ARGs via HGT. Therefore, resistome analysis of AMR plasmids and their specific bacterial hosts in WWTP effluent is expected to identify the presence of undetected nosocomial infections, leading to the detection of potential ongoing dissemination in the overall community.

Supplementary Materials

The following supporting information can be downloaded from: https://www.mdpi.com/article/10.3390/antibiotics11101283/s1, Figure S1: Flowchart for verification of strain clonality using comparative genomic analysis; Figure S2: Flowchart of plasmidome analysis; Table S1: General information on wastewater treatment plants and sampling sites in this study; Table S2: Whole-genome sequence information for the strain grown on CHROMagar ESBL; Table S3: Summary of isolates on CHROMagar ESBL and their sequence type in this study; Table S4: The strain information of E. coli used in the core-genome SNV phylogenetic and pan-genome analyses; Table S5: Complete plasmid sequence information of the strain growing on CHROMagar ESBL; Table S6: Complete plasmid sequence list for plasmidome analysis; Table S7: Summary of the absolute counts of plasmids for each category in plasmidome analysis.

Author Contributions

T.S., K.Y. and M.K. collected water samples. Conceptualization: T.S. and M.K.; investigation, T.S., R.T., M.H., K.Y. and M.K.; methodology, T.S. and M.K.; formal analysis, T.S.; writing—original draft, T.S. and M.K.; writing- review and editing, T.S. and M.K.; supervision, M.K.; funding acquisition, M.K.; project administration, M.K. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Research Program on Emerging and Reemerging Infectious Diseases from the Japan Agency for Medical Research and Development, AMED (grant numbers JP21fk0108103 and JP22fk0108131). This work was also supported by a grant for Research on Emerging and Reemerging Infectious Diseases and Immunization (H30 Shinkogyosei-Ippan-002 and R4 Shinkogyosei-Ippan-002) from the Ministry of Health, Labour and Welfare, Japan.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

All complete sequences are available in the DDBJ/EMBL/GenBank database (accession numbers AP021908–AP022304; see Table S2). All raw read sequence files are available from the DRA/SRA database (accession numbers DRR199157–DRR199560 [whole-genome data, see Table S2]).

Acknowledgments

We would like to thank Akifumi Yamashita and Yuba Inamine for their assistance with the whole-genome sequencing.

Conflicts of Interest

The funding agencies played no role in the study design, data collection and analysis, decision to publish, or manuscript preparation. The authors declare no conflict of interest.

References

  1. World Health Organization (WHO). Global Antimicrobial Resistance Surveillance System: Manual for Early Implementation; World Health Organization: Geneva, Switzerland, 2016; pp. 1–4.
  2. Fijalkowski, K.; Rorat, A.; Grobelak, A.; Kacprzak, M.J. The presence of contaminations in sewage sludge—The current situation. J. Environ. Manag. 2017, 203, 1126–1136. [Google Scholar] [CrossRef] [PubMed]
  3. Amos, G.C.; Hawkey, P.M.; Gaze, W.H.; Wellington, E.M. Waste water effluent contributes to the dissemination of CTX-M-15 in the natural environment. J. Antimicrob. Chemother. 2014, 69, 1785–1791. [Google Scholar] [CrossRef] [PubMed]
  4. Marti, E.; Jofre, J.; Balcazar, J.L. Prevalence of antibiotic resistance genes and bacterial community composition in a river influenced by a wastewater treatment plant. PLoS ONE 2013, 8, e78906. [Google Scholar] [CrossRef]
  5. Che, Y.; Xu, X.; Yang, Y.; Brinda, K.; Hanage, W.; Yang, C.; Zhang, T. High-resolution genomic surveillance elucidates a multilayered hierarchical transfer of resistance between WWTP- and human/animal-associated bacteria. Microbiome 2022, 10, 16. [Google Scholar] [CrossRef] [PubMed]
  6. Bengtsson-Palme, J.; Kristiansson, E.; Larsson, D.G.J. Environmental factors influencing the development and spread of antibiotic resistance. FEMS Microbiol. Rev. 2018, 42, fux053. [Google Scholar] [CrossRef] [PubMed]
  7. Osinska, A.; Harnisz, M.; Korzeniewska, E. Prevalence of plasmid-mediated multidrug resistance determinants in fluoroquinolone-resistant bacteria isolated from sewage and surface water. Environ. Sci. Pollut. Res. Int. 2016, 23, 10818–10831. [Google Scholar] [CrossRef]
  8. Di Cesare, A.; Sabatino, R.; Yang, Y.; Brambilla, D.; Li, P.; Fontaneto, D.; Eckert, E.M.; Corno, G. Contribution of plasmidome, metal resistome and integrases to the persistence of the antibiotic resistome in aquatic environments. Environ. Pollut. 2022, 297, 118774. [Google Scholar] [CrossRef]
  9. Ekwanzala, M.D.; Dewar, J.B.; Momba, M.N.B. Environmental resistome risks of wastewaters and aquatic environments deciphered by shotgun metagenomic assembly. Ecotoxicol. Environ. Saf. 2020, 197, 110612. [Google Scholar] [CrossRef]
  10. Katagiri, M.; Kuroda, M.; Sekizuka, T.; Nakada, N.; Ito, Y.; Otsuka, M.; Watanabe, M.; Kusachi, S. Comprehensive Genomic Survey of Antimicrobial-Resistance Bacteria in the Sewage Tank Replacement with Hospital Relocation. Infect. Drug Resist. 2021, 14, 5563–5574. [Google Scholar] [CrossRef]
  11. Rizzo, L.; Manaia, C.; Merlin, C.; Schwartz, T.; Dagot, C.; Ploy, M.C.; Michael, I.; Fatta-Kassinos, D. Urban wastewater treatment plants as hotspots for antibiotic resistant bacteria and genes spread into the environment: A review. Sci. Total Environ. 2013, 447, 345–360. [Google Scholar] [CrossRef] [Green Version]
  12. Redondo-Salvo, S.; Fernandez-Lopez, R.; Ruiz, R.; Vielva, L.; de Toro, M.; Rocha, E.P.C.; Garcillan-Barcia, M.P.; de la Cruz, F. Pathways for horizontal gene transfer in bacteria revealed by a global map of their plasmids. Nat. Commun. 2020, 11, 3602. [Google Scholar] [CrossRef] [PubMed]
  13. Kirstahler, P.; Teudt, F.; Otani, S.; Aarestrup, F.M.; Pamp, S.J. A Peek into the Plasmidome of Global Sewage. mSystems 2021, 6, e0028321. [Google Scholar] [CrossRef] [PubMed]
  14. Sekizuka, T.; Itokawa, K.; Tanaka, R.; Hashino, M.; Yatsu, K.; Kuroda, M. Metagenomic analysis of urban wastewater treatment plant effluents in Tokyo. Infect. Drug Resist. 2022, 15, 4763–4777. [Google Scholar] [CrossRef] [PubMed]
  15. Sekizuka, T.; Yatsu, K.; Inamine, Y.; Segawa, T.; Nishio, M.; Kishi, N.; Kuroda, M. Complete Genome Sequence of a blaKPC-2-Positive Klebsiella pneumoniae Strain Isolated from the Effluent of an Urban Sewage Treatment Plant in Japan. mSphere 2018, 3, e00314-18. [Google Scholar] [CrossRef] [PubMed]
  16. Sekizuka, T.; Inamine, Y.; Segawa, T.; Hashino, M.; Yatsu, K.; Kuroda, M. Potential KPC-2 carbapenemase reservoir of environmental Aeromonas hydrophila and Aeromonas caviae isolates from the effluent of an urban wastewater treatment plant in Japan. Environ. Microbiol. Rep. 2019, 11, 589–597. [Google Scholar] [CrossRef]
  17. Sekizuka, T.; Inamine, Y.; Segawa, T.; Kuroda, M. Characterization of NDM-5- and CTX-M-55-coproducing Escherichia coli GSH8M-2 isolated from the effluent of a wastewater treatment plant in Tokyo Bay. Infect. Drug Resist. 2019, 12, 2243–2249. [Google Scholar] [CrossRef]
  18. Matsumura, Y.; Pitout, J.D.; Gomi, R.; Matsuda, T.; Noguchi, T.; Yamamoto, M.; Peirano, G.; DeVinney, R.; Bradford, P.A.; Motyl, M.R.; et al. Global Escherichia coli Sequence Type 131 Clade with blaCTX-M-27 Gene. Emerg. Infect. Dis. 2016, 22, 1900–1907. [Google Scholar] [CrossRef]
  19. Azuma, T.; Katagiri, M.; Sekizuka, T.; Kuroda, M.; Watanabe, M. Inactivation of Bacteria and Residual Antimicrobials in Hospital Wastewater by Ozone Treatment. Antibiotics 2022, 11, 862. [Google Scholar] [CrossRef]
  20. Azuma, T.; Usui, M.; Hayashi, T. Inactivation of Antibiotic-Resistant Bacteria in Wastewater by Ozone-Based Advanced Water Treatment Processes. Antibiotics 2022, 11, 210. [Google Scholar] [CrossRef]
  21. Zhong, Y.M.; Liu, W.E.; Liang, X.H.; Li, Y.M.; Jian, Z.J.; Hawkey, P.M. Emergence and spread of O16-ST131 and O25b-ST131 clones among faecal CTX-M-producing Escherichia coli in healthy individuals in Hunan Province, China. J. Antimicrob. Chemother. 2015, 70, 2223–2227. [Google Scholar] [CrossRef] [Green Version]
  22. Birgy, A.; Levy, C.; Bidet, P.; Thollot, F.; Derkx, V.; Bechet, S.; Mariani-Kurkdjian, P.; Cohen, R.; Bonacorsi, S. ESBL-producing Escherichia coli ST131 versus non-ST131: Evolution and risk factors of carriage among French children in the community between 2010 and 2015. J. Antimicrob. Chemother. 2016, 71, 2949–2956. [Google Scholar] [CrossRef] [PubMed]
  23. Rogers, B.A.; Ingram, P.R.; Runnegar, N.; Pitman, M.C.; Freeman, J.T.; Athan, E.; Havers, S.; Sidjabat, H.E.; Gunning, E.; De Almeida, M.; et al. Sequence type 131 fimH30 and fimH41 subclones amongst Escherichia coli isolates in Australia and New Zealand. Int. J. Antimicrob. Agents 2015, 45, 351–358. [Google Scholar] [CrossRef] [PubMed]
  24. Kuroda, H.; Yano, H.; Hirakata, Y.; Arai, K.; Endo, S.; Kanamori, H.; Yamamoto, H.; Ichimura, S.; Ogawa, M.; Shimojima, M.; et al. Molecular characteristics of extended-spectrum beta-lactamase-producing Escherichia coli in Japan: Emergence of CTX-M-15-producing E. coli ST131. Diagn. Microbiol. Infect. Dis. 2012, 74, 201–203. [Google Scholar] [CrossRef] [PubMed]
  25. Bevan, E.R.; Jones, A.M.; Hawkey, P.M. Global epidemiology of CTX-M beta-lactamases: Temporal and geographical shifts in genotype. J. Antimicrob. Chemother. 2017, 72, 2145–2155. [Google Scholar] [CrossRef] [PubMed]
  26. Bonomo, R.A.; Burd, E.M.; Conly, J.; Limbago, B.M.; Poirel, L.; Segre, J.A.; Westblade, L.F. Carbapenemase-Producing Organisms: A Global Scourge. Clin. Infect. Dis. 2018, 66, 1290–1297. [Google Scholar] [CrossRef] [PubMed]
  27. Matsumura, Y.; Peirano, G.; Motyl, M.R.; Adams, M.D.; Chen, L.; Kreiswirth, B.; DeVinney, R.; Pitout, J.D. Global Molecular Epidemiology of IMP-Producing Enterobacteriaceae. Antimicrob. Agents Chemother. 2017, 61, e02729-16. [Google Scholar] [CrossRef] [PubMed]
  28. Kayama, S.; Shigemoto, N.; Kuwahara, R.; Oshima, K.; Hirakawa, H.; Hisatsune, J.; Jove, T.; Nishio, H.; Yamasaki, K.; Wada, Y.; et al. Complete nucleotide sequence of the IncN plasmid encoding IMP-6 and CTX-M-2 from emerging carbapenem-resistant Enterobacteriaceae in Japan. Antimicrob. Agents Chemother. 2015, 59, 1356–1359. [Google Scholar] [CrossRef] [PubMed]
  29. Abe, R.; Akeda, Y.; Sugawara, Y.; Takeuchi, D.; Matsumoto, Y.; Motooka, D.; Yamamoto, N.; Kawahara, R.; Tomono, K.; Fujino, Y.; et al. Characterization of the Plasmidome Encoding Carbapenemase and Mechanisms for Dissemination of Carbapenem-Resistant Enterobacteriaceae. mSystems 2020, 5, e00759-20. [Google Scholar] [CrossRef] [PubMed]
  30. ECDC. Antimicrobial Consumption in the EU/EEA, Annual Epidemiological Report for 2018. Available online: https://www.ecdc.europa.eu/sites/default/files/documents/Antimicrobial-consumption-EU-EEA.pdf2018 (accessed on 1 October 2020).
  31. Higa, S.; Sarassari, R.; Hamamoto, K.; Yakabi, Y.; Higa, K.; Koja, Y.; Hirai, I. Characterization of CTX-M type ESBL-producing Enterobacteriaceae isolated from asymptomatic healthy individuals who live in a community of the Okinawa prefecture, Japan. J. Infect. Chemother. 2019, 25, 314–317. [Google Scholar] [CrossRef]
  32. Nakane, K.; Kawamura, K.; Goto, K.; Arakawa, Y. Long-Term Colonization by bla(CTX-M)-Harboring Escherichia coli in Healthy Japanese People Engaged in Food Handling. Appl. Environ. Microbiol. 2016, 82, 1818–1827. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  33. Manaia, C.M. Assessing the Risk of Antibiotic Resistance Transmission from the Environment to Humans: Non-Direct Proportionality between Abundance and Risk. Trends Microbiol. 2017, 25, 173–181. [Google Scholar] [CrossRef] [PubMed]
  34. Vaz-Moreira, I.; Nunes, O.C.; Manaia, C.M. Bacterial diversity and antibiotic resistance in water habitats: Searching the links with the human microbiome. FEMS Microbiol. Rev. 2014, 38, 761–778. [Google Scholar] [CrossRef] [PubMed]
  35. Kolmogorov, M.; Yuan, J.; Lin, Y.; Pevzner, P.A. Assembly of long, error-prone reads using repeat graphs. Nat. Biotechnol. 2019, 37, 540–546. [Google Scholar] [CrossRef] [PubMed]
  36. Li, H. Minimap and miniasm: Fast mapping and de novo assembly for noisy long sequences. Bioinformatics 2016, 32, 2103–2110. [Google Scholar] [CrossRef]
  37. Vaser, R.; Sovic, I.; Nagarajan, N.; Sikic, M. Fast and accurate de novo genome assembly from long uncorrected reads. Genome Res. 2017, 27, 737–746. [Google Scholar] [CrossRef]
  38. Hunt, M.; Silva, N.D.; Otto, T.D.; Parkhill, J.; Keane, J.A.; Harris, S.R. Circlator: Automated circularization of genome assemblies using long sequencing reads. Genome Biol. 2015, 16, 294. [Google Scholar] [CrossRef]
  39. Walker, B.J.; Abeel, T.; Shea, T.; Priest, M.; Abouelliel, A.; Sakthikumar, S.; Cuomo, C.A.; Zeng, Q.; Wortman, J.; Young, S.K.; et al. Pilon: An integrated tool for comprehensive microbial variant detection and genome assembly improvement. PLoS ONE 2014, 9, e112963. [Google Scholar] [CrossRef]
  40. Tanizawa, Y.; Fujisawa, T.; Nakamura, Y. DFAST: A flexible prokaryotic genome annotation pipeline for faster genome publication. Bioinformatics 2018, 34, 1037–1039. [Google Scholar] [CrossRef]
  41. Zankari, E.; Hasman, H.; Cosentino, S.; Vestergaard, M.; Rasmussen, S.; Lund, O.; Aarestrup, F.M.; Larsen, M.V. Identification of acquired antimicrobial resistance genes. J. Antimicrob. Chemother. 2012, 67, 2640–2644. [Google Scholar] [CrossRef]
  42. Chen, L.; Xiong, Z.; Sun, L.; Yang, J.; Jin, Q. VFDB 2012 update: Toward the genetic diversity and molecular evolution of bacterial virulence factors. Nucleic Acids Res. 2012, 40, D641–D645. [Google Scholar] [CrossRef]
  43. Carattoli, A.; Zankari, E.; Garcia-Fernandez, A.; Voldby Larsen, M.; Lund, O.; Villa, L.; Moller Aarestrup, F.; Hasman, H. In silico detection and typing of plasmids using PlasmidFinder and plasmid multilocus sequence typing. Antimicrob. Agents Chemother. 2014, 58, 3895–3903. [Google Scholar] [CrossRef] [PubMed]
  44. Souvorov, A.; Agarwala, R.; Lipman, D.J. SKESA: Strategic k-mer extension for scrupulous assemblies. Genome Biol. 2018, 19, 153. [Google Scholar] [CrossRef] [PubMed]
  45. Pierce, N.T.; Irber, L.; Reiter, T.; Brooks, P.; Brown, C.T. Large-scale sequence comparisons with sourmash. F1000Research 2019, 8, 1006. [Google Scholar] [CrossRef]
  46. Kurtz, S.; Phillippy, A.; Delcher, A.L.; Smoot, M.; Shumway, M.; Antonescu, C.; Salzberg, S.L. Versatile and open software for comparing large genomes. Genome Biol. 2004, 5, R12. [Google Scholar] [CrossRef]
  47. Reis-Cunha, J.L.; Bartholomeu, D.C.; Manson, A.L.; Earl, A.M.; Cerqueira, G.C. ProphET, prophage estimation tool: A stand-alone prophage sequence prediction tool with self-updating reference database. PLoS ONE 2019, 14, e0223364. [Google Scholar] [CrossRef]
  48. Li, H.; Durbin, R. Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics 2010, 26, 589–595. [Google Scholar] [CrossRef] [PubMed]
  49. Koboldt, D.C.; Chen, K.; Wylie, T.; Larson, D.E.; McLellan, M.D.; Mardis, E.R.; Weinstock, G.M.; Wilson, R.K.; Ding, L. VarScan: Variant detection in massively parallel sequencing of individual and pooled samples. Bioinformatics 2009, 25, 2283–2285. [Google Scholar] [CrossRef]
  50. Croucher, N.J.; Page, A.J.; Connor, T.R.; Delaney, A.J.; Keane, J.A.; Bentley, S.D.; Parkhill, J.; Harris, S.R. Rapid phylogenetic analysis of large samples of recombinant bacterial whole genome sequences using Gubbins. Nucleic Acids Res. 2015, 43, e15. [Google Scholar] [CrossRef]
  51. Price, M.N.; Dehal, P.S.; Arkin, A.P. FastTree 2--approximately maximum-likelihood trees for large alignments. PLoS ONE 2010, 5, e9490. [Google Scholar] [CrossRef]
  52. Hadfield, J.; Croucher, N.J.; Goater, R.J.; Abudahab, K.; Aanensen, D.M.; Harris, S.R. Phandango: An interactive viewer for bacterial population genomics. Bioinformatics 2018, 34, 292–293. [Google Scholar] [CrossRef]
  53. Letunic, I.; Bork, P. Interactive tree of life (iTOL) v3: An online tool for the display and annotation of phylogenetic and other trees. Nucleic Acids Res. 2016, 44, W242–W245. [Google Scholar] [CrossRef] [PubMed]
  54. Page, A.J.; Cummins, C.A.; Hunt, M.; Wong, V.K.; Reuter, S.; Holden, M.T.; Fookes, M.; Falush, D.; Keane, J.A.; Parkhill, J. Roary: Rapid large-scale prokaryote pan genome analysis. Bioinformatics 2015, 31, 3691–3693. [Google Scholar] [CrossRef] [PubMed]
  55. Maheshwari, M.; Yaser, N.H.; Naz, S.; Fatima, M.; Ahmad, I. Emergence of ciprofloxacin-resistant extended-spectrum beta-lactamase-producing enteric bacteria in hospital wastewater and clinical sources. J. Glob. Antimicrob. Resist. 2016, 5, 22–25. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Experimental procedures to isolate potential ESBL-producing bacteria. Sewage effluent samples were collected from eight WWTPs (WP1–WP9, and WP6 was treated as missing numbers owing to incorrect sampling locations) along the Tama River and around the Tokyo Bay (Table S1). Surface water from a recreational beach (BEC1) was used as an environmental control sample. Sampling was conducted during the summer and winter seasons for 2 years between August 2017 and February 2019 (Table S1).
Figure 1. Experimental procedures to isolate potential ESBL-producing bacteria. Sewage effluent samples were collected from eight WWTPs (WP1–WP9, and WP6 was treated as missing numbers owing to incorrect sampling locations) along the Tama River and around the Tokyo Bay (Table S1). Surface water from a recreational beach (BEC1) was used as an environmental control sample. Sampling was conducted during the summer and winter seasons for 2 years between August 2017 and February 2019 (Table S1).
Antibiotics 11 01283 g001
Figure 2. Core-genome SNVs phylogeny of E. coli ST131 isolates using publicly available ST131 draft or complete genome sequences (total 315 strains, see Table S4). Isolates in this study was highlighted by red in the strain name (see detail in Tables S2 and S3).
Figure 2. Core-genome SNVs phylogeny of E. coli ST131 isolates using publicly available ST131 draft or complete genome sequences (total 315 strains, see Table S4). Isolates in this study was highlighted by red in the strain name (see detail in Tables S2 and S3).
Antibiotics 11 01283 g002
Figure 3. Characterization of E. coli O16:H5-ST131 isolates from WWTP effluents. (A) Highlight image for E. coli O16:H5-ST131-fimH41 with blaCTX-M-27 from Figure 2. (B) Core genome SNV network, genome recombination, and pan-genome analysis of clonal O16:H5-ST131-fimH41 with blaCTX-M-27 strains. Isolates in this study were highlighted by red in the strain name (see detail in Tables S2 and S3).
Figure 3. Characterization of E. coli O16:H5-ST131 isolates from WWTP effluents. (A) Highlight image for E. coli O16:H5-ST131-fimH41 with blaCTX-M-27 from Figure 2. (B) Core genome SNV network, genome recombination, and pan-genome analysis of clonal O16:H5-ST131-fimH41 with blaCTX-M-27 strains. Isolates in this study were highlighted by red in the strain name (see detail in Tables S2 and S3).
Antibiotics 11 01283 g003
Figure 4. Core genome SNV phylogeny of other E. coli ST isolates from WWTP effluents. Isolates in this study was highlighted by red in the strain name (see detail in Tables S2 and S3).
Figure 4. Core genome SNV phylogeny of other E. coli ST isolates from WWTP effluents. Isolates in this study was highlighted by red in the strain name (see detail in Tables S2 and S3).
Antibiotics 11 01283 g004
Figure 5. Characterization of other CTX-M-positive bacteria from WWTP effluents. Core genome SNV network, genome recombination, and pan-genome analysis of (A) A. caviae and (B) K. quasipneumoniae isolates.
Figure 5. Characterization of other CTX-M-positive bacteria from WWTP effluents. Core genome SNV network, genome recombination, and pan-genome analysis of (A) A. caviae and (B) K. quasipneumoniae isolates.
Antibiotics 11 01283 g005
Figure 6. Plasmidome analysis of EPB and CPB isolates from WWTP effluents and environment. Nodes on the network are illustrated with different colors based on communities with sequence similarity, source, bla gene type, host bacteria genus, and its isolate location on the continent. The absolute counts for plasmids in plasmidome analysis are summarized in Table S7.
Figure 6. Plasmidome analysis of EPB and CPB isolates from WWTP effluents and environment. Nodes on the network are illustrated with different colors based on communities with sequence similarity, source, bla gene type, host bacteria genus, and its isolate location on the continent. The absolute counts for plasmids in plasmidome analysis are summarized in Table S7.
Antibiotics 11 01283 g006
Table 1. Whole-Genome Sequencing of CHROMagar ESBL-Positive Isolates Obtained from WWTPs.
Table 1. Whole-Genome Sequencing of CHROMagar ESBL-Positive Isolates Obtained from WWTPs.
Summer, 2017Winter, 2018Summer, 2018Winter, 2019Total
Total isolates9893109104404
EPB/CPB
E. coli1819181671
Klebsiella spp.812181048
Enterobacter spp.595423
Acinetobacter spp.10411126
Pseudomonas spp.2412202581
Aeromonas spp.1725252188
Others1612122767
β-lactamase type
CTX-M29353230126
IMP02226
KPC-2005 a38
NDM001 b12
GES154616
a [15,16]; b [17]; See the information of whole-genome sequence for all isolates in Table S2. EPB, extended-spectrum β-lactamase-producing bacteria CPB, carbapenemase-producing bacteria.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Sekizuka, T.; Tanaka, R.; Hashino, M.; Yatsu, K.; Kuroda, M. Comprehensive Genome and Plasmidome Analysis of Antimicrobial Resistant Bacteria in Wastewater Treatment Plant Effluent of Tokyo. Antibiotics 2022, 11, 1283. https://doi.org/10.3390/antibiotics11101283

AMA Style

Sekizuka T, Tanaka R, Hashino M, Yatsu K, Kuroda M. Comprehensive Genome and Plasmidome Analysis of Antimicrobial Resistant Bacteria in Wastewater Treatment Plant Effluent of Tokyo. Antibiotics. 2022; 11(10):1283. https://doi.org/10.3390/antibiotics11101283

Chicago/Turabian Style

Sekizuka, Tsuyoshi, Rina Tanaka, Masanori Hashino, Koji Yatsu, and Makoto Kuroda. 2022. "Comprehensive Genome and Plasmidome Analysis of Antimicrobial Resistant Bacteria in Wastewater Treatment Plant Effluent of Tokyo" Antibiotics 11, no. 10: 1283. https://doi.org/10.3390/antibiotics11101283

APA Style

Sekizuka, T., Tanaka, R., Hashino, M., Yatsu, K., & Kuroda, M. (2022). Comprehensive Genome and Plasmidome Analysis of Antimicrobial Resistant Bacteria in Wastewater Treatment Plant Effluent of Tokyo. Antibiotics, 11(10), 1283. https://doi.org/10.3390/antibiotics11101283

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop