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Article

Bacterial Hosts and Genetic Characteristics of Antibiotic Resistance Genes in Wastewater Treatment Plants of Xinjiang (China) Revealed by Metagenomics

by
Ziteng Liu
1,
Junqin Yao
1,*,
Huiying Ma
1,
Abudukelimu Rukeya
1,
Zenghui Liang
1,
Wenyan Du
1 and
Yinguang Chen
2
1
College of Ecology and Environment, Xinjiang University, Urumqi 830017, China
2
College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China
*
Author to whom correspondence should be addressed.
Appl. Sci. 2022, 12(6), 3100; https://doi.org/10.3390/app12063100
Submission received: 6 December 2021 / Revised: 10 March 2022 / Accepted: 15 March 2022 / Published: 18 March 2022
(This article belongs to the Special Issue Microbiology and Antibiotic Resistance in the Environment)
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Abstract

:
Antibiotic resistance genes (ARGs) pose a widespread concern for human health and wastewater treatment plants (WWTPs) are considered to be a major source of ARG transmission. In this paper, the potential hosts and genetic characteristics of ARGs in the influent, activated sludge and effluent of WWTPs in Xinjiang were studied by metagenomics. Bacitracin resistance gene (bacA), beta-lactamase gene (class A beta-lactamase), multidrug resistance genes (mexD, qacEdelta1), and sulfonamide resistance genes (sul1, and sul2) are persistent antibiotic resistance genes (PARGs). The potential hosts of ARGs were mainly pathogens, with Escherichia coli (12.9%), Acinetobacter johnsonii (8.94%), and Klebsiella pneumoniae (5.30%) accounting for the highest proportions. Chromosomal sequences and plasmid sequences accounted for 42.0% and 22.6% of ARG-carrying contigs (ACCs) in the influent, respectively. Meanwhile, the effluent contained 58.3% of ACCs in plasmids and 8.30% in chromosomes. Bacitracin resistance genes and multidrug resistance genes were mainly carried by chromosomes, while resistance genes for macrolide–lincosamide–streptogramin (MLS), vancomycin, sulfonamide, beta-lactam, tetracycline, chloramphenicol, and aminoglycoside were mainly carried by plasmids. ICEPae690-sul1-qacEdelta1 and ICEPmiChn3-sul2 were stable coexistence structures and heighten the transfer potential of ARGs in the environment. This study provided a clearer picture of host bacterial sources and genetic context of ARGs in the environment.

1. Introduction

The spread of antimicrobial resistance in the environment was declared a global public health threat by the WHO [1]. Wastewater treatment plants (WWTPs) are hotspots for antibiotic resistance gene (ARG) transmission since domestic sewage contains a variety of ARGs, high biomass and diverse microorganisms, and promote the exchange of ARGs through horizontal gene transfer (HGT) [2,3]. In particular, the persistent antibiotic resistance genes (PARGs), which are defined as ARGs that cannot be removed by wastewater treatment process, pose a threat to the spread of antibiotic resistance for the downstream environment [4].
The bacterial host is a major factor affecting the emergence and diversification of ARGs, and the identification of ARG hosts is essential for controlling antibiotic resistance [5,6]. The acquisition of ARGs by clinical pathogens such as ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species) contributes to the emergence and spread of antibiotic-resistant pathogens (ARPs) and poses a threat to human health [3]. Mobile genetic elements (MGEs) including plasmids, integrative and conjugative elements (ICEs), insertion sequences (ISs), and integrons can be transferred inside or between bacterial cells [7]. The ARGs carried by MGEs are easy to transfer even between bacteria from distant taxonomic lineages, thereby potentially generating new antibiotic-resistant bacteria (ARB) [8]. ARGs associated with MGEs have a higher risk of persisting in the environment [9]. The genetic characteristics of ARGs require further investigation to evaluate the transfer potential of ARGs.
Metagenomics is widely used to identify the abundance and removal rate of ARGs in WWTPs and is a powerful tool for ARG research [10,11,12]. Yang and collaborators used metagenomic sequencing to investigate the fate of ARGs in WWTP for the first time [4]. The host, removal rate, and enrichment of ARGs during wastewater treatment were also studied by metagenomics [13]. Luo et al. used metagenomics to study the difference in the abundance of ARGs and MGEs in different processes in a WWTP [14]. Previous approaches to ARG annotation commonly using short reads provided more diverse ARG annotation results. However, antibiotic resistance in the environment was inaccurate [15]. Therefore, contigs of sufficient length are required for accurate assembly and ARG identification to reveal the genomic background and potential hosts of ARGs [16]. This approach revealed the host and genetic location of ARGs in coastal beaches and sewage waters [17], the mobility of ARGs and bacterial hosts under antibiotic selection pressure [18], and the pathogenic host of ARGs in the foam of WWTPs [19]. However, few studies have investigated the genetic background of ARGs in Xinjiang, one of the driest regions in the world.
In this study, the potential host and genetic characteristics of ARGs in WWTPs of Xinjiang were studied based on metagenomic assembly. The main objectives were: (1) to understand the abundance and diversity of ARGs in WWTPs and to determine the persistent ARGs; (2) to track potential ARG hosts through the classification of ARG-carrying contigs (ACCs), especially ARG-carrying pathogens; (3) to predict the genetic position and the coexistence of ARGs; and (4) to investigate the coexistence structure between ARGs and MGEs and evaluate the transfer potential of ARGs. This study will provide useful insights into the potential hosts and genetic background of ARGs, leading to controlling the spread of ARGs in WWTPs.

2. Materials and Methods

2.1. Sample Collection, DNA Extraction, and Library Construction

Hexi (HX) WWTP (44.030° N, 87.356° E) and Changji (CJ) WWTP (43.963° N, 87.522° E) in Xinjiang (China) were selected for sample analysis. The design scales of HX and CJ WWTPs were 200,000 m3/d and 100,000 m3/d, respectively. Both WWTPs use the oxidation ditch process and ultraviolet disinfection, and the main influent is municipal sewage from Urumqi city and Changji city separately. Specific information on sample collection is provided in Table 1. On site, each sample was randomly mixed by collecting three subsamples at the sampling point to enhance the representativeness. The solids from influent samples were collected by centrifugation using a TDL-5-A centrifuge (Anting Scientific Instrument, Shanghai, China) at 4380× g for 10 min, while effluent samples were collected using vacuum filtration with a 0.22 μm cellulose nitrate membrane. All pre-treated samples were transported to the laboratory and immediately stored at −80 °C.
Total genomic DNA was extracted using the E.Z.N.A. Soil DNA Kit (Omega Bio-Tek, Norcross, GA, USA) according to the manufacturer’s instructions. The concentration and purity of extracted DNA were determined using a TBS-380 mini fluorometer (Invitrogen, Carlsbad, CA, USA) and NanoDrop2000 (Thermo Fisher Scientific, Wilmington, NC, USA) spectrophotometer, respectively. The DNA integrity was checked by 1% agarose gel electrophoresis at 5 V/cm for 20 min.
Extracted DNA was segmented into approximately 400 bp by a Covaris M220 Focused-ultrasonicator (Gene Company Limited, Hong Kong, China), and DNA fragments were used to construct a paired-end library via NEXTFLEX Rapid DNA-Seq (Bioo Scientific, Austin, TX, USA). Adapters containing the full complement of sequencing primer hybridization sites were ligated to the blunt ends of fragments.

2.2. Metagenomic Sequencing, Assembly, and Gene Prediction

Paired-end sequencing was performed on an Illumina NovaSeq 6000 system (Illumina Inc., San Diego, CA, USA) at Majorbio Bio-pharm Technology Co., Ltd. (Shanghai, China) using the paired-end 150 bp strategy. The raw metagenomic datasets were deposited into the NCBI SRA database (Accession number: PRJNA796130).
The paired-end Illumina reads were filtered to remove adaptors and low-quality reads (length < 50 bp, quality score < 20, or ambiguous nucleotides > 3) by fastp v0.20.1 [20]. Clean reads were assembled using MEGAHIT v1.2.9 (parameters: --k-list 21,29,39,59,79,99,119,141 and --min-contig-len 1000) [21]. Open reading frames (ORFs) were predicted on the resulting contigs by Prodigal v2.6.3 (parameter: -p meta) [22], generating over six million ORFs (Table S1, Supplementary Materials). Finally, Bowtie2 v2.3.3 was used to map clean reads to the ORF and calculate ORF coverage [23].

2.3. Identification of ARG-Like ORFs and ARG-Carrying Contigs

The predicted ORF sequences were aligned against the Structured ARG (SARG) database v2.2 (https://smile.hku.hk/SARGs, accessed on 16 August 2021) using BLASTX and sequences were annotated as ARG-like ORFs when BLASTX alignments had an E-value ≤ 10−10 and exceeded 80% similarity over 70% of the query coverages [18,24]. The relative abundances of ARGs were defined as ‘ppm’ (one read in one million reads) [5]. Contigs harboring ARG-like ORFs were annotated as ACCs.

2.4. Host Tracking, Genetic Location, and Coexistence Structure of MGEs and ARGs

Taxonomic identification of ACCs was determined using Kraken2 v2.0.7 [25] to identify the potential host of ARGs [26,27]. The classification results of the potential host carrying ARGs were visualized with Pavian [28]. ARPs were identified by reference to a bacterial pathogen list [29]. The relative abundance of potential hosts was calculated by Equation (1).
Relative   abundance = Na Nc × 100 % ,
Na represents the number of ACCs annotated as a potential host, and Nc represents the number of ACCs classified at the taxonomic level of this potential host.
The chromosomal and plasmid contigs carrying ARGs were predicted with Plasflow v1.1 using default settings [30]. The ORFs of ACCs were annotated following comparison with the IS database of ISfinder [31], Integron database of INTEGRALL [32], and ICE database of ICEberg [33] to investigate the coexistence structure of ARGs and MGEs in contigs. Only BLASTX values with an E-value ≤ 10−5 and identity ≥ 80% over a query coverage of ≥70% were retained [18]. The metagenomic analysis process and more detailed information of sequences are shown in Figure 1 and Table S1, respectively.

3. Results and Discussion

3.1. The Abundance and Diversity of ARGs

A total of 171 ARG subtypes were identified from 17 ARG types in HX WWTP with 48 multidrug resistance genes representing the most diverse ARG subtype (Figure S1A). This may be related to the widespread use of various antibiotics in hospitals, communities, and animal husbandry [34]. ARG diversity and abundance was the highest in the influent (144 ARG subtypes, 540.2 ppm), followed by activated sludge (45 ARG subtypes, 50.7 ppm), and effluent (11 ARG subtypes, 7.6 ppm) (Figure 2A and Figure S1B). This is unsurprising since the influent contained large amounts of ARBs and ARGs from urban wastewater [16,35]. The dominant influent ARG types were multidrug resistance genes, tetracycline, macrolide–lincosamide–streptogramin (MLS), and aminoglycoside, which is consistent with the findings of Shatin WWTP [4]. ARG distribution in the influent may reflect the average abundance and diversity of intestinal ARGs of residents in this area [36]. Sulfonamide is the most abundant ARG type in activated sludge, followed by multidrug resistance genes, tetracycline, and aminoglycoside. Changes in ARGs are mainly driven by MGEs in activated sludge [37]. The main ARG types in effluent after ultraviolet disinfection were multidrug resistance genes, bacitracin, and beta-lactam, which may be due to the resistance to common disinfection strategies. A recent study confirmed that bacitracin, multidrug, and beta-lactam resistance genes were the main ARG types in large drinking water treatment plants after the ozone and chlorine disinfection [11]. Multidrug resistance genes dominated in influent, activated sludge, and effluent because multidrug resistance is the natural state for most microorganisms to overcome environmental pressure [38].
PARGs are the most worrying ARG category because they cannot be removed by disinfection [11,26]. Moreover, PARGs entering the downstream environment present serious challenges [4,39] and may lead to the widespread occurrence of ARGs in the natural environment [40,41]. Eleven ARG subtypes from seven ARG types were PARGs including an aminoglycoside resistance gene (aadA), a bacitracin resistance gene (bacA), a beta-lactamase resistance gene (class A beta-lactamase), 2 MLS resistance genes (macB and mphA), 2 multidrug resistance genes (mexD and qacEdelta1), 2 sulfonamide resistance genes (sul1 and sul2) and a tetracycline resistance gene (tetA) in the HX WWTP (Figure 2B). The abundance of PARGs gradually decreased from influent to activated sludge and effluent, but the proportion of total abundance of ARGs significantly increased from 16.9% to 40.9% and 98.4%, respectively (Figure S2). The persistence of macB may be related to human activities and horizontal gene transfer between pathogens and local bacteria [42]. Furthermore, tetA is a recognized PARG in three WWTPs of Hong Kong, while aadA, bacA, sul1, and sul2 are often detected as PARGs in drinking water [11], lake water, and seawater [43]. Among them, sul1 and sul2 stably exist in hospital wastewater [44] and lakes [45,46] of Xinjiang. The corresponding samples (such as HX-INF and CJ-INF) had no significant difference in ARG type abundance (Kruskal–Wallis, p > 0.05) and six PARGs (bacA, class A beta-lactamase, mexD, qacEdelta1, sul1, and sul2) were shared in both locations (Figures S1–S3).

3.2. Host Tracking of ARGs

Identifying the potential hosts of ARGs is crucial for the risk assessment of the spread of antibiotic resistance [47]. Potential ARG hosts in HX WWTP were classified into seven phyla with Proteobacteria accounting for more than 70% (Figure 3A). This correlated with previous studies showing that ARGs in WWTP sludge are mainly carried by Proteobacteria, and this phylum contains a variety of human pathogens [26,48]. A total of 91 genera carrying ARGs were identified, with the majority represented by Acinetobacter (21.1%), Escherichia (11.6%), and Klebsiella (7.71%) (Figure 3A).
The classifiable ACCs belonged to 119 bacterial species (Table S2) with six of the top 10 species carrying ARGs classified as pathogens, including Bacteroides fragilis, Acinetobacter johnsonii, Escherichia coli, A. baumannii, K. pneumoniae, and P. aeruginosa (Figure 3A). The last three species mentioned belong to ESKAPE pathogens and carry a variety of ARGs (Table 2). These ESKAPE pathogens are the key microorganisms for high-risk ARGs to spread in the environment, and they are the main cause of nosocomial infections worldwide [41,49]. E. coli was the most abundant potential host (12.9%) of ARGs and carried the most diverse ARG subtypes (40) in HX WWTP followed by A. johnsonii (8.94%, 13 ARG subtypes), and K. pneumoniae (5.30%, 16 ARG subtypes) (Figure 3A; Table 2). E. coli was the most prevalent resistant pathogen in a hospital study in Xinjiang [50], and this organism easily acquires multidrug resistance genes [51], including acrA, mdtO, mdtH, and mdtL [36,52], which is consistent with our results (Table 2). E. coli and K. pneumoniae carried ARGs from at least seven ARG types and expressed resistance to multiple antibiotics (Figure 3B). A. johnsonii carried over 80% of multidrug resistance genes harboring abeS, adeJ, adeK, emrB, mdfA, mdtK, mexB, mexT, oprM, and TolC in this study (Table 2), and Acinetobacter is a potential host for adeK [53]. Approximately 84.5% of B. fragilis carried ermF and tetQ genes, which confer resistance to MLS and tetracycline antibiotics (Figure 3B; Table 2). This type of resistance was similarly observed in Bacteroides from human intestinal and pig manure samples [6]. Bacteroides mainly carry tetQ [36], with the proportion of tetQ in Bacteroides increasing sharply from 30% to over 80% because of HGT [54]. More than half of P. aeruginosa carried class A beta-lactamase and OXA-101 (Figure 3B; Table 2). P. aeruginosa is a well-known and difficult-to-treat pathogen that may cause serious infection and disease [55] and is the most dominant ARP among agricultural WWTP, carrying 20 ARG subtypes [19].
Out of the six widespread PARGs in Xinjiang WWTPs, 60% of class A beta-lactamase-carrying contigs belong to P. aeruginosa (Table S2). Additionally, about half of qacEdelta1-carrying contigs and all sul1-carrying contigs were derived from K. pneumoniae (Table S2). Similar results were obtained in CJ WWTP (Figure S4; Tables S2 and S3). The reason that pathogens were the major hosts of ARGs in Xinjiang WWTPs may be due to two reasons: WWTPs contain significant loads of human pathogens which may spread to surrounding rivers and soil [56,57], and pathogens with no ARGs tend to acquire them under antibiotic selective pressure, while pathogens previously containing ARGs preferentially survive and are enriched in the population [57]. Pathogens carrying ARGs may cause multiple-disease resistance and pose a more serious threat to human health than non-pathogenic bacteria [9]. E. coli was the most abundant ARP in CJ WWTP and accounted for 15.4% (Figure S4A). P. aeruginosa and K. pneumoniae were the presumed hosts of three PARGs (class A beta-lactamase, qacEdelta1 and sul1) in CJ WWTP which is consistent with HX WWTP (Table S2). Furthermore, K. pneumoniae and P. aeruginosa persist in the influent, activated sludge, and effluent of HX and CJ WWTPs (Figure S5) which is consistent with other WWTPs [48]. This indicated that these two ESKAPE pathogens have a high probability of entering the receiving environment and promoting the spread of ARGs. More effective effluent disinfection methods should be studied to prevent ARB and ARPs from entering the receiving environment, especially considering their regeneration and reactivation [58,59].
Meanwhile, a few non-pathogenic species showed multidrug resistance and resistance to bacitracin: Acidovorax sp. 1608163 and Acidovorax sp. KKS102 (Figure 3 and Figure S4). Non-pathogenic environmental species are important ARG carriers and the potential risk of these species to the spread of antibiotic resistance needs further evaluation [47].

3.3. Genetic Location of ARGs

The genetic location of ARGs in the influent, activated sludge, and effluent of HX WWTP was variable (Figure 4A). The influent contained 42.2% of ACCs from chromosome sequences, and only 22.6 % were plasmid sequences (Figure 4A). This differed from the genetic location of ARGs in the influent of Hong Kong WWTPs, with 30.6% from chromosomes and 55.3% of ACCs derived from plasmids and ICEs [48], and may be related to the diverse antibiotic pressure on ARGs in different regions. Antibiotic selection pressure significantly increased the abundance and proportion of plasmid-related ARGs [18]. The proportion of chromosomal ACCs and plasmid ACCs gradually decreased and increased, respectively, in activated sludge and effluent. The effluent had the highest proportion of plasmid ACCs (58.3%), with 8.3% of chromosomal ACCs (Figure 4A). This indicated that plasmid-related ARGs may be mobile and HGT occurred in the activated sludge. Moreover, plasmid-related ARGs are approximately two-fold more likely to be transcriptionally expressed than chromosome-related ARGs in Taiwan WWTPs [60].
Bacitracin and multidrug resistance genes were mostly carried by chromosomes, while MLS, vancomycin, sulfonamide, beta-lactam, tetracycline, chloramphenicol, and aminoglycoside resistance genes were mainly carried by plasmids (Figure 4B). This agrees with previous work showing that multidrug resistance genes are primarily located on chromosomes [18,19] and the transcript abundance of aminoglycoside, sulfonamide, and tetracycline resistance genes are mainly contributed by plasmid-related ARGs [60]. Bacitracin resistance genes tend to be chromosomally coded, probably because bacitracin resistance genes are inherent in bacteria [11]. The ARG types carried by plasmids are closely linked to commonly used antibiotics in humans: aminoglycoside, beta-lactam, MLS, sulfonamide, and tetracycline.
The vast majority of ACCs carry only one ARG with only 9% of ACCs carrying at least two ARGs (Figure S6). There was a tendency for multiple ARGs to be located on the same contig in this study, which was previously suggested to be driven by the same resistance mechanism [10]. For example, the multidrug efflux protein combination adeC-adeJ-adeK and multidrug transporter mdtB-mdtC was observed in the influent (Table S2). Similarly, fosmidomycin resistance (rosA-rosB) and MLS resistance (macA-macB) were observed, amongst others (Table S2). macB and macA gene products form an ATP-binding cassette (ABC) transporter, which is ubiquitous in chicken manure, pig manure, influent, and human intestinal samples [52]. In activated sludge and effluent, most of the ARG combinations were composed of different ARG types, such as the chloramphenicol, sulfonamide, and tetracycline resistance gene combination (floR-sul1-tetG; Table S4). The different ARGs co-located on the same contig enhance the spread of multidrug resistance. The co-occurrence mechanism of ARG subtypes is common in various environments such as tetA-aph(3′)-VIb-aph(3″)-Ib-aph(6)-Id from a WWTP [61], sul1-cat-aac(6′)-Ib from pKp368/10 plasmid [62], aadA5-dfrA17 of chicken feces [52], and aadA-aacA4-blaOXA-10 from a gene cassette [63]. Similarly, results were observed in CJ WWTP (Figures S6 and S7; Table S4), demonstrating that the wastewater treatment plants in Xinjiang have the same genetic background as ARGs.

3.4. The Coexistence Structure of PARGs with MGEs

The co-occurrence frequency and genetic association of ARGs (and especially PARGs) and MGEs shows the transfer potential of ARGs as the treated sewage directly enters the receiving environment. The plasmid-related ARGs were more likely to coexist with MGEs. In HX WWTPs, most of the ACCs containing MGEs were plasmid sequences with only approximately 13% identified as chromosomal sequences (Figure S8). Plasmids are frequently transferred to new hosts even in the absence of selective pressure [64] and the combination of MGEs and plasmids facilitates the accumulation of ARGs in the environment, leading to widespread antibiotic resistance [7,48,65]. Plasmids and integrons easily recombine [66], and integrons share a gene cassette containing multiple ARGs, which is an important mechanism for multidrug resistance [67]. Class 1 integrons are the most common type of antibiotic-resistant clinical isolates [7], and class 1 integron carrying ARGs are found in a variety of water environments [52,68]. In this study, multiple contigs carry the class 1 integrase gene (intI1) and at least one gene cassette, such as the intI1-tnpA-orf1-tetG-tetR-floR-sul1 integron structure (Table S4). The interaction between different MGEs supports the rapid evolution of multidrug-resistant pathogens, and this requires further attention [7].
PARGs were divided into two categories according to the different potentials of HGT. The first type had low HGT potential because they do not coexist on the same contig with MGEs, such as the bacitracin resistance gene (bacA) and the multidrug resistance gene (mexD) (Table S2). The second type had high HGT potential with coexisting MGE combinations in separate compartments of the WWTP (Figure 5; Table S2) harboring class A beta-lactamase, qacEdelta1, sul1, and sul2. Coexistence combinations with sul1 and sul2 as the core ARGs were widely distributed in the WWTP, and ICEs were the most frequently occurring ARG-MGE combination (Figure 5; Table S2). For instance, the ICE6440-ICEPae690-sul1-qacEdelta1 and ICEPmiChn3-sul2 coexistence structures were observed in the influent, activated sludge, and effluent of HX WWTP, and K. pneumoniae may be a potential host for the combination of ICE6440-ICEPae690-sul1-qacEdelta1 (Figure 5). Meanwhile, there were frequent ARG-MGE combinations of aph(6)-I-aph(3″)-I-Tn5393-ICEKkKWG1 and class A beta-lactamase-ICE6440 (Figure S9). A fixed combination of the aph(3″)-I-aph(6)-I homolog, strA-strB was observed in wastewater under the pressure of five antibiotics [18]. ICEs are widespread in WWTPs and are the important medium for the transfer of various ARGs between human pathogens and environmental bacteria [48]. ICE carries out conjugative transfer between species and accumulates ISs or transposons on its border, and transfers them through conjugation [69,70]. Bacteria that carry both ICEs and ARGs show stronger adaptability to high concentrations of antibiotics and have a higher risk potential for causing disease than bacteria that do not carry ICEs [71]. A similar pattern was found in CJ WWTP (Figures S8–S10) with the widespread PARG-MGE coexistence structure in Xinjiang WWTP, possibly explaining their persistence. The high-frequency co-occurrence of ICEs and PARGs revealed the high transfer potential and increased the risk of PARGs in WWTP.

4. Conclusions

The presence of bacA, class A beta-lactamase, mexD, qacEdelta1, sul1 and sul2 as PARGs reveals the risk of antibiotic resistance in the WWTPs of Xinjiang. The main ARG hosts were E. coli (12.9%), A. johnsonii (8.94%) and K. pneumoniae (5.30%), which may pose a threat to human health. ARGs were mainly located on the chromosome in the influent, while activated sludge and effluent predominantly contained plasmid-localized ARGs. Most ARG types were carried by plasmids except bacitracin and multidrug resistance genes, which were mainly carried by chromosomes. There was a high frequency of stable ARG-ICE coexistence structures on ACCs such as ICEPae690-sul1-qacEdelta1 and ICEPmiChn3-sul2, indicating that there is a high risk of HGT of ARGs leading to the rapid spread of antibiotic resistance in the receiving environment. This work showed the potential hosts and genetic characteristics of ARGs in WWTPs in Xinjiang and highlights an urgent need to limit the use of antibiotics and devise strategies to control the spread of ARGs, including improving sterilization methods in wastewater.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/app12063100/s1, Table S1: Summary statistics for reads and contigs generated by metagenomic sequencing, Table S2: The information of ARG-carrying contigs as well as the genetic location and hosts of ARGs, Table S3: Pathogens in Figure S4A carry specific information about ARGs in CJ WWTP, Table S4: Co-occurrence of ARGs and MGEs, Figure S1: The diversity of ARG subtypes from different ARG types (A) and different samples (B), Figure S2: The relative abundance of persistent ARGs and the percentage of total ARG abundance, Figure S3: Summary of antibiotic resistance genes (ARGs) in the influent (INF), activated sludge (AS), and effluent (EFF) of Changji (CJ) wastewater treatment plant (WWTP). (A) Relative abundance of the ARG types. (B) Relative abundance and distribution of persistent ARGs, Figure S4: The potential host information of ARGs in CJ WWTP. (A) Phylogenetic tree representing the composition and relative abundance of the top 10 ARG potential hosts from the domain level (D), to the phylum (P), class (C), genus (G), and species (S) level. Branch width represents the relative abundance of the corresponding ARG potential hosts. Larger bold fonts represent antibiotic resistance pathogens (ARPs). (B) The bar chart shows the diversity and relative abundance of ARG types carried by hosts at the species level in (A), Figure S5: The Venn diagram shows the ARBs shared by all samples, Figure S6: The percentage of contigs carrying one and at least two ARGs, Figure S7: Genetic location of ARGs in CJ WWTP. (A) The percentage of ARG-carrying contigs belonged to plasmid, chromosomal and unclassified sequences in the influent, activated sludge, and effluent. (B) Genetic location and frequency of ARGs were carried by chromosomes or plasmids summarized by ARG type, Figure S8: The percentage of ACCs with MGEs detected in each sample, Figure S9: The aph(6)-I-aph(3′’)-I-Tn5393-ICEKkKWG1 (A) and class A beta-lactamase-ICE6440 (B) coexistence structures in two WWTPs, Figure S10: Arrangements of PARG-carrying contigs with MGEs and their putative hosts in CJ WWTP. The ICE6440-ICEPae690-sul1-qacEdelta1 (A) and ICEPmiChn3-sul2 (B) coexistence structures in the influent, activated sludge, and effluent.

Author Contributions

Conceptualization, J.Y. and Y.C.; Data curation, J.Y.; Funding acquisition, J.Y.; Investigation, Z.L. (Ziteng Liu), H.M., A.R., Z.L. (Zenghui Liang) and W.D.; Methodology, Z.L. (Ziteng Liu) and Y.C.; Project administration, J.Y. and Y.C.; Resources, J.Y., H.M. and A.R.; Software, Z.L. (Ziteng Liu); Supervision, J.Y.; Visualization, Z.L. (Ziteng Liu); Writing—original draft, Z.L. (Ziteng Liu); Writing—review and editing, Z.L. (Ziteng Liu), J.Y. and Y.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by National Natural Science Foundation of China (Grant No. 52160005) and Natural Science Foundation of Xinjiang of China (Grant No. 2021D01C047).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The metagenomic datasets can be found into the NCBI SRA database (Accession number: PRJNA796130).

Conflicts of Interest

The authors declare no conflict of interest.

Abbreviations

ACCARG-carrying contig
A. baumanniiAcinetobacter baumannii
A. johnsoniiAcinetobacter johnsonii
ARBAntibiotic-resistant bacteria
ARGAntibiotic resistance gene
ARPAntibiotic-resistant pathogen
ASActivated sludge
B. fragilisBacteroides fragilis
EFFEffluent
E. coliEscherichia coli
HGTHorizontal gene transfer
ICEIntegrative and conjugative element
INFInfluent
ISInsertion sequence
K. pneumoniaeKlebsiella pneumoniae
MGEMobile genetic element
MLSMacrolide–lincosamide–streptogramin
ORFOpen reading frame
PARGPersistent antibiotic resistance gene
P. aeruginosaPseudomonas aeruginosa
WWTPWastewater treatment plant

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Applsci 12 03100 g001 550
Figure 1. Analysis pipeline of this study. Sequences with the same color may be derived from the same DNA fragment. ORF: open reading frame, ARG: antibiotic resistance gene, MGE: mobile genetic element.
Figure 1. Analysis pipeline of this study. Sequences with the same color may be derived from the same DNA fragment. ORF: open reading frame, ARG: antibiotic resistance gene, MGE: mobile genetic element.
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Figure 2. Summary of ARGs in the influent (INF), activated sludge (AS), and effluent (EFF) of HX WWTP. (A) Relative abundance of the ARG types. (B) Relative abundance and distribution of persistent ARGs. ppm: one read in one million reads.
Figure 2. Summary of ARGs in the influent (INF), activated sludge (AS), and effluent (EFF) of HX WWTP. (A) Relative abundance of the ARG types. (B) Relative abundance and distribution of persistent ARGs. ppm: one read in one million reads.
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Figure 3. The potential host information of ARGs in HX WWTP. (A) Phylogenetic tree representing the composition and relative abundance of the top 10 ARG potential hosts from the domain level (D), to the phylum (P), class (C), genus (G), and species (S) levels. Branch width represents the relative abundance of the corresponding ARG potential hosts. Larger bold fonts represent antibiotic-resistant pathogens (ARPs). (B) The bar chart shows the diversity and relative abundance of ARG types carried by potential hosts at the species level in (A). MLS: macrolide–lincosamide–streptogramin.
Figure 3. The potential host information of ARGs in HX WWTP. (A) Phylogenetic tree representing the composition and relative abundance of the top 10 ARG potential hosts from the domain level (D), to the phylum (P), class (C), genus (G), and species (S) levels. Branch width represents the relative abundance of the corresponding ARG potential hosts. Larger bold fonts represent antibiotic-resistant pathogens (ARPs). (B) The bar chart shows the diversity and relative abundance of ARG types carried by potential hosts at the species level in (A). MLS: macrolide–lincosamide–streptogramin.
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Figure 4. Genetic location of ARGs in HX WWTP. (A) The percentage of ACCs belonged to plasmid, chromosomal and unclassified sequences in the influent, activated sludge, and effluent. (B) Genetic location and frequency of ARGs were carried by chromosomes or plasmids summarized by ARG type.
Figure 4. Genetic location of ARGs in HX WWTP. (A) The percentage of ACCs belonged to plasmid, chromosomal and unclassified sequences in the influent, activated sludge, and effluent. (B) Genetic location and frequency of ARGs were carried by chromosomes or plasmids summarized by ARG type.
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Figure 5. Arrangements of PARG-carrying contigs with MGEs and their potential hosts in HX WWTP. The ICE6440-ICEPae690-sul1-qacEdelta1 (A) and ICEPmiChn3-sul2 (B) coexistence structures in the influent, activated sludge, and effluent.
Figure 5. Arrangements of PARG-carrying contigs with MGEs and their potential hosts in HX WWTP. The ICE6440-ICEPae690-sul1-qacEdelta1 (A) and ICEPmiChn3-sul2 (B) coexistence structures in the influent, activated sludge, and effluent.
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Table
Table 1. Sample information collection.
Table 1. Sample information collection.
SamplesTemperature (°C)pHDO (mg/L)MLSS (mg/L)SVISampling PointCollection Date
HX-INF19.37.7---Distribution well29 September 2020
HX-AS18.27.21.44356108Aerobic zone
HX-EFF19.16.7---Outlet
CJ-INF17.96.5---Distribution well
CJ-AS17.56.82.34401160Aerobic zone
CJ-EFF18.26.2---Outlet
DO: Dissolved Oxygen; MLSS: Mixed Liquor Suspended Solids; SVI: Sludge Volume Index.
Table
Table 2. Pathogens in Figure 3A carry specific information about ARGs in HX WWTP.
Table 2. Pathogens in Figure 3A carry specific information about ARGs in HX WWTP.
ARPACCsCarrying ARG Subtypes
Escherichia coli39aminoglycoside: aph(3″)-I, aph(6)-I, aac(3)-II; bacitracin: bacA; beta-lactam: TEM-1; fosmidomycin: rosA, rosB; kasugamycin: ksgA; MLS: macA; multidrug: acrA, acrB, bcr, emrA, emrB, emrD, emrE, emrK, mdfA, mdtA, mdtB, mdtC, mdtD, mdtE, mdtF, mdtG, mdtH, mdtK, mdtL, mdtM, mdtN, mdtO, mdtP, TolC; polymyxin: arnA; sulfonamide: sul2; tetracycline: tet34; unclassified: CpxR, gadX, H-NS, sdiA
Acinetobacter johnsonii27beta-lactam: OXA-211, OXA-309; MLS: macB; multidrug: abeS, adeJ, adeK, emrB, mdfA, mdtK, mexB, mexT, oprM, TolC
Klebsiella pneumoniae *16aminoglycoside: aadA; beta-lactam: CTX-M, penA, VEB-3; chloramphenicol: catB; MLS: mphA; multidrug: acrA, acrB, mdtB, mdtG, mdtK, mdtL, mdtN, qacEdelta1; sulfonamide: sul1; tetracycline: tet34
Pseudomonas aeruginosa *6beta-lactam: class A beta-lactamase, OXA-10, OXA-101; tetracycline: tetA
Bacteroides fragilis6MLS: ermF; multidrug: abeS; tetracycline: tetQ
Acinetobacter baumannii *5beta-lactam: CARB-8, OXA-58; multidrug: adeB; tetracycline: tet39
* ESKAPE pathogens. ACCs: ARG-carrying contigs.
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Liu, Z.; Yao, J.; Ma, H.; Rukeya, A.; Liang, Z.; Du, W.; Chen, Y. Bacterial Hosts and Genetic Characteristics of Antibiotic Resistance Genes in Wastewater Treatment Plants of Xinjiang (China) Revealed by Metagenomics. Appl. Sci. 2022, 12, 3100. https://doi.org/10.3390/app12063100

AMA Style

Liu Z, Yao J, Ma H, Rukeya A, Liang Z, Du W, Chen Y. Bacterial Hosts and Genetic Characteristics of Antibiotic Resistance Genes in Wastewater Treatment Plants of Xinjiang (China) Revealed by Metagenomics. Applied Sciences. 2022; 12(6):3100. https://doi.org/10.3390/app12063100

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Liu, Ziteng, Junqin Yao, Huiying Ma, Abudukelimu Rukeya, Zenghui Liang, Wenyan Du, and Yinguang Chen. 2022. "Bacterial Hosts and Genetic Characteristics of Antibiotic Resistance Genes in Wastewater Treatment Plants of Xinjiang (China) Revealed by Metagenomics" Applied Sciences 12, no. 6: 3100. https://doi.org/10.3390/app12063100

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Liu, Z., Yao, J., Ma, H., Rukeya, A., Liang, Z., Du, W., & Chen, Y. (2022). Bacterial Hosts and Genetic Characteristics of Antibiotic Resistance Genes in Wastewater Treatment Plants of Xinjiang (China) Revealed by Metagenomics. Applied Sciences, 12(6), 3100. https://doi.org/10.3390/app12063100

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