Water Research 187 (2020) 116450
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Unveiling dynamics of size-dependent antibiotic resistome associated with microbial communities in full-scale wastewater treatment plants Kaifeng Yu a, Peng Li a, Yiliang He a,b,∗, Bo Zhang a, Yihan Chen c, Jinghan Yang d a
School of Environmental Science & Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, China. Shanghai Institute of Pollution Control and Ecological Security, 800 Dongchuan Road, Shanghai 200240, China c School of Resources and Environmental Engineering, Hefei University of Technology, Hefei 246011, China d School of Environmental and Municipal Engineering, Lanzhou Jiao Tong University, Lanzhou 730070, China b
a r t i c l e
i n f o
Article history: Received 27 April 2020 Revised 31 August 2020 Accepted 22 September 2020 Available online 23 September 2020 Keywords: antibiotic resistance genes particle-associated assemblages free-living bacteria cell-free DNA wastewater
a b s t r a c t Serious concerns have been raised regarding antibiotic resistance genes (ARGs) with respect to their potential threat to human health. Wastewater treatment plants (WWTPs) have been considered to be hotspots for ARGs. In this study, high-throughput quantitative polymerase chain reaction (HT-qPCR) was used to proﬁle size-dependent ARGs and mobile genetic elements (MGEs) divided by particle-associated (PA) assemblages (>3.0-μm), free-living (FL) bacteria (0.2 - 3.0-μm) and cell-free (CF) DNA (< 0.2-μm) in two full-scale WWTPs (plants A and B) and a receiving stream. The results revealed that FL-ARGs were predominant in WWTPs and the receiving stream, especially in the ﬁnal eﬄuent of both plants. More than 40 types of CF-ARGs and CF-MGEs were detected with absolute abundances ranging from 6.0 ± 0.7 × 105 to 1.0 ± 0.2 × 108 copies/mL in wastewater, and relatively high abundances were also detected in the ﬁnal eﬄuent of the two plants, suggesting that CF-ARGs were important sources spreading from the WWTPs to the receiving environment. Plant A exhibited higher log-removal of size-fractionated ARGs and MGEs than was observed for plant B, which was attributed to the enhanced settleability of PA assemblages and FL bacteria by additional macrophytes and chemical coagulants. Ultraviolet disinfection had limited effects on ARGs and MGEs of the PA and FL fractions, which was probably ascribed to the protective matrices of the particles and cell walls. The bacterial communities of the two plants were signiﬁcantly different among the size fractions (p < 0.01). The variation partitioning analysis (VPA) indicated that the microbial community structures and MGEs contributed a variation of 68.2% in total to the relative abundance changes of size-fractionated ARGs. Procrustes analyses and Mantel tests showed that the relative abundances of ARGs were signiﬁcantly correlated with bacterial community structures. These results suggested that the bacterial community structures and MGEs might have been the main drivers of the size-fractionated ARG disseminations. This study provides novel insights into size-fractionated ARGs and MGEs in full-scale WWTPs and may lead to the identiﬁcation of key targets to control the spread of ARGs. © 2020 Elsevier Ltd. All rights reserved.
1. Introduction Antibiotic resistance genes (ARGs) are emerging contaminants that have caused public concern due to their potential threat to human health, and the situation has worsened in recent years concomitant with an increased risk of no eﬃcacious medicine being available (WHO, 2014). Wastewater treatment plants (WWTPs) have been considered to be hotspots of ARGs not only because they receive domestic or hospital wastewater sources
∗ Corresponding author at: School of Environmental Science & Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, China. E-mail address: [email protected]
https://doi.org/10.1016/j.watres.2020.116450 0043-1354/© 2020 Elsevier Ltd. All rights reserved.
(Caucci et al., 2016; Quintela-Baluja et al., 2019), but also because they discharge eﬄuent containing diverse ARGs with relatively high loads (Lee et al., 2017). Furthermore, bacteria frequently detected in WWTPs can be the hosts of diverse ARGs (Haaber et al., 2016), which may threaten human health through direct or indirect pathways (Cai & Zhang, 2013). Particles are important carriers of nutrients and microorganisms (Chahal et al., 2016). Some types of bacteria tend to form bioﬁlm or become attached to particles (An et al., 2016), which can be classiﬁed as particle-associated (PA) assemblages (Ganesh et al., 2014; Gonsalves et al., 2017), while others are prone to a freeliving (FL) lifestyle with no association with inorganic substances (Huang et al., 2018). Full size-fractionated analyses are frequently
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conducted in investigations of communities of marine and riverine microorganisms (D’Ambrosio et al., 2014; Jackson et al., 2014; Savio et al., 2015). The results have indicated that microbial community structures are signiﬁcantly different between PA assemblages and FL bacteria. Particle integrity and residence time likely contributed to the differences between the PA and FL bacterial communities in coastal North Carolina (D’Ambrosio et al., 2014). In the Mississippi River Basin, the differences between the two fractions may be ascribed to the proportional abundances of major bacterial lineages (such as Alphaproteobacteria, Cyanobacteria, and Planctomycetes) (Jackson et al., 2014). However, little is known regarding the dynamics of antibiotic resistome abundances inﬂuenced by different bacterial forms in activated sludge systems or eﬄuent receiving streams. The effects of small-sized microbes on the fate of ARGs in water was recently studied, but this investigation was limited to a narrow size range (0.2 - 0.45 μm) (Ma et al., 2019). Investigations of microorganisms based on their sizes may be conducive to promoting a fundamental understanding of ARG dissemination among different fractions. However, few studies have investigated bacteria harboring ARGs and mobile genetic elements (MGEs) with respect to different size fractions. Although previous studies have investigated intracellular and extracellular ARGs (Liu et al., 2018; Sui et al., 2019), intracellular DNA is still needed to be further separated to unveil possible fundamental understanding. A recent study demonstrated that FL bacteria cannot be effectively removed in WWTPs (Huang et al., 2018). Different pore-sizes, such as 3.0-μm (Guo et al., 2018), 5.0-μm (Rieck et al., 2015) and 10.0-μm (Riemann & Winding, 2001), have been used to distinguish PA from FL bacteria, while a pore size of 3.0-μm has been widely used to separate PA assemblages from FL bacteria (D’Ambrosio et al., 2014; Garneau et al., 2009; Guo et al., 2018; Jackson et al., 2014; Milici et al., 2016; Savio et al., 2015). Therefore, this convention was used in our study. Except for ARGs in the PA and FL fractions, extracellular DNA, here deﬁned as cell-free (CF) DNA, passes through 0.22-μm poresized ﬁlters and potentially harbors ARGs, which may pose potential risks to the receiving environment (Zhang et al., 2018). This has rarely been studied. Cell-free DNA can be released by cellassociated bacteria after their decay and lysis, which is a common occurrence during wastewater treatment, thereby resulting in its ubiquitous presence in the ﬁnal eﬄuent together with resistance genes encoded enzymes in living cells. Although a recent study investigated CF DNA, only four ARGs and no MGEs were targeted to assess their occurrence and dissemination in WWTPs (Zhang et al., 2018), which is far fewer than the known ARG subtypes (Stedtfeld et al., 2018). To the best of our knowledge, no previous studies have systematically investigated the full sizefractionated antibiotic resistome with respect to PA, FL and CF ARGs in WWTPs. In this study, high-throughput quantitative polymerase chain reaction (HT-qPCR) was used to target 283 major ARGs and 12 MGEs to assess the proliferation of ARGs and MGEs among PA assemblages, FL bacteria and CF DNA in two full-scale WWTPs and a receiving stream. This research aimed to 1) investigate the diversity and distribution of ARGs and MGEs among size-fractionated bacteria in the WWTPs and an eﬄuent-receiving stream; 2) reveal the co-occurrence patterns of ARGs and MGEs among PA assemblages, FL bacteria and CF DNA; and 3) reveal the dynamics of structures of size-fractionated bacterial communities and their possible relationships with ARGs and MGEs.
2. Materials and methods 2.1. Sampling and pretreatment In our previous study (Yu et al., 2020), although the relative abundances of ARGs were reduced in a tridimensional ecobiological WW TP (TEB-WW TP; E 114°39’28.77”, N 23°37’39.64”; marked as plant A), ARGs and MGEs were still abundant in the ﬁnal eﬄuent. To further decipher the occurrences and dynamics of ARG abundance in wastewater treatment system, we selected this TEB-WWTP to conduct size-fractionated investigations. Plant A was rebuilt from the anaerobic-anoxic-oxic (AAO) process by adding internal bio-modules and macrophytes on top of the biological reactors in 2013. As a control, another WWTP (plant B) running the conventional AAO process with no macrophytes, located in the same city of Heyuan (Guangdong Province), southern China (E 114°41’54.52”, N 23°43’4.20”), was selected in this study. In addition, plant A executes a higher discharge standard than that of plant B (Table S1). We attempted to determine whether different treatment levels can affect the fate of size-fractionated resistance genes. The design parameters of the two WWTPs are presented in Tables S2 and in a previous study (Yu et al., 2020). Water samples were collected from six sites along the treatment processes of plants A and B including the inﬂuent (S1), biological reactor eﬄuent (S4), second sedimentation tank (SST) eﬄuent (S5) and ﬁnal eﬄuent (S6), respectively. In the biological reactors of both plants, activated sludge (AS) samples were obtained from the anoxic tank (S2) and aerobic tank (S3), respectively. To evaluate the impact of treated eﬄuent on the receiving stream, water samples were also collected before (G2) and after (G3 and G4) the discharge site from plant A (Table S3, Fig. S1). Both the obtained water and activated sludge samples were transported on ice within 1 h to the laboratory in plant A. PH value, dissolved oxygen (DO) and temperature were measured in situ using portable device (HQ30d, HACH, USA). As numerous studies have adopted 3.0-μm and 0.2-μm poresizes to divide the two fractions (D’Ambrosio et al., 2014; Guo et al., 2018; Milici et al., 2016; Savio et al., 2015), we used these sizes in our study. Wastewater samples were ﬁrst ﬁltered through 3.0-μm pore-sized polycarbonate membranes (Millipore, Ireland) to intercept PA assemblages. The ﬁltrates were then ﬁltered through 0.22-μm polycarbonate membranes (Millipore) to collect the FL bacteria. The membranes were cut into pieces and transferred to 50 mL centrifuge tubes for further processing. Separation of the PA- and FL-fractions was completed within 24 h. The tubes were stored at -20°C before DNA extraction. The ﬁnal ﬁltrates (through 0.22-μm membranes) were used to extract CF DNA according to previous studies (Eichmiller et al., 2016; Ficetola et al., 2008; Zhang et al., 2018). Brieﬂy, 726 mL of absolute ethanol (Aladdin Industrial Corp., Shanghai, China) and 33 mL of a 3M sodium acetate anhydrous solution (Aladdin Industrial Corp.) were added to 330 mL ﬁltrate sample. The mixtures were stored at -20°C overnight and then centrifuged at 10, 0 0 0 × g for 10 min at 4°C. Subsequently, the supernatant was discarded and the centrifuge tubes were stored at -20°C until DNA extraction. 2.2. DNA extraction DNA was extracted from all the PA, FL, and pretreated CF using a FastDNATM Spin Kit for Soil (MP Biomedical, France). Protocols were conducted according to the manufacturer’s instruction.
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(5 μM), FastPfu Polymerase, BSA and DNA template (10 ng). The thermal reaction conditions were: initial denaturation at 95°C for 3 min, then 27 cycles of ampliﬁcation at 95°C for 30 s, annealing at 55°C for 30 s, elongation at 72°C for 45 s and ﬁnal extension at 72°C for 10 min. Puriﬁed amplicons were sequenced (2 × 300 bp paired-end) on the Illumina MiSeq platform (Illumina, San Diego, USA) at Major Biotech, Inc., Shanghai, China. The obtained pairedend reads were quality-controlled and merged using Trimmomatic and FLASH (Bolger et al., 2014; Magoc & Salzberg, 2011). UPARSE (Version 7.1, http://drive5.com/uparse/) was used to perform operational taxonomic unit (OTU) clustering at the similarity threshold of 97% (Edgar, 2013). To obtain the species classiﬁcation information corresponding to each OTU, the Ribosomal Database Project (RDP) classiﬁer Bayesian algorithm was used to classify each sequence with at an 80% conﬁdence threshold according to the Silva (SSU123) database. All the obtained raw sequence datasets have been uploaded to the NCBI Sequence Read Archive (SRA) with the bio-project accession number PRJNA592276. The relative abundances of all the samples were normalized to the same lowest sequence depth (23478).
The concentration and quality of the extracted DNA samples were measured using an ultraviolet (UV)-visible spectrophotometer (ND10 0 0, NanoDrop Technologies, Inc., USA) (Table S4). 2.3. HT-qPCR HT-qPCR was performed using a SmartChip Real-time PCR System (Takarabio, Japan) to target 283 ARGs, 4 integron genes, 8 transposase genes and the 16S rRNA gene (Su et al., 2015; Zhu et al., 2017). Among which, clinical class 1 integron-integrase gene (intI-1(clinic)) is considered to be closely related to human health (Gillings et al., 2015). Additionally, intI-1(clinic) can be used as a proxy or indicator for anthropogenic pollution (Gillings et al., 2015). Therefore, intI-1(clinic) was selected. The designed primers are listed in Table S5. The HT-qPCR conditions were as follows: 1) denaturation at 95°C for 10 min; 2) 40 ampliﬁcation cycles at 95°C for 30 s and extension at 60°C for 30 s. The eﬃciency of ampliﬁcation beyond the range of 1.8 to 2.2 was considered to be a negative result. The relative and absolute abundances of ARGs and MGEs were calculated as described in previous studies (Chen et al., 2019b; Su et al., 2015) and shown as follows: 10 GCN = 10(31−Ct)/( 3 )
A =A16S ×R
2.6. Statistical analysis and graphing
Pearson’s correlation and tests for differences between groups by one-way analysis of variance (ANOVA) (Turkey’s post hoc) and the Kruskal-Wallis (K-W) tests were conducted using SPSS 21.0 (IBM, USA). Canoco V5.0 (Chen et al., 2017) was used to perform principal coordinate analysis (PCoA) of size-fractionated ARGs and microbial communities based on the Bray-Curtis distance, and redundancy analysis (RDA) between concerned genera and ARGs. Variable forward selection was applied in the RDA. Twoway permutational multivariate analysis of variance (two-way PERMANOVA; 9999 permutations, Bray-Curtis distance) regarding the size-fractionated ARGs and MGEs and bacterial community structure from the two plants together (‘plant’ and ‘size fraction’ as two factors) were conducted using PAST V 4.0.1 (Zolti et al., 2019). Oneway PERMANOVA of size-fractionated ARGs and bacterial community structure were conducted separately for plant A and plant B. Comparisons of bacterial differences between size fractions were conducted by the K-W test followed by the Tukey-Kramer posthoc test. Procrustes analysis and Mantel and Adonis tests of the bacterial community were performed on the Major Cloud platform (https://cloud.majorbio.com/). Variation partitioning analysis (VPA) was also performed using Canoco 5.0. Co-occurrence analysis of size-dependent ARGs and MGEs (Pearson’s correlation eﬃciency ≥ 0.80 and p < 0.01 adjusted by the Benjamini-Hochberg method) (Benjamini & Hochberg, 1995) and bipartite network analysis were plotted using Gephi 0.9.2. Bar and box plots were graphed using Origin 2018 (Origin Lab, USA).
where GCN is the gene copy number, Ct is the threshold cycle, and 31 is set as the detection limit. R is the relative abundance of each ARG or MGE and 16S is the 16S rRNA gene measured by HT-qPCR. A is the absolute abundance of ARG or MGE and A16S is the absolute abundance of the 16S rRNA gene of each sample measured by real-time qPCR (RT-qPCR). It should be noted that the volume of size-fractionated sample was taken into account when calculating the absolute abundance. 2.4. Real-time quantitative PCR A LightCycler 480 System (Roche) was applied to RT-qPCR to quantify the 16S rRNA according to the plasmid standard curve. Each sample was analyzed in triplicate with a reaction volume of 20 μL, including 10 μL 2 × LightCycle 480 SYBR Green I Master (Roche Applied Sciences), 1 μL each primer (10 μM), 1 μl DNA template and 8 μL nuclease-free water. The 16S rRNA primers were the same as those used in the HT-qPCR. The thermal reaction conditions were as follows: 5 min pre-incubation at 95°C, then ampliﬁcation of 40 cycles at 95°C for 15 s, annealing at 60°C for 60 s and ﬁnal extension at 72°C for 20 s. The melting curve analysis was performed by increasing the temperature stepwise from 65°C to 97°C using 0.30°C/5s ramp rate with continuous ﬂuorescence recording. The results obtained by RT-qPCR exhibited a signiﬁcant correlation with those obtained by HT-qPCR (R2 = 0.92, p < 0.01). Therefore, the absolute abundance of 16S rRNA can be used to calculate the absolute abundances of ARGs and MGEs according to the equation (3) (Ouyang et al., 2015).
3. Results 3.1. Diversity and occurrence of size-fractionated ARGs and MGEs In total, 261 ARGs and all 12 targeted MGEs were detected in all of the wastewater samples, among which, multidrug (17.9% - 19.7%), beta_lactamase (17.6% - 19.6%), aminoglycoside (12.5% 13.8%), tetracycline (14.3% - 14.9%) and marcrolide-lincosamidestreptogramin B (MLSB) (12.2% - 14.9%) were the most abundant resistance types in the PA assemblages, FL bacteria and CF DNA samples (Fig. S2). These ARGs can be interpreted by three major mechanisms: antibiotic deactivate (39.4% - 42.1%), eﬄux pump (30.3% - 31.9%) and cellular protection (21.3% - 24.5%) (Fig. S3). Notably, the numbers of ARGs and MGEs in the PA assemblages and FL bacteria were signiﬁcantly higher than those observed for CF DNA in both plants (one-way ANOVA, p < 0.01; Fig. 1a and b).
2.5. Bacterial 16S rRNA gene sequencing The bacterial communities of all the size-fractionated samples were identiﬁed via sequencing the V4-V5 region of the 16S rRNA gene with the forward primer 338F (ACTCCTACGGGAGGCAGCAG) and the reverse primer 806R (GGACTACHVGGGTWTCTAAT) using a thermocycler PCR system (GeneAmp 9700, ABI, USA). The PCR reaction was conducted in triplicate and each volume was 20 μL in total, including 5 × FastPfu Buffer, dNTPs (2.5 mM), each Primer 3
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Water Research 187 (2020) 116450
Fig. 1. Number of detected particle-associated (PA), free-living (FL) and cell-free (CF) ARG and MGE subtypes in plant A (a) and plant B (b). Signiﬁcant differences were marked with ∗ ∗ (p < 0.01). N.S. means not signiﬁcant. The Venn diagram shows the shared and unique number of PA-, FL- and CF- ARGs (c). The exact shared and unique genes were presented by the bipartite network analysis (d). Cluster I was shared by all of the three size fractions. Cluster II was shared by PA and FL parts, cluster III by FL and CF parts and cluster IV by PA and CF fractions. Cluster V, VI and VII were the unique ARG subtypes carried by PA, FL and CF fractions, respectively.
Table S6; two-way PERMANOVA; F = 2.76, p =0.0 0 03). The results indicated that the fates of ARGs and MGEs were potentially different for different fractions and different plants. Speciﬁcally, FL-ARGs were signiﬁcantly separated from PA-ARGs in plant B (Fig. S8b; one-way PERMANOVA; F = 3.64, p = 0.0062) but not signiﬁcantly separated in plant A (Fig. S8a; one-way PERMANOVA; F = 2.40, p = 0.06), which is probably ascribed to the different processes and biological structures between the two plants. Cell-free ARGs were signiﬁcantly separated from other fractions in both plants (PERMANOVA; p < 0.05). The absolute abundances of PA- and FL-ARGs ranged from 4.3 ± 0.6 × 106 to 1.6 ± 0.2 × 109 copies/mL and from 6.3 ± 0.8 × 106 to 1.0 ± 0.1 × 109 copies/mL, respectively, which were signiﬁcantly higher than that observed for CF ARGs with ranges from 2.8 ± 0.6 × 105 to 7.1 ± 1.0 × 108 copies/mL (K-W test; p < 0.01) (Fig. 2e; Fig. S9). These results (number, relative and absolute abundances) suggested that FL fractions may have the potential to carry the most ARGs compared to other two fractions. The absolute abundances of PA-MGEs, FL-MGEs and CFMGEs were within the ranges of 2.1 ± 0.1 × 106 to 7.2 ± 0.8 × 108 copies/mL, 2.7 ± 0.3 × 106 to 5.5 ± 0.2 × 108 copies/mL and 2.1 ± 0.5 × 105 to 2.9 ± 0.4 × 107 copies/mL, respectively. Although the absolute abundances of CF-MGEs were signiﬁcantly lower than that observed for the other two fractions (K-W test; p < 0.01) (Fig. 2f), MGEs were prevalent in the CF fraction, which cannot be neglected.
The number of FL-ARGs was signiﬁcantly higher than that of PAARGs in plant B (one-way ANOVA, p < 0.01; Fig. 1b), while no signiﬁcant difference was observed in plant A (one-way ANOVA, p > 0.05; Fig. 1a). Although the detected number of CF-ARGs was the lowest, over 40 ARGs and MGEs of CF DNA were still detected in all the size-fractionated samples, among which the inﬂuent of plant A had the most subtypes of ARGs and MGEs (82 in total) (Fig. S4a). The results indicated that CF-ARGs commonly existed throughout the treatment processes. Most ARG and MGE subtypes were shared (162) in different size fractions, while a few of them were unique to CF DNA in the WWTPs (Fig. 1c) and the receiving stream (Fig. S5). Detailed information regarding shared and unique ARGs and MGEs from the three size fractions of two plants are shown in Fig. 1d. All the targeted MGEs were detected in the samples of the three different size fractions, while vancomycin resistance genes were dominant in the unique types of CF-ARGs (Fig. 1d). The relative abundances of ARGs and MGEs in FL bacteria were the highest among the three different types of samples in the two WWTPs (Fig. 2a and b; Fig. S6), while PA-ARGs and PA-MGEs exhibited the lowest relative abundances. The changes of the relative abundances of ARGs and MGEs among the three different fractions were not signiﬁcant (K-W test; p > 0.05; Fig. 2a-c). The relative abundance of each gene was shown using a heatmap (Fig. S7). Size-fractionated ARGs and MGEs from two plants together were signiﬁcantly separated from each other revealed by PCoA (Fig. 3a; 4
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Water Research 187 (2020) 116450
Fig. 2. Box plots of relative abundance of ARGs (a), MGEs (b) and the total (c), and absolute abundances of 16S rRNA (d), ARGs (e) and MGEs (f) from three size fractions of the two plants. Signiﬁcance was checked by Kruskal-Wallis test (∗ ∗ , p < 0.01). Absolute abundances (copies per mL) were log-transferred.
3.2. Changes of size-fractionated ARGs along the treatment processes and the receiving stream
in the CF fractions. As shown in Fig. S10, dissolved total nitrogen (D-TN) and COD (D-COD), nitrate (NO− 3 -N) and DO were signiﬁcantly correlated with size-fractionated ARGs in the biological reactors of plant A, while dissolved total phosphorous (D-TP), ammonia (NH3 -N) and temperature were more correlated with sizefractionated ARGs in plant B. These results suggested that physicochemical parameters may have the potential to inﬂuence the abundances of size-fractionated ARGs in different plants. The removal of PA-ARGs and PA-MGEs by clariﬁcation in plant A (decrease of 2.05 orders of magnitude) was much higher than that in plant B (decrease of 0.97 orders of magnitude) (Table 1). Among the assayed fractions, FL-ARGs and FL-MGEs were the most abundant in the eﬄuent of the SSTs in both plants. The levels of FL-ARGs and FL-MGEs were reduced after precipitation in plant A by 0.63 orders of magnitude, whereas they were enriched in plant B (Table 1, Figs. S9a and b). In contrast, the levels of CF-ARGs were slightly altered in both plants, indicating that CF-ARGs were probably less inﬂuenced by sedimentation.
With respect to the inﬂuent, PA- and FL-ARGs and MGEs were the most dominant types (Figs. S4 and S9). Cell-free ARGs and MGEs were also ubiquitous in both plants, suggesting that CFARGs are important sources of these genes from domestic sewage. The highest relative abundances of FL-ARGs and FL-MGEs were observed in the bioreactors of plant A (Fig. S6a), while CF-ARGs and CF-MGEs exhibited higher relative abundances in plant B (Fig. S6b). The absolute abundances of PA-ARGs and PA-MGEs were the highest, up to 1.9 ± 0.2 × 109 copies/mL, in the sampling site of AS3, while FL-ARGs and FL-MGEs were the most abundant in the bioreactors of plant B (Fig. S9b). Both the relative and absolute abundances of PA-ARGs and PA-MGEs increased in the aerobic zone compared to the anoxic zone in the two plants, indicating that changes in the dissolved oxygen (DO) level probably affected the shift in ARG abundance. A similar phenomenon was also observed 5
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FL-ARGs were the dominant type among the assayed fractions, with the highest detected numbers and absolute abundance in the receiving stream of plant A (Fig. S4c; Fig. S9c). Both the relative and absolute abundances of PA- and FL-ARGs in the downstream (GS3 and GS4) were lower than that of the upstream (GS2) (Fig. S6; Fig. S9c), which was attributed to the high-quality treated eﬄuent from plant A. 3.3. Co-occurrence patterns of size-fractionated ARGs and MGEs All the targeted MGEs were detected in the different size fractions at different treatment stages (Fig. S7). The relative abundances of MGEs (such as tnpA-04) were maintained at high levels throughout the treatment systems and in the receiving stream (Fig. S6 and S7). PA- and FL-MGEs also exhibited strong correlations with PA-, FL- and total ARGs (p < 0.05), but not CF-ARGs (p > 0.05) (Fig. S11). A network analysis was performed to reveal co-occurrence patterns of size-fractionated ARGs and MGEs (Fig. 4; Figs. S12-14). The patterns were different in three size fractions. MGEs, such as intI-1 (clinic), intI2, Tp614 and tnpA-07, exhibited strong connections with diverse ARGs. In addition, VPA revealed that MGEs contributed 32.2% to the relative abundance changes in size-fractionated ARGs (Fig. 6d). These results suggested that MGEs may play an important role in the disseminations of sizefractionated ARGs. 3.4. Characterizations of size-fractionated microbial communities A total of 2208853 high quality sequences were obtained from the 44 size-fractionated samples (Table S7). The shared and unique OTUs were presented in Venn plots (Fig. 5a and b). Free-living fractions exhibited the highest OTU number with over 23.94% unique OTUs in both plants. Proteobacteria were the most common phylum in all the size-fractionated samples (Fig. S15). Firmicutes, Patescibacteria and Actinobacteria were predominant in the PA assemblages. Free-living bacteria were dominated by Epsilonbacteraeota, Bacteroidetes and Patescibacteria, while the DNA of Bacteroidetes, Patescibacteria and Verrucomicrobia were abundant in the CF fraction. In plant A, Gammaproteobacteria was the most abundant class in the PA assemblages (Fig. 5c). The relative abundances of Campylobacteria, Saccharimonadia and Clostridia in the FL fraction were signiﬁcantly higher than that of the PA assemblages. For the CF fraction, the DNA of Bacteroidia and Verrucomicrobiae were predominant. In plant B, Clostridia, Alphaproteobacteria, Patescibacteria, Blastocatellia_Subgroup_4, Actinobacteria and Bacilli were abundant in the PA fraction (Fig. 5d), while Campylobacteria, Parcubacteria and Gracilibacteria were abundant in the FL fraction. The DNA of Bacteroidia, Parcubacteria and WWE3 were dominant in the CF fraction. The size-fractionated bacterial communities exhibited different structures in the two plants. PCoA was implemented to assess the distribution patterns of size-fractionated bacterial communities from the two plants together (Fig. 3b). The structures of size-fractionated bacteria communities were statistically signiﬁcantly affected by the interaction effects of two factors of ‘size fraction’ and ‘plant’ (two-way PERMANOVA; F = 3.5, p = 0.0 0 01). Independently, PCoA of size-fractionated bacterial communities were also conducted in plant A (Fig. 5e) and plant B (Fig. 5f). Three sizefractionated samples were signiﬁcantly separated from each other in both plants (Adonis test; plant A: R2 = 0.5026, p = 0.0 0 01; plant B: R2 = 0.4950, p = 0.0 0 01). The microbial communities varied among the size fractions at the genus level (Fig. S16). The different fractions from the two plants were clustered (Fig. S17). Pseudomonas spp. were much more abundant in the PA fractions than in the other two types of fractions, whereas Arcobacter spp. were more plentiful in the FL fractions in the two plants. The relative abundance of Acinetobacter
Fig. 3. Bray-Curtis distance-based principle coordinate analysis (PCoA) of sizefractionated ARGs and MGEs (relative abundances) (a) and that of size-fractionated genera (b) from the two plants (plant A and plant B), respectively. The variances (two plants together) were checked by two-way PERMANOVA. ‘Size fraction’ and ‘plant’ were set as the two factors.
The relative abundances of PA-ARGs and PA-MGEs increased after UV disinfection in both plants (Figs. S6a and b), while those of the CF fractions were slightly reduced in both WWTPs. Ultraviolet lights had limited effects on both PA- and FL-ARGs in the two treatment systems (Table 1). However, contrasting results were observed for CF-ARGs and CF-MGEs, which were reduced by 1.34 orders of magnitude in plant A but increased by 0.15 orders of magnitude in plant B. In the ﬁnal eﬄuent of both plants, the absolute abundance of FL-ARGs was the highest, indicating that they were the most important sources of ARGs spreading from the hotspots of WWTPs. The CF-ARGs and CF-MGEs had the same absolute abundances as PA-ARGs and PA-MGEs in the eﬄuent of plant B. Although the absolute abundances of CF-ARGs and CF-MGEs in plant A were the lowest among the tested samples, they still reached at 5.0 ± 1.1 × 105 copies/mL, suggesting that CF-ARGs were also important sources into the receiving stream. 6
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Table 1 Log removals (calculated by minus log-transferred absolute abundance of inﬂuent and eﬄuent in each process unit) of sizefractionated ARGs and MGEs along the treatment processes of the two plants and receiving stream are shown. Negative value means that ARGs or MGEs were enriched. Color band is in the bottom of the table.
spp. was high in the PA and FL fractions in both plants. Mycobacterium spp. were more likely to exist in planktonic form in plant A, and be enriched after passing through the biological reactors while other genera tended to be reduced. Aeromonas spp. were ubiquitous in the FL and CF fractions but only in plant B. These differences may affect ARG proliferation.
CF-ARGs in plant B. These results suggested that size-fractionated bacteria may exhibit different correlations with ARGs. In addition, the VPA results suggested that microbial community structures contributed 24.7% to the changes in size-fractionated ARGs (Fig. 6d). These results indicated that microbial communities may be an important driver of ARG proliferation.
3.5. Relationship between size-fractionated ARGs and microbial communities
4. Discussion Although numerous previous studies have evaluated the potential fate of ARGs in WWTPs, especially considering intercellular and extracellular ARGs, limitations for the understanding of intercellular ARG dynamics still exist. This was the major motivation to convey the study of size-dependent ARGs to separate intercellular parts into PA and FL fractions, especially for the full-size range. The obtained results indicated that FL- and CF-ARGs and MGEs in the eﬄuents of the WWTPs may be the bottleneck of controlling the spread of ARGs from the hotspots into the receiving environmental compartments.
The Procrustes analyses indicated that size-fractionated microbial communities were signiﬁcantly correlated with ARGs in plant A (M2 = 0.61, p < 0.01; Fig. 6a) and plant B (M2 = 0.57, p < 0.01; Fig. 6b). These were further conﬁrmed by Mantel tests (plant A: r = 0.25, p = 0.008; plant B: r = 0.48, p = 0.001). As revealed by the RDA (Fig. 6c), seven genera exhibited close relationship with all the size-fractionated ARGs (pseudo-F = 4.2, p = 0.002). Acinetobacter spp. (B3), Mycobacterium spp. (B4), Arcobacter spp. (B5) and Pseudomonas spp. (B6) exhibited close connection with FL-ARGs from the two plants. Separately, Mycobacterium spp. (B4), Arcobacter spp. (B5) and Legionella spp. (B7) were correlated with FL-ARGs in plant A (Fig. S18a). Mycobacterium spp. (B4) and Pseudomonas spp. (B6) exhibited strong correlations with PA-ARGs, while Arcobacter spp. (B5) was related with FL-ARGs in plant B (Fig. S18b). The CF DNA of Legionella spp. (B7) had positively connection with
4.1. Different fates of PA-, FL- and CF-ARGs In natural environmental matrices, microbial communities are abundant in PA assemblages (D’Ambrosio et al., 2014; Gonsalves et al., 2017). Suspended sludge with abundant microor7
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Fig. 4. Network analysis of ARGs and MGEs in all wastewater samples (including three size-fractions). A connection represents a signiﬁcant correlation (Pearson’s coeﬃciency ≥ 0.80, p < 0.01). The nodes were colored according to ARG and MGE subtypes, and the node size is ranked according to the number of connections (degree).
ganisms after acclimatization and enrichment is the foundation of activated sludge treatment systems. Attributed to their abilities to adsorb materials (including nutrients), particle matrices not only provide suitable habitats for microbial communities, but also protect microorganisms from damage caused by adverse environmental conditions, such as a lack of nutrients or UV disinfection (Chahal et al., 2016). Thus, it was predictable that diverse and ubiquitous ARGs and MGEs were detected in PA assemblages consider-
ing the signiﬁcantly higher abundance of 16S rRNA sequences compared with the FL fraction (K-W test, p < 0.01) (Fig. 2d). Because FL bacteria have been shown to be ubiquitous in various environmental matrices (Ganesh et al., 2014; Guo et al., 2018; Huang et al., 2018), they tend to carry diverse ARGs and MGEs (Guo et al., 2018). Because the dynamics and occurrence of FLARGs may be different from those of PA-ARGs in WWTPs, we attempted to separate FL bacteria from PA assemblages. Bacteri8
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Fig. 5. Microbial communities of size-fractionated wastewater samples. The shared and unique number of OTU among PA, FL and CF fractions in plant A (a) and plant B (b) were shown by Venn diagrams. Comparisons of bacterial differences (class level) between three size fractions of the plant A (c) and B (d) were conducted by Kruskal-Wallis (K-W) test followed by Tukey-kramer post-hoc test (∗ , p < 0.05; ∗ ∗ , p < 0.01). PCoA (Bray-Curtis distance) of microbial communities (genus level) among PA, FL and CF in the plant A (e) and B (f). The variances were further checked by Adonis test.
oplankton is also an important type of microorganism lifestyle (Guo et al., 2018) that can be plentiful in wastewater, and exhibit the potential of carrying more diverse ARGs compared to PA assemblages. Artiﬁcial aeration in the aerobic tank and water ﬂow turbulence can potentially lead to the desorption of bacteria from particle assemblages. In addition, planktonic bacteria are not easily settled, resulting in their higher abundance at the end of WWTPs. Cell-free ARGs originate from the lysis of cells and the cytolysis of dead bacteria that harbor diverse ARGs (Vlassov et al., 2007; Zhang et al., 2018). Thus, CF DNA may not persist as long as the DNA in the PA and FL fractions, which is protected by cell walls and particulate matters in wastewater. Enzyme hydrolysis and photolysis can breakdown or damage CF DNA (Zhang et al., 2018). However, CF DNA harboring diverse ARGs may exist long durations (25 d) in the wastewater and receiving environments (Vlassov et al., 2007; Zhang et al., 2018), highlighting the concern that ARGs in receiving compartments could propagate through CFARGs. Thus, CF DNA is an important but overlooked source of ARGs in WWTPs and their receiving environments. Although we targeted much greater number of ARGs and MGEs than a previous study (only four ARGs and no MGEs) (Zhang et al., 2018), some important genes are still missing. Metagenome and other Illumina highthroughput sequencing technologies should be conducted to provide more information regarding the CF-ARGs. There might be interactions among the three size fractions in the wastewater treatment processes (Fig. S19). It should be noted that PA assemblages could potentially consist of FL bacteria (Hunt et al., 2008; Riemann & Winding, 2001), and the release of FL cells from large particles may also occur during in situ aeration or sampling (Ganesh et al., 2014; Hunt et al., 2008). The proportional abundances of ARGs among the three fractions can be af-
fected by the operational parameters of biological reactors and the treatment processes, such as hydraulic retention time, mixed liquor suspended solids (MLSS) and ﬂocculation. The mechanisms of interactions between the fractions are complicated, and more ﬁeldand laboratory-scale trails should be conducted to provide fundamental sights into the size-fractionated ARGs. In addition, the mechanical division of PA and FL bacteria by the ﬁrm pore-size ﬁlter may be biased (Guo et al., 2018). Thus, continuous pore-sized proﬁling of the living styles of bacterial assemblages as well as carried ARGs in wastewater treatment should be investigated in the future. Cell-free ARGs are not only released from activated sludge, but also can be absorbed by particulate matters (Poly et al., 20 0 0), suggesting that there may be dynamic conditions of sorption and desorption between CF DNA and activated sludge. The bias problem of quantiﬁcation caused by different PCR systems should be of concern (Nolvak et al., 2018; Nolvak et al., 2012). Although the primers of 16S rRNA and the ﬂuorescent dye were the same in conducting qPCR and HT-qPCR, and the datasets of 16S rRNA obtained were signiﬁcantly correlated (R2 = 0.92, p < 0.01), the ampliﬁcation eﬃciencies and other issues may potentially challenge the results (Nolvak et al., 2018). Therefore, further veriﬁcation and in-depth investigation warrant to avoid the bias. 4.2. Treatment processes inﬂuenced the dynamics of abundances of size-fractionated ARGs Different biological structures may affect the dynamic portions and distribution of different size fractions. A conceptual model regarding size-fractionated ARGs and MGEs from WWTP inﬂuent to the ﬁnal receiving stream is presented in Fig. S20. Due to the unique bioreactor structure of plant A, which has additional bio9
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Fig. 6. The signiﬁcant correlations between the size-fractionated microbial communities and corresponding ARGs in plant A (a) and plant B (b) were revealed by Procrustes analyses, respectively. Redundancy analysis (RDA) was conducted to explore the correlation between size-fractionated ARG and MGE subtypes and bacteria (genus level) (c). Seven genera were signiﬁcantly correlated with size-fractionated ARGs (pseudo-F = 4.2, p = 0.002). They were Aeromonas (B1), Clostridium_sensu_stricto_1 (B2), Acinetobacter (B3), Mycobacterium (B4), Arcobacter (B5), Pseudomonas (B6) and Legionella (B7), respectively. Variation partitioning analysis (VPA) was implemented to reveal the contribution of microbial community and MGEs to the changes of size-fractionated ARGs (d).
packings and numerous macrophytes (Table S2, Fig. S1), bacteria tended to be attached to suspended sludge and bioﬁlms. Macrophytes probably promoted adhesion between particles and bacteria via root exudates, which contain low relative molecular weight organic materials and polymeric adhesive substances (Coskun et al., 2017; Zhang et al., 2019). In contrast, FL-ARGs were dominant in the traditional activated sludge system of plant B, which did not have as much internal materials or aquatic plants. Abiotic factors may also affect the abundance dynamics of size-fractionated ARGs. Organic matter, nitrogen, phosphorus and temperature have been considered as important abiotic factors to affect the bacterial communities, which further inﬂuences the abundance of ARGs (Novo et al., 2013). In addition, numerous studies have demonstrated that ARGs can be affected by oxygen availability during wastewater treatment and sludge or manure digestions (Diehl & Lapara, 2010; Lee et al., 2017; Ma et al., 2018; Zhang et al., 2016). It has been found that tet(O) was speciﬁc for aerobic, while tet(W) was speciﬁc for anaerobic bacteria (Chopra & Roberts, 2001). The DO concentrations can also inﬂuence community structure dynamics of size-fractionated bacteria. The strict anaerobic Bacteroides, commonly existed in wastewater treatment systems and much
more abundant in FL lifestyle in both the two plants and the receiving stream (Fig. S16), has been identiﬁed as a host for tet(X) (Speer et al., 1991). The relative abundance of the tet(C) gene was observed to be signiﬁcantly lower under anaerobic conditions compared to that observed under aerobic conditions in a previous study, which is probably attributed to the reduction of the energetic burden of plasmid reproduction (Rysz et al., 2013). Controlling the DO level is potentially conducive to restricting the proliferations of ARGs (Rysz et al., 2013). Long-term low DO condition can reduce the relative abundances of ARGs in swine wastewater treatment (Ma et al., 2018). Signiﬁcant reductions in the abundances of ARGs were also obtained in anaerobic reactors, while the opposite phenomenon was observed in aerobic digesters (Diehl & Lapara, 2010). However, aerobic conditions are required during traditional wastewater treatment when considering the removal of other pollutants (such as ammonia). Therefore, optimal design of operational conditions and precise control of DO concentration for wastewater treatment should be taken into account. Recent studies have demonstrated that biosolids sedimentation directly results in the removal of ARGs (Ju et al., 2019; Lee et al., 2017), most of which, as revealed by our results, were actually 10
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PA-ARGs. Particle-associated ARGs were observed to be carried by large particle matrices (>3.0 μm), and their depositions occurred much more readily in the SSTs (Proia et al., 2018). FL bacteria was more diﬃcult to be settled down by gravity, resulting in their relatively high prevalence in the eﬄuent of the SSTs. The results highlighted that more attention should be paid to FL-ARGs to more efﬁciently control the spread of ARGs. The different structures of the biological reactors in plants A and B might have led to the discrepant behaviors of PA-ARGs and PA-MGEs observed in the SSTs. The coagulant dosage in plant A (PAC, Table S2) also resulted in a good sedimentation performance of particles, which is consistent with previous studies (Grehs et al., 2019; Lee et al., 2017) that the use of coagulants and higher dosages can achieve higher ARG removal (Table S8). In previous jar tests, 5 ARGs were eﬃciently removed by coagulation processes using FeCl3 and polyferric chloride (PFC) as coagulants (Li et al., 2017). Therefore, attempt to promote the settleability of FL fractions could probably increase ARG removal. UV disinfection has different effects on the three fractions. Studies have demonstrated that particles or organic matters can protect microorganisms from UV-induced damage (Chahal et al., 2016; Lee et al., 2017). Furthermore, microorganisms themselves possess the ability to repair UV-damaged DNA (Hassen et al., 20 0 0). In previous studies (Lee et al., 2017; Narciso-da-Rocha et al., 2018), slight increases of relative abundances of ARGs were also observed at comparable UV doses (Table S8), suggesting that UV disinfection has limited effects on the reduction of ARGs. In addition, CF-ARGs have typically been neglected in those studies, because extracted DNA is typically ﬁltered by 0.22- or 0.45-poresized membranes (Chen et al., 2019a; Lee et al., 2017; QuintelaBaluja et al., 2019). Although CF DNA is susceptible to environmental changes and can be completely damaged by UV light (Chahal et al., 2016), it should be noted that some types of disinfectors which can make holes in bacterioplankton (Zhang et al., 2019) will promote the release of CF DNA. UV disinfection also resulted in bacterial apoptosis, leading to the release of CF-ARGs into the environment (Zheng et al., 2017). In addition, dissolved organic matter in the wastewater may protect the CF DNA from the UV damage. Our results showing that numbers of detected CFARGs and CF-MGEs increased after UV disinfection in plant B (Fig. S4b) were consistent with these ﬁndings. The dose of UV irradiation makes a difference if used at levels higher than 200 mJ/cm2 (McKinney & Pruden, 2012). However, the higher the dose, the greater the energy consumption, and other issues also arise. Therefore, if they were not completely degraded, then CF-ARGs were enriched. Thus, comprehensive consideration is warranted for the removal of ARGs by disinfection. Some ﬁne particles could reach the discharge endpoints. It is much easier to increase the removal efﬁciency of PA-ARGs through the use of ﬁlters or enhanced sedimentation, although these methods would probably not be particularly useful for removing FL-ARGs. Membrane technologies can be used to potentially improve PA- and FL-ARG removal by the effective interception of large and ﬁne particles when passing through small pore-sized membranes (Breazeal et al., 2013). The receiving environment would beneﬁt from the removal of ARGs and MGEs carried by PA and FL fractions in the WWTPs. In contrast, CFARGs can pass through 0.22-μm pore-sized ﬁlters (Zhang et al., 2018) and easily escape traditional WWTPs, resulting in substantial increases of potential risk to receiving environments, which warrants particular attention. Although there were signiﬁcant results obtained from the proﬁling of size-fractionated antibiotic resistome from two full-scale WWTPs, sampling from much more WWTPs with different kinds of processes and wastewater should be broadly conducted to obtain general rules considering the fact that size-fractionated ARGs can be affected by the treatment processes.
4.3. Relationship between ARGs and MGEs Mobile genetic elements can promote in the dissemination of ARGs through horizontal gene transfer (HGT) in different environmental matrices (Guo et al., 2018). However, to the best of our knowledge, assessments of MGEs in size-fractionated samples from WWTPs have not previously been performed. The speciﬁc pathways of ARG dissemination through HGT in fractions may be different due to the higher relative abundance of FL-MGEs than that of PA-MGEs, especially in plant B (Fig. S6). In contrast, CF-ARGs could probably be directly captured by bacteria to facilitate the transfer of ARGs (Dong et al., 2019; Jain et al., 1999), which deserves particular attention and further investigation. Integron integrases are typically associated with anthropogenic pollution (Gillings et al., 2015; Zhu et al., 2017) and waste sources, potentially resulting in their proliferation and transfer among bacteria in WWTPs. One of the most important integron integrase-encoding genes, intI-1 (clinic), has been conﬁrmed as cassettes of over 80 genes conferring resistance to major antibiotics (Mazel, 2006). As revealed by our results that intI-1 (clinic) was abundant in all the three fractions in both plants (Fig. S7), more attention should be paid to the intI-1 (clinic) carried by CF DNA and its potential in facilitating ARG transfer. Although intI2 was observed to be encoded in fewer gene cassettes, its ability to facilitate ARG transfer cannot be neglected (Biskri & Mazel, 2003; Fluit & Schmitz, 2004; Mazel, 2006; RoweMagnus & Mazel, 2002). For size-fractionated intI2, it exhibited signiﬁcantly correlations with diverse ARGs (Fig. 4), suggesting that it had great potential to act a role in the HGT of size-fractionated ARGs. Transposases, such as tnpA-04, tnpA-07 and TP614, frequently reported in various environmental matrices and all the size fractions (Fig. S7), may play an important role in the transfer and acquisition of ARGs among bacteria (Karkman et al., 2016; Yan et al., 2018). 4.4. Microbial communities drive the dynamics of antibiotic resistome structure The structural dynamics of microbial communities have been revealed to be the main driver of ARG propagation (Han et al., 2018; Jia et al., 2017). However, few studies have explored the size-fractionated bacteria in WWTPs and the encoded ARGs and MGEs. Bacteria with different lifestyles have been investigated in oceans, rivers and lakes, which has revealed that different community structures may inﬂuence their dynamics or functions (Ganesh et al., 2014; Jackson et al., 2014; Mou et al., 2013). Our results ﬁrst revealed that size-fractionated bacteria probably shift the dynamics of ARG abundances in full-scale WWTPs and the receiving stream. Size-fractionated bacterial lineages were signiﬁcantly correlated with ARG proﬁles (Mantel test; r = 0.31, p = 0.001). The VPA results also revealed that the microbial community contributed 24.2% to the changes of size-fractionated ARGs (Fig. 6c). Speciﬁcally, among the assayed fractions, PA bacteria were highly abundant in WWTPs (Fig. 2d) and potentially carried diverse ARGs. In activated sludge systems, electrostatic interaction and hydrophobic forces can facilitate the combination of particles and microorganisms (Templeton et al., 2005), resulting in relatively stable niches where microorganisms can obtain nutrients and survive environmental changes (Guo et al., 2018). Free-living bacteria were also common in the two plants and can easily escape from the SSTs, resulting in high levels of their harbored ARGs and MGEs in the eﬄuents. The separated fractions also exhibited close connections. Free-living bacteria could be adsorbed and desorbed by PA assemblages, while cell-free DNA was released after the lysis of dead cells from PA and FL bacteria. The genera arrying speciﬁc ARGs and MGEs can increase their potential risks to human beings (Cai & Zhang, 2013; 11
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Vaz-Moreira et al., 2014). Pseudomonas spp. can harbor diverse ARGs (Sib et al., 2019). Pseudomonas aeruginosa has been reported to be a ‘superbug’ for having resistance to multiple antibiotics (Breidenstein et al., 2011). Fortunately, Pseudomonas spp. were dominant in the PA fractions which was likely to be settled down in the SST with lower relative abundance in the eﬄuent (Fig. S14). Arcobacter spp. were observed to be resistant to commonly used antibiotics (Collado & Figueras, 2011). Acinetobacter spp. have the ability to capture ARGs (Yang et al., 2014), and Mycobacterium spp. were identiﬁed as being possible carriers of multidrug and tetracycline resistance genes (Vaz-Moreira et al., 2014). Half of Aeromonas spp. may play roles in the proliferation of ARGs (Blasco et al., 2008; Vaz-Moreira et al., 2014). Considering the ubiquity of FL bacteria with ability to escape WWTPs, measures targeting the removal of FL bacteria (such as Mycobacterium strains) may aid in controlling the spreading of genera carrying ARGs from treated wastewater. Different structures of size-fractionated microbial communities are probably inﬂuenced by various factors. The sludge concentration (Table S3) may inﬂuence the distribution of PA and FL bacteria, as FL bacteria can probably be adhered onto particulate matters. Furthermore, root exudates from macrophytes and coagulants (PAC) added in plant A may facilitate the adhesions between particles and bacteria (Bulgarelli et al., 2015; Li et al., 2017). Previous studies have also demonstrated that microbial communities can be shaped by root exudates (Hu et al., 2018; Zhalnina et al., 2018). But how the exudates affect the structures of size-fractionated microbial communities needs further proﬁling. Most bacteria, especially those in the PA fraction, can be removed by traditional AS systems by sedimentation. However, ﬁne particles coated with bacteria and bacterioplankton may escape from sedimentation tanks. Furthermore, these genera exhibited protection matrixes from UV disinfection which is the last line of defense in WWTPs (Lu et al., 2015). Therefore, priority genera list (size-dependent) corresponding to effective controlling technologies should be built to better reduce the spreading of ARGs.
and Technology Program for Water Pollution Control and Treatment in China (2017ZX07202). We sincerely thank Professor YongGuan Zhu, Jian-Qiang Su, and Dr. Fu-Yi Huang for their help with the HT-qPCR analysis. Supplementary materials Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.watres.2020.116450. References An, W., Guo, F., Song, Y., Gao, N., Bai, S., Dai, J., Wei, H., Zhang, L., Yu, D., Xia, M., Yu, Y., Qi, M., Tian, C., Chen, H., Wu, Z., Zhang, T., Qiu, D., 2016. Comparative genomics analyses on EPS biosynthesis genes required for ﬂoc formation of Zoogloea resiniphila and other activated sludge bacteria. Water Res 102, 494– 504. doi:10.1016/j.watres.2016.06.058. Benjamini, Y., Hochberg, Y., 1995. Controlling The False Discovery Rate - A Practical And Powerful Approach To Multiple Testing. J. R. Statist. Soc. 57 (1), 289–300. doi:10.2307/2346101. Biskri, L., Mazel, D., 2003. 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5. Conclusion Our study conveys a novel insight into the size-fractionated ARGs of two full-scale WWTPs and the receiving stream, which may help to better understand the dynamics of antibiotic resistome structures in wastewater treatment systems. Size-fractionated antibiotic resistome, separated by particle-associated assemblages, free-living bacteria and cell-free DNA, exhibited different abundances, which can be affected by the treatment processes. Cellfree ARGs were not eﬃciently removed by clarifying and ultraviolet disinfection, and were abundant in the ﬁnal eﬄuents of the WWTPs, which should be of concern when considering the control of ARG spreading. VPA analyses indicated that the bacterial communities and MGEs may be the main two drivers in the propagations of size-fractionated ARGs. Additionally, the microbial communities of the three size-fractions exhibited different structures, which might drive the interphase exchanges of ARGs. As size portioning was conducted in only two WWTPs, extensive research and broad sampling in different WWTPs are needed to obtain general rules regarding the size-fractionated antibiotic resistome. Declaration of Competing Interest The authors declare that they have no known competing ﬁnancial interests or personal relationships that could have appeared to inﬂuence the work reported in this paper. Acknowledgement Our work was supported by the National Key Research and Development Plan of China (2016YFC0400801) and the Major Science 12
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