Relationship between modification of activated sludge wastewater treatment and changes in antibiotic resistance of bacteria

Science of the Total Environment 639 (2018) 304–315

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Relationship between modification of activated sludge wastewater treatment and changes in antibiotic resistance of bacteria Ewa Korzeniewska ⁎, Monika Harnisz Department of Environmental Microbiology, Faculty of Environmental Sciences, University of Warmia and Mazury in Olsztyn, Prawocheńskiego 1 Str., 10-720 Olsztyn, Poland

H I G H L I G H T S

G R A P H I C A L

A B S T R A C T

• The number of ARB and ARGs in 13 WWTPs’ influents & effluents were investigated • The percentage of ARB in total bacteria counts increased in effluents compared to WWTP’s influents • The highest counts of ARGs copies in wastewater samples were observed for sul1, tet(A) and qepA • The abundances of ARB and ARGs were related to the applied modification of sewage treatment • The significant increase in ARB and ARGs number was observed in WWTP’s effluents with A2/O and SBR system

a r t i c l e

i n f o

Article history: Received 1 March 2018 Received in revised form 13 May 2018 Accepted 13 May 2018 Available online xxxx Editor: D. Barcelo Keywords: Antibiotic resistance bacteria Antibiotic resistance genes qPCR Activated sludge Wastewater treatment plant Escherichia coli

a b s t r a c t Biological treatment processes at wastewater treatment plants (WWTPs), which are the most common methods of sewage treatment, could cause selective elimination and/or changes in the proportions of phenotypes/genotypes within bacterial populations in effluent. Therefore, WWTPs based on activated sludge used in sewage treatment constitute an important reservoir of enteric bacteria which harbour potentially transferable resistance genes. Together with treated wastewater, these microorganisms can penetrate the soil, surface water, rural groundwater supplies and drinking water. Because of this, the aim of this study was to determine the impact of various modification of sewage treatment (the conventional anaerobic/anoxic/oxic (A2/O) process, mechanical-biological (MB) system, sequencing batch reactors (SBR), mechanical-biological system with elevated removal of nutrients (MB-ERN)) on the amount of antibiotic resistant bacteria (ARB) (including E. coli) and antibiotic resistance genes (ARGs) in sewage flowing out of the 13 treatment plants using activated sludge technology. There were no significant differences in ARB and ARGs regardless of time of sampling and type of treated wastewater (p N 0.05). The highest percentage of reduction (up to 99.9%) in the amount of ARB and ARGs was observed in WWTPs with MB and MB-ERN systems. The lowest reduction was detected in WWTPs with SBR. A significant increase (p b 0.05) in the percentage of bacteria resistant to the new generation antibiotics (CTX and DOX) in total counts of microorganisms was observed in effluents (EFF) from WWTPs with A2/O system and with SBR. Among all ARGs analyzed, the highest prevalence of ARGs copies in EFF samples was observed for sul1, tet(A) and qepA, the lowest for blaTEM and blaSHV. Although, the results of presented study demonstrate

⁎ Corresponding author. E-mail addresses: [email protected], [email protected] (E. Korzeniewska), [email protected] (M. Harnisz).

https://doi.org/10.1016/j.scitotenv.2018.05.165 0048-9697/© 2018 Elsevier B.V. All rights reserved.

E. Korzeniewska, M. Harnisz / Science of the Total Environment 639 (2018) 304–315

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high efficiency of ARB and ARGs removal during the wastewater treatment processes, especially by WWTPs with MB and MB-ERN systems, EFF is still an important reservoir of ARGs which can be transferred to other microorganisms. © 2018 Elsevier B.V. All rights reserved.

1. Introduction Antimicrobial resistance due to the continuous selective pressure from widespread use of antimicrobials in humans, animals and agriculture has been a growing problem for decades (Bengtsson-Palme et al., 2018; Berendonk et al., 2015). Antibiotic resistance is not restricted to pathogenic bacteria. Several studies show that antibiotic resistant clinical strains and/or their modes of resistance often originate from bacteria living in the natural environment, within soils and water (Finley et al., 2013; Singer et al., 2016). These environmental antibiotic resistant bacteria (ARB) can transfer the resistance genes (ARGs) to human pathogens causing resistant infections to become more difficult or even impossible to treat with current antibiotics, leading to infections causing higher morbidity and mortality. Intrinsic resistance in bacteria of the hospital environment is problematic because it limits the therapeutic options (Sengupta et al., 2013). Antibiotics including the groups of beta-lactams, tetracyclines, fluoroquinolones and sulfonamides comprise the largest share of antibiotics for human and animal use in the world. The metabolism of those active compounds in humans and animals varies widely. Some of compounds are metabolized in 90% or more, while others are metabolized in only 10% or even less (Kümmerer, 2009). They are then excreted as parent compounds or metabolites in urine and faeces into wastewater, in the case of human medicines, (X Guo et al., 2017; Le Corre et al., 2012; Leung et al., 2012) or, in the case of veterinary, as a fertilizer in animal farms (Wei et al., 2011; R Marti et al., 2014; Tien et al., 2017). Antibiotics and their transformation products (TPs) entering the environment can affect the evolution of the bacterial community structure (Aminov and Mackie, 2007; Baran et al., 2011) which plays a significant role in the ecosystem (Grenni et al., 2018; Thiele-Bruhn and Beck, 2005). However, apart from antibiotics and their TPs, antibiotic resistance genes (ARGs) and antibiotic resistant bacteria (ARB) have been identified as emerging pollutants of concern. They also enter ecosystems with treated wastewater, specifically if influents include hospital wastewater (Korzeniewska and Harnisz, 2013a; Lien et al., 2017; Wang et al., 2018). The low efficacy of hospital sewage treatment or lack of any sewage treatment may contribute to the dissemination of multi-drug resistant bacteria (MDR) from hospital effluents to the municipal sewage and then to the environment either with treated sewage or directly into the water bodies (lakes/rivers) (Ahn and Choi, 2016; Korzeniewska et al., 2013; Lekunberri et al., 2017). The activated sludge process was developed over 100 years ago and is primarily used for removal of biodegradable organic compounds, which could otherwise cause oxygen depletion of receiving waters if discharged in the treatment plant effluent. In activated sludge process wastewater containing organic matter is aerated in an aeration basin in which micro-organisms metabolize the suspended and soluble organic matter. The amounts of air and sludge used can be modify to control the level of treatment obtained. Part of organic matter is synthesized into new cells and part is oxidized to carbon dioxide and water to derive energy. In activated sludge systems the new cells formed in the reaction are removed from the liquid stream in the form of a flocculent sludge in settling tanks. A part of this settled biomass, described as activated sludge is returned to the aeration tank and the remaining forms waste or excess sludge (Modin et al., 2016; Xu et al., 2018). In sewage, especially in untreated sewage and activated sludge, where the bacterial density is very high, microorganisms have access to a large pool of itinerant genes which move from one bacteria cell to another (horizontal and vertical transfer) (Jiao et al., 2017; Summers,

2006). The genes may spread through bacterial populations via plasmids and a variety of mobile genetic elements, such as transposons or integrons (Chamosa et al., 2017; Fletcher, 2015; Patel, 2016), carrying genes which encode resistance to other antimicrobial agents (von Wintersdorff et al., 2016). Therefore, biological treatment processes at sewage treatment plants could cause selective elimination, and/or changes in the proportions of phenotypes/genotypes within bacterial populations in effluent. Korzeniewska and Harnisz (2013b) and Osińska et al. (2017) found higher frequency of multiple resistant Escherichia coli bacteria in treated than in untreated wastewater. These findings agree with studies of Szczepanowski et al. (2009), who detected a reduction of susceptibility to selected antimicrobial drugs in bacteria isolated from activated sludge compared to those isolated from the effluent of WWTP. Ferreira da Silva et al. (2007) and Osińska et al. (2017) demonstrated higher percentage of amoxicillin and tetracycline resistance in E. coli isolated from treated effluent than in E. coli isolated in the inflow of the same WWTP. The wastewater treatment plant constitutes, therefore, an important reservoir of enteric bacteria which carry potentially transferable resistance genes. Together with treated sewage these microorganisms and their genes can penetrate the soil, surface water, rural groundwater supplies and drinking water (Khan et al., 2016; Su et al., 2018). It creates a potential risk to human and animal health because ARGs and ARB transported to the environment can be transferred back to people and animals. Biological treatment processes at wastewater treatment plants (WWTPs) are the most common methods of sewage treatment. At the end of 2016 in Poland there were 3319 working WWTPs, including 22 mechanical, 2461 biological and 836 with increased nutrients removal system (GUS, 2017). Biological WWTPs are mainly located in villages and small cities (2089) and in Poland most of them use activated sludge technology with sequencing batch reactors (SBR). SBRs are a type of activated sludge process designed for the treatment of domestic wastewater in WWTPs with low capacity. Tanks which make the installation consist of a series of walls or baffles which direct the flow either from side to side of the tank or under and over consecutive baffles. This helps to mix the incoming influent and the returned activated sludge, beginning the biological digestion process before the liquid enters the main part of the tank. As the bacteria multiply and die, the sludge within the tank increases. The quantity and age of sludge within the tank can have a marked effect on the treatment process and the presence of ARB and ARGs in WWTPs' effluents (Di Cesare et al., 2016; J Guo et al., 2017). The anaerobic/anoxic/oxic (A2/O) process, the oldest biological method with elevated removal of nutrients have gained popularity in many countries in the 90s. This process, the most often in a threestage system, is employed mainly for organic matter and phosphorus removal as well as for denitrification. The three-stage system consists of chambers connected in series: anaerobic (phosphorus removal process), anoxic (denitrification process) and oxic (nitrification process). Using a several-phase cycle and desired biochemical transformations are accomplished at flow system to force fluctuation of organics and nutrient concentrations in process reactors (Lai et al., 2011; Wang et al., 2011). To control and decrease eutrophication of receiving water bodies, various modifications of wastewater treatment with elevated biological nutrient removal of nitrogen and phosphorus are also widely used in wastewater treatment practices, both for the upgrade of existing wastewater treatment facilities and the design of new facilities. An example of this is the additional use of a pre-denitrification chamber or alternate aeration system in nitrification/denitrification chambers. However, implementation of biological nutrient removal activated

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sludge systems presents challenges attributable to the technical complexity of balancing influent chemical oxygen demand for both biological phosphorus and nitrogen removal. Sludge age and aerated/ unaerated mass fractions are identified as key parameters for optimization of this process (Hu et al., 2012). Therefore, the main aim of this study was to determine the influence of 1) various modifications of the wastewater treatment technologies based on activated sludge technological solutions, 2) type of treated sewage inflowing to WWTPs and 3) people equivalent (PE) of WWTPs on the level of pollution by antibiotic resistant microorganisms and antibiotic resistance genes carried with purified wastewater into the environment.

2. Materials and methods 2.1. Study sites and sampling Samples of inflows (INF) and effluents (EFF) were collected from 13 WWTPs located in Warmia and Mazury District, Poland. Composite INF and EFF samples (1000 mL of INF and 2000 mL of EFF) were collected using a grab sample into sterile bottles directly after grate chamber and before effluents being released to the river or drainage ditch, respectively. In each season, INF and EFF samples from all studied WWTPs were collected in the middle of the flow stream during two consecutive days (during daily medium flows). WWTPs treat various type of wastewater (domestic sewage, hospital sewage, wastewater from food industry) using activated sludge technology with different modifications. The studied WWTPs were divided into 4 categories according to the modifications of sewage treatment system they apply: A – WWTPs with A2/O system (2 WWTPs), B – WWTPs with mechanical-biological system (5 WWTPs), C – WWTPs with SBR (3 WWTPs), D – WWTPs with mechanical-biological system with elevated removal of nutrients (3 WWTPs) (for detailed technical description of WWTPs, see Table 1 and Table S1). The coagulants (PIX - FeCl3) and flocculants (PAX - AlCl3) were used in some WWTPs only occasionally

(Table 1). None of tertiary treatment phases (chlorination or UV) was used in studied WWTPs. Poland is located in moderate climate zone with clearly marked seasons. The consumption of antibiotics is strongly seasonal, it is highest at the end of winter and lowest in summer. In order to capture these differences, samples of wastewater were collected in summer (July) and at the end of winter (February), transported to a laboratory at the temperature of 4 °C and processed on the day of collection. 2.2. Physicochemical parameters The physicochemical parameters of wastewater samples, including biochemical oxygen demand over 5 days (BOD) and chemical oxygen demand (COD) of sewage were evaluated in parallel to microbial analysis. The methodology to assess those parameters was used in accordance with the APHA (1998) standard methods. The physico-chemical parameters of influent and effluent samples, including temperature (°C) and pH, were determined with the use of the Hydrolab Multiprobe 12 (Scott). MLSS (mixed liquor suspended solid), MLVSS (mixed liquor volatile suspended solid) and TSS (total suspended solids) were determined by WWTPs' labs according to Polish Standards (PN-EN 872:2007). 2.3. Heterotrophic plate counts (HPC), E. coli and ARB number To obtain 8–80 colony forming units (CFU) per plate, INF and EFF samples were decimal diluted with saline water (0.85% NaCl) and passed through a cellulose filter (pore diameter 0.45 μM, Millipore). Greater accuracy was achieved by plating triplicates. Due to high consumption of antibiotics from both β-lactams and tetracyclines groups in Poland and Europe (ECDC, 2015), only ARB resistant to these antibiotics were determined using culture method. Two antibiotics (one antibiotic of the new and one of the old generation) from each group were selected: amoxicillin, cefotaxime and oxytetracycline, doxycycline, respectively. Using the culture method following microorganisms were determined: a) total HPC and E. coli, b) HPC and E. coli resistant to

Table 1 Technical description of wastewater treatment plants (WWTPs). The number of WWTPs

Type of the wastewater treatment technologies modifications

Wastewater treatment processa

Type of inflowing wastewater

People equivalent (PE)

Average processing capacity (m3/d)

Using of PIX/PAXb

I. II.

A. WWTPs with A2/O system

3144 5200

Yes/No Yes/No

B. WWTPs with mechanical-biological (MB) system

Domestic sewage Domestic sewage + wastewater from food industry Domestic sewage + hospital sewage + wastewater from food industry Domestic sewage Domestic sewage + wastewater from food industry Domestic sewage + wastewater from food industry Domestic sewage Domestic sewage Domestic sewage Domestic sewage Domestic sewage Domestic sewage + hospital sewage + wastewater from food industry Domestic sewage + hospital sewage + wastewater from food industry

36,084 33,053

III.

M: grate chamber, grit chamber, primary settling tank B: three-stage system with separate chambers: anaerobic (phosphorus removal), anoxic (denitrification), aerobic (nitrification), secondary settling tank M: grate chamber, grit chamber, primary settling tank B: phosphorus removal tanks, nitrification/denitrification chambers, secondary settling tank

12,168

1279

No/No

24,592 98,666

5300 4600

No/No Yes/No

96,000

7100

No/No

3100 20,000 13,300 3461 7096 250,000

190 1188 1200 300 582 35,000

Yes/No Yes/No No/No No/No Yes/No Yes/Yes

9967

1700

Yes/No

IV. V.

VI.

VII. VIII. IX. X. XI. XII

C. WWTPs with Sequencing Batch Reactors (SBR) D. WWTPs with mechanical-biological system with elevated removal of nutrients (MB-ERN)

M: grate chamber, grit chamber B: Sequencing Batch Reactors, retention tank, secondary settling tank M: grate chamber, grit chamber, primary settling tank B: pre-denitrification chamber, phosphorus removal tank, nitrification/denitrification chambers, secondary settling tanks

XIII

a b

M – mechanical treatment, B – biological treatment. PIX (FeCl3) and PAX (AlCl3) coagulants used occasionally.

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beta-lactams (resistant to amoxicillin – AMOR, resistant to cefotaxime – CTXR) and c) HPC and E. coli resistant to tetracyclines (resistant to oxytetracycline – OXR, resistant to doxycycline – DOXR). HPC and E. coli were incubated on TSA medium (Oxoid Ltd.) and mFc Agar medium (Merck), respectively. Both media were used with/without antibiotics (Sigma) supplementation: amoxicillin (8 μg/mL), cefotaxime (2 μg/mL), oxytetracycline (16 μg/mL) and doxycycline (16 μg/mL). Antimicrobial dose was determined in accordance to EUCAST (2014) and CLSI (2015) guidelines. The analyzed HPC were incubated at 30 °C for 48 h, while E. coli were cultured at 44.5 ± 0.2 °C for 24 h. After incubation, presumptive E. coli colonies were counted based on the number of dark blue colonies formed on the mFc Agar medium. The presence of uidA gene, which identified E. coli was analyzed in selected E. coli colonies (5 colonies per sample) (Heijnen and Medema, 2006). Quality positive control was achieved by using standard strains of E. coli ATCC 25922. 2.4. Genomic DNA extraction Wastewater samples (1000 mL of INF and 2000 mL of EFF) were filtered through white polycarbonate filters (pore size 0.2 μm, diameter 47 mm; type GTTP, Merck, Millipore) by using vacuum. Then, genomic DNA was extracted according to a method used in our previous study (Harnisz et al., 2015b). Briefly, the filters were transferred to a sterile Falcon tubes (50 mL) and stored at −20 °C for the further analysis. In the next step, 30 mL of 1 × PBS (phosphate-buffered saline) were added to the tubes. Then, they were stirred (200 rpm/min, 3 h) at room temperature. After stirring, the buffer was poured into separate sterile 2.0 mL Eppendorf tubes and centrifuged (9000 rpm/min, 15 min). After centrifugation the supernatant was carefully discarded. DNA was extracted from the final pellet using the Genomic Mini kits (A&A Biotechnology) according to the manufacturer's guidelines. The concentration and quality of extracted DNA were determined by Nanodrop spectrophotometer (NanoDrop® ND-1000, NanoDrop Technologies, DE). Genomic DNA was stored at −20 °C for further analysis. 2.5. Detection of specific resistance genes and their quantification 2.5.1. Standard PCR The presence of 16S rRNA gene, uidA gene identifying E. coli, rfbE gene identifying E. coli O157, ten beta-lactams resistance genes (blaTEM, blaOXA, blaSHV, blaCTX-M, blaCTX-M-1, blaCTX-M-2, blaCTX-M-9, blaAmpC, blaVEB, blaCMY), thirteen tetracycline resistance genes (tet(A), tet(B), tet(C), tet(D), tet(E), tet(K, tet(L), tet(M), tet(O), tetA(P), tet(S), tet(Q), tet(X)), eight fluoroquinolones resistance genes (aac(6′)-Ib-cr, qnrA, qnrB, qnrD, qnrS, qepA, oqxA, oqxB), three sulfonamide resistance genes (sul1, sul2, sul3) and two integrase genes (intI1, intI2) was determined by standard PCR analysis in genomic DNA isolated from wastewater. All primers had been previously validated (for primer sequences, amplicon sizes, annealing temperatures, references for each sequence, additional details regarding PCR conditions, see Supplementary Material, Table S2). After PCR amplification, 3–7 μL of each amplified fragments of DNA with 2 μL BFB Xcy loading buffer (Epicentre Biotechnologies) were separated by electrophoresis in 2% agarose (Sigma) gel stained with ethidium bromide (0.5 μg/mL). Products of amplification were electrophoresed for 15 min at 130 V and 60 min at 80 V in 0.5 × TBE buffer and visualized. 2.5.2. Real-time quantitative PCR (qPCR) Based on the results of standard PCR analysis related to frequency of appearance of ARGs, eight of ARGs (blaTEM, blaOXA, blaSHV, sul1, tet(A), tet (M), aac(6′)-Ib-cr, qepA) besides of 16S rRNA, uidA, rfbE and intI2 genes were selected to qPCR analysis. The copy number of all selected genes was quantified by SYBR Green methods, with the use of real-time qPCR protocols, which were optimized with the involvement of the previously described primers (Table S2). All qPCR reactions were

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performed in the Roche Light-Cycler 480 (Roche Applied Science, USA) in a 20 μL reaction mixture containing 1 μL (20 ng) of the DNA template. All samples were assayed in triplicate. Standard curves were prepared according to Harnisz et al. (2015a). The standard curve of each gene was generated by 10-fold dilution of plasmids carrying the target gene, ranging from 106 copies to 101 copies, with three replicates. The copy number of each ARG and 16S rRNA gene was calculated from the corresponding standard curve using the CT value of each gene in the qPCR runs. The square of the related coefficient (r2) of the standard curve ranged from 0.99 to 0.998, and the amplification efficiency ranged from 95% to 110%. 2.6. Data analysis Statistical analysis was carried out using STATISTICA 12 software package (StatSoft Inc.). Due to abnormally distributed data, The Kruskal–Wallis (KW) test, a non-parametric version of classical oneway ANOVA, was used to determine differences in the abundance of ARB and ARGs in wastewater between various groups of WWTPs depending on modification of treatment, time of samples collection and type of inflowing wastewater. The correlations between number of ARB and ARGs and also between ARB/ARGs and level of BOD and COD were determined by Spearman's rank correlation. The significance level of each above statistical test (α) was set at b0.05. 3. Results and discussion 3.1. Concentration of physicochemical parameters and the influence of WWTPs' technical data The highest and the lowest average values of BOD and COD in INF were found in samples from WWTPs belonging to group B with mechanical-biological system of sewage treatment and ranged from 249 ± 101 to 1188 ± 53 mg/L (BOD) and from 713 ± 179 to 2068 ± 39 mg/L (COD), respectively (Table S1). During the process of wastewater treatment in all analyzed WWTPs, BOD and COD values were reduced in 97.2–99.6% and 92–98%, respectively. Both of those parameters were strongly positively correlated (p b 0.05) with the number of all groups of analyzed microorganisms isolated from wastewater by culture method and with the number of some genes copies, e.g. uidA, rfbE, blaTEM, blaSHV, tet(M), and intI2 (Table S3). The average temperature of influents and effluent samples in winter/summer was estimated at 11.02 ± 0.76/18.75 ± 0.88 °C and 11.01 ± 0.53/18.38 ± 0.52 °C, respectively. The average value of pH reached up 7.44 ± 0.28 and 7.56 ± 0.22 in influents and effluent samples, respectively (Table S1). However, due to the lack of significant correlation observed between their level and the number of ARB and ARGs, these physico-chemical parameters were omitted in Table S3. There was a statistically significant correlation between the level of People Equivalent (PE) and the number of almost all groups of antibiotic resistant bacteria (both HPC and E. coli), however none was found between the level of PE and the number of each of the tested genes, except for intI2. Similar dependencies were found between capacity of WWTPs and the number of antibiotic resistance E. coli (Tables S1 and S3). The level of hydraulic retention time (HRT), which was higher for WWTPs with sequencing batch reactors, was correlated in a statistically significant way with the number of most of analyzed groups of microorganisms and genes (Table S3). Wang et al. (2017) and Kumar et al. (2014), reported significant effects of HRT on bacterial community composition and behavior in WWTPs' bioreactors. The average value of MLSS and MLVSS reached up 2035 ± 64.3, 6261 ± 102.5 mg/L, respectively. No statistically significant correlations were found between their value and the number of both the number of HPC and E. coli and also the number of analyzed copies of genes (Tables S1 and S3).

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The value of TSS in influent and effluent samples ranged from 378 ± 28 to 709.1 ± 24.5 and from 2.0 ± 0.1 to 12 ± 6.8 mg/L, respectively. The value of TSS correlated with the number of all studied microorganisms and the number of analyzed genes (p b 0.05), except for 16S rRNA and qepA (Tables S1 and S3). TSS refers to the mass (mg) or concentration (mg/L) of inorganic and organic matter in wastewater which can directly influence the quantity and diversity of microorganisms in wastewater. The effect of TSS on wastewater biota is dependent on several key factors, these include the concentration of TSS, the duration of exposure to TSS concentrations, the chemical composition of TSS and the particle-size distribution of TSS. TSS are typically comprised of fine particulate matter with a diameter of b62 mm, though for the majority of cohesive solids, research has demonstrated that transport frequently occurs in the form of larger aggregated flocs (Bilotta and Brazier, 2008; Verma et al., 2013). 3.2. HPC, E. coli and ARB counts Nowadays, there are many studies reporting that WWTPs may contribute to the occurrence, spread and persistence of both antibioticresistant bacteria and antibiotic resistance determinants in the environment (Guo et al., 2018; Osińska et al., 2017; Proia et al., 2018). However, there is lack of information on how different modifications of sewage treatment system can affect the prevalence of resistance in the bacterial communities of wastewater. Even from well-functioning biological plants, huge quantities of these bacteria get into the environment with treated sewage (Bengtsson-Palme et al., 2016; Korzeniewska and Harnisz, 2012; Oliveira et al., 2016). Although wastewater treatment processes reduce bacteria number in the sewage, some antibioticresistant bacteria can remain in the sewage outflow (Harnisz and Korzeniewska, 2018). Even with a decrease of 1–3 orders of magnitude in bacterial numbers, the actual concentration of microorganisms in the treated wastewater can still be significantly high. The bacterial removal rates in the WWTPs, even close to 99%, may not prevent the dissemination of antibiotic-resistant microorganisms from the WWTPs to the environment (Korzeniewska and Harnisz, 2013b). Those bacteria may be emitted from sewage directly into the water bodies, which are receivers of WWTPs effluent (Osińska et al., 2016). This poses a public health risk which needs future evaluation and control. 3.2.1. Total HPC and E. coli counts Due to the lack of statistically significant differences in the number of bacteria and genes depending on the time of samples collection, presented data are considered globally, merely analyzing differences between different types of sewage treatment system modification used and between different types of samples. The average number of total HPC and total E. coli in INF ranged from 5.6 × 106 to 1.0 × 108 and from 7.0 × 103 to 1.2 × 106 CFU/mL (Fig. 1). In ENF samples their counts ranged from 7.4 × 103 to 5.5 × 105 and from 9.0 × 101 to 1.6 × 104 CFU/mL, respectively. The number of these microorganisms was the highest in wastewater collected from WWTPs with A2/O system in which the value of HRT was relatively high. After the treatment process, the total number of HPC was decreased by 91.1–99.9%, while total number of E. coli decreased by 56.7–99.9%. The lowest percentage of reduction for both groups of bacteria was observed in WWTPs from group C which operated with SBR, while the highest one was noticed in WWTPs from group B and D with mechanicalbiological system of sewage treatment and mechanical-biological system with elevated removal of nutrients. The length of time when activated sludge remains in SBR tanks (longer sludge age) can have a huge importance in both formation/selection of ARB and transmission of ARGs among microbiota of activated sludge (Di Cesare et al., 2016; J Guo et al., 2017). There were statistically significant (p b 0.05) differences between the number of these groups of bacteria isolated from influent and effluent samples regardless of the time of samples collection,

kind of treated sewage and type of wastewater treatment method used in WWTPs. 3.2.2. HPC and E. coli resistant to beta-lactams The average number of HPC and E. coli resistant to amoxicillin (HPC AMOR and E. coli AMOR) in INF ranged from 3.5 × 106 to 2.6 × 107 and from 4.0 × 102 to 8.2 × 105 CFU/mL (Fig. 1). In EFF samples their number ranged from 5.9 × 103 to 2.9 × 105 and from 2.8 × 101 to 7.4 × 103 CFU/mL, respectively. After the treatment process, HPC AMOR and E. coli AMOR counts decreased by 95.1–99.9 and by 8.2–99.9%. The highest decrease in their number was usually in WWTPs from group B with mechanical-biological system of sewage treatment, while the lowest in WWTPs from group C with SBR system. The differences between number of these groups of bacteria in influent and effluent samples were statistically significant (p b 0.05). Although, the differences between number of these groups of bacteria in various kinds of treated sewage were statistically insignificant, their number was generally higher in wastewater with inflowing hospital sewage. The average counts of HPC and E. coli resistant to cefotaxime (HPC CTXR and E. coli CTXR) in INF ranged from 9.2 × 104 to 3.3 × 106 and from 0 to 2.6 × 103 CFU/mL (Fig. 1). In EFF samples their number ranged from 8.1 × 102 to 5.8 × 104 and from 2.0 × 100 to 8.9 × 102 CFU/mL, respectively. After the treatment process, HPC CTXR and E. coli CTXR counts decreased by 94.5–99.9 and by 2–99.9%. These large discrepancies in the percent of reduction of these microorganisms number could be related to kind of wastewater and also to differences between the level of HRT and SA in various WWTPs. Higher decrease in their number was noticed in WWTPs from group B and D with mechanicalbiological system of sewage treatment and mechanical-biological system with elevated removal of nutrients, while the lowest in WWTPs from group A with A2/O system and from group C with SBR system. The differences between the number of these groups of bacteria in influent and effluent samples were statistically significant (p b 0.05) except of WWTPs from group C with SBR system. For both analyzed groups of microorganisms, HPC and E. coli, the percentage share of amoxicillin resistant bacteria in total counts of microorganisms in INF and EFF was the highest regardless of the kind of wastewater treatment modification and kind of treated sewage. For both INF and EFF samples, the share of HPC AMOR and E. coli AMOR ranged up to 88 and 60%, respectively (Fig. S1). The amoxicillin is one of the most common beta-lactam antibiotics and belongs to their older generation. The HPC and E. coli resistant to cefotaxime were occurred less frequently. In INF samples the percentage share of HPC CTXR and E. coli CTXR was very low and ranged from 4 to 19% and 0.1 to 2%, respectively. The significant increase was observed in the proportion of bacteria resistant to this antibiotic in the total number of bacteria in effluent of WWTPs (Fig. S1). In EFF samples the percentage share of HPC CTXR ranged from 6.4 to 19% in total counts of HPC and E. coli CTXR ranged from 15 to 66% in total counts of E. coli (Fig. S1). It could be assumed that the resistance to CTX, which is a relatively new antibiotic, can be easily transmitted between E. coli in wastewater. Similar relationships were obtained by Osińska et al. (2017) who noticed more frequent occurrence of amoxicillin resistance in E. coli isolated from EFF than from INF samples reaching 53.5 and 25.5%, respectively. Comparable trends were also reported by Amos et al. (2014) in a study of bacteria resistant to aminoglycosides, beta-lactams and fluoroquinolones. Moreover, the cited authors indicated that wastewater treatment plants can contribute to a significant increase in the counts of antibiotic-resistant bacteria in water bodies which are receivers of WWTP's effluents. 3.2.3. HPC and E. coli resistant to tetracyclines The average number of HPC and E. coli resistant to oxytetracycline (HPC OXR and E. coli OXR) in INF ranged from 2.1 × 105 to 4.6 × 106 and from 4.0 × 102 to 4.2 × 104 CFU/mL (Fig. 1). In EFF samples their number ranged from 6.3 × 102 to 4.2 × 104 and from 1.8 × 101 to 1.2 ×103 CFU/mL,

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Fig. 1. Number (CFU – colony forming units) of total HPC (heterotrophic plate counts) and E. coli and HPC and E. coli resistant to beta-lactams (AMO – amoxicillin; CTX – cefotaxime) and tetracyclines (OX – oxytetracycline; DOX – doxycycline), respectively in wastewater (IF – influent; EFF – effluent; A, B, C and D – modification of sewage treatment system). An asterisk (*) denotes a statistically significant difference (p b 0.05) between WWTPs' influent and effluent samples.

respectively. At the end of the treatment process, HPC OXR and E. coli OXR counts decreased by 82.3–99.9 and by 47.5–99.9%. The highest decrease in their number was noticed in WWTPs from groups B and D with mechanical-biological system of sewage treatment and mechanical-biological system with elevated removal of nutrients, while the lowest in WWTPs from group C with SBR system. The differences between number of these groups of bacteria in influent and effluent samples were statistically significant (p b 0.05) except of WWTPs with SBR system. The average counts of HPC and E. coli resistant to doxycycline (HPC DOXR and E. coli DOXR) in INF ranged from 1.0 × 104 to 5.4 × 106 and from 0 to 5.9 × 103 CFU/mL (Fig. 1). In EFF samples their number ranged from 3.0 × 102 to 3.7 × 103 and from 2.2 × 101 to 3.6 × 103 CFU/mL,

respectively. After the treatment process, HPC DOXR and E. coli DOXR counts decreased by 79.4–99.9 and by 0–99.5%. The highest decrease in their number was noticed in WWTPs from group A with A2/O system, while the lowest in WWTPs from group C with SBR system. The differences between number of these groups of bacteria in influent and effluent samples were statistically significant (p b 0.05) except of WWTPs with SBR system. Although, the differences between the number of both of these groups of bacteria in various kinds of treated sewage were statistically insignificant, the number of HPC DOXR was generally higher in wastewater with inflowing hospital sewage. Regardless of the type of tetracycline antibiotics, the share of antibiotic resistant bacteria in total counts of microorganisms for both HPC and E. coli was rather inconsiderable in INF samples. However, despite

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a significant reduction of the number of antibiotic-resistant E. coli, we noted that after the sewage treatment process, the percentage of E. coli OXR and E. coli DOXR increased substantially among E. coli isolated from EFF samples and it reached up to 68 and 47%, respectively. This phenomenon is very alarming, because of doxycycline belongs to a new generation of drugs from the class of tetracyclines. Similar dependences were obtained by Lupan et al. (2017), who noticed higher share of TETR in microbiome of effluent than in microbiome of WWTP's influent. The higher percentage of antibiotic resistant bacteria in effluents of WWTPs could be related to high concentrations of bacteria in the wastewater, particularly in the activated sludge, which substantially supports the spread of antibiotic resistance among bacteria. Therefore, the conventional processes of wastewater treatment based on activated sludge and anaerobic digestion, create ideal conditions for horizontal gene transfer of mobile elements presented in the bacterial cells, contributing to an increase in the prevalence of antibiotic-resistant bacteria (Kelly et al., 2009; E Marti et al., 2014). 3.3. Prevalence of ARGs WWTPs are an important source of ARB and ARGs for natural environments, especially for waters and sediments of surface reservoirs which are the receivers of WWTPs' effluents (Harnisz et al., 2015b; Lekunberri et al., 2017; Pan and Chu, 2018; Rodriguez-Mozaz et al., 2015). Although our previous studies demonstrate that WWTPs based on activated sludge process can significantly reduce organic matter concentrations (BOD and COD), total number bacteria, counts of HPC and E. coli resistant to beta-lactams and tetracyclines antibiotics from untreated wastewater, our current study shows otherwise that the total bacterial abundance estimated by copy numbers of bacterial 16S rRNA gene was not significantly reduced after treatment, independently of the kind of sewage and modification of sewage treatment system being used (Figs. 2, 3). The copy numbers of bacterial 16S rRNA gene ranged from 2.1 × 106 to 3.0 × 107 copies per mL of EFF samples. The

similar results related to insufficient reduction of 16S rRNA gene copies number after wastewater treatment were also obtained by Rafraf et al. (2016). They observed an ineffective reduction of bacterial load in five WWTPs in Tunisia. Moreover, the results of their studies conducted in WWTP located in Moknine indicate even an increase of bacterial abundance in effluents compared to WWTP's influent from 2.31 × 108 to 3.67 × 108 16S rRNA gene copies/mL of sample. The number of uidA gene copies identifying E. coli and rfbE gene identifying E. coli O157 in EFF samples ranged from 8.8 × 103 to 4.5 × 104 and 0 to 9.3 × 103 copies/mL, respectively. Their relative abundances to 16S rRNA gene target ranged from 2.7 × 10−4 to 2.0 × 10−3 and 0 to 1.5 × 10−3 (copies/16SrRNA), respectively (Figs. 2, 3). A statistically significant correlation between the number of these genes and the number of all groups of HPC and E.coli analyzed by culture method was observed (Table S3). Although their counts were reduced during the wastewater treatment process from one to two orders of magnitude, not in all cases was the difference between their number in inflow and outflow of WWTPs statistically significant (p b 0.05). In samples collected from WWTPs with A2/O system the uidA and rfbE genes abundances relative to 16S rRNA gene target were slightly increased in EFF samples compared to their abundances in INF samples. Neudorf et al. (2017) observed an increase in the relative abundance of genes copies in WWTP with biological treatment systems where hydraulic retention time was longer. The counts of intI2 gene in INF and EFF samples ranged from 1.3 × 104 to 4.4 × 105, and 1.7 × 103 to 2.0 × 104 copies/mL, respectively. The relative abundances to 16S rRNA gene target ranged from 1.2 × 10−3 to 2.6 × 10−2 and 8.7 × 10−5 to 1.2 × 10−3 (copies/16S rRNA), respectively (Figs. 2, 3). The difference between its number in inflow and outflow of WWTPs was statistically significant (p b 0.05). There was a statistically significant correlation between the number of this gene and the number of all groups of HPC and E.coli analyzed by culture method and almost all analyzed genes, except for sul1 and qepA genes (Table S3). The decrease of the percent of integron-positive bacteria including E. coli in EFF compared to INF samples was observed in previous

Fig. 2. The concentration of genes (number of copies/1 mL) in wastewater (IF – influent; EFF – effluent; A, B, C and D – modification of sewage treatment system). Within the box plot chart, the crosspieces of each box plot represent (from top to bottom) maximum, upper-quartile, median (black or white bars), lower-quartile and minimum values. An asterisk (*) denotes a statistically significant difference (p b 0.05) between WWTPs' influent and effluent samples.

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the most prevalent in EFF samples, with abundances relative to 16S rRNA gene target ranging from 1.5 × 10−2 to 5.4 × 10−1 (Fig. 5). It was approximately four to five orders of magnitude higher than those from previously reported by Tan et al. (2018) concerning areas impacted by anthropogenic activities. Thus, it shows that conventional WWTPs are not designed for the removal of emergent pollutants such as ARGs. Of the tet genes, tet(A) was the most abundant in EFF samples, with relative abundances from 6.2 × 10−2 to 3.0 × 10−1 (Fig. 5). Similar results were obtained by Harnisz et al. (2015a), who reported relative abundances of tet(A) gene ranged from 2.6 × 10−2 to 1.0 × 10−1 in INF of Polish WWTP. According to some other authors (Nguyen et al., 2014) relatively high prevalence of tet genes in a microbial community could be partially attributed to the distribution of broad-host-range plasmids. Furthermore, the high nutrient concentrations and microbial densities that are crucial to warrant a successful wastewater treatment can be a double-edged sword for the maintenance and spread of antibiotic resistance in WWTPs (Rafraf et al., 2016). In both aerobic and anaerobic treatment tanks, the co-occurrence of antibiotic residues and resistant bacteria constitutes an optimal environment to stimulate horizontal transfer of ARGs among resident bacteria (Schlüter et al., 2007). Among the quinolone resistance genes analyzed, qepA was the most abundant in EFF samples and ranged from 6.1 × 10−2 to 3.0 × 10−1 (Fig. 5). The qepA gene is a plasmid-mediated fluoroquinolone efflux pump gene which is usually readily transferable between native bacteria (Vaz-Moreira et al., 2016), and this may have contributed to their prevalence. These results were confirmed also by the study conducted by Lee et al. (2017) and Rafraf et al. (2016) who observed the significant increase of relative amounts (gene copies/16S rRNA gene copies) of ARGs encoding resistance to beta-lactams, tetracyclines, sulfonamides and fluoroquinolones during biological wastewater treatment process in WWTPs. Despite a statistically significant decrease in the counts (gene copies/mL) of ARGs responsible for resistance to beta-lactams and sulfonamides in effluents of three WWTPs in Finland and Estonia, Laht et al. (2014) observed the considerable increase of these genes copy number normalized to 16S rRNA gene (gene copies/16S rRNA gene copies) in WWTPs' effluents. A large amount of these genes in WWTPs' effluents can directly affect the increase in their number in the reservoirs that are the receivers of these treated wastewater. As a result of this, an increase in resistance to antibiotics may occur among environmental microorganisms (Di Cesare et al., 2016; J Guo et al., 2017; Hembach et al., 2017). Fig. 3. Relative concentration of genes copies (copies number/number 16S copies) in wastewater. The explanation of abbreviations are the same as in Fig. 2.

studies (Mokracka et al., 2012; Osińska et al., 2017). Reduction of int genes counts is very important due to integrons ubiquity in populations of drug-resistant bacteria as they can play the main role in the emergence and dissemination of resistance genes (Chamosa et al., 2017; Makowska et al., 2016; Schlüter et al., 2007). Taking into consideration the number of ARGs in wastewater, the results of our study indicate that the removal of ARGs in WWTPs using conventional wastewater treatment systems is insufficient, regardless of their modification. The statistical analysis did not indicate significant (p N 0.05) removal of the majority of analyzed ARGs from EFF samples. The exception was only blaSHV and blaTEM genes (Fig. 4). There were no statistically significant differences found between the abundance of ARGs copies from WWTPs dependent on the type of inflowing wastewater. However, although the normalized concentration of ARGs was generally found to be similar between WWTPs' influent and effluent samples, the abundance of blaSHV, tet(A) and aac(6′)-Ib-cr was slightly higher in effluent samples from WWTPs which not only receives domestic or industrial sewage but also untreated hospital wastewater (Figs. 4, 5). Among all ARGs analyzed, the highest counts of ARGs copies in mL of EFF samples were observed for sul1, tet(A) and qepA, the lowest for blaTEM and blaSHV (Fig. 4). The sulfonamide resistance gene sul1 was

4. Conclusion The results of our study indicate inefficient removal of ARB and ARGs by conventional WWTPs and that bacteria released in WWTP effluents may have an ability to actively spread resistance genes among indigenous microorganisms. Furthermore, our findings clearly show that the abundances of ARB and ARGs in municipal WWTPs based on activated sludge technological solution used in treatment sewage are directly or indirectly related to the applied modification of sewage treatment system. The significant increase in the percentage of HPC and E. coli resistant to the new generation antibiotics (CTX and DOX) in total counts of microorganisms in EFF was observed particularly in effluents from WWTPs with A2/O system and with sequencing batch reactors. In these WWTPs the value of HRT was the highest. The results of our studies showed statistically significant correlations between the number of some groups of analyzed ARB and ARGs and HRT. The HRT value can therefore be the cause could of low efficacy of these kind of WWTPs. There were no statistically significant differences found between the abundance of ARGs copies from WWTPs dependent on the type of inflowing wastewater. However, the abundance of some ARGs (blaSHV, tet(A) and aac(6′)-Ib-cr) was slightly higher in effluent samples from WWTPs which not only receives domestic or industrial sewage but also untreated hospital wastewater. Additional studies, including the control of the presence of different groups of antibiotics in wastewater, would allow us to eliminate/add this parameter as an important factor

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Fig. 4. The concentration of ARGs (number of ARGs copies/1 mL) in wastewater. The explanation of abbreviations are the same as in Fig. 2.

which could influence on the number of ARB and ARGs in this kind of wastewater. To the best of our knowledge, this study represents the first report of monitoring the abundance of ARB and ARGs in the huge number of WWTPs with different modification of sewage treatment system in Poland. Taking it into consideration, this study provides valuable data to assess the functioning of WWTPs regarding the presence and persistence of antibiotic resistance in wastewater as well as the potential impact that these effluents may have on the receiving environment. Moreover, our findings highlight the importance of increasing knowledge of the mutual

influence of different resistance genes and mobile elements in the complex microbial communities of WWTPs. Acknowledgment We would like to thank the staff of the WWTPs for the possibility of samples collecting. Special thanks to Małgorzata Tomczykowska, Andrzej Strus, Grzegorz Simson and Jarosław Kalinowski, the main technologists in WWTPs. This study was supported by grants No. UMO2016/23/BNZ9/03669 from the National Science Center (Poland).

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Fig. 5. Relative concentration of ARGs (number of ARGs copies/number 16S copies) in wastewater. The explanation of abbreviations are the same as in Fig. 2.

Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi. org/10.1016/j.scitotenv.2018.05.165.

References Ahn, Y., Choi, J., 2016. Bacterial communities and antibiotic resistance communities in a full-scale hospital wastewater treatment plant by high-throughput pyrosequencing. Water 8, 580.

Aminov, R.I., Mackie, R.I., 2007. Evolution and ecology of antibiotic resistance genes. FEMS Microbiol. Lett. 271, 147–161. Amos, G.C.A., Zhang, L., Hawkey, P.M., Gaze, W.H., Wellington, E.M., 2014. Functional metagenomic analysis reveals rivers are a reservoir for diverse antibiotic resistance genes. Vet. Microbiol. 171, 441–447. APHA, 1998. American Public Health Association, Standard Methods for the Examination of Water and Wastewater. 20th ed. (Washington D.C). Baran, W., Adamek, E., Ziemiańska, J., Sobczak, A., 2011. Effects of the presence of sulfonamides in the environment and their influence on human health. J. Hazard. Mater. 196, 1–15. Bengtsson-Palme, J., Hammarén, R., Pal, C., Östman, M., Björlenius, B., Flach, C.-F., Fick, J., Kristiansson, E., Tysklind, M., Larsson, D.G.J., 2016. Elucidating selection processes for antibiotic resistance in sewage treatment plants using metagenomics. Sci. Total Environ. 572, 697–712.

314

E. Korzeniewska, M. Harnisz / Science of the Total Environment 639 (2018) 304–315

Bengtsson-Palme, J., Kristiansson, E., Larsson, D.G.J., 2018. Environmental factors influencing the development and spread of antibiotic resistance. FEMS Microbiol. Rev. 42, 68–80. Berendonk, T.U., Manaia, C.M., Merlin, C., Fatta-Kassinos, D., Cytryn, E., Walsh, F., Bürgmann, H., Sřrum, H., Norström, M., Pons, M.-N., Kreuzinger, N., Huovinen, P., Stefani, S., Schwartz, T., Kisand, V., Baquero, F., Martinez, L.J., 2015. Tackling antibiotic resistance: the environmental framework. Nat/. Rev. Microbiol. Perspect. 13, 310–317. Bilotta, G.S., Brazier, R.E., 2008. Understanding the influence of suspended solids on water quality and aquatic biota. Water Res. 42, 2849–2861. Chamosa, L.S., Álvarez, V.E., Nardelli, M., Quiroga, M.P., Cassini, M.H., Centrón, D., 2017. Lateral antimicrobial resistance genetic transfer is active in the open environment. Sci. Rep. 7, 513. CLSI, Clinical and Laboratory Standards Institute, 2015. Methods for Antimicrobial Dilution and Disk Susceptibility Testing of Infrequently Isolated or Fastidious Bacteria, Approved Standard M45-A, 2015 Wayne, PA. Di Cesare, A., Eckert, E.M., D'Urso, S., Bertoni, R., Gillan, D.C., Wattiez, R., Corno, G., 2016. Co-occurrence of integrase 1, antibiotic and heavy metal resistance genes in municipal wastewater treatment plants. Water Res. 94, 208–214. ECDC, 2015. European Centre for Disease Prevention and Control. Antimicrobial Consumption Interactive Database (ESAC-Net). http://ecdc.europa.eu/en/healthtopics/ antimicrobial-resistance-and-consumption. EUCAST, 2014. European committee on antimicrobial susceptibility testing. Breakpoints Tables for Interpretation of MICs and Zones Diameters Version 4.0. http://www. eucast.org. Ferreira da Silva, M., Vaz-Moreira, I., Gonzalez-Pajuelo, M., Nunes, O.C., Manaia, C.M., 2007. Antimicrobial resistance patterns in Enterobacteriaceae isolated from an urban wastewater treatment plant. FEMS Microbiol. Ecol. 60, 166–176. Finley, R.L., Collignon, P., Larsson, D.G., McEwen, S.A., Li, X.L., Gaze, W.H., Reid-Smith, R., Timinouni, M., Graham, D.W., Topp, E., 2013. The scourge of antibiotic resistance: the important role of the environment. Clin. Infect. Dis. 57 (5), 704–710. Fletcher, S., 2015. Understanding the contribution of environmental factors in the spread of antimicrobial resistance. Environ. Health Prev. Med. 20, 243–252. Grenni, P., Ancona, V., Caracciolo, A.B., 2018. Ecological effects of antibiotics on natural ecosystems: a review. Microchem. J. 136, 25–39. Guo, X., Feng, C., Zhang, J., Tian, C., Liu, J., 2017. Role of dams in the phase transfer of antibiotics in an urban river receiving wastewater treatment plant effluent. Sci. Total Environ. 607–608, 1173–1179. Guo, J., Li, J., Chen, H., Bond, P.L., Yuan, Z., 2017. Metagenomic analysis reveals wastewater treatment plants as hotspots of antibiotic resistance genes and mobile genetic elements. Water Res. 123, 468–478. Guo, X., Yan, Z., Zhang, Y., Xu, W., Kong, D., Shan, Z., Wang, N., 2018. Behavior of antibiotic resistance genes under extremely high-level antibiotic selection pressures in pharmaceutical wastewater treatment plants. Sci. Total Environ. 612, 119–128. GUS, 2017. Główny Urząd Statystyczny, Ochrona środowiska. Central Statistical Office, Environment, Statistical Information and Elaborations, Warsaw, Poland. Harnisz, M., Korzeniewska, E., 2018. The prevalence of multidrug-resistant Aeromonas spp. in the municipal wastewater system and their dissemination in the environment. Sci. Total Environ. 626, 377–383. Harnisz, M., Korzeniewska, E., Ciesielski, S., Gołaś, I., 2015a. Tet genes as indicators of changes in the water environment: relationships between culture-dependent and culture-independent approaches. Sci. Total Environ. 505, 704–711. Harnisz, M., Korzeniewska, E., Gołaś, I., 2015b. The impact of a freshwater fish farm on the community of tetracycline-resistant bacteria and the structure of tetracycline resistance genes in river water. Chemosphere 128, 134–141. Heijnen, L., Medema, G., 2006. Quantitative detection of E. coli. E. coli O157 and other shiga toxin producing E. coli in water samples using a culture method combined with real-time PCR. J. Water Health 04 (4), 487–498. Hembach, N., Schmid, F., Alexander, J., Hiller, C., Rogall, E.T., Schwartz, T., 2017. Occurrence of the mcr-1 colistin resistance gene and other clinically relevant antibiotic resistance genes in microbial populations at different municipal wastewater treatment plants in Germany. Front. Microbiol. 8, 1282. Hu, Z.R., Houweling, D., Dold, P., 2012. Biological nutrient removal in municipal wastewater treatment: new directions in sustainability. J. Environ. Eng. 138 (3), 307–317. Jiao, Y.-N., Chen, H., Gao, R.-X., Zhu, Y.-G., Rensing, C., 2017. Organic compounds stimulate horizontal transfer of antibiotic resistance genes in mixed wastewater treatment systems. Chemosphere 184, 53–61. Kelly, B.G., Vespermann, A., Bolton, D.J., 2009. Gene transfer events and their occurrence in selected environments. Food Chem. Toxicol. 47, 978–983. Khan, S., Knapp, C.W., Beattie, T.K., 2016. Antibiotic resistant bacteria found in municipal drinking water. Environ. Prog. 3 (3), 541–552. Korzeniewska, E., Harnisz, M., 2012. Culture-dependent and culture-independent methods in evaluation of emission of Enterobacteriaceae from sewage to the air and surface water. Water Air Soil Pollut. 223, 4039–4046. Korzeniewska, E., Harnisz, M., 2013a. Beta-lactamase producing Enterobacteriaceae in hospital effluents. J. Environ. Manag. 123, 1–7. Korzeniewska, E., Harnisz, M., 2013b. Extended-spectrum beta-lactamase (ESBL)-positive Enterobacteriaceae in municipal sewage and their emission to the environment. J. Environ. Manag. 128, 904–911. Korzeniewska, E., Korzeniewska, A., Harnisz, M., 2013. Antibiotic resistant Escherichia coli in hospital and municipal sewage and their emission to the environment. Ecotoxicol. Environ. Saf. 91, 96–102. Kumar, K., Singh, G.K., Dastidar, M.G., Sreekrishnan, T.R., 2014. Effect of mixed liquor volatile suspended solids (MLVSS) and hydraulic retention time (HRT) on the performance of activated sludge process during the biotreatment of real textile wastewater. Water Resources Ind. 5, 1–8.

Kümmerer, K., 2009. Antibiotics in the aquatic environment – a review – part I. Chemosphere 75, 417–434. Laht, M., Karkman, A., Voolaid, V., Ritz, C., Tenson, T., Virta, M., Kisand, V., 2014. Abundances of tetracycline, sulphonamide and beta-lactam antibiotic resistance genes in conventional wastewater treatment plants (WWTPs) with different waste load. PLoS One 9, e103705. Lai, T.M., Dang, H.V., Nguyen, D.D., Yim, S., Hur, J., 2011. Wastewater treatment using a modified A2/O process based on fiber polypropylene media. J. Environ. Sci. Health A Tox. Hazard. Subst. Environ. Eng. 46 (10), 1068–1074. Le Corre, K.S., Ort, C., Kateley, D., Allen, B., Escher, B.I., Keller, J., 2012. Consumption-based approach for assessing the contribution of hospitals towards the load of pharmaceutical residues in municipal wastewater. Environ. Int. 45, 99–111. Lee, J., Jeon, J.H., Shin, J., Jang, H.M., Kim, S., Song, M.S., Kim, Y.M., 2017. Quantitative and qualitative changes in antibiotic resistance genes after passing through treatment processes in municipal wastewater treatment plants. Sci. Total Environ. 605–606, 906–914. Lekunberri, I., Villagrasa, M., Balcázar, J.L., Borrego, C.M., 2017. Contribution of bacteriophage and plasmid DNA to the mobilization of antibiotic resistance genes in a river receiving treated wastewater discharges. Sci. Total Environ. 601–602, 206–209. Leung, H.W., Minh, T.B., Murphy, M.B., Lam, J.C.W., So, M.K., Martin, M., Lam, P.K.S., Richardson, B.J., 2012. Distribution, fate and risk assessment of antibiotics in sewage treatment plants in Hong Kong, South China. Environ. Int. 42, 1–9. Lien, L.T.Q., Lan, P.T., Chuc, N.T.K., Hoa, N.Q., Nhung, P.H., Thoa, N.T.M., Diwan, V., Tamhankar, A.J., Lundborg, C.S., 2017. Antibiotic resistance and antibiotic resistance genes in Escherichia coli isolates from hospital wastewater in Vietnam. Int. J. Environ. Res. Public Health 14, 699. Lupan, I., Carpa, R., Oltean, A., Kelemen, B.S., Popescu, O., 2017. Release of antibiotic resistant bacteria by a waste treatment plant from Romania. Microbes Environ. 32 (3), 219–225. Makowska, N., Koczura, R., Mokracka, J., 2016. Class 1 integrase, sulfonamide and tetracycline resistance genes in wastewater treatment plant and surface water. Chemosphere 144, 1665–1673. Marti, E., Huerta, B., Rodriguez-Mozaz, S., Barceló, D., Jofre, J., Balcázar, J.L., 2014. Characterization of ciprofloxacin-resistant isolates from a wastewater treatment plant and its receiving river. Water Res. 61, 67–76. Marti, R., Tien, Y.-C., Murray, R., Scott, A., Sabourin, L., Topp, E., 2014. Safely coupling livestock and crop production systems: how rapidly do antibiotic resistance genes dissipate in soil following a commercial application of swine or dairy manure? Appl. Environ. Microbiol. 80, 3258–3265. Modin, O., Persson, F., Wilén, B.M., Hermansson, M., 2016. Nonoxidative removal of organics in the activated sludge process. Crit. Rev. Environ. Sci. Technol. 46 (7), 635–672. Mokracka, J., Koczura, R., Kaznowski, A., 2012. Multiresistant Enterobacteriaceae with class 1 and class 2 integrons in a municipal wastewater treatment plant. Water Res. 46, 3353–3363. Neudorf, K.D., Huang, Y.N., Ragush, C.M., Yost, C.K., Jamieson, R.C., Hansen, L.T., 2017. Antibiotic resistance genes in municipal wastewater treatment systems and receiving waters in Arctic Canada. Sci. Total Environ. 598, 1085–1094. Nguyen, H.N., Van, T.T., Nguyen, H.T., Smooker, P.M., Shimeta, J., Coloe, P.J., 2014. Molecular characterization of antibiotic resistance in Pseudomonas and Aeromonas isolates from catfish of the Mekong Delta, Vietnam. Vet. Microbiol. 171, 397–405. Oliveira, M., Serrano, I., Van Harten, S., Bessa, L.J., Bernardo, F., da Costa, P.M., 2016. Fecal contamination of wastewater treatment plants in Portugal. Environ. Sci. Pollut. Res. 23, 14671–14675. Osińska, A., Harnisz, M., Korzeniewska, E., 2016. Prevalence of plasmid-mediated multidrug resistance determinants in fluoroquinolone-resistant bacteria isolated from sewage and surface water. Environ. Sci. Pollut. Res. 23, 10818–10831. Osińska, A., Korzeniewska, E., Harnisz, M., Niestępski, S., 2017. The prevalence and characterization of antibiotic-resistant and virulent Escherichia coli strains in the municipal wastewater system and their environmental fate. Sci. Total Environ. 577, 367–375. Pan, M., Chu, L.M., 2018. Occurrence of antibiotics and antibiotic resistance genes in soils from wastewater irrigation areas in the Pearl River Delta region, southern China. Sci. Total Environ. 624, 145–152. Patel, S., 2016. Drivers of bacterial genomes plasticity and roles they play in pathogen virulence, persistence and drug resistance. Infect. Genet. Evol. 45, 151–164. PN-EN 872:2007/Ap1:2007P, 2007. Water Quality - Determination of Suspensions - The Method Using Filtration Through Glass Fiber Filters (in Polish). Proia, L., Anzil, A., Subirats, J., Borrego, C., Farrè, M., Llorca, M., Balcázar, J.L., Servais, P., 2018. Antibiotic resistance along an urban river impacted by treated wastewaters. Sci. Total Environ. 628–629, 453–466. Rafraf, D., Lekunberri, I., Sànchez-Melsió, A., Aouni, M., Borrego, C.M., Balcázar, J.L., 2016. Abundance of antibiotic resistance genes in five municipal wastewater treatment plants in the Monastir governorate, Tunisia. Environ. Pollut. 219, 353–358. Rodriguez-Mozaz, S., Chamorro, S., Marti, E., Huerta, B., Gros, M., Sànchez-Melsió, A., Borrego, C.M., Barceló, D., Balcázar, J.L., 2015. Occurrence of antibiotics and antibiotic resistance genes in hospital and urban wastewaters and their impact on the receiving river. Water Res. 69, 234–242. Schlüter, A., Szczepanowski, R., Pühler, A., Top, E.M., 2007. Genomics of IncP-1 antibiotic resistance plasmids isolated from wastewater treatment plant provides evidence for a widely accessible drug resistance pool. FEMS Microbiol. Rev. 31, 449–477. Sengupta, S., Chattopadhyay, M.K., Grossart, H.P., 2013. The multifaceted roles of antibiotics and antibiotic resistance in nature. Front. Microbiol. 4, 1–13. Singer, A.C., Shaw, H., Rhodes, V., Hart, A., 2016. Review of antimicrobial resistance in the environment and its relevance to environmental regulators. Front. Microbiol. 7, 1728. Su, H.C., Liu, Y.S., Pan, C.G., Chen, J., He, L.Y., Ying, G.G., 2018. Persistence of antibiotic resistance genes and bacterial community changes in drinking water treatment system: from drinking water source to tap water. Sci. Total Environ. 616–617, 453–461.

E. Korzeniewska, M. Harnisz / Science of the Total Environment 639 (2018) 304–315 Summers, A.O., 2006. Genetic linkage and horizontal gene transfer, the roots of the antibiotic multi-resistance problem. Anim. Biotechnol. 17 (2), 125–135. Szczepanowski, R., Linke, B., Krahn, I., Gartemann, K.-H., Guetzkow, T., Eichler, W., Puehler, A., Schlueter, A., 2009. Detection of 140 clinically relevant antibiotic resistance genes in the plasmid metagenome of wastewater treatment plant bacteria showing reduced susceptibility to selected antibiotics. Microbiol.-SGM 155, 2306–2319. Tan, L., Li, L., Ashbolt, N., Wang, X., Cui, Y., Zhu, X., Xu, Y., Yang, Y., Mao, D., Luo, Y., 2018. Arctic antibiotic resistance gene contamination, a result of anthropogenic activities and natural origin. Sci. Total Environ. 621, 1176–1184. Thiele-Bruhn, S., Beck, I.-C., 2005. Effects of sulfonamide and tetracycline antibiotics on soil microbial activity and microbial biomass. Chemosphere 59, 457–465. Tien, Y.C., Li, B., Zhang, T., Scott, A., Murray, R., Sabourin, L., Marti Romain Topp, E., 2017. Impact of dairy manure pre-application treatment on manure composition, soil dynamics of antibiotic resistance genes, and abundance of antibiotic-resistance genes on vegetables at harvest. Sci. Total Environ. 581–582, 32–39. Vaz-Moreira, I., Varela, A.R., Pereira, T.V., et al., 2016. Multidrug resistance in quinolone resistant gram-negative bacteria isolated from hospital effluent and the municipal wastewater treatment plant. Microb. Drug Resist. 22 (2), 155–163. Verma, A., Wei, X., Kusiak, A., 2013. Predicting the total suspended solids in wastewater: a data-mining approach. Eng. Appl. Artif. Intell. 26, 366–1372.

315

von Wintersdorff, C.J.H., Penders, J., van Niekerk, J.M., Mills, N.D., Majumder, S., Alphen, van, Lieke, B., Savelkoul, P.H.M., Wolffs, P.F.G., 2016. Dissemination of antimicrobial resistance in microbial ecosystems through horizontal gene transfer. Front. Microbiol. 7, 173. Wang, J., Peng, Y., Chen, Y., 2011. Advanced nitrogen and phosphorus removal in A2O-BAF system treating low carbon-to-nitrogen ratio domestic wastewater. Front. Environ. Sci. Eng. China 5 (3), 474–480. Wang, X., Cheng, B., Ji, C., Zhou, M., Wang, L., 2017. Effects of hydraulic retention time on adsorption behaviours of EPS in an A/O-MBR: biofouling study with QCM-D. Sci. Rep. 7, 2895. Wang, Q., Wang, P., Yang, Q., 2018. Occurrence and diversity of antibiotic resistance in untreated hospital wastewater. Sci. Total Environ. 621, 990–999. Wei, R., Ge, F., Huang, S., Chen, M., Wang, R., 2011. Occurrence of veterinary antibiotics in animal wastewater and surface water around farms in Jiangsu Province, China. Chemosphere 82, 1408–1414. Xu, S., Yao, J., Ainiwaer, M., Hong, Y., Zhang, Y., 2018. Analysis of Bacterial Community Structure of Activated Sludge from Wastewater Treatment Plants in Winter BioMed Research International ID 8278970.