Removal of pharmaceuticals from municipal wastewaters at laboratory scale by treatment with activated sludge and biostimulation

STOTEN-21736; No of Pages 12 Science of the Total Environment xxx (2017) xxx–xxx

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Science of the Total Environment journal homepage: www.elsevier.com/locate/scitotenv

Removal of pharmaceuticals from municipal wastewaters at laboratory scale by treatment with activated sludge and biostimulation Olga Muter a,⁎, Ingus Perkons b, Turs Selga c, Andrejs Berzins a, Dita Gudra d, Ilze Radovica-Spalvina d, Davids Fridmanis d, Vadims Bartkevics b a

Institute of Microbiology & Biotechnology, University of Latvia, 1 Jelgavas Str., Riga LV-1004, Latvia Faculty of Chemistry, University of Latvia, 1 Jelgavas Str., Riga LV-1004, Latvia Faculty of Biology, University of Latvia, 1 Jelgavas Str., Riga LV-1004, Latvia d Latvian Biomedical Research and Study Center, 1 Ratsupites Str., Riga LV-1067, Latvia b c

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

• Nutrients stimulated the removal of the majority of pharmaceuticals detected in WW • 21 pharmaceutical compounds (PCs) ranged from 13.2 ng/L to 51.8 μg/L in WW • The majority of PCs with concentrations above 1 μg/L belong to NSAID • Caffeine concentration exceeded other detected PCs by at least one order of magnitude • Comparatively low rate of ibuprofen and diclofenac removal was observed after 7 days

a r t i c l e

i n f o

Article history: Received 1 December 2016 Received in revised form 3 January 2017 Accepted 4 January 2017 Available online xxxx Editor: D. Barcelo Keywords: Antimicrobials Topic: Biodegradation Ion-Torrent Next-Generation Sequencing Pharmaceuticals Topic: Wastewater

a b s t r a c t Municipal wastewater containing 21 pharmaceutical compounds, as well as activated sludge obtained from the aeration tank of the same wastewater treatment plant were used in lab-scale biodegradation experiments. The concentrations of pharmaceutical compounds were determined by high-performance liquid chromatography coupled to Orbitrap high-resolution mass spectrometry and ranged from 13.2 ng/L to 51.8 μg/L. Activated sludge was characterized in the terms of phylogenetic and catabolic diversity of microbial community, as well as its morphology. Proteobacteria (24.0%) represented the most abundant phylum, followed by Bacteroidetes (19.8%) and Firmicutes (13.2%). Bioaugmentation of wastewater with activated sludge stimulated the biodegradation process for 14 compounds. The concentration of carbamazepine in non-amended and bioaugmented WW decreased during the first 17 h up to 30% and 70%, respectively. Diclofenac and ibuprofen demonstrated comparatively slow removal. The stimulating effect of the added nutrients was observed for the degradation of almost all pharmaceuticals detected in WW. The most pronounced effect of nutrients was found for erythromycin. The results were compared with those obtained for the full-scale WW treatment process. © 2017 Elsevier B.V. All rights reserved.

⁎ Corresponding author. E-mail address: [email protected] (O. Muter).

http://dx.doi.org/10.1016/j.scitotenv.2017.01.023 0048-9697/© 2017 Elsevier B.V. All rights reserved.

Please cite this article as: Muter, O., et al., Removal of pharmaceuticals from municipal wastewaters at laboratory scale by treatment with activated sludge and biostimulation, Sci Total Environ (2017), http://dx.doi.org/10.1016/j.scitotenv.2017.01.023

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O. Muter et al. / Science of the Total Environment xxx (2017) xxx–xxx

1. Introduction The presence of pharmaceutical compounds (PCs) in the environment has received an increasing attention of researchers (Kümmerer, 2009). PCs are continuously introduced into the environment with personal hygiene products, pharmaceutical industry waste, hospital waste and therapeutic drugs, and are prevalent at small concentrations (Kolpin et al., 2002). Consumption of abused and illicit drugs, e.g., cannabinoids, methadone, etc., is a new concern for water management, posing serious risks to human health and ecosystem integrity (Mastroianni et al., 2013; Repice et al., 2013; Nefau et al., 2013). The potential chronic effects of these compounds associated with long-term ingestion of PCs mixtures through drinking water are still largely unknown (Kümmerer, 2001; Stackelberg et al., 2004; Reungoat et al., 2010; Rivera-Utrilla et al., 2013). Wastewater treatment plants (WWTPs) were considered to be the major source discharging PCs to the environment. Fish ponds are reservoirs of antibiotic resistance genes (ARGs), which also might imply potential risks to human health (Xiong et al., 2015). The concentrations of most PCs were diluted along the river stretches, with the largest decrease found in the smallest river where solutes underwent intense exchange between surface water and the sediments (Li et al., 2016). Seasonal variation in the stability of PCs along the watercourse was reported by (Meierjohann et al., 2016). Typically, PCs are polar lipophilic molecules with more than one ionizable functional group, and most of them are moderately soluble in water. The molecular weight, structure, the identity of functional groups, and molecular shape can vary widely. Some PCs, such as erythromycin, cyclophosphamide, naproxen, and sulfamethoxazole can persist in the environment for more than a year, while others, such as clofibric acid, can persist for several years and may bioaccumulate to biologically active concentrations (Rivera-Utrilla et al., 2013). Thus, effective removal of PCs along with other priority pollutants from wastewater (WW) prior to discharge into the environment remains an important issue. The effectiveness of PCs removal depends on the WWTP technology, operating conditions, microbial community composition, methods of disinfection, and other parameters (Khanal et al., 2006; Radjenovic et al., 2009; Suarez et al., 2008; Hedgespeth et al., 2012). Aerobic conditions were shown to have faster degradation kinetics for the majority of PCs, as compared to anaerobic ones. Anaerobic process was characterized as compound-specific and did not depend on operational parameters (Suarez et al., 2010; Gonzalez-Gil et al., 2016). Differences in the micropollutant removal kinetics by attached and suspended biomass were reported by (Falås et al., 2013). Activated carbon adsorption, ozonation and other advanced oxidation processes, as well as membrane filtration are used in the treatment process. Nevertheless, none of these processes can remove all the compounds of concern (Reungoat et al., 2010). Elimination pathways of pharmaceuticals can include sorption, biodegradation, phototransformation, and other processes (Meierjohann et al., 2016). In this respect, microorganisms associated with the co-metabolic and metabolic degradation of pharmaceuticals in WW treatment process are intensively studied. The biodegradation rate is dependent on the sludge retention time and sludge characteristics, temperature, pH, redox conditions, and other parameters (Kruglova et al., 2016; Bertelkamp et al., 2016; Cherik and Louhab, 2015). The presence of carboxy groups, hydroxyl groups, and carbonyl groups in the molecule can increase the biodegradation rate, while the presence of ethers, halogens, aliphatic ethers, methyl groups and ring structures can slow this process (Bertelkamp et al., 2016). During biodegradation, PCs may undergo mineralization or transformation to either more hydrophobic or more hydrophilic derivatives (Halling-Sørensen et al., 1998; Kümmerer, 2003; Zhang et al., 2014). These processes have been shown to depend on the chemical characteristics of PCs, e.g., the presence of secondary, tertiary or quaternary

carbon atoms as well as specific functional groups (Imfeld et al., 2009; Zhang et al., 2014). However, even small changes in chemical structure of PCs may change their solubility, polarity, and other properties that govern their environmental fate. In this respect, enzymatic reactions may result in a great variation of biodegradation rates, even within the same therapeutic class (Kümmerer, 2009). Metabolites of PCs also may be persistent and may have similar ecotoxicological effects (Kim et al., 2008; Zhang et al., 2014). Biodegradation of PCs in WW could be limited due to the relatively high concentrations of other pollutants, which induce the activity of enzymes not relevant to the biodegradation of PCs. Besides, many PCs inhibit the growth or metabolism of microorganisms (Kim et al., 2008; Joss et al., 2005; Zhang et al., 2014). Addition of selected strains/mixed cultures to wastewater reactors is expected to improve the catabolism of specific compounds, including recalcitrant organic compounds (Shah, 2014; Semrany et al., 2012). Nevertheless, bioaugmentation in WWT frequently leads to inconclusive outcomes (Herrero and Stuckey, 2015). This study was aimed at comparing the microbial activity in municipal WW containing 21 PCs, while applying biostimulation and/or bioaugmentation approaches under laboratory conditions. Activated sludge from the aeration tank of the same WWTP was used for bioaugmentation. The removal of PCs, microbial growth kinetics, enzymatic activity, as well as the concentration of proteins and ammonium (NH+ 4 ) ions were evaluated. 2. Materials and methods 2.1. Wastewater and activated sludge WW was collected in May 2016 from the untreated WW basin of the major “Daugavgriva” WWTP near Riga, Latvia. The WW sample had the following characteristics: pH 6.7–6.9; biological and chemical oxygen demand up to 200 mg L−1 and 350 mg L−1, respectively. Activated sludge was sampled from the aeration tank of the same WWTP. WW retention time in the aeration tank was 5 days. WW samples were analyzed applying the HPLC-Q-Orbitrap-HRMS method described in our previous studies (Pugajeva et al., 2017). 21 PCs were included in our study and this selection was based on literature studies of pharmaceutical occurrence in municipal WWs in Europe and other countries. The compounds included in our study have the most frequent occurrence rate throughout the Europe and their concentration levels were also higher in comparison with other compounds. Detailed information on the analytical procedure is given in Supplement 3. 2.2. Biodegradation experiments Prior to incubation, WW was filtered and aerated for 15 min. Afterwards, a 100 mL aliquot of WW was enriched with microorganisms and/or nutrient composition according to the experiment setup (Table 1). Incubation was performed in 200 mL columns in triplicate, at 24 °C, with periodic agitation (once a day) for 7 days. Sampling was performed after 1 h, 24 h, 48 h, and 168 h incubation. Nutrient composition consisted of 333 μL 30% sugar beet molasses containing 40% w/w sucrose (final concentration 0.1%), previously autoclaved for 20 min at 1 bar, and 500 μL cabbage leaf extract, prepared according to Muter et al. (2008) and sterilized by filtering through hydrophilic Minisart® Syringe Filter (Sartorius, Germany). Sludge-derived culturable bacteria (WB) and fungi (WF) were obtained by plating the activated sludge on Tryptone Glucose Yeast Extract Agar (TGA, Sifin, Germany) and Rose Bengal Agar with Chloramphenicol (Biolife, Italy), respectively. Bacteria and fungi were harvested after 48 h and 72 h, respectively, and the prepared suspensions contained 2.9 × 108 CFU/mL and 3.1 × 107 CFU/mL, respectively.

Please cite this article as: Muter, O., et al., Removal of pharmaceuticals from municipal wastewaters at laboratory scale by treatment with activated sludge and biostimulation, Sci Total Environ (2017), http://dx.doi.org/10.1016/j.scitotenv.2017.01.023

O. Muter et al. / Science of the Total Environment xxx (2017) xxx–xxx

2.3. Ion Torrent PGM sequencing 2.3.1. DNA extraction DNA was extracted from a total of seven samples using MoBio PowerSoil DNA Isolation Kit (MoBio Laboratories, Inc., USA). Samples first were centrifuged at 4000 rpm +4 °C for 10 min and the supernatant was discarded. The following protocol was performed according to the manufacturer's guidelines. The concentration of extracted DNA was measured using Qubit® 2.0 Fluorometer High Sensitivity Assay (Life Technologies, USA), but the amount, average size and quality of the DNA was assessed using electrophoresis in 1.2% agarose gels. 2.3.2. Polymerase chain reaction Primers were designed for the PCR amplification of 16S rRNA V3 region specific to the domain bacteria. DNA was amplified separately by reverse (Probio_Uni_R 5′-ATTACCGCGGCTGCT-3′) and forward (Probio_Uni_F 5′-CCTACGGGRSGCAGCAG-3′) primers as previously described (Milani et al., 2013). Both primers were tagged with 10–11 bp unique barcode labels along with the adapter sequence (5′CCATCTCATCCCTGCGTGTCTCCGAC-3′) to allow multiple samples to be included in a single sequencing run. PCR amplification was carried out using GeneAmp® PCR System 9700 (Thermo Fisher Scientific, USA). The PCR conditions used were as follows: 98 °C for 30 s, 35 cycles of 98 °C for 10 s, 67 °C for 15 s, 72 °C for 15 s with a final extension at 72 °C for 7 min. 16S rRNA PCR products were then quantified, pooled and purified for the sequencing reaction using NucleoMag® NGS Clean-Up and Size Select kit (Macherey-Nagel, Germany). The quality and acquired amount of 16S rRNA V3 amplicons was assessed using Agilent DNA 7500 kit on Agilent 2100 BioAnalyzer (Agilent Technologies, USA). 2.3.3. 16S sequencing analysis Prior to clonal amplification, each library was diluted to 12 pM and pooled. Sample emulsion PCR, emulsion breaking, and enrichment were performed using the Ion PGM™ Hi-Q™ OT2 Kit (Life Technologies, USA) by following the manufacturer's instructions. In brief, the input concentration of the DNA template copy/Ion Sphere Particles (ISPs) was added to the emulsion PCR master mix and the emulsion was generated using the One Touch DL apparatus (Life Technologies, USA). Next, the ISPs were recovered and template-positive ISPs were enriched using Dynabeads MyOne™ Streptavidin C1 beads (Life Technologies, USA). ISP enrichment was confirmed using a Qubit 2.0 fluorometer (Life Technologies, USA). The complete sample was loaded onto a 318 v2 chip and sequenced on the PGM for 500 cycles employing the Ion PGM™ Hi-Q™ Sequencing Kit. Bidirectional sequencing was performed (i.e., the sequence reads started from forward and reverse PCR primers), but the reads were not paired. Each run was expected to produce approximately 190,000 reads. After the sequencing run was completed, the individual sequence reads were filtered by the PGM software to remove low Table 1 Experiment setup. Seta

Wastewater, mL

Microorganisms

Nutrient composition, μL

W W-N WS WS-N WB WB-N WF WF-N

100.0 99.2 98.0 97.2 99.0 98.2 99.0 98.2

No No Activated sludgeb, 2 mL Activated sludge, 2 mL Sludge-derived bacteria, 1 mL Sludge-derived bacteria, 1 mL Sludge-derived fungi, 1 mL Sludge-derived fungi, 1 mL

No 833 No 833 No 833 No 833

a W – wastewater; WS – wastewater with activated sludge; WB – wastewater with sludge-derived culturable bacteria; WF – wastewater with sludge-derived culturable fungi; N – nutrient composition. b Concentration of the total suspended solids (TSS) in WS and WS-N was 390 mg TSS/L.

3

quality sequences. Sequences matching the PGM 3′ adaptor were automatically trimmed. All PGM quality-approved, trimmed and filtered data were exported as bam files. 2.3.4. Data analysis Sequencing data analysis was carried out using QIIME version 1.8.0 and UPARSE pipeline version 7.0.1001 to quality-filter and cluster 16S rRNA amplicon sequences (Pylro et al., 2014). Sequences with the mean sequence quality score N 20 passed the quality control. Operational Taxonomic Units (OTUs) were built at 97% sequence identity with UCLUST algorithm (Edgar, 2010). Taxonomic assignment to the lowest possible rank was performed with RDP (Wang et al., 2007), using the Greengenes (DeSantis et al., 2006) (http://greengenes.secondgenome. com) reference dataset (gg_otus-13_8 release). 2.4. Microscopy study Samples were analyzed using a Leica DM RA-2 confocal laser scanning microscope (Germany) equipped with a TCS-SL confocal scanning head. Propidium iodide (PI) was excited at 488 nm band and fluorescence was detected between 600 nm and 640 nm. 2.5. Microbiological and biochemical assays The dehydrogenase (DHA) activity was determined by reduction of 2-(4-iodophenyl)-3-(4-nitrophenyl)-5-phenyl-2H-tetrazolium chloride (INT, Fluka, Switzerland) to iodonitrophenylformazan (INTF). A 100 μL portion of a solution prepared from INT (40 mg), 1% aqueous glucose solution (1 mL), and 0.25 M TRIS (20 mL) was added to 50 μL of WW and incubated for 24 h at 37 °C. INTF was extracted with a 1:1 mixture of ethanol and dimethylformamide (Lab-Scan, Poland) for 10 min and the absorbance of the extract was measured at 485 nm (Camiña et al., 1998). The concentration of NH+ 4 ions was measured colorimetrically at 425 nm in the presence of Nessler reagent. The concentration of proteins was determined with Bradford reagent and measured at 595 nm. Fluorescein diacetate (FDA, Fluka, Switzerland) hydrolysis activity was determined by incubating for 3 h in 0.06 M phosphate buffer (pH 7.6) at 37 °C, and the absorbance was measured at 490 nm (Adam and Duncan, 2001). The WW samples were diluted serially, afterwards spread on Tryptone Glucose Yeast Extract Agar (TGA, Sifin, Germany) to cultivate aerobic heterotrophic bacteria. The colony forming units (CFUs) were counted after plate incubation for 72 h at 37 °C. The susceptibility test was performed with ciprofloxacin (5 μg) (BD BBL™ SensiDisc™, USA). 2.5.1. Estimation of microbial functional diversity by Biolog EcoPlate™ Catabolic diversity of the microbial community in the activated sludge was determined using Biolog EcoPlate™ (Biolog, Inc., USA). The measurement of substrate metabolism with EcoPlate™ is based on color formation from tetrazolium dye, a redox indicator. A 10 mL aliquot of activated sludge was suspended in 40 mL of sterile 0.85% NaCl solution, then inoculated (180 μL) into each well and afterwards incubated for 48 h at 37 °C. The microbial activity in each well was expressed as average well-color development measured at 620 nm, using microplate reader Asys Expert Plus (Biochrom, UK). The results of Biolog profiles were presented by the Shannon diversity index, which was calculated by the following Eq. (1): H ¼ −Σ p j log2 p j

ð1Þ

where pj = relative color intensity of individual well (Gabor et al., 2003). 2.6. Statistical analysis The experiment was performed in triplicate. Microbiological and biochemical measurements were also made in triplicate, thus nine

Please cite this article as: Muter, O., et al., Removal of pharmaceuticals from municipal wastewaters at laboratory scale by treatment with activated sludge and biostimulation, Sci Total Environ (2017), http://dx.doi.org/10.1016/j.scitotenv.2017.01.023

O. Muter et al. / Science of the Total Environment xxx (2017) xxx–xxx

the analgesic acetaminophen (10.2 μg/L) and antibiotic trimethoprim (1.17 μg/L). Both of these compounds degraded by about 5 times during the treatment (Petrović et al., 2005). Paracetamol, naproxen, and ibuprofen were the most abundant compounds at five WWTPs in China, with the mean concentrations of 41.7, 35.7, and 22.3 μg/L, respectively, with the removal efficiency for most compounds exceeding 90% (Yu et al., 2013). Kostich and co-workers reported data on the occurrence of 56 PCs in the effluents from 50 WWTPs across the US. Hydrochlorothiazide was found in all samples. Metoprolol, atenolol, and carbamazepine were found in over 90% of the samples. Valsartan had the highest average concentration (1.60 μg/L) across all 50 samples (Kostich et al., 2014).

values for each experimental variant were obtained. The data presented in the figures are expressed as mean value ± standard deviation. The differences between treatments were assessed by the Student's t-test and one-way analysis of variance (ANOVA). The coefficient of determination (r2) of linear regression model was estimated using Microsoft Excel. 3. Results and discussion 3.1. Characterization of WW 3.1.1. Chemical testing for the presence of PCs The determination of PCs in WW samples revealed the presence of 21 PCs with concentrations ranging from 13.2 ng/L to 51,833.6 ng/L (Fig. 1). The concentration of caffeine exceeded those of other pharmaceuticals by at least one order of magnitude. Caffeine is characterized as an easily degradable compound and the mean removal efficiency for caffeine is about 90% (Li et al., 2014). Among the other PCs with the concentrations above 1000 ng/L, were the following: acetaminophen N naproxen N ibuprofen N xylazine N diclofenac N ciprofloxacin N valsartan (Fig. 1). The majority of these compounds belong to the group of nonsteroidal anti-inflammatory drugs (NSAID), except for the veterinary alpha-adrenergic agonist xylazine, the antibiotic ciprofloxacin and the angiotensin-receptor blocker valsartan. Comparing the literature data on the occurrence of PCs in untreated WW samples obtained from different countries and different WWTPs, specific differences can be observed. As reported by Petrović et al. (2005), the mean concentrations of PCs detected in untreated WW ranged from 23 ng/L to 590 ng/L, except for

3.2.1. Bacterial diversity by Ion-Torrent PGM Next-Generation Sequencing The massive parallel sequencing analysis of the activated sludge provided 683,777 sequences, but the number of sequences was reduced to 328,444 after QC. Overall, 18,845 OTUs have been identified. The relative abundance of bacterial taxonomic groups is shown in Fig. 2. Proteobacteria (24.0%) represented the most abundant phylum, followed by Bacteroidetes (19.8%) and Firmicutes (13.2%). These phyla are usually found in activated sludge (Zhang et al., 2016a; Zhang et al., 2016b; Hu et al., 2012; Kwon et al., 2010; Yang et al., 2011). Among the 16S rDNA sequences, 20.2% of OTUs remained unassigned. Fig. 2A shows 15 phyla, which were found to be represented at N 0.1% levels. Additionally, 20 phyla were identified with the number of OTUs ranging from 0.01% to 0.08% (data not shown).

2232.5 ± 222.3

1274.8 ± 30.1

315.5 ± 17.4

137.3 ± 18.1

3998.5 ± 537.9

1184.0 ± 77.6

329.1 ± 38.8

602.9 ± 22.9

224.7 ± 17.8

245.8 ± 27.7

385.9 ± 38.6

967.4 ± 95.7

173.4 ± 21.8

1916.2 ± 211.6

51833.6 ± 2553.6 1264.8 ± 41.7

4673.1 ± 674.9 289.9 ± 21.7

1.0E+04

154.2 ± 16.0

ng/L

1.0E+05

1.0E+03

3.2. Characterization of the activated sludge

740.1 ± 67.8

4

13.2 ± 1.3

1.0E+02

1.0E+01

Ibuprofen

Diclofenac

Simvastatin

Atorvastatin

Valsartan

Naproxen

Ketoprofen

Losartan

Clarithromycin

Carbamazepine

Fluoxetine

Erythromycin

Azithromycin

Metoprolol

Sulfamethoxazole

Xylazine

Caffeine

Ciprofloxacin

Trimethoprim

Acetaminophen

Atenolol

1.0E+00

Fig. 1. The concentration of PCs in untreated wastewater used in the biodegradation experiments.

Please cite this article as: Muter, O., et al., Removal of pharmaceuticals from municipal wastewaters at laboratory scale by treatment with activated sludge and biostimulation, Sci Total Environ (2017), http://dx.doi.org/10.1016/j.scitotenv.2017.01.023

O. Muter et al. / Science of the Total Environment xxx (2017) xxx–xxx

5

100% 90% Relative abundance, %

80% 70% 60% 50% 40% 30% 20% 10%

Spirochaetes WS3 Verrucomicrobia Other GN02 SR1 Gemmatimonadetes TM7 Nitrospirae Chlorobi Acidobacteria Chloroflexi Actinobacteria Firmicutes Bacteroidetes Unassigned;Other Proteobacteria

0% A. Phylum level distribution 100% 90% Relative abundance, %

80% 70% 60% 50% 40% 30% 20% 10%

Phylum Proteobacteria; class Alphaproteobacteria; order Rhizobiales Phylum Actinobacteria; class Acidimicrobiia; order Acidimicrobiales Phylum Chlorobi; class SJA-28; order Phylum Bacteroidetes; class Sphingobacteriia; order Sphingobacteriales Phylum Nitrospirae; class Nitrospira; order Nitrospirales Phylum Proteobacteria; class Gammaproteobacteria; order Xanthomonadales Phylum Chloroflexi; class Anaerolineae; order Caldilineales Phylum Proteobacteria; class Alphaproteobacteria; order Sphingomonadales Phylum Proteobacteria; class Alphaproteobacteria; order Rhodobacterales Phylum Proteobacteria; class Deltaproteobacteria; order Myxococcales Phylum Bacteroidetes; class Flavobacteriia; order Flavobacteriales Phylum Proteobacteria; class Betaproteobacteria; order Rhodocyclales Phylum Actinobacteria; class Actinobacteria; order Actinomycetales Phylum Firmicutes; class Clostridia; order Clostridiales Phylum Proteobacteria; class Betaproteobacteria; order Burkholderiales Phylum Firmicutes; class Bacilli; order Lactobacillales Phylum Bacteroidetes; class [Saprospirae]; order [Saprospirales] Unassigned; Other

0% B. Order level distribution

Fig. 2. The composition of bacterial community of 16S rRNA sequences from activated sludge. A and B - taxonomical profiling of the phylum and order level distribution, respectively.

3.2.2. The characteristics of microorganisms culturable by EcoPlate™ The activated sludge was characterized by community level physiological profile (CLPP). The catabolic diversity of this microbial community is presented in Fig. 3. Among the substrates represented in EcoPlates™,

2 1.8 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0 Water Pyruvic Acid… Tween 40 Tween 80 Cyclodextrin Glycogen F2 D D-Cellobiose α-D-Lactose β-Methyl-… D-Xylose -Erythritol D-Mannitol N-Acetyl-… D-Glucosaminic … Glucose-1-… D,L-α-Glycerol … D-Galactonic … D-Galacturonic … 2-Hydroxy … 4-Hydroxy … γ-Hydroxy Itaconic Acid α-Ketobutyric … D-Malic Acid L-Arginine L-Asparagine L-Phenylalanine L-Serine L-Threonine Glycyl-LGlutamic … Phenylethylamine

OD 620

At the order level, 87 bacterial taxa were identified in the range from 0.03% to 13.82%. Fig. 2B represents those bacterial taxa with abundance exceeding 1%. Saprospirales (13.8%) and Lactobacillales (8.9%) were found to be the most abundant order in the tested activated sludge.

Fig. 3. Substrate utilization patterns of the sludge microorganisms determined by EcoPlates™, where the OD620 value for each substrate is an average of three replicates. The incubation time was 48 h.

Please cite this article as: Muter, O., et al., Removal of pharmaceuticals from municipal wastewaters at laboratory scale by treatment with activated sludge and biostimulation, Sci Total Environ (2017), http://dx.doi.org/10.1016/j.scitotenv.2017.01.023

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Fig. 4. Confocal laser scanning micrographs of activated sludge. A and B, scanned along xyz axes (20 μm and 10 μm, respectively), 20 optical sections. Free projection, green color corresponds to particles of degraded organic matter, red – nucleic acids containing organisms, yellow – co-localization of nucleic acids containing organisms with particles of degraded organic matter. Scale bar: 30 μm and 7.5 μm, respectively. C-1 and C-2. Scanned along xyz axes (20 μm and 10 μm, respectively), 20 optical sections, red – nucleic acids containing organisms. C-2, color coded projection, blue – top, red – bottom. Scale bar: 7.5 μm. D-1 and D-2. Scanned along xyz axes (20 μm and 10 μm, respectively), 20 optical sections, red – nucleic acids containing organisms. D-2, color coded projection, blue – top, red – bottom. Scale bar: 7.5 μm. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

The data on catabolic diversity of activated sludge obtained in EcoPlates™ have been previously reported (Yang et al., 2011; Paixão et al., 2007; Gryta et al., 2014). The results obtained in different studies varied due to the differences between WWTPs, experiment setup, incubation time, and other factors.

only few were used by microorganisms, among them D-galacturonic acid and L-asparagine being metabolized most actively. The Shannon-Weiner's index (H′) was calculated for assessing the biodiversity of microbial community in activated sludge. For metabolic potential, the H′ index was found to be 2.58, while for phylogenetic diversity it was 10.80.

120 Remained PCs, %

W

WS

WB

WF

100 80 60 40

Diclofenac

Ibuprofen

Simvastatin

Atorvastatin

Valsartan

Naproxen

Losartan

Ketoprofen

Clarithromycin

Fluoxetine

Carbamazepine

Erythromycin

Metoprolol

Azithromycin

Xylazine

Ciprofloxacin

Caffeine

Trimethoprim

Atenolol

Acetaminophen

0

Sulfamethoxazole

20

Fig. 5. The concentration of PCs remaining in wastewater after incubation for 17 h. W – wastewater; WS – wastewater with activated sludge; WB – wastewater with sludge-derived culturable bacteria; WF – wastewater with sludge-derived culturable fungi. Error bars represent the standard deviation at 5% level of significance.

Please cite this article as: Muter, O., et al., Removal of pharmaceuticals from municipal wastewaters at laboratory scale by treatment with activated sludge and biostimulation, Sci Total Environ (2017), http://dx.doi.org/10.1016/j.scitotenv.2017.01.023

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3.2.3. Visualization by microscopy Microscopy examination showed that activated sludge was typical with a high variety of bacteria. There were free living, colony forming and filamentous species of bacteria. Bacteria were located among sludge particles of degraded organic matter (Fig. 4, A and B). Among eukaryotes, protozoans Sarcodina (represented by Arcella artocrea) and Mastigophora; ciliate protist Opercularia sp., rotifer Rotaria citrinus were observed. Confocal laser scanning microscopy with 3 D projections permitted to observe three dimensional structure of the sludge for better classification of protozoa and metazoa and analyze co-localization of these diverse organisms (Fig. 4, C-1, C-2, D-1 and D-2). Microscopic observations proved that activated sludge used in this experiment were potentially effective for degradation and removal of waste products.

7

3.3. Removal of pharmaceuticals from WW during incubation 3.3.1. The effect of bioaugmentation on the biodegradation of PCs Microbial activity in the control set, i.e., nonaugmented WW was found to be compound-specific. Thus, for six of the observed 21 PCs the removal efficiency was below 20% after 17 h in WW without bioaugmentation (W), in the following order: diclofenac ≤ ibuprofen b sulfamethoxazole b ketoprofen b valsartan = losartan (Fig. 5). Bioaugmentation (WS) stimulated the biodegradation process for 14 compounds. The activated sludge was more efficient for trimethoprim followed by acetaminophen (Fig. 5). Conversely, the addition of activated sludge to WW did not stimulate the biodegradation of ciprofloxacin and sulfamethoxazole, while the addition of sludge-derived bacteria

30 W/W-N WB/WB-N

17h

25

WS/WS-N WF/WF-N

15 10

Diclofenac

Ibuprofen

Simvastatin

Valsartan

Atorvastatin

Naproxen

Losartan

W/W-N WB/WB-N

48h

25

WS/WS-N WF/WF-N

20 15 10

30

Diclofenac

Ibuprofen

Simvastatin

Valsartan

Atorvastatin

Naproxen

Losartan

W/W-N WB/WB-N

168h

25

Ketoprofen

Clarithromycin

Carbamazepine

Fluoxetine

Erythromycin

Metoprolol

Azithromycin

Caffeine

Ciprofloxacin

Trimethoprim

Acetaminophen

Atenolol

0

Xylazine

5 Sulfamethoxazole

Ratio W/W-N

Ketoprofen

Clarithromycin

Carbamazepine

Fluoxetine

Erythromycin

Metoprolol

30

Azithromycin

Xylazine

Sulfamethoxazole

Trimethoprim

Acetaminophen

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Fig. 6. The effects of nutrients on the removal of PCs, expressed as the ratio of the residual PCs in the non-stimulated wastewater, compared to the nutrient-stimulated wastewater. W – wastewater; WS – wastewater with activated sludge; WB – wastewater with sludge-derived culturable bacteria; WF – wastewater with sludge-derived culturable fungi; N – nutrients. Error bars given as in Fig. 5.

Please cite this article as: Muter, O., et al., Removal of pharmaceuticals from municipal wastewaters at laboratory scale by treatment with activated sludge and biostimulation, Sci Total Environ (2017), http://dx.doi.org/10.1016/j.scitotenv.2017.01.023

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(WB) or fungi (WF) reduced the remaining concentration compared to non-augmented water (W) during the first 17 h from 65% to 30% and from 98% to 40%, respectively (Fig. 5). Ibuprofen and diclofenac were found to be comparatively resistant to biodegradation. More detailed behavior of these compounds will be discussed below, in Section 3.3.3. On the contrary, the concentration of carbamazepine in the nonaugmented and bioaugmented wastewater decreased during the first 17 h by up to 30% and 70%, respectively. Zhang et al. (2014) summarized the data from the studies with aquatic plant-based systems. According to that review, the removal efficiency of ibuprofen and diclofenac (0 b Log Dow b 2) was indicated as high (60%–80%) and moderate (40%–60%), respectively. Carbamazepine (2 b Log Dow b 3) was considered to be a poorly degradable compound (b 40%) (Zhang et al., 2014). The high persistence of carbamazepine in the activated sludge as well as in the effluents of a WWTP was reported earlier (Daneshvar et al., 2010; Yu et al., 2013). The concentration of carbamazepine in WW could decrease due to its adsorption on suspended solids, followed by further removal from water by sedimentation (Jelic et al., 2011). Besides that, photodegradation could contribute to the removal of some PCs from WW, e.g., naproxen, diclofenac, and triclosan (Zhang et al., 2014; Zhang et al., 2013; Matamoros et al., 2012). Our earlier study on the efficiency of the full-scale WWTP “Daugavgriva” in terms of the removal of PCs showed that the typical degradation extent for most of the PCs did not exceed 50%, with the exception of caffeine, acetaminophen, atenolol, and naproxen, which were

removed by up to 90% by the biological treatment in ponds (Reinholds et al., 2016). 3.3.2. Effect of biostimulation on the biodegradation of BCs The addition of nutrients to WW changed the dynamics of the removal of pharmaceuticals. The most pronounced positive effect on the removal of nutrients was found for erythromycin after 17 h, 48 h, and 168 h. Its removal was accelerated by 2.3 ÷ 11.1, 5.9 ÷ 23.1, and 6.3 ÷ 24.2 times, respectively, compared to non-stimulated sets. The degradation of sulfamethoxazole was also accelerated by the added nutrients in the range of 6.6 ÷ 27.9 times, but this effect was detected only at the beginning of incubation, i.e. after 17 h (Fig. 6). Most of the other PCs detected in WW also were more rapidly removed in the presence of added nutrients. The residual concentration of PCs in the non-stimulated wastewater was from 1.1 to 3.0 times higher than the concentration in the nutrient-stimulated WW. The positive role of glucose in the biodegradation of ibuprofen and naproxen by Bacillus thuringiensis B1 was studied by Marchlewicz et al., 2016. Ibuprofen at 20 mg L−1 concentration was degraded within 6 days and 6 mg L− 1 of naproxen was removed within 35 days (Marchlewicz et al., 2016). Interestingly, some PCs were affected by the addition of nutrients in the opposite way. In particular, the removal of clarithromycin and atorvastatin was hindered in the presence of nutrients at the beginning of incubation, while for atenolol, xylazine, and carbamazepine this effect was observed after 48 h and 168 h (Fig. 6).

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Please cite this article as: Muter, O., et al., Removal of pharmaceuticals from municipal wastewaters at laboratory scale by treatment with activated sludge and biostimulation, Sci Total Environ (2017), http://dx.doi.org/10.1016/j.scitotenv.2017.01.023

O. Muter et al. / Science of the Total Environment xxx (2017) xxx–xxx

3.3.3. The biodegradation of pharmaceuticals known as easily biodegradable The comparison of different PCs in WW by their biodegradability under the test conditions provided some unexpected results. Thus, diclofenac and ibuprofen were removed comparatively slowly. During the first 17 h of incubation, no degradation of these two compounds in the original WW was observed, although slight decrease (up to 20– 30%) was detected in the bioaugmented WW samples (Figs. 5, 7). Nevertheless, further incubation resulted in gradual removal of these PCs. After incubation for 168 h, the lowest remaining concentrations of ibuprofen among the tested types of treatment were found to be in WS-N (19%), WB-N (13%), and WB-F (12%) samples. The removal of diclofenac was slower, as compared to ibuprofen, and varied in the range from 29% to 53%, irrespectively of the type of treatment (Fig. 7). The stimulating effect of nutrients on biodegradation was more pronounced for ibuprofen. Particularly, the ratio of the remaining ibuprofen in the non-stimulated vs. the nutrient-stimulated types of treatment gradually increased from [0.9 ÷ 1.5] to [1.4 ÷ 1.8] and [1.8 ÷ 2.5] after 17 h to 48 h and 168 h, respectively (Fig. 6). Such a tendency was also observed for diclofenac, but to a lesser extent. The maximum

A

ratio of 1.4 was achieved in the W-N and WF-N sets after incubation for 168 h (Fig. 6). In earlier studies by other authors, the average extent of ibuprofen and diclofenac degradation in WWTP was reported to be 49% and 14%, respectively (Petrović et al., 2005). Li et al. (2014) reported the average removal efficiency of 87% and 37% for ibuprofen and diclofenac, respectively (Li et al., 2014). The structural similarity of both compounds was pointed out. They belong to a group of aryl derivatives of propionic acid, and differ only by the composition of aryl group (Matamoros and Bayona, 2006; Zhang et al., 2014). Nevertheless, the presence of chlorine substituents and two aromatic rings in the molecule of diclofenac should result in a lower bioavailability, as compared to ibuprofen. 3.3.4. The biodegradation of pharmaceuticals with antimicrobial properties Particular attention was paid to the biodegradation dynamics of PCs having antimicrobial properties. Six compounds of those represented in the tested WW were selected for this analysis, i.e., azithromycin, ciprofloxacin, clarithromycin, erythromycin, sulfamethoxazole and trimethoprim. A gradual decrease of the concentration of all mentioned PCs

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Fig. 8. The biodegradation of pharmaceuticals with antimicrobial properties. W – wastewater; WS – wastewater with activated sludge; WB – wastewater with sludge-derived culturable bacteria; WF – wastewater with sludge-derived culturable fungi; N – nutrients. Octanol-water partition coefficient and the initial concentration of the compound in wastewater are indicated in the title.

Please cite this article as: Muter, O., et al., Removal of pharmaceuticals from municipal wastewaters at laboratory scale by treatment with activated sludge and biostimulation, Sci Total Environ (2017), http://dx.doi.org/10.1016/j.scitotenv.2017.01.023

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was observed during the first 48 h (Fig. 8). Further incubation did not result in any significant changes of the remaining concentrations (data not shown). As shown in Fig. 8, sulfamethoxazole and trimethoprim after incubation for 17 h were comparatively more resistant to degradation, especially in the original WW (W), as compared to the other four antimicrobials. Further incubation resulted in a gradual degradation of the remaining six antimicrobials, although a removal activity was dependent on the treatment type. For example, the remaining concentrations of trimethoprim after 17 h incubation in the sets W and WS were 76.5 ± 25.5% and 5.4 ± 2.9%, respectively. In a study by Petrović et al. (2005), the mean degradation of sulfamethoxazole and trimethoprim in WWTP was reported as 35% and 75%, respectively (Petrović et al., 2005). The biodegradation of erythromycin was influenced by nutrients, as previously mentioned in Section 3.3.2. Another specific characteristic of

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this compound was the rapid degradation during the first 17 h, after which its concentration in WW remained unchanged (Fig. 8). Ciprofloxacin was detected in WW at the concentration of 1265 ng/L, which was the highest level among all six antimicrobials. Its biodegradation was stimulated by nutrients, as well as sludge-derived bacteria and fungi. Interestingly, the addition of intact activated sludge did not influence the removal of ciprofloxacin and the remaining concentration in the set WS after 168 h incubation was the highest among the tested variants, i.e., 36.3% of the original concentration (Fig. 8). Agar diffusion test revealed the abundance of ciprofloxacin resistant bacteria in the activated sludge (Suppl. 4). However, it is not clear whether this fact is attributable to the biodegradation dynamics or not. Ciprofloxacin belongs to the fluoroquinolone class of antibiotics with a wide spectrum of activity against Gram-negative bacteria. Sulfamethoxazole and trimethoprim are active against Gram-positive and Gram-

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Fig. 9. The changes of optical density (A), protein concentration (B), fluorescein diacetate hydrolysis rate (C), dehydrogenase activity (D), the number of CFU (E) and ammonium ion concentration (F) in wastewater. The error bars are as in Fig. 5.

Please cite this article as: Muter, O., et al., Removal of pharmaceuticals from municipal wastewaters at laboratory scale by treatment with activated sludge and biostimulation, Sci Total Environ (2017), http://dx.doi.org/10.1016/j.scitotenv.2017.01.023

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negative bacteria (except Pseudomonas aeruginosa), as well as some protozoa (http://www.emedexpert.com/compare-meds/ciprofloxacinvs-tmp-smz.shtml). In a study about the removal of antibiotics from wastewaters in China, 19 antibiotics were detected in the untreated and treated wastewaters, with clarithromycin (6524 ng/L) and ofloxacin (5411 ng/L) being the most abundant. The mean concentrations of target antibiotics in treated WW were obviously lower than in the untreated WW, except for ciprofloxacin (Dong et al., 2016). The sorption of ciprofloxacin on sludge particles was considered to be the principal removal pathway, and its desorption from sludge might cause a variation of its concentration during the WWT process (Plosz et al., 2010; Giger et al., 2003; Golet et al., 2003; Dong et al., 2016). Besides, some increase of the antimicrobial compound concentrations in treated WW compared to the untreated WW can occur. In the case of the WWTP used as the source of WW and activated sludge for this study, elevated contents of azithromycin, clarithromycin, and erythromycin were observed after the treatment (Reihholds et al., in press). 3.4. The microbial activity during incubation For a more complete evaluation of microbial activity towards biodegradation of PCs, the measurements of optical density, concentration of proteins, enzyme activity, and the number of CFU were performed over time. The most rapid increase of OD620 during the first 17 h of incubation was detected in non-bioaugmented wastewater (W and W-N) and WW with activated sludge (WS and WS-N) (Fig. 9A). The comparatively high standard deviation in these samples (ranging from 19% to 39%) can be explained by the process of flocculation and, hence, the inhomogeneities of samples. After 48 h incubation, the standard deviation for all tested sets varied in the range from 4% to 8%. Further incubation for 65 h and 168 h resulted in some increase of standard deviation only in the sets of experiments with activated sludge (WS and WS-N) (data not shown). The addition of nutrients (experiments W-N, WS-N, WB-N, and WFN) lead to a gradual increase of protein content, on average from 20 to 122 mg L−1 during the first 48 h of incubation (Fig. 9B). These data could point to the active growth of microbial biomass. Further incubation did not result in an increase of protein concentration (data not shown). Regression analysis revealed a correlation between the data on OD620 and the concentration of proteins, except in the case of WW with activated sludge. The highest coefficient of determination r2 (from 0.68 to 0.88) was obtained after incubation for 48 h. Proteins represent a large portion of organic nitrogen and carbon in WW treatment effluents (Westgate and Park, 2010). The enzymatic activity of microorganisms in WW serves as a valuable criterion of microbial activity. Importantly, not only bacteria and fungi, but also protozoa contributed to these reactions. Two types of enzymatic activity were tested in this study, namely, FDA and DHA. FDA is a substrate that can be hydrolyzed by a variety of non-specific enzymes and the assessment of FDA degradation is used as an indicator of total microbial activity. Dehydrogenases are ubiquitous in all intact viable microbial cells. The highest FDA hydrolysis rate among the tested variants was achieved in WW with activated sludge (WS and WS-N), which subsequently gradually decreased. No effect of nutrients on the FDA hydrolysis was found (Fig. 9C). Conversely, DHA activity was dependent on the presence of nutrients, especially in the WW augmented with bacteria (WB-N) and fungi (WF-N) (Fig. 9D). Interestingly, the experiments without added nutrients (WB and WF) exhibited the lowest DHA activity among the tested variants (Fig. 9D). The increased proliferation of microorganisms in the WW amended with nutrients is in a good agreement with the data on OD620, protein content, and DHA activity (Fig. 9E). Besides, the significantly (p b 0.01) lower concentration of N-NH+ 4 remaining in WW after 168 h incubation of the samples with added nutrients, compared to the original sample,

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pointed to the stimulating effect of nutrients on the nitrification process (Fig. 9F). 4. Conclusions Characterization of the activated sludge, as well as findings on its biodegradation potential related to different PCs, are summarized in the following conclusions. 1. The effect of activated sludge on the biodegradation process was compound-specific. In particular, the biodegradation of ciprofloxacin and sulfamethoxazole was retarded in the presence of the sludge. 2. The maximum microbial activity during 7 days of incubation was detected after 17 h. This effect was more pronounced for the WW amended with nutrient composition. 3. The stimulating effect of the added nutrients was observed for the degradation of almost all pharmaceuticals detected in WW. The addition of nutrients stimulated the nitrification process. In case of industrial WW, a biostimulation approach can be applied at the pretreatment facility before discharging to a municipal WWTP. 4. The occurrence of PCs in untreated WW varies across countries and particular WWTPs. Nevertheless, the model experiments with WW contribute further knowledge on the behavior of PCs during WW treatment process. 5. The exploration of microbial communities in activated sludge is crucial for studying and improving the performance of WW treatment. The massive DNA sequencing analysis of the activated sludge made in this study has revealed the abundance of the same taxonomic groups of bacteria that have been reported to dominate also at other WWTPs. This confirms the possibility of extrapolating the obtained data to the common processes taking place in all WWTPs in the context of PCs removal. Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.scitotenv.2017.01.023. Acknowledgements This research was financially supported by the Project No. NFI/R/ 2014/010 “Establishing of the scientific capacity for the management of pharmaceutical products residues in the environment of Latvia and Norway”. Authors are grateful to Janis Jaunbergs for suggested manuscript revisions. References Adam, G., Duncan, H., 2001. Development of a sensitive and rapid method for the measurement of total microbial activity using fluorescein diacetate (FDA) in a range of soils. Soil Biol. Biochem. 33, 943–951. Bertelkamp, C., Verliefde, A.R.D., Reynisson, J., Singhal, N., Cabo, A.J., de Jonge, M., Van der Hoek, J.P., 2016. A predictive multi-linear regression model for organic micropollutants, based on a laboratory-scale column study simulating the river bank filtration process. J. Hazard. Mater. 304, 502–511. Camiña, F., Trasar-Cepeda, C., Gil-Sotres, F., Leirós, C., 1998. Measurement of dehydrogenase activity in acid soils rich in organic matter. Soil Biol. Biochem. 30 (8–9), 1005–1011. Cherik, D., Louhab, K., 2015. Biodegradation of diclofenac: a review. Res. J. Chem. Environ. 19 (10), 40–45. Daneshvar, A., Svanfelt, J., Kronberg, L., Prévost, M., Weyhenmeyer, G.A., 2010. Seasonal variations in the occurrence and fate of basic and neutral pharmaceuticals in a Swedish river-lake system. Chemosphere 80 (3), 301–309. DeSantis, T.Z., Hugenholtz, P., Larsen, N., Rojas, M., Brodie, E.L., Keller, K., Huber, T., Dalevi, D., Hu, P., Andersen, G.L., 2006. Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl. Environ. Microbiol. 72 (7), 5069–5072. Dong, H., Yuan, X., Wang, W., Qiang, Z., 2016. Occurrence and removal of antibiotics in ecological and conventional wastewater treatment processes: a field study. J. Environ. Manag. 178, 11–19. Edgar, R.C., 2010. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26, 2460. Falås, P., Longrée, P., la Cour Jansen, J., Siegrist, H., Hollender, J., Joss, A., 2013. Micropollutant removal by attached and suspended growth in a hybrid biofilm-activated sludge process. Water Res. 47 (13), 4498–4506.

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Please cite this article as: Muter, O., et al., Removal of pharmaceuticals from municipal wastewaters at laboratory scale by treatment with activated sludge and biostimulation, Sci Total Environ (2017), http://dx.doi.org/10.1016/j.scitotenv.2017.01.023