Chemosphere 171 (2017) 118e125 Contents lists available at ScienceDirect Chemosphere journal homepage: www.elsevier.com/locate/chemosphere Effects of multiple antibiotics exposure on denitrification process in the Yangtze Estuary sediments Guoyu Yin a, b, Lijun Hou c, *, Min Liu a, b, Yanling Zheng a, b, Xiaofei Li a, b, Xianbiao Lin a, b, Juan Gao c, Xiaofen Jiang c, Rong Wang c, Chendi Yu c a b c Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai, 200241, China School of Geographic Sciences, East China Normal University, Shanghai, 200241, China State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai, 200062, China h i g h l i g h t s Multiple antibiotics exposure has synergistic inhibition on denitrification rates. Different species of antibiotics have different effect on N2O release. Combined effects of antibiotics lead to stimulation on N2O release. Multiple antibiotics exposure inhibits the abundances of nirS and nosZ genes. Different inhibition on nirS and nosZ may explain the variations of N2O release. a r t i c l e i n f o a b s t r a c t Article history: Received 10 September 2016 Received in revised form 31 October 2016 Accepted 14 December 2016 Available online 18 December 2016 Denitrification is a dominant reactive nitrogen removal pathway in most estuarine and coastal ecosystems, and plays a significant role in regulating N2O release. Although multiple antibiotics residues are widely detected in aquatic environment, combined effects of antibiotics on denitrification remain indistinct. In this work, 5 classes of antibiotics (sulfonamides, chloramphenicols, tetracyclines, macrolides, and fluoroquinolones) were selected to conduct orthogonal experiments in order to explore their combined effects on denitrification. 15N-based denitrification and N2O release rates were determined in the orthogonal experiments, while denitrifying functional genes were examined to illustrate the microbial mechanism of the combined antibiotics effect. Denitrification rates were inhibited by antibiotics treatments, and synergistic inhibition effect was observed for multiple antibiotics exposure. Different classes of antibiotics had different influence on N2O release rates, but multiple antibiotics exposure mostly led to stimulatory effect. Abundances of denitrifying functional genes were inhibited by multiple antibiotics exposure due to the antimicrobial properties, and different inhibition on denitrifiers may be the major mechanism for the variations of N2O release rates. Combined effects of antibiotics on denitrification may lead to nitrate retention and N2O release in estuarine and coastal ecosystems, and consequently cause cascading environmental problems, such as greenhouse effects and hyper-eutrophication. © 2016 Elsevier Ltd. All rights reserved. Handling Editor: Jian-Ying Hu Keywords: Denitrification N2O Antibiotics Multiple exposure Yangtze Estuary 1. Introduction The loading of reactive nitrogen (mainly nitrate) has increased significantly in the past few decades, as a result of human activities (Cui et al., 2013; Galloway et al., 2008; Liu et al., 2013; Yin et al., 2014a). A huge quantity of this reactive nitrogen, however, has * Corresponding author. E-mail address: ljhou@sklec.ecnu.edu.cn (L. Hou). http://dx.doi.org/10.1016/j.chemosphere.2016.12.068 0045-6535/© 2016 Elsevier Ltd. All rights reserved. been transported into estuarine and coastal areas, consequently leading to various environmental problems in these aquatic ecosystems (Burgin and Hamilton, 2007; Chen et al., 2016; Hou et al., 2015; Seitzinger, 2008; Zheng et al., 2016). As the dominant microbial nitrogen removal pathway in most estuarine and coastal ecosystems, denitrification has received much attention (Fernandes et al., 2012; Gomez-Velez et al., 2015; Hou et al., 2014; Yin et al., 2014a). Denitrification can mitigate eutrophication by eliminating reactive nitrogen from aquatic ecosystems permanently in the form of nitrogen gas (Deng et al., 2015; Devol, 2015; Hou et al., 2012; Yin G. Yin et al. / Chemosphere 171 (2017) 118e125 et al., 2014a). Denitrification is also intimately related to N2O generation and consumption, as N2O is an intermediate product of denitrification process (Dong et al., 2011; Hou et al., 2014; Yin et al., 2016). The radiative forcing potential of N2O is approximately 4 times of CH4 and 200 times of CO2, thus it is considered to be a major greenhouse gas affecting ozone depletion in atmospheric environment (Ravishankara et al., 2009; Reay et al., 2012). Since denitrification plays an important role in regulating eutrophication and the release of greenhouse gas, an understanding of anthropogenic influence on denitrification process is of great importance (Conley et al., 2009; Hou et al., 2014; Yin et al., 2014a). Nowadays, up to 200,000 tons of antibiotics are used annually around the world (Shi et al., 2014), due to the huge demand of medical care, aquaculture, farming, and veterinary drug usage (Looft et al., 2012; Yang et al., 2011; Zhang et al., 2015; Zhou et al., 2013). Consistent antibiotics input leads to wide distribution and occurrence of antibiotics residues in aquatic ecosystems lez et al., 2015; Yan et al., (Kümmerer, 2009a; Moreno-Gonza 2013a), and antibiotics residues may disturb natural microbial processes because of the antibacterial properties (Kümmerer, 2009b; Novo et al., 2013; Yan et al., 2013a). The effects of antibiotics on nitrate reduction processes have become an emerging topic (Brandt et al., 2015; DeVries and Zhang, 2016; Roose-Amsaleg and Laverman, 2015), and several recent studies have been operated to investigate the antibiotics influence on denitrification process (DeVries et al., 2015; Hou et al., 2014; Yan et al., 2013b; Yin et al., 2016). However, these studies are mostly carried out with single antibiotic exposure. Actually, multiple antibiotics occurrence is widely detected in aquatic ecosystems (Chen and Zhou, 2014; Looft et al., 2012; Yan et al., 2013a; Zhao et al., 2015). Combined effects of multiple antibiotics exposure may disturb N2O release and nitrate reduction in denitrification process, thus leading to various environmental problems, such as greenhouse effect and eutrophication (Canfield et al., 2010; Deegan et al., 2012; Ravishankara et al., 2009; Reay et al., 2012). Therefore, study of combined effects of antibiotics on denitrification is required to give a further understanding of reactive nitrogen and antibiotics pollution control (DeVries and Zhang, 2016; Roose-Amsaleg and Laverman, 2015). The Yangtze Estuary, one of the most heavily populated and industrialized estuarine and coastal regions in China (Deng et al., 2015), was selected as the study area. Consistent inputs of industrial and domestic sewage lead to sustained antibiotics residues and hyper-eutrophication in this area (Chen et al., 2016; Yan et al., 2013a). The most widely detected antibiotics residues in the Yangtze Estuary are sulfonamides, chloramphenicols, tetracyclines, macrolides, and fluoroquinolones (Chen and Zhou, 2014; Yan et al., 2013a; Zhang et al., 2015; Zhao et al., 2015), thus sulfamethazine (SMT), thiamphenicol (TAP), oxytetracycline (OTC), erythromycin (ERY), and norfloxacin (NOR) were selected to represent the five classes of these antibiotics, respectively. In this work, orthogonal experiments were employed to illustrate the combined effects of antibiotics on denitrification and N2O release rates, and abundances of denitrifying functional genes were also detected to investigate the microbial mechanisms of multiple antibiotics exposure at genic level. This work provides more realistic data for the understanding of denitrification process responding to multiple antibiotics exposure in aquatics ecosystems, which may help to control the pollution of both reactive nitrogen and antibiotics. 2. Materials and methods 2.1. Sampling and pretreatment Box corers were used to collect surface sediments (0e5 cm) from the intertidal zone of the Yangtze Estuary in December 2015 119 (Fig. S1, Supporting Information). The sediment samples were transported to the laboratory within 2 h. A pre-incubation was conducted to eliminate ambient antibiotics in the sediment samples in order to resemble a pristine status. Briefly, the sediment corers were pre-incubated at room temperature (25 C) in a recirculating glass container which was filled with artificial seawater having near in situ nutrient levels and salinity (Yin et al., 2016). The pre-incubation experiment lasted for about 2 months. After the pre-incubation, the sediments were extracted and the antibiotics concentrations were examined to confirm that no antibiotics residuals were left (Shi et al., 2014; Yan et al., 2013a). Subsequently, the sediment samples were used for the slurry experiments and functional gene abundance measurements. 2.2. Orthogonal experimental design The L16 (45) orthogonal experiment was applied to study the effects of multiple antibiotics exposure on denitrification rates. Five antibiotics (SMT, TAP, OTC, ERY, and NOR) were designated as five influence factors to represent the most widespread antibiotics residues in the study area (Chen and Zhou, 2014; Shi et al., 2014; Yan et al., 2013a). Four concentration levels were applied for each antibiotic, which were specifically assigned as 0, minimum concentration detected, average concentration detected, and maximum concentration detected in both estuarine water and sediments of the study area (Chen and Zhou, 2014; Yan et al., 2013a; Zhao et al., 2015). Detailed information on antibiotics concentrations and assignments in the orthogonal experimental design is exhibited in Table S1 (Supporting Information). Range analysis was conducted to make a brief description of different antibiotics influence. K value and Rj value were defined in the range analysis as two parameters. K value is referred to as the average value of each result at the same antibiotic concentration. Rj value is referred to as subtracting the minimum K value from the maximum K value in each antibiotic group. A large Rj value means a great influence of the antibiotic (Shen et al., 2016). Analysis of variance was also done to examine the significance of antibiotics influence (Yang et al., 2014). 2.3. Slurry experiments The surface sediment samples were homogenized with artificial seawater having near in situ salinity at a ratio of 1:7 (Hou et al., 2014). The slurries were purged with helium and stirred vigorously for 15 min (Hou et al., 2013). The mixed slurries were filled into respective 12 mL gas-tight vials (Exetainer, Labco, High Wycombe, UK), and then the vials were sealed with butyl-rubber septa and screw caps. A 24-h pre-incubation was operated to eliminate the background nitrate/nitrite (Hou et al., 2014). After the pre-incubation, the vials were spiked with 15NO 3 (final concentration ca. 100 mmol L1, final % 15N ca. 90e99%) (Hou et al., 2012). Meanwhile, solutions of selected antibiotics were injected into the respective vials following the orthogonal experimental design. An initial group was designated for each trial and preserved with 250 ml 50% ZnCl2 solution (Yin et al., 2016), and 8 replicates were prepared for each group. The slurries were incubated for 8 h at room temperature on a shaker table (200 rpm) (Hou et al., 2012). After the incubation, replicates of all the groups were preserved with ZnCl2 as described for the initial groups. Half of the replicates in each group were used to analyze the dissolved nitrogen gases (29N2 and 30N2) generated during the incubations by membrane inlet mass spectrometry (HPR-40, Hiden Analytical, UK), with a detection limit of 0.1 mmol L1 for N2 (Yin et al., 2014b). The denitrification rates were calculated according to the following equation (Hou et al., 2014): 120 G. Yin et al. / Chemosphere 171 (2017) 118e125 RD ¼ N30 2 ð1 Fn Þ Fn1 þ 2 N30 where RD (mmol 15N kg1 h1) represents the total 15NO 3 -based rates of denitrification; N30 (mmol 30N2 kg1 h1) represents the measured generation rates of 30N2 derived from 15NO 3 during the incubation; Fn (%) represents the fraction of 15N in total NO 3 . The remaining replicates were used to measure dissolved N2O using gas chromatography with a detection limit of 0.001 mmol L1 (Shimadzu GC-14B, Shimadzu Co., Kyoto, Japan) (Yin et al., 2016). N2O release rates were calculated using headspace equilibrium technique (Hinshaw and Dahlgren, 2013) with the following equation (Hou et al., 2014): RN ¼ Tf Ti V H1 where RN (mmol kg1 h1) means the N2O release rates; Ti and Tf (mmol mL1) mean the measured contents of dissolved N2O in the initial and final samples, respectively; H (h) means the incubation time; V (mL) is the volume of the gas-tight vials. 2.4. Molecular microbial analysis The incubated sediment slurries were collected to analyze functional gene abundances of denitrifiers. The nirS gene encoding for nitrite reductase and the nosZ gene encoding for nitrous oxide reductase were quantified to illustrate the combined effects of antibiotics on the denitrifying microbes (Black et al., 2016; Kandeler et al., 2006). The total DNA extraction in the sediment samples were conducted using Powersoil™ DNA Isolation Kits (MO BIO, USA), according to the instructions of manufacturer. The abundances of nirS and nosZ genes in the extracted DNA were determined via realtime quantitative PCR assays. The nirS gene (nitrite reductase) fragments in the extracted DNA were amplified with primers R3cd (50 -GAS TTC GGR TGS GTC TTG A- 30 ) and cd3aF (50 -GTS AAC GTS €ck et al., 2004). AAG GAR ACS GG- 30 ) (Michotey et al., 2000; Throba The nosZ gene (nitrous oxide reductase) fragments were amplified with primers nosZ2R (50 -CAK RTG CAK SGC RTG GCA GAA- 30 ) and nosZ2F (50 -CGC RAC GGC AAS AAG GTS MSS GT- 30 ) (Jones et al., 2013). The gene copy numbers of nirS and nosZ were quantified in quadruplicate using the SYBR green qPCR method with an ABI 7500 Sequence Detection System (Applied Biosystems, Canada). The qPCR systems contained 12.5 mL of Maxima SYBR Green/Rox qPCR Master Mix (Fermentas, Lithuania), 1 mL of template DNA, 1 mL of each primer (10 mmol L1, Sangon, China), and 10.5 mL of sterile ddH2O. The qPCR reactions were performed with the thermal cycling conditions of 2 min at 50 C, 10 min at 95 C, followed by 40 cycles of 30 s at 95 C, 1 min at 57 C for nirS, 60 C for nosZ, and 1 min at 72 C. Serial dilution of a known amount of plasmid DNA containing the target fragment was conducted to build the standard curves. Real-time qPCR consistency was confirmed by strong linear relationships of the standard curves between the log10 values of gene copy numbers and the threshold cycle (CT) (R2 ¼ 0.9953 for nirS, and R2 ¼ 0.9976 for nosZ). Three negative controls with no template DNA were prepared for all experiments in order to exclude possible contamination. The abundances of nirS and nosZ genes were calculated on the basis of the constructed standard curve, and then converted and expressed as copies g1 dry sediment. 2.5. Statistical analysis An analysis of variance (ANOVA) was conducted in this study. Statistical analyses were performed at the 95% confidence level (alpha ¼ 0.05) to determine whether the changes in the measured data were statistically significant. The Statistical Package of Social Sciences (SPSS, version-22.0) was used to perform all statistical analyses. 3. Results 3.1. Denitrification rates Rates of denitrification ranged from 6.87 to 12.32 mmol 15N kg1 h in the 16 trials of the orthogonal experiment (Table 1). Due to the addition of antibiotics, the denitrification rates decreased by 44.2%. The maximum denitrification rate was observed in trial 1, which was a blank group without antibiotics addition, while the minimum rate was found in trial 4. Based on the range analysis (Table 2), TAP had greater inhibition on denitrification rates than the other antibiotics (Rj ¼ 1.682), whereas ERY had the smallest inhibition effect (Rj ¼ 0.940). Denitrification rates were inhibited significantly by all the 5 antibiotics (one-way ANOVA, p < 0.05) (Table 3), however, they were observed to be slightly stimulated by the minimum concentration of ERY (0.05 ng L1) (Fig. 1). 1 Table 1 Results of the L16 (45) orthogonal experiment. RD represents the total 15NO 3 -based denitrification rates; RN represents the N2O release rates; nirS gene and nosZ gene represent the abundances of nirS gene and nosZ gene. Trials 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 SMT (ng L1) TAP (ng L1) OTC (ng L1) NOR (ng L1) ERY (ng L1) RD (mmol 0 0 0 0 0.53 0.53 0.53 0.53 47.6 47.6 47.6 47.6 89.1 89.1 89.1 89.1 0 0.91 62.9 110 0 0.91 62.9 110 0 0.91 62.9 110 0 0.91 62.9 110 0 5.13 11.6 22.5 5.13 0 22.5 11.6 11.6 22.5 0 5.13 22.5 11.6 5.13 0 0 0.2 2.6 14.2 2.6 14.2 0 0.2 14.2 2.6 0.2 0 0.2 0 14.2 2.6 0 0.05 9.68 45.4 45.4 9.68 0.05 0 0.05 0 45.4 9.68 9.68 45.4 0 0.05 12.32 ± 0.2 10.18 ± 1.0 8.66 ± 0.9 6.87 ± 0.2 9.13 ± 0.5 8.42 ± 0.6 8.77 ± 1.1 8.79 ± 0.6 8.94 ± 0.9 7.61 ± 0.2 8.80 ± 0.6 7.58 ± 0.5 8.53 ± 0.6 8.32 ± 0.7 8.16 ± 0.2 8.95 ± 0.1 15 N kg1 h1) RN (mmol kg1 h1) 0.070 0.063 0.081 0.111 0.069 0.061 0.165 0.118 0.125 0.168 0.201 0.202 0.269 0.334 0.187 0.287 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± 0.02 0.02 0.05 0.05 0.04 0.02 0.06 0.02 0.05 0.03 0.03 0.03 0.08 0.05 0.02 0.04 nirS gene (108 copies g1) 2.86 2.23 2.57 1.62 2.19 2.35 2.24 2.12 2.14 1.91 2.21 2.09 1.82 2.29 2.02 1.87 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± 0.3 0.2 0.2 0.2 0.1 0.4 0.1 0.2 0.2 0.3 0.2 0.3 0.1 0.1 0.4 0.2 nosZ gene (107 copies g1) 8.82 7.71 7.60 6.20 7.65 6.97 6.69 6.63 6.27 6.51 6.38 5.75 5.83 6.18 6.26 6.04 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± 0.2 0.3 0.3 0.3 0.5 0.6 0.3 0.2 0.2 0.3 0.2 0.2 0.2 0.4 0.2 0.2 G. Yin et al. / Chemosphere 171 (2017) 118e125 121 Table 2 The basic range analysis data of the L16 (45) orthogonal experiment. RD represents the total 15NO 3 -based denitrification rates; RN represents the N2O release rates; nirS gene and nosZ gene represent the abundances of nirS gene and nosZ gene. K1, K2, K3, and K4 represent the average value of each result at the same antibiotic concentration. Result K value SMT TAP OTC NOR ERY RD K1 K2 K3 K4 Rj K1 K2 K3 K4 Rj K1 K2 K3 K4 Rj K1 K2 K3 K4 Rj 9.508 8.778 8.232 8.490 1.276 0.081 0.103 0.174 0.269 0.188 2.320 2.225 2.088 2.000 0.320 7.582 6.985 6.228 6.078 1.504 9.730 8.632 8.598 8.048 1.682 0.133 0.156 0.158 0.180 0.046 2.252 2.195 2.260 1.925 0.327 7.142 6.842 6.732 6.155 0.987 9.622 8.762 8.678 7.945 1.677 0.155 0.130 0.164 0.178 0.048 2.322 2.132 2.280 1.897 0.425 7.052 6.842 6.670 6.307 0.745 9.248 9.075 8.588 8.098 1.150 0.193 0.163 0.151 0.121 0.072 2.370 2.095 2.135 2.032 0.338 6.860 6.638 6.950 6.425 0.525 9.220 9.230 8.298 8.280 0.940 0.136 0.160 0.153 0.179 0.043 2.228 2.120 2.208 2.078 0.150 7.055 6.678 6.538 6.602 0.517 RN nirS gene nosZ gene Fig. 1. Relationship between denitrification rates (RD) and concentrations of different antibiotics. min, ave, and max in the horizontal axis stand for minimum concentration detected, average concentration detected, and maximum concentration detected of each antibiotic, respectively. down the N2O release rates by 37.3%. TAP, OTC, and ERY accelerated the N2O release rates slightly (Fig. 2), but the stimulation was not significant (one-way ANOVA, p > 0.05). 3.2. N2O production N2O release rates ranged from 0.06 to 0.33 mmol kg1 h1 in the orthogonal experiment trials (Table 1). Compared to the blank group (trial 1), the release rates of N2O were stimulated in most trials (except for trials 2, 5, and 6). Range analysis showed that SMT (Rj ¼ 0.188) and NOR (Rj ¼ 0.072) had a greater influence on N2O release rates than TAP, OTC, and ERY (Table 2). N2O release rates were accelerated significantly by SMT (one-way ANOVA, p < 0.05), and the minimum concentration of SMT (0.53 ng L1) led to a 27.2% increase of the N2O release rates (Table 3). On the contrary, NOR inhibited N2O release rates significantly (one-way ANOVA, p < 0.05), and the maximum concentration of NOR (14.2 ng L1) cut 3.3. Q-PCR of denitrifying functional genes Abundances of denitrifying functional genes in the incubated sediments of the orthogonal experiment were quantified. The abundances of nirS and nosZ genes ranged from 1.62 108 to 2.86 108 copies g1 and from 5.75 107 to 8.82 107 copies g1 in the 16 trials, respectively (Table 1). Compared to the blank group (trial 1), the abundances of nirS and nosZ genes in the other trials were all inhibited by the addition of antibiotics. Range analysis indicated that OTC (Rj ¼ 0.425) and SMT (Rj ¼ 1.504) had the greatest inhibition effect on the abundances of nirS genes and nosZ genes, respectively (Table 2). On the other hand, ERY had the Table 3 The analysis of variance (ANOVA) data of the L16 (45) orthogonal experiment. RD represents the total 15NO 3 -based denitrification rates; RN represents the N2O release rates; nirS gene and nosZ gene represent the abundances of nirS gene and nosZ gene. SUM ¼ sum of square; df ¼ degree of freedom; MS ¼ mean of square; p < 0.05 means changes in the measured data were statistically significant at the 95% confidence level. Result Antibiotic SUM df MS F value p value RD SMT TAP OTC NOR ERY SMT TAP OTC NOR ERY SMT TAP OTC NOR ERY SMT TAP OTC NOR ERY 14.559 23.855 22.635 12.884 13.730 0.344 0.017 0.020 0.042 0.015 0.948 1.186 1.785 1.037 0.240 23.037 6.043 1.564 5.273 7.411 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4.853 7.952 7.545 4.295 4.577 0.115 0.006 0.007 0.014 0.005 0.316 0.395 0.595 0.346 0.080 7.679 2.014 0.521 1.758 2.470 3.497 5.730 5.437 3.095 3.298 38.006 1.927 2.180 4.650 1.684 5.736 7.179 10.799 6.278 1.455 22.023 5.777 7.085 1.495 2.085 0.022 0.002 0.003 0.036 0.028 0.000 0.138 0.103 0.006 0.183 0.002 0.000 0.000 0.001 0.239 0.000 0.002 0.028 0.228 0.104 RN nirS gene nosZ gene Fig. 2. Relationship between N2O release rates (RN) and concentrations of different antibiotics. min, ave, and max in the horizontal axis stand for minimum concentration detected, average concentration detected, and maximum concentration detected of each antibiotic, respectively. 122 G. Yin et al. / Chemosphere 171 (2017) 118e125 Fig. 3. Relationship between abundances of nirS gene and concentrations of different antibiotics. min, ave, and max in the horizontal axis stand for minimum concentration detected, average concentration detected, and maximum concentration detected of each antibiotic, respectively. smallest influence on the abundances of both nirS and nosZ genes (Rj ¼ 0.150 and 0.517, respectively). SMT, TAP, and OTC inhibited both nirS and nosZ genes significantly (one-way ANOVA, p < 0.05), and NOR only had significant inhibition on nirS genes (Table 3). Though a slight inhibition effect was observed for ERY on both nirS and nosZ genes (Fig. 3 and Fig. 4), the inhibition was not significant (one-way ANOVA, p > 0.05). 4. Discussion 4.1. Antibiotics influence on denitrification rates The denitrification rates were inhibited significantly by all the 5 antibiotics used in this study, as the metabolism of denitrifying bacteria can be inhibited by antibiotics (Conkle and White, 2012; Yan et al., 2013a). According to our previous study, denitrification rates were reduced approximately 30% by 500 ng L1 SMT and 1000 ng L1 TAP, respectively (Hou et al., 2014; Yin et al., 2016). In this study, the total concentrations of antibiotics were no more than 300 ng L1 in all the 16 trials. However, denitrification rates were cut down by up to 44.2% in the orthogonal experiment, implying that multiple antibiotics exposure may lead to greater inhibition effect on denitrification rates. The inhibition of single SMT exposure on denitrification rates has an upper limit (Hou et al., 2014), as denitrifying bacteria may harbor sulfonamide resistance genes (Hou et al., 2014; Kotzerke et al., 2008). The inhibition effect of average SMT concentration (47.6 ng L1) and maximum SMT concentration (89.1 ng L1) on denitrification rates resembled each other (Table 2), as they both reached the upper limit. However, multiple antibiotics exposure may decrease the overall antibiotics resistance of the denitrifying bacteria community (Chait et al., 2007). The resistance to a single antibiotic may remove the suppression effect among the antibiotics, which could explain the greater inhibition effect of multiple antibiotics exposure (Ding and He, 2010). Synergistic effects of both OTC and ERY on aquatic microorganisms have been reported (Christensen et al., 2006), and the synergy and additivity among different antibiotics on denitrifying bacteria could be another reason of the greater inhibition effect. Range analysis showed that TAP had the greatest inhibition effect on denitrification rates among the 5 antibiotics. As the average and maximum concentrations of TAP detected in the study area were generally higher than the other antibiotics, the greatest inhibition effect may be caused by dosage effect (Basarab et al., 2015). On the contrary, the concentrations of OTC were much lower than TAP, but the inhibition effect was nearly at the same level (Rj ¼ 1.682 for TAP, Rj ¼ 1.677 for OTC). The distribution coefficient (Kd value) of OTC was much larger than that of TAP, which indicated that OTC was more likely to be combined with sediment (Chen et al., 2015; Xu et al., 2009). OTC and TAP both inhibit the protein synthesis and the related enzyme activities (Evaggelopoulou and Samanidou, 2013). The higher combination with sediment makes OTC more exposed to the denitrifying bacteria community, which may lead to a higher inhibition efficiency of OTC than TAP. Antibacterial properties of ERY can be suppressed by the presence of chloramphenicols (Chakraborty et al., 2014), thus ERY had the smallest inhibition effect on denitrification rates. However, the antagonism between ERY and TAP did not mitigate the total synergistic effect of multiple antibiotics exposure. The minimum concentration of ERY (0.05 ng L1) slightly stimulated the denitrification rates, which may be caused by the hormesis effect of ultra-low dose antibiotics exposure (Calabrese and Baldwin, 2003; Deng et al., 2012). Relationship of ultra-low dose stimulation and high-dose inhibition has been demonstrated to be highly generalizable for several classes of antibiotics (Deng et al., 2012). However, it is not easy to be observed under environmental concentrations of antibiotics, as the multiple exposure of antibiotics mostly leads to concentrations far beyond the ultra-low dose in estuarine and coastal regions (Chen and Zhou, 2014; Yan et al., 2013a). Stimulatory effect of sulfonamides on denitrification under ultra-low dose exposure has also been reported recently (DeVries et al., 2015). Combined effects of multiple antibiotics exposure lead to greater inhibition on denitrification rates, which may cause the retention of excessive reactive nitrogen, and further contribute to hyper-eutrophication in estuarine and coastal ecosystems. 4.2. Antibiotics influence on N2O release Fig. 4. Relationship between abundances of nosZ gene and concentrations of different antibiotics. min, ave, and max in the horizontal axis stand for minimum concentration detected, average concentration detected, and maximum concentration detected of each antibiotic, respectively. N2O release rates were significantly stimulated by SMT and inhibited by NOR, while no significant influence was observed for TAP, OTC, and ERY. Although different influence of antibiotics on N2O release rates was detected, the combination of multiple G. Yin et al. / Chemosphere 171 (2017) 118e125 antibiotics resulted in stimulatory effect in the orthogonal experiment trials. The stimulation of SMT was much greater than the inhibition of NOR, thus only in trials 2, 5, and 6 the N2O release rates were lower than the blank group (trial 1), where the concentrations of SMT were quite low. SMT single exposure has also been reported to stimulate N2O release rates, which can be explained by the different inhibition effect between N2O generation and N2O reduction to N2 (Hou et al., 2014). The stimulation was not affected by multiple antibiotics exposure, as SMT inhibits the synthesis of folic acid, which is a quite different antibacterial mechanism from other classes of antibiotics (Hou et al., 2014). NOR may also have different inhibition on N2O generation and N2O reduction to N2 procedures, but the effect is opposite to SMT. NOR inhibits DNA replication in microorganisms (Cheng et al., 2013), the disparate antibacterial mechanism may lead to a stronger inhibition on N2O generation than N2O reduction to N2, and eventually cause the inhibition on N2O release rates. Single exposure of TAP has been recently reported to stimulate N2O release rates (Yin et al., 2016), but no significant influence of TAP on N2O release rates was found in this study. TAP and ERY both inhibit the protein synthesis and the related enzyme activities of denitrifying bacteria (Evaggelopoulou and Samanidou, 2013). The antagonism between TAP and ERY may be the main factor causing no significant influence of both TAP and ERY on N2O release rates (Chakraborty et al., 2014). Though different classes of antibiotics have different influence on N2O release rates, the multiple antibiotics exposure mostly leads to stimulatory effect. Multiple antibiotics residues can be a fatal factor of increasing N2O release in estuarine and coastal ecosystems, which may contribute to ozone depletion and greenhouse effects in the atmosphere (Ravishankara et al., 2009; Reay et al., 2012). 4.3. Microbial mechanisms of antibiotics influence Nitrite reduction and N2O reduction to N2 are key steps involved in denitrification process (Pan et al., 2013), thus the abundances of nirS and nosZ genes were quantified to investigate the microbial mechanisms of multiple antibiotics exposure in this work. Compared to the blank group (trial 1), the abundances of nirS and nosZ genes were all inhibited by antibiotics treatments in the other orthogonal experiment trials, due to the antimicrobial properties of antibiotics (Conkle and White, 2012; Yan et al., 2013a). OTC had the greatest inhibition effect on nirS genes according to the range analysis, demonstrating that OTC has a higher inhibition efficiency on denitrification than other antibiotics used in this study. OTC has a higher tendency to combine with sediment (Chen et al., 2015; Xu et al., 2009), which may lead to a greater inhibition on nitrite reductase, and eventually cause a higher inhibition efficiency on denitrification rates. OTC also inhibited nosZ genes significantly, and the inhibition effect may resemble that on nirS genes, which may explain why OTC had no significant influence on N2O release rates. Range analysis showed that SMT had the greatest influence on nosZ genes, and inhibited the abundances of nosZ genes significantly. The greatest inhibition effect on nosZ genes may be the main factor leading to the N2O accumulation during the incubation, as the N2O reduction to N2 step was inhibited by SMT. Similar mechanism has been reported in single SMT exposure assays, where N2O release rates were also stimulated by SMT treatment (Hou et al., 2014). NOR inhibited nirS genes significantly, but had no significant influence on nosZ genes. That means that N2O generation was inhibited significantly by NOR, while no significant influence was observed on the N2O reduction to N2 step. Therefore, N2O release rates were significantly inhibited by NOR. NOR has also been reported to inhibit N2O generation in sewage treatment plant 123 (Costanzo et al., 2005). Antibacterial properties of ERY were suppressed by the presence of TAP (Chakraborty et al., 2014), thus ERY had no significant influence on both nirS genes and nosZ genes. Single TAP exposure has been reported to stimulate N2O release rates due to the different inhibition on denitrifying functional genes (Yin et al., 2016), but both TAP and ERY had no significant influence on N2O release rates in this study. The antagonistic effect between TAP and ERY may disturb their inhibition effects on nirS genes and nosZ genes, which could be the major mechanism causing no significant influence on N2O release rates. Multiple antibiotics exposure leads to various effects on denitrifying functional genes, and subsequently affects denitrification rates and N2O release rates dissimilarly. 5. Conclusions This work demonstrates that multiple antibiotics exposure is intimately related to denitrification rates and associated N2O release rates in estuarine and coastal sediments. Denitrification rates are inhibited by antibiotics treatments, and multiple antibiotics exposure leads to a synergistic inhibition effect. OTC has the highest inhibition efficiency on denitrification rates, and hormesis effect of ultra-low dose ERY exposure may be detected. N2O release rates are stimulated by SMT and inhibited by NOR, and multiple antibiotics exposure mostly leads to stimulatory effect. Antibiotics exposure inhibits the growth of denitrifying bacteria due to the antimicrobial properties, and different inhibition on denitrifying functional genes may be the major mechanism for the variations of N2O release rates. The interaction among different classes of antibiotics may create shifts of inhibition on denitrifying functional genes, and lead to different effects compared with single antibiotic exposure. The combined effects of antibiotics may cause reactive nitrogen retention and enhanced N2O release, thus contributing to environmental problems in estuarine and coastal regions. Acknowledgements This work was funded by National Natural Science Foundations of China (Nos. 41071135, 41130525, 41271114, 41322002 and 41501524), National key research and development program (2016YFA0600904), and China Postdoctoral Science Foundation (2015M571522). 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