And Copper (Cu) on Soil Enzyme Activities and Microbial Community Structure

environmental toxicology and pharmacology 34 (2012) 358–369

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The combined effect of decabromodiphenyl ether (BDE-209) and copper (Cu) on soil enzyme activities and microbial community structure

Wei Zhang a,b,∗, Meng Zhang a,b, Shuai An a,b, Kuangfei Lin a,b,∗, Hui Li a,b, Changzheng Cui a,b, Rongbing Fu c, Jiang Zhu c a State Environmental Protection Key Laboratory of Environmental Risk Assessment and Control on Chemical Process, Shanghai Key Laboratory of Functional Materials Chemistry, East China University of Science and Technology, Shanghai 200237, PR China b School of Resource and Environmental Engineering, East China University of Science and Technology, Shanghai 200237, PR China c Shanghai Academy of Environmental Sciences, Shanghai 200233, PR China article info abstract

Article history: Waste electrical and electronic equipment (e-waste) is now the fastest growing waste stream Received 13 August 2011 in the world. It is reported that polybrominated diphenyl ethers (PBDEs) and heavy metals Received in revised form were main contaminants in e-waste recycling site. Among these contaminants BDE-209 5 April 2012 and Cu were widespread, yet their combined effect on soil enzyme activities and microbial Accepted 23 May 2012 community structure are not well understood. In this study, the ecotoxicological effects of Available online 5 June 2012 both combined and single pollution of BDE-209 and Cu at different concentration levels were studied under laboratory conditions. The activities of soil catalase, urease and saccharase Keywords: were sensitive to BDE-209 and Cu pollution. Although the enzyme activities varied over BDE-209 time, the concentration effects were obvious. Statistical analyses revealed that, at the same Cu incubation time, as the concentration of BDE-209 or Cu increased, the enzyme activities Combined effect were decreased. Combined effects of both BDE-209 and Cu were different from that of BDE- Soil enzyme activity 209 or Cu alone. Enzyme activities data were essentially based on the multiple regression Microbial community structure technique. The results showed that the action and interaction between BDE-209 and Cu were Ecotoxicological effect strongly dependent on the exposure time, as the combined effects of BDE-209 and Cu were either synergistic or antagonistic at different incubation times. Soil catalase and saccharase were more comfortable used as indicators of BDE-209 and Cu combined pollution, as the variation trends were similar to the single contaminant treatments, and the responses were quick and signiﬁcant. Denaturing Gradient Gel Electrophoresis (DGGE) analysis of bacterial 16S rDNA gene showed that BDE-209 and Cu pollution altered the bacterial community structure by promoting changes in species composition and species richness. The existence of BDE-209 and Cu in soils reduced the microbial diversity, and the concentration effects were obvious. Overall, microbial diversity in the combined treatments were lower than the single

∗ Corresponding authors at: State Environmental Protection Key Laboratory of Environmental Risk Assessment and Control on Chemical Process, Shanghai Key Laboratory of Functional Materials Chemistry, East China University of Science and Technology, Shanghai 200237, PR China. Tel.: +86 21 64253244; fax: +86 21 64253988. E-mail addresses: [email protected] (W. Zhang), kﬂ[email protected] (K. Lin). 1382-6689/$ – see front matter © 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.etap.2012.05.009 environmental toxicology and pharmacology 34 (2012) 358–369 359

ones, and when the concentration of BDE-209 and Cu increased, and the Shannon–Weaver index decreased, which indicated the combined effect of BDE-209 and Cu on the microbial community structure was synergistic. Our results further the understanding of the toxic effects of BDE-209 and Cu on soil enzyme activities and microbial community structure, and suggest the need for more in-depth analysis to increase progressively the understanding of the toxicological mechanisms involved. © 2012 Elsevier B.V. All rights reserved.

provide only part of the knowledge necessary to evaluate the 1. Introduction toxic potential for wildlife and human. Also it is difficult to make clearly hazard assessments and predictions of possible With the rapid development of electric technology, waste elec- ecotoxicological effects. As everyone knows, POPs and heavy trical and electronic equipment, also known as e-waste, refers metal that accumulate in the environment and in food webs to end-of-life products including computer, cellular phone result in long-term threats to public health and ecosystem and television is rather striking. It has been estimated that stability (Ariese et al., 2001; Altındag˘ and Yigit,˘ 2005; Opopol, 20–50 million tonnes of e-waste are produced annually in 2007). the world and increases rapidly at a rate of 3–5% per year Soil microflora plays a major role in the decomposition (Robinson, 2009). Taking advantage of inexpensive cost of labor of organic matter and the mineralization of nitrogen, phos- and weak enforcement of environmental laws, much more phorus, and sulfur in the agro-ecosystem, they also play e-waste is being exported to developing countries. It was esti- significant roles in maintenance of soil structure, detoxifi- mated that 50–80% of the global e-waste was imported into cation of noxious chemicals, and the control of plant pests Asia, from which 90% ended up in China (Schmidt, 2002, 2006). and plant growth (Elsgaard et al., 2001; Filip, 2002). Since However, the recycling techniques in these countries are soil microorganisms can respond rapidly, they reflect a haz- often crude and do not have the appropriate facilities (Tang ardous environment and are, therefore, considered when et al., 2010a); waste processing operations such as uncon- monitoring soil status. A number of soil microbiological trolled dismantling, acid stripping and open burning in parameters, notably such as enzyme activities, microbial com- Chinese e-waste recycling sites (EWRSs) have resulted in munity structure, microbial biomass, have been suggested as severe environmental contamination (Wong et al., 2007a). The possible indicators of soil environmental quality, and have hazard of e-waste lies in the high content of many toxic sub- been employed in national and international monitoring pro- stances. As a result of the unprotected recycling techniques, grams (Dick, 1994; Yao et al., 2000; Kakkar and Jaffery, 2005). various high toxic pollutants such as persistent organic pol- Enzymatic activities are sensitive indicators of stress, and lutants (POPs) (e.g. PBDEs) and heavy metals (e.g. Cu), were a reduction in enzymatic activities would be the expected released into the environment (Wong et al., 2007a,b; Ni et al., response to an acutely toxic chemical. Catalase, urease and 2010). For instance, Guiyu, one of the largest EWRSs in South saccharase have been widely used as indicators of the pertur- China, the sum concentrations of PBDEs in combusted residue bation of soil by pollutants (Sahrawat, 1979; Lu et al., 2004; Qian and soil samples were 33,000–97,400 and 2020–4250 ng/g dw, et al., 2007). The activity of urease is known to be sensitive to respectively, and BDE-209 was the most dominant congener pollutants, such as heavy metals (Yang et al., 2006), pesticides (35–82%) among the study sites (Li et al., 2011). In soil near (Sahrawat, 1979), and antibiotics, and the catalase activity printer roller dumping area and plastic burn site, the concen- is often used to indicate the microbial anti-oxidation ability trations of Cu were 712 and 496 mg/kg dw, respectively (Leung (Caldwell, 2005), which is stimulated when slightly toxic com- et al., 2006). Luo and Shen reported that PBDEs concentration pounds are present, and inhibited when the toxicity increases in the farmland soils 2 km from an e-waste recycling work- (Shi et al., 2004). shop were 191–9156 ng/g dw and BDE-209 were ranged from BDE-209 was dominant PBDEs congener (Hale et al., 2003; 69.1 to 6319 ng/g with average of 1539 ng/g (Luo et al., 2009; Christensen et al., 2005; Voorspoels et al., 2007; Law et al., Shen et al., 2009). Tang and Zhang found that paddy soils near 2008). Because of the ubiquitous use of BDE-209 and their an e-waste recycling area were contaminated with Cu (mean lipophilic and inert characteristics, soil is very likely a sink concentration 176.2 or 256.4 mg/kg) (Zhang and Ming, 2009; for BDE-209 (Lacorte et al., 2003; Hassanin et al., 2004). It is Tang et al., 2010b). All these have led to high pollution level reported that BDE-209 can reach toxic concentrations that are in the ambient environment, and further threaten the ecosys- detrimental to the environment as well as to human health tem local and inhabitants’ health (Deng et al., 2006; Yu et al., (Covaci et al., 2008; Harrad and Porter, 2007). Some study has 2006). demonstrated that BDE-209 in soil, although of low bioavail- Some studies have been focused on the environment pol- ability, had an adverse impact on the microbial structure and lution caused by e-wastes in China since the last decade. The function (Zhu et al., 2010; Liu et al., 2011). Furthermore, heavy accumulation of PBDEs and heavy metals in soil has been metal pollution can not only result in adverse effects on var- reported in some sites of e-waste recycling locations (Cai and ious parameters relating to plant quality and yield but also Jiang, 2006; Yu et al., 2006; Hu et al., 2009). However, since these cause changes in the composition and activity of microbial data do not take into account the possible combined effects of community (Giller et al., 1998). Copper is classified as one different contaminants, as well as their bioavailability, they of the most hazardous heavy metals, although it poses risk 360 environmental toxicology and pharmacology 34 (2012) 358–369

only when its quantities exceed natural background. It is so a spectrophotometer under the 578 nm wavelength (May and because Cu is also a micronutrient, without which no living Douglas, 1976). organism could function. On the other hand, its excess in Catalase activity was expressed as the volume of KMnO4 natural environment may cause malfunctions of ecosystem necessary for titration. 5 g of soil was put into a 150 mL Erlen- (Wyszkowska et al., 2009). meyer ﬂask, then 40 mL of distilled water and 5 mL of 0.3%

In the real EWRSs, these pollutants were usually existed H2O2 were added into the flask. The flask was sealed and together. However, as far as we know, almost no study noted shaken, and then gently placed in a water bath at 37 ◦C for the combined effect of PBDEs and heavy metal on soil enzyme 30 min. Next, 5 mL of 3 mol/L H2SO4 was added to terminate and microbial diversity, so in this study, we employed DGGE the reaction. The amount of surplus H2O2 from the 25 mL of as well as enzymatic activity assays to determine the changes the filtrate was determined by titration with 0.02 mol/L KMnO4 of microbial activities in soils, and examined the combined (Roberge, 1978). and single exposure effects of BDE-209 and Cu contaminants, Saccharase assessment was performed utilizing the to allow direct comparison. This work will assist in providing method described by Guan. 5 g of soil was put into a 50 mL theoretical arguments on soil quality evaluation and bioreme- Erlenmeyer flask, then 15 mL of 8% sucrose solution, 5 mL of diation in the EWRSs. pH 5.5 phosphate buffer and 5 drops of toluene were added into the flask, the flask was sealed and shaken, and then placed in a constant temperature incubators at 37 ◦C for 24 h. 2. Materials and methods After the incubation, 1 mL filter liquor was put into a 50 mL volumetric flask, then 3 mL of 3,5-dinitrosalicylic acid was added, 2.1. Chemicals placed the volumetric flask in a water bath at 100 ◦C for 5 min, cooled down under running water for 3 min, Finally diluted BDE-209 (purity >98.0%) was obtained from J&K Scientific Ltd, with distilled water to 50 mL, detected in a spectrophotometer Shanghai, China. Cupric Chloride (CuCl2), Dimethyl sulfoxide under the 508 nm wavelength (Guan, 1986). (DMSO) and other reagents were analytical grade and provided by Shanghai Zhanyun Chemical Co., Ltd., Shanghai, China.

2.4. DNA extraction and PCR-DGGE 2.2. Incubation experiment design

At 0, 7, 15, 30, 60 and 90 days, the total genomic DNA of the The soil used in this research (Silty clay loam, 6.5% organic soil was extracted from each soil sample (1.0 g dry equivalent matter, pH 7.3) was collected from East China University of Sci- weight), as previously described (Zhou et al., 1996). A 16S rDNA ence and Technology in Shanghai, China. An aggregate sample gene fragment was amplified by PCR, using the bacterium- was generated by collecting soil from five separate locations specific primers 968 F-GC and 1401R (Nübel et al., 1996). The across the field. At the laboratory, the soil was fully mixed, reaction volume was 50 ␮l, containing 5 ␮lof10× PCR buffer, pebbles and large plant residues were removed. Copper stock 5 ␮l of dNTPs, 1 ␮l of each primer, 1 ␮l of Taq polymerase, and solution was prepared by dissolving CuCl2 in deionized water, 1 ␮l of template DNA. Amplification was performed using an and BDE-209 stock solution was prepared by dissolving the initial denaturation at 95 ◦C for 5 min, followed by 30 cycles BDE-209 powder in dimethyl sulfoxide. Packing the soil in sev- of 1 min, 45 s, 1 min each at 95, 56, and 72 ◦C, with a final eral 10 mL tissue culture flasks, 5 g each flask, then treating the extension of 10 min at 72 ◦C. The DGGE method was modi- soil samples with the BDE-209 and Copper stock solution. The fied with the technique introduced by Cremonesi et al. (1997). concentration levels of different treatments (low dose: 1 mg/kg PCR products for each sample (30 ␮l) were loaded into a 6% BDE-209 or 200 mg/kg Cu; moderate dose: 10 mg/kg BDE-209 or denaturing gradient polyacrylamide linear porosity gradient 400 mg/kg Cu; high dose: 100 mg/kg BDE-209 or 800 mg/kg Cu) gel (acrylamide:bisacrylamide, 37.5:1 ratio) with a denaturing were indicated in Table 1. gradient ranging from 45% to 75% (where the 100% denaturant Each treatment was replicated three times. The control contains 7 mol/L urea and 40% formamide). Electrophoresis without any artificial contaminant received the same amounts was performed with a Dcode system (Bio-Rad).The gel was run of distilled water. All treatments were incubated at room tem- at 150 V for 6 h at 60 ◦Cin1× TAE running buffer. The gel was perature, and kept in complete darkness. Soil samples were stained with GelRed (1:10,000 dilution) for 45 min, rinsed with collected for further analysis at 0, 7, 15, 30, 60, and 90 days 1× TAE running buffer and visualized under UV in a Gel Doc after exposure treatment. 2000 (Bio-Rad). DGGE bands were excised and eluted in 50 ␮l TE buffer 2.3. Enzymatic activities assay overnight at 4 ◦C. A total of 5 ␮l of the eluent was used for reamplification with primers 968F and 1401R. DNA sequence Urease activity was expressed as mg NH4+-N produced kg−1 analysis was performed by Shanghai Sangon Biological Engi- dry soil 24 h−1. 5 g of soil was incubation with 5 mL 10% urea neering Technology & Services Co., Ltd, China. Close relatives and 10 mL citrate buffer at 37 ◦C for 24 h, then diluted with and phylogenetic affiliation of the obtained sequences were 38 ◦C distilled water to 50 mL. 1 mL filter liquor was put into determined using the BLASTN search program at the NCBI a 50 ml volumetric flask, then diluted with distilled water to web site. Multiple alignment and calculation of the distance 10 mL, 4 mL of sodium phenate and 3 mL Sodium Hypochlo- matrix were conducted using Clustal, and a phylogenetic tree rite was added, the flask was sealed and shaken, detected in was constructed using MEGA 5.0. environmental toxicology and pharmacology 34 (2012) 358–369 361

Table 1 – BDE-209 and Cu concentration levels in different treatment groups. Contaminant Concentration (mg/kg dw)

CK S1 S2 S3 S4 S5 S6

BDE-209 0 1 10 100 0 0 0

CuCl2 0 0 0 0 200 400 800

Contaminant Concentration (mg/kg dw)

S7 S8 S9 S10 S11 S12 S13 S14 S15

BDE-209 1 10 100 1 10 100 1 10 100

CuCl2 200 200 200 400 400 400 800 800 800

2.5. Statistical analysis Data in Fig. 2 show the combined effect of BDE-209 and Cu on soil catalase, urease and saccharase activity during 90 days All experimental data, means of three repeats, were processed incubation time. by OriginPro8.0. The linear regression and the stepwise linear In the combined pollution experiment, the catalase activ- regression were conducted by using the statistical software ities in all treatments gradually decreased from 0 to 30 days package of SPSS (Ver.16.0). Multiple comparisons were statis- (Fig. 2A), and touched the bottom at the 30th day, then tically evaluated by the ANOVA and Tukey’s test. The least increased in the remaining experimental time, which revealed significant differences (LSD) among mean values were calcu- a same trend as the single BDE-209 or Cu treatments (Fig. 1A). lated at P < 0.05 confidence level. However, compared to the single Cu treatments, the catalase activity of low and moderate dose BDE-209 combined treatment groups (S7, S8, S10, S11, S13, S14) increased significant 3. Results (P < 0.05 or P < 0.01) at the 90th day. The response of urease activity was irregular, as it was 3.1. Effect of BDE-209 or Cu on soil enzyme activities either stimulated or inhibited in all combined treatments (Fig. 2B). However, compared to the single Cu treatments, the Data in Fig. 1 show the catalase, urease and saccharase activi- urease activity of low and moderate dose Cu combined treat- ties for the soils incubated with BDE-209 or Cu for 90 days. On ments (S7–S12) decreased extremely significant (P < 0.01) at the whole, the enzyme activities were inhibited by BDE-209 or the first 30 days. Then, the urease activity of all treatments Cu at different levels, and the response varied over time. was increased at 60th day, and in some treatments (all treat- The inhibited effect of BDE-209 or Cu on catalase (Fig. 1A) ments except S7, S9, S10) the stimulated effects were highly touched the bottom at 30th day (the inhibition rate was rang- significant (P < 0.01). ing from 19% to 29.8% or 21.9% to 40.3%, respectively), and then The saccharase activities of the combined treatments showed a large increase from the 60th day to the 90th day (but touched the bottom at the 15th day, and showed a large still significant lower (P < 0.05 or P < 0.01) than the controls). increased at the 30th day, then gradually reduced in the At the first 15 days, BDE-209 were highly significant inhibited remaining experimental time (Fig. 2C). The variation trend was the activities of urease and saccharase (P < 0.01) (Fig. 1B and similar to the single BDE-209 treatments. However, the saccha- C), but increased suddenly at the 30th day and then gradually rase activities of low and moderate dose BDE-209 combined reduced. The activities of urease and saccharase were inhib- treatments increased extremely significant from 30 to 90 days ited by Cu through the whole experiment, as the concentration compared to Cu treatments (P < 0.01). increased, and the activities of urease and saccharase were Generally, to account for combined effect of different going down, and touched the bottom and exhibited highly sig- important independent variables, second-order polynomial nificant difference (P < 0.01) compared to the controls at 90th models are preferred (Poorna and Kulkarni, 1995; Shen et al., day (the inhibition rate was ranging from 39.6% to 49.2% and 2005, 2006). Therefore, it was thought of interest to develop a 30.5% to 42.2%, respectively). second-order polynomial model describing the effect of two selected independent variables, namely, the concentration of 3.2. Combined effect of BDE-209 and Cu on soil BDE-209 and Cu on soil catalase, urease and saccharase activ- enzyme activities ity. The model was expressed as:

The combined effects of mixtures composed of chemicals with m diverse concentrations are not the simple sums of the individ- Y = ˇ0 + ˇiXi + ˇijXiXj + ε ual effects of the mixture components. If only one chemical of i=1 i

Fig. 1 – Catalase, urease and saccharase activities of soil samples after single exposure to different concentrations of BDE-209 or Cu. Each point is the mean of three replicates. Error bars indicate the standard deviation. Pound (#) and asterisk (*) indicate signiﬁcance at the P < 0.05 and P < 0.01 level compared to the controls (LSD test).

ˇ value of ij is positive, the interactive effect is synergistic, and effect was antagonistic (Table 2). This phenomenon can be a negative value represents antagonistic, while zero stands for also clearly observed, and the data in all combined treatments additive toxicity. decreased or significant decreased at 7th and 30th day com- In order to analyze the combined effect between BDE-209 pared to the single Cu treatments (Fig. 2A). and Cu on enzyme activities, second-order polynomial models For urease, at the first 15 days the combined effect of BDE- were established with the multiple regression technique, as 209 and Cu was synergistic, but in the other days of incubation shown in Table 2. time, the interactive effect was antagonistic (Table 2). The ure- The regression coefficient of BDE-209 and Cu on catalase ase activity of the combined treatments were touched the − − activity was 2.628 × 10 7 and 3.159 × 10 6 at the 7th and 30th bottom at 15th day, and then increased, but the urease activity day, so the combined effect of BDE-209 and Cu was synergis- still lower or significant lower than the single Cu treatments tic, but in the other days of incubation time, the interactive as shown in Fig. 2B. environmental toxicology and pharmacology 34 (2012) 358–369 363

6.0 A 0d 7d 5.5 15d 5.0 30d 60d 4.5 ∗ # 90d

) ∗ ∗ # # # 4.0 # ∗ ∗ ∗ 3.5 ∗ ∗ ∗ #

/ g soil / g ∗ ∗ 4 3.0 ∗ ∗ ∗ ∗ ∗ ∗ 2.5 ∗ ∗ ∗ ∗ ∗ 2.0 ∗ ∗

Activity of catalase 1.5 mL KMnO ( 1.0 0.5 0.0 S4 S7 S8 S9 S5 S10 S11 S12 S6 S13 S14 S15 Soil Samples B 0d 1.6 7d 15d 1.4 30d

) 60d 90d 1.2 ∗

soil ∗ ∗ ∗ ∗ ∗ ∗ ∗ ∗ ∗ ∗ ∗ ∗ 1.0 ∗ ∗ ∗ -N / g ∗ ∗ ∗ ∗ 4 ∗ ∗ ∗ ∗ ∗ ∗ ∗ ∗ ∗ ∗ ∗ 0.8 ∗ ∗ ∗ ∗ 0.6 ∗ Activity of urease mg NH ( 0.4

0.2

0.0 S4 S7 S8 S9 S5 S10 S11 S12 S6 S13 S14 S15 Soil Samples

0d C 120 7d 15d 110 30d 100 ∗ ∗ 60d 90d ) ∗ 90 ∗ ∗ ∗ ∗ ∗ ∗ ∗ 80 ∗ # ∗ ∗ ∗ ∗ ∗ ∗ ∗ ∗ # ∗∗ 70 ∗ ∗ ∗ ∗ ∗ ∗ 60 ∗ ∗ ∗ 50 ∗ ∗ ∗ ∗ ∗ 40 ∗ mg Glucose / g soil mg Glucose / g (

Activity of saccharase 30 20 10 0 S4 S7 S8 S9 S5 S10 S11 S12 S6 S13 S14 S15 Soil Samples

Fig. 2 – Catalase, urease and saccharase activities of soil samples after exposure to different concentrations of BDE-209 and Cu combined pollution. Each point is the mean of three replicates. Error bars indicate the standard deviation. Pound (#) and asterisk (*) indicate signiﬁcance at the P < 0.05 and P < 0.01 level compared to different Cu treatments (S4, S5, S6) (LSD test).

The stepwise regression analysis indicated that the con- 3.3. DGGE and phylogenetic analysis centration of BDE-209 and Cu were negatively correlated with saccharase activity, and Cu in this study was signiﬁcantly The DGGE patterns were similar for all the soil samples except more inhibitory to saccharase than BDE-209. Furthermore, the for changes in the densities of some bands. Some bands were inhibiting effect of BDE-209 can be augmented signiﬁcantly by shared in different samples, such as bands 1, 2, 5, 11, 12. While the addition of Cu (Fig. 2C). The combined effect of BDE-209 some bands, such as band 13, appeared in the 90 days samples and Cu on saccharase activity was synergistic (Table 2). of the combined treatment groups. In the present study, the 364 environmental toxicology and pharmacology 34 (2012) 358–369

Table 2 – Relationship between soil enzyme activity (Y) and concentration of BDE-209 and Cu (X). Soil enzyme Time (days) Multiple regression model R2 Sig.

−7 Catalase 7 Y = 4.387 + 2.628 × 10 XBDE-209 XCu 0.703 <0.05 −6 15 Y = 3.577 + 0.005 XBDE-209 − 0.001 XCu − 8.891 × 10 XBDE-209 XCu 0.759 <0.05 −6 30 Y = 2.291 − 0.005 XCu + 3.159 × 10 XBDE-209 XCu 0.612 <0.05 −6 60 Y = 3.758 − 0.003 XCu − 4.092 × 10 XBDE-209 XCu 0.738 <0.05 −5 90 Y = 3.836 + 0.003 XBDE-209 − 1.24 × 10 XBDE-209 XCu 0.855 <0.05 −6 Urease 7 Y = 1.152 − 0.001 XBDE-209 + 5.174 × 10 XBDE-209 XCu 0.664 <0.05 −7 15 Y = 1.050 − 0.001 XBDE-209 + 3.159 × 10 XBDE-209 XCu 0.976 <0.05 −7 30 Y = 0.926 − 2.013 × 10 XBDE-209 XCu 0.895 <0.05 −5 −7 60 Y = 0.916 − 5.438 × 10 XCu − 8.04 × 10 XBDE-209 XCu 0.608 <0.05 −6 90 Y = 0.828 − 2.202 × 10 XBDE-209 XCu 0.862 <0.05 Saccharase 7 Y = 94.414 − 0.417 XBDE-209 − 0.044XCu 0.854 <0.05 −5 15 Y = 74.114 − 0.252 XBDE-209 − 0.026 XCu + 9.933 × 10 XBDE-209 XCu 0.683 <0.05 −5 30 Y = 92.826 − 0.104 XBDE-209 − 0.027 XCu + 9.630 × 10 XBDE-209 XCu 0.698 <0.05 −6 60 Y = 87.068 − 0.07 XBDE-209 − 0.024 XCu + 7.023 × 10 XBDE-209 XCu 0.851 <0.05 90 Y = 87.803 − 0.128 XBDE-209 − 0.03 XCu 0.903 <0.05 disappearance of normal bands and the appearance of extra synergistic. In addition, PCR-DGGE analysis indicated that sin- bands occurred in treated soil, and the mechanism needs to gle or combined addition of BDE-209 and Cu, although of be further investigated. low concentration, yet could obviously affect the diversity A total of 13 bands were excised and sequenced. Nearest of microbial community. Langford et al. (2007) found that neighbor strains by BLAST search are shown in Table 3.A PBDE congeners displayed effects on the bacterial community phylogenetic tree based on analysis of 16S rDNA sequences and decreased population diversity within one-sludge age of obtained is shown in Fig. 3. All bands contained DNA exposure. Smit et al. (1997) also found distinct differences in sequences 92–100% identical to their closest relative in microbial community structure, with a lower diversity in soil GenBank. This result seems to support the presence of a contaminated by copper compared with that of a non-polluted considerable number of uncultured, and potentially not previ- soil. ously described, bacterial taxa in the soil ecosystem polluted by BDE-209 and Cu (single or combined pollution). The analysis of DNA sequences showed that Comamonas species were the most common species found in all treat- 4. Discussion ment groups. DGGE bands 2, 5 and 10 had close relationship with Comamonas sp., whereas band 13 showed the highest Many authors stressed the inhibition of urease caused by cop- nucleotide similarity to Zoogloea sp. Band 8 was identiﬁed as per: if the concentration of Cu was high, the inhibition rate iron-reducing bacterium, and the sequence homology was 96% could exceed 50% and last for a long time (Tabatabai, 1977; (Table 3). Uncultured bacterial strains were also detected. For Frankenberger et al., 1983; Marzadori et al., 2000). BDE-209 example, bands 7 and 9 showed a nucleotide similarity to could suppress the urease activity at the concentration of uncultured gamma proteobacterium and Rhodocyclales bacterium, 1 mg/kg (Zhu et al., 2010). Our results showed that, low concen- respectively, with sequence homologies from 97% to 98%. tration BDE-209 (1 mg/kg) or Cu (200 mg/kg) could extremely Shannon–Weaver diversity index (H) is commonly used signiﬁcant (P < 0.01) inhibited the activities of soil catalase, to measure biodiversity (Shannon and Weaver, 1949). In the urease and saccharase. Although soil enzyme activities varied present study, Shannon–Weaver diversity index was used to over time, the concentration effects were obvious. Statistical estimate bacterial diversity in both single and combined pol- analyses revealed that, at the same incubation time, when the lution soils using the following equation (Zak et al., 1994): concentration of BDE-209 or Cu increased, the enzyme activities decreased, and this trend was clearly displayed in Fig. 1. S The combined effects of BDE-209 and Cu on these enzyme H =− pi ln pi activities were either synergistic or antagonistic at different i=1 incubation times, and the action and interaction between Cu

Here pi is the ratio between speciﬁc band intensity and total and BDE-209 were strongly dependent on the exposure time. intensity of all bands in a lane sample, and S is the total num- And in some cases the activities of soil catalase recovered with ber of bands in each sample lane. A higher Shannon–Weaver time, which might be due to the variation of microbial bio- index indicates a more diversiﬁed bacteria community. coenosis (Zhou, 1987), and future studies should be carried As displayed in Table 4, the Shannon–Weaver index indi- out to expound this phenomenon. In conclusion, the activity cated that the existence of BDE-209 and Cu (especially with of soil catalase, urease and saccharase were sensitive to BDE- high concentration) in soils reduced microbial diversity com- 209 and Cu pollution (single or combined exposure). According pared to the controls, although the population diversity to the data showed in Fig. 2, we hypothesize that soil catalase increased with the incubation time in all microcosms. Over- and saccharase were more comfortable used as the indicators all, microbial diversity in the combined treatment groups of BDE-209 and Cu combined pollution, as the variation trends were lower than the single ones, and the combined effect were similar to the single treatments, and the responses were of BDE-209 and Cu on microbial community structure was quick and sensitive. environmental toxicology and pharmacology 34 (2012) 358–369 365

Table 3 – Comparison of genomic sequences in dominant DGGE bands by sequencing and BLAST analysis. DGGE band name Closest relative and alignment Similarity

Band 1 Comamonas testosteroni strain CW (JF411016) 98% Uncultured beta proteobacterium FTL2 (AF529091) 98% Comamonas sp. A7-5 (GQ49722) 98% Band 2 Bacterium enrichment culture clone G11 (HQ602836) 96% Comamonas sp. CNB 8 (JF775508) 96% Comamonas sp. NEHU.BSSRJ.7 (HM448985) 96% Band 3 Uncultured bacterium clone hfmB109 (AB600423) 96% Uncultured bacterium clone ZSB-B9-6 (GU205553) 96% Uncultured bacterium clone ZSB-F9 (GU205689) 96% Band 4 Bacillus sp. IITRSU2 (FJ581022) 92% Uncultured bacterium clone SMA41 (AM182998) 92% Band 5 Comamonas sp. T108 (FJ719342) 94% Uncultured Comamonas sp. clone 1P-1-O24 (EU704937) 94% Band 6 Uncultured bacterium clone oze05B45 (AB504954) 96% Uncultured bacterium clone oze05B47 (AB504955) 96% Band 7 Uncultured bacterium clone D13S-16 (EU617749) 96% Uncultured gamma proteobacterium clone Nubeena232 (AY499955) 97% Uncultured bacterium clone TSBW31 (AB186841) 97% Band 8 Uncultured compost bacterium clone FS2142 (FN667226) 96% Iron-reducing bacterium enrichment culture clone HN-HFO91 (FJ269102) 96% Band 9 Uncultured bacterium copi43 (AY563461) 100% Uncultured Rhodocyclaceae bacterium clone (JF736624) 98% Uncultured Rhodocyclales bacterium MFC63H01 (FJ823938) 98% Band 10 Comamonas sp. MQ (HQ176414) 98% Band 11 Uncultured bacterium clone oze05B57 (AB504956) 98% Band 12 Uncultured bacterium clone P3-B61 (FR852989) 96% Uncultured bacterium clone B2-9 (JF922446) 96% Band 13 Zoogloea sp. A5 (DQ342276) 94% Zoogloea resiniphila strain PIV-3C2y (AJ505854) 94% Zoogloea resiniphila strain PIV-3C2w (AJ505853) 94%

The effects of organic pollutants on bacterial community to heavy metal stresses than other organisms in soil ecosys- structure in natural communities are complex. This complex- tem (Giller et al., 1998). It is known, however, that Cu does ity is reﬂected by the diverse physical, chemical, and biological have bactericidal properties, which could explain the eventual factors (Battin et al., 2008). First of all, the activity and com- decreases in bacterial diversity at the greater Cu application position of soil bacterial community are closely related to rates (Borkow and Gabbay, 2004). Second, POPs entering the soil fertility and environmental quality. It has been demon- soil may affect bacterial communities not only by reducing strated that the toxicity of heavy metals is an important factor the diversity, but they may also change the composition of affecting the composition of soil microbial community (Wang the bacterial community, for instance, enhancing certain POP- et al., 2006), and microorganisms are generally more sensitive consuming cohorts (Gao et al., 2006).

Table 4 – Shannon–Weaver diversity index for the bacterial community. Time (days) Soil samples

CK S1 S2 S3 S4 S5 S6

0 1.25 1.25 1.25 1.25 1.25 1.25 1.25 7 1.37 1.35 1.34 1.32 1.33 1.30 1.32 15 1.48 1.42 1.40 1.37 1.39 1.39 1.37 30 1.58 1.54 1.56 1.47 1.52 1.49 1.47 60 1.66 1.64 1.63 1.52 1.65 1.59 1.58 90 1.81 1.76 1.74 1.56 1.73 1.70 1.64

Time (days) Soil samples

S7 S8 S9 S10 S11 S12 S13 S14 S15

0 1.25 1.25 1.25 1.25 1.25 1.25 1.25 1.25 1.25 7 1.30 1.28 1.29 1.31 1.29 1.28 1.23 1.28 1.26 15 1.36 1.35 1.37 1.35 1.41 1.33 1.30 1.34 1.32 30 1.47 1.45 1.44 1.43 1.47 1.39 1.41 1.43 1.40 60 1.58 1.59 1.56 1.55 1.51 1.52 1.50 1.50 1.48 90 1.72 1.69 1.67 1.72 1.66 1.64 1.61 1.59 1.58 366 environmental toxicology and pharmacology 34 (2012) 358–369

Comamonas sp. CNB 8(JF775508) Uncultured bacterium clone B2-9(JF922446) Comamonas testosteroni strain CW(JF411016) Bacterium enrichment culture clone G11(HQ602836) Comamonas sp. NEHU.BSSRJ.7(HM448985) Comamonas sp. A7-5(GQ497242) 20 Comamonas sp. T108(FJ719342) Uncultured beta proteobacterium clone FTL2(AF529091) Uncultured bacterium clone P3-B61(FR852989) Uncultured Comamonas sp. clone 1P-1-O24(EU704937) 53 2 5 1 84 12 Bacillus sp. IITRSU2(FJ581022) 100 Comamonas sp. MQ(HQ176414) 10

60 Uncultured bacterium clone SMA41(AM182998) 4 9

100 62 Uncultured Rhodocyclales bacterium clone MFC63H01(FJ823938)

99 Uncultured Rhodocyclaceae bacterium clone GS25(JF736624) Uncultured bacterium clone copi43(AY563461) Zoogloea resiniphila strain PIV-3C2w(AJ505853) 49 Zoogloea resiniphila strain PIV-3C2y(AJ505854) 100 13 68 Zoogloea sp. A5(DQ342276) Uncultured bacterium clone TSBW31(AB186841) Uncultured bacterium clone D13S-16(EU617749) 87 Uncultured gamma proteobacterium clone Nubeena232(AY499955) 43 7 11

67 Uncultured bacterium clone ZSB-B9-6(GU205553) 3 52 Uncultured bacterium clone ZSB-F9(GU205689)

98 Uncultured bacterium clone hfmB109(AB600423)

50 Uncultured bacterium clone oze05B45(AB504954)

100 Uncultured bacterium clone oze05B47(AB504955) Uncultured bacterium clone oze05B57(AB504956) Uncultured compost bacterium clone FS2142(FN667226) 8 100 Iron-reducing bacterium enrichment culture clone HN-HFO91(FJ269102)

0.12 0.10 0.08 0.06 0.04 0.02 0.00

Fig. 3 – Neighbor-joining tree showing the relationships between the partial 16S rDNA sequences retrieved from the DGGE bands.

DGGE is a rapid and culture-independent technique that sequence homology was 94%), which was founded at the ben- can be used to assess the composition of a microbial commu- zene and chlorate contaminated sites, was thought to have a nity. This technique has previously been utilized to identify close relationship with the degradation of benzene (Weelink and quantify microorganism species (Zhang et al., 2010; Zhu et al., 2007). We concluded that these bacteria were highly tol- et al., 2010). In this study, DGGE was used to examine the erant to BDE-209 and Cu pollution, and it is potentially the combined effect of BDE-209 and Cu on the distribution of reason why they existed in most soil samples in our investi- microorganism community in soil. The DGGE patterns were gation. similar for all the soil samples except for changes in the One of the advantages of Shannon–Weaver diversity index densities of some bands, while some bands were shared in dif- is that it takes into account the number of species and ferent samples. Comamonas, one of the main bands detected by the evenness of the given community. Our results indicated DGGE, is reported to utilized p-chloronitrobenzene, nitroben- that the existence of BDE-209 and Cu (especially with high zene, catechol, and protocatechuate as sole sources of carbon concentration) in soils reduced microbial diversity. Further- and energy (Wu et al., 2005). In addition, band 13 only appeared more, when the concentration of BDE-209 and Cu increased, in the combined treatments at 90th day. Zoogloea sp. A5 (the Shannon–Weaver index decreased, which showed that the environmental toxicology and pharmacology 34 (2012) 358–369 367

concentration effects were obvious. Microbial diversity in the Battin, T.J., Kaplan, L.A., Findlay, S., Hopkinson, C.S., Marti, E., combined treatments was lower than the single ones, so we Packman, A.I., Newbold, J.D., Sabater, F., 2008. Biophysical can hypothesize that the combined effect of BDE-209 and Cu controls on organic carbon fluxes in fluvial networks. Nat. Geosci. 1, 95–100. on microbial community structure was synergistic. Borkow, G., Gabbay, J., 2004. Putting copper into action, copper-impregnated products with potent biocidal activities. 5. Conclusions FASEB J. 18, 1728–1730. Cai, Z.W., Jiang, G.B., 2006. Determination of polybrominated diphenyl ethers in soil from e-waste recycling site. Talanta 70, In this study, we employed DGGE as well as enzymatic activity 88–90. assays to determine the changes of microbial activities in soils, Caldwell, B., 2005. Enzyme activities as a component of soil and examined the single and combined effects of BDE-209 and biodiversity, a review. Pedobiologia 49, Cu exposure, to allow direct comparison. 637–644. Soil microbial activity and community composition are Christensen, J.R., MacDuffee, M., MacDonald, R.W., Whiticar, M., Ross, P.S., 2005. Persistent organic pollutants in British difficult to elucidate, and no single approach provides a com- Columbia grizzly bears, consequences of divergent diets. plete depiction of the soil microbial situation. However, by Environ. Sci. Technol. 39, 6952–6960. combining different monitoring approaches, insights into the Covaci, A., Voorspoels, S., Roosens, L., Jacobs, W., Blust, R., Neels, microbial environment are possible. We can draw the follow- H., 2008. Polybrominated diphenyl ethers (PBDEs) and ing conclusions from our own work: First, the combined effects polychlorinated biphenyls (PCBs) in human liver and adipose of BDE-209 and Cu on soil catalase, urease and saccharase tissue samples from Belgium. Chemosphere 73, activities revealed a set of action and interaction between two 170–175. Cremonesi, L., Firpo, S., Ferrari, M., Righetti, P.G., Gelfi, C., 1997. pollutants, and these soil enzyme activities were sensitive Double-gradient DGGE for optimized detection of DNA point to BDE-209 and Cu (single and combined exposure). Second, mutations. Biotechniques 22, 326–330. short-term exposure to BDE-209 and Cu can obviously change Deng, W.J., Louie, P.K.K., Liu, W.K., Bi, X.H., Fu, J.M., Wong, M.H., the microbial community. The microbial diversity reduced 2006. Atmospheric levels and cytotoxicity of PAHs and heavy gradually, although the population diversity increased with metals in TSP and PM2.5 at an electronic waste recycling site the incubation time in all microcosms. The combined effect in southeast China. Atmos. Environ. 40, 6945–6955. of BDE-209 and Cu on the microbial community structure was Dick, R.P., 1994. Soil enzyme activities as indicators of soil quality. Soil Sci. Soc. Am., 107–124. synergistic, and Shannon–Weaver index of combined treat- Elsgaard, L., Petersen, S.O., Debosz, K., 2001. Effects and risk ment groups were lower than the single exposure. assessment of linear alkylbenzene sulfonates in agricultural The present results suggest that PCR-DGGE analysis in con- soil. 1. Short-term effects on soil microbiology. Environ. junction with other indicators such as soil enzyme parameter Toxicol. Chem. 20, 1656–1663. etc. would be proved a powerful ecotoxicological tool. Fur- Filip, Z., 2002. International approach to assessing soil quality by thermore, more experiments should be performed to better ecologically-related biological parameters. Agric. Ecosyst. Environ. 88, 169–174. understand the relationship of different biomarkers. Frankenberger, J.R., Johanson, J.B., Nelson, C.O., 1983. Urease activity in sewage sludge-amended soils. Soil Biol. Biochem. Conflict of interest 15, 543–549. Gao, Y., Yu, X.Z., Wu, S.C., Cheung, K.C., Tam, N.F.Y., Qian, P.Y., Wong, M.H., 2006. Interactions of rice (Oryza sativa L.) and The authors declare that there is no conflict of interest. PAH-degrading bacteria (Acinetobacter sp.) on enhanced dissipation of spiked phenanthrene and pyrene in waterlogged soil. Sci. Total Environ. 372, 1–11. Acknowledgements Giller, K.E., Witte, E., McGrath, S.P., 1998. Toxicity of heavy metals to micro-organisms and microbial processes in agricultural This research was financially supported by the National soils, a review. Soil Biol. Biochem. 30, 1389–1414. 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