Impacts of different nanoparticles on functional ...

Chemosphere 104 (2014) 141–148

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Impacts of different nanoparticles on functional bacterial community in activated sludge q Jian Chen a, Yue-Qin Tang b, Yan Li a, Yong Nie a, Linlin Hou c, Xi-Qing Li c,1, Xiao-Lei Wu a,⇑ a

College of Engineering, Peking University, Beijing 100871, PR China College of Architecture and Environment, Sichuan University, Chengdu 610065, PR China c Laboratory of Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, PR China b

h i g h l i g h t s Silver and ZnO nanoparticles exert different impacts on functional bacterial community. Denitrifying bacteria were inhibited by high dosage of silver and ZnO nanoparticles. Sludge bulking, heavy metal resistant and biosorption bacteria enriched by both nanoparticles. Increase of bulking related bacteria may help to maintain functional redundancy of the community.

a r t i c l e

i n f o

Article history: Received 7 August 2013 Received in revised form 22 October 2013 Accepted 30 October 2013 Available online 23 November 2013 Keywords: Nanoparticles Activated sludge qPCR T-RFLP Functional bacterial community Functional redundancy

a b s t r a c t Rapidly developing industry raises concerns about the environmental impacts of nanoparticles, but the effects of inorganic nanoparticles on functional bacterial community in wastewater treatment remain unclear. The discriminated effects of silver nanoparticles (Ag-NP) and zinc oxide nanoparticles (ZnO-NP) in a simulated sequencing batch reactor (SBR) system were therefore evaluated by the RNA-based terminal restricted fragment length polymorphism (T-RFLP), 16S rcDNA gene clone library and real-time reverse transcription-PCR (RT-PCR) analyses. Although the COD and NH4-N removal efficiencies were not or slightly reduced by the addition of ZnO-NP and Ag-NP, the functional bacterial community changed remarkably. The denitrification related species were inhibited by high dosage of ZnO-NP and Ag-NP, including Diaphorobacter species, Thauera species and those in the SphaerotilusLeptothrix group. However, the bacteria related to sludge bulking, heavy metal resistant and biosorption were increased, especially by ZnO-NPs treatment, including those closely related to Haliscomenobacter hydrossis, Zoogloea ramigera and Methyloversatilis universalis. In addition, Ag-NP and ZnO-NP treatments influenced the functional bacterial community differently. Increasing of bulking related bacteria may help to compensate the COD removal efficiency and to maintain functional redundancy, but could lead to operation failure of activated sludge system when expose to ZnO-NPs. Ó 2013 Elsevier Ltd. All rights reserved.

1. Introduction Nanotechnology provides more solutions to solar energy conversion, catalysis, medicine, and water treatment (Sharma et al., 2009), which leads to a great deal of nanoparticle (NP) discharging into sewage. Wastewater treatment plant (WWTP) is therefore one of the final defenses for preventing NPs from discharging into water environments. It is well known that silver nanoparticle

q Note: Sequences of 16S rRNA gene in this study have been submitted to GenBank database under accession numbers JN609296 to JN609381. ⇑ Corresponding author. Tel./fax: +86 10 62759047. E-mail addresses: [email protected] (X.-Q. Li), [email protected] (X.-L. Wu). 1 Co-corresponding author.

0045-6535/$ - see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.chemosphere.2013.10.082

(Ag-NP) can conduct bactericidal properties to many Grampositive and Gram-negative bacteria including multi-resistant strains (Panacek et al., 2006) by a variety of antimicrobial mechanisms (Sharma et al., 2009). In addition, Zinc oxide nanoparticles (ZnO-NPs) and titanium dioxide nanoparticles (TiO2-NPs) were also proved to have antibacterial abilities (Adams et al., 2006; Zhang et al., 2007). Concern can be therefore raised. Whether the NPs in wastewater treatment plant shall negatively impact the activated sludge microbial community, which eventually hampers the function of WWTP in removing pollutants in wastewater, such as COD, nitrogen, phosphorus. Recently, studies started to address this issue. Zheng et al. (2011) reported that NH3-N removal was not significantly influenced by ZnO-NP, but total nitrogen removal efficiency was decreased from 81.5% to 75.6% in the presence of 10 mg L1

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ZnO-NP. Choi et al. (2008) reported the respiration of autotrophic nitrifying bacteria (ammonia oxidation bacteria or nitrite oxidation bacteria) was inhibited by 86 ± 3% at 1 mg L1 Ag-NP in a continuously stirred tank reactor (CSTR). In addition, both the TiO2-NP and ZnO-NP nanoparticles caused microbial biomass reduction, bacterial community shifts and diversity decline in soil bacterial communities (Ge et al., 2011). Our previous studies suggested that most of the ZnO-NPs and Ag-NPs could be removed by activated sludge process. In the simulated sequencing batch reactor (SBR) processes, continuous input of ZnO-NPs and Ag-NPs into the wastewater did not significantly reduce chemical oxygen demand (COD) removal but reduced NH4-N removal by inhibiting the respiration of nitrifying microorganisms (Hou et al., 2012, 2013). However, it is still not clear whether different nanoparticles exert different impacts on functional bacteria in wastewater treatment activated sludge. Therefore, we investigated the impacts of Ag-NP and ZnO-NP with different doses on the functional bacterial community with the methods based on RNA analyses, including quantitative reverse transcription PCR (RT-PCR), terminal restricted fragment length polymorphism (T-RFLP) and 16S rRNA gene clone library based on cDNA. Results revealed that although the COD and nitrogen removal functions of the activated sludge community did not change remarkably, the functional community structure did changed significantly. 2. Material and methods 2.1. Experiment set-up and sampling Silver nanoparticles were prepared as described previously (Hou et al., 2012). Zinc oxide nanoparticles were commercial products purchased from Emperor Nanomaterials Co., Ltd., (Nanjing, China) with the properties described previously (Hou et al., 2013). Lab-scale sequenced batch reactors (SBR) (with the volume of 1 L) with the returned sludge from the Xiaojiahe plant as inoculum (with the final biomass concentration of 2.4 g L1) and their operating realm were described previously (Hou et al., 2012, 2013). Briefly, the SBR cycle involved 10 h of aeration using a mini-aerator (Model AK-8, Risheng Electric Products Inc., Guangdong, China), followed by 2 h of settling. The wastewater used were collected from the effluent from the primary clarifier at the Xiaojiahe plant. In each cycle, after discarding that supernatant treated wastewater, nanoparticles with different dosage were added into the 15 experimental reactors with the fresh wastewater (Table 1). All the treatments were repeated in triplicates with the reactors without NP addition as controls. In each cycle, 35 mL of completely mixed suspensions were sampled from all the reactors (at the beginning of aeration soon after nanoparticles addition). The samples were numbered with sampling date-reactor number. The samples were immediately centrifuged with 7000 rpm for 15 min at 4 °C. The supernatants of the samples were collected for measuring the concentrations of COD and NH4-N (Hou et al., 2013); the sludge pellets were collected and used to analyze the sludge concentrations, to extract the DNA and RNA which were subjected to bacterial community analyses by using clone library, T-RFLP and RT-PCR approaches. Table 1 Reactors and treatments. Reactors

Treatments

Reactors

Treatments

4#, 5#, 6#

Control (No NPs addition) Addition with 0.1 mg L1 Ag-NP Addition with 0.5 mg L1Ag-NP

13#, 14#, 15# 16#, 17#, 18#

Addition with 1 mg L1 ZnO-NP Addition with 5 mg L1 ZnO-NP

7#, 8#, 9# 10#, 11#, 12#

2.2. RNA and DNA extraction and application The total RNA was extracted from the centrifuged sludge pellets of each sample with the modified method described previously (Griffiths et al., 2000). Briefly, in a 2 mL RNase-free screw-caped tube, about 0.2 g of activated sludge pellets, 0.5 g of RNase-free 0.10–0.11 mm diameter glass beads (Sartorius AG, Goettingen, Germany), 0.5 mL of CTAB buffer, and 0.5 mL of phenol–chloroform–isoamyl alcohol mixture (25:24:1) were homogenized for 30 s twice at 2500 rpm in the Mikro-Dismenbrator S with 1 min on ice between shakings. After centrifugation, 400 lL of aqueous phase was transferred to a new RNase-free tube. The phenol was removed by mixing with equal volume of chloroform–isoamyl alcohol (24:1) followed by centrifugation. Total nucleic acids were precipitated from 300 lL of aqueous layer by 2 volumes of 30% PEG 6000. The pellets were washed in ice-chilled 70% ethanol and re-suspended in 50 lL of DEPC treated water. To obtain pure RNA, 15 lL aliquot was digested by 15U DNase I (TaKaRa, Dalian, China) for 1.5 h, prior to phenol–chloroform–isoamyl alcohol purification. The integrity of RNA was evaluated by electrophoresis, while the amount and purity were estimated spectrophotometrically by measuring the optical density at 260, 230 and 280 nm. Reverse transcription PCR was conducted for obtaining the cDNA with the specific primer 1492R (50 -GGTT ACCT TGTT ACGA CTT-30 ) and random forward primer, which was performed from 500 ng RNA using First Strand cDNA Synthesis kit (TOYOBO, Osaka, Japan) according to the manufacturer’s instructions. In addition, parallel reactions without reverse transcriptase were also made to confirm that no DNA contamination was present in the RNA samples. From the cDNA amplified, the bacterial 16S rRNA gene fragments were amplified using the bacterial universal primers, 8F (50 -AGAGT TTGAT CCTGG CTCAG-30 ) (for clone library construction) or 8F fluorescently labeled with 6-FAM (for T-RFLP analysis) and 1492R (50 -GGTTA CCTTG TTACG ACTT-30 ) in a 50 lL of PCR reaction mixture containing 5 lL 10 PCR buffer, 4 lL dNTP (2.5 mM each dNTP), 0.5 lL Taq™ DNA polymerase (5 units lL1) (Takara, Dalian, China), 1 lL each primer (10 pmol lL1) and 1 lL cDNA. The PCR was performed with initial denaturation at 95 °C for 5 min; followed by 14 cycles of 1 min at 94 °C, 45 s at 55 °C and 90 s at 72 °C; and a final extension at 72 °C for 10 min. The PCR amplicons were purified using PCR Purification Kit (BioTeKe, Beijing, China), and subjected to clone library and T-RFLP analyses. The extraction of the activated sludge DNA, amplification of the bacterial 16S rRNA genes (16S rDNA) for T-RFLP analysis were conducted with the protocols as described previously (Yu et al., 2010; Tang et al., 2012). 2.3. T-RFLP analysis About 5–8 lL fluorescently labeled PCR products were digested by restricted enzyme Rsa I (Fermentas, China), desalted, mixed with formamide and a DNA fragment length internal standard, denatured and subjected to electrophoresis in 3130 Genetic Analyzer (Applied Biosystems) with the protocol described previously (Yu et al., 2010; Tang et al., 2012). The restricted fragments’ sizes and peak areas of terminal restriction fragments (T-RFs) were automatically calculated by ABI supplied GeneMapper software (Version 4.0). T-RFs that differed by ±1 bp in different profiles were considered as identical. The relative abundance of each T-RF within a given T-RFLP pattern was calculated as the peak area of the respective T-RF divided by the total peak area of all detected T-RFs. Calculation of the pair-wise similarities of T-RFLP profiles was based on Pearson’s correlation coefficients (Andoh et al., 2007; Smalla et al., 2007). The T-RFLP profiles of different samples were compared statistically by principal component analysis (PCA)


and partial least squares-discriminant analysis (PLS-DA) in the SIMCA-P software environment (Umetrics) (Wikström et al., 2001; Hjort et al., 2007). The above analyses were also carried out for the 16S rDNA. 2.4. Cloning and phylogenic analysis For understanding the meaning of each T-RF in the T-RFLP pattern, clone library was constructed and analyzed. Different samples had different cDNA T-RFLP patterns. Since samples from Reactor 4# at day 0 (0–4) and day 15 (15–4) together had all the T-RF peaks appeared in all the other samples, samples 0–4 and 15–4 were chosen as representative for the clone library analyses. The PCR amplicons of 16S rRNA gene were ligated into pGEM-T easy vector (Promega, WI, USA), transformed into Escherichia coli DH5a competent cells. In total, 180 and 158 positive clones, from library 0–4 and 15–4 respectively, were picked up and screened by restricted fragment length polymorphism (RFLP) pattern with Rsa I as the digestion enzyme, resulting in the classification of 45 OTUs and 42 OTUs in the libraries 0–4 and 15–4 respectively. Then 110 representative clones were randomly selected from each OTU and sequenced. The 16S rRNA gene based phylogenetic trees were then constructed using the neighbor-joining algorithm, with the Jukes–Cantor correction factor in ARB program. Tree topology was also evaluated by the Maximum Parsimony algorithm in the ARB program (Ludwig et al., 2004). Sequences with similarity of over 97% were defined as the same OTU in the tree. Richness and diversity of the two clone libraries were analyzed by MOTHUR (Schloss et al., 2009). The applied Chao1 and ACE estimator for the species richness estimation and the Shannon and Simpson indices for the diversity estimation were calculated with 95% confidence intervals. The Boneh index was calculated when sampling size was set at 50. 2.5. Quantification of 16S rRNA gene transcripts At the 15th day, the activated sludge samples were subjected to the analysis of the transcription of the bacterial 16S rRNA gene. The transcripts of the bacterial 16S rRNA gene were quantified using a Bio-Rad CFX-96 real-time PCR system with the universal bacterial primer set composed of Bac331f (50 -TCCT ACGG GAGG CAGC AGT30 ) and Bac797r (50 -GGAC TACC AGGG TCTA ATCC TGTT-30 ). Each 20 lL of reaction mixture contained 1 lL of cDNA, 0.8 lL of 10 lM forward primer and reverse primer, 10 lL of SYBR Premix Ex Taq (2) buffer (TaKaRa, Dalian, China) and an appropriate volume of water. The PCR protocol was as follows: 1 cycle at 95 °C for 30 s, 30 cycles consisted of denaturation at 95 °C for 5 s, annealing and extension at 60 °C for 30 s. Following amplification, a melting curve analysis of amplified DNA was performed at temperatures between 65 and 95 °C, with the temperature increasing at a rate of 0.5 °C s1. Measurement of qPCR was replicated at least three times in all samples to check the reproducibility. Standard curves were constructed using serial dilutions (103–108 16S rRNA gene copies per lL) of the standard DNA solution. The R2 values were greater than 0.99 for all of the curves. Standard DNA solution was prepared from the plasmid extracts of clone 0–4–26. The concentration of plasmid DNA was determined spectrophotometrically by measuring absorbance at 260 nm (Nie et al., 2011). 3. Results 3.1. Functional bacteria in activated sludge In total, 180 clones and 158 clones were retrieved from the 0–4 to 15–4 cDNA libraries respectively, which belonged to 44 OTUs

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and 42 OTUs. The Coverage and Boneh Indexes as well as the rarefaction curves of both clone libraries all indicated that the clone sampling size was big enough for each library (Schloss et al., 2009) (Supplementary Table S1 and Fig. S1). Phylogenetic analyses on the cDNA sequences of the 16S rRNA genes (Supplementary Fig. S2) revealed that three common phyla, Proteobacteria, Bacteroidetes and Actinobacteria were retrieved from both libraries. Six phyla, Chloroflexi, Cyanobacteria, Candidate division OP11, Armotimonadetes and Candidate division BRC1 were specifically detected in the library 0–4, while Verrucomicrobia and Gemmatimonadetes relatives were only detected in library 15–4 (Table 2). In the most abundant phylum Proteobacteria (77.8% in library 0–4 and 85.4% in the library 15–4), the beta subclass was particularly predominant, accounting for 32.8% and 55.7% of the total clones in libraries 0–4 and 15–4 respectively. Among the Betaproteobacteria, 10 OTUs from library 0–4 and 13 OTUs from library 15–4 were assigned into three orders, Rhodocyclales, Neisseriales and Burkholderiales with their isolated relatives having different potential water treatment functions, including phosphorus removal (Peterson et al., 2008), activated sludge flocculation (Crabtree and Mccoy, 1967; Farrah and Unz, 1976), heavy metal biosorption and aromatic compounds resistant (Sag and Kutsal, 2000; De Marco et al., 2004), (per)chlorate-reduction (Achenbach et al., 2001), phenylacetate degradation (Mechichi et al., 2002), denitrification (Thomsen et al., 2004, 2007), poly-b-hydroxybutyrate (PHB) and brown pigments production (Mulder and van Veen, 1963; Kumar et al., 1974; Van Veen et al., 1978; Boivin et al., 1985; Song et al., 2009), vibrioid cells and catalase activity as well as PHB-degradation (Tabrez Khan and Hiraishi, 2002; Ding and Yokota, 2004) (Supplementary Table S2). The Gammaproteobacteria bacteria belonged to Moraxellaceae, Pseudomonadaceae, Chromatiaceae, Sinobacteraceae, and Enterobacteriaceae, with their close isolated relatives having potential water treatment functions, including steroidal hormones utilizing denitrification (Fahrbach et al., 2008), sludge congregation (Malik et al., 2003), nitrogen fixation (Yu et al., 2011) and the polyhydroxyalkanoates (PHAs) production (Guo et al., 2011). The 5 Alphaproteobacteria OTUs (10 clones) were mainly closely related to those with the functions, including aerobic aromatic compounds degradation (Balkwill et al., 1997), nitrate reduction (Sohn et al., 2004) and so on. The 14 Deltaproteobacteria OTUs were mainly closely related to uncultured clones retrieved from water or sediment habitats (Supplementary Table S2). Bacteroidetes, as one of the most abundant aquatic heterotrophic bacteria groups (O’Sullivan et al., 2004), was the second dominant phylum, accounting for 13.3% and 5.7% in library 0–4 and 15–4 respectively. In this cluster, most of the OTUs were closely related to uncultured bacterial clones or with very low similarities with known isolates (Supplementary Table S2). Besides the Proteobacteria and Bacteroidetes, bacteria affiliated to other phyla, including Actinobacteria, in both reactors composed the minor populations of the bacterial community, although some of them have proved water treatment capabilities (Supplementary Table S2). Among the functional bacteria, OTUs with T-RFs 106 bp, 108 bp, 152 bp, 310 bp, 423 bp, 462 bp, 465 bp, 468 bp, 476 bp, and 644 bp composed the dominant functional community, accounting for more than 50% of the total abundance. OTUs with T-RF 106 bp belonged to Bacteroidetes or Rhodomicrobium (Alphaproteobacteria) which occupied a high proportion in the enhanced biological phosphorus removal (EBPR) plant (Kong et al., 2007) (Supplementary Table S2). T-RF 644 bp (OTU 15-4-174) was typical T-RF of Pseudomonas. OTUs with T-RF 476 bp (OTU 0-4-190) and T-RF 310 bp (OTU 0-4-184) were affiliated to the Deltaproteobacteria clone (HM057795) retrieved from Yellow Sea water, and an unclassified Bacteroidetes clone respectively. OTUs with T-RF 462 bp (OTUs 15-4-26, 15-4-112, 0-4-7 and 15-4-151) was closely

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Table 2 Phylogenetic distribution of clones from the two 16S rcDNA clone libraries. Classification

Proteobacteria Betaproteobacteria Gammaproteobacteria Alphaproteobacteria Deltaproteobacteria Bacteroidetes Actinobacteria Verrucomicrobia Gemmatimonadetes Chloroflexi Cyanobacteria Candidate division OP11 Armotimonadetes Candidate division BRC1 Unclassified Total

Library 0–4

Library 15–4

No. of clones

No. of OUT’s

Percentage of clones (%)

No. of clones

No. of OUT’s

Percentage of clones (%)

140 59 38 5 38 24 10 0 0 1 2 1 1 1 0 180

26 11 3 3 9 9 4 0 0 1 1 1 1 1 0 44

77.8 32.8 21.1 2.8 21.1 13.3 5.6 0.0 0.0 0.6 1.1 0.6 0.6 0.6 0.0 100.0

135 88 26 5 16 9 2 7 1 0 0 0 0 0 4 158

29 13 9 2 5 8 2 1 1 0 0 0 0 0 1 42

85.4 55.7 16.5 3.2 10.1 5.7 1.3 4.4 0.6 0.0 0.0 0.0 0.0 0.0 2.5 100.0

related to unclassified Betaproteobacteria clones, belonging to the Sphaerotilus-Leptothrix group, whose members mostly showed PHB granules formation, oxidase activity, nitrate reduction capability (Song et al., 2009). OTUs with T-RF 465 bp (OTUs 0-4-6 and 15-4-72) were relatives of Candidatus Accumulibacter phophatis known as PAOs (Peterson et al., 2008) probably capable of denitrifying in the SBR system (Zeng et al., 2003), or Inhella species. T-RF 152 bp was typical of Thauera phenylacetica, a denitrifier capable of aromatic compounds degradation (Mechichi et al., 2002). OUT with T-RF 423 bp (OTU 15-4-12), representing Curvibacter/Diaphorobacter, among which Diaphorobacter nitroreducens was a nitrate reducer isolated from activated sludge samples (Tabrez Khan and Hiraishi, 2002). OTUs with T-RF 108 bp (OTUs 0-4-80, 0-4-22, 0-4-20 and 15-4-76) clustered with uncultured Deltaproteobacteria clone (HQ828018, FJ905734) and Haliscomenobacter hydrossis, a filamentous bulking related species (van Veen et al., 1973). OTUs with T-RF 468 bp (OTUs 0-4-10 and 0-4-136) was affiliated with Zoogloea ramigera and Methyloversatilis universalis, with the functions of heavy metal pollutants resistance (Sag and Kutsal, 2000; De Marco et al., 2004) as well as the biosorption ability (Supplementary Table S2).

3.2. Change of bacterial community The DNA and RNA based T-RFLP analyses showed different changes of bacterial community with time and treatments (Fig. 1). At the DNA level, the bacterial community clustered with time. For example, bacterial community retrieved from the 1st day samples clustered together, distant from the initial inoculating sludge as well as the 15th day samples. In addition, at the 1st day, the clustering of samples treated with either ZnO-NP or Ag-NP suggested that not much different influence happened between the two treatments. However, at the 15th day, sub-clustering of samples according to ZnO-NP or Ag-NP treatment could suggest the discriminated influences of ZnO-NP or Ag-NP on the bacterial community at the DNA level (Fig. 1a). At the RNA level, although the samples clustered with time at a larger scale, different ZnO-NP or Ag-NP treatments led to different distribution of samples in the PLS-DA diagram, suggesting the different potential impacts of ZnO-NP or Ag-NP treatments on the functional community (Fig. 1b). This differentiation was easier observed in the 2-dimension PLS-DA diagram. The T-RFLP profiles from the controls without treatment (R-15-4, R-15-5 and R-15-6) clustered together, distant from the Ag-NPs treated samples (R-15-7, R-15-8, R-15-9, R-15-11 and R-15-12) and the ZnO-NPs

treated samples (R-15-13, R-15-14, R-15-15, R-15-16, R-15-17 and R-15-18). However, the lower the dosage of both ZnO-NP and Ag-NP were added, the closer of the samples to the control group (Fig. 1c). 3.3. Change of the dominant functional bacteria The shift of dominant functional bacteria, those OTUs with T-RFs 106 bp, 108 bp, 152 bp, 310 bp, 423 bp, 462 bp, 465 bp, 468 bp, 476 bp, and 644 bp, was further analyzed by comparison with RNA T-RFs in the T-RFLP patterns (Fig. 2). The T-RFs 106 bp, 644 bp, 476 bp, 462 bp were remarkably reduced in peak area ratio by ZnO-NP and Ag-NP treatments, and the higher doses of nanoparticles resulted in higher decrease of the ratio. The relative ratios of T-RFs 152 bp and 423 bp were also reduced by Ag-NP treatments, while the ZnO-NP treatment led to the decrease of T-RF 465 bp in relative ratio. Although the relative ratios of 310 bp, 465 bp and 468 bp in the Ag-NP treated reactors were lower than those of the control at the dose level of 0.5 mg L1, the lower dose (0.1 mg L1) resulted in increase of relative ratios of these T-RFs. Remarkably different from the Ag-NP treatments, treatments by ZnO-NP increase the relative ratios of T-RFs 152 bp, 108 bp, 468 bp at both of the doses. It also led to increase of the relative ratios of T-RFs 310 bp and 423 bp at the dose level of 1 mg L1, but decreased the ratio at 5 mg L1 (Fig. 2). 4. Discussions Although recent studies have commenced investigations into the impacts of nanoparticles on the activated sludge microbial community, few researches were focused on the functional bacteria. Our study was therefore conducted to understand the influences of different nanoparticles with different dosages on the functional bacterial species in an activated sludge system. To our knowledge, it is the first report in related work. It is clear that functional bacteria in our present activated sludge mainly belonged to Proteobacteria with the Beta sub-group being the dominant (Table 2). Following the Proteobacteria, Bacteroidetes was the second dominant phylum. Among them, many bacterial clones could not be affiliated to isolated bacterial strains with identified functions although the functions of higher taxa could be concluded from some phylogenetically distant relatives. At these levels, most of the functions could be related to nitrate reduction, aromatic organics degradation, phosphorus removal, metal resistant, biosorption and sludge bulking (Supplementary Table S2).


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Fig. 1. PLS-DA diagrams of DNA and RNA T-RFs. (a) PLS-DA 3d score plot of DNA T-RFs; (b) PLS-DA 3d score plot of cDNA T-RFs; and (c) PLS-DA plot of cDNA T-RFs retrieved from the activated sludge bacterial community sampled at the 15th day. In (a and b), each dot represents a sample. All stars represent original samples from WWTP; red open triangle represents control group in the 1st day; blue square represents Ag-NP treated group in the 1st day; green circle represents ZnO2-NP treated group in the 1st day; red triangle represents control group in the 15th day; blue box represents Ag-NP treated group in the 15th day; green dot represents ZnO-NP treated group in the 15th day. In (c), the black square dots including R-15-4, R-15-5 and R-15-6, were samples without nanoparticles treatment. The five red dots, including R-15-7, R-15-8, R-15-9, R-15-11 and R-15-12, clustered together, which represented that samples treated by Ag-NPs. The six blue diamond shaped dots, labeled with R-15-13, R-15-14, R-15-15, R-15-16, R-15-17 and R-15-18, were samples treated by ZnO-NPs. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

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Fig. 2. Change in the relative abundance of the dominant T-RFs with different treatments at 15th day. 106 bp, unclassified Bacteroidetes or Alphaproteobacteria; 108 bp, uncultured Deltaproteobacteria or Bacteroidetes; 152 bp, Thauera species; 310 bp, uncultured Bacteroidetes; 423 bp, Curvibacter or Diaphorobacter species; 462 bp, Betaproteobacteria clone; 465 bp, Candidatus Accumulibacter phosphatis/Inhella species; 476 bp, unclassified Deltaproteobacteria; 468 bp, Zoogloea or Methyloversatilis species; 644 bp, Pseudomonas species. All the data represent mean ± SD [n = 3/group].

The operation of the SBR reactor resulted in the shift of the bacterial community as indicated by the different positions of the samples in the PLS-DA diagram (Fig. 1) as well as the clone libraries (Table 2). It is reasonable that shift of environmental conditions select and/or enrich different bacterial population as well as bacterial functions. After the activated sludge sampled from the wastewater treatment plant, it was kept at 4 °C till inoculating into reactors. The restart of incubation offered different surroundings and conditions for microorganisms. For example, the aeration strength and mixing were different from the real WWTP. These could be the reason to example why bacterial community after 1-d operation differed remarkably from the inoculating sludge. However, the treatments by nanoparticles additionally influenced the functional bacterial community as indicated by the different distribution and clustering of the samples (Fig. 1). For example, the bacteria remarkably repressed by both ZnO-NP and Ag-NP treatments could be affiliated to different functional groups (Fig. 2), including the Bacteroidetes or Alphaproteobacteria (Rhodomicrobium) species (T-RF 106 bp) (Fig. 2a), bacteria in the Sphaerotilus-Leptothrix group (T-RF 462 bp) with potential nitrate reduction capability (Song et al., 2009) (Fig. 2f), Pseudomonas (T-RFs 644 bp) (Fig. 2j), and Deltaproteobacteria species (T-RF 476 bp) (Fig. 2i). The inhibition of these functional bacteria was Ag-NP and ZnO-NP dose-dependent. Compared with ZnO-NP, Ag-NP remarkably inhibited the bacteria belonging to Thauera (T-RF 152 bp) (Fig. 2b), and Curvibacter/ Diaphorobacter (T-RF 423 bp) species (Fig. 2e), while ZnO-NP led

to more seriously inhibition of Candidatus Accumulibacter phophatis or Inhella species (T-RF 465 bp) (Fig. 2g). And these inhibitions were also Ag-NP and ZnO-NP dose dependent. On the other hand, low dose of Ag-NP (0.1 mg L1) somehow increase the functional population of bacteria belonging to Bacteroidetes (T-RF 310 bp) (Fig. 2d), Candidatus Accumulibacter phophatis or Inhella genera (T-RF 465 bp) (Fig. 2g), and Zoogloea ramigera and Methyloversatilis universalis relatives (T-RF 468 bp) (Fig. 2h), however, high dose (0.5 mg L1) of Ag-NP inhibited them. Remarkably different from the Ag-NP treatments, treatments by ZnO-NP enriched the functional bacterial populations that were related to Thauera (T-RF 152 bp) (Fig. 2b), Deltaproteobacteria, Haliscomenobacter hydrossis (Bacteroidetes) (T-RF 108 bp) (Fig. 2c), Zoogloea ramigera and Methyloversatilis universalis (T-RF 468 bp) (Fig. 2h). In addition, ZnO-NP also increased Bacteroidetes (T-RF 310 bp) (Fig. 2d) and Curvibacter/Diaphorobacter (T-RF 423 bp) species (Fig. 2e) at the dose level of 1 mg L1, but repressed them at 5 mg L1. Nevertheless, not all bacteria were affected by nanoparticles exposure. It is obvious that Ag-NP and ZnO-NP exerted different influences on different bacterial groups. Generally Ag-NP reduced the relative ratios of the dominant functional bacteria, while the ZnO-NP could increase the relative ratios of bacteria with the functions of sludge bulking, biosorption and metal resistance. In addition, high dose of ZnO-NP (5 mg L1) could even increase the copy numbers of the 16S RNA transcripts (Fig. 3). The reasons why Ag-NP and ZnO-NP had different impacts on different bacteria might be because


their different structures and different mechanisms on microbial metabolism. However, further investigation should be made to clarify the issue. On the other hand, some minor populations, including OTU 0-4-182 (T-RF 469 bp) affiliated with potential denitrifying Aquaspirillum serpens (Thomsen et al., 2007), OTU 15-4-6 (T-RF 415 bp) closely related to the halophilic nitrate reducing Novosphingobium pentaromativorans US 6-1 (Sohn et al., 2004), and OTU 0-4-2 (T-RF 807 bp) closely related to denitrifying Steroidobacter denitrificans FS (Fahrbach et al., 2008), were not remarkably decreased in the nanomaterial treatment groups. Along with the change in functional bacterial community, the COD removal capability of SBR was not influenced by either Ag-NPs or ZnO-NPs treatments, while the NH3-N removal efficiency was only slightly repressed by 5 mg L1 ZnO-NP exposure (Hou et al., 2012, 2013). In an activated sludge system, COD removal is the comprehensive functions of all heterotrophic bacteria through carbon metabolism. Therefore, the stable COD removal might be because of the special structure of the activated sludge and high diversity of the microbial community. The stableness of the bacterial community in both copy numbers and activity might be attributed to the structure of the activated sludge. The exopolymers like carbohydrates and proteins surrounding the activated sludge zoogloea could absorb and accumulate the nanoparticles, preventing them from penetrating into the zoogloea, which could be beneficial to protect the bacteria from direct contact with nanoparticles (Neal, 2008). The increase of the bacteria with the functions of biosorption (T-RFs 468 bp) and metal resistance (T-RFs 108 bp) could enrich the nanoparticles to these bacteria, which additionally exert the detoxification. The alleviation of severe damages by the ROS (reactive oxygen species) (Bloomfield et al., 1998) produced from nanoparticles’ interaction with oxygen could therefore maintain the relative stable population as indicated by the relative stable 16S rRNA gene copy number retrieved from the cDNA (Fig. 3). Secondly, the functional redundancy could ensure the maintenance of systems functions by different functional groups, which could react differently toward environmental perturbation. The decline of some functional bacteria such as OTUs with T-RFs of 106 bp, 644 bp, 476 bp 462 bp, could be complemented by other bacteria with similar functions including the bacteria with T-RFs of 108 bp and 468 bp. It is well-known that the filamentous bacteria could tolerate improper condition for the zoogloea bacteria, which could be enriched and complement COD degradation when the nanoparticles exert bad

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influence on the activated sludge. This is different from the purecultured system without functional redundancy (Choi et al., 2008). Besides the COD removal, the removal of ammonia nitrogen (NH3-N) was slightly decreased in the presence of 5 mg L1 ZnONPs (Hou et al., 2012, 2013). Although ZnO-NP was proved not to inhibit ammonia oxidation (Zheng et al., 2011), Ag-NP at 1 mg L1 level could lead to inhibit the respiration of autotrophic nitrifying bacteria in a continuously stirred tank reactor (CSTR) (Choi et al., 2008). However, few autotrophic ammonia oxidizing bacteria were detected in the present although NH3-N was sufficiently removed. It is generally considered that ammonia oxidation is an obligatory aerobic, chemoautotrophic process restricted to a few groups within the Proteobacteria (Kowalchuk and Stephen, 2001). However, heterotrophic nitrification was recently reported by various investigations (Inamori et al., 1997). Further research is needed to address whether it was because of the heterotrophic population or because of the restriction of the analytic approaches. 5. Conclusions In summary, although the COD and NH4-N removal efficiencies were not or slightly reduced by the addition of ZnO-NP and Ag-NP, the functional bacterial community changed remarkably. The denitrification related species were inhibited by high dosage of ZnO-NP and Ag-NP, including Diaphorobacter species, Thauera species and those in the Sphaerotilus-Leptothrix group. However, the bacteria related to sludge bulking, heavy metal resistant and biosorption were increased, especially by ZnO-NPs treatment, including those closely related to Haliscomenobacter hydrossis, Zoogloea ramigera and Methyloversatilis universalis. The nitrogen removal was slightly inhibited by ZnO-NPs at high concentrations, but not in other treatment groups, indicating Ag-NP and ZnO-NP treatments influenced the functional bacterial community differently. Increasing of bulking related bacteria may help to compensate the COD removal efficiency and to maintain functional redundancy, but could lead to operation failure of activated sludge system when expose to ZnO-NPs. Acknowledgements The study was supported by the International cooperation project of Ministry of science and technology (S2011ZR0434) to X.L.W. Appendix A. Supplementary material Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.chemosphere. 2013.10.082. References

Fig. 3. Real-time RT-PCR analysis of the bacterial 16SrRNA gene transcription levels at different treatments at the 15th day. All the data represent mean ± SD [n = 3/ group].

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